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Prefrontal Cortex

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Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth.

PloS one
Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy r...

Persistent irregular activity is a result of rebound and coincident detection mechanisms: A computational study.

Neural networks : the official journal of the International Neural Network Society
Persistent irregular activity is defined as elevated irregular neural discharges in the brain in such a way that while the average network activity displays high frequency oscillations, the participating neurons display irregular and low frequency os...

Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions.

Neuron
Decision making involves dynamic interplay between internal judgements and external perception, which has been investigated in delayed match-to-category (DMC) experiments. Our analysis of neural recordings shows that, during DMC tasks, LIP and PFC ne...

Binding by Random Bursts: A Computational Model of Cognitive Control.

Journal of cognitive neuroscience
A neural synchrony model of cognitive control is proposed. It construes cognitive control as a higher-level action to synchronize lower-level brain areas. Here, a controller prefrontal area (medial frontal cortex) can synchronize two cortical process...

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed...

Working Memory and Decision-Making in a Frontoparietal Circuit Model.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and dis...

Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.

BMC medical informatics and decision making
BACKGROUND: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physiological data supporting and a unified data analysis method, doctors can only rely on the subjective experience of the data to distinguish normal peop...

A neural network model for the orbitofrontal cortex and task space acquisition during reinforcement learning.

PLoS computational biology
Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and uses the knowledge to choose actions and a...

Resting-state functional connectivity predicts the ability to adapt arm reaching in a robot-mediated force field.

NeuroImage
Motor deficits are common outcomes of neurological conditions such as stroke. In order to design personalised motor rehabilitation programmes such as robot-assisted therapy, it would be advantageous to predict how a patient might respond to such trea...

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis.

Schizophrenia bulletin
BACKGROUND: The variability of responses to plasticity-inducing repetitive transcranial magnetic stimulation (rTMS) challenges its successful application in psychiatric care. No objective means currently exists to individually predict the patients' r...