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V. Srinivasa Chakravarthy

Bio: V. Srinivasa Chakravarthy is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Basal ganglia & Computer science. The author has an hindex of 19, co-authored 111 publications receiving 1079 citations. Previous affiliations of V. Srinivasa Chakravarthy include Indian Institutes of Technology & Department of Biotechnology.


Papers
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Journal ArticleDOI
TL;DR: A new perspective of neurodegenerative diseases as metabolic disorders at molecular, cellular, and systems levels is presented to understand a common underlying mechanism of the many facets of the disease and may lead to more promising disease-modifying therapeutic interventions.
Abstract: Neurodegenerative diseases, including Alzheimer, Parkinson, Huntington, and amyotrophic lateral sclerosis, are a prominent class of neurological diseases currently without a cure. They are characterized by an inexorable loss of a specific type of neurons. The selective vulnerability of specific neuronal clusters (typically a subcortical cluster) in the early stages, followed by the spread of the disease to higher cortical areas, is a typical pattern of disease progression. Neurodegenerative diseases share a range of molecular and cellular pathologies, including protein aggregation, mitochondrial dysfunction, glutamate toxicity, calcium load, proteolytic stress, oxidative stress, neuroinflammation, and aging, which contribute to neuronal death. Efforts to treat these diseases are often limited by the fact that they tend to address any one of the above pathological changes while ignoring others. Lack of clarity regarding a possible root cause that underlies all the above pathologies poses a significant challenge. In search of an integrative theory for neurodegenerative pathology, we hypothesize that metabolic deficiency in certain vulnerable neuronal clusters is the common underlying thread that links many dimensions of the disease. The current review aims to present an outline of such an integrative theory. We present a new perspective of neurodegenerative diseases as metabolic disorders at molecular, cellular, and systems levels. This helps to understand a common underlying mechanism of the many facets of the disease and may lead to more promising disease-modifying therapeutic interventions. Here, we briefly discuss the selective metabolic vulnerability of specific neuronal clusters and also the involvement of glia and vascular dysfunctions. Any failure in satisfaction of the metabolic demand by the neurons triggers a chain of events that precipitate various manifestations of neurodegenerative pathology.

122 citations

Proceedings Article
23 Oct 2006
TL;DR: A system for recognition of online handwritten characters has been presented for Indian writing systems and the results have been presented after testing the system on Devanagari and Telugu scripts.
Abstract: A system for recognition of online handwritten characters has been presented for Indian writing systems. A handwritten character is represented as a sequence of strokes whose features are extracted and classied. Support vector machines have been used for constructing the stroke recognition engine. The results have been presented after testing the system on Devanagari and Telugu scripts.

99 citations

Journal ArticleDOI
TL;DR: This review article focuses on CCN models of the basal ganglia and how they use the neuroanatomy of the BG to account for cognitive and motor functions such as categorization, instrumental conditioning, probabilistic learning, working memory, sequence learning, automaticity, reaching, handwriting, and eye saccades.
Abstract: Many computational models of the basal ganglia have been proposed over the past twenty-five years. While computational neuroscience models have focused on closely matching the neurobiology of the basal ganglia, computational cognitive neuroscience models have focused on how the basal ganglia can be used to implement cognitive and motor functions. This review article focuses on computational cognitive neuroscience models of the basal ganglia and how they use the neuroanatomy of the basal ganglia to account for cognitive and motor functions such as categorization, instrumental conditioning, probabilistic learning, working memory, sequence learning, automaticity, reaching, handwriting, and eye saccades. A total of 19 basal ganglia models accounting for one or more of these functions are reviewed and compared. The review concludes with a discussion of the limitations of existing computational cognitive neuroscience models of the basal ganglia and prescriptions for future modeling, including the need for computational models of the basal ganglia that can simultaneously account for cognitive and motor functions, and the need for a more complete specification of the role of the basal ganglia in behavioral functions.

