A neurometabolic mechanism involving dmPFC/dACC lactate in physical effort-based decision-making

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We consider the problem of computing mixed Nash equilibria of two-player zero-sum games with continuous sets of pure strategies and with first-order access to the payoff function. This problem arises for example in game-theory-inspired machine learning app ...

Traditional models of human brain activity often represent it as a network of pairwise interactions between brain regions. Going beyond this limitation, recent approaches have been proposed to infer higher-order interactions from temporal brain signals inv ...

Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from simulatio ...

Preserving privacy is a growing concern in our society where cameras are ubiquitous. In this work, we propose a trainable image acquisition method that removes the sensitive information in the optical domain before it reaches the image sensor. The method b ...

We investigate methods for manipulating classifier explanations while keeping the predictions unchanged. Our focus is on using a sparse attack, which seeks to alter only a minimal number of input features. We present an efficient and novel algorithm for co ...

One prominent approach toward resolving the adversarial vulnerability of deep neural networks is the two-player zero-sum paradigm of adversarial training, in which predictors are trained against adversarially-chosen perturbations of data. Despite the promi ...

Disruption of brain development early in life may underlie the neurobiology behind schizophre-nia. We have reported more immature synaptic spines in the frontal cortex (FC) of adult Roman High-Avoidance (RHA-I) rats, a behavioural model displaying schizoph ...

Spiking neural networks (SNNs) are mimicking computationally powerful biologically inspired models in which neurons communicate through sequences of spikes, regarded here as sparse binary sequences of zeros and ones. In neuroscience it is conjectured that ...

Deep neural networks (DNNs) have achieved great success in image classification and recognition compared to previous methods. However, recent works have reported that DNNs are very vulnerable to adversarial examples that are intentionally generated to misl ...

Recently, it has been shown that methods based on the dynamics of 1 H nuclear hyperpolarization in magic angle spinning (MAS) NMR experiments can be used to determine mesoscale structures in complex materials. However, these methods suffer from low sensiti ...

The intense but transient increase in nuclear magnetic resonance signal provided by dynamic nuclear polarization (DNP) has enabled a range of new applications, including rapid, minimally-invasive metabolic imaging at the second timescale. This chapter prov ...

This study evaluates and compares several machine learning methods on the effects of different parameters in the hydrothermal carbonisation (HTC) process of macroalgae Sargassum horneri. Reaction temperature, residence time, biomass particle size, the amou ...

As the size and complexity of models and datasets grow, so does the need for communication-efficient variants of stochastic gradient descent that can be deployed to perform parallel model training. One popular communication-compression method for data-para ...

We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study of moving organs such as the heart. We introduce a generalized version of t ...

Dynamic Nuclear Polarization (DNP) has recently emerged as a key method to increase the sensitivity of solid-state NMR spectroscopy under Magic Angle Spinning (MAS). While efficient binitroxide polarizing agents such as AMUPol have been developed for MAS D ...

Tactile working memory engages a broad network of cortical regions in primates. To assess whether the conclusions drawn from primates apply to rodents, we examined the vibrissal primary somatosensory cortex (vS1) and the prelimbic cortex (PL) in a delayed ...

Neonatal Intensive Care Units (NICU) provide special equipment designed to give life support for the increasing number of prematurely born infants and assure their survival. More recently NICU's strive to include developmentally oriented care and modulate ...

Rodent models are decisive for translational research in healthy and pathological conditions of motor function thanks to specific similarities with humans. Here, we present an upgraded version of the M-Platform, a robotic device previously designed to trai ...

A neurometabolic mechanism involving dmPFC/dACC lactate in physical effort-based decision-making

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Adversarial Training Should Be Cast As a Non-Zero-Sum Game

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