NREM sleep improves behavioral performance by desynchronizing cortical circuits.

Sleep improves cognitive performance, yet little is known about the neural mechanisms of this improvement. We performed multielectrode recording in macaque visual and dorsolateral prefrontal cortex while animals performed a visual discrimination task before and after non-rapid eye movement (NREM) sleep. Although sleep induces synchronized fluctuations in population activity across cortical areas, the post-sleep population activity became more desynchronized relative to the pre-sleep state.

High-order interactions explain the collective behavior of cortical populations in executive but not sensory areas.

One influential view in neuroscience is that pairwise cell interactions explain the firing patterns of large populations. Despite its prevalence, this view originates from studies in the retina and visual cortex of anesthetized animals. Whether pairwise interactions predict the firing patterns of neurons across multiple brain areas in behaving animals remains unknown.

Heterogeneous side effects of cortical inactivation in behaving animals.

Cortical inactivation represents a key causal manipulation allowing the study of cortical circuits and their impact on behavior. A key assumption in inactivation studies is that the neurons in the target area become silent while the surrounding cortical tissue is only negligibly impacted. However, individual neurons are embedded in complex local circuits composed of excitatory and inhibitory cells with connections extending hundreds of microns.

Neurophysiological brain mapping of human sleep-wake states.

Objective: We recently proposed a spectrum-based model of the awake intracranial electroencephalogram (iEEG) (Kalamangalam et al., 2020), based on a publicly-available normative database (Frauscher et al., 2018).

Functional Connectivity in Dorsolateral Frontal Cortex: Intracranial Electroencephalogram Study.

Mechanisms underlying the variation in the appearance of electroencephalogram (EEG) over human head are not well characterized. We hypothesized that spatial variation of the EEG, being ultimately linked to variations in cortical neurobiology, was dependent on cortical connectivity patterns. Specifically, we explored the relationship of resting-state functional connectivity derived from intracranial EEG (iEEG) data in seven ( = 7) human epilepsy patients with the intrinsic dynamic variability of the local iEEG.

A neurophysiological brain map: Spectral parameterization of the human intracranial electroencephalogram.

Objective: A library of intracranial electroencephalography (iEEG) from the normal human brain has recently been made publicly available (Frauscher et al., 2018). The library - which we term the Montreal Neurological Institute Atlas (MNIA) - comprises 30 hours of iEEG from over a hundred epilepsy patients.

A Continuous Clustering Algorithm for Detection of Local Sleep in Humans.

Objective: Research in animal models has shown that many EEG sleep features reflect local conditions, which is a consequence of relative inactivity of neuronal clusters. In humans, the authors previously reported that focal sleep patterns appear on the cortex during the wake state and suggested that this underlies the condition described as drowsiness. The focal changes at individual electrodes appeared as a combination of increased instantaneous amplitude in the delta band and decreased instantaneous frequency in the theta-alpha band during non-REM sleep, with the opposite occurring during the wake state, permitting their categorization as "active" and "inactive.

Focal Changes to Human Electrocorticography With Drowsiness: A Novel Measure of Local Sleep.

Drowsiness may be defined as the progressive loss of cortical processing efficiency that occurs with time passing while awake. This loss of cortical processing efficiency is reflected in focal changes to the electroencephalogram, including islands of increased delta power concurrent with drop-offs in neuronal activity (i.e.

A unified statistical model for the human electrocorticogram.

Objective: Extracellular field potentials (ECFs) generated in the cerebral cortex span a vast range of spatiotemporal scales. The process(es) leading to this large dynamic range remain debatable. Here we propose a novel statistical description of the amplitude spectrum of the human electrocorticogram (ECoG).

Reactivation of visual-evoked activity in human cortical networks.

In the absence of sensory input, neuronal networks are far from being silent. Whether spontaneous changes in ongoing activity reflect previous sensory experience or stochastic fluctuations in brain activity is not well understood. Here we demonstrate reactivation of stimulus-evoked activity that is distributed across large areas in the human brain.

Negative Correlations in Visual Cortical Networks.

The amount of information encoded by cortical circuits depends critically on the capacity of nearby neurons to exhibit trial-to-trial (noise) correlations in their responses. Depending on their sign and relationship to signal correlations, noise correlations can either increase or decrease the population code accuracy relative to uncorrelated neuronal firing. Whereas positive noise correlations have been extensively studied using experimental and theoretical tools, the functional role of negative correlations in cortical circuits has remained elusive.

Correlated variability in laminar cortical circuits.

Despite the fact that strong trial-to-trial correlated variability in responses has been reported in many cortical areas, recent evidence suggests that neuronal correlations are much lower than previously thought. Here, we used multicontact laminar probes to revisit the issue of correlated variability in primary visual (V1) cortical circuits. We found that correlations between neurons depend strongly on local network context--whereas neurons in the input (granular) layers showed virtually no correlated variability, neurons in the output layers (supragranular and infragranular) exhibited strong correlations.

Sex differences in the behavioral response to methylphenidate in three adolescent rat strains (WKY, SHR, SD).

Methylphenidate (MPD) is the most widely used drug in the treatment of attention-deficit hyperactivity disorder (ADHD). ADHD has a high incidence in children and can persist in adolescence and adulthood. The relation between sex and the effects of acute and chronic MPD treatment was examined using adolescent male and female rats from three genetically different strains: spontaneously hyperactive rat (SHR), Wistar-Kyoto (WKY) and Sprague-Dawley (SD).

Levodopa-induced dyskinesias detection based on the complexity of involuntary movements.

Complexity of the biological system output reflects the system's ability to adapt in a changing environment. Disease states and aging, which influence the adaptation of biological systems, modify the complexity of system response to environment changes. The alteration of motor adaptivity seen in Parkinson's disease (PD) has never been properly investigated by using the motor response complexity measured with sample entropy.

Efficient coding in heterogeneous neuronal populations.

A ubiquitous feature of neuronal responses within a cortical area is their high degree of inhomogeneity. Even cells within the same functional column are known to have highly heterogeneous response properties when the same stimulus is presented. Whether the wide diversity of neuronal responses is an epiphenomenon or plays a role for cortical function is unknown.

Asymmetric synaptic depression in cortical networks.

Synaptic depression is essential for controlling the balance between excitation and inhibition in cortical networks. Several studies have shown that the depression of intracortical synapses is asymmetric, that is, inhibitory synapses depress less than excitatory ones. Whether this asymmetry has any impact on cortical function is unknown.

Spike source localization with tetrodes.

The paper presents in detail a method for approximating the spatial position of neural spike activity from tetrode recordings. The method uses a nonlinear mapping of a set of tetrode tip amplitudes into three-dimensional (3D) space, followed by a self-organizing map clustering technique. Viewed as a spike sorting method, it performs better than tetrode peak amplitudes and it is roughly equivalent with amplitude ratios.