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International audience; Sleep spindles are approximately 1 s bursts of 10-16 Hz activity that occur during stage 2 sleep. Spindles are highly synchronous across the cortex and thalamus in animals, and across the scalp in humans, implying correspondingly widespread and synchronized cortical generators. However, prior studies have noted occasional dissociations of the magnetoencephalogram (MEG) from the EEG during spindles, although detailed studies of this phenomenon have been lacking. We systematically compared high-density MEG and EEG recordings during naturally occurring spindles in healthy humans. As expected, EEG was highly coherent across the scalp, with consistent topography across spindles. In contrast, the simultaneously recorded MEG was not synchronous, but varied strongly in amplitude and phase across locations and spindles. Overall, average coherence between pairs of EEG sensors was approximately 0.7, whereas MEG coherence was approximately 0.3 during spindles. Whereas 2 principle components explained approximately 50% of EEG spindle variance, >15 were required for MEG. Each PCA component for MEG typically involved several widely distributed locations, which were relatively coherent with each other. These results show that, in contrast to current models based on animal experiments, multiple asynchronous neural generators are active during normal human sleep spindles and are visible to MEG. It is possible that these multiple sources may overlap sufficiently in different EEG sensors to appear synchronous. Alternatively, EEG recordings may reflect diffusely distributed synchronous generators that are less visible to MEG. An intriguing possibility is that MEG preferentially records from the focal core thalamocortical system during spindles, and EEG from the distributed matrix system.

International audience; Affective neuroscience is concerned with identifying the neural bases of emotion. For historical and methodological reasons, models describing the brain architecture that supports emotional processes in humans have tended to neglect the basal ganglia, focusing instead on cortical and amygdalar mechanisms. Now, however, deep brain stimulation (DBS) of the subthalamic nucleus (STN), a neurosurgical treatment for Parkinson's disease and obsessive-compulsive disorder, is helping researchers explore the possible functional role of this particular basal ganglion in emotional processes. After reviewing studies that have used DBS in this way, we propose a model in which the STN plays a crucial role in producing temporally organized neural co-activation patterns at the cortical and subcortical levels that are essential for generating emotions and related feelings.

International audience; Loss of consciousness (LOC) is a dramatic clinical manifestation of temporal lobe seizures. Its underlying mechanism could involve altered coordinated neuronal activity between the brain regions that support conscious information processing. The consciousness access hypothesis assumes the existence of a global workspace in which information becomes available via synchronized activity within neuronal modules, often widely distributed throughout the brain. Re-entry loops and, in particular, thalamo-cortical communication would be crucial to functionally bind different modules together. In the present investigation, we used intracranial recordings of cortical and subcortical structures in 12 patients, with intractable temporal lobe epilepsy (TLE), as part of their presurgical evaluation to investigate the relationship between states of consciousness and neuronal activity within the brain. The synchronization of electroencephalography signals between distant regions was estimated as a function of time by using non-linear regression analysis. We report that LOC occurring during temporal lobe seizures is characterized by increased long-distance synchronization between structures that are critical in processing awareness, including thalamus (Th) and parietal cortices. The degree of LOC was found to correlate with the amount of synchronization in thalamo-cortical systems. We suggest that excessive synchronization overloads the structures involved in consciousness processing, preventing them from treating incoming information, thus resulting in LOC.

International audience; Developing cortical networks generate a variety of coherent activity patterns that participate in circuit refinement. Early network oscillations (ENOs) are the dominant network pattern in the rodent neocortex for a short period after birth. These large-scale calcium waves were shown to be largely driven by glutamatergic synapses albeit GABA is a major excitatory neurotransmitter in the cortex at such early stages, mediating synapse-driven giant depolarizing potentials (GDPs) in the hippocampus. Using functional multineuron calcium imaging together with single-cell and field potential recordings to clarify distinct network dynamics in rat cortical slices, we now report that the developing somatosensory cortex generates first ENOs then GDPs, both patterns coexisting for a restricted time period. These patterns markedly differ by their developmental profile, dynamics, and mechanisms: ENOs are generated before cortical GDPs (cGDPs) by the activation of glutamatergic synapses mostly through NMDARs; cENOs are low-frequency oscillations (approximately 0.01 Hz) displaying slow kinetics and gradually involving the entire network. At the end of the first postnatal week, GABA-driven cortical GDPs can be reliably monitored; cGDPs are recurrent oscillations (approximately 0.1 Hz) that repetitively synchronize localized neuronal assemblies. Contrary to cGDPs, cENOs were unexpectedly facilitated by short anoxic conditions suggesting a contribution of glutamate accumulation to their generation. In keeping with this, alterations of extracellular glutamate levels significantly affected cENOs, which are blocked by an enzymatic glutamate scavenger. Moreover, we show that a tonic glutamate current contributes to the neuronal membrane excitability when cENOs dominate network patterns. Therefore, cENOs and cGDPs are two separate aspects of neocortical network maturation that may be differentially engaged in physiological and pathological processes.

