Memories in a network with excitatory and inhibitory plasticity are encoded in the spiking irregularity

Cell assemblies are thought to be the substrate of memory in the brain. Theoretical studies have previously shown that assemblies can be formed in networks with multiple types of plasticity. But how exactly they are formed and how they encode information is yet to be fully understood. One possibility is that memories are stored in silent assemblies. Here we used a computational model to study the formation of silent assemblies in a network of spiking neurons with excitatory and inhibitory plasticity. We found that even though the formed assemblies were silent in terms of mean firing rate, they had an increased coefficient of variation of inter-spike intervals. We also found that this spiking irregularity could be read out with support of short-term plasticity, and that it could contribute to the longevity of memories.

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Memories in a network with excitatory and inhibitory plasticity are encoded in the spiking irregularity

10.1101/2021.07.22.453370 ◽

2021 ◽

Author(s):

Julia V Gallinaro ◽

Claudia Clopath

Keyword(s):

Computational Model ◽

Firing Rate ◽

Coefficient Of Variation ◽

Spiking Neurons ◽

Theoretical Studies ◽

Short Term ◽

Cell Assemblies ◽

Short Term Plasticity ◽

Inhibitory Plasticity ◽

The Brain

Cell assemblies are thought to be the substrate of memory in the brain. Theoretical studies have previously shown that assemblies can be formed in networks with multiple types of plasticity. But how exactly they are formed and how they encode information is yet to be fully understood. One possibility is that memories are stored in silent assemblies. Here we used a computational model to study the formation of silent assemblies in a network of spiking neurons with excitatory and inhibitory plasticity. We found that even though the formed assemblies were silent in terms of mean firing rate, they had an increased coefficient of variation of inter-spike intervals. We also found that this spiking irregularity could be readout with support of short-term plasticity, and that it could contribute to the longevity of memories.

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SIMULATING VERTICAL AND HORIZONTAL INHIBITION WITH SHORT-TERM DYNAMICS IN A MULTI-COLUMN MULTI-LAYER MODEL OF NEOCORTEX

International Journal of Neural Systems ◽

10.1142/s0129065714400024 ◽

2014 ◽

Vol 24 (05) ◽

pp. 1440002 ◽

Cited By ~ 19

Author(s):

BEATA STRACK ◽

KIMBERLE M. JACOBS ◽

KRZYSZTOF J. CIOS

Keyword(s):

Epileptiform Activity ◽

Inhibitory Neuron ◽

Normal Function ◽

Spiking Neurons ◽

Layer Model ◽

Neuronal Connectivity ◽

Short Term ◽

Short Term Plasticity ◽

Low Threshold ◽

Fast Spiking

The paper introduces a multi-layer multi-column model of the cortex that uses four different neuron types and short-term plasticity dynamics. It was designed with details of neuronal connectivity available in the literature and meets these conditions: (1) biologically accurate laminar and columnar flows of activity, (2) normal function of low-threshold spiking and fast spiking neurons, and (3) ability to generate different stages of epileptiform activity. With these characteristics the model allows for modeling lesioned or malformed cortex, i.e. examine properties of developmentally malformed cortex in which the balance between inhibitory neuron subtypes is disturbed.

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Short-term plasticity in a computational model of the tail-withdrawal circuit in Aplysia

Neurocomputing ◽

10.1016/j.neucom.2006.10.080 ◽

2007 ◽

Vol 70 (10-12) ◽

pp. 1993-1999 ◽

Cited By ~ 3

Author(s):

Douglas A. Baxter ◽

John H. Byrne

Keyword(s):

Computational Model ◽

Short Term ◽

Short Term Plasticity

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Music Changes the Brain

The Oxford Handbook of Music and the Body ◽

10.1093/oxfordhb/9780190636234.013.5 ◽

2018 ◽

pp. 98-111

Author(s):

Paul Lennard

Keyword(s):

Brain Development ◽

Language Processing ◽

Cerebral Hemisphere ◽

Critical Periods ◽

Short Term ◽

Music Training ◽

Short Term Plasticity ◽

Process Music ◽

The Brain

This chapter examines ways in which listening to or making music changes our brains morphologically and functionally. Evidence for short-term plasticity in response to music is reviewed. Critical periods early in life, when exposure to music and music training can alter brain development, are summarized. Evidence that the brains of musicians and nonmusicians differ is presented. It is shown that nonmusicians process music primarily in the nondominant cerebral hemisphere, while musicians have structural and functional shifts of lateralization to the dominant cerebral hemisphere. This shift is discussed in terms of a theory that nonmusicians process music holistically in the nondominant cerebral hemisphere, while trained musicians tend to apply syntax to music, using language-processing circuitry in the dominant cerebral hemisphere.

