scholarly journals Circuit models of low dimensional shared variability in cortical networks

2017 ◽  
Author(s):  
Chengcheng Huang ◽  
Douglas A. Ruff ◽  
Ryan Pyle ◽  
Robert Rosenbaum ◽  
Marlene R. Cohen ◽  
...  
Keyword(s):  
Brain Area ◽  
Inhibitory Neurons ◽  
Cortical Circuits ◽  
Cortical Networks ◽  
Visual Neurons ◽  
Spatial And Temporal Scales ◽  
External Sources ◽  
Inhibitory Coupling ◽  
Low Dimensional

AbstractTrial-to-trial variability is a reflection of the circuitry and cellular physiology that makeup a neuronal network. A pervasive yet puzzling feature of cortical circuits is that despite their complex wiring, population-wide shared spiking variability is low dimensional with all neurons fluctuating en masse. Previous model cortical networks are at loss to explain this global variability, and rather assume it is from external sources. We show that if the spatial and temporal scales of inhibitory coupling match known physiology, model spiking neurons internally generate low dimensional shared variability that captures the properties of in vivo population recordings along the visual pathway. Shifting spatial attention into the receptive field of visual neurons has been shown to reduce low dimensional shared variability within a brain area, yet increase the variability shared between areas. A top-down modulation of inhibitory neurons in our network provides a parsimonious mechanism for this attentional modulation, providing support for our theory of cortical variability. Our work provides a critical and previously missing mechanistic link between observed cortical circuit structure and realistic population-wide shared neuronal variability and its modulation.

scholarly journals Spatiotemporal constraints on optogenetic inactivation in cortical circuits

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Nuo Li ◽  
Susu Chen ◽  
Zengcai V Guo ◽  
Han Chen ◽  
Yan Huo ◽  
...  
Keyword(s):  
Cortical Neurons ◽  
Pyramidal Neurons ◽  
Inhibitory Neurons ◽  
Dependent Manner ◽  
Cortical Circuits ◽  
Neuronal Populations ◽  
Multiple Length Scales ◽  
Dose Dependent ◽  
Reduced Activity

Optogenetics allows manipulations of genetically and spatially defined neuronal populations with excellent temporal control. However, neurons are coupled with other neurons over multiple length scales, and the effects of localized manipulations thus spread beyond the targeted neurons. We benchmarked several optogenetic methods to inactivate small regions of neocortex. Optogenetic excitation of GABAergic neurons produced more effective inactivation than light-gated ion pumps. Transgenic mice expressing the light-dependent chloride channel GtACR1 produced the most potent inactivation. Generally, inactivation spread substantially beyond the photostimulation light, caused by strong coupling between cortical neurons. Over some range of light intensity, optogenetic excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks ('paradoxical effect'). The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, limiting temporal resolution. Our data offer guidance for the design of in vivo optogenetics experiments.

scholarly journals Robust associative learning is sufficient to explain structural and dynamical properties of local cortical circuits

2018 ◽  
Author(s):  
Danke Zhang ◽  
Chi Zhang ◽  
Armen Stepanyants
Keyword(s):  
Associative Learning ◽  
Network Activity ◽  
Inhibitory Neurons ◽  
Cortical Circuits ◽  
Cortical Networks ◽  
Connection Weight ◽  
Postsynaptic Potential ◽  
Weight Distributions ◽  
Network Properties ◽  
Dynamical Properties

ABSTRACTThe ability of neural networks to associate successive states of network activity lies at the basis of many cognitive functions. Hence, we hypothesized that many ubiquitous structural and dynamical properties of local cortical networks result from associative learning. To test this hypothesis, we trained recurrent networks of excitatory and inhibitory neurons on memory sequences of varying lengths and compared network properties to those observed experimentally. We show that when the network is robustly loaded with near-maximum amount of associations it can support, it develops properties that are consistent with the observed probabilities of excitatory and inhibitory connections, shapes of connection weight distributions, overrepresentations of specific 3-neuron motifs, distributions of connection numbers in clusters of 3–8 neurons, sustained, irregular, and asynchronous firing activity, and balance of excitation and inhibition. What is more, memories loaded into the network can be retrieved even in the presence of noise comparable to the baseline variations in the postsynaptic potential. Confluence of these results suggests that many structural and dynamical properties of local cortical networks are simply a byproduct of associative learning.

