SINGLE-NEURON THEORY OF CONSCIOUSNESS
Journal of Theoretical Biology (2005, In Press)
Steven Sevush
Departments
of Psychiatry and Neurology
University
of Miami School of Medicine
1400 NW 10
Ave, Suite 702
Miami,
Florida 33136, USA
ssevush@med.miami.edu
Tel:
305-243-4082
This work
was presented in abstract form at
"Toward
a Science of Consciousness" held in Tucson, April 2002.
ABSTRACT:
By most accounts, the mind arises from
the integrated activity of large populations of neurons distributed across
multiple brain regions. A contrasting
model is presented in the present paper that places the mind/brain interface
not at the whole brain level but at the level of single neurons. Specifically, it is proposed that each
neuron in the nervous system is independently conscious, with conscious content
corresponding to the spatial pattern of a portion of that neuron's dendritic
electrical activity. For most neurons,
such as those in the hypothalamus or posterior sensory cortices, the conscious
activity would be assumed to be simple and unable to directly affect the
organism's macroscopic conscious behavior.
For a subpopulation of layer 5 pyramidal neurons in the lateral
prefrontal cortices, however, an arrangement is proposed to be present such
that, at any given moment: i) the
spatial pattern of electrical activity in a portion of the dendritic tree of
each neuron in the subpopulation individually manifests a complexity and
diversity sufficient to account for the complexity and diversity of conscious
experience; ii) the dendritic trees of the neurons in the subpopulation all
contain similar spatial electrical patterns; iii) the spatial electrical
pattern in the dendritic tree of each neuron interacts nonlinearly with the
remaining ambient dendritic electrical activity to determine the neuron's
overall axonal response; iv) the dendritic spatial pattern is reexpressed at
the population level by the spatial pattern exhibited by a synchronously firing
subgroup of the conscious neurons, thereby providing a mechanism by which
conscious activity at the neuronal level can influence overall behavior. The resulting scheme is one in which
conscious behavior appears to be the product of a single macroscopic mind, but
is actually the integrated output of a chorus of minds, each associated with a
different neuron.
Key Words: binding problem; consciousness; hard problem; neural correlate of consciousness; single-neuron theory.
1.
INTRODUCTION
The purpose of this paper is to suggest a
shift in emphasis from the large to the small in the search for a brain
correlate for the mind. Currently, the
general view is that the mind arises from the integrated activity of large
populations of neurons distributed across multiple cortical and subcortical
brain regions (Sperry 1969; Crick and Koch 1990a; Llinas et al. 1998; Damasio
1999, Edelman and Tononi 2000, John 2001, Singer 2001). Dynamic mechanisms, such as those involving
reentrant flow of information (Edelman and Tononi 200), synchronous electrical
oscillatory activity (Singer 1998; Engel et al. 1999; Sauve 1999; Sewards and
Sewards 2001), and top-down attentional effects (Reynolds and Desimone 1999;
Wolfe and Cave 1999), have then been invoked to provide for the
"binding" of the dispersed neuronal activity into a unified stream of
consciousness. The perspective,
according to this view, is that the activity within any single neuron
correlates with merely a fragment of the total conscious experience; it is only
through the integration of these fragments that a single whole-brain
consciousness is assumed to emerge.
A contrasting model is outlined in the
present paper that places the mind/brain interface not at the whole brain level
but at the level of the single neuron.
According to the model, a single brain at any given moment harbors many
separate conscious minds, each being associated with the activity of a
different neuron. For most neurons,
only a simple conscious experience is assumed to be present. For a subpopulation of neurons populating
the lateral prefrontal cortices, however, a complex consciousness is assumed to
be separately present in each neuron, with each of the neurons having a similar
conscious experience, and with that conscious experience being that which in
most models is attributed to the joint action of vast numbers of neurons
distributed throughout the brain. The
theory posits a mechanism that explains how the separately conscious neurons
might express their output in terms of whole brain behavior. The resulting scheme is one in which
conscious behavior, while appearing to be the product of a single macroscopic
mind, is actually the result of the assembled output of a chorus of minds, each
associated with a different individual neuron.
The main features of the theory can be
summarized as follows:
a) Each neuron in the nervous system is
assumed to be independently conscious, with a component of the electrical
activity in the neuron's dendritic tree serving as the neural correlate of
consciousness (NCC) for that neuron.
b) For most neurons, such as those in the
hypothalamus or those in the posterior sensory cortices, or for cortical
interneurons, the conscious activity of the neuron is assumed to be simple and
unable to directly affect the organism's macroscopic behavior. Such neurons would not, therefore,
contribute to what is usually taken as a person’s conscious behavior.
c) For layer 5 pyramidal neurons in the
lateral prefrontal cortices, however, the electrical activity within a portion of
the apical dendritic tree is presumed to be by itself complex and diverse
enough to account for the complexity and diversity of conscious experiences
usually ascribed to the activity of the brain as a whole. Additionally, as a result of the diversity of
afferent input that uniquely characterizes the lateral prefrontal cortices, the
layer 5 pyramidal neurons in these areas can plausibly be regarded as
recipients of input pertaining to all of the sensations, thoughts, feelings,
and memories that make up conscious experience.
d) A mechanism can be delineated by which
a subgroup of synchronously firing layer 5 lateral PFC neurons with similar
conscious experiences can express that experience by means of the spatial
pattern they manifest at the neuronal population level. The axonal output of these neurons then
transmits the conscious content to other brain regions, including those that
control behavior.
e) As a result, while the content of
conscious experience is seen to correlate with activity in individual neurons,
the production of conscious behavior results from population activity at the
network level.
The most immediate implication of this
arrangement is that it offers a novel approach to solving the "binding
problem," the problem of explaining how spatially dispersed neuronal
activity can correlate with an apparently seamless single experience. The currently popular views are that
either: a) perceptual unity is achieved
through temporal synchrony of the component elements, perhaps via 40 Hz gamma
frequency oscillations (Singer 1998; Engel et al. 1999; Sauve 1999; Sewards and
Sewards 2001); or b) perceptual unity is an illusion, with only coordinated
behavioral output being in need of an explanation (Dennett 1991; Shadlen and
Movshon 1999). These approaches have
their difficulties, however. The
evidence for temporal synchrony as a basis for binding has been criticized on
both technical and conceptual grounds (Hardcastle 1994, 1997; Gold 1999;
Revonsuo 1999; Bieberich 2002; Edwards 2005), while the argument that
perceptual unity is an illusion has been challenged both empirically and
philosophically (Chalmers 1996; Robertson 2003; Bayne and Chalmers 2003). The theory presented in this paper proposes
an alternative explanation for perceptual binding, with perceptual unity being
achieved through spatial convergence of incoming signals upon single neurons.
In what follows I present an outline of
the single-neuron model and argue for its feasibility given what we know of
brain architecture and function at both the macroscopic and microscopic
levels. I will then compare the model
with other popular theories of consciousness and describe the empirical
predictions made by the model that might adjudicate between the competing
perspectives. I will conclude by
offering a brief speculation as to how the model might be extended to an
ultramicroscopic domain, and how this extension might be used to formulate a
framework for addressing the philosophically difficult aspects of the
mind/brain problem.
The model, it should be stressed, is at
this point presented as a hypothesis, not a proven theory. The contention, given the data presently
available, is not that the proposed single-neuron mechanism is necessarily the
way the brain processes information, only that it is a possible way for it to
accomplish the task and that it should not be dismissed out of hand. There is no question that the theory takes a
stance that is at odds with prevailing intuitions. Yet, the stakes are high and, in view of the difficulties
inherent in the mind/brain problem, unusual approaches to its solution may be
warranted.
2.
TERMINOLOGY AND THE POSSIBILITY OF MULTIPLE CONSCIOUSNESSES
With regard to terminology, when the
terms "mind" and "consciousness" appear in this paper, they
are being used in the specific sense that Chalmers uses the term
"experience" in his discussion of the easy and hard problems of
consciousness (Chalmers 1996). As
described by Chalmers, the "easy" problems of consciousness are those
that appear tractable by the usual methods of science and include the ways in
which the brain focuses attention, integrates information, controls behavior,
and so on. In contrast, the
"hard" problem of consciousness is the problem of accounting for the
content of subjective experience, that elusive datum that appears to accompany
certain high level brain processes. Why
does the electrical processing in the brain that ensues when one looks at the
sky give rise to the experience of "blue" and not to the experience
of some other color, or to no color experience at all? In what follows, it will be to consciousness
in this sense that a neural correlate will be sought.
An additional matter is the potential ambiguity
associated with the proposal that multiple minds are present in a single brain,
a feature that plays centrally in the proposed theory at both the macroscopic
and microscopic levels. The problem is
that since multiple consciousnesses are assumed to be present in a single
brain, and since these include consciousnesses of varying types, how will we
know what is to be denoted by the term "consciousness?" That is, to which of the different kinds of consciousness will the term refer?
In order to minimize the potential for
ambiguity of this kind, the theory will initially be developed for the
restricted case of verbally reportable consciousness (designated in this paper
as "VR-consciousness"), by which I mean consciousness that has direct
access to verbal report. It must be
stressed that this restriction is a temporary one, and will be introduced only
as a convenience to minimize ambiguity in the initial presentation of the
theory. It is not implied that
VR-consciousness is the only type of consciousness present in the brain, nor
that VR-consciousness is even the only high level consciousness present in the
brain. Nor is it implied that verbal
output is the only form of behavior that can be influenced by VR-consciousness. VR-consciousness has been chosen for this
purpose because it is around this form of consciousness that the debate over
the hard problem of consciousness has been primarily focused. Once the theory has been examined for the
special case of VR-consciousness, the argument will then be expanded to account
for the presence of other types of consciousness.
Armed with these preliminaries, we can
now turn to the presentation of the model.
A sketch of the single-neuron theory for VR-consciousness will be
developed in two steps, one macroscopic, the other microscopic. At both levels, a divergent/convergent
feedforward model of information flow (Abeles 1991) will be adopted. In the macroscopic step, the suggestion will
be made that within a divergent/convergent feedforward framework, much of the
distributed brain processing usually taken as the correlate of VR-consciousness
can be recast as either previous or subsequent to VR-conscious experience. Plausibility arguments will be offered in support
of the contention that only when the information flow reaches the left[1]
lateral prefrontal cortex (PFC) does it achieve VR-conscious status. In the microscopic step, the argument will
be made that it is not the left lateral PFC as a whole that mediates
VR-consciousness, but rather that VR-consciousness is mediated separately and
redundantly by individual pyramidal neurons inhabiting the region. A divergent/convergent feedforward model of
information flow involving a subset of individual neuron within the population
will be offered. Finally, the theory
will be extended to account for consciousness of a nonverbally reportable
variety.
3. THE MACROSCOPIC STEP: PLAUSIBILITY OF A FOCAL MODEL
The first objective in developing the
single-neuron theory is to determine, on a macroscopic level, just which brain
region or regions participate directly in VR-conscious experience. The commonly held view is that it is the
activity of neuronal populations dispersed across multiple cortical and
subcortical brain regions that mediates VR-consciousness (Llinas et al. 1998;
Damasio 1999, Edelman and Tononi 2000, John 2001). Importance is usually placed not only on cortical processing but
also on thalamocortical loops (Llinas et al. 1998; Edelman and Tononi 2000) and
involvement of the upper brainstem and other subcortical structures (Damasio
1999). With regard to cortical
information flow, while there is general acknowledgment of a hierarchical
arrangement for posterior cortical subregions (Hubel and Wiesel 1962, 1965;
Rockland and Pandya 1979; Maunsell and Essen 1983; Felleman and Van Essen 1991;
Barbas and Rempel-Clower 1997; Lamme and Roelfsema 2000; Inui et al. 2004), the
flow of information between posterior and frontal cortex is usually regarded as
inherently bidirectional and lacking any feedforward directional bias (Fuster 1998).
On the face of it, this multifocal view
of conscious information processing seems unavoidable. It is indeed difficult to imagine how a
single brain region could serve as a focus of convergent inputs sufficiently
rich to account for the manifest intricacy and multifarious nature of
VR-conscious experience. Additionally,
the multifocal view is encouraged by data obtained from brain ablation,
neuroimaging, and single-cell electrical recording studies, each of which has
demonstrated the importance of widely dispersed brain regions in even the
simplest VR-conscious tasks. Thus, the
ablation paradigm, which regards a brain region as important for a given task
only if damage to that brain region regularly results in the loss of ability to
perform the task, has implicated brainstem, thalamic, limbic, and widespread
cortical regions in VR-conscious processing (Crick and Koch 1990a; Damasio
1998; Parvizi and Damasio 2001). More
recently, neuroimaging studies employing functional MRI and related imaging
techniques or with those utilizing single-cell recordings from pyramidal
neurons in various brain areas have provided direct evidence of a role for
widespread cortical and subcortical regions in VR-consciously mediated behavior
(Crick and Koch 1990a; Dehaene et al. 1998; Llinas et al. 1998; Raichle 2000).
Despite these arguments, it remains
possible that while a distributed model is consistent with the available data,
so might be a convergent model. It may
be possible that just a subset or even only one of the areas delineated in the
above studies actually subserves VR-conscious experience and that the other
areas function only to provide information to this convergent region. For example, during a VR-conscious visual task,
ablation, neuroimaging, and single-cell recording data have together implicated
activity spread across primary and secondary occipital cortices, tertiary
temporal and parietal association cortices, PFC, and multiple diencephalic and
brainstem structures in the context of VR-conscious experience. Since, however, these disparate regions are
highly interconnected, the possibility that only one of the identified regions
actually subserves VR-conscious experience and that the other regions serve
only to provide input to this focal region cannot be dismissed without further consideration.
For a focal model to gain serious
consideration, a brain region would need to be identified that could serve as a
locus of convergence for the full set of stimuli that feed VR-conscious
experience. Such a region should
manifest certain empirically demonstrable features. First, the area should be the recipient of afferent connections
from brain localities corresponding to each of the sensory, emotional,
mnemonic, and other components that make up VR-conscious experience. Second, it should be the case that the area
is adequately connected with brain regions capable of mediating VR-conscious
behavioral output. Third, the area
should show activation with neuroimaging or single-cell recording techniques
during engagement in VR-consciously mediated tasks. And fourth, ablation of the area should result in loss of
VR-conscious experience. In the
following, the argument will be made that the left lateral PFC (corresponding
to portions of Brodmann areas 9, 10, 11, 46, 47) appears to satisfy each of the
enumerated requirements.
