AIMC Topic: Brain

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Using artificial neural networks to ask 'why' questions of minds and brains.

Trends in neurosciences
Neuroscientists have long characterized the properties and functions of the nervous system, and are increasingly succeeding in answering how brains perform the tasks they do. But the question 'why' brains work the way they do is asked less often. The...

High-throughput 3DRA segmentation of brain vasculature and aneurysms using deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic segmentation of the cerebral vasculature and aneurysms facilitates incidental detection of aneurysms. The assessment of aneurysm rupture risk assists with pre-operative treatment planning and enables in-silico inv...

Deep learning prediction of diffusion MRI data with microstructure-sensitive loss functions.

Medical image analysis
Deep learning prediction of diffusion MRI (DMRI) data relies on the utilization of effective loss functions. Existing losses typically measure the signal-wise differences between the predicted and target DMRI data without considering the quality of d...

Parametric control of flexible timing through low-dimensional neural manifolds.

Neuron
Biological brains possess an unparalleled ability to adapt behavioral responses to changing stimuli and environments. How neural processes enable this capacity is a fundamental open question. Previous works have identified two candidate mechanisms: a...

A machine-learning algorithm for predicting brain age using Rey-Osterrieth complex figure tests of healthy participants.

Applied neuropsychology. Adult
OBJECTIVE: Neuropsychologists widely use the Rey-Osterrieth complex figure test (RCFT) as part of neuropsychological test batteries to evaluate cognitive function and assess constructional ability, with age being the most significant factor. Our stud...

Decoding of human identity by computer vision and neuronal vision.

Scientific reports
Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity...

Deep Learning-Based Multiclass Brain Tissue Segmentation in Fetal MRIs.

Sensors (Basel, Switzerland)
Fetal brain tissue segmentation is essential for quantifying the presence of congenital disorders in the developing fetus. Manual segmentation of fetal brain tissue is cumbersome and time-consuming, so using an automatic segmentation method can great...

Classification of BCI Multiclass Motor Imagery Task Based on Artificial Neural Network.

Clinical EEG and neuroscience
Motor imagery (MI) signals recorded by electroencephalography provide the most practical basis for conceiving brain-computer interfaces (BCI). These interfaces offer a high degree of freedom. This helps people with motor disabilities communicate with...