Available abstracts/paper summaries for this Workshop's talks

Bernard J. Baars
Do Brain Rhythms Underlie Conscious and Unconscious Cognition?

David Edelman
Necessity and Sufficiency in the Emergence of Consciousness: When is a Complex Brain Complex Enough?

Stan Franklin
The LIDA model’s hypotheses on the cognitive cycle, high-level cognitive processes, and theta/alpha and gamma rhythms.

Wolfgang Klimesch
Alpha and theta oscillations: Conscious control of information processing in the human brain?

Lucia Melloni
Long-distance Synchronization of Neural Activity across Cortical Areas Correlates with Conscious Perception

Paul L. Nunez
Brain Rhythms, Anatomy and the Emergence of Consciousness: Why Hearts Don't Love and Brains Don't Pump.

Satu Palva
Brain Rhythms and the Global Workspace Theory

Lawrence M. Ward
Neural Synchrony in Attention and Consciousness


Do Brain Rhythms Underlie Conscious and Unconscious Cognition?

Bernard J. Baars

forthcoming ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Necessity and Sufficiency in the Emergence of Consciousness: When is a Complex Brain Complex Enough?

David Edelman

Over the past decade, there has been a growing interest in animal consciousness, particularly in regard to the possibility of conscious states in non-mammalian lineages. Yet a comprehensive review of animal cognitive neuroscience relevant to consciousness has not been forthcoming; nor has there been a serious experimental program undertaken to investigate animal consciousness substantively and systematically. Clearly, investigations of human consciousness can provide benchmarks in the design of such a program; specifically, certain properties of, and criteria for, consciousness can be extrapolated from the human case to those of non-human animals. Moreover, there is some neuroanatomical, neurophysiological, and behavioral evidence that at least suggests the possibility of awareness in some non-human species. But a fundamental question arises when considering the issue of consciousness in non-human species: precisely what kind of a brain is required for conscious experience? Specifically, how much central nervous system (CNS) (i.e., number of neural and non-neural cells), regional and cellular specialization, and inter- and intra-areal connectivity actually underlie the process of consciousness? At its heart, this is, of course, a question of neural complexity, the properties and measurement of which have recently become prominent points of departure in the scientific investigation of consciousness. So, to rephrase the question: what degree of neural complexity is both necessary and sufficient to yield conscious experience? We don’t really know, of course. However, recent computer simulations based on actual neurophysiological and neuroanatomical data do suggest that, in terms of numbers of neurons and the degree of connectivity between them, nervous systems with far fewer cells and less connectivity—by at least several orders of magnitude—than the typical mammalian CNS could exhibit spontaneously a number of functional properties previously associated with very large brains containing hyper-dense connectivity.

I will discuss the problem of animal consciousness in the context of findings in a variety of species, as well as with regard to recent computer simulations of aspects of the mammalian brain undertaken at the Neurosciences Institute. Data from the work I will summarize here suggest that, in the quest to identify consciousness in non-human species, we may have to cast our net a bit wider than previously imagined.


The LIDA model’s hypotheses on the cognitive cycle, high-level cognitive processes, and theta/alpha and gamma rhythms.

Stan Franklin

The LIDA conceptual and partially computational model of cognition is based on Global Workspace Theory and other theories from cognitive science and neuroscience. It hypothesizes that high-level cognitive processes such as deliberation and volitional decision making are composed of cascading sequences of cognitive cycles corresponding to action-perception cycles. Occurring at a rate of ~10 hz these cognitive sense-process-act cycles can be thought of as cognitive atoms or cognitive moments. The LIDA model further hypothesizes that theta/alpha rhythms are generated by passing cognitive cycles while the superimposed gamma rhythms reflect the internal activity of individual cognitive cycles. As the LIDA model is a broad, integrated model of cognition itself, it must be founded on the underlying neuroscience. We finally hypothesize that representations in LIDA correspond to basins of attraction in the non-linear dynamics of trajectories of activation patterns of cell assemblies. In this talk we will briefly describe the LIDA model, and expand upon these several hypotheses.


Alpha and theta oscillations: Conscious control of information processing in the human brain?

