scholarly journals Synchronization through uncorrelated noise in excitatory-inhibitory networks

2021 ◽  
Author(s):  
Lucas Rebscher ◽  
Klaus Obermayer ◽  
Christoph Metzner
Keyword(s):  
Information Transfer ◽  
Gamma Oscillations ◽  
Inhibitory Neurons ◽  
Synaptic Coupling ◽  
Uncorrelated Noise ◽  
Beneficial Effects ◽  
Gamma Rhythm ◽  
Modelling Studies ◽  
Interacting Networks ◽  
Inhibitory Networks

Gamma rhythms play a major role in many different processes in the brain, such as attention, working memory and sensory processing. While typically considered detrimental, counterintuitively noise can sometimes have beneficial effects on communication and information transfer. Recently, Meng and Riecke showed that synchronization of interacting networks of inhibitory neurons increases while synchronization within these networks decreases when neurons are subject to uncorrelated noise. However, experimental and modelling studies point towards an important role of the pyramidal-interneuronal network gamma (PING) mechanism in the cortex. Therefore, we investigated the effect of uncorrelated noise on the communication between excitatory-inhibitory networks producing gamma oscillations via a PING mechanism. Our results suggest that synaptic noise can have a supporting role in facilitating inter-regional communication and that noise-induced synchronization between networks is generated via a different mechanism than when synchronization is mediated by strong synaptic coupling. Noise-induced synchronization is achieved by lowering synchronization within networks which allows the respective other network to impose its own gamma rhythm resulting in synchronization between networks.

scholarly journals Inhibitory networks orchestrate the self-organization of computational function in cortical microcircuit motifs through STDP

2017 ◽  
Author(s):  
Stefan Häusler ◽  
Wolfgang Maass
Keyword(s):  
Lateral Inhibition ◽  
Network Motif ◽  
Pyramidal Cells ◽  
Theoretical Work ◽  
Spike Timing ◽  
The Self ◽  
Inhibitory Neurons ◽  
Self Organization ◽  
Interacting Networks ◽  
Inhibitory Networks

AbstractInterneurons have diverse morphological and physiological characteristics that potentially contribute to the emergence of powerful computational properties of cortical networks. We investigate the functional role of inhibitory subnetworks in the arguably most common network motif of cortical microcircuits: ensembles of pyramidal cells (PCs) with lateral inhibition, commonly referred to as Winner-Take-All networks. Recent theoretical work has shown that spike-timing-dependent plasticity installs in this network motif an important and ubiquitously useful self-organization process: The emergence of sparse codes and Bayesian inference for repeatedly occurring high-dimensional input patterns. However, this link has so far only been established for strongly simplified models with a symbolic implementation of lateral inhibition, rather than through the interaction of PCs with known types of interneurons. We close this gap in this article, and show that the interaction of PCs with two types of inhibitory networks, that reflect salient properties of somatic-targeting neurons (e.g. basket cells) and dendritic-targeting neurons (e.g. Martinotti cells), provides a good approximation to the theoretically optimal lateral inhibition needed for the self-organization of these network motifs. We provide a step towards unraveling the functional roles of interacting networks of excitatory and inhibitory neurons from the perspective of emergent neural computation.

scholarly journals Neural Dynamics and Gamma Oscillation on a Hybrid Excitatory-Inhibitory Complex Network (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13957-13958
Author(s):  
Yuan Wang ◽  
Xia Shi ◽  
Bo Cheng ◽  
Junliang Chen
Keyword(s):  
Complex Network ◽  
Small World ◽  
Gamma Oscillations ◽  
Gamma Oscillation ◽  
Inhibitory Neurons ◽  
Critical Parameters ◽  
Neural Dynamics ◽  
Gamma Rhythm ◽  
Excitatory Neurons ◽  
Fast Spiking

