Xerxes D. Arsiwalla

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BrainX(3) is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data(More)
We analyze large N phase transitions for U(N) q-deformed two-dimensional YangMills theory on the sphere. We determine the phase diagram of the model and we show that, for small values of the deformation parameter, the theory exhibits a phase transition which is smoothly connected to the Douglas-Kazakov phase transition. For large values of the deformation(More)
The intricate web of information we generate nowadays is more massive than ever in the history of mankind. The sheer enormity of big data makes the task of extracting semantic associations out of complex networks more complicated. Stemming this "data deluge" calls for novel unprecedented technologies. In this work, we engineered a system that enhances a(More)
Multi-electrode recordings of local field potentials (LFPs) provide the opportunity to investigate the spatiotemporal organization of neural activity on the scale of several millimeters. In particular, the phases of oscillatory LFPs allow studying the coordination of neural oscillations in time and space and to tie it to cognitive processing. Given the(More)
Compared to standard laboratory protocols, the measurement of psychophysiological signals in real world experiments poses technical and methodological challenges due to external factors that cannot be directly controlled. To address this problem, we propose a hybrid approach based on an immersive and human accessible space called the eXperience Induction(More)
How does one quantify dynamic complexity in large stochastic networks? While measures of integrated information serve as a good start to address these issues, all existing versions of the measure have been plagued with normalization ambiguities and combinatorial explosions which has hindered applications to large-scale networks. In this paper, we propose a(More)
In this note we reconsider Sen’s entropy function analysis for 5D supergravity actions containing Chern-Simons terms. The apparent lack of gauge invariance is usually tackled via a 4D reduction. Here we motivate how a systematic 5D procedure also works. In doing so, it becomes important to identify the correct 5D charges. In particular, we perform explicit(More)