scholarly journals Coexistence of fast and slow gamma oscillations in one population of inhibitory spiking neurons

2019 ◽  
Author(s):  
Hongjie Bi ◽  
Marco Segneri ◽  
Matteo di Volo ◽  
Alessandro Torcini
Keyword(s):  
Gamma Oscillations ◽  
Brain Regions ◽  
Neural Population ◽  
Neural Firing ◽  
Phase Coupling ◽  
Population Activity ◽  
Brain Functions ◽  
Wide Range ◽  
Gamma Rhythms ◽  
Phase Phase

Oscillations are a hallmark of neural population activity in various brain regions with a spectrum covering a wide range of frequencies. Within this spectrum gamma oscillations have received particular attention due to their ubiquitous nature and to their correlation with higher brain functions. Recently, it has been reported that gamma oscillations in the hippocampus of behaving rodents are segregated in two distinct frequency bands: slow and fast. These two gamma rhythms correspond to different states of the network, but their origin has been not yet clarified. Here, we show theoretically and numerically that a single inhibitory population can give rise to coexisting slow and fast gamma rhythms corresponding to collective oscillations of a balanced spiking network. The slow and fast gamma rhythms are generated via two different mechanisms: the fast one being driven by the coordinated tonic neural firing and the slow one by endogenous fluctuations due to irregular neural activity. We show that almost instantaneous stimulations can switch the collective gamma oscillations from slow to fast and vice versa. Furthermore, to make a closer contact with the experimental observations, we consider the modulation of the gamma rhythms induced by a slower (theta) rhythm driving the network dynamics. In this context, depending on the strength of the forcing and the noise amplitude, we observe phase-amplitude and phase-phase coupling between the fast and slow gamma oscillations and the theta forcing. Phase-phase coupling reveals on average different theta-phases preferences for the two coexisting gamma rhythms joined to a wide cycle-to-cycle variability.

Human cortical responses to slow and fast binaural beats reveal multiple mechanisms of binaural hearing

2014 ◽  
Vol 112 (8) ◽  
pp. 1871-1884 ◽  
Author(s):  
Bernhard Ross ◽  
Takahiro Miyazaki ◽  
Jessica Thompson ◽  
Shahab Jamali ◽  
Takako Fujioka
Keyword(s):  
Binaural Hearing ◽  
Gamma Oscillations ◽  
Neural Population ◽  
Neural Firing ◽  
Sound Location ◽  
Binaural Beats ◽  
Cortical Responses ◽  
Left And Right ◽  
Auditory Cortices ◽  
40 Hz

When two tones with slightly different frequencies are presented to both ears, they interact in the central auditory system and induce the sensation of a beating sound. At low difference frequencies, we perceive a single sound, which is moving across the head between the left and right ears. The percept changes to loudness fluctuation, roughness, and pitch with increasing beat rate. To examine the neural representations underlying these different perceptions, we recorded neuromagnetic cortical responses while participants listened to binaural beats at a continuously varying rate between 3 Hz and 60 Hz. Binaural beat responses were analyzed as neuromagnetic oscillations following the trajectory of the stimulus rate. Responses were largest in the 40-Hz gamma range and at low frequencies. Binaural beat responses at 3 Hz showed opposite polarity in the left and right auditory cortices. We suggest that this difference in polarity reflects the opponent neural population code for representing sound location. Binaural beats at any rate induced gamma oscillations. However, the responses were largest at 40-Hz stimulation. We propose that the neuromagnetic gamma oscillations reflect postsynaptic modulation that allows for precise timing of cortical neural firing. Systematic phase differences between bilateral responses suggest that separate sound representations of a sound object exist in the left and right auditory cortices. We conclude that binaural processing at the cortical level occurs with the same temporal acuity as monaural processing whereas the identification of sound location requires further interpretation and is limited by the rate of object representations.

scholarly journals Modelling the neural code in large populations of correlated neurons

