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Background: Identifying and characterising the longitudinal patterns of multimorbidity associated with stroke is needed to better understand patients' needs and inform new models of care. Methods: We used an unsupervised patient-oriented…

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is…

Neurons and Cognition · Quantitative Biology 2013-10-31 Danielle S. Bassett , Nicholas F. Wymbs , M. Puck Rombach , Mason A. Porter , Peter J. Mucha , Scott T. Grafton

The goal of the present study is to identify autism using machine learning techniques and resting-state brain imaging data, leveraging the temporal variability of the functional connections (FC) as the only information. We estimated and…

Neurons and Cognition · Quantitative Biology 2017-12-22 Ravi Tejwani , Adam Liska , Hongyuan You , Jenna Reinen , Payel Das

Cognitive distortions, distorted patterns of thinking, have been increasingly studied in computational mental health research. Although they are related to many, if not all, mental health disorders, most existing studies focus primarily on…

Computation and Language · Computer Science 2026-05-26 Alina Anikejeva , Kairit Sirts

Stroke-induced disturbances of large-scale cortical networks are known to be associated with the extent of motor deficits. We argue that identifying brain networks representative of motor behavior in the resting brain would provide…

Neurons and Cognition · Quantitative Biology 2019-07-24 Ozan Özdenizci , Timm Meyer , Felix Wichmann , Jan Peters , Bernhard Schölkopf , Müjdat Çetin , Moritz Grosse-Wentrup

The electroencephalography (EEG) source imaging problem is very sensitive to the electrical modelling of the skull of the patient under examination. Unfortunately, the currently available EEG devices and their embedded software do not take…

Machine Learning · Computer Science 2020-02-04 Alexandra Koulouri , Ville Rimpilainen

Developmental dyslexia is characterized by persistent reading and spelling deficits. Partly due to technical challenges with investigating subcortical sensory structures, current research on dyslexia in humans by-and-large focuses on the…

Neurons and Cognition · Quantitative Biology 2017-11-20 Christa Müller-Axt , Alfred Anwander , Katharina von Kriegstein

Neuroimaging-based prediction methods for intelligence and cognitive abilities have seen a rapid development in literature. Among different neuroimaging modalities, prediction based on functional connectivity (FC) has shown great promise.…

Neurons and Cognition · Quantitative Biology 2023-07-20 Yang Li , Xin Ma , Raj Sunderraman , Shihao Ji , Suprateek Kundu

Imaging the human brain vasculature with high spatial and temporal resolution remains challenging in the clinic today. Transcranial ultrasound is scarcely used for cerebrovascular imaging, due to low sensitivity and strong phase aberrations…

Ischemic brain injuries are frequent and difficult to detect reliably or early. We present the multi-modal data set containing cardiovascular (blood pressure, blood flow, electrocardiogram) and brain electrical activities to derive…

Quantitative Methods · Quantitative Biology 2021-02-26 Martin G. Frasch , Bernd Walter , Christophe L. Herry , Reinhard Bauer

Patients with Frontotemporal Dementia (FTD) have impaired cognitive abilities, executive and behavioral traits, loss of language ability, and decreased memory capabilities. Based on the distinct patterns of cortical atrophy and symptoms,…

Artificial Intelligence · Computer Science 2021-04-13 Km Poonam , Rajlakshmi Guha , Partha P Chakrabarti

Correlated component analysis as proposed by Dmochowski et al. (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption…

Machine Learning · Statistics 2018-02-08 Simon Kamronn , Andreas Trier Poulsen , Lars Kai Hansen

Parkinson disease (PD) is marked by progressive neurodegeneration, yet early and subtle structural alterations in brain tissue remain difficult to detect with conventional imaging and analytical methods. Fractal and multifractal frameworks…

Medical Physics · Physics 2025-12-09 Santanu Maity , Mousa Alrubayan , Mohammad Moshahid Khan , Prabhakar Pradhan

Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders in children and is characterised by inattention, impulsiveness and hyperactivity. While several studies have analysed the static…

Neurons and Cognition · Quantitative Biology 2023-02-17 Rohit Misra , Tapan K. Gandhi

Severe traumatic brain injury can lead to disorders of consciousness (DOC) characterized by deficit in conscious awareness and cognitive impairment including coma, vegetative state, minimally consciousness, and lock-in syndrome. Of crucial…

Neurons and Cognition · Quantitative Biology 2013-10-14 Verónica Mäki-Marttunen , Ibai Diez , Jesus M. Cortes , Dante R. Chialvo , Mirta Villarreal

Researchers have reported high decoding accuracy (>95%) using non-invasive Electroencephalogram (EEG) signals for brain-computer interface (BCI) decoding tasks like image decoding, emotion recognition, auditory spatial attention detection,…

Signal Processing · Electrical Eng. & Systems 2025-10-17 Xiran Xu , Bo Wang , Boda Xiao , Yadong Niu , Yiwen Wang , Xihong Wu , Jing Chen

Functional Connectivity between brain regions is known to be altered in Alzheimer's disease, and promises to be a biomarker for early diagnosis of the disease. While several approaches for functional connectivity obtain an un-directed…

Neurons and Cognition · Quantitative Biology 2024-02-21 Rahul Biswas , SuryaNarayana Sripada

The identification of abnormal electrographic activity is important in a wide range of neurological disorders, including epilepsy for localising epileptogenic tissue. However, this identification may be challenging during non-seizure…

Financial stability is a key challenge for individuals living with bipolar disorder (BD). Symptomatic periods in BD are associated with poor financial decision-making, contributing to a negative cycle of worsening symptoms and an increased…

Human-Computer Interaction · Computer Science 2024-02-29 Jeff Brozena , Johnna Blair , Thomas Richardson , Mark Matthews , Dahlia Mukherjee , Erika F. H. Saunders , Saeed Abdullah

Depersonalisation/derealisation disorder (DPD) refers to frequent and persistent detachment from bodily self and disengagement from the outside world. As a dissociative disorder, DPD affects 1-2% of the population, but takes 7-12 years on…

Neurons and Cognition · Quantitative Biology 2021-11-12 Abbas Salami , Javier Andreu-Perez , Helge Gillmeister
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