63 citations

18 Aug 2016
TL;DR: Table of contents Functional advantages of cell-type heterogeneity in neural circuits, Dynamics and biomarkers of mental disorders, and Objective criteria for computational neuroscience model selection are presented.
Abstract: Table of contentsA1 Functional advantages of cell-type heterogeneity in neural circuitsTatyana O. SharpeeA2 Mesoscopic modeling of propagating waves in visual cortexAlain DestexheA3 Dynamics and biomarkers of mental disordersMitsuo KawatoF1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneuronsVladislav Sekulić, Frances K. SkinnerF2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brainsDaniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán SomogyváriF3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir JosićO1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generatorsIrene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo VaronaO2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrainEunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun ChoiO3 Modeling auditory stream segregation, build-up and bistabilityJames Rankin, Pamela Osborn Popp, John RinzelO4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fieldsAlejandro Tabas, André Rupp, Emili Balaguer-BallesterO5 A simple model of retinal response to multi-electrode stimulationMatias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish MeffinO6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination taskVeronika Koren, Timm Lochmann, Valentin Dragoi, Klaus ObermayerO7 Input-location dependent gain modulation in cerebellar nucleus neuronsMaria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker SteuberO8 Analytic solution of cable energy function for cortical axons and dendritesHuiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo YuO9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal networkJimin Kim, Will Leahy, Eli ShlizermanO10 Is the model any good? Objective criteria for computational neuroscience model selectionJustas Birgiolas, Richard C. Gerkin, Sharon M. CrookO11 Cooperation and competition of gamma oscillation mechanismsAtthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan GielenO12 A discrete structure of the brain wavesYuri Dabaghian, Justin DeVito, Luca PerottiO13 Direction-specific silencing of the Drosophila gaze stabilization systemAnmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby MaimonO14 What does the fruit fly think about values? A model of olfactory associative learningChang Zhao, Yves Widmer, Simon Sprecher,Walter SennO15 Effects of ionic diffusion on power spectra of local field potentials (LFP)Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen, Gaute T. EinevollO16 Large-scale cortical models towards understanding relationship between brain structure abnormalities and cognitive deficitsYasunori YamadaO17 Spatial coarse-graining the brain: origin of minicolumnsMoira L. Steyn-Ross, D. Alistair Steyn-RossO18 Modeling large-scale cortical networks with laminar structureJorge F. Mejias, John D. Murray, Henry Kennedy, Xiao-Jing WangO19 Information filtering by partial synchronous spikes in a neural populationAlexandra Kruscha, Jan Grewe, Jan Benda, Benjamin LindnerO20 Decoding context-dependent olfactory valence in Drosophila Laurent Badel, Kazumi Ohta, Yoshiko Tsuchimoto, Hokto KazamaP1 Neural network as a scale-free network: the role of a hubB. KahngP2 Hemodynamic responses to emotions and decisions using near-infrared spectroscopy optical imagingNicoladie D. TamP3 Phase space analysis of hemodynamic responses to intentional movement directions using functional near-infrared spectroscopy (fNIRS) optical imaging techniqueNicoladie D.Tam, Luca Pollonini, George ZouridakisP4 Modeling jamming avoidance of weakly electric fishJaehyun Soh, DaeEun KimP5 Synergy and redundancy of retinal ganglion cells in predictionMinsu Yoo, S. E. PalmerP6 A neural field model with a third dimension representing cortical depthViviana Culmone, Ingo BojakP7 Network analysis of a probabilistic connectivity model of the Xenopus tadpole spinal cordAndrea Ferrario, Robert Merrison-Hort, Roman BorisyukP8 The recognition dynamics in the brainChang Sub KimP9 Multivariate spike train analysis using a positive definite kernelTaro TezukaP10 Synchronization of burst periods may govern slow brain dynamics during general anesthesiaPangyu JooP11 The ionic basis of heterogeneity affects stochastic synchronyYoung-Ah Rho, Shawn D. Burton, G. Bard Ermentrout, Jaeseung Jeong, Nathaniel N. UrbanP12 Circular statistics of noise in spike trains with a periodic componentPetr MarsalekP14 Representations of directions in EEG-BCI using Gaussian readoutsHoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung JeongP15 Action selection and reinforcement learning in basal ganglia during reaching movementsYaroslav I. Molkov, Khaldoun Hamade, Wondimu Teka, William H. Barnett, Taegyo Kim, Sergey Markin, Ilya A. RybakP17 Axon guidance: modeling axonal growth in T-Junction assayCsaba Forro, Harald Dermutz, László Demkó, János VörösP19 Transient cell assembly networks encode persistent spatial memoriesYuri