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      Flexible information routing by transient synchrony.

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          Abstract

          Perception, cognition and behavior rely on flexible communication between microcircuits in distinct cortical regions. The mechanisms underlying rapid information rerouting between such microcircuits are still unknown. It has been proposed that changing patterns of coherence between local gamma rhythms support flexible information rerouting. The stochastic and transient nature of gamma oscillations in vivo, however, is hard to reconcile with such a function. Here we show that models of cortical circuits near the onset of oscillatory synchrony selectively route input signals despite the short duration of gamma bursts and the irregularity of neuronal firing. In canonical multiarea circuits, we find that gamma bursts spontaneously arise with matched timing and frequency and that they organize information flow by large-scale routing states. Specific self-organized routing states can be induced by minor modulations of background activity.

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          Most cited references42

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          Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks.

          Gamma frequency oscillations are thought to provide a temporal structure for information processing in the brain. They contribute to cognitive functions, such as memory formation and sensory processing, and are disturbed in some psychiatric disorders. Fast-spiking, parvalbumin-expressing, soma-inhibiting interneurons have a key role in the generation of these oscillations. Experimental analysis in the hippocampus and the neocortex reveals that synapses among these interneurons are highly specialized. Computational analysis further suggests that synaptic specialization turns interneuron networks into robust gamma frequency oscillators.
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            The importance of mixed selectivity in complex cognitive tasks.

            Single-neuron activity in the prefrontal cortex (PFC) is tuned to mixtures of multiple task-related aspects. Such mixed selectivity is highly heterogeneous, seemingly disordered and therefore difficult to interpret. We analysed the neural activity recorded in monkeys during an object sequence memory task to identify a role of mixed selectivity in subserving the cognitive functions ascribed to the PFC. We show that mixed selectivity neurons encode distributed information about all task-relevant aspects. Each aspect can be decoded from the population of neurons even when single-cell selectivity to that aspect is eliminated. Moreover, mixed selectivity offers a significant computational advantage over specialized responses in terms of the repertoire of input-output functions implementable by readout neurons. This advantage originates from the highly diverse nonlinear selectivity to mixtures of task-relevant variables, a signature of high-dimensional neural representations. Crucially, this dimensionality is predictive of animal behaviour as it collapses in error trials. Our findings recommend a shift of focus for future studies from neurons that have easily interpretable response tuning to the widely observed, but rarely analysed, mixed selectivity neurons.
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              Large-scale cortical correlation structure of spontaneous oscillatory activity.

              Little is known about the brain-wide correlation of electrophysiological signals. We found that spontaneous oscillatory neuronal activity exhibited frequency-specific spatial correlation structure in the human brain. We developed an analysis approach that discounts spurious correlation of signal power caused by the limited spatial resolution of electrophysiological measures. We applied this approach to source estimates of spontaneous neuronal activity reconstructed from magnetoencephalography. Overall, correlation of power across cortical regions was strongest in the alpha to beta frequency range (8–32 Hz) and correlation patterns depended on the underlying oscillation frequency. Global hubs resided in the medial temporal lobe in the theta frequency range (4–6 Hz), in lateral parietal areas in the alpha to beta frequency range (8–23 Hz) and in sensorimotor areas for higher frequencies (32–45 Hz). Our data suggest that interactions in various large-scale cortical networks may be reflected in frequency-specific power envelope correlations.
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                Author and article information

                Journal
                Nat. Neurosci.
                Nature neuroscience
                Springer Nature
                1546-1726
                1097-6256
                May 22 2017
                Affiliations
                [1 ] Max Planck Institute for Dynamics and Self-organization, Göttingen, Germany.
                [2 ] Bernstein Center for Computational Neuroscience, Göttingen, Germany.
                [3 ] Institute for Nonlinear Dynamics, Georg-August University School of Science, Göttingen, Germany.
                [4 ] SFB-889 Cellular Mechanisms of Sensory Processing, Göttingen, Germany.
                [5 ] Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes, Marseille, France.
                Article
                nn.4569
                10.1038/nn.4569
                28530664
                6df1efb2-9011-4975-9881-10776e18e23b
                History

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