This paper investigates the neural dynamics and gamma oscillation on a complex network with excitatory and inhibitory neurons (E-I network), as such network is ubiquitous in the brain. The system consists of a small-world network of neurons, which are emulated by Izhikevich model. Moreover, mixed Regular Spiking (RS) and Chattering (CH) neurons are considered to imitate excitatory neurons, and Fast Spiking (FS) neurons are used to mimic inhibitory neurons. Besides, the relationship between synchronization and gamma rhythm is explored by adjusting the critical parameters of our model. Experiments visually demonstrate that the gamma oscillations are generated by synchronous behaviors of our neural network. We also discover that the Chattering(CH) excitatory neurons can make the system easier to synchronize.

scholarly journals Impaired spike-gamma coupling of area CA3 fast-spiking interneurons as the earliest functional impairment in the AppNL-G-F mouse model of Alzheimer’s disease

2021 ◽  
Author(s):  
Luis Enrique Arroyo-García ◽  
Arturo G. Isla ◽  
Yuniesky Andrade-Talavera ◽  
Hugo Balleza-Tapia ◽  
Raúl Loera-Valencia ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mouse Model ◽  
Functional Impairment ◽  
Amyloid Β ◽  
Gamma Oscillations ◽  
Gamma Oscillation ◽  
Gamma Rhythm ◽  
Fast Spiking

AbstractIn Alzheimer’s disease (AD) the accumulation of amyloid-β (Aβ) correlates with degradation of cognition-relevant gamma oscillations. The gamma rhythm relies on proper neuronal spike-gamma coupling, specifically of fast-spiking interneurons (FSN). Here we tested the hypothesis that decrease in gamma power and FSN synchrony precede amyloid plaque deposition and cognitive impairment in AppNL-G-F knock-in mice (AppNL-G-F). The aim of the study was to evaluate the amyloidogenic pathology progression in the novel AppNL-G-F mouse model using in vitro electrophysiological network analysis. Using patch clamp of FSNs and pyramidal cells (PCs) with simultaneous gamma oscillation recordings, we compared the activity of the hippocampal network of wild-type mice (WT) and the AppNL-G-F mice at four disease stages (1, 2, 4, and 6 months of age). We found a severe degradation of gamma oscillation power that is independent of, and precedes Aβ plaque formation, and the cognitive impairment reported previously in this animal model. The degradation correlates with increased Aβ1-42 concentration in the brain. Analysis on the cellular level showed an impaired spike-gamma coupling of FSN from 2 months of age that correlates with the degradation of gamma oscillations. From 6 months of age PC firing becomes desynchronized also, correlating with reports in the literature of robust Aβ plaque pathology and cognitive impairment in the AppNL-G-F mice. This study provides evidence that impaired FSN spike-gamma coupling is one of the earliest functional impairment caused by the amyloidogenic pathology progression likely is the main cause for the degradation of gamma oscillations and consequent cognitive impairment. Our data suggests that therapeutic approaches should be aimed at restoring normal FSN spike-gamma coupling and not just removal of Aβ.

scholarly journals Effects of optogenetic stimulation of basal forebrain parvalbumin neurons on Alzheimer’s disease pathology

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Caroline A. Wilson ◽  
Sarah Fouda ◽  
Shuzo Sakata
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Basal Forebrain ◽  
Gamma Oscillations ◽  
Cortical Region ◽  
Sensory Stimuli ◽  
Beneficial Effects ◽  
Amyloid Load ◽  
5Xfad Mice ◽  
Frontal Cortical Region

Abstract Neuronal activity can modify Alzheimer’s disease pathology. Overexcitation of neurons can facilitate disease progression whereas the induction of cortical gamma oscillations can reduce amyloid load and improve cognitive functions in mouse models. Although previous studies have induced cortical gamma oscillations by either optogenetic activation of cortical parvalbumin-positive (PV+) neurons or sensory stimuli, it is still unclear whether other approaches to induce gamma oscillations can also be beneficial. Here we show that optogenetic activation of PV+ neurons in the basal forebrain (BF) increases amyloid burden, rather than reducing it. We applied 40 Hz optical stimulation in the BF by expressing channelrhodopsin-2 (ChR2) in PV+ neurons of 5xFAD mice. After 1-h induction of cortical gamma oscillations over three days, we observed the increase in the concentration of amyloid-β42 in the frontal cortical region, but not amyloid-β40. Amyloid plaques were accumulated more in the medial prefrontal cortex and the septal nuclei, both of which are targets of BF PV+ neurons. These results suggest that beneficial effects of cortical gamma oscillations on Alzheimer’s disease pathology can depend on the induction mechanisms of cortical gamma oscillations.

