Neural ensemble
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Methodological considerations for studying neural oscillations Open
Neural oscillations are ubiquitous across recording methodologies and species, broadly associated with cognitive tasks, and amenable to computational modelling that investigates neural circuit generating mechanisms and neural population dy…
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The brain in motion: How ensemble fluidity drives memory-updating and flexibility Open
While memories are often thought of as flashbacks to a previous experience, they do not simply conserve veridical representations of the past but must continually integrate new information to ensure survival in dynamic environments. Theref…
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Multiple timescales of neural dynamics and integration of task-relevant signals across cortex Open
Significance The brain exhibits a tremendous amount of heterogeneity, and to make sense of this seemingly random system neuroscientists have explored various ideas to organize it into distinct areas, each performing certain computations. O…
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Neural ensemble dynamics in dorsal motor cortex during speech in people with paralysis Open
Speaking is a sensorimotor behavior whose neural basis is difficult to study with single neuron resolution due to the scarcity of human intracortical measurements. We used electrode arrays to record from the motor cortex ‘hand knob’ in two…
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Information-Limiting Correlations in Large Neural Populations Open
Understanding the neural code requires understanding how populations of neurons code information. Theoretical models predict that information may be limited by correlated noise in large neural populations. Nevertheless, analyses based on t…
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The Computational and Neural Basis of Rhythmic Timing in Medial Premotor Cortex Open
The neural underpinnings of rhythmic behavior, including music and dance, have been studied using the synchronization-continuation task (SCT), where subjects initially tap in synchrony with an isochronous metronome and then keep tapping at…
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Superior colliculus neuronal ensemble activity signals optimal rather than subjective confidence Open
Significance Previously, the neuronal correlates of perceptual confidence have been identified in neural circuits responsible for deciding what an animal sees. However, behaviorally, confidence and perceptual decision accuracy are confound…
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Deep Neural Network Ensembles for Time Series Classification Open
Deep neural networks have revolutionized many fields such as computer vision\nand natural language processing. Inspired by this recent success, deep learning\nstarted to show promising results for Time Series Classification (TSC).\nHowever…
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The Behavioral Relevance of Cortical Neural Ensemble Responses Emerges Suddenly Open
Whereas many laboratory-studied decisions involve a highly trained animal identifying an ambiguous stimulus, many naturalistic decisions do not. Consumption decisions, for instance, involve determining whether to eject or consume an alread…
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Constraints on neural redundancy Open
Millions of neurons drive the activity of hundreds of muscles, meaning many different neural population activity patterns could generate the same movement. Studies have suggested that these redundant (i.e. behaviorally equivalent) activity…
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A Brief Review of Chimera State in Empirical Brain Networks Open
Understanding the human brain and its functions has always been an interesting and challenging problem. Recently, a significant progress on this problem has been achieved on the aspect of chimera state where a coexistence of synchronized a…
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Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex Open
Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial f…
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Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons Open
Neurons recorded in behaving animals often do not discernibly respond to sensory input and are not overtly task-modulated. These non-classically responsive neurons are difficult to interpret and are typically neglected from analysis, confo…
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Contribution of behavioural variability to representational drift Open
Neuronal responses to similar stimuli change dynamically over time, raising the question of how internal representations can provide a stable substrate for neural coding. Recent work has suggested a large degree of drift in neural represen…
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Sparse Computation in Adaptive Spiking Neural Networks Open
Artificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a comput…
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Neural theta oscillations support semantic memory retrieval Open
Lexical–semantic retrieval emerges through the interactions of distributed prefrontal and perisylvian brain networks. Growing evidence suggests that synchronous theta band neural oscillations might play a role in this process, yet, their f…
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Real-time classification of experience-related ensemble spiking patterns for closed-loop applications Open
Communication in neural circuits across the cortex is thought to be mediated by spontaneous temporally organized patterns of population activity lasting ~50 –200 ms. Closed-loop manipulations have the unique power to reveal direct and caus…
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Trial-by-Trial Motor Cortical Correlates of a Rapidly Adapting Visuomotor Internal Model Open
Accurate motor control is mediated by internal models of how neural activity generates movement. We examined neural correlates of an adapting internal model of visuomotor gain in motor cortex while two macaques performed a reaching task in…
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Discrepancies between Multi-Electrode LFP and CSD Phase-Patterns: A Forward Modeling Study Open
Multi-electrode recordings of local field potentials (LFPs) provide the opportunity to investigate the spatiotemporal organization of neural activity on the scale of several millimeters. In particular, the phases of oscillatory LFPs allow …
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Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters Open
In invasive electrophysiological recordings, a variety of neural oscillations can be detected across the cortex, with overlap in space and time. This overlap complicates measurement of neural oscillations using standard referencing schemes…
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Neural signature of flexible coding in prefrontal cortex Open
The ability of prefrontal cortex to quickly encode novel associations is crucial for adaptive behavior and central to working memory. Fast Hebbian changes in synaptic strength permit forming new associations, but neuronal signatures of thi…
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Elucidating the Neural Representation and the Processing Dynamics of Face Ensembles Open
Extensive behavioral work has documented the ability of the human visual system to extract summary representations from face ensembles (e.g., the average identity of a crowd of faces). Yet, the nature of such representations, their underly…
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Inferring decoding strategies for multiple correlated neural populations Open
Studies of neuron-behaviour correlation and causal manipulation have long been used separately to understand the neural basis of perception. Yet these approaches sometimes lead to drastically conflicting conclusions about the functional ro…
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Dendritic plateau potentials can process spike sequences across multiple time-scales Open
The brain constantly processes information encoded in temporal sequences of spiking activity. This sequential activity emerges from sensory inputs as well as from the brain's own recurrent connectivity and spans multiple dynamically changi…
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Neural phase locking predicts BOLD response in human auditory cortex Open
Natural environments elicit both phase-locked and non-phase-locked neural responses to the stimulus in the brain. The interpretation of the BOLD signal to date has been based on an association of the non-phase-locked power of high-frequenc…
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Efficient Computation in Adaptive Artificial Spiking Neural Networks Open
Artificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a comput…
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Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information Open
When preparing a movement, we often rely on partial or incomplete information, which can decrement task performance. In behaving monkeys we show that the degree of cued target information is reflected in both, neural variability in motor c…
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Drift of neural ensembles driven by slow fluctuations of intrinsic excitability Open
Representational drift refers to the dynamic nature of neural representations in the brain despite the behavior being seemingly stable. Although drift has been observed in many different brain regions, the mechanisms underlying it are not …
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Strong inhibitory signaling underlies stable temporal dynamics and working memory in spiking neural networks Open
Cortical neurons process information on multiple timescales, and areas important for working memory (WM) contain neurons capable of integrating information over a long timescale. However, the underlying mechanisms for the emergence of neur…
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Neuronal ‘Ensemble’ Recording and the Search for the Cell Assembly: A Personal History Open
This contribution is part of the special issue on the Hippocampus focused on personal histories of advances in knowledge on the hippocampus and related structures. An account is offered of the author's role in the development of neural ens…