scholarly journals Aberrant development of excitatory circuits to inhibitory neurons in the primary visual cortex after neonatal binocular enucleation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rongkang Deng ◽  
Joseph P. Y. Kao ◽  
Patrick O. Kanold
Keyword(s):  
Visual Cortex ◽  
Nmda Receptors ◽  
Laser Scanning ◽  
Inhibitory Neurons ◽  
Gabaergic Interneurons ◽  
Cortical Circuits ◽  
Retinal Input ◽  
Layer 4 ◽  
Ampa And Nmda Receptors ◽  
Laser Scanning Photostimulation

AbstractThe development of GABAergic interneurons is important for the functional maturation of cortical circuits. After migrating into the cortex, GABAergic interneurons start to receive glutamatergic connections from cortical excitatory neurons and thus gradually become integrated into cortical circuits. These glutamatergic connections are mediated by glutamate receptors including AMPA and NMDA receptors and the ratio of AMPA to NMDA receptors decreases during development. Since previous studies have shown that retinal input can regulate the early development of connections along the visual pathway, we investigated if the maturation of glutamatergic inputs to GABAergic interneurons in the visual cortex requires retinal input. We mapped the spatial pattern of glutamatergic connections to layer 4 (L4) GABAergic interneurons in mouse visual cortex at around postnatal day (P) 16 by laser-scanning photostimulation and investigated the effect of binocular enucleations at P1/P2 on these patterns. Gad2-positive interneurons in enucleated animals showed an increased fraction of AMPAR-mediated input from L2/3 and a decreased fraction of input from L5/6. Parvalbumin-expressing (PV) interneurons showed similar changes in relative connectivity. NMDAR-only input was largely unchanged by enucleation. Our results show that retinal input sculpts the integration of interneurons into V1 circuits and suggest that the development of AMPAR- and NMDAR-only connections might be regulated differently.

Fast Inhibition Alters First Spike Timing in Auditory Brainstem Neurons

2004 ◽  
Vol 92 (4) ◽  
pp. 2615-2621 ◽  
Author(s):  
Antonio G. Paolini ◽  
Janine C. Clarey ◽  
Karina Needham ◽  
Graeme M. Clark
Keyword(s):  
Lateral Inhibition ◽  
Cochlear Nucleus ◽  
Stellate Cell ◽  
Discharge Rate ◽  
Stellate Cells ◽  
Auditory Pathway ◽  
Auditory Brainstem ◽  
Spike Timing ◽  
Inhibitory Neurons

Within the first processing site of the central auditory pathway, inhibitory neurons (D stellate cells) broadly tuned to tonal frequency project on narrowly tuned, excitatory output neurons (T stellate cells). The latter is thought to provide a topographic representation of sound spectrum, whereas the former is thought to provide lateral inhibition that improves spectral contrast, particularly in noise. In response to pure tones, the overall discharge rate in T stellate cells is unlikely to be suppressed dramatically by D stellate cells because they respond primarily to stimulus onset and provide fast, short-duration inhibition. In vivo intracellular recordings from the ventral cochlear nucleus (VCN) showed that, when tones were presented above or below the characteristic frequency (CF) of a T stellate neuron, they were inhibited during depolarization. This resulted in a delay in the initial action potential produced by T stellate cells. This ability of fast inhibition to alter the first spike timing of a T stellate neuron was confirmed by electrically activating the D stellate cell pathway that arises in the contralateral cochlear nucleus. Delay was also induced when two tones were presented: one at CF and one outside the frequency response area of the T stellate neuron. These findings suggest that the traditional view of lateral inhibition within the VCN should incorporate delay as one of its principle outcomes.

scholarly journals Statistical Comparison of Spike Responses to Natural Stimuli in Monkey Area V1 With Simulated Responses of a Detailed Laminar Network Model for a Patch of V1

2011 ◽  
Vol 105 (2) ◽  
pp. 757-778 ◽  
Author(s):  
Malte J. Rasch ◽  
Klaus Schuch ◽  
Nikos K. Logothetis ◽  
Wolfgang Maass
Keyword(s):  
Network Model ◽  
Network Models ◽  
Cortical Network ◽  
Inhibitory Neurons ◽  
Sensory Stimuli ◽  
Natural Stimuli ◽  
Cortical Areas ◽  
Model Response ◽  
Spiking Activity