Wolfgang Klimesch
Division of Physiological Psychology, University of Salzburg

Understanding the emergence of spatially and temporally organized firing patterns in neural networks may provide important insights into mechanisms reflecting conscious control on human information processing. It is suggested that theta, and alpha oscillations in particular, play an important role for the temporal organization of neural activity during top-down control in two large processing systems. One system, associated with theta activity, is related to the processing of new information. Another system, associated with alpha activity, enables controlled access to already stored information, thereby providing us with the very basic ability to be ‘semantically’ oriented in continuously changing environments.

The functional-physiological significance of oscillations for the controlled timing of neural activity is seen in the fact that they reflect rhythmic changes in the (relative) level of depolarization in the (dendritic and somatic) membrane potentials of masses of neurons. Consequently, different phases of a single oscillatory cycle are related to phases of enhanced or suppressed neural firing. Rhythmic synchronization between neurons will have a strong impact on common target cells, because they will receive neural activity not only synchronously but also in predictable time windows.

A variety of empirical findings will be discussed that document the role of theta and alpha oscillations for the timing of cognitive processes in working memory, semantic memory and perceptual tasks (cf. the review by Klimesch et al. 2007a). As an example, it will be shown that alpha and theta phase coherence increases between task relevant sites and that phase lag lies within a time range that is consistent with neuronal transmission speed (cf. e.g., Nunez, 2000). Another important aspect is that phase reset will be a powerful mechanism for the event-related timing of cortical processes (Klimesch et al. 2007b) and empirical evidence suggests that the extent of phase locking is a functionally sensitive measure that is related to cognitive performance (for a review cf. Klimesch et al. 2007c).

For the functional-cognitive understanding of EEG-oscillations, alpha is remarkable in several ways: It usually represents the dominant oscillation, and - in contrast to delta, theta and gamma which show event-related increases in amplitude in response to cognitive task demands - alpha typically exhibits decreases in amplitudes. This peculiar functional reactivity raises the question, whether alpha is associated with a special and possibly unique type of cognitive process. With respect to this question there is an interesting functional similarity with studies on brain metabolism, which typically have focussed on increases in activity in task relevant regions. Most interestingly, however, as a variety of findings meanwhile document, certain brain regions (comprising posterior medial/lateral and ventral/dorsal medial prefrontal cortices) are more active during rest and show a decrease in activity in a large variety of tasks (cf. e.g., Gusnard & Raichle, 2001). These findings have led to the hypothesis that during the resting state the brain is active in a specifically organized way which was termed ‘default mode’ (for a more recent review cf., Fox & Raichle, 2007) and the corresponding brain regions were termed ‘default (mode) network’. Many regions of this network are known to play an important role for consciousness. The functional similarities between alpha and the default network (both are active during rest and decrease their activity in many types of cognitive tasks; in both systems task-related reactivity depends on the resting state) raise the question, whether alpha reflects a subsystem of the default network, one that is located in posterior parts of the default network and is functionally associated with ‘representing or monitoring the world around us‘ (Gusnard & Raichle, 2001).


Fox, M.D. & Raichle M.E., (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Review Neuroscience, 8, 700-711.

Gusnard, D. A. & Raichle, M. E. (2001). Searching for a baseline: Functional imaging and the resting human brain. Nature Reviews Neuroscience, 2, 685-694.

Klimesch, W., Sauseng, P., & Hanslmayr, S., 2007a. EEG alpha oscillations: The inhibition–timing hypothesis. Brain Res. Brain Res. Rev. 53, 63-88.

Klimesch, W., Hanslmayr, S., Sauseng, P., Gruber, W., & Doppelmayr, M., 2007b. The P1 and traveling alpha waves: Evidence for evoked oscillations. J. Neurophysiol. 97, 1311-1318.

Klimesch, W., Sauseng, P., Hanslmayr, S., Gruber, W., & Freunberger, R., 2007c. Event-related phase reorganization may explain evoked neural dynamics. Neurosci. Biobehav. Rev. 31 (7), 1003-1016.

Nunez, P.L., 2000. Toward a quantitative description of large-scale neocortical dynamic function and EEG. Behav. Brain Sci. 23, 371–437.


Long-distance Synchronization of Neural Activity across Cortical Areas Correlates with Conscious Perception

Lucia Melloni
Brain Imaging Center Frankfurt, Germany

In my talk I will present evidence which suggests that long-distance synchronization in the gamma frequency range plays a crucial role in conscious perception. I will present several studies where long–distance synchronization and local gamma synchronization were measured during the presentation of visible versus invisible stimuli.

