Topic: gamma oscillations

We used dense (20 m site spacing) local field potential (LFP) and single unit recordings across all layers of the gRSC concurrent with CA1 LFP recordings in behaving mice to investigate circuit activity of high-frequency oscillations (HFOs) in theta and sharp wave-ripples (SWRs). By comparing HFOs occurring at times of SWRs (+/-50 ms) or during theta, we found using current-source density analysis that HFOs in different states are uniformly localized to layer 2/3 (L2/3) with current sources and sinks bridging the L1-L2/3 border. HFOs that occurred outside of SWR times where rhythmically locke

The medial entorhinal cortex (MEC) hosts many of the brain’s circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience. While location is known to be encoded by a plethora of spatially tuned cell types in this brain region, little is known about how the activity of entorhinal cells is tied together over time. Among the brain’s most powerful mechanisms for neural coordination are network oscillations, which dynamically synchronize neural activity across circuit elements. In MEC, theta and gamma oscill

Neural information processing in dynamic, natural environments requires the brain to flexibly allocate limited computational resources to varying task demands. One example is selective attention in the visual system, which allows to preferentially route signals from behaviourally relevant stimuli to downstream visual areas, while suppressing irrelevant visual information. It is an open question which neural mechanisms realize selective routing, and how this process is controlled. Here we propose that spontaneous synchronization in recurrent networks is the key mechanism for selective processin

Sensory cortices display a suite of ubiquitous dynamical features, such as ongoing noise variability, transient overshoots, and oscillations, that have so far escaped a common, principled theoretical account. We developed a unifying model for these phenomena by training a recurrent excitatory-inhibitory neural circuit model of a visual cortical hypercolumn to perform sampling-based probabilistic inference. The optimized network displayed several key biological properties, including divisive normalization, as well as stimulus-modulated noise variability, inhibition-dominated transients at stimu

With advances in high-density epicortical electrophysiological recordings (i.e., ECoGs), it became possible to investigate precise spatio-temporal evolution of neural dynamics behind various cognitive functions. This improved resolution allowed for investigation of until now largely disregarded spatial features of neuronal oscillations and challenged the conventional view of global zero-lag synchrony as a basis of neuronal communication. More specifically, it revealed structured phase-offsets in superficial cortical singals corresponding to wave-like dynamics. Further investigation of single-c

Coherent oscillations of neural activity are ubiquitous across brain spatial and temporal scales and have been associated with the formation of sensory or behavioral representations [1]. Refined experimental techniques report today a new complexity of this oscillatory activity, especially in the gamma (30-100 Hz) band. Indeed, the frequency of these oscillations shows a large variability through time [2], questioning the classical view of γ oscillations being separated into different frequency bands. Oscillations appear instead in bursts characterised by rapid, synchronous neuronal firing. Thi

Coherent oscillations of neuronal activity are ubiquitous across brain spatial and temporal scales. Gamma oscillations (30-120Hz), detectable with Local Field Potentials (LFPs), are classically analyzed through massive trial averages. This approach leaves us with one average oscillation shape, one mean power and a view based on rigid frequency bands. Consistently, mechanisms based on biophysical models of neural networks typically predict periodic oscillations (e.g. PING models [1]). The functional role of oscillations have been largely investigated in the hippocampus, where, different gamma-f

Our goal is to extend the open thermodynamic model of cortical neurodynamic Freeman hypothesis using the theoretical Carnot and then Rankine Cycles to define biomarkers for mean field energy versus entropy change and relevancy to temperature. We are using the Rankine cycle to incorporate criticality which is at null spikes of theta rate (3-7 Hz) as onset of amplitude modulations with envelopes of gamma oscillations from one zero to another zero with gaps. We are analyzing the dynamics of zeroes establishing local equilibrium. We found gaps staying close to the global average gap size of whole