scholarly journals Voltage-based inhibitory synaptic plasticity: network regulation, diversity, and flexibility

2020 ◽  
Author(s):  
Victor Pedrosa ◽  
Claudia Clopath
Keyword(s):  
Synaptic Plasticity ◽  
Pyramidal Cell ◽  
Brain Regions ◽  
Postsynaptic Membrane ◽  
Network Activity ◽  
Inhibitory Neurons ◽  
Plasticity Model ◽  
Feedforward Network ◽  
Voltage Dependent ◽  
Homeostatic Mechanisms

AbstractNeural networks are highly heterogeneous while homeostatic mechanisms ensure that this heterogeneity is kept within a physiologically safe range. One of such homeostatic mechanisms, inhibitory synaptic plasticity, has been observed across different brain regions. Computationally, however, inhibitory synaptic plasticity models often lead to a strong suppression of neuronal diversity. Here, we propose a model of inhibitory synaptic plasticity in which synaptic updates depend on presynaptic spike arrival and postsynaptic membrane voltage. Our plasticity rule regulates the network activity by setting a target value for the postsynaptic membrane potential over a long timescale. In a feedforward network, we show that our voltage-dependent inhibitory synaptic plasticity (vISP) model regulates the excitatory/inhibitory ratio while allowing for a broad range of postsynaptic firing rates and thus network diversity. In a feedforward network in which excitatory and inhibitory neurons receive correlated input, our plasticity model allows for the development of co-tuned excitation and inhibition, in agreement with recordings in rat auditory cortex. In recurrent networks, our model supports memory formation and retrieval while allowing for the development of heterogeneous neuronal activity. Finally, we implement our vISP rule in a model of the hippocampal CA1 region whose pyramidal cell excitability differs across cells. This model accounts for the experimentally observed variability in pyramidal cell features such as the number of place fields, the fields sizes, and the portion of the environment covered by each cell. Importantly, our model supports a combination of sparse and dense coding in the hippocampus. Therefore, our voltage-dependent inhibitory plasticity model accounts for network homeostasis while allowing for diverse neuronal dynamics observed across brain regions.

scholarly journals Wherefore Art Thou, Homeo(stasis)? Functional Diversity in Homeostatic Synaptic Plasticity

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Bridget N. Queenan ◽  
Kea Joo Lee ◽  
Daniel T. S. Pak
Keyword(s):  
Synaptic Plasticity ◽  
Homeostatic Plasticity ◽  
Network Activity ◽  
Control Mechanisms ◽  
Adaptive Responses ◽  
Neuronal Function ◽  
Homeostatic Synaptic Plasticity ◽  
Regulatory Principle ◽  
Functional Classes ◽  
Homeostatic Mechanisms

Homeostatic plasticity has emerged as a fundamental regulatory principle that strives to maintain neuronal activity within optimal ranges by altering diverse aspects of neuronal function. Adaptation to network activity is often viewed as an essential negative feedback restraint that prevents runaway excitation or inhibition. However, the precise importance of these homeostatic functions is often theoretical rather than empirically derived. Moreover, a remarkable multiplicity of homeostatic adaptations has been observed. To clarify these issues, it may prove useful to ask: why do homeostatic mechanisms exist, what advantages do these adaptive responses confer on a given cell population, and why are there so many seemingly divergent effects? Here, we approach these questions by applying the principles of control theory to homeostatic synaptic plasticity of mammalian neurons and suggest that the varied responses observed may represent distinct functional classes of control mechanisms directed toward disparate physiological goals.

scholarly journals Altered network properties in C9ORF72 repeat expansion cortical neurons are due to synaptic dysfunction

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Emma M. Perkins ◽  
Karen Burr ◽  
Poulomi Banerjee ◽  
Arpan R. Mehta ◽  
Owen Dando ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Synaptic Vesicle ◽  
Cortical Neurons ◽  
Electrode Array ◽  
Repeat Expansion ◽  
Cortical Network ◽  
Synaptic Function ◽  
Network Activity ◽  
Cortical Function ◽  
Network Function