We hypothesized that brain states associated with conscious processing should be characterized by a high degree of synchrony, i.e. temporal coherence of activity between distant cerebral assemblies, whereas unconscious processing would be characterized by local synchronization.

In a first experiment we studied the sequence of electrophysiological events leading to conscious perception. We found that the earliest electrophysiological marker that distinguished visible from invisible stimuli was a brief burst of long-range synchrony in the gamma frequency range.

Given that visible stimuli are usually associated with more extensive processing, it could be argued that enhanced long-distance synchrony in the former experiment is a reflection of differential depths of processing and not of a mechanism related to conscious perception. To disentangle these two hypotheses we studied the differential electrophysiological responses of conscious and unconscious processing of information under conditions of similar depth of processing. In a subliminal semantic priming paradigm we found that invisible but highly processed words elicited local gamma oscillations whereas visible and highly processed words elicited both local gamma oscillations and long distance synchronization. This result is compatible with the hypothesis that local gamma oscillations correlate with depth of processing and long-distance synchronization with conscious perception.

In a third experiment we studied how bottom-up information is modulated by top-down representations. Higher-order representations might serve the crucial role of stabilizing percepts and bringing them into conscious perception in an environment where stimuli can be either ambiguous or where constant changes in low-level stimulus parameters occur (i.e., contrast variations). It is currently unknown how such top-down influence is reflected in brain activity, and how neuronal activity related to perceptual awareness is modulated by top-down and bottom-up influences. To investigate this question, we measured electroencephalographic activity in a visual paradigm where we generated perceptual hysteresis by gradually increasing and then decreasing the visibility of an initially hidden stimulus in a stepwise manner. Under this condition, perceptual hypotheses are built up as soon as the subject perceives the stimuli, which in turn increases the visibility of subsequent lower contrast stimuli.

Our behavioral results confirmed this effect by demonstrating a shift in the visibility threshold. In addition, we found that long distance synchronization correlates with conscious perception (seen vs. unseen stimuli), whereas gamma oscillations correlate with the hysteresis phenomenon itself, i.e. the presence or absence of a preceding top-down concept.

In summary, our studies suggest that precise synchronization of oscillatory neuronal responses in the high frequency range plays an important role in gating the access of sensory signals to the work space of consciousness.


Brain Rhythms, Anatomy and the Emergence of Consciousness: Why Hearts Don’t Love and Brains Don’t Pump.

Paul L Nunez
Tulane University and Brain Physics LLC


Knowledge from several disparate scientific fields is integrated with plausible conjectures to suggest neural correlates of conscious experience. I address a fundamental question of brain science: What physical and biological properties of brain tissue are critical to consciousness? The earth’s weather system provides a useful analogy. Weather patterns are determined by solar radiation, fluid frictional forces, the earth’s spin, energy exchanges between oceans and atmosphere, and so forth. Knowing these variables is a necessary, but insufficient, condition for weather prediction.

My tentative answers to the basic question of critical brain properties are based on the following scientific fields (1) Brain anatomy, especially the columnar structure of neocortex (grey matter) and its long range interconnections, the corticocortical fibers (white matter). (2) Neurophysiology with emphasis on signal transmission by action potentials, system control with chemical neurotransmitters, and synaptic action fields Psi(r, t) . (3) Electroencephalography (EEG), the electric field recorded from the scalp, a large scale measure of synaptic action fields in neocortex. (4) Synergetics, the so-called science of cooperation, which describes dynamic processes in complex physical, biological, and social systems, especially (nested) hierarchical interactions across spatial scales, both top-down and bottom-up. The preponderance of long range (non-local) cortico-cortical connections and the existence of distinct anatomical structures at multiple spatial scales, columns within columns nested like a Russian doll, distinguish brains from other tissue, e.g., the heart. Furthermore, cortico-cortical connections appear to be much more important in the human brain than in lower mammals.

