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Basal Ganglia

Nair, S.S.; Chakravarthy, S. A Computational Model of Deep Brain Stimulation for Parkinson’s Disease Tremor and Bradykinesia. Brain Sci. 2024, 14, 620. Link

Vigneswaran, C., Nair, S.S. & Chakravarthy, V.S. A Basal Ganglia model for understanding working memory functions in healthy and Parkinson's conditions. Cogn Neurodyn (2024). Link

Nair, S. S., Muddapu, V. R., Vigneswaran, C., Balasubramani, P. P., Ramanathan, D. S., Mishra, J., & Chakravarthy, V. S. (2023). A generalized reinforcement learning based deep neural network agent model for diverse cognitive constructs. Scientific Reports, 13(1), 5928. Link

Muddapu, Vignayanandam Ravindernath-Jayashree, Karthik Vijayakumar, Keerthiga Ramakrishnan, and V. Srinivasa Chakravarthy. "A Multi-Scale Computational Model of Levodopa-Induced Toxicity in Parkinson's Disease." Frontiers in neuroscience 16 (2022). Link

Nair, Sandeep Sathyanandan, Vignayanandam Ravindernath Muddapu, and V. Srinivasa Chakravarthy. "A multiscale, systems-level, neuropharmacological model of cortico-basal ganglia system for arm reaching under normal, Parkinsonian, and Levodopa medication conditions." Frontiers in computational neuroscience (2022): 122. Link

Muddapu, V.R., Chakravarthy, V.S. Influence of energy deficiency on the subcellular processes of Substantia Nigra Pars Compacta cell for understanding Parkinsonian neurodegeneration. Sci Rep 11, 1754 (2021). Link

Vignayanandam R. Muddapu, & V. Srinivasa Chakravarthy (2020) A Multi-Scale Computational Model of Excitotoxic Loss of Dopaminergic Cells in Parkinson's Disease, Frontiers in Neuroinformatics. Link

Vignayanandam R. Muddapu, Karthik Vijayakumar, Keerthiga Ramakrishnan, & V. Srinivasa Chakravarthy (2020) A Computational Model of Levodopa-Induced Toxicity in Substantia Nigra Pars Compacta in Parkinson's Disease, bioRxiv 2020.04.05.026807. Link

Vignayanandam R. Muddapu, S. Akila P. Dharshini, V. Srinivasa Chakravarthy, M. Michael Gromiha (2020) Neurodegenerative diseases -Is metabolic deficiency the root cause?, Frontiers in Neuroscience| Neurodegeneration Link

Vignayanandam R. Muddapu & V. Srinivasa Chakravarthy (2020) A Multi-Scale Computational Model of Excitotoxic Loss of Dopaminergic Cells in Parkinson's Disease. bioRxiv: 2020.02.20.957704 Link

Vignayanandam R. Muddapu & V. Srinivasa Chakravarthy (2020) Influence of Energy Deficiency on the Molecular Processes of Substantia Nigra Pars Compacta Cell for Understanding Parkinsonian Neurodegeneration - A Comprehensive Biophysical Computational Model. bioRxiv:2020.02.18.950337 Link

Balasubramani, P. P., & Chakravarthy, S. (2019). Bipolar oscillations between positive and negative mood states in a computational model of Basal Ganglia. Cognitive Neurodynamics, Springer, 17412556. Link

Vignayanandam R. Muddapu, Alekhya Mandali, V. Srinivasa Chakravarthy, Srikanth Ramaswamy (2019) A computational model of loss of dopaminergic cells in Parkinson's disease due to glutamate-induced excitotoxicity. Frontiers in Neural Circuits. Link

Muddapu VR, Mandali A, Chakravarthy S V, Ramaswamy S (2018) A computational model of loss of dopaminergic cells in Parkinson's disease due to glutamate-induced excitotoxicity. bioRxiv:1-69 PDF

Chakravarthy, V.S., Balasubramani, P.P., Mandali, A., Jahanshahi, M., Moustafa., A.A., The many facets of Dopamine: Toward an integrative theory of the role of Dopamine in managing the body's energy resources, Journal of Physiology and Behavior, (accepted).

Shivkumar, S., Chakravarthy, V. S., & Rougier, N. P. (2018). Modeling the Role of the Striatum in Non-Stationary Bandit Tasks. PDF

Shivkumar, Sabyasachi, Vignesh Muralidharan, and V. Srinivasa Chakravarthy. "A Biologically Plausible Architecture of the Striatum to Solve Context-Dependent Reinforcement Learning Tasks." Frontiers in neural circuits 11 (2017).