Abstract Background Physiological disturbances in cortical network excitability and plasticity are established and widespread in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients, including those harbouring the C9ORF72 repeat expansion (C9ORF72RE) mutation – the most common genetic impairment causal to ALS and FTD. Noting that perturbations in cortical function are evidenced pre-symptomatically, and that the cortex is associated with widespread pathology, cortical dysfunction is thought to be an early driver of neurodegenerative disease progression. However, our understanding of how altered network function manifests at the cellular and molecular level is not clear. Methods To address this we have generated cortical neurons from patient-derived iPSCs harbouring C9ORF72RE mutations, as well as from their isogenic expansion-corrected controls. We have established a model of network activity in these neurons using multi-electrode array electrophysiology. We have then mechanistically examined the physiological processes underpinning network dysfunction using a combination of patch-clamp electrophysiology, immunocytochemistry, pharmacology and transcriptomic profiling. Results We find that C9ORF72RE causes elevated network burst activity, associated with enhanced synaptic input, yet lower burst duration, attributable to impaired pre-synaptic vesicle dynamics. We also show that the C9ORF72RE is associated with impaired synaptic plasticity. Moreover, RNA-seq analysis revealed dysregulated molecular pathways impacting on synaptic function. All molecular, cellular and network deficits are rescued by CRISPR/Cas9 correction of C9ORF72RE. Our study provides a mechanistic view of the early dysregulated processes that underpin cortical network dysfunction in ALS-FTD. Conclusion These findings suggest synaptic pathophysiology is widespread in ALS-FTD and has an early and fundamental role in driving altered network function that is thought to contribute to neurodegenerative processes in these patients. The overall importance is the identification of previously unidentified defects in pre and postsynaptic compartments affecting synaptic plasticity, synaptic vesicle stores, and network propagation, which directly impact upon cortical function.

Endocannabinoid system in the neurodevelopment of GABAergic interneurons: implications for neurological and psychiatric disorders

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Chang-geng Song ◽  
Xin Kang ◽  
Fang Yang ◽  
Wan-qing Du ◽  
Jia-jia Zhang ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Endocannabinoid System ◽  
Autism Spectrum ◽  
Network Activity ◽  
Inhibitory Neurons ◽  
Gabaergic Interneurons ◽  
Neural Stem Progenitor Cells ◽  
The Central Nervous System ◽  
Interneuron Development

Abstract In mature mammalian brains, the endocannabinoid system (ECS) plays an important role in the regulation of synaptic plasticity and the functioning of neural networks. Besides, the ECS also contributes to the neurodevelopment of the central nervous system. Due to the increase in the medical and recreational use of cannabis, it is inevitable and essential to elaborate the roles of the ECS on neurodevelopment. GABAergic interneurons represent a group of inhibitory neurons that are vital in controlling neural network activity. However, the role of the ECS in the neurodevelopment of GABAergic interneurons remains to be fully elucidated. In this review, we provide a brief introduction of the ECS and interneuron diversity. We focus on the process of interneuron development and the role of ECS in the modulation of interneuron development, from the expansion of the neural stem/progenitor cells to the migration, specification and maturation of interneurons. We further discuss the potential implications of the ECS and interneurons in the pathogenesis of neurological and psychiatric disorders, including epilepsy, schizophrenia, major depressive disorder and autism spectrum disorder.

scholarly journals Proteolytic Remodeling of Perineuronal Nets: Effects on Synaptic Plasticity and Neuronal Population Dynamics

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
P. Lorenzo Bozzelli ◽  
Seham Alaiyed ◽  
Eunyoung Kim ◽  
Sonia Villapol ◽  
Katherine Conant
Keyword(s):  
Population Dynamics ◽  
Synaptic Plasticity ◽  
Synaptic Input ◽  
Neuronal Plasticity ◽  
Population Level ◽  
Gamma Oscillations ◽  
Brain Regions ◽  
Neuronal Population ◽  
Perineuronal Nets ◽  
Perineuronal Net