Afferent Connections: The first question is whether the left
lateral PFC is appropriately positioned to be the recipient of afferent
connections pertaining to each of the sensory, emotional, and mnemonic
components that comprise VR-conscious experience. This possibility is often dismissed summarily, but invariably without an accompanying in-depth analysis (eg, see Dehaene
1998). Yet a review of the
neuroanatomical literature suggests that the idea of a convergence zone should
not be so casually disregarded. It has
been suggested, for example,
that the PFC as a whole functions as a convergence zone, receiving input from
most other brain regions (Miller and Cohen 2001; Elston 2003). Since PFC subregions are strongly
interconnected (Barbas and Pandya 1991), any one PFC subregion could be capable
of serving as a convergence target for all the other PFC subregions. In the single-neuron theory, it is the left
lateral PFC that is assumed to serve as the final convergence area for the
sensory, emotional, and mnemonic components of VR-consciousness, with evidence in support of this
contention available for each of these components.
With regard to sensory input, the lateral
PFC has long been established to receive input from the occipital, temporal,
and parietal association cortices that process the incoming visual, acoustic,
and tactile signals that provide the organism with information about its extrapersonal
and proprioceptive space (Kuypers et al. 1965; Pandya and Kuypers 1969;
Goldman-Rakic and Schwartz 1982;
Petrides and Pandya 1984, 1999; Seltzer and Pandya 1989; Barbas and
Pandya 1989; Pandya and Yeterian 1990), including simultaneous convergent input
from multiple modalities (Jones and Powell 1970; Chavis and Pandya 1976; Bruce
et al. 1981). Additionally, the lateral
PFC receives inputs from the caudal orbitofrontal cortical regions that
function as association areas for taste and smell (Baylis et al. 1995, Johnson
et al. 2000), with inputs for the latter bypassing the thalamus and projecting
solely to the frontal lobes.
With regard to emotion, ablation and
activation studies have each supported a role for both anterior cingulate and ventromedial
orbitofrontal cortices in assessing the emotional significance of stimuli
(Baleydier and Mauguiere 1980, Bush et al. 2000, Phan et al. 2002). Anatomically, these regions are the
recipients of input from the amygdala, the hypothalamus, and the hippocampus
(Porrino et al. 1981; Amaral and Price 1984; Goldman-Rakic et al. 1984; Barbas
and DE Olmos 1990) which carry the processed
visceral stimuli from which emotions are proposed to be comprised
(Damasio 1999). Both regions project
strongly to lateral PFC (Eslinger and Damasio 1985) where, it is suggested
(Damasio 1999; Gray et al. 2002), emotion and cognition become integrated, with
feelings providing “value,” which is needed for decision-making.
With regard to memory, links to lateral
PFC are well established for both short-term working memory and long-term
distraction-stable memory. For
short-term working memory, findings from ablation, neuroimaging, and
single-cell recording studies point to the lateral PFC as a principal site
(along with temporal and parietal tertiary association cortex) wherein
information is retained for brief periods during the performance of complex
problem-solving tasks (Fuster and Alexander 1971; Kubota and Niki 1971;
Goldman-Rakic 1992; Cohen et al. 1997; Courtney et al. 1997; D'Esposito et al.
1998; Rainer et al. 1998, 1999; Romo et al. 1999; Fletcher and Henson 2001;
Constantinidis and Goldman-Rakic 2001; Constantinidis et al. 2002).
For long-term distraction-stable memory,
the lateral PFC plays a key role in the retrieval of episodic memories stored
in posterior neocortex and hippocampus (Goldman-Rakic 1992; Fuster 1999), a
component of memory that is inherently conscious (Tulving 2002). Direct connections between the hippocampus
and the lateral prefrontal cortex have been established, and ablation (Wheeler
1995) and neuroimaging studies (Fletcher and Henson 2001; Braver et al. 2001,
Slotnick et al. 2003) have provided direct evidence of a relationship between
lateral PFC and long-term memory function.
Efferent Connections: On the efferent side, the question is
whether the left lateral PFC is able to access the motor programs that
presumably mediate VR-conscious behavioral output. There is ample evidence that this is the case for lateral PFC,
which sends outputs to the frontal eye fields, the premotor frontal cortex, the
basal ganglia, cerebellum, and superior colliculus (Goldman and Nauta 1976;
Alexander et al. 1986, Bates and Goldman-Rakic 1993; Lu et al. 1994; Schmahmann
and Pandya 1997). For VR-consciousness
in particular, a critical issue is whether the left lateral PFC is connected
adequately with Broca's area, the brain region that provides for syntactical
linguistic output. The pivotal role of
Broca's area, situated in the posterior part of the inferior frontal gyrus
(Brodmann's areas 44 and 45) of the left frontal lobe, in language expression
was established first in 1861 (Broca 1861) and has been amply confirmed in the
one and a half centuries that have followed.
For logical, grammatical output, which is the type involved in verbally
reporting on VR-conscious experience, the situation is asymmetric, with only
the "dominant" hemisphere (the left hemisphere in most humans and
almost all right-handers) capable of performing the function. Left lateral PFC is ideally positioned to
influence Broca's area and thereby express verbal reports pertaining to
VR-conscious experience since it lies immediately adjacent to it and projects
to it strongly (Deacon 1992).
Activation Studies: The principal evidence for activation of the
left lateral PFC during VR-conscious tasks comes from studies of working
memory, a cognitive function that is usually regarded as VR-conscious (Baddeley 2003). As noted above, neuroimaging and single-cell
recording studies indicate that lateral PFC is a principal mediating site for
working memory. Additionally, left
lateral PFC has been shown directly to become active in neuroimaging studies
during tasks involving VR-conscious experience (McIntosh et al. 1999; Kjaer et
al. 2001, Stephan et al. 2002).
Event-related potential measurements in humans have shown further that
lateral PFC is activated subsequent to posterior cortex in association with
performance of VR-conscious tasks, with a mean latency of activity in response
to visual stimuli over occipital areas measured at 56 msec and over lateral PFC
at 80 msec (Foxe and Simpson 2002).
This temporal sequence of events would be in keeping with a model in
which posterior cortex provides preliminary processing of stimuli for subsequent
VR-conscious processing by lateral PFC.
Results of Ablation: If the left lateral PFC were, by itself, the
mediator of VR-conscious experience, then ablation of the region should result
in its elimination. Care is needed, however,
in applying this syllogism in clinical situations. To begin with, since the focus up to this point has been
specifically on VR-consciousness, not on higher consciousness in general,
clinical cases would need to be assessed for the presence or absence of this
particular form of consciousness if they were to serve as an appropriate test
of the proposed theory as presented so far.
As we will see when we extend the discussion of the theory beyond the
confines of consciousness of the verbally reportable variety, it would be
damage to the lateral PFC bilaterally that would be expected to eliminate
higher consciousness in general.
There is also a methodological concern
having to do with the extent of the cortical damage incurred in reported cases. As will be evident when the theory is described on the microscopic
level, only nearly complete
inactivation of the left lateral PFC would be predicted to eliminate
VR-consciousness, and only complete inactivation of the lateral PFC bilaterally
would be predicted to eliminate higher consciousness more generally. Thus,
we note that some authors (Bogen 1995; Alexander and Stuss 2000; Taylor
2001) have cited clinical examples in the literature, such as the celebrated
case of Phineas Gage (Damasio 1999), where
extensive prefrontal lesions failed to eliminate higher conscious experience,
and have used these to argue
that the lateral PFC by itself cannot be the sole mediator of higher
consciousness. As pointed out by Crick
and Koch (1998), however, in none of these cases did the damage include the
entirety of the lateral PFC, rendering their significance uncertain. With only partial removal of the relevant
cortex, the remaining tissue might have been able to maintain residual higher
conscious function. On the other hand,
situations in which the lateral PFC is known to have been entirely destroyed
bilaterally, such as in patients with advanced Pick's disease, massive
bilateral strokes, extensive anoxic damage, or massive surgical bilateral
frontal lobe ablations as reported by Walter Dandy (1946), the clinical picture
is of a persistent vegetative state in which the victim is devoid of any higher
level consciousness (Sato et al. 1989; Laureys et al. 1999; Heilman and
Valenstein 1993; Laureys 2004). And in
cases in which the left lateral PFC is known for certain to have been destroyed
entirely, such as in global aphasia from a massive left middle cerebral artery
stroke, VR-consciousness is clearly lost, with the right hemisphere providing
residual, nonverbal higher conscious function (Heilman and Valenstein
1993). While such cases are consistent
with the notion that VR-consciousness is mediated solely by the left lateral
PFC, and that higher consciousness in general is mediated solely by the lateral
PFC bilaterally, the extensive nature of the damage in these reports ruins the
specificity of the correlation.
Cases are needed in which the left lateral PFC (or the lateral PFC
bilaterally) has been completely removed or rendered inoperative while other
structures have been left
intact, and an assessment made specifically for the presence or absence of
VR-consciousness (or higher consciousness more generally). Such cases have yet to be reported.
In summary, anatomical and functional
studies have been reviewed that point to the importance of left lateral PFC for
VR-conscious experience. Other authors
have also emphasized the importance of the lateral PFC to consciousness (Crick
and Koch 1998; Rees et al. 2002; Stephan et al. 2002). The present theory goes further, however, in
proposing that the left lateral PFC, situated within a divergent/convergent
feedforward information processing system, serves by itself as the direct
neural correlate for VR-consciousness.
On the other hand, suggestions have occasionally been made favoring
other brain regions as a center for consciousness (Dandy 1946; Taylor
2001). The parietal tertiary
association cortex is an attractive possibility (Taylor 2001), but the parietal
lobes do not receive direct information pertaining to smell, which is a common
component of VR-conscious experience.
Alternatively, the orbitofrontal cortex, which is a region that receives
convergent input from all modalities, might be considered to be a candidate for
a localized NCC. However, complete orbitofrontal
ablations, while they impair emotional processing, do not eliminate
VR-consciousness (Eslinger and Damasio 1985; Heilman and Valenstein 1993;
Damasio 1999).
The localization to the left lateral PFC
proposed in this paper, it should be noted, may not be the full extent to which
VR-consciousness is localized. The
lateral PFC might itself be further divisible.
In fact, support has been garnered for the lateral PFC encompassing two
functionally distinct subregions, one dorsolateral (portions of Brodmann 9, 46)
the other ventrolateral (portions of Brodmann 10, 11, 47), the two subregions
differing with respect to both anatomical connections and type of information
being processed (Oliveri et al. 2001). It has been suggested that the established
division of the posterior cortex into "dorsal" and
"ventral" streams (Ungerleider and Mishkin 1982; Goodale and Milner
1992; Milner and Goodale 1993; Foxe and Simpson 2002) continues into the
frontal lobes, with the dorsolateral PFC receiving input from the dorsal stream
via the parietal association cortex and the ventrolateral PFC receiving input
from the ventral stream via the temporal association cortex (Milner and Goodale
1995). Since both areas are strongly
connected to Broca's area, both are in a position to affect verbal output. Further, since both areas are strongly interconnected, either could
ultimately be the sole mediator of VR-conscious experience with the one serving to provide input to or receive output from the other. In fact, Milner and Goodale (1995) have argued for just this possibility,
suggesting that only the ventral stream is associated with VR-conscious
experience and that the dorsal stream processes information VR-unconsciously.
In the discussion that follows, the question
of which subregion by itself might mediate VR-conscious experience will be left
undecided and the generic term "lateral PFC" will be used to refer to
the area in general. In any case,
whatever the final localization of the macroscopic anatomical substrate for
VR-consciousness might be, all that is needed for the further development of
the single-neuron theory is that a macroscopically focal correlate for
VR-consciousness exists that is relatively homogeneous and is in a position to
receive all the sensory, emotional, and mnemonic stimuli that characterize the
VR-conscious experience.
4.
THE MICROSCOPIC STEP: THE SINGLE-NEURON
THEORY
Subsequent to the question of which
macroscopic brain region mediates VR-consciousness is the question of how the neurons
populating this region accomplish the task.
According to the generally accepted view, the participating neurons join
their activity into a single VR-conscious experience via dynamic interactive
mechanisms. The single-neuron theory
posits instead that a subpopulation of neurons in the left lateral PFC, rather
than joining their activity into a single VR-consciousness, remain separately
VR-conscious and produce the illusion of a joint VR-consciousness by virtue of
the joint action of their outputs. In
the model, each of the VR-conscious neurons at any moment is proposed to
experience not merely a fragment of a higher-order joint VR-consciousness but,
rather, the whole range and complexity of VR-conscious experience generally
attributed to the population as a whole.
Plausible candidates for
the role of VR-conscious neurons are the layer 5 pyramidal cells of the left
lateral PFC. A pivotal role for these
neurons in conscious processing has been suggested by other investigators
(Crick 1994; Orpwood 1994; Gilbert 1998; Bieberich 2002). It will be useful to briefly review the main
characteristics of these neurons before describing how they might individually
serve as neural correlates of VR-consciousness.
Anatomical
and Functional Characteristics of Lateral PFC Layer 5 Pyramidal Neurons
Like all neurons, layer 5 pyramidal cells
function by integrating the electrical responses of an enormous array of
dendritic synaptic inputs, the result
of which determines a single channel of axonal output consisting of
sequences of action potentials of identical shape and amplitude. Early on, the dendritic tree was modeled as
a single entry point (McCullough and Pitts 1943), with inputs simply summing
linearly to produce axonal output. In
the late 1950s, Rall (1959, 1967) introduced the passive cable model, in which
the spatial extent of the dendritic tree was taken into account and
accommodation was made for the effects of location and amplitude of
postsynaptic potentials on the neuron's axonal response. The passive cable model provided for a
degree of intradendritic information processing that was not possible with the
earlier "point neuron" model.
In recent years, the presence of significant nonlinear intersynaptic
effects occurring on multiple levels has been discovered (Cash and
Yuste 1999; Magee
1999; Koch 1999; Larkum et al. 1999a; Magee and Cook 2000; Spruston 2000;
Hausser et al. 2001; Wei et al. 2001), suggesting that considerable intradendritic computational processing
precedes the eventual generation of axonal action potential.
Additionally,
there is evidence that intradendritic processing occurs independently in
separated compartments before an overall effect is delivered to the soma (Koch
1997). For layer 5 pyramidal neurons, a
unique anatomy facilitates this compartmentalization. Most notable is the long ascending dendritic shaft, extending 1.3
mm from the cell body in layer 5 to the apical tip in layer 1, that separates
the proximal basal dendrites from the distal apical dendrites. Midway along the shaft are the oblique
dendrites, both proximal and distal.