Vignesh Muralidharan, Pragathi Priyadharsini Balasubramani, Srinivasa Chakravarthy, Moran Gilat, Simon JG Lewis, Ahmed A. Moustafa (2016), A neurocomputational model of the effect of cognitive load on freezing of gait in Parkinson's disease, Frontiers in Human Neuroscience.

Alekhya Mandali, Srinivasa Chakravarthy, Roopa Rajan, Sankara Sarma, Asha Kishore (2016), Electrode position and current amplitude modulate impulsivity after subthalamic stimulation in Parkinson's disease, Frontiers in Physiology.

Alekhya Mandali,Srinivasa Chakravarthy V (2016), Probing the role of medication, DBS electrode position and antidromic activation on impulsivity using a computational model of Basal Ganglia. Frontiers in Human Neuroscience.ID:197629 (accepted) Article

Moustafa, A.A., Chakravarthy, S., Phillips, J. Gupta, A., Keri, S, Polner, B., Frank, M. J., Jahanshahi, M. (2016). Motor symptoms in Parkinson's disease: A unified framework. Neuroscience & Biobehavioral Reviews (accepted)

Ahmed A. Moustafa, Srinivasa Chakravarthy, Joseph R. Phillips, Jacob J. Crouse, Ankur Gupta, Michael J. Frank, Julie M. Hall, Marjan Jahanshahi. Interrelations between cognitive dysfunction and motor symptoms of Parkinson's disease: Behavioral and neural studies. Reviews in the Neurosciences (2016)

P. P. Balasubramani, V. S. Chakravarthy, M. Ali, B. Ravindran, and A. A. Moustafa, "Identifying the basal ganglia network model markers for medication-induced impulsivity in Parkinson's Disease patients," PloS one, vol. 10, p. e0127542, 2015PDF

A. Mandali, M. Rengaswamy, V. S. Chakravarthy, and A. A. Moustafa, "A spiking Basal Ganglia model of synchrony, exploration and decision making," Frontiers in Neuroscience, vol. 9, p. 191, 2015PDF

P. P. Balasubramani, V. S. Chakravarthy, B. Ravindran, and A. A. Moustafa, "A network model of basal ganglia for understanding the roles of dopamine and serotonin in reward-punishment-risk based decision making," Frontiers in Computational Neuroscience, vol. 9, 2015PDF

P. P. Balasubramani, V. S. Chakravarthy, B. Ravindran, and A. A. Moustafa, "An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning," Frontiers in computational neuroscience, vol. 8, 2014PDF

Gupta, A., Balasubramani, P.P., and Chakravarthy, S. (2013). Computational model of precision grip in Parkinson's disease: A Utility based approach. Frontiers in Computational Neuroscience 7 PDF

Chakravarthy VS (2013) Do Basal Ganglia Amplify Willed Action by Stochastic Resonance? A Model. PLoS ONE 8(11): e75657PDF

Helie, S. Chakravarthy, and A. A. Moustafa, "Exploring the cognitive and motor functions of the basal ganglia: an integrative review of computational cognitive neuroscience models," Frontiers in computational neuroscience, vol. 7, 2013.PDF

V. Muralidharan, P. P. Balasubramani, V. S. Chakravarthy, S. J. Lewis, and A. A. Moustafa, "A computational model of altered gait patterns in parkinson's disease patients negotiating narrow doorways," Frontiers in computational neuroscience, vol. 7, 2013PDF

Maya M., Chakravarthy V. S., Ravindran B., An Oscillatory neural network model for birdsong learning and generation: Implications for the role of Dopamine in Song Learning, International Journal of Mind, Brain and Cognition, 2012. (Accepted)

Sanjeeva K. Kalva, Maithreye Rengaswamy, V.S. Chakravarthy, Neelima Gupte, On the neural substrates for exploratory dynamics in basal ganglia: A model, Neural Networks, pp. 65-73, February, 2012

R.Krishnan, S. Ratnadurai, D. Subramanian, V.S. Chakravarthy, M. Rengaswamy, Modeling the role of Basal Ganglia in Saccade Generation: Is the Indirect Pathway the Explorer?, Neural Networks, Volume: 24, Issue: 8, Pages: 801-813, 2011.