International audience; It is becoming increasingly clear that attention-demanding tasks engage not only activation of specific cortical regions but also deactivation of other regions that could interfere with the task at hand. At the same time, electrophysiological studies in animals and humans have found that the participation of cortical regions to cognitive processes translates into local synchronization of rhythmic neural activity at frequencies above 40 Hz (so-called gamma-band synchronization). Such synchronization is seen as a potential facilitator of neural communication and synaptic plasticity. We found evidence that cognitive processes can also involve the disruption of gamma-band activity in high-order brain regions. Intracerebral electroencephalograms were recorded in 3 epileptic patients during 2 reading tasks. Visual presentation of words induced a strong deactivation in a broad (20-150 Hz) frequency range in the left ventral lateral prefrontal cortex, in parallel with gamma-band activations within the reading network, including Broca's area. The observed energy decrease in neural signals was reproducible across patients. It peaked around 500 ms after stimulus onset and appeared subject to attention-modulated amplification. Our results suggest that cognition might be mediated by a coordinated interaction between regional gamma-band synchronizations and desynchronizations, possibly reflecting enhanced versus reduced local neural communication.

GABAergic interneurons play a major role in the emergence of various types of synchronous oscillatory patterns of activity in the central nervous system. Motivated by these experimental facts, modeling studies have investigated mechanisms for the emergence of coherent activity in networks of inhibitory neurons. However, most of these studies have focused either when the noise in the network is absent or weak or in the opposite situation when it is strong. Hence, a full picture of how noise affects the dynamics of such systems is still lacking. The aim of this letter is to provide a more comprehensive understanding of the mechanisms by which the asynchronous states in large, fully connected networks of inhibitory neurons are destabilized as a function of the noise level. Three types of single neuron models are considered: the leaky integrate-and-fire (LIF) model, the exponential integrate-and-fire (EIF), model and conductance-based models involving sodium and potassium Hodgkin-Huxley (HH) currents. We show that in all models, the instabilities of the asynchronous state can be classified in two classes. The first one consists of clustering instabilities, which exist in a restricted range of noise. These instabilities lead to synchronous patterns in which the population of neurons is broken into clusters of synchronously firing neurons. The irregularity of the firing patterns of the neurons is weak. The second class of instabilities, termed oscillatory firing rate instabilities, exists at any value of noise. They lead to cluster state at low noise. As the noise is increased, the instability occurs at larger coupling, and the pattern of firing that emerges becomes more irregular. In the regime of high noise and strong coupling, these instabilities lead to stochastic oscillations in which neurons fire in an approximately Poisson way with a common instantaneous probability of firing that oscillates in time.

International audience; Delay-related sustained activity in the prefrontal cortex of primates, a neurological analogue of working memory, has been proposed to arise from synaptic interactions in local cortical circuits. The implication is that memories are coded by spatially localized foci of sustained activity. We investigate the mechanisms by which sustained foci are initiated, maintained, and extinguished by excitation in networks of Hodgkin-Huxley neurons coupled with biophysical spatially structured synaptic connections. For networks with a balance between excitation and inhibition, a localized transient stimulus robustly initiates a localized focus of activity. The activity is then maintained by recurrent excitatory AMPA-like synapses. We find that to maintain the focus, the firing must be asynchronous. Consequently, inducing transient synchrony through an excitatory stimulus extinguishes the sustained activity. Such a monosynaptic excitatory turn-off mechanism is compatible with the working memory being wiped clean by an efferent copy of the motor command. The activity that codes working memories may be structured so that the motor command is both the read-out and a direct clearing signal. We show examples of data that is compatible with our theory.