Effective Stimuli for Constructing Reliable Neuron Models

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The Emo-FilM dataset stands for Emotion research using Films and fMRI in healthy participants. This dataset includes emotion annotations by 44 raters for 14 short films with a combined duration of over 2 1/2 hours and recordings of respiration, heart rate, ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Music is ubiquitous, both in its instrumental and vocal forms. While speech perception at birth has been at the core of an extensive corpus of research, the origins of the ability to discriminate instrumental or vocal melodies is still not well investigate ...

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 ...

Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...

Subcortical brain structures such as the basal ganglia or the thalamus are involved in regulating motor and cognitive behavior. However, their contribution to perceptual consciousness is still unclear, due to the inherent difficulties of recording subcorti ...

In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signa ...

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

The pyroresistive response of conductive polymer composites (CPCs) has attracted much interest because of its potential applications in many electronic devices requiring a significant responsiveness to changes in external physical parameters such as temper ...

Topographical disorientation refers to the selective inability to orient oneself in familiar surroundings. However, to date its neural correlates remain poorly understood. Here we use quantitative lesion analysis and a lesion network mapping approach in or ...

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

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 ...

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Electrically connected and plasmonically enhanced molecular junctions combine the optical functionalities of high field confinement and enhancement (cavity function), and of high radiative efficiency (antenna function) with the electrical functionalities o ...

The way biological brains carry out advanced yet extremely energy efficient signal processing remains both fascinating and unintelligible. It is known however that at least some areas of the brain perform fast and low-cost processing relying only on a smal ...

The shift towards DC power distribution networks, enabled by power electronics technologies, is changing the nature of electrical power systems. Nowadays, DC power distribution networks can effectively support the high penetration of distributed energy res ...

Humans and animals constantly adapt to their environment over the course of their life. This thesis seeks to integrate various timescales of adaptation, ranging from the adaptation of synaptic connections between spiking neurons (milliseconds), rapid behav ...

Creators Meystre Julie Olivier Burri Contributors Jean Jacquemier Description This dataset contains 7 QuPath projects. The raw data images linked to these projects and located in other Zenodo datasets need to be downloaded as well. The raw data contains im ...

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

Effective Stimuli for Constructing Reliable Neuron Models

Chat with Graph Search

Emo-film: a Multimodal Dataset for Affective Neuroscience Using Naturalistic Stimuli

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Newborn's neural representation of instrumental and vocal music as revealed by fMRI: A dynamic effective brain connectivity study

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

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Subcortical correlates of consciousness with human single neuron recordings

Fast adaptation to rule switching using neuronal surprise

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

Pyroresistive response of percolating conductive polymer composites

The neural correlates of topographical disorientation-a lesion analysis study

Unveiling the complexity of learning and decision-making

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

Small-scale robotic devices for medical interventions in the brain

Machine learning-aided generative molecular design

Light Emission and Conductance Fluctuations in Electrically Driven and Plasmonically Enhanced Molecular Junctions

Supervised learning and inference of spiking neural networks with temporal coding

DC Power Distribution Networks with Direct Current Transformers

From event-based surprise to lifelong learning. A journey in the timescales of adaptation

Supplementary files for Machine learning for histological annotation and quantification of cortical layers

Deep Learning Theory Through the Lens of Diagonal Linear Networks