M. Magdoom , D. Subramanian, V.S. Chakravarthy, B. Ravindran, Shun-ichi Amari. N. Meenakshisundaram, Modeling Basal Ganglia for understanding Parkinsonian Reaching Movements, Neural Computation, February 2011, Vol. 23, No. 2, Pages 477-516.

V.S. Chakravarthy, Denny Joseph, Raju S. Bapi, "What do the Basal Ganglia Do? A modeling perspective", Biological Cybernetics, 2010, Sep;103(3):237-53.

D. Joseph, G. Gangadhar, V.S. Chakravarthy, ACE (Actor - Critic - Explorer) Paradigm for Reinforcement Learning in Basal Ganglia: Highlighting the role of Sub-Thalamic and Pallidal Nuclei, Neurocomputing, Volume 74, Issue 1-3, December, 2010.

Garipelli Gangadhar, Denny Joseph, A.V. Srinivasan, Deepak Subramanian, Shiva Keshavan, V. Srinivasa Chakravarthy, A computational model of Parkinsonian handwriting that high lights the role of the indirect pathway in the basal ganglia. Human Movement Science, 2009 Oct;28(5):602-18.

G. Gangadhar, D. Joseph, V.S. Chakravarthy, Understanding Parkinsonian Handwriting using a computational model of basal ganglia, Neural Computation, 20, 1-35 (2008).

S. Devarajan, P.S. Prashanth, V.S. Chakravarthy, "The Role of the Basal Ganglia in Exploration in a Neural Model based on Reinforcement Learning," International Journal of Neural Systems, vol. 16, No. 2, pp111-124, 2006.

Hippocampus: Spatial Navigation and Memory

Azra Aziz, Bharat K. Patil, Kailash Lakshmikanth, Peesapati S. S. Sreeharsha, Ayan Mukhopadhyay & V. Srinivasa Chakravarthy “Modeling hippocampal spatial cells in rodents navigating in 3D environments ” Nature Scientific Reports. Link

Kanagamani, Tamizharasan, V. Srinivasa Chakravarthy, Balaraman Ravindran, and Ramshekhar N. Menon. "A deep network-based model of hippocampal memory functions under normal and Alzheimer's disease conditions." Frontiers in Neural Circuits 17, 1092933. 2023. Link

Aziz, Azra, Peesapati SS Sreeharsha, Rohan Natesh, and Vaddadhi S. Chakravarthy. "An integrated deep learning-based model of spatial cells that combines self-motion with sensory information." Hippocampus 32, no. 10 (2022): 716-730. Link

Ankur Chauhan, Karthik Soman and Srinivasa Chakravarthy, "Saccade Velocity Driven Oscillatory Network model of Grid cells", by, Frontiers in Computational Neuroscience, 2019. Link

Samyukta Jayakumar, Rukhmani Narayanamurthy, Reshma Ramesh, Karthik Soman, Vignesh Muralidharan and V. Srinivasa Chakravarthy, Modeling the Effect of Environmental Geometries on Grid Cell Representations", Frontiers in Neural Circuits, 2019. Link

Karthik Soman, Srinivasa Chakravarthy, and Michael Yartsev An Empirically Driven Hierarchal Anti-Hebbian Network Model for the Formation of Spatial Cells in Three-Dimensional Space, Nature Communications, (accepted), 2018. PDF

Soman, Karthik, Vignesh Muralidharan, and V. Srinivasa Chakravarthy "An Oscillatory Neural Autoencoder based on Frequency Modulation and Multiplexing" Frontiers in computational neuroscience, 2018 (In Press).

Soman, Karthik, Vignesh Muralidharan, and Vaddadi Srinivasa Chakravarthy. "A unified hierarchical oscillatory network model of head direction cells, spatially periodic cells, and place cells." European Journal of Neuroscience 47.10 (2018): 1266-1281. PDF

Jayakumar, S., Narayanamurthy, R., Ramesh, R., Soman, K., Muralidharan, V., & Chakravarthy, S. (2017). A computational model that explores the effect of environmental geometries on grid cell representations. PDF

Soman, Karthik, Vignesh Muralidharan, and V. Srinivasa Chakravarthy. "A Model of Multisensory Integration and its Influence on Hippocampal Spatial Cell Responses." IEEE Transactions on Cognitive and Developmental Systems(2017). PDF