scholarly journals Population dynamics of the modified theta model: macroscopic phase reduction and bifurcation analysis link microscopic neuronal interactions to macroscopic gamma oscillation

2014 ◽  
Vol 11 (95) ◽  
pp. 20140058 ◽  
Author(s):  
Kiyoshi Kotani ◽  
Ikuhiro Yamaguchi ◽  
Lui Yoshida ◽  
Yasuhiko Jimbo ◽  
G. Bard Ermentrout
Keyword(s):  
Bifurcation Analysis ◽  
Field Potential ◽  
Reversal Potential ◽  
Planck Equation ◽  
Gamma Oscillations ◽  
Gamma Oscillation ◽  
Synaptic Coupling ◽  
Time Constants ◽  
Shunting Inhibition ◽  
Synaptic Interactions

Gamma oscillations of the local field potential are organized by collective dynamics of numerous neurons and have many functional roles in cognition and/or attention. To mathematically and physiologically analyse relationships between individual inhibitory neurons and macroscopic oscillations, we derive a modification of the theta model, which possesses voltage-dependent dynamics with appropriate synaptic interactions. Bifurcation analysis of the corresponding Fokker–Planck equation (FPE) enables us to consider how synaptic interactions organize collective oscillations. We also develop the adjoint method (infinitesimal phase resetting curve) for simultaneous equations consisting of ordinary differential equations representing synaptic dynamics and a partial differential equation for determining the probability distribution of the membrane potential. This method provides a macroscopic phase response function (PRF), which gives insights into how it is modulated by external perturbation or internal changes of parameters. We investigate the effects of synaptic time constants and shunting inhibition on these gamma oscillations. The sensitivity of rising and decaying time constants is analysed in the oscillatory parameter regions; we find that these sensitivities are not largely dependent on rate of synaptic coupling but, rather, on current and noise intensity. Analyses of shunting inhibition reveal that it can affect both promotion and elimination of gamma oscillations. When the macroscopic oscillation is far from the bifurcation, shunting promotes the gamma oscillations and the PRF becomes flatter as the reversal potential of the synapse increases, indicating the insensitivity of gamma oscillations to perturbations. By contrast, when the macroscopic oscillation is near the bifurcation, shunting eliminates gamma oscillations and a stable firing state appears. More interestingly, under appropriate balance of parameters, two branches of bifurcation are found in our analysis of the FPE. In this case, shunting inhibition can effect both promotion and elimination of the gamma oscillation depending only on the reversal potential.

scholarly journals Orientation and color tuning of the human visual gamma rhythm

2021 ◽  
Author(s):  
Ye Li ◽  
William Bosking ◽  
Michael S Beauchamp ◽  
Sameer A Sheth ◽  
Daniel Yoshor ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Brain Activity ◽  
Population Level ◽  
Gamma Oscillations ◽  
Cell Orientation ◽  
Population Activity ◽  
Color Tuning ◽  
Human Visual Cortex ◽  
Gamma Rhythm

