The role of the ventromedial prefrontal cortex in abstract state-based inference during decision making in humans

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Background Stroke is the leading cause of long-term disability, making the search for successful rehabilitation treatment one of the most important public health issues. A better understanding of the neural mechanisms underlying impairment and recovery is ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

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 ...

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, ...

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 ...

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a ...

The growing global obesity issue emphasizes the importance of understanding its health implications. Previous research has identified consistent alterations in gray matter (GM) volume in connection with obesity. Given the various implications of distinct f ...

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 ...

Aim: Adolescents born very preterm (VPT;

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 ...

Neuroprostheses have been used clinically for decades, to help restore or preserve brain functions, when pharmaceutical treatments are inefficient. Although great progress in the field has been made over the years to interface with the nervous system, surf ...

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

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 ...

The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

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 ...

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 ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

The role of the ventromedial prefrontal cortex in abstract state-based inference during decision making in humans

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Brain Oscillatory Modes as a Proxy of Stroke Recovery

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

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

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

Unveiling the complexity of learning and decision-making

White adipose tissue distribution and amount are associated with increased white matter connectivity

The interplay between white adipose tissue, adipokines, and structural gray matter changes

Fast adaptation to rule switching using neuronal surprise

Impact of a mindfulness-based intervention on neurobehavioral functioning and its association with large-scale brain networks in preterm young adolescents

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

Unraveling behavior and cortical signals to guide the development of soft neuroprostheses for auditory restoration and spreading depolarization

Driving and suppressing the human language network using large language models

Subcortical correlates of consciousness with human single neuron recordings

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Reliable data-driven decision-making through optimal transport

Small-scale robotic devices for medical interventions in the brain

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

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Predicting the long-term collective behaviour of fish pairs with deep learning

Incorporating Projective Geometry into Deep Learning