Soman, K., Muralidharan, V., Chakravarthy, V.S. (2016), An oscillatory network model of head direction, spatially periodic cells and place cells using locomotor inputs, Bioarxiv, Article

Sukumar, D., Rengaswamy, M., and Chakravarthy, V.S. (2012). Modeling the contributions of Basal ganglia and Hippocampus to spatial navigation using reinforcement learning. PloS one 7, e47467

Stroke Rehabilitation

Paul, Rinta, Sundari Elango, Srinivasa Chakravarthy, Aniruddha Sinha, P. R. Srijithesh, Bapi Raju, C. Kesavadas et al. "Feasibility and efficacy of virtual reality rehabilitation compared with conventional physiotherapy for upper extremity impairment due to ischaemic stroke: protocol for a randomised controlled trial." BMJ open 14, no. 7 (2024): e086556.Link

Elango, S., Chakravarthy, S. and Mutha, P. A lateralized motor network in order to understand adaptation to visuomotor rotation. Journal of Neural Engineering. (2024) Link

Elango, Sundari, Francis, Amal Jude Ashwin, and V. Srinivasa Chakravarthy. "Interaction of network and rehabilitation therapy parameters in defining recovery after stroke in a Bilateral Neural Network" Journal of NeuroEngineering and Rehabilitation. Link

Narayanamurthy, Rukhmani, Jayakumar, Samyukta, Elango, Sundari, Chakravarthy, Srinivasa, Muralidharan, Vignesh."A Cortico-Basal Ganglia Model for choosing an optimal rehabilitation strategy in Hemiparetic Stroke." (Accepted in Scientific Reports on 12 Aug, 2019)

Neural Oscillations

Anirban Bandyopadhyay, Sayan Ghosh, Dipayan Biswas, V. Srinivasa Chakravarthy, and Raju S. Bapi. "A phenomenological model of whole brain dynamics using a network of neural oscillators with power-coupling." Scientific Reports 13, no. 1 (2023): 16935. Link

Akhil,Bonagiri;Dipayan, Biswas;V Srinivasa Chakravarthy, "Coupled Memristor Oscillators for Neuromorphic Locomotion Control: Modelling and Analysis". IEEE Transactions on Neural Networks and Learning Systems. Link

Biswas, Dipayan, V. Srinivasa Chakravarthy, and Asit Tarsode. "Modelling the tonotopic map using a two-dimensional array of neural oscillators." Frontiers (2022). Link

Biswas, Dipayan, Sooryakiran Pallikkulath, and V. Srinivasa Chakravarthy. "A Complex-Valued Oscillatory Neural Network for Storage and Retrieval of Multidimensional Aperiodic Signals." Frontiers in computational neuroscience 15 (2021): 551111. LInk

G. Gangadhar, D. Joseph, V.S. Chakravarthy, "An oscillatory neuromotor model of handwriting generation," International Journal of Document Analysis and Recognition, Vol. 10, No. 2, November 2007.

P.S. Prashanth, V.S. Chakravarthy (2007), "An oscillator theory of motor unit recruitment in skeletal muscle." Biological Cybernetics, 97:351-361.

V.S. Chakravarthy, N. Gupte, S.Yogesh, A. Salhotra, Chaotic Synchronization using a Network of Neural Oscillators, International Journal of Neural Systems, vol. 18, No. 2, pp. 157-164, 2008.

VS. Chakravarthy and J. Ghosh. A Complex-valued Associative Memory for Storing Patterns as Oscillatory States, Biological Cybernetics, 75, p229-238, 1996.

Vision: Perception and Attention

Raj S R, K., Chakravarthy V, S. & Sahoo, A. From Pixels to Prepositions: Linking Visual Perception with Spatial Prepositions Far and Near. Cogn Comput (2024). Link

Anila Gundavarapu and Srinivasa Chakravarthy, Modeling the development of cortical responses in primate dorsal ("where") pathway to optic flow using hierarchical neural field models", "Frontiers in Neuroscience-Visual Neuroscience". 2023. Link

Kumari, S., Chandrasekaran, V., & Chakravarthy, V. S. (2023). The flip-flop neuron: a memory efficient alternative for solving challenging sequence processing and decision-making problems. Neural Computing and Applications, 1-17. Link

Kumari, Sweta, VY Shobha Amala, M. Nivethithan, and V. Srinivasa Chakravarthy. "BIAS-3D: Brain inspired attentional search model fashioned after what and where/how pathways for target search in 3D environment." Frontiers in Computational Neuroscience 16 (2022). Link