Narrowband gamma oscillations (NBG: ~20-60Hz) in visual cortex reflect rhythmic fluctuations in population activity generated by underlying circuits tuned for stimulus location, orientation, and color. Consequently, the amplitude and frequency of induced NBG activity is highly sensitive to these stimulus features. For example, in the non-human primate, NBG displays biases in orientation and color tuning at the population level. Such biases may relate to recent reports describing the large-scale organization of single-cell orientation and color tuning in visual cortex, thus providing a potential bridge between measurements made at different scales. Similar biases in NBG population tuning have been predicted to exist in the human visual cortex, but this has yet to be fully examined. Using intracranial recordings from human visual cortex, we investigated the tuning of NBG to orientation and color, both independently and in conjunction. NBG was shown to display a cardinal orientation bias (horizontal) and also an end- and mid-spectral color bias (red/blue and green). When jointly probed, the cardinal bias for orientation was attenuated and an end-spectral preference for red and blue predominated. These data both elaborate on the close, yet complex, link between the population dynamics driving NBG oscillations and known feature selectivity biases in visual cortex, adding to a growing set of stimulus dependencies associated with the genesis of NBG. Together, these two factors may provide a fruitful testing ground for examining multi-scale models of brain activity, and impose new constraints on the functional significance of the visual gamma rhythm.

A MULTI-LAYER NEURAL-MASS MODEL FOR LEARNING SEQUENCES USING THETA/GAMMA OSCILLATIONS

2013 ◽  
Vol 23 (03) ◽  
pp. 1250036 ◽  
Author(s):  
FILIPPO CONA ◽  
MAURO URSINO
Keyword(s):  
Associative Memory ◽  
Gamma Oscillations ◽  
Neural Mass Model ◽  
Mass Model ◽  
The Third ◽  
Gamma Range ◽  
Gamma Rhythm ◽  
Neural Mass ◽  
Phase Precession ◽  
Theta Range

A neural mass model for the memorization of sequences is presented. It exploits three layers of cortical columns that generate a theta/gamma rhythm. The first layer implements an auto-associative memory working in the theta range; the second segments objects in the gamma range; finally, the feedback interactions between the third and the second layers realize a hetero-associative memory for learning a sequence. After training with Hebbian and anti-Hebbian rules, the network recovers sequences and accounts for the phase-precession phenomenon.

scholarly journals Duration analysis using matching pursuit algorithm reveals longer bouts of gamma rhythm

2018 ◽  
Vol 119 (3) ◽  
pp. 808-821 ◽  
Author(s):  
Subhash Chandran KS ◽  
Chandra Sekhar Seelamantula ◽  
Supratim Ray
Keyword(s):  
Reference Frame ◽  
Matching Pursuit ◽  
Temporal Structure ◽  
Simulated Data ◽  
Gamma Oscillations ◽  
Center Frequency ◽  
Temporal Reference ◽  
Gamma Rhythm ◽  
Matching Pursuit Algorithm ◽  
Spiking Activity

The gamma rhythm (30–80 Hz), often associated with high-level cortical functions, is believed to provide a temporal reference frame for spiking activity, for which it should have a stable center frequency and linear phase for an extended duration. However, recent studies that have estimated the power and phase of gamma as a function of time suggest that gamma occurs in short bursts and lacks the temporal structure required to act as a reference frame. Here, we show that the bursty appearance of gamma arises from the variability in the spectral estimator used in these studies. To overcome this problem, we use another duration estimator based on a matching pursuit algorithm that robustly estimates the duration of gamma in simulated data. Applying this algorithm to gamma oscillations recorded from implanted microelectrodes in the primary visual cortex of awake monkeys, we show that the median gamma duration is greater than 300 ms, which is three times longer than previously reported values. NEW & NOTEWORTHY Gamma oscillations (30–80 Hz) have been hypothesized to provide a temporal reference frame for coordination of spiking activity, but recent studies have shown that gamma occurs in very short bursts. We show that existing techniques have severely underestimated the rhythm duration, use a technique based on the Matching Pursuit algorithm, which provides a robust estimate of the duration, and show that the median duration of gamma is greater than 300 ms, much longer than previous estimates.

