AIMC Topic: Brain

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Support vector machine-based multivariate pattern classification of methamphetamine dependence using arterial spin labeling.

Addiction biology
Arterial spin labeling (ASL) magnetic resonance imaging has been widely applied to identify cerebral blood flow (CBF) abnormalities in a number of brain disorders. To evaluate its significance in detecting methamphetamine (MA) dependence, this study ...

Qoala-T: A supervised-learning tool for quality control of FreeSurfer segmented MRI data.

NeuroImage
Performing quality control to detect image artifacts and data-processing errors is crucial in structural magnetic resonance imaging, especially in developmental studies. Currently, many studies rely on visual inspection by trained raters for quality ...

Accuracy of robot-assisted versus optical frameless navigated stereoelectroencephalography electrode placement in children.

Journal of neurosurgery. Pediatrics
OBJECTIVE The aim of this study was to compare the accuracy of optical frameless neuronavigation (ON) and robot-assisted (RA) stereoelectroencephalography (SEEG) electrode placement in children, and to identify factors that might increase the risk of...

A Deep Learning-Based Approach to Reduce Rescan and Recall Rates in Clinical MRI Examinations.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: MR imaging rescans and recalls can create large hospital revenue loss. The purpose of this study was to develop a fast, automated method for assessing rescan need in motion-corrupted brain series.

Pain-Related Fear-Dissociable Neural Sources of Different Fear Constructs.

eNeuro
Fear of pain demonstrates significant prognostic value regarding the development of persistent musculoskeletal pain and disability. Its assessment often relies on self-report measures of pain-related fear by a variety of questionnaires. However, base...

State-of-the-art review on deep learning in medical imaging.

Frontiers in bioscience (Landmark edition)
Deep learning (DL) is affecting each and every sphere of public and private lives and becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the activities of neurons in the neocortex of human brain where the thought...

DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning.

BMC bioinformatics
BACKGROUND: N6-methyladensine (m6A) is a common and abundant RNA methylation modification found in various species. As a type of post-transcriptional methylation, m6A plays an important role in diverse RNA activities such as alternative splicing, an ...

Task activations produce spurious but systematic inflation of task functional connectivity estimates.

NeuroImage
Most neuroscientific studies have focused on task-evoked activations (activity amplitudes at specific brain locations), providing limited insight into the functional relationships between separate brain locations. Task-state functional connectivity (...

Automated Cell Counts on Tissue Sections by Deep Learning and Unbiased Stereology.

Journal of chemical neuroanatomy
In recent decades stereology-based studies have played a significant role in understanding brain aging and developing novel drug discovery strategies for treatment of neurological disease and mental illness. A major obstacle to further progress in a ...

Resting-state anticorrelated networks in Schizophrenia.

Psychiatry research. Neuroimaging
Converging evidences from different lines of research suggest abnormalities in functional brain connectivity in schizophrenia. While positively correlated brain networks have been well researched, anticorrelated functional connectivity remains under ...