E/I balance

…to develop input selectivity and E/I balance via Hebbian synaptic plasticity. We model a single ra

Modeling brain dynamics requires addressing processes that span different temporal and spatial scales [1]. This is crucial, when studying phenomena at the circuit level that are consequences of pharmacological or pathological alterations occurring at the single-cell level, such as changes in ionic or synaptic currents. Here, our aim is to study how single-cell dynamics interact with and affect circuit dynamics in a mouse model of autism (IB2 knock-out, KO), within the context of the cerebellar cortical microcircuit. In this work, we used a bottom-up approach: the microcircuit connectivity was

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental condition with heterogeneous phenotype. Here, we investigated prefrontal cortex (PFC) alterations and cerebellum-PFC connectivity in the IB2 KO mouse model of ASD. Significant alterations in signal processing and plasticity have been reported in the cerebellar granular layer of IB2 KO mice, confirming the crucial cerebellar involvement in ASD pathophysiology. Given the PFC renowned role in ASD and its functional connections with the cerebellum, we explored the prelimbic cortex (PrL) microcircuitry in IB2 KO and WT mice at differe

Activation of hippocampal inhibitory pathways is essential for maintaining the balance between excitation and inhibition during hippocampal information processing. Somatostatin (SOM) and Parvalbumin (PV) positive GABAergic neurons are two major classes of interneurons in the hippocampus, providing strong dendritic and peri-somatic inhibition to excitatory neurons, respectively. It is well known that exposure of mice to an enriched environment (EE) reliably increases performance on hippocampus-dependent learning and memory tasks. However, the mechanisms underlying the behavioral improvements an

…On one end, mechanistic models such as balanced spiking networks resemble activity regimes observed in data, but are often limited to simple computations. On the other end, functional models like trained deep networks can show comparable performance and dynamical motifs, but are far removed from experimental physiology. Here, we put forth a new framework for excitatory-inhibitory spiking networks which retains key properties of both mechanistic and functional models. Based on previous studies of the geometry o

Excitatory and inhibitory (E & I) inputs to cortical neurons remain balanced across different conditions. The balanced network model provides a self-consistent account of this observation: population rates dynamically adjust to yield a state in which all neurons are active at biological levels, with their E & I inputs tightly balanced. But global tight E/I balance predicts population responses with linear stimulus-dependence and does not account for systematic cortical response nonlinearities such as divisive normalization, a canonical brain computation. However, when necessary connectivity co

The error-backpropagation (backprop) algorithm has stood at the forefront as a solution to the credit assignment problem in artificial neural networks. Whether the brain adopts a similar strategy to ensure that the correct synapses are modified remains unclear. Recent work has attempted to bridge this gap with backprop-like learning mechanisms that are consistent with several cortical experimental observations. However, these models are either unable to effectively backpropagate error signals across several brain areas or require a multi-phase learning process, neither of which are reminiscent

To prevail in a dynamic and noisy environment, the brain must create reliable and meaningful representations from sensory inputs that are often ambiguous or corrupt. Since only information that permeates the cortical hierarchy can influence sensory perception and decision-making, it is critical that noisy external stimuli are encoded and propagated through different processing stages with minimal signal degradation. Here we hypothesize that stimulus-specific pathways akin to cortical topographic maps may provide the structural scaffold for such signal routing. We investigate whether the featur

…for excitation-inhibition (E/I) balance. In particular, we find that such an opti