A major goal of computational neuroscience is the creation of computer models for cortical areas whose response to sensory stimuli resembles that of cortical areas in vivo in important aspects. It is seldom considered whether the simulated spiking activity is realistic (in a statistical sense) in response to natural stimuli. Because certain statistical properties of spike responses were suggested to facilitate computations in the cortex, acquiring a realistic firing regimen in cortical network models might be a prerequisite for analyzing their computational functions. We present a characterization and comparison of the statistical response properties of the primary visual cortex (V1) in vivo and in silico in response to natural stimuli. We recorded from multiple electrodes in area V1 of 4 macaque monkeys and developed a large state-of-the-art network model for a 5 × 5-mm patch of V1 composed of 35,000 neurons and 3.9 million synapses that integrates previously published anatomical and physiological details. By quantitative comparison of the model response to the “statistical fingerprint” of responses in vivo, we find that our model for a patch of V1 responds to the same movie in a way which matches the statistical structure of the recorded data surprisingly well. The deviation between the firing regimen of the model and the in vivo data are on the same level as deviations among monkeys and sessions. This suggests that, despite strong simplifications and abstractions of cortical network models, they are nevertheless capable of generating realistic spiking activity. To reach a realistic firing state, it was not only necessary to include both N -methyl-d-aspartate and GABAB synaptic conductances in our model, but also to markedly increase the strength of excitatory synapses onto inhibitory neurons (>2-fold) in comparison to literature values, hinting at the importance to carefully adjust the effect of inhibition for achieving realistic dynamics in current network models.

scholarly journals Circuit Models of Low-Dimensional Shared Variability in Cortical Networks

Neuron ◽  
2019 ◽  
Vol 101 (2) ◽  
pp. 337-348.e4 ◽  
Author(s):  
Chengcheng Huang ◽  
Douglas A. Ruff ◽  
Ryan Pyle ◽  
Robert Rosenbaum ◽  
Marlene R. Cohen ◽  
...  
Keyword(s):  
Cortical Networks ◽  
Low Dimensional

scholarly journals Seizures start as silent microseizures by neuronal ensembles

2018 ◽  
Author(s):  
Michael Wenzel ◽  
Jordan P. Hamm ◽  
Darcy S. Peterka ◽  
Rafael MD Yuste
Keyword(s):  
Calcium Imaging ◽  
Travelling Wave ◽  
Inhibitory Neurons ◽  
Neural Activation ◽  
Calcium Dynamics ◽  
Neuronal Ensembles ◽  
Two Photon ◽  
Step Model

AbstractUnderstanding seizure formation and spread remains a critical goal of epilepsy research. While many studies have documented seizure spread, it remains mysterious how they start. We used fast in-vivo two-photon calcium imaging to reconstruct, at cellular resolution, the dynamics of focal cortical seizures as they emerge in epileptic foci (intrafocal), and subsequently propagate (extrafocal). We find that seizures start as intrafocal coactivation of small numbers of neurons (ensembles), which are electrographically silent. These silent “microseizures” expand saltatorily until they break into neighboring cortex, where they progress smoothly and first become detectable by LFP. Surprisingly, we find spatially heterogeneous calcium dynamics of local PV interneuron sub-populations, which rules out a simple role of inhibitory neurons during seizures. We propose a two-step model for the circuit mechanisms of focal seizures, where neuronal ensembles first generate a silent microseizure, followed by widespread neural activation in a travelling wave, which is then detected electrophysiologically.

scholarly journals Homeostatic plasticity and external input shape neural network dynamics

2018 ◽  
Author(s):  
Johannes Zierenberg ◽  
Jens Wilting ◽  
Viola Priesemann
Keyword(s):  
Neural Network ◽  
Brain Area ◽  
External Input ◽  
Homeostatic Plasticity ◽  
Dynamic State ◽  
Network Topologies ◽  
Neural Network Dynamics ◽  
Spiking Activity

In vitro and in vivo spiking activity clearly differ. Whereas networks in vitro develop strong bursts separated by periods of very little spiking activity, in vivo cortical networks show continuous activity. This is puzzling considering that both networks presumably share similar single-neuron dynamics and plasticity rules. We propose that the defining difference between in vitro and in vivo dynamics is the strength of external input. In vitro, networks are virtually isolated, whereas in vivo every brain area receives continuous input. We analyze a model of spiking neurons in which the input strength, mediated by spike rate homeostasis, determines the characteristics of the dynamical state. In more detail, our analytical and numerical results on various network topologies show consistently that under increasing input, homeostatic plasticity generates distinct dynamic states, from bursting, to close-to-critical, reverberating and irregular states. This implies that the dynamic state of a neural network is not fixed but can readily adapt to the input strengths. Indeed, our results match experimental spike recordings in vitro and in vivo: the in vitro bursting behavior is consistent with a state generated by very low network input (< 0.1%), whereas in vivo activity suggests that on the order of 1% recorded spikes are input-driven, resulting in reverberating dynamics. Importantly, this predicts that one can abolish the ubiquitous bursts of in vitro preparations, and instead impose dynamics comparable to in vivo activity by exposing the system to weak long-term stimulation, thereby opening new paths to establish an in vivo-like assay in vitro for basic as well as neurological studies.

