AIMC Topic: Cerebral Cortex

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PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.

Psychophysiology
Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and hypervigilance; however, the dissociative subtype of PTSD (PTSD+DS) presents with additional symptoms of depersonalization and derealization. Although ...

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

NeuroImage. Clinical
BACKGROUND: The development of optimal classification criteria for specific mental disorders which share similar symptoms is an important issue for precise diagnosis. We investigated whether P300 features in both sensor-level and source-level could b...

Cortical Tracking of Surprisal during Continuous Speech Comprehension.

Journal of cognitive neuroscience
Speech comprehension requires rapid online processing of a continuous acoustic signal to extract structure and meaning. Previous studies on sentence comprehension have found neural correlates of the predictability of a word given its context, as well...

Sensory processing and categorization in cortical and deep neural networks.

NeuroImage
Many recent advances in artificial intelligence (AI) are rooted in visual neuroscience. However, ideas from more complicated paradigms like decision-making are less used. Although automated decision-making systems are ubiquitous (driverless cars, pil...

Intracortical neural activity distal to seizure-onset-areas predicts human focal seizures.

PloS one
The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in...

Bayesian Computation through Cortical Latent Dynamics.

Neuron
Statistical regularities in the environment create prior beliefs that we rely on to optimize our behavior when sensory information is uncertain. Bayesian theory formalizes how prior beliefs can be leveraged and has had a major impact on models of per...

A fast machine learning approach to facilitate the detection of interictal epileptiform discharges in the scalp electroencephalogram.

Journal of neuroscience methods
BACKGROUND: Finding interictal epileptiform discharges (IEDs) in the EEG is a part of diagnosing epilepsy. Automated software for annotating EEGs of patients with suspected epilepsy can therefore help with reaching a diagnosis. A large amount of data...

Cortical graph neural network for AD and MCI diagnosis and transfer learning across populations.

NeuroImage. Clinical
Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it remains unclear how well the classifiers built on one population can predict MCI/...

A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy.

NeuroImage
In the analysis of functional Near-Infrared Spectroscopy (fNIRS) signals from real-world scenarios, artifact rejection is essential. However, currently there exists no gold-standard. Although a plenitude of methodological approaches implicitly assume...

Improving human cortical sulcal curve labeling in large scale cross-sectional MRI using deep neural networks.

Journal of neuroscience methods
BACKGROUND: Human cortical primary sulci are relatively stable landmarks and commonly observed across the population. Despite their stability, the primary sulci exhibit phenotypic variability.