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Brain Mapping

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Explainability of three-dimensional convolutional neural networks for functional magnetic resonance imaging of Alzheimer's disease classification based on gradient-weighted class activation mapping.

PloS one
Currently, numerous studies focus on employing fMRI-based deep neural networks to diagnose neurological disorders such as Alzheimer's Disease (AD), yet only a handful have provided results regarding explainability. We address this gap by applying sev...

CT-Net: an interpretable CNN-Transformer fusion network for fNIRS classification.

Medical & biological engineering & computing
Functional near-infrared spectroscopy (fNIRS), an optical neuroimaging technique, has been widely used in the field of brain activity recognition and brain-computer interface. Existing works have proposed deep learning-based algorithms for the fNIRS ...

A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivity.

Journal of affective disorders
BACKGROUND: Functional connectivity has garnered interest as a potential biomarker of psychiatric disorders including borderline personality disorder (BPD). However, small sample sizes and lack of within-study replications have led to divergent findi...

Shared functional specialization in transformer-based language models and the human brain.

Nature communications
When processing language, the brain is thought to deploy specialized computations to construct meaning from complex linguistic structures. Recently, artificial neural networks based on the Transformer architecture have revolutionized the field of nat...

Spontaneous brain activity in patients with central retinal artery occlusion: a resting-state functional MRI study using machine learning.

Neuroreport
Central retinal artery occlusion (CRAO) is a serious eye condition that poses a risk to vision, resulting from the blockage of the central retinal artery. Because of the anatomical connection between the ocular artery, which derives from the internal...

Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes.

Communications biology
In this study, we aimed to compare imaging-based features of brain function, measured by resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total intracranial volume to predict behavioral measures. We developed a ma...

Aberrant patterns of spontaneous brain activity in schizophrenia: A resting-state fMRI study and classification analysis.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Schizophrenia is a prevalent mental disorder, leading to severe disability. Currently, the absence of objective biomarkers hinders effective diagnosis. This study was conducted to explore the aberrant spontaneous brain activity and invest...

Do we empathize humanoid robots and humans in the same way? Behavioral and multimodal brain imaging investigations.

Cerebral cortex (New York, N.Y. : 1991)
Humanoid robots have been designed to look more and more like humans to meet social demands. How do people empathize humanoid robots who look the same as but are essentially different from humans? We addressed this issue by examining subjective feeli...

7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery.

European radiology experimental
Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in ar...

A Plug-In Graph Neural Network to Boost Temporal Sensitivity in fMRI Analysis.

IEEE journal of biomedical and health informatics
Learning-based methods offer performance leaps over traditional methods in classification analysis of high-dimensional functional MRI (fMRI) data. In this domain, deep-learning models that analyze functional connectivity (FC) features among brain reg...