Kumari, Sweta, and V. Srinivasa Chakravarthy. "Biologically inspired image classifier based on saccadic eye movement design for convolutional neural networks." Neurocomputing 513 (2022): 294-317. Link

Anila Gundavarapu, Srinivasa Chakravarthy and Karthik Soman, A model of motion processing in the visual cortex using neural field with asymmetric Hebbian learning", Frontiers in Neuroscience-Perception Science, 2019. Link

Chakravarthy, V. S. (2017). Seeing vision with the eyes of math. Kerala Journal of Ophthalmology, 29(2), 66. PDF

Philips, R. T., Sur, M., & Chakravarthy, V. S. (2017). The influence of astrocytes on the width of orientation hypercolumns in visual cortex: A computational perspective. PLoS Computational Biology, 13(10), e1005785. PDF

Ryan Thomas Philips, Srinivasa Chakravarthy (2017), A global orientation map in the primary visual cortex (V1): Could a self-organizing model reveal its hidden bias? Frontiers in Neural Circuits.

R. T. Philips and V. S. Chakravarthy, "The mapping of eccentricity and meridional angle onto orthogonal axes in the primary visual cortex: an activity-dependent developmental model," Frontiers in computational neuroscience, vol. 9, 2015PDF

Neurovascular Coupling

Kumar, B. S., O'Herron, P. J., Kara, P., & Chakravarthy, V. S. (2021). The development of bi-directionally coupled self-organizing neurovascular networks captures orientation-selective neural and hemodynamic cortical responses. European Journal of Neuroscience, April, 2023. Link

Kumar, Bhadra S., Sarath C. Menon, Sriya R. Gayathri, and V. Srinivasa Chakravarthy. "The Influence of Neural Activity and Neural Cytoarchitecture on Cerebrovascular Arborization: A Computational Model." Frontiers in Neuroscience (2022): 933. Link

Kumar, B.S., Mayakkannan, N., Manojna, N.S. et al. Artificial neurovascular network (ANVN) to study the accuracy vs. efficiency trade-off in an energy dependent neural network. Sci Rep 11, 13808 (2021). Link

Kumar, B.S., Khot, A., Chakravarthy, V.S. and Pushpavanam, S., 2021. A network architecture for bidirectional neurovascular coupling in rat whisker barrel cortex. Frontiers in Computational Neuroscience, 15, LInk

Bhadra S Kumar, Avinash Kori, Sundari Elango, and V. Srinivasa Chakravarthy, Phase and Amplitude Modulation in a Neural Oscillatory Model of the Orientation Map, 25th International Conference on Neural Information Processing (ICONIP 2018), Cambodia, Dec 2018. Link

Philips RT, Chhabria K, Chakravarthy VS. Vascular Dynamics Aid a Coupled Neurovascular Network Learn Sparse Independent Features: A Computational Model. Frontiers in Neural Circuits. 2016;10:7. DOI:10.3389/fncir.2016.00007.PDF

Chhabria K,Chakravarthy VS, Low-dimensional models of 'Neuro-glio-vascular unit' for describing neural dynamics under normal and energy-starved conditions, Frontiers in Neurology,2016.PDF

Chander, B.S., and Chakravarthy, V.S. (2012). A computational model of neuro-glio-vascular loop interactions. PloS one 7, e48802.

Ranjan K. Pradhan and V. S. Chakravarthy, Informational dynamics of Vasomotion in Microvascular Networks: A Review, Acta Physiologica (Oxf). 201(2):193-218, Feb, 2011.

Rohit Gandrakota, V. S. Chakravarthy, Ranjan K. Pradhan, A model of indispensability of a large glial layer in cerebrovascular circulation. Neural Computation 2010 Apr;22(4):949-68.

R.K Pradhan, V.S.Chakravarthy, A. Prabhakar, Effect of Chaotic Vasomotion in Skeletal Muscle on Tissue oxygenation , Microvascular Research,Vol 74/1,pp 51-64, July 2007.

R.K. Pradhan, V. S. Chakravarthy. A computational Model that Links Nonperiodic Vaosomotion to Enhanced Oxygenation in Skeletal Muscle. Mathematical Biosciences, 209 (2), p.486-499, Oct 2007.

