AIMC Topic: Brain

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Could simplified stimuli change how the brain performs visual search tasks? A deep neural network study.

Journal of vision
Visual search is a complex behavior influenced by many factors. To control for these factors, many studies use highly simplified stimuli. However, the statistics of these stimuli are very different from the statistics of the natural images that the h...

Beyond the Brain: MIDS Extends BIDS to Multiple Modalities and Anatomical Regions.

Studies in health technology and informatics
Brain Imaging Data Structure (BIDS) provides a valuable tool to organise brain imaging data into a clear and easy standard directory structure. Moreover, BIDS is widely supported by the scientific community and has been established as a powerful stan...

Relational graph convolutional networks for predicting blood-brain barrier penetration of drug molecules.

Bioinformatics (Oxford, England)
MOTIVATION: Evaluating the blood-brain barrier (BBB) permeability of drug molecules is a critical step in brain drug development. Traditional methods for the evaluation require complicated in vitro or in vivo testing. Alternatively, in silico predict...

Automatic Identification of Brain Injury Mechanism Based on Deep Learning.

Fa yi xue za zhi
OBJECTIVES: To apply the convolutional neural network (CNN) Inception_v3 model in automatic identification of acceleration and deceleration injury based on CT images of brain, and to explore the application prospect of deep learning technology in for...

[Evaluation of brain injury caused by stick type blunt instruments based on convolutional neural network and finite element method].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because of its technology barrier of time-consuming and strong professionalism. In this study, a rapid and ...

Gell-Mann-Low Criticality in Neural Networks.

Physical review letters
Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory of critical brain dynamics, however, so far limits insights into this form of biological information processing to mean-field results. These methods ne...

Direct Discriminative Decoder Models for Analysis of High-Dimensional Dynamical Neural Data.

Neural computation
With the accelerated development of neural recording technology over the past few decades, research in integrative neuroscience has become increasingly reliant on data analysis methods that are scalable to high-dimensional recordings and computationa...

Learning to represent continuous variables in heterogeneous neural networks.

Cell reports
Animals must monitor continuous variables such as position or head direction. Manifold attractor networks-which enable a continuum of persistent neuronal states-provide a key framework to explain this monitoring ability. Neural networks with symmetri...

How to remove or control confounds in predictive models, with applications to brain biomarkers.

GigaScience
BACKGROUND: With increasing data sizes and more easily available computational methods, neurosciences rely more and more on predictive modeling with machine learning, e.g., to extract disease biomarkers. Yet, a successful prediction may capture a con...