Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Access to Consciousness



Citation: Dehaene S, Changeux J-P (2005) Ongoing Spontaneous Activity Controls Access to Consciousness: A Neuronal Model for Inattentional Blindness. PLoS Biol 3(5) : e141. doi:10.1371/journal.pbio.0030141

Ongoing Spontaneous Activity Controls Access to Consciousness: A Neuronal Model for Inattentional Blindness

Stanislas Dehaene1, Jean-Pierre Changeux2

1 INSERM-CEA Unit 562, Cognitive Neuroimaging, Service Hospitalier Frédéric Joliot, Orsay, France, 2 CNRS URA2182 Récepteurs and Cognition, Institut Pasteur, Paris, France


Even in the absence of sensory inputs, cortical and thalamic neurons can show structured patterns of ongoing spontaneous activity, whose origins and functional significance are not well understood. We use computer simulations to explore the conditions under which spontaneous activity emerges from a simplified model of multiple interconnected thalamocortical columns linked by long-range, top-down excitatory axons, and to examine its interactions with stimulus-induced activation. Simulations help characterize two main states of activity. First, spontaneous gamma-band oscillations emerge at a precise threshold controlled by ascending neuromodulator systems. Second, within a spontaneously active network, we observe the sudden “ignition” of one out of many possible coherent states of high-level activity amidst cortical neurons with long-distance projections. During such an ignited state, spontaneous activity can block external sensory processing. We relate those properties to experimental observations on the neural bases of endogenous states of consciousness, and particularly the blocking of access to consciousness that occurs in the psychophysical phenomenon of “inattentional blindness,” in which normal subjects intensely engaged in mental activity fail to notice salient but irrelevant sensory stimuli. Although highly simplified, the generic properties of a minimal network may help clarify some of the basic cerebral phenomena underlying the autonomy of consciousness.


Ongoing spontaneous activity is present throughout the nervous system, but its function remains enigmatic. In the embryo, spontaneous movements and waves of endogenous retinal activity are thought to play an important role in the epigenesis of neural networks through selective synapse stabilization. Ongoing spontaneous activity is also present in the adult brain, where it is responsible for the highly variable patterns of the electroencephalogram (EEG). Thalamocortical networks generate a variety of oscillations whose rhythms change across the sleep-wake cycle. Optical imaging methods in anesthetized animals also reveal fast spontaneous states of neuronal activity that, far from being random, exhibit patterns that resemble those evoked by external stimuli. In parallel, functional neuroimaging studies in humans have shown a globally elevated brain metabolism at rest, with localized patterns suggesting that particular cortical regions are maintained in a high, although variable, state of activity. At present, the functional roles of this spontaneous activity in the adult brain at rest remains to be elucidated.

Architecture of Thalamocortical Areas

As a result of previous neuronal modeling studies and computer simulations, we proposed a broader framework of a formal architecture of thalamocortical areas, in which top-down activity generated in hierarchically higher cortical areas plays a key role in what we referred to as “access to consciousness” in an effortful task. Like several previous proposals, our model of a conscious neuronal workspace distinguishes lower automatized systems from increasingly higher and more autonomous supervisory systems. It also builds upon Baars' cognitive theory of consciousness, which distinguishes a vast array of unconscious specialized processors running in parallel, and a single limited-capacity serial “workspace” that allows them to exchange information.

Subcortical Automatized Processors

The proposed neuronal architecture separates, in a first minimal description, two computational spaces, each characterized by a distinct pattern of connectivity. Subcortical networks and most of the cortex can be viewed as a collection of specialized and automatized processors, each attuned to the processing of a particular type of information via a limited number of local or medium-range connections that bring to each processor the “encapsulated” inputs necessary to its function. On top of this automatic level, we postulate a distinct set of cortical “workspace” neurons characterized by their ability to send and receive projections to many distant areas through long-range excitatory axons, thus allowing many different processors to exchange information.

Long-distance, Brain-scale Connectivity

Our previous simulations demonstrated how this architecture could account for a psychological phenomenon, the “attentional blink.” Because of its long-distance, brain-scale connectivity, the global workspace establishes a central processing bottleneck such that, in the presence of two competing stimuli, processing of the first temporarily blocks high-level processing of the second. While this work simulated only sensory processing, a key hypothesis of the workspace model is that the neurons of the higher level, the workspace neurons, are the seat of a permanent spontaneous activity that creates a succession of active internal states. The aim of the present paper is to explore in a more extensive and systematic manner the role of this ongoing spontaneous activity in a similar neural network comprising several nested levels of neuronal architecture. We propose a specific network architecture and perform explicit computer simulations that offer plausible explanations for the origins and function of structured spontaneous activity in adult thalamocortical circuits, and in particular its critical role in allowing or blocking access by sensory stimuli.