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Towards biologically constrained attractor models of schizophrenia

10.31234/osf.io/uxg2a ◽

2021 ◽

Author(s):

Heike Stein ◽

Joao Barbosa ◽

Albert Compte

Keyword(s):

Working Memory ◽

Synaptic Transmission ◽

Firing Rate ◽

Experimental Evidence ◽

Cognitive Deficits ◽

Critical Points ◽

Network Models ◽

Short Term ◽

Short Term Plasticity ◽

Network Simulations

Alterations in neuromodulation or synaptic transmission in biophysical attractor network models, as proposed by the dominant dopaminergic and glutamatergic theories of schizophrenia, successfully mimic working memory (WM) deficits in people with schizophrenia (PSZ). Yet, multiple, often opposing circuit mechanisms can lead to the same behavioral patterns in these network models. Here, we critically revise the computational and experimental literature that links NMDAR hypofunction to WM precision loss in PSZ. We show in network simulations that currently available experimental evidence cannot set apart competing mechanistic accounts, and critical points to resolve are firing rate tuning and shared noise modulations by E/I ratio alterations through NMDAR blockade, and possible concomitant deficits in short-term plasticity. We argue that these concerted experimental and computational efforts will lead to a better understanding of the neurobiology underlying cognitive deficits in PSZ.

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Coincident glutamatergic depolarizations enhance GABAA receptor-dependent Cl- influx in mature and suppress Cl- efflux in immature neurons

10.1101/2020.08.18.255323 ◽

2020 ◽

Author(s):

Aniello Lombardi ◽

Peter Jedlicka ◽

Heiko J. Luhmann ◽

Werner Kilb

Keyword(s):

Gaba Receptors ◽

Temporal Correlation ◽

Gabaergic Inhibition ◽

Relevant Factor ◽

Decay Kinetics ◽

Short Term ◽

Substantial Impact ◽

Short Term Plasticity ◽

The Impact ◽

The Brain

AbstractThe impact of GABAergic transmission on neuronal excitability depends on the Cl−-gradient across membranes. However, the Cl−-fluxes through GABAA receptors alter the intracellular Cl− concentration ([Cl−]i) and in turn attenuate GABAergic responses, a process termed ionic plasticity. Recently it has been shown that coincident glutamatergic inputs significantly affect ionic plasticity. Yet how the [Cl−]i changes depend on the properties of glutamatergic inputs and their spatiotemporal relation to GABAergic stimuli is unknown. To investigate this issue, we used compartmental biophysical models of Cl− dynamics simulating either a simple ball-and-stick topology or a reconstructed immature CA3 neuron. These computational experiments demonstrated that glutamatergic co-stimulation enhances GABA receptor-mediated Cl− influx at low and attenuates or reverses the Cl− efflux at high initial [Cl−]i. The size of glutamatergic influence on GABAergic Cl−-fluxes depends on the conductance, decay kinetics, and localization of glutamatergic inputs. Surprisingly, the glutamatergic shift in GABAergic Cl−-fluxes is invariant to latencies between GABAergic and glutamatergic inputs over a substantial interval. In agreement with experimental data, simulations in a reconstructed CA3 pyramidal neuron with physiological patterns of correlated activity revealed that coincident glutamatergic synaptic inputs contribute significantly to the activity-dependent [Cl−]i changes. Whereas the influence of spatial correlation between distributed glutamatergic and GABAergic inputs was negligible, their temporal correlation played a significant role. In summary, our results demonstrate that glutamatergic co-stimulation had a substantial impact on ionic plasticity of GABAergic responses, enhancing the destabilization of GABAergic inhibition in the mature nervous systems, but suppressing GABAergic [Cl−]i changes in the immature brain. Therefore, glutamatergic shift in GABAergic Cl−-fluxes should be considered as a relevant factor of short term plasticity.Author SummaryInformation processing in the brain requires that excitation and inhibition are balanced. The main inhibitory neurotransmitter in the brain is gamma-amino-butyric acid (GABA). GABA actions depend on the Cl−-gradient, but activation of ionotropic GABA receptors causes Cl−-fluxes and thus reduces GABAergic inhibition. Here, we investigated how a coincident membrane depolarization by excitatory, glutamatergic synapses influences GABA-induced Cl−-fluxes using a biophysical compartmental model of Cl− dynamics, simulating either simple or realistic neuron topologies. We demonstrate that glutamatergic co-stimulation directly affects GABA-induced Cl−-fluxes, with the size of glutamatergic effects depending on the conductance, the decay kinetics, and localization of glutamatergic inputs. We also show that the glutamatergic shift in GABAergic Cl−-fluxes is surprisingly stable over a substantial range of latencies between glutamatergic and GABAergic inputs. We conclude from these results that glutamatergic co-stimulation alters GABAergic Cl−-fluxes and in turn affects the strength of GABAergic inhibition. These coincidence-dependent ionic changes should be considered as a relevant factor of short term plasticity in the CNS.