Neuron sociology as a brain metaphor

In order to facilitate communication with minimal mathematical and technical detail, I choose a convenient brain metaphor, but emphasize that metaphor cannot replace genuine theory. My metaphor of choice is the human global social system, which has the following properties that serve our purpose. (1) This metaphorical system is quite familiar to scientists, philosophers, mathematicians and laymen, distinguishing social systems from several common brain analogs, the brain as a hologram, so-called “quantum brains” as so forth. For readers lacking expertise in holography or quantum theory, adoption of these analogs may defeat the purpose of drawing parallels between well known and poorly understood systems. (2) Human brains are often considered to be systems of preeminent complexity. Our metaphorical system not only qualifies as a genuine complex system (as defined in the physical sciences); it is more complex than any single brain. (3) For genuine scientific reasons that are independent of our sociological metaphor, it appears that two general features of brain tissue are especially important in healthy brains, nested hierarchical interactions and non-local interactions. These properties are also important characteristics of the human global social system. The cooperation and conflict between individuals, cities, nations and so forth serves as a convenient metaphor for neural interactions at multiple spatial scales.

Neurophysiology and the time for consciousness to develop

Sensory signals (action potentials) pass through midbrain relay stations in the thalamus (excepting smell) and enter primary sensory neocortex. These inputs then spread widely in the brain, especially to other cortical areas. After integration with endogenous activity (representing memory, attention, motivation, and so forth), decisions are made that lead to motor output (physical action). While the input and output parts of this process are partly understood, very little is known of the intermediate steps involving conscious decision making. It does appear, however, that consciousness of an external event takes substantial time to develop. A visual or auditory signal may reach neocortex in 10 ms, and it takes perhaps 30 ms for signals to cross the entire brain on corticocortical fibers. Consciousness of the external signal, on the other hand, appears to take perhaps 300 to 500 ms, implying that consciousness requires multiple feedback loops (in corticocortical, thalamocortical, and other fiber systems) involving widespread neocortical and other brain regions. The form of the sensory stimulus is represented in the total activity of distributed cortical networks rather than being located at any one “node.”

Brain Rhythms and Cognition

Electroencephalography is a very large scale measure of dynamic electrical activity in neocortex. A single electrode may space average the activity in 1000 macrocolumns, each column containing 100,000 or so neurons and perhaps a billion synapses. It might seem unlikely that useful information about consciousness could be obtained with the severe space averaging resulting from such blunt instruments. However, it has long been recognized that EEG provides a genuine window on the mind, albeit one with many technical limitations. Human brains exhibit complex dynamic behavior measured by scalp recordings of electric fields (EEG). These fields typically oscillate at frequencies in the range of 1 to 15 cycles per second and are distributed over the scalp in various ways. Both oscillation frequencies and spatial patterns are strongly correlated with conscious experience. Here I cite only a small subset of these data.

EEG signals reveal the general state of consciousness with high reliability: large amplitude, low frequency signals near 1 Hz (deep sleep, coma, epileptic seizure, and moderate to deep anesthesia) and with very low amplitudes and irregular waveforms (very deep anesthesia, deep coma, and brain death). Consciousness nearly always occurs with low to intermediate amplitudes and higher frequencies, with substantial relative power in the 4 to 15 Hz range when recorded from the scalp. More sophisticated dynamic measures reveal information about sleep stage, depth of anesthesia, cognitive state, behavioral state, and so forth.

Various studies show that behavior and mental activity of various kinds are correlated with EEG oscillations in selective frequency bands, especially theta (4 to 7 Hz), alpha (8 to 13 Hz) and beta (14 to 20 Hz) in scalp recordings. These bands act in different ways in different brain states; for example, mental calculations may occur with increased amplitude or coherence (a frequency domain correlation coefficient between scalp locations) of 6 Hz theta and 10 Hz alpha rhythms, at the same time that the 8 Hz alpha amplitude or coherence decreases. Other subjects exhibit different dynamic behaviors, reminding us that our brains are unique; however, nearly all subjects appear to use some combination of alpha and theta bands to accomplish the task. Animal studies and some human studies suggest that gamma oscillations (especially near 40 Hz) are also important measures of cortical function, although these higher frequencies are difficult to study in scalp recordings for technical reasons. I conjecture that complex tasks involve multiple frequency bands, but only the lower frequencies are observed in scalp recordings.

Ramesh Srinivasan and colleagues have carried out studies of binocular rivalry using steady state visually evoked magnetic fields, suggesting that consciousness of a single percept (e.g., pattern flicker of one color) is associated with increases in cross-hemispheric coherence; frontal and occipital/temporal areas of the brain also appear to synchronize to the perceived stimulus. In summary, conscious perception of an image is correlated with a more integrated dynamic state of the neurons that process the stimulus. More generally we find that conscious perception and selective attention to stimuli involve both functional integration of some cortical areas (including occipital and prefrontal cortex), together with the segregation of other areas, for example, parietal cortex. This observation that some brain areas become more functionally connected while other areas tend to disconnect has often been observed in subjects doing various mental tasks as suggested by the works of Alan Gevins, Richard Silberstein, Wolfgang Klimesch, and others.

