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Appointment

Dr. Harilal Parasuram

Dr. Harilal Parasuram

Assistant Professor

Department: Amrita Advanced Centre for Epilepsy, Neurology
Qualification: M.Sc. in Bioinformatics and Ph.D. in Computational Neuroscience
Email: harilalp@aims.amrita.edu

About Me

Dr. Harilal holds Ph.D. in Computational Neuroscience from Amrita University, where he studied neuronal excitability in granular layer ensembles of the cerebellum by modeling local field potential (LFP). He worked as Project Associate at Neurophysiology and Simulation Virtual Lab project, National Mission on Education through ICT, funded by Ministry for Human Resource Development, Govt. of India. His post-doctoral study was on “Quantification of epileptogenic network from Stereo EEG recordings using Epileptogenicity Ranking method”. Currently, he is an Assistant Professor and in-charge of the Brain Mapping research lab associated with Amrita Advanced Center for Epilepsy and the Department of Neurology.

Reviewer :

  • Frontiers in Human Neuroscience
  • Journal of Engineering in Medicine
  • Epilepsy & Behavior Reports
  • Biomedical and Pharmacology Journal (BPJ)

Master Thesis – Guided

  • 2021, Arjun V, MCA – Localizing epileptogenic zone from spikes and high frequency oscillation’s using machine learning models in temporal lobe epilepsy.
  • 2021, Irfana Noushad, M.Tech,- Studying autonomic dysfunction in epilepsy patients using stereo EEG and ECG.
  • 2021, Nimisha K S, M.Sc. Neuro-electro-physio. – Localizing epileptogenic zone using spikes and High Frequency Oscillations.
  • 2020, Abhilash Saj George &Arjun VijayanathaKurup, MCA – Predicting Autonomic Dysfunction in Anxiety Disorder from ECG and Respiratory Signals Using Machine Learning Models
  • 2020, Rohith Devisetty, Amsitha MB &Sasi Jyothirmai, B. Tech- Localizing epileptogenic network from SEEG using h2 non-linear correlation, mutual information and graph theory analysis.

Research Interest

  • Epileptogenic zone localization – Stereo EEG, HD-EEG & electrical source localization, SISCOM and Voxel Based Morphometry
  • Modeling and simulation of neuronal dynamics
  • Artificial Intelligence in medicine & Open source tool development

Advanced Courses & Training

  • BCD Stereo-EEG collaborative workshop at IISc, India, 7-8 October 2022
  • BESA research workshop, 09th – 13th May 2022
  • HD EEG and ESI training, University Hospital Geneva, 2019.
  • Computational Approaches to Memory and Plasticity – summer school (June 28th – July 12th, 2014), NCBS – India
  • 3rd Bangalore Cognition Workshop (Dec 8-21 2013), Indian Institute of Science
  • INCF workshop 2012, Indian Institute of Technology- Madras
  • INNNI summer course 2012, Indian Statistical Institute
  • International workshop on Brain and Cognition 2011, Indian Institute of Science
  • INNNI summer course 2011, National Brain Research Centre-India