Dabaghian, Andrey BabichevP20 Theory of population coupling and applications to describe high order correlations in large populations of interacting neuronsHaiping HuangP21 Design of biologically-realistic simulations for motor controlSergio Verduzco-FloresP22 Towards understanding the functional impact of the behavioural variability of neuronsFilipa Dos Santos, Peter AndrasP23 Different oscillatory dynamics underlying gamma entrainment deficits in schizophreniaChristoph Metzner, Achim Schweikard, Bartosz ZurowskiP24 Memory recall and spike frequency adaptationJames P. Roach, Leonard M. Sander, Michal R. ZochowskiP25 Stability of neural networks and memory consolidation preferentially occur near criticalityQuinton M. Skilling, Nicolette Ognjanovski, Sara J. Aton, Michal ZochowskiP26 Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural SystemsSheng-Jun Wang, Guang Ouyang, Jing Guang, Mingsha Zhang, K. Y. Michael Wong, Changsong ZhouP27 Neurofield: a C++ library for fast simulation of 2D neural field modelsPeter A. Robinson, Paula Sanz-Leon, Peter M. Drysdale, Felix Fung, Romesh G. Abeysuriya, Chris J. Rennie, Xuelong ZhaoP28 Action-based grounding: Beyond encoding/decoding in neural codeYoonsuck Choe, Huei-Fang YangP29 Neural computation in a dynamical system with multiple time scalesYuanyuan Mi, Xiaohan Lin, Si WuP30 Maximum entropy models for 3D layouts of orientation selectivityJoscha Liedtke, Manuel Schottdorf, Fred WolfP31 A behavioral assay for probing computations underlying curiosity in rodentsYoriko Yamamura, Jeffery R. WickensP32 Using statistical sampling to balance error function contributions to optimization of conductance-based modelsTimothy Rumbell, Julia Ramsey, Amy Reyes, Danel Draguljić, Patrick R. Hof, Jennifer Luebke, Christina M. WeaverP33 Exploration and implementation of a self-growing and self-organizing neuron network building algorithmHu He, Xu Yang, Hailin Ma, Zhiheng Xu, Yuzhe WangP34 Disrupted resting state brain network in obese subjects: a data-driven graph theory analysisKwangyeol Baek, Laurel S. Morris, Prantik Kundu, Valerie VoonP35 Dynamics of cooperative excitatory and inhibitory plasticityEverton J. Agnes, Tim P. VogelsP36 Frequency-dependent oscillatory signal gating in feed-forward networks of integrate-and-fire neuronsWilliam F. Podlaski, Tim P. VogelsP37 Phenomenological neural model for adaptation of neurons in area ITMartin Giese, Pradeep Kuravi, Rufin VogelsP38 ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experimentAlexander Seeholzer, William Podlaski, Rajnish Ranjan, Tim VogelsP39 Temporal input discrimination from the interaction between dynamic synapses and neural subthreshold oscillationsJoaquin J. Torres, Fabiano Baroni, Roberto Latorre, Pablo VaronaP40 Different roles for transient and sustained activity during active visual processingBart Gips, Eric Lowet, Mark J. Roberts, Peter de Weerd, Ole Jensen, Jan van der EerdenP41 Scale-free functional networks of 2D Ising model are highly robust against structural defects: neuroscience implicationsAbdorreza Goodarzinick, Mohammad D. Niry, Alireza ValizadehP42 High frequency neuron can facilitate propagation of signal in neural networksAref Pariz, Shervin S. Parsi, Alireza ValizadehP43 Investigating the effect of Alzheimer’s disease related amyloidopathy on gamma oscillations in the CA1 region of the hippocampusJulia M. Warburton, Lucia Marucci, Francesco Tamagnini, Jon Brown, Krasimira Tsaneva-AtanasovaP44 Long-tailed distributions of inhibitory and excitatory weights in a balanced network with eSTDP and iSTDPFlorence I. Kleberg, Jochen TrieschP45 Simulation of EMG recording from hand muscle due to TMS of motor cortexBahar Moezzi, Nicolangelo Iannella, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Michael C. Ridding, Jochen TrieschP46 Structure and dynamics of axon network formed in primary cell cultureMartin Zapotocky, Daniel Smit, Coralie Fouquet, Alain TrembleauP47 Efficient signal processing and sampling in random networks that generate variabilitySakyasingha Dasgupta, Isao Nishikawa, Kazuyuki Aihara, Taro ToyoizumiP48 Modeling the effect of riluzole on bursting in respiratory neural networksDaniel T. Robb, Nick Mellen, Natalia ToporikovaP49 Mapping relaxation training using effective connectivity analysisRongxiang Tang

59 citations


Cited by
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Journal ArticleDOI
06 Jun 1986-JAMA
TL;DR: The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or her own research.
Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

7,563 citations

01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

2,933 citations

01 Jan 2010
TL;DR: In this paper, the authors describe a scenario where a group of people are attempting to find a solution to the problem of "finding the needle in a haystack" in the environment.
Abstract: 中枢神経系疾患の治療は正常細胞(ニューロン)の機能維持を目的とするが,脳血管障害のように機能障害の原因が細胞の死滅に基づくことは多い.一方,脳腫瘍の治療においては薬物療法や放射線療法といった腫瘍細胞の死滅を目標とするものが大きな位置を占める.いずれの場合にも,細胞死の機序を理解することは各種病態や治療法の理解のうえで重要である.現在のところ最も研究の進んでいる細胞死の型はアポトーシスである.そのなかで重要な位置を占めるミトコンドリアにおける反応および抗アポトーシス因子について概要を紹介する.

2,716 citations