AIMC Topic: Brain Mapping

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Spec2VolCAMU-Net: a spectrogram-to-volume model for EEG-to-fMRI reconstruction based on Multi-directional Time-Frequency Convolutional Attention Encoder and Vision-Mamba U-Net.

Journal of neural engineering
High-resolution functional magnetic resonance imaging (fMRI) is essential for mapping human brain activity; however, it remains costly and logistically challenging. If comparable volumes could be generated directly from widely available scalp electro...

Image complexity-based fMRI-BOLD visual network categorization across visual datasets using topological descriptors and deep-hybrid learning.

Scientific reports
This study proposes a new approach that investigates differences in topological characteristics of visual networks, which are constructed using fMRI BOLD time-series corresponding to visual datasets of COCO, ImageNet, and SUN. A publicly available BO...

Forewarned Is Forearmed: The Single- and Dual-Brain Mechanisms in Detectors from Dyads of Varying Social Distance during Deceptive Outcome Evaluation.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Preventing deception requires understanding how lie detectors process social information across social distance. Although the outcomes of such information are crucial, how detectors evaluate gains or losses from close versus distant others remains un...

Neural predictors of hidden, persistent psychological states at work.

Proceedings of the National Academy of Sciences of the United States of America
Common workplace challenges such as feeling overwhelmed, burned out, or disengaged often remain hidden due to fear of judgment or social norms, contributing to rising mental health crises and organizational dysfunction. This study presents a brain-ba...

Reconfiguration of functional brain hierarchy in schizophrenia.

Translational psychiatry
The multidimensional nature of schizophrenia requires a comprehensive exploration of the functional and structural brain networks. While prior research has provided valuable insights into these aspects, our study goes a step further to investigate th...

A deep learning-enriched framework for analyzing brain functional connectivity.

Scientific reports
Cognitive and motor functions require a coordinated communication among brain regions, with the directionality of interactions playing a key role, as the brain relies on functional asymmetries of reciprocal connections. Predictive models based on dee...

Beyond tractography in brain connectivity mapping with dMRI morphometry and functional networks.

Brain structure & function
Traditional brain connectivity studies have focused mainly on structural connectivity, often relying on tractography with diffusion MRI (dMRI) to reconstruct white matter pathways. In parallel, studies of functional connectivity have examined correla...

Machine Learning-Based Classification of White Matter Functional Changes in Stroke Patients Using Resting-State fMRI.

Brain topography
Neuroimaging studies of brain function are important research methods widely applied to stroke patients. Currently, a large number of studies have focused on functional imaging of the gray matter cortex. Relevant research indicates that certain areas...

How musicality enhances top-down and bottom-up selective attention: Insights from precise separation of simultaneous neural responses.

Science advances
Natural environments typically contain a blend of simultaneous sounds. A substantial challenge in neuroscience is identifying specific neural signals corresponding to each sound and analyzing them separately. Combining frequency tagging and machine l...

From perceiving words to reading: Neural multivariate representations of sublexical vs. lexico-semantic processing during word-reading.

NeuroImage
While the neural underpinnings of semantic cognition have been extensively studied, the brain mechanisms that allow the extraction of meaning from the initially perceptual visual linguistic input are less understood. These mechanisms have typically b...