Recent evidence suggests that the output of the various compartments
interact via two intraneuronal dendritic action potentials. The first is a forward propagating,
calcium-mediated potential originating at the distal end of the dendritic stalk
that is produced as a result of nonlinear integration of apical dendritic
inputs. This action potential courses
from the apical end of the dendritic shaft to the soma where it induces a burst
of axonal action potentials (Helmchen et al. 1999; Schiller et al. 1995, 1997; Schwindt
and Crill 1999; Larkum et al. 1999a; Williams and Stuart 2002). The second is a backpropagating
sodium-mediated action potential that is triggered by axonal firing and that
courses from the soma back into each of the dendritic arbors (Stuart and Sakmann
1994). The two action potentials appear
to be coupled, with the backpropagating potential lowering the threshold for
triggering of the forward propagating potential, provided the two potentials
occur within a few milliseconds of each other (Larkum et al.1999a, 1999b; Larkum et al. 2001; Schaefer et al.
2003; Larkum et al. 2004). The coupling has been shown to depend
crucially on the morphology of the participating dendritic branches (Mainen and Sejnowski 1996; Schaefer et al. 2003; Vetter et al. 2001).
Aside from the nonlinear interactions
present at the intercompartmental level, nonlinear interactions have been found
within the dendritic arbors as well (Cash and Yuste 1999; Magee 1999; Koch 1999; Larkum et
al. 1999a; Magee and Cook 2000; Spruston 2000; Hausser et al. 2001; Wei et
al. 2001; see Magee
2000 for a review). It has been
suggested that nonlinear interactions between neighboring synapses provide for
increased computational capability in dendritic trees (Segev and London 2000;
Van Ooyen et al. 2002; see Hausser and Mel 2000 for a review).
Because of the anatomy and
compartmentalization of the layer 5 pyramidal neurons, they are ideally
positioned to integrate input from the different cortical layers (Spratling
2002; Thomsen et al. 2002a; Briggs and Callaway 2005).
Thus, the basal dendrites, which are situated near the cell body in
layer 5, receive intralaminar input from other pyramidal neurons in the same
layer (Lubke et al. 1996; Thomson et al. 2002b; Douglas and Martin 2004). Higher up, the oblique dendrites receive
inputs from layers 2, 3 and 4 (Schaefer et al. 2003). Still more distally, the apical dendrites receive inputs from
layers 1, 2 and 3 (Schaefer et al. 2003).
A functional interpretation of these
inputs is provided by a proposed microscopic feedforward circuit that includes
the layer 5 pyramidal neurons (Gilbert and Wiesel 1986; Thomson et al. 2002a,b;
Thomson and Bannister 2003). The main
pathway in this circuit is characterized by a feedforward flow beginning with
the layer 4 stellate (granular) neurons, which receive incoming feedforward
signals from other cortical and thalamic regions, and moving on to the
pyramidal neurons in layers 2 and 3, then on to layer 5 pyramidal neurons, and
finally out to pyramidal neurons in layers 1 and 5 elsewhere in the prefrontal
cortex, as well as to premotor cortex, posterior cortex, thalamus, basal ganglia,
and superior colliculus. Return input
from these distant targets arrive via diffusely projecting layer 1 fibers,
whose signals are received by the pyramidal neurons in layers 2 and 3, and 5
(the latter receiving inputs from layer 1 both directly and also indirectly via
inputs from layers 2 and 3). In this
scheme, the input from layer 1 consists of diffusely encoded signals derived
from thalamus, hippocampus, and posterior and frontal limbic areas (Barbas and
Rempel-Clower 1997; Rempel-Clower and Barbas 2000; Mitchell and Cauller 2001;
Barbas and Hilgetag 2002). These inputs
have been postulated to be associated with attention, feedback, and context
(Williams and Stuart 2002; Douglas and Martin 2004)). The inputs to layer 2 and
3 pyramidal neurons derive from both local and distant layer 2 and 3 pyramidal
neurons located throughout the lateral PFC.
These layer 2 and 3 pyramidal neurons are, especially in the lateral
PFC, highly interconnected and have been proposed to serve an important role in
the maintenance of reverberatory circuits underlying working memory (Kritzer
and Goldman-Rakic 1995; Gonzalez-Burgos et al. 2000; Melchitzky et al.
2001).
An important implication of these pathways
and connections (see Larkum 2001), and one that will be used in developing the
single-neuron model, is that the apical dendrites of layer 5 pyramidal neurons,
by virtue of being recipients of layer 2/3 pyramidal cell output, are in a
position to receive inputs representing the full range of VR-conscious content. In the following sections, we will build on
this and the other characteristics of layer 5 pyramidal neurons to present a
specific way in which the single-neuron theory of consciousness might play out
at the microscopic level. It should be
noted that it is not contended that the model to be presented is the only way a
single-neuron theory can be instantiated.
For example, it may be that neurons other than the layer 5 pyramidals
might equally well serve as loci for VR-consciousness, or it may turn out that
the details of layer 5 pyramidal function as described above need
modification. The purpose of the
presentation is mainly to provide a specific instantiation of the theory in
order to demonstrate that a single-neuron model is in principle feasible. The model will be built upon a framework of
convergent/divergent feedforward information flow, in which feedback and
reentrant circuits play only an adjunctive role. The features of the model will be presented in a feedforward
sequence: A) first, a mechanism of information encoding at the neuronal
population level will be described for the network of neurons that will serve
as the afferent input for VR-conscious neurons; B) second, the process by which signals converge upon the
dendritic trees of VR-conscious neurons and induce intradendritic NCCs will be
considered; C) third, a
mechanism by which the dendritic NCCs reexpress themselves at the neuronal
population level will be suggested.
A) Population Encoding of the
Information to be Inputted to the VR-Conscious Neurons:
We begin by examining the
information processing characteristics of layer 2 and 3 pyramidal neurons in
left lateral PFC, which will be presumed to be the source of the inputs to layer 5 pyramidal neurons that
lead to VR-consciousness. In overview, it is hypothesized that the
convergent input to the left PFC as a whole, argued in the previous section to
contain the sensory, emotional, and mnemonic signals that feed VR-consciousness,
passes from layer 4 stellate neurons to layer 2/3 pyramidal neurons, and that
the relevant information is encoded in the spatial arrangement of a
synchronously firing subpopulation of these layer 2/3 neurons.
We now consider this process in more detail.
As a preliminary, we need
first to address the nature of the neural code. There has been an ongoing debate over how information is encoded
by neuronal populations in neocortex.
The principal questions have to do with the relative importance of
individual neuronal spikes in cortical processing and whether spikes derived
from different neurons are bound by means of temporal synchrony.
The early view was that information is encoded in the cortex by the
average rate of axonal action potential production over a given time interval,
typically between 20 and 200 msec, and that the exact timing of individual
spikes is unimportant. (Adrian 1926; Barlow 1972; Shadlen and Newsome 1994;
Shadlen and Newsome 1998; Shadlen and Movshon 1999; Yazdanbakhsh et al. 2002;
Rolls et al. 2003). In recent years,
however, the alternative possibility, that each spike individually carries
relevant information, has gained a growing following (Softky and Koch 1993;
Gray 1999; Borst and Theunissen 1999; Williams and Stuart 2000; Abeles
2004). A related idea, that brain
neuronal activity can be synchronized, and that synchrony is in fact a widely
occurring and robust phenomenon that might serve to define functional
relationships between spatially distributed cortical neurons, has also gained
considerable support (Abeles
1991; Konig et al. 1995; Singer
and Gray 1995; Lumer et al. 1997; Stevens and Zador 1998; Lachaux JP et al.
1999; Usrey and Reid 1999; Grammont and Riehle 2003).
The possible mechanisms underlying the induction of temporal synchrony
of cortical neuronal activity have been explored (Niebur et al. 2002; Reyes 2003; Segev 2003; Nowotny and
Huerta 2003), as has its
possible behavioral relevance (Sougne and French 2001). In particular, it has been suggested that
synchronous firing promotes synergy between spikes arriving simultaneously at
target neurons, thereby providing a powerful signal selection mechanism (Niebur
et al. 2002; Averbeck and Lee 2004).
For the theory presented in this paper,
it will be assumed that individual spikes do matter, and that synchronous
firing identifies subpopulations of neurons that encode salient information in
their spatial arrangement. The model
employed is an adaptation of the
well-studied "synfire chain" mode of cortical signal transmission
(Abeles 1991, 2004; Aviel et al. 2002), which invokes the importance of both
individual spike timing and the synchronization of spatially dispersed neuronal
activity. The synfire chain theory
describes a process of synchronous convergent/divergent feedforward signal
transmission through multiple neuronal layers.
Synchrony is hypothesized to result from an arrangement in which, for
each layer, there is a pool of neurons with the property that each neuron in
the pool: a) receives afferent inputs
from all the neurons in the pool in the previous layer, and b) projects its
output to all the neurons in the pool in the next layer. Empirical observations supporting the
presence of synfire chain activity in the brain have been reported by a number
of investigators (Abeles 1991; Miller 1996; Prut et al. 1998; Abeles 2004;
Ikegaya et al. 2004) and their properties have been analyzed through
theoretical simulations (Abeles 1991; MacGregor et al. 1995; Aertsen et al.
1996; Hertz and Prugel-Bennett 1996; Diesmann et al. 1999; Arnoldi et al. 1999;
Gewaltig et al. 2001; Sougne and French 2001; Yazdanbakhsh et al. 2002). Theoretical simulations have indicated how,
in a multilayered feedforward neural network consisting of integrate-and-fire
neurons, synchronous firing on a millisecond time scale arises in successive
layers, even if the initial input to the chain are asynchronous (Pinsky 1995;
Arnoldi and Brauer 1996; Hertz and Prugel-Bennett 1996; Marsalek et al. 1997;
Rudd and Brown 1997; Campbell et al. 1999; Neltner et al. 2000; Niebur et al. 2002; Reyes 2003; Segev 2003; Nowotny and
Huerta 2003). The synchronous chains
have been shown to be stable against noise, provided a sufficient number of
neurons populate each pool, estimated to be on the order of 100 neurons (Abeles
1991; Postma et al. 1996; Diesmann et al. 1999; Gewaltig et al. 2001; 2001). In the stable state, essentially all response spikes in a volley
fall within ±1 ms, which is within the precision of experimentally observed
neuronal firing patterns, despite the presence of a membrane time constant of
10 ms or more (Diesmann et al. 1999; Gewaltig et al. 2001).
In the proposed single-neuron theory, the
presence of a synfire chain comprising two consecutive pools of neurons is hypothesized: one pool in lateral PFC layer 2/3, the other
pool in lateral PFC layer 5. The pool
in layer 2/3 is taken to
comprise a subpopulation of synchronously firing pyramidal neurons that have
received feedforward input from layer 4 pertaining to VR-consciousness, with
that information being encoded in the spatial arrangement of the participating
neurons. The presence of identifiable
spatial patterns of neuronal excitation in cortical neuronal populations has
been reported in a variety of contexts.
These include the peculiar complex
logarithmic relationship between spatial patterns of excitation in the
retina and those in area V1 pyramidal neurons (Schwartz 1980; Alexander et al.
2004), the specific topographic pattern of layer 5 pyramidal neurons in cat
visual cortex that exhibited repeating temporal spike sequences (Ikegaya et al
2004), the specific spatial patterns of neuronal response to air currents in
the cricket cercal system (Jacobs and Theunissen 2000), and the work of
Grossberg et al. (1999), which implicates an important role for the topography
of primate visual cortex in shaping neuronal responses at subsequent levels of
cortical visual processing. In the
single-neuron theory, it is the topography of neuronal activation in the
synchronously firing layer 2/3 pyramidal population that is assumed to carry
the information to be delivered to the layer 5 pyramidal neurons.
B) Conversion of Afferent
Population Patterns into Intradendritic Neuronal Electrical Patterns:
The next issue in the feedforward
progression is the matter of how the afferent signals from the synchronously
firing layer 2/3 pyramidal neurons converge upon layer 5 pyramidal neurons and
lead to intradendritic electrical activity that serves as the neural correlate
for VR-consciousness. Consideration
will be given first to the synaptic activation patterns induced in the layer 5
pyramidal neurons, and then to the conversion of these synaptic activation
patterns into spatial electrical patterns within the dendrites. For the model to work, two hypotheses are
needed:
HYPOTHESIS 1: THE MAPPING FROM POPULATION TO
DENDRITIC IS HOMOTOPIC AND
INFORMATION PRESERVING: Despite its
vital importance to an understanding of neuronal information processing, there
is little available data pertaining to the neurons of origin for particular
synaptic inputs within a dendritic tree.
That is, while neurons of origin have been identified with respect to
one or another overall dendritic compartment, similar information with respect
to individual synaptic inputs within a compartment are not yet available. In the absence of such empirical clues, I would suggest that a plausible possibility is that the topographic mapping of
inputs from the synchronously firing layer 2/3 pyramidal neurons onto layer 5 pyramidal
dendrites is homotopic (the shape of the one can be continuously transformed
into the shape of the other) and information preserving.
Homotopic, information preserving mappings have been found elsewhere in the nervous system, such as in the
complex logarithmic mapping of
retina onto V1 already mentioned (Schwartz 1980; Alexander et al. 2004),
and in the homotopic connections between the cerebral hemispheres via the
corpus callosum (Mitchell and Macklis 2005).
The suggestion is that the axons arriving from the synchronously firing
layer 2/3 pyramidals retain their relative positions and preserve topological information in coursing toward their
targets and do not
"criss-cross" on their way to innervating the dendritic tree of the
layer 5 pyramidals. Whether this is in
fact the case will need to be determined experimentally. Since it plays a key role in the
hypothesized theory, testing for its presence will serve as an empirical test
for the plausibility of the proposed theory.
HYPOTHESIS 2: SIMILAR PATTERNS ARE RECEIVED BY
MULTIPLE NEURONS: A second assumption is that the
projections from layers 2 and 3 to layer 5 involve convergence of a similar
pattern onto multiple neurons. If the topographic pattern of synaptic
excitation is relevant in determining whether it induces axonal firing or not,
then this is in effect the central assumption of the synfire chain
theory that was discussed in detail above, and upon which the currently
proposed model is based.