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The Cochlear Nuclei

The Oxford Handbook of the Auditory Brainstem ◽

10.1093/oxfordhb/9780190849061.013.4 ◽

2018 ◽

pp. 94-122 ◽

Cited By ~ 1

Author(s):

Donata Oertel ◽

Xiao-Jie Cao ◽

Alberto Recio-Spinoso

Keyword(s):

Sensory Information ◽

Short Term ◽

Temporal Precision ◽

Short Term Plasticity ◽

Ventral Cochlear Nucleus ◽

Cochlear Nuclei ◽

Electrophysiological Studies ◽

The Face ◽

The Brain

Plasticity in neuronal circuits is essential for optimizing connections as animals develop and for adapting to injuries and aging, but it can also distort the processing, as well as compromise the conveyance of ongoing sensory information. This chapter summarizes evidence from electrophysiological studies in slices and in vivo that shows how remarkably robust signaling is in principal cells of the ventral cochlear nucleus. Even in the face of short-term plasticity, these neurons signal rapidly and with temporal precision. They can relay ongoing acoustic information from the cochlea to the brain largely independently of sounds to which they were exposed previously.

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Short-term plasticity at cerebellar granule cell to molecular layer interneuron synapses expands information processing

eLife ◽

10.7554/elife.41586 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 4

Author(s):

Kevin Dorgans ◽

Valérie Demais ◽

Yannick Bailly ◽

Bernard Poulain ◽

Philippe Isope ◽

...

Keyword(s):

Information Processing ◽

Granule Cell ◽

Motor Behavior ◽

Molecular Layer ◽

Short Term ◽

Short Term Plasticity ◽

Synapsin Ii ◽

Heterogeneous Expression ◽

Molecular Layer Interneuron ◽

The Brain

Information processing by cerebellar molecular layer interneurons (MLIs) plays a crucial role in motor behavior. MLI recruitment is tightly controlled by the profile of short-term plasticity (STP) at granule cell (GC)-MLI synapses. While GCs are the most numerous neurons in the brain, STP diversity at GC-MLI synapses is poorly documented. Here, we studied how single MLIs are recruited by their distinct GC inputs during burst firing. Using slice recordings at individual GC-MLI synapses of mice, we revealed four classes of connections segregated by their STP profile. Each class differentially drives MLI recruitment. We show that GC synaptic diversity is underlain by heterogeneous expression of synapsin II, a key actor of STP and that GC terminals devoid of synapsin II are associated with slow MLI recruitment. Our study reveals that molecular, structural and functional diversity across GC terminals provides a mechanism to expand the coding range of MLIs.

