AIMC Topic: Brain

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Robot assistance of motor learning: A neuro-cognitive perspective.

Neuroscience and biobehavioral reviews
The last several years have seen a number of approaches to robot assistance of motor learning. Experimental studies have produced a range of findings from beneficial effects through null-effects to detrimental effects of robot assistance. In this rev...

Computational rationality: A converging paradigm for intelligence in brains, minds, and machines.

Science (New York, N.Y.)
After growing up together, and mostly growing apart in the second half of the 20th century, the fields of artificial intelligence (AI), cognitive science, and neuroscience are reconverging on a shared view of the computational foundations of intellig...

Unsupervised lineage-based characterization of primate precursors reveals high proliferative and morphological diversity in the OSVZ.

The Journal of comparative neurology
Generation of the primate cortex is characterized by the diversity of cortical precursors and the complexity of their lineage relationships. Recent studies have reported miscellaneous precursor types based on observer classification of cell biology f...

Weighting training images by maximizing distribution similarity for supervised segmentation across scanners.

Medical image analysis
Many automatic segmentation methods are based on supervised machine learning. Such methods have proven to perform well, on the condition that they are trained on a sufficiently large manually labeled training set that is representative of the images ...

Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity--A multi-center study.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Resting-state functional magnetic resonance imaging studies examining low frequency fluctuations (0.01-0.08 Hz) have revealed atypical whole brain functional connectivity patterns in adolescents with autism spectrum disorder (ASD), and th...

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging.

Medical image analysis
Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that cont...

A Sensitive and Specific Neural Signature for Picture-Induced Negative Affect.

PLoS biology
Neuroimaging has identified many correlates of emotion but has not yet yielded brain representations predictive of the intensity of emotional experiences in individuals. We used machine learning to identify a sensitive and specific signature of emoti...

Brain Signature Predicts Negative Emotion in Individuals.

PLoS biology
Emotions are central to our daily lives, but their neural basis is not well understood; a new study uses fMRI to identify a complex multisystem neural signature of negative emotion induced by viewing distressing photographs.

Complex Learning in Bio-plausible Memristive Networks.

Scientific reports
The emerging memristor-based neuromorphic engineering promises an efficient computing paradigm. However, the lack of both internal dynamics in the previous feedforward memristive networks and efficient learning algorithms in recurrent networks, funda...

Blurring the boundaries between frame-based and frameless stereotaxy: feasibility study for brain biopsies performed with the use of a head-mounted robot.

Journal of neurosurgery
OBJECT: Frame-based stereotactic interventions are considered the gold standard for brain biopsies, but they have limitations with regard to flexibility and patient comfort because of the bulky head ring attached to the patient. Frameless image guida...