R.K. Pradhan, V. S. Chakravarthy, Desynchronized Vasomotion and Desynchronized Fiber Activation Pattern Enhance Oxygenation in a Model of Skeletal Muscle, Jnl of Theoretical Biology, Vol. 259, No. 2., 21 July 2009, pp. 242-252.

AI and ML

Sruthi Krishna, K. P., Nithin Puthiyaveettil, and V. Srinivasa Chakravarthy. "Simulation-assisted AI for the evaluation of thermal barrier coatings using pulsed infrared thermography." (2022). Link

Deepesh.V, R.J. Pardikar, K.Karthik, A. Sricharan, V.S. Chakravarthy, and K. Balasubramanian, Automatic defect recognition (ADR) system for real-time radioscopy (RTR) of straight tube butt (STB) welds, Journal of Non-destructive Testing & Evaluation (Accepted).

V. Deepesh, R.J. Pardikar, A. Sricharan, V.G. Ramanathan, S. Chakravarthy and K. Balasubramaniam, Automatic Defect Recognition System for Real Time Radioscopy of Hancock Valve Welds, Journal of Non destructive Testing & Evaluation, 9 (1) 12-16, (2010).

S. Chakravarthy and J. Ghosh. Function Emulation using the Radial Basis Function Network. Neural Networks. Vol. 10, No. 3, pp459-478, 1997.

S. Chakravarthy and J. Ghosh. Scale-based Clustering using the Radial Basis Function Network. IEEE Transactions on Neural Networks, vol. 7, no. 5 ,p1250-1261,September, 1996.

J. Ghosh and S. Chakarvarthy, Rapid Kernel Classifier: A link between Self-Organizing Feature Map and the Radial Basis Function Network. Journal of Intelligent Material Systems and Structures (Sp. Issue on Neural Networks), March 1994.

Robotics:

Vishwanathan Mohan, Pietro Morasso, Jacopo Zenzeri, Giorgio Metta, V. Chakravarthy, Giulio Sandini, Teaching a humanoid Robot how to draw 'Shapes,' Autonomous Robots, pp. 1-33. Volume: 31, Issue: 1, Pages: 21-53, 21 April 2011.

Cardiac Modeling

Balakrishnan Minimol, Chakravarthy Srinivasa, Guhathakurta Soma "Simulation of cardiac arrhythmias using a 2D heterogeneous whole heart model" , Frontiers in Physiology, vol. 6, p. 00374 , 2015PDF

Sachdeva G, Kalyanasundaram K, Krishnan J, Chakravarthy VS. Bistable dynamics of cardiac cell models coupled by dynamic gap junctions linked to Cardiac Memory. Biol Cybern. 2010 Feb;102(2):109-21.

J. Krishnan, G. Sachdeva, V S Chakravarthy, Interpreting voltage-sensitivity of Gap Junctions as a mechanism of Cardiac Memory, Mathematical Biosciences, vo. 212, pp. 132-148, 2008.

J. Krishnan, V.S. Chakravarthy and S. Radhakrishnan (2005), On the Role of Gap junctions in cardiac Memory Effect, Computers in Cardiology, 32.13-16.

J.Krishnan V.S. Chakravarthy, S.Radhakrishnan, Solomon Victor and Vijaya Nayak (2005) Neural Influence is essential for synchronization of Cardiac Oscillators - A computational Model, Indian Journal of Cardiac Vascular Thoracic Surgery, 21.262-268.

V.S. Chakravarthy, J.Krishnan, S. Radhakrishnan, Chaitanya Sai, Activity-dependent plasticity in Gap Junctions as a Mechanism for Cardiac Memory, NeuroQuantology, Vol. 4, Issue 4, Page 307-320 (2006).

S.Chakravarthy and J.Ghosh. On Hebbian-like Adaptation in Heart Muscle: A proposal for "Cardiac Memory". Biological Cybernetics, 76(3), April, 1997, pp 207-215.

Miscellaneous

Abhishek De, V. Srinivasa Chakravarthy, Michael Levinc.(2016), A computational model of planarian regeneration. International Journal of Parallel, Emergent and Distributed Systems. DOI:10.1080/17445760.2016.1185521. Article

S. Mohamed Yacin, M. Manivannan and V. Srinivasa Chakravarthy, Reconstruction of Gastric Slow wave from Finger Photoplethysmographic Signal using Radial Basis Function Neural Network, Medical Biological Engineering and Computing, Volume 49, Number 11, 1241-1247, 2011.