The perineuronal net (PNN) represents a lattice-like structure that is prominently expressed along the soma and proximal dendrites of parvalbumin- (PV-) positive interneurons in varied brain regions including the cortex and hippocampus. It is thus apposed to sites at which PV neurons receive synaptic input. Emerging evidence suggests that changes in PNN integrity may affect glutamatergic input to PV interneurons, a population that is critical for the expression of synchronous neuronal population discharges that occur with gamma oscillations and sharp-wave ripples. The present review is focused on the composition of PNNs, posttranslation modulation of PNN components by sulfation and proteolysis, PNN alterations in disease, and potential effects of PNN remodeling on neuronal plasticity at the single-cell and population level.

scholarly journals Facilitating the propagation of spiking activity in feedforward networks by including feedback

2019 ◽  
Author(s):  
Hedyeh Rezaei ◽  
Ad Aertsen ◽  
Arvind Kumar ◽  
Alireza Valizadeh
Keyword(s):  
Resonance Frequency ◽  
External Input ◽  
Network Activity ◽  
Inhibitory Neurons ◽  
Modular System ◽  
Feedforward Networks ◽  
Successful Transmission ◽  
Successful Communication ◽  
Resonance Frequencies ◽  
Feedback Connections

AbstractTransient oscillations in the network activity upon sensory stimulation have been reported in different sensory areas. These evoked oscillations are the generic response of networks of excitatory and inhibitory neurons (EI-networks) to a transient external input. Recently, it has been shown that this resonance property of EI-networks can be exploited for communication in modular neuronal networks by enabling the transmission of sequences of synchronous spike volleys (‘pulse packets’), despite the sparse and weak connectivity between the modules. The condition for successful transmission is that the pulse packet (PP) intervals match the period of the modules’ resonance frequency. Hence, the mechanism was termed communication through resonance (CTR). This mechanism has three sever constraints, though. First, it needs periodic trains of PPs, whereas single PPs fail to propagate. Second, the inter-PP interval needs to match the network resonance. Third, transmission is very slow, because in each module, the network resonance needs to build-up over multiple oscillation cycles. Here, we show that, by adding appropriate feedback connections to the network, the CTR mechanism can be improved and the aforementioned constraints relaxed. Specifically, we show that adding feedback connections between two upstream modules, called the resonance pair, in an otherwise feedforward modular network can support successful propagation of a single PP throughout the entire network. The key condition for successful transmission is that the sum of the forward and backward delays in the resonance pair matches the resonance frequency of the network modules. The transmission is much faster, by more than a factor of two, than in the original CTR mechanism. Moreover, it distinctly lowers the threshold for successful communication by synchronous spiking in modular networks of weakly coupled networks. Thus, our results suggest a new functional role of bidirectional connectivity for the communication in cortical area networks.Author summaryThe cortex is organized as a modular system, with the modules (cortical areas) communicating via weak long-range connections. It has been suggested that the intrinsic resonance properties of population activities in these areas might contribute to enabling successful communication. A module’s intrinsic resonance appears in the damped oscillatory response to an incoming spike volley, enabling successful communication during the peaks of the oscillation. Such communication can be exploited in feedforward networks, provided the participating networks have similar resonance frequencies. This, however, is not necessarily true for cortical networks. Moreover, the communication is slow, as it takes several oscillation cycles to build up the response in the downstream network. Also, only periodic trains of spikes volleys (and not single volleys) with matching intervals can propagate. Here, we present a novel mechanism that alleviates these shortcomings and enables propagation of synchronous spiking across weakly connected networks with not necessarily identical resonance frequencies. In this framework, an individual spike volley can propagate by local amplification through reverberation in a loop between two successive networks, connected by feedforward and feedback connections: the resonance pair. This overcomes the need for activity build-up in downstream networks, causing the volley to propagate distinctly faster and more reliably.

scholarly journals Theory of Mind network activity is associated with metaethical judgment: An item analysis

2017 ◽  
Author(s):  
Jordan E. Theriault ◽  
Adam Waytz ◽  
Larisa Heiphetz ◽  
Liane Young
Keyword(s):  
Theory Of Mind ◽  
Item Analysis ◽  
Positive Association ◽  
Brain Regions ◽  
Social Contexts ◽  
Network Activity ◽  
Predictive Processing ◽  
Temporoparietal Junction ◽  
Social Tasks ◽  
Stimulus Features

The theory of mind network (ToMN) is a set of brain regions activated by a variety of social tasks. Recent work has proposed that these associations with ToMN activity may relate to a common underlying computation: processing prediction error in social contexts. The present work presents evidence consistent with this hypothesis, using a fine-grained item analysis to examine the relationship between ToMN activity and variance in stimulus features. We used an existing dataset (consisting of statements about morals, facts, and preferences) to explore variability in ToMN activity elicited by moral statements, using metaethical judgments (i.e. judgments of how fact-like/preference-like morals are) as a proxy for their predictability/support by social consensus. Study 1 validated expected patterns of behavioral judgments in our stimuli set, and Study 2 associated by-stimulus estimates of metaethical judgment with ToMN activity, showing that ToMN activity was negatively associated with objective morals and positively associated with subjective morals. Whole brain analyses indicated that these associations were strongest in bilateral temporoparietal junction (TPJ). We also observed additional by-stimulus associations with ToMN, including positive associations with the presence of a person (across morals, facts, and preferences), a negative association with agreement (among morals only), and a positive association with mental inference (in preferences only, across 3 independent measures and behavioral samples). We discuss these findings in the context of recent predictive processing models, and highlight how predictive models may facilitate new perspectives on metaethics, the centrality of morality to personal identity, and distinctions between social domains (e.g. morals vs. preferences).

scholarly journals Neuronal and Astrocytic Regulations in Schizophrenia: A Computational Modelling Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Lea Fritschi ◽  
Johanna Hedlund Lindmar ◽  
Florian Scheidl ◽  
Kerstin Lenk
Keyword(s):  
Computational Models ◽  
Glutamate Release ◽  
Signal Transmission ◽  
Computational Modelling ◽  
Atp Release ◽  
Network Activity ◽  
Inhibitory Neurons ◽  
Neuronal Network Activity ◽  
Cell Densities ◽  
Synapse Model

According to the tripartite synapse model, astrocytes have a modulatory effect on neuronal signal transmission. More recently, astrocyte malfunction has been associated with psychiatric diseases such as schizophrenia. Several hypotheses have been proposed on the pathological mechanisms of astrocytes in schizophrenia. For example, post-mortem examinations have revealed a reduced astrocytic density in patients with schizophrenia. Another hypothesis suggests that disease symptoms are linked to an abnormality of glutamate transmission, which is also regulated by astrocytes (glutamate hypothesis of schizophrenia). Electrophysiological findings indicate a dispute over whether the disorder causes an increase or a decrease in neuronal and astrocytic activity. Moreover, there is no consensus as to which molecular pathways and network mechanisms are altered in schizophrenia. Computational models can aid the process in finding the underlying pathological malfunctions. The effect of astrocytes on the activity of neuron-astrocyte networks has been analysed with computational models. These can reproduce experimentally observed phenomena, such as astrocytic modulation of spike and burst signalling in neuron-astrocyte networks. Using an established computational neuron-astrocyte network model, we simulate experimental data of healthy and pathological networks by using different neuronal and astrocytic parameter configurations. In our simulations, the reduction of neuronal or astrocytic cell densities yields decreased glutamate levels and a statistically significant reduction in the network activity. Amplifications of the astrocytic ATP release toward postsynaptic terminals also reduced the network activity and resulted in temporarily increased glutamate levels. In contrast, reducing either the glutamate release or re-uptake in astrocytes resulted in higher network activities. Similarly, an increase in synaptic weights of excitatory or inhibitory neurons raises the excitability of individual cells and elevates the activation level of the network. To conclude, our simulations suggest that the impairment of both neurons and astrocytes disturbs the neuronal network activity in schizophrenia.