Global fields and local or regional networks

One way to think about large scale electrical activity in neocortex involves (generally) extended networks, believed responsible for behavior and cognition, embedded within global synaptic action fields Psi(r, t). A synaptic action field is defined as a continuous mathematical function representing the number of active synapses (excitatory or inhibitory) per mm^3 of cortical tissue, independent of functional significance. Neural networks are believed to be embedded within the synaptic fields in a manner analogous to social networks embedded within a global culture. We introduce these field variables because their dynamic modulations dPsi(r, t) are apparently directly responsible for EEG, thereby providing an important cortical metric of conscious experience. We conjecture substantial hierarchical interactions between global fields and networks, both top-down and bottom-up. In this manner, local networks can influence global fields, and these fields can facilitate interactions between remote networks, leading to an (apparent) unified behavior and consciousness. This view differs substantially from the old idea of thalamic pacemakers driving the cortex (strictly bottom up interactions) and is more consistent with known dynamic processes in genuine complex systems.

The idea of neural networks (or cell assemblies) is closely associated with the mid-20^th century work of Donald Hebb. By contrast, Gestalt psychology at the time regarded neocortex as governed by an abstract field theory. In this historical context, I am essentially proposing a marriage of Hebbian neurophysiology to Gestalt psychology, except that synaptic fields are neither abstract nor controversial, rather they are based on conventional neurophysiology and estimated with EEG.


Top-down and bottom-up hierarchical interactions across spatial scales are critical to the operation of human social systems as well as neocortex. Analogous dynamic phenomena have been studied in physical, biological, social, and financial systems under the rubric synergetics, the so-called science of cooperation. Top down/bottom up interactions in complex dynamic systems, including our postulated neocortical interactions, have been labeled circular causality by Herman Haken, the founder of synergetics. In the global social system, families, neighborhoods, cities, and nations interact with each other, at both the same scales and across scales. In neocortex, the metaphorical nested “Russian dolls”, the minicolumns, corticocortical columns, macrocolumns, Broadman regions, lobes, cortical hemispheres, and brain may interact similarly. I conjecture that such cross-scale interactions are essential to brain function.

Complexity measures and local/global neocortical dynamics

My proposed global picture, with local and regional networks embedded in synaptic action fields, substantially overlaps views expressed by many other neuroscientists. For example, a quantitative measure of complexity has been proposed as a measure of consciousness and brain binding by Gerald Edelman and Giulio Tononi

…high values of complexity correspond to an optimal synthesis of functional specialization and functional integration within a system. This is clearly the case for systems like the brain--different areas and different neurons do different things (they are differentiated) at the same time they interact to give rise to a unified conscious scene and to unify behaviors (they are integrated).

In this view complexity (and by implication, cognition) tends to maximize between the extremes of isolated networks and global coherence. I find this to be a compelling working hypothesis. It then follows that local network dynamics, interactions between networks, and interactions between networks and global fields are critical for healthy brain function.

Implications for disease states

Richard Silberstein has taken this general local/global dynamic picture a step further in the physiological and clinical directions by suggesting several ways in which brainstem neurotransmitter systems might act to change the coupling strength between global fields and local or regional networks. He outlines how different neurotransmitters might alter coupling by selective actions at different cortical depths. For example, dopamine appears to be well positioned in the appropriate cortical layers to reduce corticocortical coupling and increase local network (cortical or thalamocortical) coupling, effecting a shift from more global to more locally dominated dynamics, a shift from more hypercoupled to more hypocoupled brain states. In contrast, the neurotransmitter 5-HT could move the cortex to a more hypercoupled state. Silberstein further conjectures that several diseases may be manifestations of hypercoupled or hypocoupled dynamic states brought on by faulty neurotransmitter action. For example, the association of (positive) schizophrenia symptoms with hypocoupled states is consistent with observations of a therapeutic response to dopamine receptor blockers and prominent beta activity likely due to enhanced local networks. Again, healthy consciousness is associated with a proper balance between local, regional and global mechanisms.