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Short-term synaptic plasticity makes neurons sensitive to the distribution of presynaptic population firing rates

10.1101/707398 ◽

2019 ◽

Author(s):

Luiz Tauffer ◽

Arvind Kumar

Keyword(s):

Discrimination Problem ◽

Background Activity ◽

Strong Relationship ◽

Sparse Signals ◽

Population Code ◽

Short Term ◽

Short Term Plasticity ◽

Rate Analysis ◽

The Brain ◽

Latent Function

AbstractThe ability to discriminate spikes that encode a particular stimulus from spikes produced by background activity is essential for reliable information processing in the brain. We describe how synaptic short-term plasticity (STP) modulates the output of presynaptic populations as a function of the distribution of the spiking activity and find a strong relationship between STP features and sparseness of the population code, which could solve the discrimination problem. Furthermore, we show that feedforward excitation followed by inhibition (FF-EI), combined with target-dependent STP, promote substantial increase in the signal gain even for considerable deviations from the optimal conditions, granting robustness to this mechanism. A simulated neuron driven by a spiking FF-EI network is reliably modulated as predicted by a rate analysis and inherits the ability to differentiate sparse signals from dense background activity changes of the same magnitude, even at very low signal-to-noise conditions. We propose that the STP-based distribution discrimination is likely a latent function in several regions such as the cerebellum and the hippocampus.

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Short-term plasticity at Purkinje to deep cerebellar nuclear neuron synapses supports a slow gain-control mechanism enabling scaled linear encoding over second-long time windows

10.1101/749259 ◽

2019 ◽

Author(s):

Christine M. Pedroarena

Keyword(s):

Control Mechanism ◽

Background Activity ◽

Time Windows ◽

Gain Control ◽

Short Term ◽

Frequency Dependent ◽

Short Term Plasticity ◽

Gain Adaptation ◽

Long Time ◽

The Brain

ABSTRACTModifications in the sensitivity of neural elements allow the brain to adapt its functions to varying demands. Frequency-dependent short-term synaptic depression (STD) provides a dynamic gain-control mechanism enabling adaptation to different background conditions alongside enhanced sensitivity to input-driven changes in activity. In contrast, synapses displaying frequency-invariant transmission can faithfully transfer ongoing presynaptic rates enabling linear processing, deemed critical for many functions. However, rigid frequency-invariant transmission may lead to runaway dynamics and low sensitivity to changes in rate. Here, I investigated the Purkinje cell to deep cerebellar nuclei neuron synapses (PC_DCNs), which display frequency-invariance, and yet, PCs maintain background-activity at disparate rates, even at rest. Using protracted PC_DCNs activation (120s) in cerebellar slices to mimic background-activity, I identified a previously unrecognized frequency-dependent, slow STD (S_STD) of PC_DCN inhibitory postsynaptic currents. S_STD supports a novel form of gain-control that enabled—over second-long time windows—scaled linear encoding of PC rate changes mimicking behavior-driven/learned PC-signals, alongside adaptation to background-activity. Cell-attached DCN recordings confirmed these results. Experimental and computational modeling results suggest S_STD-gain-control may emerge through a slow depression factor combined with balanced fast-short-term plasticity. Finally, evidence from opto-genetic experiments, statistical analysis and computer simulations pointed to a presynaptic, input-specific and possibly activity-dependent decrease in active synaptic release-sites as the basis for S_STD. This study demonstrates a novel slow gain-control mechanism, which could explain efficient and comprehensive PC_DCN linear transfer of input-driven/learned PC rates over behavioral-relevant time windows despite disparate background-activity, and furthermore, provides an alternative pathway to hone PCs output via background-activity control.SIGNIFICANCE STATEMENTThe brain can adapt to varying demands by dynamically changing the gain of its synapses; however, some tasks require linear transfer of presynaptic rates over extended periods, seemingly incompatible with non-linear gain adaptation. Here, I report a novel gain-adaptation mechanism, which enables scaled linear encoding of changes in presynaptic rates over second-long time windows and adaptation to background-activity at longer time-scales at the Purkinje to deep cerebellar nuclear neurons synapses (PC_DCNs). A previously unrecognized PC_DCN slow and frequency-dependent short-term synaptic depression (S_STD), together with frequency-invariant transmission at faster time scales likely explains this process. This slow-gain-control/modulation mechanism may enable efficient linear encoding of second-long presynaptic signals under diverse synaptic background-activity conditions, and flexible fine-tuning of synaptic gains by background-activity modulation.

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