With these hypotheses in hand, a
mechanism can be described by which the spatially encoded pattern at the
population level in layer 2/3 reappears as a spatially encoded pattern of
intradendritic electrical activity in layer 5 pyramidal cells, this pattern
serving as the neural correlate for VR-consciousness. We start by proposing
that the spatial electrical pattern corresponding to VR-consciousness forms
within the thin distal branches of the apical dendritic tree. While alternative locations, such as the thin oblique dendritic branches,
could also be chosen, the apical branches are selected here to provide a
concrete example of how the overall model would work. By hypothesis 1, it is assumed that a specific pattern of
synaptic excitation is induced by convergent input from a synchronously firing
pool of layer 2/3 pyramidal neurons, and that this pattern of synaptic
excitation is a homotopic, information
preserving transform of the spatial pattern of the layer 2/3 neuronal
pool. By hypothesis 2, it is assumed
that a similar pattern of input is received by a pool of layer 5 pyramidal
cells.
The shape of the electrical response
within the dendritic branches of each neuron receiving this pattern of synaptic
input will, in turn, be an ordered transformation of the shape of the incoming
signals (Bieberich 2002, Orpwood 1994, and Livingstone 1998), modified by the
effects of synapse efficiency and local nonlinear effects (including those due
to the state of depolarization of the synapses at the time of signal input, the
interactive effects between synapses due to induced local chemical and
electrical changes, and the morphology of the dendritic tree itself), each of
which is likely somewhat different for each of the neurons in the receiving
pool (Spruston et al. 1995; Mainen and
Sejnowski 1996; Hoffman et al. 1997; Agmon-Snir et al. 1998; Cash and Yuste
1999; Magee 1999; Koch 1999; Larkum et al. 1999a; Magee and
Cook 2000; Spruston 2000; Magee
2000; Vetter et al. 2001; Hausser et al. 2001; Wei et al.
2001;; Schaefer et al.
2003; Polsky et al. 2004).
The variations in the shape of the intradendritic electrical responses
across the different neurons would be assumed to be relatively small, so that
variations in VR-conscious experiences of the different neurons would be
relatively small as well. I will
consider later the potential impact that
large variations might have on the single-neuron theory.
Of critical importance to the
singe-neuron theory is the assumption that the intradendritic electrical
pattern that forms in the distal apical branches, which is proposed to serve as
the direct neural correlate for VR-consciousness, extends through only a
portion of the neuronal dendritic tree.
It is hypothesized that its ultimate
effect on axonal firing therefore comes only after it combines nonlinearly with other
intradendritic electrical activity, both within the more proximal apical tuft
in generating a calcium-mediated dendritic action potential and in the
subsequent interaction between the different dendritic compartments. That is, the local electrical activity that
serves as the neural correlate for VR-consciousness in the distal apical tree
of a given neuron is assumed to affect neuronal output only in the context of
other inputs received by the neuron at the same time. Again, this effect is presumed to be different for the different
layer 5 pyramidal neurons in the pool, and therefore the responses of the
different neurons to the same (more or less) VR-conscious electrical activity
forming in the distal apical dendrites will be different. In the next section, this fact will be used in proposing a mechanism by which the
intradendritic VR-conscious shape reexpresses itself at the neuronal population
level. Before turning to that
mechanism, it is important to consider whether the electrical activity
purported to serve as the neural correlate for VR-consciousness has the right
type and degree of complexity to encode
for conscious experience.
COMPLEXITY OF INPUTS TO THE LAYER 5 PYRAMIDAL
NEURONS: For the single-neuron theory to be
plausible, it needs to be the case that the electrical activity in the distal
apical branches of an individual neuron is by itself complex enough to support
the complexity of VR-conscious experience.
The relevant observation pertaining to this requirement is that cortical
pyramidal neurons receive a huge number of afferent signals over their
dendritic trees. It is estimated that
for humans each cortical pyramidal neuron incorporates between 20,000 and 40,000
synapses within its dendritic tree (Abeles 1991), a number larger than is
usually appreciated and one that allows for an impressive complexity of
information encoding. For example, if
only one tenth of one percent of the synapses of a cortical pyramidal neuron
were assumed to participate in a given VR-conscious experience, and if only a
simple binary code were being used (that is, one in which the synapse is either
active or inactive), then 240 or about one trillion different
patterns could be encoded by that neuron.
Alternatively, as noted by Bieberich
(2002), if it is assumed that 5,000 simultaneously arriving synaptic input
bytes, corresponding to 5,000 active spines in the dendritic tree, are turned
over with a frequency of 50 Hz, then a single neuron would be capable of
processing 5 mB of information per second.
This, Bieberich argues, constitutes a rate of information processing
adequate to plausibly account for the complexity of VR-conscious experience.
By either of these calculations, individual
cortical pyramidal neurons appear capable of processing information of a
complexity greater than often appreciated, and quite possibly sufficient to
mediate the entirety of the VR-conscious experience.
CONVERGENCE OF MODALITIES UPON INDIVIDUAL LAYER 5
NEURONS: Another requirement that the
single-neuron theory must meet is that the dendritic trees of the VR-conscious neurons would need to
individually be recipients of all of the kinds of inputs that make up the
VR-conscious experience. If it is
assumed that the lateral PFC as a whole receives all of the inputs that
comprise VR-conscious experience, then the question is whether it plausible
that there are individual pyramidal neurons within the region that do likewise? That is, is it plausible that the
information that converges upon the region as a whole converges separately on
each of a subgroup of pyramidal neurons populating the region? In support of the presence of such an
arrangement is the clinical observation that focal lesions within lateral PFC
do not result in modality-specific deficits but only diminish the region's
function in a general manner. This
suggests at least some degree of microscopically redundant convergence
throughout the extent of the region.
Additionally, individual cortical neurons typically receive inputs from
thousands of other neurons (Koch 1997, Schuz 1998) and so are in a position to
serve as nodes of converging information.
Aside form general considerations, however, are the reports that direct
single-cell recordings have identified neurons in lateral PFC that respond
selectively to conjoint visual and auditory stimuli (Aou et al. 1983), to
conjoint visual, auditory and tactile stimuli (Tanila et al. 1992), and to
conjoint object and location features (Rao et al. 1997). Whether a subgroup of
lateral prefrontal neurons exists in which each neuron in the subgroup receives
convergent input from all the sensory, emotional, and mnemonic stimuli that
comprise VR-conscious experience is yet to be empirically determined.
C) Generation of the Outgoing
Signal:
Supposing that the spatial pattern of
distal apical intradendritic electrical activity of left PFC layer 5 pyramidal
neurons serves as the neural correlate for VR-conscious experience, there is
then the vexing question of how the information encoded at the dendritic level
is passed on to brain output mechanisms that control behavior. In particular, how can dendritic signal
patterns of high complexity converge into a single axonal output channel
without a drastic loss of information?
On the face of it, it would appear that such information loss is
unavoidable, since axons transmit action potentials that are uniform in shape
and amplitude and therefore only the timing of the transmitted spikes can be
used to encode information (Adrian 1926).
Across a range of settings, the information contributed by individual
axonal spikes has been measured to be on the order of one bit to 3 bits per
spike, with an axonal information transmission rate therefore reaching no more than
several hundred bits per second (Bialek et al. 1991, Borst and Theunissen
1999). This rate of information
processing is far smaller than that performed by the dendritic tree. How, then, can a gross loss of information
be averted?
A possible solution to this problem may
reside in another application of synchronous neuronal firing, one that is
inspired by a model of neuronal
information processing recently proposed by Bieberich (2002). The
idea is that a mechanism by which the VR-conscious electrical activity
present within the layer 5 pyramidal dendrites might be reexpressible
at the population level in the form of
the spatial arrangement of a synchronously active subset of the layer 5
pyramidal cells. Conceptually, the sequence is as follows:
1) First, as described above, similar
VR-conscious spatial patterns of electrical activity are formed in the distal
apical trees of a population of synchronously activated layer 5 pyramidal
neurons in the left lateral PFC.
2) Next, the VR-conscious spatial patterns
interact nonlinearly, at both the intracompartmental and intercompartmental
levels, with the other inputs received by these layer 5 neurons.
3) The results of these interactions are
assumed to differ across neurons in the population and therefore to have
different effects on the propensity for axonal spike generation in the
different neurons in the population, such that some neurons fire while others
remain silent.
4) As a consequence of (3), only a subgroup
of neurons in the population respond with synchronous firing, with the active
subgroup marking out a spatial pattern at the population level. The spatial pattern, it will be noted, would in part have been dictated by the spatial pattern of the
VR-conscious dendritic electrical activity in the neurons of the population.
5) If there are N neurons in the starting
population and only M neurons fire (M<N), then the number of different
subgroups that can be formed (and therefore the number of different spatial
arrangements of firing neurons that can arise) is given by the combination of N
things taken M at a time: N!/M!(N-M)!
For even small populations, this is a huge number. For example, say there are 100 layer 5
pyramidal neurons that receive synchronous dendritic inputs of similar shape
from the layer 2/3 neurons, and that half of these 100 neurons fire. Then the number of different spatial
patterns that can form would be equal to the combination of 100 things taken 50
at a time, or (100!)/(50!)(2) = 4 x 1012, an enormous number that
matches the complexity of dendritic input as calculated above.
6) The spatial pattern formed by the
subpopulation of synchronously firing left lateral PFC layer 5 pyramidal
neurons, which incorporates the interaction between VR-conscious information
and other information received by the layer 5 pyramidal neurons, serves as the
source of conscious output from the left lateral PFC to other brain regions.
While this mechanism may provide a means
for the information contained in the intradendritic VR-conscious electrical
patterns to be re-expressed at the population level, there is the additional
question of whether enough neurons are present in the proposed synchronous
populations in layers 2/3 and 5 to affect gross behavior. As so far described, this would appear
unlikely, since previous work with synfire chains has usually associated the
phenomenon with relatively small neuronal groups (Abeles 1991). A realistic model would need to incorporate
the possible presence of many small competing synchronous neuronal groups. For a single dominant synchronous group to
arise, still additional assumptions would have to be made. This issue is, of course, not unique to the theory
presented here. It is a challenge that
must be faced by most current neuronal network models of consciousness.
A plausible approach to solving this
problem may be to invoke the concept of attention as a mechanism for amplifying
the effects of selected synchronously firing neuronal pools. Studies have, in fact, been reported that
suggest a role for attention in increasing the synchrony of neuronal firing
(Steinmetz 2000; Fries et al. 2001), possibly mediated by gamma frequency
oscillations (Crick and Koch 1990a,b; Niebur et al. 1993; Niebur and Koch
1994). In this way, attention might
serve as an "on-off" switch for lateral PFC conscious function. The detailed nature of the attentional
mechanism by which the small population of synchronously firing neurons might
gain control over VR-conscious output systems can only be speculated on at
present. One possibility is that the
"bursty" output of the layer 5 pyramidal neurons (Crick 1994; Schiller et al. 1995, 1997;
Helmchen et al. 1999; Schwindt and Crill 1999; Larkum et al. 1999a; Williams
and Stuart 2002), in association with cortico-thalamo-cortical loops (Llinas et al. 1998), may provide
for the proliferation of the synchronous groups. This could conceivably be accomplished through competition, as in
the "neural darwinism" mechanism described by Edelman (1993), or
perhaps via merging of separate synfire chains (Arnoldi et al. 1999; Hayon et
al. 2005). Yet another possibility
might involve the creation of a fractal architecture in which multiple copies
of the synfire neuronal pool arise as a result of the fractal geometry of
axonal branching (Bieberich 2002). With
each of these proposed mechanisms, the lateral PFC would be envisioned as
functioning in a “holographic” manner, with the same information represented
repeatedly in neurons dispersed across the full extent of the region. As a result, it would be expected that
damage to the entire lateral PFC would be required to eliminate the
corresponding conscious functioning, a
point that was stressed earlier in Section 3.
In summary, a case has been made for the
possibility that, at the microscopic level, VR-consciousness is mediated by
single neurons rather than by a neuronal population. The macroscopic step was necessary to provide for individual
neurons that receive all the inputs comprising VR-conscious experience and for
the supposition that there might be groups of such neurons that individually
receive similar input. In the
microscopic step, it was argued additionally that individual neurons are by
themselves sufficiently complex to account for the complexity of VR-conscious
experience and that a mechanism may be present that translates the spatial
pattern of dendritic activation within synchronously firing neurons into the
spatial arrangement formed by those neurons at the population level.
5. ADDITIONAL
CONSIDERATIONS:
Other Conscious Regions: The discussion so far has been limited to
the case of VR-consciousness, that form of consciousness largely responsible
for the debate over the "hard" problem of consciousness. It was useful to invoke this restriction in
order to narrow the focus of the presentation.
The theory can, however, be extended to include forms of consciousness
that are not verbally reportable.
Indeed, patients with lesions that result in the loss of
VR-consciousness often appear to manifest residual nonverbal consciousness,
presumably mediated by structures outside the left lateral PFC. Damasio (1998, 1999) has suggested that the
residual consciousness observed in such patients be regarded as one of two
overlapping types of consciousness, a non-verbal "core consciousness"
mediated by midline cortical and subcortical structures, and a linguistically
competent "extended consciousness" mediated by lateral neocortical
structures. The notion that a single
brain might contain multiple centers of consciousness has been suggested by
other investigators as well (Geschwind 1981, Edelman and Tononi 2000).
A particularly intriguing possible center
of nonverbal consciousness is the right lateral PFC. Since this region is
anatomically homologous to the left lateral PFC, being anatomically distinguishable from the latter principally by its
lack of direct connections with Broca's area and related structures, it might
be possible that it mediates a nonverbal form of higher consciousness separate from that mediated by the left
hemisphere. In 1973, Rolando Puccetti
suggested exactly this possibility (Puccetti 1973), proposing that the apparent
duplication of consciousness that results from corpus callosum resection (the
so-called "split-brain" procedure) is best explained by assuming that
the right and left hemispheres maintain separate conscious streams not only
after callosal disconnection but before the disconnection as well. According to his hypothesis, the callosal
section merely serves to uncouple what are already, in the normal state, two
anatomically separate consciousnesses.
Such a notion would fit well with the single-neuron theory, which
readily admits to the existence of multiple anatomically separate centers of
conscious experience.
In Puccetti's model, it should be noted,
the hypothesis is that there are no more than two conscious centers present,
and the discussion is limited to the macroscopic level only. With the presently proposed theory, an
additional step is taken, that of proposing that many macroscopic conscious
centers may be present in a single brain, and that the multiplicity of
consciousnesses extends to the microscopic single-neuron level as well. The overall picture would be one in which
multiple macroscopic centers of consciousness are proposed to exist, including
ones located throughout neocortical, subcortical, and brainstem regions, with
each center composed, in turn, of populations of neurons that individually and
redundantly mediate the conscious activity appropriate to the brain region
within which they reside.