Non-local neocortical interactions

Cortical neurons interact locally by means of mm scale intracortical fibers and the corticocortical fibers. The dynamic significance of the label “non-local” is that neural activity at some location A can influence another location B without altering local dynamics in the intervening tissue. In our sociological metaphor, a croissant baker in Paris can have (same scale) influence on a colleague in New Orleans with a simple e-mail message without activating a serial chain of bakers connecting the two locations. Alternately, a croissant expert can provide a top-down influence on the global croissant culture using the mass media, perhaps facilitating correlated croissant activity between disconnected bakers. In mathematical physics, non-local systems are governed by integral equations in contrast to local systems governed by differential equations. Intuitively, we expect that non-local systems are generally capable of much more complex dynamics.

Brains also provide for non-local dynamics interactions in the time domain when information is retrieved from long term memory. A system in which the conditional probability of future states depends only on the current state is known as a Markovian process in probability theory. If long term memory (stored chemically) is separate from brain dynamics, brain dynamics is non-Markovian in this sense. In an analogous manner, our global social system dynamics may be considered non-Markovian since the dead easily communicate to us through books, films, and so forth, thereby altering the future in ways that cannot be predicted from the current dynamic state of our culture. The dead have much to tell us.

What makes the human brain “human”?

Consider the following paradox: For a variety of reasons, we know that much of the “humanness” of human brains results from processes in neocortex. However, an anatomist looking through a microscope at a slice of cortex will have a difficult time distinguishing one mammalian cortex from another. Rat, cow, dog, and cat look very much the same. Humans are often said to be distinguished by their large brains with convoluted surfaces; however, dolphins, elephants and whales have even larger brains with extensive cortical folding. To the best of my knowledge none of these species has contributed papers in the scientific literature.

One possible clue to this apparent paradox concerns non-local interactions. Consider the fibers that enter (or leave) the underside of a patch of neocortex. Such white matter is mostly composed of thalamocortical fibers (radial input/output from the midbrain) and corticocortical fibers (tangential interactions from other parts of cortex). Based on the work of anatomist Valentino Braitenberg, my colleague Ron Katznelson estimated the ratio of corticocortical to thalamocortical input/output fibers (per unit of cortical surface) in several mammals. In rat, for example, only about 60% of white matter input/output fibers are corticocortical, whereas the corresponding figure for humans is perhaps 98%. Unfortunately, we do not have similar estimates for dolphins, elephants, and whales. These ideas are closely related to the classic work of Donald Hebb, who emphasized that the ratio of association areas to sensory areas of neocortex progressively increases from rat to dog to monkey to human. Maybe we are smarter than our pet dogs partly because human neocortex is very strongly interconnected by non-local connections with relatively fewer connections to the more primitive midbrain, thereby allowing for more complex neocortical dynamic behavior.

Standing and traveling brain waves

Over the past 37 years, I have modeled the excitatory and inhibitory global fields of synaptic action Psi_e(r,t), Psi_i(r, t) with an integral equation derived from known (but substantially simplified) anatomy and physiology. The basic model accounts for the non-local feature of neocortical dynamics, but does not include hierarchical interactions or embedded networks, which have been included approximately in detailed studies by perhaps a dozen scientists, especially Viktor Jirsa and Herman Haken. The excitatory synaptic action at cortical location r may be expressed in terms of an inner integral over the cortical surface and outer integral over distributed axon propagation speeds.

This integral equation is based on the simple, non-controversial idea that excitatory synaptic action at cortical location r is due to excitatory sub-cortical input dPsi_0(r,t) plus excitatory action potential density dTheta(r,t) integrated over the entire neocortex; action potentials produce synaptic activity at some distant location after a delay that is proportional to cortical separation distance and inversely proportional to axon speed. Distances are defined on an equivalent smooth cortex. All the complications of white matter (cortico-cortical) fiber tracts (after smoothing) are included in an anatomical distribution function. The model is able to predict several aspects of the measured spatial temporal dynamics of large scale EEG, including approximate oscillation frequencies, propagation velocities of traveling waves, relations between spatial and temporal properties (dispersion relations), and so forth.

