AI Medical Compendium Journal:
Brain structure & function

Showing 1 to 10 of 10 articles

Classifying athletes and non-athletes by differences in spontaneous brain activity: a machine learning and fMRI study.

Brain structure & function
Different types of sports training can induce distinct changes in brain activity and function; however, it remains unclear if there are commonalities across various sports disciplines. Moreover, the relationship between these brain activity alteratio...

ds-FCRN: three-dimensional dual-stream fully convolutional residual networks and transformer-based global-local feature learning for brain age prediction.

Brain structure & function
The brain undergoes atrophy and cognitive decline with advancing age. The utilization of brain age prediction represents a pioneering methodology in the examination of brain aging. This study aims to develop a deep learning model with high predictive...

The human cost of ethical artificial intelligence.

Brain structure & function
Foundational models such as ChatGPT critically depend on vast data scales the internet uniquely enables. This implies exposure to material varying widely in logical sense, factual fidelity, moral value, and even legal status. Whereas data scaling is ...

Structure can predict function in the human brain: a graph neural network deep learning model of functional connectivity and centrality based on structural connectivity.

Brain structure & function
Although functional connectivity and associated graph theory measures (e.g., centrality; how centrally important to the network a region is) are widely used in brain research, the full extent to which these functional measures are related to the unde...

The NanoZoomer artificial intelligence connectomics pipeline for tracer injection studies of the marmoset brain.

Brain structure & function
We describe our connectomics pipeline for processing anterograde tracer injection data for the brain of the common marmoset (Callithrix jacchus). Brain sections were imaged using a batch slide scanner (NanoZoomer 2.0-HT) and we used artificial intell...

Mechanisms of memory storage in a model perirhinal network.

Brain structure & function
The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked ...

Graph-guided joint prediction of class label and clinical scores for the Alzheimer's disease.

Brain structure & function
Accurate diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, is very important for early treatment. Over the last decade, various machine learning methods have been proposed to predict disease status and clinica...

Deep sparse multi-task learning for feature selection in Alzheimer's disease diagnosis.

Brain structure & function
Recently, neuroimaging-based Alzheimer's disease (AD) or mild cognitive impairment (MCI) diagnosis has attracted researchers in the field, due to the increasing prevalence of the diseases. Unfortunately, the unfavorable high-dimensional nature of neu...

Synchronization among neuronal pools without common inputs: in vivo study.

Brain structure & function
Periodic synchronization of activity among neuronal pools has been related to substantial neural processes and information throughput in the neocortical network. However, the mechanisms of generating such periodic synchronization among distributed po...

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.

Brain structure & function
Recently, there have been great interests for computer-aided diagnosis of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods that considered simple low-level features such as gray matter tis...