2020 ◽  
Author(s):  
Sacha Sokoloski ◽  
Amir Aschner ◽  
Ruben Coen-Cagli
Keyword(s):  
Neural Coding ◽  
Large Scale ◽  
Neural Code ◽  
Neural Population ◽  
Population Activity ◽  
Fundamental Properties ◽  
Wide Range ◽  
Large Populations ◽  
Scale Population ◽  
Quantitative Understanding

AbstractThe activity of a neural population encodes information about the stimulus that caused it, and decoding population activity reveals how neural circuits process that information. Correlations between neurons strongly impact both encoding and decoding, yet we still lack models that simultaneously capture stimulus encoding by large populations of correlated neurons and allow for accurate decoding of stimulus information, thus limiting our quantitative understanding of the neural code. To address this, we propose a class of models of large-scale population activity based on the theory of exponential family distributions. We apply our models to macaque primary visual cortex (V1) recordings, and show they capture a wide range of response statistics, facilitate accurate Bayesian decoding, and provide interpretable representations of fundamental properties of the neural code. Ultimately, our framework could allow researchers to quantitatively validate predictions of theories of neural coding against both large-scale response recordings and cognitive performance.

scholarly journals On cross-frequency phase-phase coupling between theta and gamma oscillations in the hippocampus

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Robson Scheffer-Teixeira ◽  
Adriano BL Tort
Keyword(s):  
Phase Locking ◽  
Gamma Oscillations ◽  
Linear Phase ◽  
Phase Coupling ◽  
Neuronal Coding ◽  
Theoretical Support ◽  
Hippocampal Activity ◽  
Phase Amplitude ◽  
Phase Phase ◽  
Frequency Phase

Phase-amplitude coupling between theta and multiple gamma sub-bands is a hallmark of hippocampal activity and believed to take part in information routing. More recently, theta and gamma oscillations were also reported to exhibit phase-phase coupling, or n:m phase-locking, suggesting an important mechanism of neuronal coding that has long received theoretical support. However, by analyzing simulated and actual LFPs, here we question the existence of theta-gamma phase-phase coupling in the rat hippocampus. We show that the quasi-linear phase shifts introduced by filtering lead to spurious coupling levels in both white noise and hippocampal LFPs, which highly depend on epoch length, and that significant coupling may be falsely detected when employing improper surrogate methods. We also show that waveform asymmetry and frequency harmonics may generate artifactual n:m phase-locking. Studies investigating phase-phase coupling should rely on appropriate statistical controls and be aware of confounding factors; otherwise, they could easily fall into analysis pitfalls.

scholarly journals Lack of evidence for cross-frequency phase-phase coupling between theta and gamma oscillations in the hippocampus

2016 ◽  
Author(s):  
Robson Scheffer-Teixeira ◽  
Adriano BL Tort
Keyword(s):  
Phase Locking ◽  
Gamma Oscillations ◽  
Actual Data ◽  
Gamma Phase ◽  
Phase Coupling ◽  
Neuronal Coding ◽  
Theoretical Support ◽  
Hippocampal Activity ◽  
Phase Amplitude ◽  
Phase Phase

AbstractPhase-amplitude coupling between theta and multiple gamma sub-bands hallmarks hippocampal activity and is believed to take part in information routing. More recently, theta and gamma oscillations were also reported to exhibit reliable phase-phase coupling, or n:m phase-locking. The existence of n:m phase-locking suggests an important mechanism of neuronal coding that has long received theoretical support. However, here we show that n:m phase-locking (1) is much lower than previously reported, (2) highly depends on epoch length, (3) does not statistically differ from chance (when employing proper surrogate methods), and that (4) filtered white noise has similar n:m scores as actual data. Moreover, (5) the diagonal stripes in theta-gamma phase-phase histograms of actual data can be explained by theta harmonics. These results point to lack of theta-gamma phase-phase coupling in the hippocampus, and suggest that studies investigating n:m phase-locking should rely on appropriate statistical controls, otherwise they could easily fall into analysis pitfalls.

