Encoding and Decoding Models in Cognitive Electrophysiology

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Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions ...

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 ...

As a universal expression of human creativity, music is capable of conveying great subtlety and complexity. Crucially, this complexity is not encoded in the score or in the sounds, but is rather construed in the mind of the listener in the form of nuanced ...

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...

Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedia ...

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

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 ...

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Encoding and Decoding Models in Cognitive Electrophysiology

Chattez avec Graph Search

Ethological computational psychiatry: Challenges and opportunities

Small-scale robotic devices for medical interventions in the brain

Hearing structure in music: An empirical inquiry into listening as representation and processing

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Neurobiological and metabolic basis of motivation and effort-based decision-making - A human 1H-MRS, fMRI and machine learning study

Orchestrating chromosome conformation capture analysis with Bioconductor

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Unveiling the complexity of learning and decision-making

Data-driven statistical optimization of a groundwater monitoring network

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems