Publications related to Models of neural computation

Static and Dynamic Stochastic Analysis of a Temperature-Sensitive VO2 Spiking Neuron

In this work, we investigate the intrinsic cycle-to-cycle variations in a spiking temperature-sensitive neuron, based on the resistive switching of a Vanadium dioxide (VO2) two-terminal device. We study how this phenomenon impacts the spike rate jitter, an ...

New York2023

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

Willem Anna Mark Wybo, Bernd Albert Illing, Matthias Chinyen Tsai, Walter Senn

While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at the biophysical level, and how processing layers further in the hierarchy can extract useful features for each possible contex-tual sta ...

Washington2023

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

Mahsa Shoaran, Uisub Shin, Cong Ding

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

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Silvestro Micera, Michael Lassi

Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by ...

ELSEVIER SCI LTD2023

Backpropagation-free training of deep physical neural networks

Romain Christophe Rémy Fleury, Ali Momeni, Matthieu Francis Malléjac, Babak Rahmani, Marc Philipp Del Hougne

Recent successes in deep learning for vision and natural language processing are attributed to larger models but come with energy consumption and scalability issues. Current training of digital deep-learning models primarily relies on backpropagation that ...

2023

A universal workflow for creation, validation and generalization of detailed neuronal models

Henry Markram, Srikanth Ramaswamy, Werner Alfons Hilda Van Geit, Alexis Arnaudon, Maria Reva, Mustafa Anil Tuncel, Darshan Mandge, Christian Andreas Rössert, Tanguy Pierre Louis Damart

Detailed single neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools are dedicated to the reproduction of a small set of specific ...

2022

Lactate supply overtakes glucose when neural computational and cognitive loads scale up

Pierre Magistretti

Neural computational power is determined by neuroenergetics, but how and which energy substrates are allocated to various forms of memory engram is unclear. To solve this question, we asked whether neuronal fueling by glucose or lactate scales differently ...

NATL ACAD SCIENCES2022

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

Tilo Schwalger, Valentin Marc Schmutz

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal rep ...

PUBLIC LIBRARY SCIENCE2022

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Models of neural computation

Static and Dynamic Stochastic Analysis of a Temperature-Sensitive VO2 Spiking Neuron

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

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

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

Backpropagation-free training of deep physical neural networks

A universal workflow for creation, validation and generalization of detailed neuronal models

Lactate supply overtakes glucose when neural computational and cognitive loads scale up

Leveraging Spiking Deep Neural Networks to Understand the Neural Mechanisms Underlying Selective Attention

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation

Graph Chatbot

Chat with Graph Search

Static and Dynamic Stochastic Analysis of a Temperature-Sensitive VO2 Spiking Neuron

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

Lactate supply overtakes glucose when neural computational and cognitive loads scale up

ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

Leveraging Spiking Deep Neural Networks to Understand the Neural Mechanisms Underlying Selective Attention

Backpropagation-free training of deep physical neural networks

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum?

A universal workflow for creation, validation and generalization of detailed neuronal models