Complexity and performance in simple neuron models

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Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

Synaptic plasticity underlies our ability to learn and adapt to the constantly changing environment. The phenomenon of synapses changing their efficacy in an activity-dependent manner is often studied in small groups of neurons in vitro or indirectly throu ...

Objective. Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locom ...

Cell-sized giant unilamellar vesicles (GUVs) are an ideal tool for understanding lipid membrane structure and properties. Label-free spatiotemporal images of their membrane potential and structure would greatly aid the quantitative understanding of membran ...

Neocortical neurons can increasingly be divided into well-defined classes, but their activity patterns during quantified behavior remain to be fully determined. Here, we obtained membrane potential recordings from various classes of excitatory and inhibito ...

Synaptic plasticity underlies the brain’s ability to learn and adapt. While experiments in brain slices have revealed mechanisms and protocols for the induction of plasticity between pairs of neurons, how these synaptic changes are coordinated in biologica ...

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

Over the course of a lifetime, the human brain acquires an astonishing amount of semantic knowledge and autobiographical memories, often with an imprinting strong enough to allow detailed information to be recalled many years after the initial learning exp ...

Objective. Syntax involves complex neurobiological mechanisms, which are difficult to disentangle for multiple reasons. Using a protocol able to separate syntactic information from sound information we investigated the neural causal connections evoked by t ...

Complexity and performance in simple neuron models

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Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

On distributional autoregression and iterated transportation

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Principles of Network Plasticity in Neocortical Microcircuits

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

High throughput wide field second harmonic imaging of giant unilamellar vesicles

Membrane potential dynamics of excitatory and inhibitory neurons in mouse barrel cortex during active whisker sensing

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

A theory of memory consolidation and synaptic pruning in cortical circuits

Event-related causality in stereo-EEG discriminates syntactic processing of noun phrases and verb phrases