Relationship between the Single-Neuron
Theory and Other Anatomical Theories of
Consciousness:
The theory presented in this paper is compatible with many of the
anatomical and functional features that characterize other recently proposed
theories of consciousness. For example,
Dehaene (1998) places the lateral PFC in a prominent position in his
description of Baars' global
workspace theory (Baars 1988; Baars and
Franklin 2003), Llinas (1998) focuses on thalamo-cortico-thalamic
oscillating loops, Damasio (1998) distinguishes between a brainstem mediated
core consciousness and a cortically mediated extended consciousness, Dandy
(1946) favors a striatal dominance in his theory of consciousness, and Edelman
(1993) proposes a theory based on “neural darwinism.” The neuroanatomical and functional proposals made in these
theories are for the most part compatible with the single-neuron theory. The principal differences are that with the
single-neuron theory, the lateral PFC by
itself is assumed to serve as the macroscopic correlate for higher
consciousness, with the other structures playing only an adjunctive role, and
the individual neuron is assumed to serve as the microscopic correlate for
consciousness of all kinds, while in the other models, consciousness is always
a network property.
Philosophical Caveat: The legitimacy of employing
"experience" as a target of scientific investigation is not, it
should be noted, universally accepted.
It has, for example, been argued by Dennett (1991) and others that
"subjective experience"
as illusory and that once all
the brain processes associated with a given behavior are objectively described
there is nothing left to be explained.
Dennett's arguments, if correct, would eliminate the need to localize a
mind/brain interface or to solve a "binding problem." If, on the other hand, subjective
experience is a phenomenon in need of explanation, then the proposed
single-neuron theory, which shifts the locus of the mind/brain interface from a
macroscopic to a microscopic domain, might provide fresh avenues for addressing
Chalmers' "hard problem." In
the section of the paper entitled “Speculative Implications” I will provide a
specific example of how this might play out.
Other Single-Neuron Models:
Comparison of the single-neuron theory with other models that focus on single
neurons may help clarify just what the single-neuron theory does and does not
propose. For example, it is important
to distinguish the function of the single neurons in the single-neuron theory
from those referred to as "grandmother cells," single neurons whose
activation corresponds to the experience of a single memory (Thorpe 1998). The grandmother cell concept has in common
with the single-neuron theory the notion that a single neuron may contain
sufficient complexity to account for the complexity of a complete conscious
experience. It differs, however, in
that the grandmother cell is assumed, in the context of explaining memory
function, to be forever attached to a single experience, whereas the single
neurons of the single-neuron theory flexibly change their experiences over
time. Among other consequences of this
distinction, the limitations in processing capacity that plague grandmother
cell models, referred to variously as the "combinatorial problem"
(Singer and Gray 1995) or the "problem of exponential explosion"
(Gold 1999), do not apply to the single-neuron theory.
Zeki's Model: Another single-neuron based model was
described by William James (1890) in his discussion of what he called the
"theory of polyzoism or multiple monadism." According to this view, "every brain-cell has its own
individual consciousness, which no other cell knows anything about, all individual
consciousnesses being 'ejective' to each other." Along similar lines, Zeki and Bartels (1999) have recently
proposed that a primate visual brain consists of many separate functionally
specialized processing systems comprising hierarchical nodes that each generate
a "microconsciousness."
Neither of these schemes, however, explains how the individual
microconsciousnesses are able to induce macroscopically evident behavior. Zeki attempts to solve this problem by
suggesting that the many microconsciousnesses participate in a higher order
integrative activity that produces macroscopic consciousness. This, however, returns us to the received
view that consciousness is ultimately mediated by multiple neurons linked
through dynamic mechanisms. James, on
the other hand, considers the possibility that a single pontifical arch-cell by
itself might mediate the
totality of one's consciousness but he goes on to assert that there is no
evidence for such a single "center of gravity" in the brain. Both authors appear to overlook the
possibility that multiple separately and redundantly conscious neurons might
summate their outputs so as to produce the illusion of a single mind.
Bieberich's Model: Two other investigators have published
models featuring single-neuron consciousness.
Edwards (2005) proposes a model
of individual neuron consciousness not unlike the one presented here, but he
approaches the subject from the point of view of philosophy and physics and
offers no specific neuroanatomical mechanisms. Bieberich (2002), on the other hand, gives a detailed anatomical
account of his single-neuron theory. He
proposes a theory of "recurrent fractal neural networks" in which
spatial information encoded at the neuronal network level is reflected in the
spatial activity patterns exhibited in the dendritic trees at the single neuron
level. As with the single-neuron theory
proposed in the present paper, the individual neurons in Bieberich's model are
assumed to mediate the entirety of a subject's conscious experience at a given
moment.
Bieberich's theory has certain difficulties, however. First, he hypothesizes the existence of
feedback connections from layer 5 pyramidal neurons to layer 2/3 pyramidal
neurons in the construction of his theory.
However, feedback connections from layer 5 to layer 2/3 synapse on
inhibitory interneurons, not on layer 2/3 pyramidal neurons (Dantzer and
Callaway 2001; Thomson and Bannister 2003).
His theory would need to account for this. Additionally, while he offers an intriguing anatomical mechanism
to explain his theory at the microscopic level, he has yet to explain how it
would function on the macroscopic level.
If these difficulties could be
surmounted, Bieberich's theory might provide a possible complement to the microscopic mechanism proposed in
this paper.
The Single-Neuron Theory and the
Binding Problem: The most immediate
implication of the single-neuron theory is that it provides a novel way of
tackling the "binding problem," the problem of accounting for the
apparent unity of conscious experience.
According to the currently popular view, which attempts to solve the
binding problem in the context of an anatomically distributed model of
consciousness, the expectation is that dynamic mechanisms, including those
associated with 40 Hz gamma frequency electrical oscillations, will ultimately
resolve the difficulty. In contrast,
the single-neuron theory offers an alternative possibility, that binding may be
achieved by anatomical convergence.
That is, if it were true that single neurons were present that received
the full complement of inputs that comprise conscious experience, then
perceptual binding might be achievable on the basis of convergence of input
upon individual neurons. In such a
model, topographical convergence rather than temporal synchrony would be
invoked to explain perceptual unity. Of
course, a mechanism would then be needed to explain binding within neurons,
which, as William James noted over a century ago (James 1890), are themselves
aggregates of individual particles. But
at least the venue would be changed, with the search for a mechanism of binding
being transferred from the neural network level to that within the single
neuron.
It must be noted that the above
presupposes that the apparent unity of conscious perception is a real
phenomena. It is possible, instead,
that, as has been asserted by Dennett (1991) and others, perceptual unity is an
illusion. It is possible, that is, that
our apparently unified experience actually consists of independent fragments,
and that the fragments never combine into a single experience. If such were only partially the case, with
the fragments being themselves composed of convergent elements, then there
would still be a role for the single-neuron theory arrangement in explaining
the partial convergence. But if the
extreme situation were present, in which each and every component of what seems
to be a unified experience were associated with the activity of a different
neuron, then the single-neuron theory proposed here would be rendered
trivial. Instead, Dennett's approach to
explaining consciousness would suffice.
What is needed to resolve this issue is a
better understanding of the process of introspection, the principal source of
our intuition that perceptual unity is real.
The nature of introspection is also relevant for addressing the question
of how similar the conscious experiences of the PFC neurons have to be to one
another for the single-neuron theory to be plausible. It may be that the single neurons themselves lack self-awareness
and base their identity solely on the feedback they receive pertaining to the
neuronal population as a whole. If that
were the case, then a large variance in the conscious experiences of the PFC
neurons might be compatible with a stable single-neuron model. Until a comprehensive theory of
introspection is available, however, deciding whether this is or is not the
case will have to remain a matter of conjecture.
Empirical Predictions: There are a number of testable predictions
made by the single-neuron theory, the presence of which serves to distinguish
it from the competing network theories of consciousness. At the macroscopic level, there is the
question of whether lesions confined to the entirety of the left lateral PFC
destroy VR-consciousness, and whether lesions confined to the entirety of
lateral PFC bilaterally destroy higher consciousness more generally. This is still an open question that needs
directed empirical investigation. At
the microscopic level, the single-neuron theory makes the testable anatomical
prediction that layer 5 pyramidal neurons will be found in the left lateral PFC
that are individually the recipients of convergent axonal input derived from
brain regions considered to be involved in the processing of the sensory,
mnemonic, and emotional stimuli that compose VR-conscious content. In addition, the theory makes the
electrophysiological prediction that left lateral PFC neurons will be found
that respond in single-cell recording experiments to combinations of sensory,
emotional, and mnemonic stimuli that typify VR-conscious experience. As noted above, direct single-cell
recordings have already identified neurons in lateral PFC that respond
selectively to conjoint visual and auditory stimuli (Aou et al. 1983), to
conjoint visual, auditory and tactile stimuli (Tanila et al. 1992), and to
conjoint object and location features (Rao et al. 1997). The question is whether lateral PFC neurons
exist that respond to conjoint input from the full complement of sensory,
emotional, and mnemonic stimuli that comprise VR-conscious experience. The demonstration of the existence of
neurons that are suitably convergent, both anatomically and electrophysiologically,
while expected with the single-neuron theory, would be difficult to justify
within the network NCC framework.
Alternatively, the failure to identify such neurons despite a concerted
effort to do so would militate against the single-neuron theory and favor the
network approach. Finally, there is the
prediction that subgroups of lateral PFC neurons will be found that share
similar spatially encoded dendritic inputs, and that the shape of those inputs
will be found to be a homotopic, information
preserving transform of the shape of neuronal activity at the population
level.
Speculative Implications: As so far presented, the single-neuron
theory does no more than shift the locus of the mind/brain interface from the neural
network to the single neuron level of information processing. It does not, by itself, offer any
fundamental advance in tackling the philosophical difficulties inherent in the
problem. That is, the theory as so far
presented does not take on the deeper questions of how and why individual
neurons are imbued with experience. It
might, though, be possible to extend the theory in a way that does address
these deeper questions. In particular,
since the mind/brain interface has been shifted to the level of the single
neuron, certain physical processes, such as those involving electromagnetic
fields or quantum mechanical phenomena, might be more plausibly invoked in
theories of mind/brain interaction since the need to explain how these
phenomena traverse synaptic
spaces can be avoided. Inclusion of
such phenomena in evolving mind/brain theories might, in turn, offer a degree
of flexibility that could allow such theories to address the deeper
philosophical issues.
As an example of how this might work, I
offer the following brief speculative sketch derived from Whitehead's
panpsychist approach to the hard problem of consciousness. According to Whitehead (1933), the basic
stuff of the universe is neither subjective experience nor objective matter but
neutral "occasions" (or "events") that appear as either
subjects or objects depending on one's observational perspective. Thus, the same event is a subject with
respect to the information it receives (that is, it "perceives" the
incoming information) but is an object with respect to the information it emits
(and which is subsequently "perceived" by other events). In Whitehead's view, mind/brain duality is
just a complex macroscopic instance of the perspectival duality that pervades
all of nature.
The difficulty with Whitehead's
formulation is that it lacks a convincing explanation of how simple
subject/object events combine to form complex subject/object entities such as
those embodied by human minds. Seager (1995)
has called this difficulty the "combination problem." Why do some configurations of matter (such
as human brains) appear to serve as complex but unified subject/object
entities, while others (such as rocks and thermostats) remain as mere aggregates
of elementary subject/object events?
Seager suggests that only the synthetic nature of quantum mechanics,
especially the phenomenon of quantum entanglement (in which spatially
distributed occurrences are joined into a single event at the moment of
reduction of the state vector), appears capable of resolving the combination
problem.
The possible involvement of quantum
mechanics in consciousness has been summarily dismissed by many authors because
the entanglement would, it is usually supposed, have to extend across
macroscopic distances and involve spatially dispersed neuronal
populations. The difficulties imposed
by such large distances, together with the lack of a plausible mechanism by
which entanglement might "jump" across synapses, has been argued to
render quantum mechanical theories of consciousness untenable (Grush and
Churchland 1995). With the
single-neuron theory, however, the proposed entanglement would need to extend
only throughout a portion of the dendritic tree of a single neuron. While still a formidable proposition, the speculation
that quantum mechanical effects might be relevant to consciousness might
nevertheless gain in plausibility.
The specific way that quantum
entanglement could be invoked to explain consciousness would be as
follows. Suppose that within a small
component of the dendritic tree of the neuron there were indivisible entangled
events whose topology were reflective of the spatial patterns of electrical
activity within larger portions of the dendritic tree. It might be possible that such entangled events
could individually be recipients of all the stimuli that go into conscious
experience and be complex enough to match the complexity of conscious
experience. If such entangled events
existed, then populations of them could conceivably summate their outputs and
affect the neuron's outgoing message in a manner analogous to that in which, on
the macroscopic level, populations of neurons are proposed to summate their
outputs and affect macroscopic behavior.
As has been noted by Bieberich, who has
articulated an argument similar to the one being offered here (Bieberich 2002),
entangled intraneuronal events could conceivably support a complexity of
information processing comparable to that attributable to the whole brain in
the neural network models. Such
entangled events could, in turn, act as indivisible Whiteheadean subject/object
entities with subjective aspects serving as units of conscious experience and
with objective aspects contributing to the information content of outgoing
electrochemical messages at the axon hillock.
In the final model, then, a single subjective experience would
correspond not to the activity of a single neuron but to the occurrence of a
single entangled event within a single neuron.
In a logical extension of the single-neuron theory, an individual's
brain would be construed as comprising a multiplicity of subjective experiences
corresponding not just to the multitude of neurons within that brain, but to
the larger number of entangled events within all those neurons. In sum, the combination problem would be
solved by avoiding altogether the need to combine the individual
consciousnesses.
This process would be assumed to be
occurring not only in the right and left lateral prefrontal cortical neurons
but in other neurons as well and even more generally throughout nature. That is, every quantum mechanical event in
the universe would be considered to manifest subjective/objective duality. What would elevate a given quantum event to
the status of a macroscopically observable conscious entity would be the manner
in which it was coupled with input and output.
Thus, quantum mechanical events found generally in nature might well act
as Whiteheadean subject/object entities but would have inputs and outputs
reflecting only their immediate ultramicroscopic environments. Events within the lateral PFC, in contrast,
would be connected with inputs and outputs attached to happenings in the
far-removed macroscopic world.
There are, of course, serious challenges
to this scheme, not the least of which is the need to demonstrate that there
exist quantum mechanically entangled events spatially dispersed enough to
invade at least several dendritic branches.