scholarly journals Understanding the Effects of General Anesthetics on Cortical Network Activity Using Ex Vivo Preparations

2019 ◽  
Vol 130 (6) ◽  
pp. 1049-1063 ◽  
Author(s):  
Logan J. Voss ◽  
Paul S. García ◽  
Harald Hentschke ◽  
Matthew I. Banks
Keyword(s):  
Molecular Mechanisms ◽  
Ex Vivo ◽  
Brain Slices ◽  
Brain Regions ◽  
Cortical Network ◽  
Network Activity ◽  
Common Mechanism ◽  
General Anesthetics ◽  
Neural Basis

Abstract General anesthetics have been used to ablate consciousness during surgery for more than 150 yr. Despite significant advances in our understanding of their molecular-level pharmacologic effects, comparatively little is known about how anesthetics alter brain dynamics to cause unconsciousness. Consequently, while anesthesia practice is now routine and safe, there are many vagaries that remain unexplained. In this paper, the authors review the evidence that cortical network activity is particularly sensitive to general anesthetics, and suggest that disruption to communication in, and/or among, cortical brain regions is a common mechanism of anesthesia that ultimately produces loss of consciousness. The authors review data from acute brain slices and organotypic cultures showing that anesthetics with differing molecular mechanisms of action share in common the ability to impair neurophysiologic communication. While many questions remain, together, ex vivo and in vivo investigations suggest that a unified understanding of both clinical anesthesia and the neural basis of consciousness is attainable.

Synaptic integration in an excitable dendritic tree

1993 ◽  
Vol 70 (3) ◽  
pp. 1086-1101 ◽  
Author(s):  
B. W. Mel
Keyword(s):  
Pyramidal Cell ◽  
Neuronal Response ◽  
Dendritic Tree ◽  
Pattern Discrimination ◽  
Synaptic Activity ◽  
Visual Neurons ◽  
Voltage Dependent ◽  
Sum Of Products ◽  
Very High ◽  
Synaptic Drive

1. Compartmental modeling experiments were carried out in an anatomically characterized neocortical pyramidal cell to study the integrative behavior of a complex dendritic tree containing active membrane mechanisms. Building on a previously presented hypothesis, this work provides further support for a novel principle of dendritic information processing that could underlie a capacity for nonlinear pattern discrimination and/or sensory processing within the dendritic trees of individual nerve cells. 2. It was previously demonstrated that when excitatory synaptic input to a pyramidal cell is dominated by voltage-dependent N-methyl-D-aspartate (NMDA)-type channels, the cell responds more strongly when synaptic drive is concentrated within several dendritic regions than when it is delivered diffusely across the dendritic arbor. This effect, called dendritic "cluster sensitivity," persisted under wide-ranging parameter variations and directly implicated the spatial ordering of afferent synaptic connections onto the dendritic tree as an important determinant of neuronal response selectivity. 3. In this work, the sensitivity of neocortical dendrites to spatially clustered synaptic drive has been further studied with fast sodium and slow calcium spiking mechanisms present in the dendritic membrane. Several spatial distributions of the dendritic spiking mechanisms were tested with and without NMDA synapses. Results of numerous simulations reveal that dendritic cluster sensitivity is a highly robust phenomenon in dendrites containing a sufficiency of excitatory membrane mechanisms and is only weakly dependent on their detailed spatial distribution, peak conductances, or kinetics. Factors that either work against or make irrelevant the dendritic cluster sensitivity effect include 1) very high-resistance spine necks, 2) very large synaptic conductances, 3) very high baseline levels of synaptic activity, and 4) large fluctuations in level of synaptic activity on short time scales. 4. The functional significance of dendritic cluster sensitivity has been previously discussed in the context of associative learning and memory. Here it is demonstrated that the dendritic tree of a cluster-sensitive neuron implements an approximative spatial correlation, or sum of products operation, such as that which could underlie nonlinear disparity tuning in binocular visual neurons.

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