Concluding remarks

The large-scale dynamic behavior of neocortex measured with EEG is closely correlated with brain state. I describe brain dynamics in terms of neural networks embedded within global excitatory and inhibitory synaptic action fields and the action potential field, given the symbols Psi_e(r,t), Psi_i(r, t) and Theta(r, t), respectively. The (short time) modulation of these synaptic fields is recorded as EEG. Embedded network dynamics may or may not be recorded with scalp EEG depending on various technical issues. By studying the physiological and anatomical bases for this dynamic behavior, we infer that hierarchical interactions across spatial scales and non-local interactions in space and time are essential to a healthy consciousness.

Cognitive processes and even consciousness itself appear to be correlated with EEG oscillations in selective frequency bands. Eugene Izhikevich has shown that weakly connected “oscillators” (very broadly defined) substantially interact only when their characteristic (resonant) frequencies obey certain resonant relations. In the context of this paper, such oscillators may be associated with both the networks and global fields. A simple example is the case in which global synaptic fields oscillating at frequency f0 can cause strong coupling between two isolated networks with characteristic frequencies f1 and f2, for example when f0 = f1 +- f2. Each of these characteristic frequencies could be selectively altered by neurotransmitters. This raises the speculation that consciousness depends critically on resonance phenomena and only properly tuned brains can orchestrate the beautiful music of sentience. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Abstract: Brain Rhythms and the Global Workspace Theory

Satu Palva

Functionally specialized brain regions extract and construct features and feature conjunctions from sensory data. The neuronal signals representing individual features are transiently integrated into neuronal representations of the entire perceptual objects because human perception, attention, and short-term memory operate with objects rather than with constellations of features1,2,3. The question of how the neuronal feature representations are bound into coherent object representations is called the binding problem4 and is though to be achieved by oscillatory synchronization of the underlying anatomically distributed neuronal activity5,6. Indeed, many findings4,5,7,8 are in line with the idea that oscillatory activity in the beta- (14–30 Hz) and, in particular, in the gamma- (30–80 Hz) frequency bands beget the binding of features into neuronal object representations and reflect, in general, the cortical states of “active” neuronal processing. How are these sensory object representations perceived consciously? Functional imaging studies have shown that a circuit of frontal and parietal regions is engaged during conscious perception9,10 but it is not clear how this circuit evolve and how it is coordinated.

Conceptual models of consciousness provide frameworks that can guide experimental work on, e.g., how sensory objects become consciously perceived. In the global workspace (GW) theory, consciousness is understood to consist of unconscious “specialized processors or sensory modules” that i.e. represent sensory information and of a global workspace that integrate these competing and co-operative networks11,12,13. The global workspace is thought to involve a fronto-parietal network with which sensory information should interact in order to enter awareness.

Alpha-frequency band (8-14 Hz) oscillations may be phase synchronized between widely separated cortical structures14,15,16,17,18 and hence could mediate the integration of large-scale networks required e.g. by global workspace. This possibility, however, has not been widely embraced because the amplitude dynamics of oscillations in the alpha (8–14 Hz) frequency band have been interpreted to indicate that these oscillations have a role in inhibition and inactivate the task-irrelevant cortical regions19. Nevertheless, many recent studies on the phase dynamics of alpha oscillations, imply a direct role for alpha oscillations in attention16,18,20, consciousness14,21, and STM15,17. I show that alpha-band phase-locking in human sensorimotor, as well as in frontoparietal regions is correlated selectively with the conscious perception of weak somatosensory stimuli14. These data show no other clear correlates of conscious perception in other frequency bands and underline the putative role of alpha oscillations in sensory awareness. I also present a model in which alpha-band synchronized network of frontal and parietal regions define the global workspace22. We suggest that this global workspace mediates, e.g., attentional and central executive functions and is also essential for working memory. In line with this hypothesis, human perception23,24, action25,26,27 and eye movements28 are associated with alpha frequency band rhythmicity22,29.

In addition, I present data on cross-frequency phase synchrony between oscillations in distinct frequency bands15. I show that the phase-synchrony between alpha and gamma oscillations is load dependently strengthened by working memory. Taken the proposed representational5,8 and attentional16,18,20,22 roles of these oscillations these results suggest that cross-frequency phase synchrony between alpha and gamma oscillations may mediate content-to context binding during working memory.

We thus suggest that local beta- and gamma-band oscillatory assemblies could be coordinated by the alpha-band synchronized frontoparietal network through CF-phase synchrony. Such CF synchronized network of oscillatory activity could underlie conscious perception and integrate “local processors” to “global workspace”.