Neuromodulatory Facilitation of Sensory Processing

The observed dynamic properties of the network lead us to distinguish two main transitions in activation. First, a neuromodulatory substance is assumed to control the level of network activation; as its input increases continuously, the network exhibits a sudden surge in spontaneous activation and switches to a state of thalamocortical resonance characterized by temporary bouts of synchronized gamma-band oscillations of increasing amplitude. This state of activity leads to a facilitation of sensory processing, and is proposed to correspond to the state of vigilance or being awake.

Coherent State of Activity (“ignition”)

When the simulated areas are reciprocally connected by long-distance excitatory connections, a second state transition can occur. A subset of areas may suddenly show a strong temporary increase in synchronized firing and form a coherent state of activity (“ignition”). The transition to this state of high correlated activity is fast and characterized by an amplification of local neural activation and the subsequent ignition of multiple distant areas. This state of activity competes with, rather than facilitates, sensory processing, and thus leads to an extinction of sensory processing. We propose that this blocking may account for the “inattentional blindness” phenomenon, in which normal subjects intensely engaged in mental activity fail to notice salient but task-irrelevant sensory stimuli.

Computer Simulations characterize Complex Nested Architecture

We used computer simulations to characterize spontaneous and evoked activity in a complex nested architecture comprising multiple neurons, columns, and areas. To facilitate comprehension, we organize the results section as a progression from local to more global states of activity. We start by describing the spontaneous and evoked activity in the building blocks of the model, namely the single neuron and an isolated thalamocortical column. We then consider the extent to which those properties are affected when multiple thalamocortical columns are interconnected by long-distance, bottom-up and top-down connections.

Global Ignition of the Workspace by External Stimuli

We now describe how the response to external stimuli is radically changed once multiple columns are interconnected by long-distance connections into a global workspace. We simulated a multicolumn cortical model with four hierarchical levels, interconnected by long-distance corticocortical connections, and with two representations at each level. As in the previous section, spontaneous activity could be generated by intrinsic oscillations, random spikes, or a mixture of both; yet, those simulations again showed few differences, and we therefore only report the results of the intrinsic oscillation model.

Ignition is a high-level collective phenomenon and is critically dependent on the integrity of long-distance recurrent connections. When top-down connections are disabled, then ignition fails to occur and activation duration becomes exclusively proportional to stimulus duration, as in the single-column model. If top-down connection strengths are weakened, or if the connection probability is lowered, then a corresponding increase of the threshold duration for ignition is seen (up to a critical value beyond which ignition cannot occur, regardless of stimulus strength).

Ignition as an All-or-None Stochastic Phenomenon

According to the model, the thalamocortical network is under a permanent state of spontaneous activity. Therefore, the processing of an identical external input may change with the local context of ongoing activation. For stimuli close to threshold, this “resonance” of external inputs with internal spontaneous activity plays a determinant role in allowing or blocking ignition.

Spontaneous Ignition

Up to now we have considered mostly the impact of an external stimulus onto the workspace system (ignition) and its interaction with ongoing oscillations of moderate intensity. However, simulations also revealed that ignition can occur spontaneously. In addition to waxing-and-waning gamma-band oscillations that are already present in the single-column model, the network with global long-distance connectivity occasionally falls into a state of globally synchronous elevated activity analogous to its ignition by external stimuli. For a period of about 200–300 ms, the neurons coding for a given representation become spontaneously active synchronously within each of the four areas, with firing rates approaching 50–100 Hz. Meanwhile, the neurons coding for the other representation are quiescent and oscillations are actively suppressed in the higher areas.


Two main states of the network have been observed: spontaneous gamma-band thalamocortical oscillations under the control of ascending neuromodulator systems; and, within a spontaneously active network, the sudden “ignition” of one out of many possible coherent states of high-level activity amidst cortical neurons with long-distance projections. In this discussion, we examine to what extent the delineation of these two dynamic states can capture empirical data on consciousness and its available neural correlates. We consider first how changes in spontaneous activity relate to the continuum of consciousness states that can be observed in the transitions between the awake state, sleep, anesthesia, or coma. Second, we discuss the all-or-none transition in neuronal activity associated with ignition and attempt to relate it to the transition from subliminal to conscious processing in various perceptual paradigms. Third, we discuss the interactions between vigilance and conscious access, and examine whether the model captures some of the processes underlying inattentional blindness.

Spontaneous Thalamocortical Rhythms and States of Vigilance

The transition between the awake and asleep states is known to be regulated by various diffuse ascending neuromodulatory systems located in the brainstem, hypothalamus, and basal forebrain, and liberating substances such as acetylcholine, noradrenalin, serotonin, and histamine in the cortex and thalamus. In particular, cholinergic neurons in the pedunculopontine nucleus increase their firing prior to awakening and, through their diffuse projections, depolarize thalamic neurons, directly or indirectly, switching them out of the slow bursting mode and into fast gamma-band oscillations. Similar effects can be obtained by electrical stimulation of the brain stem or by direct application of acetylcholine.