scholarly journals Functional selectivity and specific connectivity of inhibitory neurons in primary visual cortex

2018 ◽  
Author(s):  
Petr Znamenskiy ◽  
Mean-Hwan Kim ◽  
Dylan R. Muir ◽  
Maria Florencia Iacaruso ◽  
Sonja B. Hofer ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Pyramidal Cells ◽  
Fine Tuning ◽  
Inhibitory Neurons ◽  
Local Network ◽  
Cortical Circuits ◽  
Sensory Stimuli ◽  
Excitatory Neurons ◽  
Strong Excitation

In the cerebral cortex, the interaction of excitatory and inhibitory synaptic inputs shapes the responses of neurons to sensory stimuli, stabilizes network dynamics1 and improves the efficiency and robustness of the neural code2–4. Excitatory neurons receive inhibitory inputs that track excitation5–8. However, how this co-tuning of excitation and inhibition is achieved by cortical circuits is unclear, since inhibitory interneurons are thought to pool the inputs of nearby excitatory cells and provide them with non-specific inhibition proportional to the activity of the local network9–13. Here we show that although parvalbumin-expressing (PV) inhibitory cells in mouse primary visual cortex make connections with the majority of nearby pyramidal cells, the strength of their synaptic connections is structured according to the similarity of the cells’ responses. Individual PV cells strongly inhibit those pyramidal cells that provide them with strong excitation and share their visual selectivity. This fine-tuning of synaptic weights supports co-tuning of inhibitory and excitatory inputs onto individual pyramidal cells despite dense connectivity between inhibitory and excitatory neurons. Our results indicate that individual PV cells are preferentially integrated into subnetworks of inter-connected, co-tuned pyramidal cells, stabilising their recurrent dynamics. Conversely, weak but dense inhibitory connectivity between subnetworks is sufficient to support competition between them, de-correlating their output. We suggest that the history and structure of correlated firing adjusts the weights of both inhibitory and excitatory connections, supporting stable amplification and selective recruitment of cortical subnetworks.

scholarly journals Subanesthetic ketamine reactivates adult cortical plasticity to restore vision from amblyopia

2020 ◽  
Author(s):  
Steven F. Grieco ◽  
Xin Qiao ◽  
Xiaoting Zheng ◽  
Yongjun Liu ◽  
Lujia Chen ◽  
...  
Keyword(s):  
Functional Recovery ◽  
Neural Plasticity ◽  
Cortical Plasticity ◽  
Brain Plasticity ◽  
Excitatory Input ◽  
Inhibitory Neurons ◽  
List Type ◽  
Visual Cortical

SummarySubanesthetic ketamine evokes rapid and long-lasting antidepressant effects in human patients. The mechanism for ketamine’s effects remains elusive, but ketamine may broadly modulate brain plasticity processes. We show that single-dose ketamine reactivates adult mouse visual cortical plasticity and promotes functional recovery of visual acuity defects from amblyopia. Ketamine specifically induces down-regulation of neuregulin-1 (NRG1) expression in parvalbumin-expressing (PV) inhibitory neurons in mouse visual cortex. NRG1 downregulation in PV neurons co-tracks both the fast onset and sustained decreases in synaptic inhibition to excitatory neurons, along with reduced synaptic excitation to PV neurons in vitro and in vivo following a single ketamine treatment. These effects are blocked by exogenous NRG1 as well as PV targeted receptor knockout. Thus ketamine reactivation of adult visual cortical plasticity is mediated through rapid and sustained cortical disinhibition via downregulation of PV-specific NRG1 signaling. Our findings reveal the neural plasticity-based mechanism for ketamine-mediated functional recovery from adult amblyopia.Highlights○ Disinhibition of excitatory cells by ketamine occurs in a fast and sustained manner○ Ketamine evokes NRG1 downregulation and excitatory input loss to PV cells○ Ketamine induced plasticity is blocked by exogenous NRG1 or its receptor knockout○ PV inhibitory cells are the initial functional locus underlying ketamine’s effects

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