scholarly journals Cross-Frequency Phase-Phase Coupling between Theta and Gamma Oscillations in the Hippocampus

2012 ◽  
Vol 32 (2) ◽  
pp. 423-435 ◽  
Author(s):  
M. A. Belluscio ◽  
K. Mizuseki ◽  
R. Schmidt ◽  
R. Kempter ◽  
G. Buzsaki
Keyword(s):  
Gamma Oscillations ◽  
Phase Coupling ◽  
Phase Phase ◽  
Frequency Phase

Errant ensembles: dysfunctional neuronal network dynamics in schizophrenia

2010 ◽  
Vol 38 (2) ◽  
pp. 516-521 ◽  
Author(s):  
Matt W. Jones
Keyword(s):  
Calcium Binding ◽  
Field Potential ◽  
Brain Regions ◽  
Aminobutyric Acid ◽  
Neural Population ◽  
Population Activity ◽  
Potential Oscillations ◽  
Disconnection Syndrome ◽  
Hyperactivity Disorder ◽  
Neuronal Network Dynamics

Most complex psychiatric disorders cannot be explained by pathology of a single brain region, but arise as a consequence of dysfunctional interactions between brain regions. Schizophrenia, in particular, has been described as a ‘disconnection syndrome’, but similar principles are likely to apply to depression and ADHD (attention deficit hyperactivity disorder). All these diseases are associated with impaired co-ordination of neural population activity, which manifests as abnormal EEG (electroencephalogram) and LFP (local field potential) oscillations both within and across subcortical and cortical brain regions. Importantly, it is increasingly possible to link oscillations and interactions at distinct frequencies to the physiology and/or pathology of distinct classes of neurons and interneurons. Such analyses increasingly implicate abnormal levels, timing or modulation of GABA (γ-aminobutyric acid)-ergic inhibition in brain disease. The present review discusses the evidence suggesting that dysfunction of a particular class of interneurons, marked by their expression of the calcium-binding protein parvalbumin, could contribute to the broad range of neurophysiological and behavioural symptoms characteristic of schizophrenia.

scholarly journals Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing

2021 ◽  
Author(s):  
Thomas Pfeffer ◽  
Christian Keitel ◽  
Daniel S. Kluger ◽  
Anne Keitel ◽  
Alena Russmann ◽  
...  
Keyword(s):  
Low Frequency ◽  
Intermediate Frequency ◽  
Brain Regions ◽  
Neuronal Population ◽  
Neural Population ◽  
Cortical Circuits ◽  
Population Activity ◽  
Linear Relationships ◽  
Cortical Regions ◽  
Aperiodic Component

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has only been characterized for a few selected brain regions so far. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide a comprehensive account of the relationships between fluctuations in arousal and neuronal population activity across the human brain. Exploiting the established link between pupil size and central arousal systems, we performed concurrent magnetoencephalographic (MEG) and pupillographic recordings in a large number of participants, pooled across three laboratories. We found a cascade of effects relative to the peak timing of spontaneous pupil dilations: Decreases in low-frequency (2-8 Hz) activity in temporal and lateral frontal cortex, followed by increased high-frequency (>64 Hz) activity in mid-frontal regions, followed by linear and non-linear relationships with intermediate frequency-range activity (8-32 Hz) in occipito-parietal regions. The non-linearity resembled an inverted U-shape whereby intermediate pupil sizes coincided with maximum 8-32 Hz activity. Pupil-linked arousal also coincided with widespread changes in the structure of the aperiodic component of cortical population activity, indicative of changes in the excitation-inhibition balance in underlying microcircuits. Our results provide a novel basis for studying the arousal modulation of cognitive computations in cortical circuits.

Sign in / Sign up

Export Citation Format

Share Document