The waxing-and-waning synchronous bursts of oscillations that we observed bear similarity with empirical observations. During the waking state, thalamic neurons exhibit fast spontaneous oscillations of their membrane potential at frequencies in the gamma band (20–80 Hz). These oscillations exhibit transient periods of thalamocortical resonance, which are detectable macroscopically as bouts of gamma-band oscillations using electrophysiological recordings.

Following Llinas et al., we propose that the spontaneous oscillatory activity that arises in thalamocortical networks constitutes the neuronal basis of the state of consciousness referred to as vigilance. An original feature of our simulation is to characterize precisely, in terms of a dynamic phase transition, the change in thalamocortical activity that characterizes a change in vigilance. We show that there exists a vigilance threshold around which thalamocortical activity changes suddenly according to a Hopf bifurcation. The combination of continuity and discontinuity that this bifurcation presents may shed interesting light on the nature of the awakening process at the neuronal level. The Hopf bifurcation is continuous in the amplitude of spontaneous activity, which increases steadily from zero as vigilance increases. In that respect, our model incorporates a true continuum of consciousness states, from high vigilance to drowsiness and the various states of sleep, anesthesia, or coma. It is consistent with empirical observations that the ratio of high-to-low frequencies in the scalp EEG changes with the depth of anesthesia and correlates with objective tests of vigilance and reportability and with subjective measures of consciousness.

Anatomical Basis of the Awake State

Anatomically, our view predicts that, in the awake state, spontaneous activity is present in all areas, but exhibits a higher degree of organization (stream of discrete states) in higher cortical association areas, whose neurons are tightly interconnected at long-distance into a global neuronal workspace and mobilize other low-level areas in a top-down manner. Thus, we would expect cortical areas particularly rich in “workspace neurons” with long-distance connections (i.e., prefrontal, parietal, superior temporal, and cingulate cortices) to show the most intense and consistent spontaneous activity in the awake state. Other areas would also be active, but with more variability, reflecting the changes in contents contemplated by the subject at any given moment.

This prediction fits within a recent line of research that has examined the “resting state,” “default mode,” or “baseline” activity of the awake human brain at rest. This research has evidenced a broadly distributed network of areas active during rest, including dorsal and ventral medial prefrontal, lateral parietotemporal, and posterior cingulate cortices. This network is not static and strictly confined, but constantly fluctuates in synchrony with changes in EEG spectral content. Furthermore, prefrontal, parietal, and cingulate areas show the greatest drop in metabolism during various types of transitions away from the awake state, whether during anesthesia, sleep, coma, or the vegetative state

Global Amplification and Conscious Access

In our model, ignition places the thalamocortical network in a metastable state that lasts for a relatively fixed duration (e.g., 200–300 ms). Once an ignited assembly loses its support, the network again becomes available for either spontaneous or externally induced ignition. Thus, our simulations predict that multiple episodes of metastability should follow each other in a stream of discrete states, nested within a much slower fluctuation of vigilance.

Interactions between Ongoing Spontaneous Activity and External Stimuli

An original aspect of the present simulations concerns the interactions between ongoing spontaneous activity and external stimuli. These interactions are mostly facilitatory: Higher spontaneous activity brings neurons closer to firing threshold, thus facilitating the detection of weak stimuli. However, very high spontaneous activity (spontaneous ignition) has a blocking role, preventing access to other external stimuli.

Spontaneous Activity and Autonomy of the Organism

We close by noting that most theories of conscious processing have failed to recognize the important role of spontaneous thalamocortical activity. By contrast, the present computational model proposes an essential role for spontaneous activity within an anatomically distinct set of “workspace neurons” in giving the formal organism an autonomy relative to the external world. Autonomy has several facets. First, in the absence of external signals, an autonomous organism must be capable of generating spontaneous representations and intentions (self-activation). Our present and past work proposes that spontaneous neuronal activity is an essential component of this “projective style”, which departs from the input-output view currently dominant in the neural network community. The present work shows how sources of noise such as spontaneous membrane oscillations and noisy synaptic transmission can be harnessed to generate a stream of highly organized states of self-activation in the complete absence of external inputs. This capacity is expected to play a crucial role in the spontaneous generation of novel, flexible behavior, as evidenced for instance in neuropsychological tests such as the Tower of London test or the Wisconsin card sorting test.

Second, even when submitted to external stimulation, an autonomous organism must be capable of representing internally only those stimuli that are relevant to the present situation. Relevant stimuli must first be selected, based on reward-based evaluation systems not included in the present model, all the while resisting distraction by irrelevant stimuli. The present work provides the basic building blocks for such a decoupling of part of the organism's internal activity from its current inputs. A crucial role is attributed to the strongly recurrent connectivity of cortical neurons in association areas, which collectively form a conscious workspace, an internal “milieu” buffered from the outside world, and within which mental hypotheses can be entertained and discarded at will. An inevitable consequence of this autonomy, however, is that some stimuli are inappropriately filtered out, thus causing inattentional blindness.

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