S. Mohamed Yacin and M. Manivannan, V.S. Chakravarthy, Effect of gastric myoelectric activity on Pulse Rate Variability in fasting and postprandial conditions, International Journal of Healthcare Technology and Management, Vol. 12, No.5/6 pp. 434 - 446, 2011.

Saguna Dubey, Sandeep Sambaraju , Sarat C. Cautha, A. Parthasarathy, N. Srivastava, V. S. Chakravarthy, On the role of ambiguity in copying oriented line diagrams, International Journal of Brain, Mind and Cognition, Vol. 1, No. 2, Jul--Dec 2010.

S. Mohamed Yacin, M. Manivannan, V. Srinivasa Chakravarthy, On non-invasive measurement of Gastric motility from finger photoplethysmographic signal, Annals of Biomedical Engineering, vol 38, no 12, 3744-3755, 2010.

Dubey, S., Sambaraju, S., Chautha, S.C., Arya, V., Chakravarthy, V.S., A phase dynamic model of systematic error in simple copying tasks. Biological Cybernetics, 2009 Sep;101(3):201-13.

S. Mohamed Yacin, M. Manivannan and V. Srinivasa Chakravarthy, Effect of Gastric Myoelectric Activity on Photoplethysmographic Signals, International Journal of Recent Trends in Engineering, Vol. 2(Electrical), No. 1,pp 27-29, Nov 2009.

Hema Smanathan, Renee M. Borges, and V. Srinivasa Chakravarthy, "Does Neighbourhood Floral Display Matter? Fruit Set in Carpenter Bee-pollinated Heterophragma quadriloculare and Beetle-pollinated Lasiosiphon eriocephalus" Biotropica, vol. 36, no. 2, 2004.

V.S. Chakravarthy & Bhaskar Kompella, "The Shape of Handwritten Character," Pattern Recognition Letters, Vol. 24, No. 12, August, 2003.

Book Chapters

Alekhya Mandali, Srinivasa Chakravarthy V, Ahmed A. Moustafa , A neuro-computational model of Pallidal vs. Subthalamic Deep Brain Stimulation Effect on synchronization at Tremor frequency in Parkinson's disease, Vassilis Cutsuridis (Ed.), Multiscale Models of Brain Disorders, Springer, 2019.

Balasubramani, P.P, Chakravarthy, S., Wong-Lin, K., Wang, D.,Cohen, J. Y.,, Nakamura, K., and Moustafa,, A. A. (in press). Neural circuit models of serotonergic system: From microcircuits to cognition. In A. Moustafa (Ed.) Computational models of Brain and Behavior. Wiley-Blackwell, (pp 389-400).

Chakravarthy V.S., Balasubramani, P.P. "Basal Ganglia System as an Engine for Exploration.", in: Encyclopedia of Computational Neuroscience. (ed.) J.R. Jaeger D. (Berlin Heidelberg),2014.

V. S. Chakravarthy, A model of the neural substrates for exploratory dynamics in Basal Ganglia, In Progress in Brain Research: Decision Making: Neural and Behavioural Approaches, Edited by V. S. Chandrasekhar Pammi and Narayanan Srinivasan, Elsevier, 2012.

Denny Joseph, Garipelli Gangadhar, V. Srinivasa Chakravarthy, ACE (Actor - Critic - Explorer) Paradigm for Reinforcement Learning in Basal Ganglia: Highlighting the role of the Indirect Pathway, Srinivasan, N., Kar, B. R., & Pandey, J. (Eds.). (forthcoming) Advances in Cognitive Science: Volume 2, Sage Publications, India, 2012.

V. S. Chakravarthy (2009), Complex-valued Hopfield Neural Network: Dynamics and Applications, In Complex-Valued Neural Networks: Utilizing High-Dimensional Parameters, Tohru Nitta (Ed.), Information Science Reference, pp. 79-103.

Aparna Kokku, V. Srinivasa Chakravarthy, A complete OCR system development for Tamil Magazine Documents, In OCR for Indic Scripts, Venu Govindaraju and Srirangaraj Setlur (Eds.), Springer, 2009.

Patents

Srinivasa Chakravarthy, Pravin Gupta, Raghu Chunduru, Berthold Krieghauser, and Otto Fanini, "Conductivity Anisotropy Estimation Method for Inversion processing of Measurements made by a Transverse Electromagnetic Induction Logging Instrument." (U.S. Patent #: 6,044,325).

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