The assumptions are, however, empirically testable in principle. The quantum mechanical model is offered, in
any case, principally to illustrate how the transfer of the locus of mind/brain
interaction to the intraneuronal domain might bring into play physical
processes that might otherwise
be regarded as irrelevant.
6.
SUMMARY:
A model of mind/brain interaction has
been outlined that places the mind/brain interface at the level of single
neurons or even at the level of single quantum events within neurons. The scheme is built on the combined premise
that there are populations of neurons for which individual neurons in the
subgroup (1) receive all the types of inputs that characterize conscious
experience, (2) are sufficiently complex on the input side to match the
complexity of conscious experience, (3) produce complex output via interaction
of conscious and ambient electrical spatial patterns within their dendritic
trees, and (4) express that output in terms of the spatial pattern of their
joint activation at the population level.
It is not argued that this model is necessitated by the available data,
only that it is compatible with them.
The theory is built upon a
divergent/convergent feedforward model of information flow, both at the
macroscopic and microscopic levels. It
is hypothesized on the macroscopic level that the lateral PFC serves as a
region of convergence for all
the inputs that feed conscious experience.
On the microscopic level, a variation of the synfire chain model is employed, in which successive pools of
synchronously firing pyramidal neurons are hypothesized to exist that carry
information in their spatial arrangement.
The theory provides a possible mechanism by which the spatial
arrangement of synchronously firing pyramidal neurons can induce a corresponding
spatial pattern of intradendritic electrical activity in the multiple neurons
they target, and that the information contained in this pattern can be reexpressed by the spatial arrangement of a
synchronously firing subgroup of the targeted neurons. Amplification of selected synfire patterns may then occur in the context of
attention, possibly involving gamma frequency oscillating
cortico-thalamo-cortico loops.
Ultimately, further empirical investigation into the behavior of single
neurons will determine whether the model is valid. Toward this end, specific testable predictions have been
delineated, rendering the theory potentially falsifiable and therefore of a
legitimately scientific nature.
The idea that single neurons might be
individually conscious was originally considered by William James (1890) who
went on, however, to note that "the cell is no more a unit, materially
considered, than the total brain is a unit.
It is a compound of molecules, just as the brain is a compound of cells
and fibers. And the molecules,
according to the prevalent physical theories, are in turn compounds of
atoms." A single-neuron theory
would, then, still have to explain how the atoms of a neuron combine to form a
single consciousness. In response to
this issue, and to illustrate the way in which the transfer of mind/brain
interaction to the intraneuronal domain might facilitate the development of
models of mind/brain interaction, a speculative sketch has been offered that is
built upon Whitehead's panpsychist approach to the mind/brain problem. Specifically, it is postulated that entangled quantum mechanical events within
neurons might serve as indivisible Whiteheadean subject/object entities of
sufficient complexity and connectedness to allow them to individually mediate
the totality of conscious experience usually attributed to the brain as a
whole. The individual consciousnesses
attached to single events would, in this picture, not combine but would instead
remain independently conscious, thereby solving the combination problem by
avoiding it altogether. Such an
extension of the single-neuron theory would, admittedly, be highly speculative
but it would provide an example of how the theory might offer more than just an
alternative model of cerebral information processing and go the further step of
addressing the fundamental problem of mind/brain interaction itself.
ACKNOWLEDGMENTS:
I wish to thank Josef Ashkenazi, PhD,
Associate Professor of Physics, University of Miami, for his help in developing
the ideas pertaining to quantum mechanics.
I also wish to thank Mohammad Rahat, David Wilson, Robert Fujimora,
Mihai Preda, Gloria Peruyera, Nancy Tedone, David Chalmers, Todd Feinberg, and
Kenneth Heilman for their valuable comments and suggestions.
REFERENCES:
Abeles M, 1991:
Corticonics: Neural Circuits of the Cerebral Cortex. New York:
Cambridge
University Press.
Abeles M,
2004: Time is precious. Science 304:523-524.
Adrian ED,
1926: J Physiol 61:47.
Aertsen A,
Diesmann M, Gewaltig MO, 1996: Propagation of synchronous spiking activity in
feedforward neural networks. J Physiol Paris 90:243-247.
Agmon-Snir
H, Carr CE, Rinzel J, 1998: The role of dendrites in auditory coincidence
detection. Nature 393:268-272.
Alexander
GE, Delong MR, Strick PL, 1986: Parallel organization of functionally
segregated circuits linking basal ganglia and cortex. Annu Rev Neurosci
9:357-381.
Alexander
DM, Bourke PD, Sheridan P, Konstandatos O, Wright JJ, 2004: Intrinsic
connections in tree shrew V1 imply a global to local mapping. Vision Research
44:857-876.
Alexander MP, Stuss DT, 2000: Disorders of frontal lobe
functioning. Seminars in Neurology 20:427-437.
Amaral DG,
Price JL, 1984: Amydalo-cortical projections in the monkey (Macaca
fascicularis). J Comp Neurol 230:465-496.
Anderson
JC, Binzegger T, Kahana O, Martin KAC, Segev I, 1999: Dendritic asymmetry
cannot account for directional responses of neurons in visual cortex. Nature
Neuroscience 2:820-824.
Aou S,
Oomura Y, Hishino H, Ono T, Yambe K, Sikdar SK, Noda T, Inoue M, 1983:
Functional heterogeneity of single neuronal activity in the monkey dorsolateral
prefrontal cortex. Brain Res 260:121-124.
Arnoldi
HM, Brauer W, 1996: Synchronization without oscillatory neurons. Biol Cybern
74:209-223.
Arnoldi HM,
Englmeier KH, Brauer W, 1999: Translation-invariant pattern recognition based
on Synfire chains. Biol Cybern 80:433-447.
Averbeck
BB, Lee D, 2004: Coding and transmission of information by neural ensembles.
Trends in Neurosciences 4:225-230.
Aviel Y,
Pavlov E, Abeles M, Horn D, 2002: Synfire chain in a balanced network.
Neurocomputing 44-46:285-292.
Baars BJ, 1988: A Cognitive Theory of Consciousness, Cambridge University
Press.
Baars BJ, Franklin S, 2003: How conscious experience and working memory
interact. Trends in Cognitive Sciences 7:166-172.
Baddeley A, 2003: Working memory: looking back and looking forward.
Nature Reviews Neuroscience 4:829-839.
Baleydier
C, Mauguiere F, 1980: The duality of the cingulated gyrus in monkey.
Neuroanatomical study and functional hypothesis. Brain 103:525-554.
Barbas H,
1986: Pattern in the laminar origin of corticocortical connections. J Comp
Neurol 252:415-422.
Barbas H,
De Olmos J, 1990: Projections from the amygdala to basoventral and mediodorsal
prefrontal regions in the rhesus monkey. J Comp Neurol 300:549-571.
Barbas H,
Hilgetag CC, 2002: Rules relating connections to cortical structure in primate
prefrontal cortex. Neurocomputing 44-46:301-308.
Barbas H,
Pandya DN, 1989: Architecture and intrinsic connections of the prefrontal
cortex in the rhesus monkey. J Comp Neurol 286:353-375.
Barbas H,
Rempel-Clower N, 1997: Cortical structure predicts the pattern of
corticocortical connections. Cerebral Cortex 7:635-646.
Barlow HB,
1972: Single units and sensation: a neuron doctrine for perceptual psychology?
Perception 1:371-394.
Bates JF,
Goldman-Rakic PS, 1993: Prefrontal connections of medial motor areas in the
rhesus monkey. J Comp Neurol 336:211-228.
Baylis LL,
Rolls ET, Baylis GC, 1995: Afferent connections of the caudolateral
orbitofrontal cortex taste area of the primate. Neuroscience 64:801-812.
Bayne T,
Chalmers DJ, 2003: What is the unity of consciousness? In: Cleeremans A (ed), The
Unity of Consciousness: Binding, Integration, Dissociation. Oxford University
Press: New York.
Bieberich
E, 2002: Recurrent fractal neural networks: a strategy for the exchange of
local and global information processing in the brain. BioSystems 66:145-164.
Binzegger
T, Douglas RJ, Martin KAC, 2005: Axons in cat visual cortex are topologically
self-similar. Cerebral Cortex 15:152-165.
Bialek W,
Rieke F, de Ruyter van Steveninck RR, Warland D, 1991: Reading a neural code.
Science 252: 1854-1857.
Bogen JE,
1995: On the neurophysiology of consciousness: Part II. Constraining the
semantic problem. Consciousness and Cognition 4:137-158.
Borst A,
Theunissen FE, 1999: Information theory and neural coding. Nature Neuroscience
2: 947-957.
Braver TS,
Barch DM, Kelley WM, Buckner RL, Cohen NJ, Miezin FM, Snyder AZ, Ollinger JM,
Akbudak E, Conturo TE, Petersen SE, 2001: Direct comparison of prefrontal
cortex regions engaged by working and long-term memory tasks. Neuroimage
14:48-59.
Briggs F,
Callaway EM, 2005: Laminar patterns of local excitatory input to layer 5
neurons in macaque primary visual cortex. Cerebral Cortex 15:479-488.
Broca P,
1861: Perte de la parole, remollissement chronique et destruction partielle du
lobe anterieur gauche du cerveau. Bull Soc Anthropol 2:235-238.
Bruce C,
Desimone R, Gross CG, 1981: Visual properties of neurons in a polysensory area
in superior temporal sulcus of the macaque. J Neurophysiol 46:369-384.
Bush G,
Luu P, Posner MI, 2000: Cognitive and emotional influences in anterior
cingulated cortex. Trends in Cognitive Science 4:215-222.
Campbell SR, Wang DL, Jayaprakash C, 1999: Synchrony and
desynchrony in integrate-and-fire oscillators. Neural Comput 11:1595-1619.
Cannon RC, Wheal HV, Turner DA, 1999: Dendrites of classes of
hippocampal neurons differ in structural complexity and branching patterns.
Journal of Comparative Neurology 413:619-633.
Cash S,
Yuste R, 1999: Linear summation of excitatory inputs by CA1 pyramidal neurons.
Neuron 22:383-394.
Chalmers D,
1996: The Conscious Mind. New York: Oxford University Press.
Chavis DA,
Pandya DN, 1976: Further observations on cortico-frontal connections in the
rhesus monkey. Brain Res 117:369-386.
Cohen JD,
Perlstein WM, Braver TS, Nystrom LE, Noll DC
Conde F,
Lund JS, Lewis DA, 1996: The hierarchical development of monkey visual cortical
regions as revealed by the maturation of parvalbumin-immunoreactive neurons.
Developmental Brain Research 96:261-276.
Constantinidis
C, Franowicz, Goldman-Rakic PS, 2001: Coding specificity in cortical
microcircuits: a multiple-electrode analysis of primate prefrontal cortex. The
Journal of Neuroscience 21:3646-3655.
Constantinidis
C, Goldman-Rakic PS, 2002: Correlated discharges among putative pyramidal
neurons and interneurons in the primate prefrontal cortex. J Neurophysiol
88:3487-3497.
Crick F,
Koch C, 1990a: Towards a neurobiological theory of consciousness. Seminars in
Neuroscience 2:263-275.
Crick F,
Koch C, 1990b: Some reflections on visual awareness. Cold Spring Harbor Symp
Quant Biol 55:953-962.
Crick F,
1994: The Astonishing Hypothesis. Simon and Schuster: New York.
Crick F,
Koch C, 1998: Consciousness and Neuroscience. Cerebral Cortex 8:97-107.
Dahaene S,
Kerszberg M, Changeux JP, 1998: A neuronal model of a global workspace in
effortful cognitive tasks. PNAS 95:14529-14534.
Damasio
AR, 1998: Investigating the biology of consciousness. Phil Trans R Soc Lond B
353:1879-1882.
Damasio
AR, 1999: The Feeling of What Happens. Harcourt Brace and Company: New York.
Dandy WE,
1946: The location of the conscious center in the brain – the corpus striatum.
Bull Johns Hopkins Hosp 79:34-58.
Dantzker
JI, Callaway EM, 2000: Laminar sources of synaptic input to cortical inhibitory
interneurons and pyramidal neurons. Nature Neuroscience 3:701-707.
Deacon TW,
1992: Cortical connections of the inferior arcuate sulcus cortex in the macaque
brain. Brain Research 573:8-26.
Dehaene S,
Kerszberg M, Changeux JP, 1998: A neuronal model of a global workspace in
effortful cognitive tasks. Proc Nat Acad Sci 95:14529-14534.
Dennett
DC, 1991: Consciousness Explained. Boston: Little, Brown and Company.
D'Esposito
M, Aguirre GK, Zarahn E, Ballard D, Shin RK, Lease J, 1998: Functional MRI
studies of spatial and nonspatial working memory. Cognitive Brain Research
7:1-13.
Diesmann
M, Gewaltig MO, Aertsen A, 1999: Stable propagation of synchronous spiking in
cortical neural networks. Nature 402:529-533.
Douglas
RF, Martin KAC, 2004: Neuronal circuits of the neocortex. Annu Rev Neurosci
27:419-451.
Durstewitz
D, Seamans JK, Sejnowski TJ, 2000: Neurocomputational models of working memory.
Nature Neuroscience Suppl 3: 1184-1191.
Edelman
GM, 1993: Neural darwinism - selection and reentrant signaling in higher
brain-function. Neuron 10:115-125.
Edelman GM
and Tononi G, 2000: A Universe of Consciousness: How Matter Becomes
Imagination. New York: Basic Books.
Edwards
JCW, 2005: Is consciousness only a property of individual cells? J Cons Studies
(in press).
Elston GN,
2003: Cortex, cognition and the cell: new insights into the pyramidal neuron
and prefrontal function. Cerebral Cortex 13:1124-1138.
Engel AK,
Fries P, Konig P, Brecht M, Singer W, 1999: Temporal binding, binocular
rivalry, and consciousness. Consciousness and Cognition 8:128-151.
Eslinger
PJ, Damasio AR, 1985: Severe disturbance of higher cognition after bilateral
frontal lobe ablation: patient EVR. Neurology 35:1731-1741.
Felleman
DJ, Van Essen DC, 1991: Distributed hierarchical processing in primate cerebral
cortex. Cerebral Cortex 1:1-47.
Fletcher
PC, Henson RNA, 2001: Frontal lobes and human memory: insights from functional
neuroimaging. Brain 124:849-881.
