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A high percentage of patients with Parkinson's disease suffer from depression in addition to their motor disabilities. However, the etiology of this depression and its relation to Parkinson's disease are unknown. Within the framework of the monoamine deficiency hypothesis of depression, we propose that the dopaminergic and serotonergic systems are coupled(More)
This paper presents a solution to the problem of pattern formation on a grid, for a group of identical autonomous robotic agents, that have very limited communication capabilities. The chief method of communication between the agents is by moving and observing their positions on the grid. The proposed algorithm is a sequence of several coordinated “bee(More)
The minimal change in a stimulus property that is detectable by neurons has been often quantified using the receiver operating characteristic (ROC) curve, but recent studies introduced the use of the related Fisher information (FI). Whereas ROC analysis and FI quantify the information available for discriminating between two stimuli, global aspects of the(More)
The monoamine-deficiency and the hippocampal-neurogenesis hypotheses of depression propose that alterations in the serotonin system and of hippocampal functionality are critical in the pathogenesis of depression. We measured the alterations in the connectivity level of the raphe nucleus in the chronic mild stress (CMS) rat model of depression using the(More)
This paper aims to better understand the physiological meaning of negative correlations in resting state functional connectivity MRI (r-fcMRI). The correlations between anatomy-based brain regions of 18 healthy humans were calculated and analyzed with and without a correction for global signal and with and without spatial smoothing. In addition,(More)
A simple method to generate a 2-D binary grid pattern, which allows for absolute and accurate self-location in a finite planar region, is proposed. The pattern encodes position information in a local way so that reading a small number of its black or white pixels at any place provides sufficient data from which the location can be decoded both efficiently(More)
There is a growing understanding that both top-down and bottom-up signals underlie perception. But it is not known how these signals integrate with each other and how this depends on the perceived stimuli's predictability. 'Predictive coding' theories describe this integration in terms of how well top-down predictions fit with bottom-up sensory input.(More)
Understanding the integration of top-down and bottom-up signals is essential for the study of perception. Current accounts of predictive coding describe this in terms of interactions between state units encoding expectations or predictions, and error units encoding prediction error. However, direct neural evidence for such interactions has not been well(More)
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