Individual differences in direction-selective motion adaptation revealed by change-detection performance.

The motion aftereffect (MAE) and motion adaptation in general are usually considered to be universal phenomena. However, in a preliminary study using a bias-free measure of the MAE we found some individuals who showed at best a weak effect of adaptation. These same individuals also performed poorly in a "change detection" test of motion adaptation based on visual search, leading to the conjecture that there is a bimodality in the population with respect to motion adaptation.

Monocular and binocular mechanisms detect modulations of dot density and dot contrast.

Strong reciprocity has been demonstrated between (1) spatial modulations of dot density and modulations of dot luminance, and (2) modulations of dot density and modulations of dot contrast, in textures. The latter are much easier to detect when presented in phase with one another than when presented 180° out of phase, although out-of-phase modulations can also be detected given sufficient amplitude. This result supports the existence of two detection mechanisms: one that is excited by both density modulations and contrast modulations (quiescent when those modulations are presented 180° out of phase) and another that is relatively insensitive to either density modulations or contrast modulations (thus remaining stimulated regardless of phase angle).

Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning.

Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely 'core regions') comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients.

Subthalamic stimulation modulates motor network in Parkinson's disease: recover, relieve and remodel.

Aberrant dynamic switches between internal brain states are believed to underlie motor dysfunction in Parkinson's disease. Deep brain stimulation of the subthalamic nucleus is a well-established treatment for the motor symptoms of Parkinson's disease, yet it remains poorly understood how subthalamic stimulation modulates the whole-brain intrinsic motor network state dynamics. To investigate this, we acquired resting-state functional magnetic resonance imaging time-series data from 27 medication-free patients with Parkinson's disease (mean age: 64.

Subthalamic and pallidal stimulation in Parkinson's disease induce distinct brain topological reconstruction.

The subthalamic nucleus (STN) and globus pallidus internus (GPi) are the two most common and effective target brain areas for deep brain stimulation (DBS) treatment of advanced Parkinson's disease. Although DBS has been shown to restore functional neural circuits of this disorder, the changes in topological organization associated with active DBS of each target remain unknown. To investigate this, we acquired resting-state functional magnetic resonance imaging (fMRI) data from 34 medication-free patients with Parkinson's disease that had DBS electrodes implanted in either the subthalamic nucleus or internal globus pallidus (n = 17 each), in both ON and OFF DBS states.