1. Wheeler ME, Treisman AM J Exp Psychol Gen 2002 131:48-64.
2. Luck SJ, Vogel EK Nature 1997 390:279–281.
3. Zang W, Luck SJ Nature 2008 in print.
4. See “Reviews on the Binding Problem” Neuron 1999 24.
5. Singer W, Gray CM Annu Rev Neurosci 1995 18:555–586.
6. Varela F, Lachaux J-P, Rodriguez E, Martinerie J Nat Rev Neurosci 2001 2:229–239.
7. Palva S, Palva JM, et al. J Neurosci 2002 22:RC211
8. Tallon-Baudry C, Bertrand O Trends Cognit Sci 1999 3:151-162.
9. Corbetta M, Shulman, G Nat. Rev. Neurosci. 2002 3:201-215.
10. Kastner S , Ungerleider L, Annu.Rev. Neurosci. 2000 23:315–341.
11. Baars, B.J. (1988) A Cognitive Theory of Consciousness, Cambridge University Press
12. Baars B, Franklin S Trends Cogn Sci 2003 7:166-172.
13. Dehaene S, Changeux JP, Naccache L, Sackur J, Sergent C Trends Cogn Sci 2006 10:204–211
14. Palva S, Linkenkaer-Hansen K, Nikulin V, Ilmoniemi RJ, Palva JM J Neurosci 2005 25:5248–5258.
15. Palva JM, Palva S, Kaila K J Neurosci 2005 25:3962–3972.
16. von Stein A, Chiang, Konig P Proc Natl Acad Sci USA 2000 97:14748–14753.
17. Halgren E et al. Cereb Cortex 2002 12:710–728.
18. Bar M et al, Proc Natl. Acd. Sci 2006 103: 449-454.
19. Pfurtscheller G Epilepsia 2003 44:2–8.
20. Mima T, et al. J Neurosci 200121:3942–3948.
21. Gail A, Brinksmeyer HJ, Eckhorn R Cereb Cortex 2004 14:300–313.
22. Palva S, Palva JM Trends Neurosci 2007, 30:150–158.
23. VanRullen R, Reddy L, Koch C Proc Natl Acad Sci USA 2005 102:5291–5296.
24, VanRullen R, Reddy L, Koch C J Neurosci 2006 26:502–507.
25. Gross J, et al. Proc Natl Acad Sci USA 2002 99:2299–2302.
26. Pollok B, et al. Neuroimage 2005 24:646–655.
27. Pollok et al., CognBrain Res 2005 25: 300–311.
28. McAuley JH, Rothwell JC, Marsden CD Neuroscience 1999 94:339-350.
29. VanRullen R, Koch C Trends Cogn Sci 2003 7:207–213.

Neural synchrony in attention and consciousness
Lawrence M. Ward
University of British Columbia

Complex cognitive processes such as attention, memory, and consciousness require the recruitment and coordination of task-relevant neural populations that are widely distributed throughout the brain. Modern neuroimaging techniques have been able to identify specific regions of cortex that comprise a functional network for some cognitive tasks, including attention, memory, and consciousness, but the precise nature of the processing involved remains elusive. Other techniques, more sensitive to temporal progression, such as EEG and MEG, have revealed that neural synchronization is deeply involved in bringing brain activity to consciousness. In particular, increased synchronization of neural activity in widespread brain areas has been directly related to the awareness of binocularly-rivaling stimuli. I will present our recent data on the time course of neural synchronization (phase locking) in particular frequency bands within and among specific brain areas involved in endogenous attention orienting and in consciousness changes during binocular rivalry. These data support the idea that local and long-distance synchrony play different but complementary roles in the brain's dynamic functional organization, and that such neural synchrony is an important neural correlate of consciousness awareness, creating a dynamic core of neural activity that in turn is responsible for primary conscious awareness. I will also present arguments that the dynamic core is realized in both cortical and thalamic brain regions, mediated by reciprocal connections between them. In my theory, also supported by lesion, direct stimulation, anesthetic, and psychological data as well as neural modeling and neuroanatomy (which I will briefly review), the cortex computes the contents of consciousness whereas the thalamus (more specifically the dendritic trees of higher-order thalamic "relay" neurons) is the locus of synchronized neural activity that directly reflects/creates phenomenal experience.








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