نتایج جستجو برای: voxel pattern analysismvpa
تعداد نتایج: 361371 فیلتر نتایج به سال:
Evidence suggests that the cerebellum contributes to cognition as well as motor function. We investigated cerebellar grey matter (GM) and white matter (WM) changes from magnetic resonance images in dementia with Lewy bodies (DLB), Alzheimer׳s disease (AD) and healthy older subjects using voxel-based morphometry (VBM). Subjects (39 controls, 41 DLB, and 48 AD) underwent magnetic resonance imagin...
Previous studies have revealed regions in human visual cortex with a strong preference for faces, headless bodies, and buildings. We investigated whether the pattern of activity in these category-selective regions is related to more subordinate distinctions among objects. Our experiments included two types of faces (elderly faces and baby faces), body parts (hands and torsos), and buildings (ru...
We propose a novel concept for comparing fMRI activations of brain regions of interest (ROI) across subjects. Each individual activation pattern is compared with a group activation model, rather than comparing the activations directly, e.g. on a voxel–level basis. Meaningful mappings of functional activations are based on correspondences in the respective modal eigenspaces. First results on aud...
In two replication studies we examined response bias and dependencies in voluntary decisions. We trained a linear classifier to predict "spontaneous decisions" and in the second study "hidden intentions" from responses in preceding trials and achieved comparable prediction accuracies as reported for multivariate pattern classification based on voxel activities in frontopolar cortex. We discuss ...
A key goal of cognitive neuroscience is to find simple and direct connections between brain and behaviour. However, fMRI analysis typically involves choices between many possible options, with each choice potentially biasing any brain-behaviour correlations that emerge. Standard methods of fMRI analysis assess each voxel individually, but then face the problem of selection bias when combining t...
Huang (arXiv:1612.03270) argues that the perceptual learning induced by our decoded neurofeedback method (DecNef) can be explained by Hebbian synaptic plasticity of connections between V1/V2 and V3/V4 rather than that within V1/V2, and that reinforcement learning at a cellular level should not be possible, and thus challenges our conclusions. In this reply, first, we show that Huang’s model is ...
UNLABELLED The resting brain dynamics self-organize into a finite number of correlated patterns known as resting-state networks (RSNs). It is well known that techniques such as independent component analysis can separate the brain activity at rest to provide such RSNs, but the specific pattern of interaction between RSNs is not yet fully understood. To this aim, we propose here a novel method t...
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