A NEUROBIOLOGICAL THEORY OF MEANING IN PERCEPTION PART III: MULTIPLE CORTICAL AREAS SYNCHRONIZE WITHOUT LOSS OF LOCAL AUTONOMY

2003 ◽  
Vol 13 (10) ◽  
pp. 2845-2856 ◽  
Author(s):  
WALTER J. FREEMAN ◽  
GYöNGYI GAÁL ◽  
REBECKA JORSTEN
Keyword(s):  
Information Transfer ◽  
Phase Locking ◽  
Pulse Frequency ◽  
Inhibitory Neurons ◽  
Oscillatory Activity ◽  
Electrode Arrays ◽  
Ensemble Averaging ◽  
Pulse Frequency Modulation ◽  
Cortical Areas ◽  
Gamma Range

Information transfer and integration among functionally distinct areas of cerebral cortex of oscillatory activity require some degree of phase synchrony of the trains of action potentials that carry the information prior to the integration. However, propagation delays are obligatory. Delays vary with the lengths and conduction velocities of the axons carrying the information, causing phase dispersion. In order to determine how synchrony is achieved despite dispersion, we recorded EEG signals from multiple electrode arrays on five cortical areas in cats and rabbits, that had been trained to discriminate visual or auditory conditioned stimuli. Analysis by time-lagged correlation, multiple correlation and PCA, showed that maximal correlation was at zero lag and averaged 0.7, indicating that 50% of the power in the gamma range among the five areas was at zero lag irrespective of phase or frequency. There were no stimulus-related episodes of transiently increased phase locking among the areas, nor EEG "bursts" of transiently increased amplitude above the sustained level of synchrony. Three operations were identified to account for the sustained correlation. Cortices broadcast their outputs over divergent–convergent axonal pathways that performed spatial ensemble averaging; synaptic interactions between excitatory and inhibitory neurons in cortex operated as band pass filters for gamma; and signal coarse-graining by pulse frequency modulation at trigger zones enhanced correlation. The conclusion is that these three operations enable continuous linkage of multiple cortical areas by activity in the gamma range, providing the basis for coordinated cortical output to other parts of the brain, despite varying axonal conduction delays, something like the back plane of a main frame computer.

scholarly journals Sensory-driven and spontaneous gamma oscillations engage distinct cortical circuitry

2016 ◽  
Vol 115 (4) ◽  
pp. 1821-1835 ◽  
Author(s):  
Cristin G. Welle ◽  
Diego Contreras
Keyword(s):  
Visual Cortex ◽  
Visual Stimulation ◽  
Oscillation Amplitude ◽  
Gamma Oscillations ◽  
Gamma Oscillation ◽  
Inhibitory Neurons ◽  
Sensory Representation ◽  
Cortical Circuitry ◽  
Mouse Visual Cortex

Gamma oscillations are a robust component of sensory responses but are also part of the background spontaneous activity of the brain. To determine whether the properties of gamma oscillations in cortex are specific to their mechanism of generation, we compared in mouse visual cortex in vivo the laminar geometry and single-neuron rhythmicity of oscillations produced during sensory representation with those occurring spontaneously in the absence of stimulation. In mouse visual cortex under anesthesia (isoflurane and xylazine), visual stimulation triggered oscillations mainly between 20 and 50 Hz, which, because of their similar functional significance to gamma oscillations in higher mammals, we define here as gamma range. Sensory representation in visual cortex specifically increased gamma oscillation amplitude in the supragranular (L2/3) and granular (L4) layers and strongly entrained putative excitatory and inhibitory neurons in infragranular layers, while spontaneous gamma oscillations were distributed evenly through the cortical depth and primarily entrained putative inhibitory neurons in the infragranular (L5/6) cortical layers. The difference in laminar distribution of gamma oscillations during the two different conditions may result from differences in the source of excitatory input to the cortex. In addition, modulation of superficial gamma oscillation amplitude did not result in a corresponding change in deep-layer oscillations, suggesting that superficial and deep layers of cortex may utilize independent but related networks for gamma generation. These results demonstrate that stimulus-driven gamma oscillations engage cortical circuitry in a manner distinct from spontaneous oscillations and suggest multiple networks for the generation of gamma oscillations in cortex.

Sign in / Sign up

Export Citation Format

Share Document