p Robotically-induced hallucination triggers subtle changes in brain network transitions

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Background: The computational mechanisms underlying psychiatric disorders are hotly debated. One hypothesis, grounded in the Bayesian predictive coding framework, proposes that patients with schizophrenia have abnormalities in encoding prior beliefs about ...

Magnetic resonance imaging (MRI) is a powerful modality for investigating abnormal developmental patterns in utero. However, since it is not the first-line diagnostic tool in this sensitive population, data remain scarce and heterogeneous across scanners a ...

Functional magnetic resonance imaging (fMRI) relies upon the blood-oxygenation-level-dependent (BOLD) signal as a proxy for neuronal activity. Whole-brain coverage and millimetric resolution have propelled this modality as a workhorse for human neuroscienc ...

For almost five decades of its existence, imaging neuroscience—the research branch that uses noninvasive brain imaging to provide inferences about brain structure and function, has focused almost exclusively on studies pertaining to well-controlled laborat ...

Objective. Many psychiatric disorders involve excessive avoidant or defensive behavior, such as avoidance in anxiety and trauma disorders or defensive rituals in obsessive-compulsive disorders. Developing algorithms to predict these behaviors from local fi ...

Connectome spectrum electromagnetic tomography (CSET) combines diffusion MRI-derived structural connectivity data with well-established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and t ...

However, their use in imaging applications has been limited by their relatively large pixel size (≥ 55 μm) and high-energy (>80 keV) electrons scattering over multiple pixels in the sensor layer. To realize the full potential of fast, radiation-hard HPDs a ...

Anticipating potential threats in the environment and responding with adaptive behavior is essential for animal survival. Therefore, strong mechanisms of aversively-motivated associative learning, called fear learning, have evolved in the animal kingdom. I ...

Despite a lack of scientific consensus on the definition of emotions, they are generally considered to involve several modifications in the mind, body, and behavior. Although psychology theories emphasized multi-componential characteristics of emotions, li ...

This paper systematically demonstrates the feasibility of wirelessly monitoring dopamine concentration in the brain with an implantable biosensor. The biosensor was realized using microwires, and then, the dopamine concentration was measured in-vitro rangi ...

p Robotically-induced hallucination triggers subtle changes in brain network transitions

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Oscillatory Traveling Waves Provide Evidence for Predictive Coding Abnormalities in Schizophrenia

A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain

Direct imaging of neuronal activity: a multivariate perspective on DIANA data in human subjects

Mapping the Human Brain with Computational Anatomy

Neural decoding and feature selection methods for closed-loop control of avoidance behavior

Connectome spectrum electromagnetic tomography: A method to reconstruct electrical brain source networks at high-spatial resolution

Enhancing spatial resolution in MÖNCH for electron microscopy via deep learning

Neuronal dynamics of principal neurons and three types of interneurons in the posterior Insula during fear learning

Brain networks subserving functional core processes of emotions identified with componential modeling

Editorial: Hybrid brain-robot interfaces for enhancing mobility

Implantable Biosensor for Brain Dopamine using Microwire-Based Electrodes