Fries P, Reynolds
JH, Rorie AE, DesimoneR, 2001: Modulation of oscillatory neuronal
synchronization by selective visual attention. Science 291:1560-1563
Foxe JJ,
Simpson GV, 2002: Flow of activation from V1 to frontal cortex in humans. A
framework for defining "early" visual processing. Exp Brain Res
142:139-150.
Frick A, Magee J, Johnston D, 2004: LTP is accompanied by an enhanced
local excitability of pyramidal neuron dendrites. Nat Neurosci 7:126-35
Froemke
RC, Pou MM, Dan Y, 2005: Spike-timing-dependent synaptic plasticity depends on
dendritic location. Nature 43:221-225.
Funahashi
S, Inoue M, 2000: Neuronal interactions related to working memory processes in
the primate prefrontal cortex revealed by cross-correlation analysis. Cerebral
Cortex 10:533-551.
Fuster JM, 1998: Linkage at the top. Neuron 21:1223-1229.
Fuster JM,
1999: Memory in the cerebral cortex. MIT Press: Cambridge.
Fuster JM,
Alexander GE, 1971: Neuron activity related to short-term memory. Science
173:652-654.
Geschwind
N, 1981: The perverseness of the right hemisphere. The Behavioral and Brain
Sciences 4:106-107.
Gewaltig
MO, Diesmann M, Aertsen S, 2001: Propagation of cortical synfire activity:
survival probability in single trials and stability in the mean. Neural
Networks 14:657-673.
Gilbert
CD, 1998: Adult cortical dynamics. Physiological Reviews 78:467-485.
Gilbert
CD, Wiesel TN, 1986: Intrinsic connectivity and receptive field properties in
visual cortex. Vision Res 25:365-374.
Gold I,
1999: Does 40-Hz oscillation play a role in visual consciousness? Consciousness
and Cognition 8:186-195.
Golding
NL, Kath WL, Spruston N, 2001: Dichotomy of action-potential backpropagation in
CA1 pyramidal neuron dendrites. J Neurophysiol 10:2998-3010.
Goldman PS,
Nauta WJ, 1976: Autoradiographic demonstration of a projection from prefrontal
association cortex to the superior colliculus in the rhesus monkey. Brain Res
116:145-149.
Goldman-Rakic
PS, 1992: Working memory and the mind. Scientific American September.
Goldman-Rakic
PS, Schwartz ML, 1982: Interdigitation of contralateral and ipsilateral
columnar projections to frontal association cortex in primates. Science
216:755-757.
Goldman-Rakic
PS, Selemon LD, Schwartz ML, 1984: Dual pathways connecting the dorsolateral
prefrontal cortex with the hippocampal formation and parahippocampal cortex in
the rhesus monkey. Neuroscience 12:719-743.
Gonzalez-Burgos
G, Barrionuevo G, Lewis DA, 2000: Horizontal synaptic connections in monkey
prefrontal cortex: an in vitro electrophysiological study. 10:82-92.
Goodale
MA, Milner AD, 1992: Separate visual pathways for perception and action. Trends
Neurosci 15:20-25.
Grammont
F, Riehle A, 2003: Spike synchronization and firing rate in a population of
motor cortical neurons in relation to movement direction and reaction time.
Biological Cybernetics 88:360-373.
Gray CM,
1999: The temporal correlation hypothesis of visual feature interaction: still
alive and well. Neuron 24:31-47.
Gray JR,
Braver TS, Raichle ME, 2002: Integration of emotion and cognition in the
lateral prefrontal cortex. PNAS 99:4115-4120.
Grossberg
S, Mingolla E, Pack C, 1999: A neural model of motion processing and visual
navigation by cortical area MST. Cerebral Cortex 9:878-895.
Grush R,
Churchland PS, 1995: Gaps in Penrose's toilings. J of Consciousness Studies
2:10-29.
Hardcastle
V, 1994: Psychology's binding problem and possible neurobiological solutions. J
of Consciousness Studies 1:66-90.
Hardcastle
V, 1997: Consciousness and the neurobiology of perceptual binding. Seminars in
Neurology 17:163-170.
Hausser M,
2001: Synaptic function: dendritic democracy. Curr Biol 11:R10-R12.
Hausser M,
Major G, Stuart GJ, 2001: Differential shunting of EPSPs by action potentials.
Science 291:138-141.
Hausser M,
Mel B, 2003: Dendrites: bug or feature? Current Opinions in Neurobiology
13:372-383.
Heilman
KM. and Valenstein EV, 1993: Clinical Neuropsychology. New York: Oxford
University Press.
Helmchen
F, Svoboda K, Denk W, Tank DW, 1999: In vivo dendritic calcium dynamics in
deep-layer cortical pyramidal neurons. Nature Neuroscience 2:989-996.
Hertz J,
Prugel-Bennett A, 1996: Learning synfire chains: turning noise into signal. Int
J Neural Syst 7:445-450
Hoffman
DA, Magee JC, Colbert CM, Johnston D: Potassium channel regulation of signal
propagation in dendrites of hippocampal pyramidal neurons. Nature 38:869-875.
Hopfield
JJ, 1982: Neural networks and physical systems with emergent collective
computational abilities. PNAS 79:2554-2558.
Hopfield
JJ, Herz AVM, 1995: Rapid local synchronization of action potentials: toward
computation with coupled integrate-and-fire neurons. PNAS 92:6655-6662.
Hubel DH,
Wiesel TN, 1962: Receptive fields, binocular interaction and functional
architecture in the cat’s visual cortex. J Physiol (Lond) 160:106-154.
Hubel DH,
Wiesel TN, 1965: Receptive fields and functional architecture in two
non-striate areas (18 and 19) of the cat. J Neurophysiol 28:229-289.
Ikegaya Y,
Aarn G, Cossart R, Aronov D, Lampl I, Ferster D, Yuste R: Synfire chains and
cortical songs: temporal modules of cortical activity. Science 304:559-564.
Inui K,
Wang X, Tamura Y, Kaneoke Y, Kakigi R, 2004: Serial processing in the human
somatosensory system. Cerebral Cortex 14:851-857.
Ishai A,
Ungerleider LG, Haxby JV, 2000: Distributed neural systems for the generation
of visual images. Neuron 28:979-990.
Izhikevich
EM, Gally JA, Edelman GM, 2004: Spike-timing dynamics of neuronal groups.
Cerebral Cortex 14:933-944.
Jacobs GA,
Theunissen FE, 2000: Extraction of sensory parameters from a neural map by
primary sensory interneurons. The Journal of neuroscience 20:2934-2943.
James W,
1890: Principles of Psychology. Cambridge: Harvard University Press.
John ER, 2001:
A field theory of consciousness. Consciousness and Cognition 10:184-213.
Johnson
DMG, Illig KR, Behan M, Haberty LB, 2000: New features of connectivity in
piriform cortex visualized by intracellular injection of pyramidal cells
suggest that "primary" olfactory cortex functions like
"association" cortex in other sensory systems. The Journal of
Neuroscience 20:6974-6982.
Jones EG,
2002: Thalamic circuitry and thalamocortical synchrony. Phil Trans R Soc Lond B
357:1659-1673.
Jones EG,
Powell TPS, 1970: An anatomical study of converging sensory pathways within the
cerebral cortex of the monkey. Brain 93:793-820.
Koch C,
1999: Biophysics of Computation: Information Processing in Singe Neurons,
Oxford University Press: Oxford.
Koch C,
1997: Computation and the single neuron. Nature 385:207-210.
Kjaer TW,
Nowak M, Kjaer KW, Lou AR, Lou HC, 2001: Precuneus-prefrontal activity during
awareness of visual verbal stimuli. Consciousness and Cognition 10:356-365.
Konig P, Engel AK, Roelfsema PR, Singer W, 1995: How precise
is neural synchronization? Neural Computation 7:469-485.
Kritzer
MF, Goldman-Rakic PS, 1995: Intrinsic circuit organization of the major layers
and sublayers of the dorsolateral prefrontal cortex in the rhesus monkey. J
Comp Neurol 359:131-143.
Kubota K,
Niki H, 1971: Prefrontal cortical unit activity and delayed alternation
performance in monkeys. J Neurophysiol 34:337-347.
Kuypers
HGJM, Szwarcbart MK, Mishkin M, 1965: Occipitotemporal cortico-cortical
connections in the rhesus monkey. Expl
Neurol 11:245.
Lamme VAF,
Roelfsema PR, 2000: The distinct modes of vision offered by feedforward and
recurrent processing. Trends in Neurosciences 23:571-579.
Larkum ME,
Zhu JJ, Sakmann B, 1999a: A new cellular mechanism for coupling inputs arriving
at different cortical layers. Nature 398:338-341.
Larkum
ME, Kaiser KMM, Sakmann B, 1999b: Calcium electrogenesis in distal apical dendrites of layer 5
pyramidal cells at a critical frequency of back-propagating action potentials. Proc Natl Acad Sci USA 96:14600–14604.
Larkum ME, Zhu JJ, Sakmann
B, 2001: Dendritic mechanisms underlying the coupling of the dendritic with the
axonal action potential initiation zone of adult rat layer 5 pyramidal neurons.
J Physiol 2001, 533:447-466.
Larkum ME,
Senn W, Luscher HR, 2004: Top-down dendritic input increases the gain of layer
5 pyramidal neurons. Cerebral Cortex 14:1059-1070.
Larkum ME, Zhu JJ, 2002:
Signaling of layer 1 and whisker-evoked Ca2+ and Na+
action potentials in distal and terminal dendrites of rat neocortical pyramidal
neurons in vitro and in vivo. J Neurosci 22:6991-7005.
Lachaux
JP, Rodriguez E, Martinerie J, Varela FJ, 1999: Measuring phase synchrony in
brain signals. Hum Brain Mapp 8:194-208.
Laureys S,
Lemaire C, Maquet P, 1999: Cerebral metabolism during vegetative state and
after recovery to consciousness. J Neurol Neurosurg Psychiatry 67:121-133.
Laureys S,
2004: Functional neuroimaging in the vegetative state. NeuroRehabilitation
19:335-341.
Livingstone
MS, 1998: Mechanisms of direction selectivity in macaque V1. Neuron 20:509-526.
Llinas R,
Ribary U, Contreras D, Pedroarena C, 1998: The neuronal basis for
consciousness. Phil Trans R Soc Lond B 353:1841-1849.
Lu MT,
Preston JB, Strick PL, 1994: Interconnections between the prefrontal cortex and
the premotor areas in the frontal lobe. J Comp Neurol 341:375-392.
Lubke J,
Markram H, Frotscher M, Salmann B, 1996: Frequency and dendritic distribution
of autapses established by layer 5 pyramidal neurons in the developing rat
neocortex: comparison with synaptic innervation of adjacent neurons of the same
class. J Neurosci 10:3209-3218.
Lumer ED,
Edelman GM, Tononi G, 1997: Neural dynamics in a model of the thalamocortical
system. II. The role of neural synchrony tested through perturbations of spike
timing. Cereb Cortex 7:228-236.
MacGregor
RJ, Ascarrunz FG, Kisley MA, 1995: Characterization, scaling, and partial
representation of neural junctions and coordinated firing patterns by dynamic
similarity. Biol Cybern 73:155-166.
Magee JC,
2000: Dendritic integration of excitatory synaptic input. Nature Reviews
Neuroscience 1:181-190.
Magee
JC, 1999: Dendritic Ih normalizes temporal summation in hippocampal
CA1 neurons. Nat Neurosci 2:508-514
Magee JC, Cook
EP, 2000: Somatic EPSP amplitude is independent of synapse location in
hippocampal pyramidal neurons. Nature Neuroscience 3:895-903.
Mainen ZF,
Sejnowski TJ, 1996: Influence of dendritic structure on firing pattern inn
model neocortical neurons. Nature 382:363-366.
Marsalek
P, Koch C, Maunsell J, 1997: On the relationship between synaptic input and
spike output jitter in individual neurons. PNAS 94:735-740.
Maunsell
JHR, Van Essen DC: The connections of the middle temporal visual area (MT) and
their relationship to a cortical hierarchy in the macaque monkey. The Journal
of Neuroscience 2563-2586.
McCullough
W, Pitts W, 1943: A logical calculus of the ideas immanent in nervous activity.
Bull Math Biophys 5:115-133.
McIntosh
AR, Rajah MN, Lobaugh NJ, 1999: Interactions of prefrontal cortex in relation
to awareness in sensory learning. Science 284:1531-1533.
Melchitzky
DS, Gonzalez-Burgos G, Barrionuevo G, Lewis DA, 2001: Synaptic targets of the
intrinsic axon collaterals of supragranular pyramidal neurons in monkey
prefrontal cortex. J Comp Neurol 430:209-221.
Miller R,
1996: Cortico-thalamic interplay and the security of operation of neural
assemblies and temporal chains in the cerebral cortex. Biol Cybern 75:263-275.
Miller EK,
Cohen JD, 2001: An integrative theory of prefrontal cortex function. Annu Rev
Neurosci 24:167-202.
Milner AD,
Goodale MA, 1995: The Visual Brain in Action. Oxford University Press: Oxford.
Milner AD
Goodale MA, 1993: Visual pathways to perception and action. Prog Brain Res
95:317-337.
Mitchell
BD, Cauller LJ, 2001: Corticocortical and thalamocortical projections to layer
1 of the frontal neocortex in rats. Brain Res 921:68-77.
Mitchell
BD, Macklis JD, 2005: Large-scale maintenance of dual projections by callosal
and frontal cortical projection neurons in adult mice. J Comp Neurol 482:17-32.
Neltner L,
Hansel D, Mato G, Meunier C, 2000: Synchrony in heterogeneous networks of
spiking neurons. Neural Comput 12:1607-1641.
Niebur E, Hsiao
SS, Johnson KO, 2002: Synchrony: a neuronal mechanism for attentional
selection? Current Opinions in Neurobiology 12:190-194.
Niebur E,
Koch C, 1994: A model for the neuronal implementation of selective visual
attention based on temporal correlation among neurons. J Comput Neurosci
1:141-158.
Niebur E,
Koch C, Rosin C, 1993: An oscillation-based model for the neural basis of
attention. Vision Res 33:2789-2802.
Nirenberg
S, Latham PE, 2003: Decoding neuronal spike trains: How important are correlations?
PNAS 100:7348-7353.
Nowotny T,
Huerta R, 2003: Explaining synchrony in feed-forward networks: are
McCulloch-Pitts neurons good enough? Biol Cybern 89:237-241.
Oliveri M,
Purriziani P, Carlesimo GA, Koch G, Tomaiuolo F, Panella M, Caltagirone C, 2001:
Parieto-frontal interactions in visual-object and visual-spatial working
memory: evidence from transcranial magnetic stimulation. Cerebral Cortex
11:606-618.
Orpwood
RD, 1994: A possible neural mechanism underlying consciousness based on the
pattern processing capabilities of pyramidal neurons in the cerebral cortex. J
Theor Biol 169:403-418.
Pandya DN,
Kuypers HG, 1969: Cortico-cortical connections in the rhesus monkey. Brain
Research 13:13-48.
Pandya DN,
Yeterian EH, 1990: Prefrontal cortex in relation to other cortical areas in
rhesus monkey - architecture and connections. Prog Brain Res 85:63-94.
Parvizi J,
Damasio A, 2001: Consciousness and the brainstem. Cognition 49:135-159.
Petrides
M, Pandya DN, 1984: projections to the frontal cortex from the posterior
parietal region in the rhesus monkey. J Comp Neurol 228:106-116.
Petrides
M, Pandya DN, 1999: Dorsolateral prefrontal cortex: comparative
cytoarchitectonic analysis in the human and the macaque brain and corticocortical connection
pattern. Eur J Neurosci 11:1011-1036.
Phan KL,
Wager T, Taylor SF, Liberzon I, 2002: Functional neuroanatomy of emotion: a
meta-analysis of emotion activation studies in PET and fMRI. Neuroimage
16:331-348.
Pinsky PF,
Rinzel J, 1995: Synchrony measures for biological neural networks. Biol Cybern
73:129-137.
Poirzai P,
BrannonT, Mel BW, 2003: Pyramidal neuron as two-layer neural network. Neuron
37:989-999.
Polsky A,
Mel BW, Schiller J, 2004: Computational subunits in thins dendrites of pyramidal
cells. Nature Neuroscience 7:621-627.
Porrino
LJ, Crane AM, Goldman-Rakic PS, 1981: Direct and indirect pathways from the
amygdala to the frontal lobe in rhesus monkeys. J Comp Neurol 198:121-136.
Porter R,
Ghosh S, Lange GD, Smith TG, 1991: A fractal analysis of pyramidal neurons in
mammalian motor cortex. Neuroscience letters 130:112-116.
Postma EO,
van den Herik HJ, Hudson PT, 2996: Robust feedforward processing in synfire
chains. Int J Neural Syst 7:537-542.
Pouget A,
Latham P, 2002: Digitalized neural networks:
long-term stability from forgetful neurons. Nature Neuroscience
5:709-710.
Prut Y,
Vaadia E, Bergman H, Haalman I, Slovin H, Abeles M, 1998: Spatiotemporal
structure of cortical activity: properties and behavioral relevance. J Neurophysiol
79:2857-2874.
Puccetti
R, 1973: Brain bisection and personal identity. British Journal of Philosophy
of Science 24:339-355.
Raichle
ME, 2000: The neural correlates of consciousness: an analysis of cognitive
skill learning. In Gazzaniga MS: The New Cognitive Neurosciences, Second
Edition, MIT Press: Cambridge.
Rainer G,
Asaad WF, Miller EK, 1998: Memory fields of neurons in the primate prefrontal
cortex. PNAS 95:15008-15013.
Rainer G,
Rao SC, Miller EK, 1999: Prospective coding for objects in the primate
prefrontal cortex. J Neurosci 19:5493-5505.
Rall W,
1959: Branching dendritic trees and motoneuron membrane resistivity. Exp
Neurol 1:491-527.
Rall W,
1967: Distinguishing theoretical synaptic potentials computed for different
soma-dendritic distributions of synaptic input. Journal of Neurophysiology
30:1138-1168.
Rammont F,
Riehle A, 2003: Spike synchronization and firing rate in a population of motor
cortical neurons in relation to movement direction and reaction time. Biol
Cybernetics 88:30-373.
Rao SC,
Rainer G, Miller EK, 1997: Integration of what and where in the primate
prefrontal cortex. Science 276:821-824.
Rempel-Clower
NL, Barbas H, 2000: The laminar pattern of connections between prefrontal and anterior
temporal cortices in the rhesus monkey is related to cortical structure and
function. Cerebral Cortex 10:851-865.
Revonsuo
A, 1999: Binding and the phenomenal unity of consciousness. Consciousness and
Cognition 8:178-185.
Reyes AD,
2003: Synchrony-dependent propagation of firing rate in iteratively constructed
networks in vitro. Nature Neurosci 6: 593-599.
Reynolds
JH, Desimone R, 1999: The role of neural mechanisms of attention in solving the
binding problem Neuron 24:19-29.
Robertson
LC, 2003: Binding, spatial attention and perceptual awareness. Nature Reviews
Neuroscience 4:93-102.
Rockland
KS, Pandya DN, 1979: Laminar origins and terminations of cortical connections
of the occipital lobe in the rhesus monkey. Brain Research 179:3-20.
Rolls ET, France L, Aggelopoulos NC, Reece S, 2003: An information
theoretic approach to the contributions of the firing rates and the
correlations between the firing of neurons. J Neurophysiol 89:2810-2822.
Romo R, Brody CD, Hernandez A, Lemus L, 1999: Neuronal correlates
of parametric working memory in the prefrontal cortex. Nature 399:470-473.
Rudd ME, Brown LG, 1997: Noise adaptation in integrate-and-fire
neurons. Neural Comput 9:1047-1069.
Sato M, Kuroda R, Ioku M, Kim A, Tanaka S, Nakakita K, Kohama A, Fugii
C, Ono S, 1989: Regional cerebral blood flow in the resistant vegetative state.
Neurol Med Chir 29:389-394.
Sauve K, 1999: Gamma-band synchronous oscillations: recent
evidence regarding their functional significance. Consciousness and Cognition
8:213-224.
Schaefer
AT, Larkum ME, Sakmann B, Roth A, 2003: Coincidence detection in pyramidal neurons is tuned by
their dendritic branching pattern. J
Neurophysiol 89:3143–3154.
Schiller J, Helmchen F,
Sakmann B, 1997: Calcium action potentials restricted to distal apical
dendrites of rat neocortical pyramidal neurons. J Physiol 505:605-616.
Schiller J, Schiller Y,
Stuart G, Sakmann B, 1997: Calcium action potentials restricted to distal
apical dendrites of rat neocortical pyramidal neurons. J Physiol 505, 605–616.
Schmahmann
JD, Pandya DN, 1997: Anatomic organization of the basilar pontine projections
from prefrontal cortices in rhesus monkey. J Neurosci 17:438-458.
Schubert
D, Staiger JF, Cho N, Kotter R, Zilles K, Luhmann HJ, 2001: Layer-specific intracolumnar
and transcolumnar functional connectivity of layer V pyramidal cells in rat
barrel cortex. The Journal of Neuroscience 21:3580-3592.
Schuz A,
1998: Neuroanatomy in a computational perspective. In Arbib MA: Handbook of
Brain Theory and neural Networks. MIT
Press: Cambridge.
Schwartz
EL, 1980: Computational anatomy and functional architecture of striate cortex:
a spatial mapping approach to perceptual coding. Vision Research 20:645-669.
Schwindt P, Crill W, 1999:
Mechanisms underlying burst and regular spiking evoked by
dendritic depolarization in
layer 5 cortical pyramidal neurons. J
Neurophysiol 81:1341–1354.
Seltzer B, Pandya DN, 1989: Frontal lobe connections of the
superior temporal sulcus in rhesus monkey. J Comp Neurol 281:97-1113.
Shadlen MN, Newsome WT, 1994: Noise, neural codes and cortical
organization. Curr Opin Neurobiol 4:569-579.
Shadlen MN, Newsome WT, 1998: The variable discharge of cortical
neurons: implications for connectivity, computation, and information coding. J
Neurosci 18:3870-3896.
Shadlen MN, Movshon JA, 1999: Synchrony unbound: a critical
evaluation of the temporal binding hypothesis. Neuron 24:67-77.
Seager W,
1995: Consciousness, information and panpsychism. Journal of Consciousness
Studies 2:272-288.
Segev I,
London M, 2000: Untangling dendrites with quantitative models. Science
290:744-750.
Segev I,
2003: Synchrony is stubborn in feedforward cortical networks. Nature Neurosci
6:543-544.
Sewards
TV, Sewards MA, 2001: On the correlation between synchronized oscillatory
activities and consciousness. Consciousness and Cognition 10:485-495.
Singer W,
1998: Consciousness and the structure of neuronal representations. Phil Trans R
Soc Lond B 353:1829-1840.
Singer W, 2001:
Consciousness and the binding problem. Ann NY Acad Sci 929:123-146.
Singer W,
Gray CM, 1995: Visual feature integration and the temporal correlation
hypothesis. Annu Rev Neurosci 18:555-586.
Slotnick
SD, Moo LR, Segal JB, Hart J, 1969: Distinct prefrontal cortex activity
associated with item memory and source memory for visual shapes. Cognitive
Brain Research 17:75-82.
Softky WR,
Koch C, 1993: The highly irregular firing of cortical cells is inconsistent
with temporal integration of random EPSPs. The Journal of Neuroscience
13:334-350.
Sougné JP, French RM, 2001: Synfire chains and catastrophic
interference. In JD Moore and K Stenning (Eds.) Proceedings of the Twenty-Third Annual Conference of the Cognitive
Science Society. Pp. 970-975. Mahwah,NJ: Lawrence Erbaum Ass.
Sperry RW,
1969: A modified concept of consciousness. Psychological Reviews 26:532-536.
Spratling
MW, 2002: Cortical region interactions and the functional role of apical
dendrites. Behavioral and Cognitive Neuroscience Reviews 1:219-228.
Spruston
N, Schiller Y, Stuart G, Sakmann B, 1995: Activity-dependent action potential
invasion and calcium influx into hippocampal CA1 dendrites. Science
286:297-300.
Spruston
N, 2000: Distant synapses raise their voices. Nature Neuroscience 3:849-895.
Steinmetz
PN, Roy A, Fitzgerald PJ, Hsiao SS, Johnson KO, Niebur E, 2000: Attention
modulates synchronized neuronal firing in primate somatosensory cortex. Nature
404:187-190.
Stephan
KM, Thaut MH, Wunderlich G, Schicks W, Tian B, Tellmann L, Schmitz T, Herzog H,
McIntosh C, Seitz RJ, Homberg V, 2002: Conscious and subconscious sensorimotor
synchronization - prefrontal cortex and the influence of awareness. Neuroimage
15:345-352.
Stevens CF, Zador AM, 1998: Input synchrony and the irregular firing of
cortical neurons. Nature Neuroscience
1:210-217.
Stuart
GJ, Sakmann B, 1994: Active
propagation of somatic action potentials
into neocortical pyramidal
cell dendrites. Nature 367:69–72.
Tanila H, Carlson
S, Linnankoski I, Lindroos F, Kahila H, 1992: Functional properties of
dorsolateral prefrontal cortical neurons in awake monkey. Behav Brain Res
47:169-180.
Taylor JG,
2001: The central role of the parietal lobes in consciousness. Consciousness and
Cognition 10:379-417.
Thomson
AM, Bannister AP, 1998: Postsynaptic pyramidal target selection by descending
layer III pyramidal axons: dual
intracellular recordings and biocytin filling in slices of rat neocortex.
Neuroscience 3:669-683.
Thomson
AM, Bannister AP, Mercer A, Morris OT, 2002a: Target and temporal pattern
selection at neocortical synapses. Phil Trans R Soc Lond B 357:1781-1791.
Thomson
AM, West DC, Wang Y, Bannister AP, 2002b: Synaptic connections and small
circuits involving excitatory and inhibitory neurons in layers 22-5 of adult
rat and cat neocrotex: triple intracellular recordings and biocytin labelling
in vitro. Cerebral Cortex 12:936-953.
Thomson
AM, Bannister AP, 2003: Interlaminar connections in the neocortex. Cerebral
Cortex 13:5-17.
Thorpe S,
1998: Localized versus distributed
representations. In: Arbib MA: Handbook
of Brain Theory and Neural Networks. MIT Press: Boston.
Tulving E, 2002: Episodic memory: from mind to brain. Annu
Rev Psychol. 2002;53:1-25.
Ungerleider
LG, Mishkin M, 1982: Two cortical visual systems. In Analysis of Visual
Behavior, DJ Ingle, MA Goodale, RJW Mansfield, eds. (Cambridge, MA: MIT Press).
Usrey WM,
Reid RC, 1999: Synchronous activity in the visual system. Annu Rev Physiol
61:435-456.
Van Essen DC,
Gallant JL, 1994: Neural mechanisms and motion processing in primate visual
system. Neuron 13:1-10.
Van Ooyen
A, Duijnhouwer J, Remme MWH, van Pelt J, 2002: The effect of dendritic topology
on firing patterns in model neurons. Network Computation iin Neural Systems 13:
311-325.
Vetter P,
Roth A, Hausser M, 2001: Propagation of action potentials in dendrites depends
on dendritic morphology. J Neurophysiol 85:926-937.
Wei DS, Mei YA, Bagal A, Kao JP, Thompson SM,
Tang CM, 2001: Compartmentalized and binary behavior of terminal dendrites in
hippocampal pyramidal neurons. Science 293:2272-2275.
Weinberg
RJ, Pierce JP, Rustioni A, 1990: Single fiber studies of ascending input to the
cuneate nucleus of cats: I. Morphometry of primary afferent fibers. J Comp
Neurol 300:113-133.
Wheeler
MA, Stuss DT, Tulving E, 1995: Frontal lobe damage produces episodic memory
impairment. Journal of the International Neuropsychological Society 1:525-536.
Whitehead
AN, 1933: Adventures of Ideas. New York: The Free Press.
Williams
SR, Stuart GJ, 2000: Backpropagation of physiological spike trains. J Neurosci
20:8238-8246.
Williams
SR, Stuart GJ, 2002: Dependence of EPSP efficacy on synapse location in
neocortical pyramidal neurons. Science 295:1907-1910.
Wolfe JM,
Cave KR, 1999: The psychophysical evidence for a binding problem in human
vision. Neuron 24:11-17.
Yazdanbakhsh
A, Babadi B, Rouhani S, Arabzadeh E, Abbassian A, 2002: New attractor states for
synchronous activity in synfire chains with excitatory and inhibitory coupling.
Biol Cybern 86:367-378.
Zeki S,
Bartels A, 1999: Toward a theory of visual consciousness. Consciousness and
Cognition 8:225-259.
[1] The designation "left hemisphere" will be used to refer to the "dominant" or "language" hemisphere, located on the left side of the brain in most people.