Publication

On the choice of metric in gradient-based theories of brain function

Related publications (35)

A parcellation scheme of mouse isocortex based on reversals in connectivity gradients

Michael Reimann

The brain is composed of several anatomically clearly separated structures. This parcellation is often extended into the isocortex, based on anatomical, physiological or functional differences. Here, we derive a parcellation scheme based purely on the spat ...
2023

Surprise and novelty in the brain

Wulfram Gerstner, Johanni Michael Brea, Alireza Modirshanechi, Sophia Becker

Notions of surprise and novelty have been used in various experimental and theoretical studies across multiple brain areas and species. However, 'surprise' and 'novelty' refer to different quantities in different studies, which raises concerns about whethe ...
CURRENT BIOLOGY LTD2023

Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research

Nicolas Clairis

The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) is a brain area subject to many theories and debates over its function(s). Even its precise anatomical borders are subject to much controversy. In the past decades, the dmPFC/d ...
Oxford2023

A Unified Framework for Neuroscience Morphological Data Visualization

Juan José García Cantero

The complexity of the human brain makes its understanding one of the biggest challenges that science is currently confronting. Due to its complexity, the brain has been studied at many different levels and from many disciplines and points of view, using a ...
2021

Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem

Lenka Zdeborová, Francesca Mignacco

In this paper we investigate how gradient-based algorithms such as gradient descent (GD), (multi-pass) stochastic GD, its persistent variant, and the Langevin algorithm navigate non-convex loss-landscapes and which of them is able to reach the best general ...
IOP PUBLISHING LTD2021

Sparse coupled logistic regression to estimate co-activation and modulatory influences of brain regions

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Ye Tian

Accurate mapping of the functional interactions between remote brain areas with resting-state functional magnetic resonance imaging requires the quantification of their underlying dynamics. In conventional methodological pipelines, a spatial scale of inter ...
IOP PUBLISHING LTD2020

Gene replacement therapy provides benefit in an adult mouse model of Leigh syndrome

Johan Auwerx

Mutations in nuclear-encoded mitochondrial genes are responsible for a broad spectrum of disorders among which Leigh syndrome is the most common in infancy. No effective therapies are available for this severe disease mainly because of the limited capabili ...
2020

Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval

Florent Gérard Krzakala, Lenka Zdeborová

Despite the widespread use of gradient-based algorithms for optimizing high-dimensional non-convex functions, understanding their ability of finding good minima instead of being trapped in spurious ones remains to a large extent an open problem. Here we fo ...
Curran Associates, Inc.2020

Gradients of structure-function tethering across neocortex

Patric Hagmann

The white matter architecture of the brain imparts a distinct signature on neuronal coactivation patterns. Interregional projections promote synchrony among distant neuronal populations, giving rise to richly patterned functional networks. A variety of sta ...
PNAS2019

A Brief History of Simulation Neuroscience

Henry Markram, Xue Fan

Our knowledge of the brain has evolved over millennia in philosophical, experimental and theoretical phases. We suggest that the next phase is simulation neuroscience. The main drivers of simulation neuroscience are big data generated at multiple levels of ...
FRONTIERS MEDIA SA2019

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.