Rajan Kashyap

Bio: Rajan Kashyap is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Transcranial direct-current stimulation & Psychology. The author has an hindex of 5, co-authored 19 publications receiving 100 citations. Previous affiliations of Rajan Kashyap include National University of Singapore & Hong Kong Baptist University.

The Role of Primary Motor Cortex: More Than Movement Execution.

Abstract: The predominant role of the primary motor cortex (M1) in motor execution is well acknowledged. However, additional roles of M1 are getting evident in humans owing to advances in noninvasive brain stimulation (NIBS) techniques. This review collates such studies in humans and proposes that M1 also plays a key role in higher cognitive processes. The review commences with the studies that have investigated the nature of connectivity of M1 with other cortical regions in light of studies based on NIBS. The review then moves on to discuss the studies that have demonstrated the role of M1 in higher cognitive processes such as attention, motor learning, motor consolidation, movement inhibition, somatomotor response, and movement imagery. Overall, the purpose of the review is to highlight the additional role of M1 in motor cognition besides motor control, which remains unexplored.

Simulation analyses of tDCS montages for the investigation of dorsal and ventral pathways

Abstract: Modulating higher cognitive functions like reading with transcranial direct current stimulation (tDCS) can be challenging as reading involves regions in the dorsal and ventral cortical areas that lie in close proximity. If the two pathways are stimulated simultaneously, the function of dorsal pathway (predominantly used for graphophonological conversion) might interfere with the function of the ventral pathway (used for semantics), and vice-versa. To achieve functional specificity in tDCS for investigating the two pathways of reading, it is important to stimulate each pathway per session such that the spread of current across the cortical areas due to the two montages has minimal overlap. The present study intends to achieve this by introducing a systematic approach for tDCS analysis. We employed the COMETS2 software to simulate 10 montage configurations (5 for each pathway) for three electrode sizes: 5 × 5, 3 × 3, and 5 × 7 cm2. This diversity in montage configuration is chosen since previous studies found the position and the size of anode and cathode to play an important role. The values of the magnitude of current density (MCD) obtained from the configuration were used to calculate: (i) average MCD in each cortical lobe, (ii) number of overlapping coordinates, and (iii) cortical areas with high MCD. The measures (i) and (iii) ascertained the current spread by each montage within a cortical lobe, and (ii) verified the overlap of the spread of current between a pair of montages. The analyses show that a montage using the electrode size of 5 × 5 cm2 with the anode at CP5 and cathode at CZ, and another with anode at TP7 and cathode at nape of the neck are optimal choices for dorsal and ventral pathways, respectively. To verify, we cross-validated the results with ROAST. This systematic approach was helpful in reducing the ambiguity of montage selection prior to conducting a tDCS study.

The Oxford Handbook Of Event Related Potential Components

Abstract: Thank you very much for reading the oxford handbook of event related potential components. Maybe you have knowledge that, people have look numerous times for their chosen readings like this the oxford handbook of event related potential components, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some infectious virus inside their desktop computer.

The Organization of Will

Abstract: The combining of the efforts of a number of persons for the accomplishment of a particular purpose results in the organization of effort.' Such an organization may receive its direction either from the will of an individual or from the will of a group. The process by which a group will is arrived at may be termed the organization of will. In the organization of effort, he movement is from the one toward the many, i.e., from the controlling purpose to the coordinated efforts of the various persons who contribute to its accomplishment. In the organization of will, the movement is from the many toward the one, i.e., from the wills of individual members to the single purpose which comes to direct and unify the activities of the group. Organizations may be represented graphically by the cone, the base of the cone representing the individuals organized, the apex their unifying purpose. The organizing of will may be thought of as a movement from base toward apex; the organizing of effort as a movement from apex toward base. These two types of organization may exist separately or combined. In an army, a railroad, a government department, and a x See paper on this topic in the July number of this Journal.

Deep Neural Networks and Kernel Regression Achieve Comparable Accuracies for Functional Connectivity Prediction of Behavior and Demographics

Abstract: There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there are few direct comparisons of relative utility. Here, we compared the performance of three DNN architectures and a classical machine learning algorithm (kernel regression) in predicting individual phenotypes from whole-brain resting-state functional connectivity (RSFC) patterns. One of the DNNs was a generic fully-connected feedforward neural network, while the other two DNNs were recently published approaches specifically designed to exploit the structure of connectome data. By using a combined sample of almost 10,000 participants from the Human Connectome Project (HCP) and UK Biobank, we showed that the three DNNs and kernel regression achieved similar performance across a wide range of behavioral and demographic measures. Furthermore, the generic feedforward neural network exhibited similar performance to the two state-of-the-art connectome-specific DNNs. When predicting fluid intelligence in the UK Biobank, performance of all algorithms dramatically improved when sample size increased from 100 to 1000 subjects. Improvement was smaller, but still significant, when sample size increased from 1000 to 5000 subjects. Importantly, kernel regression was competitive across all sample sizes. Overall, our study suggests that kernel regression is as effective as DNNs for RSFC-based behavioral prediction, while incurring significantly lower computational costs. Therefore, kernel regression might serve as a useful baseline algorithm for future studies.

Lexical and Sub-lexical Semantic Preview Benefits in Chinese Reading

Abstract: Semantic processing from parafoveal words is an elusive phenomenon in alphabetic languages, but it has been demonstrated only for a restricted set of noncompound Chinese characters. Using the gaze-contingent boundary paradigm, this experiment examined whether parafoveal lexical and sublexical semantic information was extracted from compound preview characters. Results generalized parafoveal semantic processing to this representative set of Chinese characters and extended the parafoveal processing to radical (sublexical) level semantic information extraction. Implications for notions of parafoveal information extraction during Chinese reading are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved) doi: 10.1037/a0026935 Yan, M., Zhou, W., Shu, H., & Kliegl, R. (Feb 27 , 2012). Lexical and sublexical semantic preview benefits in Chinese reading. Journal of Experimental Psychology: Learning, Memory, and Cognition.