Concept

Phase precession

Publications associées (26)

A 16-Channel Low-Power Neural Connectivity Extraction and Phase-Locked Deep Brain Stimulation SoC

Growing evidence suggests that phase-locked deep brain stimulation (DBS) can effectively regulate abnormal brain connectivity in neurological and psychiatric disorders. This letter therefore presents a low-power SoC with both neural connectivity extraction ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Different responses of mice and rats hippocampus CA1 pyramidal neurons to in vitro and in vivo-like inputs

Ying Shi, Armando Romani, Michele Migliore, Maurizio Ferdinando Pezzoli, Rosanna Migliore

The fundamental role of any neuron within a network is to transform complex spatiotemporal synaptic input patterns into individual output spikes. These spikes, in turn, act as inputs for other neurons in the network. Neurons must execute this function acro ...

2023

Approximating Relu Networks By Single-Spike Computation

Wulfram Gerstner, Stanislaw Andrzej Wozniak, Ana Stanojevic, Evangelos Eleftheriou, Giovanni Cherubini, Angeliki Pantazi

Developing energy-saving neural network models is a topic of rapidly increasing interest in the artificial intelligence community. Spiking neural networks (SNNs) are biologically inspired models that strive to leverage the energy efficiency stemming from a ...

IEEE2022

Phase Reconstruction of Low-Energy Electron Holograms of Individual Proteins

Klaus Kern, Stephan Rauschenbach, Sven Alexander Szilagyi, Hannah Julia Ochner

Low-energy electron holography (LEEH) is one of the few techniques capable of imaging large and complex three-dimensional molecules, such as proteins, on the single molecule level at subnanometer resolution. During the imaging process, the structural infor ...

AMER CHEMICAL SOC2022

HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data

Eilif Benjamin Muller, Werner Alfons Hilda Van Geit, Armando Romani, Szabolcs Kali, Carmen Alina Lupascu, Rosanna Migliore, Luca Leonardo Bologna, Sàra Sàray, Shailesh Appukuttan

Anatomically and biophysically detailed data-driven neuronal models have become widely used tools for understanding and predicting the behavior and function of neurons. Due to the increasing availability of experimental data from anatomical and electrophys ...

PUBLIC LIBRARY SCIENCE2021

A dynamical systems approach to synaptic consolidation and associations of concepts in hippocampus

Chiara Gastaldi

In the present work, we approach two key aspects of memory formation: associative memory and synaptic consolidation. The storage of associative memory is commonly related to the medial temporal lobe in humans. Experimental evidence shows that the memories ...

EPFL2021

Modeling spinal locomotor circuits for movements in developing zebrafish

Yann Roussel

Many spinal circuits dedicated to locomotor control have been identified in the developing zebrafish. How these circuits operate together to generate the various swimming movements during development remains to be clarified. In this study, we iteratively b ...

eLIFE SCIENCES PUBL LTD2021

Layer-Dependent Short-Term Synaptic Plasticity Between Excitatory Neurons in the C2 Barrel Column of Mouse Primary Somatosensory Cortex

Carl Petersen, Sandrine Lefort

Neurons process information through spatiotemporal integration of synaptic input. Synaptic transmission between any given pair of neurons is typically a dynamic process with presynaptic action potentials (APs) evoking depressing or facilitating postsynapti ...

Oxford Univ Press Inc2017

Electromagnetic Inspired Acoustic Metamaterials

Seyyed Hussein Seyyed Esfahlani

This thesis deals with electromagnetic inspired acoustic metamaterials, enabling sound-matter interactions in different wave scenarios that include propagation, guided-waves, radiation, refraction, reflection and transmission. To this end, a particular emp ...

EPFL2017

Learning spatio-temporal patterns in the presence of input noise using phase-change memristors

Stanislaw Andrzej Wozniak, Evangelos Eleftheriou, Angeliki Pantazi

Neuromorphic systems increasingly attract research interest owing to their ability to provide biologically inspired methods of computing, alternative to the classic von Neumann architecture. In these systems, computing relies on spike-based communication b ...

2016

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