Publications

Journal Articles

  • R. Devisetty, MD, Amsitha MB, S. Jyothirmai, R. Ajai, A. Pillai, A. Kumar, S. Gopinath and H. Parasuram. Localizing epileptogenic network from SEEG using non-linear correlation, mutual information and graph theory analysis, Journal of engineering in medicine, 2022.
  • R. Sankaran, A. Kumar and H. Parasuram, Role of Artificial Intelligence and Machine Learning in the prediction of the pain: A Scoping Systematic Review, Journal of engineering in medicine, 2022.
  • A Shridharani,H. Parasuram, B. Mrudula,R.Bhaskaran, A. Kumar & S.Gopinath, Retrospective analysis of autonomic dysfunction in epilepsy patients from neurophysiological recordings, Neurology Asia, 2022.
  • H. Parasuram, S. Gopinath, A. Pillai, S. Diwakar and A. Kumar, Quantification of Epileptogenic Network From Stereo EEG Recordings Using Epileptogenicity Ranking Method, Front. Neurol., 03 November 2021 | https://doi.org/10.3389/fneur.2021.738111
  • A. George, A. Kurup, P. Balachandran, M. Nair, S. Gopinath, A. Kumar, H. Parasuram. Predicting Autonomic Dysfunction in Anxiety Disorder from ECG and Respiratory Signals Using Machine Learning Models, IJOE, 2021, https://doi.org/10.3991/ijoe.v17i07.22581
  • H. Parasuram, B. Nair, G. Naldi, E. D`Angelo, S. Diwakar. Understanding Cerebellum Granular Layer Network Computations through Mathematical Reconstructions of Evoked Local Field Potentials. Ann Neurosci, 2017
  • H. Parasuram, B. Nair, G. Naldi, E. D`Angelo, S. Diwakar. Understanding Cerebellum Granular Layer Network Computations through Mathematical Reconstructions of Evoked Local Field Potentials. Ann Neurosci, 2017.
  • H. Parasuram, B. Nair, E. D`Angelo, M. Hines, G. Naldi, S. Diwakar. Computational modeling of single neuron extracellular electric potentials and network Local Field Potentials using LFPsim. Front. Comput. Neurosci., 2016, 10:65doi: 10.3389/fncom.2016.00065
  • S. Diwakar, H. Parasuram, C. Medini, R. Raman, P. Nedungadi,E. Wiertelak, S. Srivastava, K. Achuthan & B. Nair Complementing Neurophysiology Education for Developing Countries via Cost-Effective Virtual Labs: Case Studies and Classroom Scenarios, The Journal of Undergraduate Neuroscience Education (JUNE), Spring 2014.
  • H. Parasuram, B. Nair, G. Naldi, E. D’Angelo, S. Diwakar. A modeling based study on the origin and natureof evoked post-synaptic local field potentials in granular layer, Journal of Physiology Paris, 2011, doi:10.1016/j.jphysparis.2011.07.011.

Peer-reviewed Conference Articles

  • Nithin G, Shameer Aslam, Sathidevi P S, P M Ameer, Siby Gopinath, Radhakrishnan K and Harilal Parasuram. Localization of Epileptogenic Zone: A Graph Theoretical Approach, Proceedings of International Conference on Vision, Image and Signal Processing (ICVISP), Las Vegas, 2018.
  • S. Bodda, H. Parasuram, B. Nair, S. Diwakar. Computing LFP From Biophysical Models of Neurons and Neural Microcircuits, Proceedings of 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI 2016), Jaipur, India, Sept 21-24,2016.
  • H. Parasuram, B. Nair, G. Naldi, E. D’Angelo & S. Diwakar. Exploiting Point Source Approximation on Detailed Neuronal Models to Reconstruct Single Neuron Electric Field and Population LFP, Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN) 2015, Killarney, Ireland, July 12-17, 2015.
  • H. Parasuram, B. Nair & S. Diwakar, Studying cerebellar dysfunction at single neuron and circuit level, Proceedings of International Conference on Recent Advances in Cognition and Health (ICRACH – 2014), Banaras Hindu University, Varanasi, India, December 19-21, 2014.
  • A. Yoosef, H. Parasuram, C. Medini, S. Solinas, E. D’Angelo, B. Nair and S. Diwakar, Parallelization of a Computational Model of a Biophysical Neuronal Circuitry of Rat Cerebellum, Proceedings of International Conference on Interdisciplinary Advances in Applied Computing, Oct 10-11, 2014.
  • H. Parasuram, B. Nair & S. Diwakar, Studying plasticity effects in cerebellum granular layer micro circuitry using local field potential reconstruction, Proceedings of the International XXXI Annual meeting of Indian Academy of Neurosciences, October 25th – 27th, 2013.
  • H. Parasuram, B. Nair, S. Diwakar. Implications of algorithms on LFP reconstruction in cerebellar granular layer, Proceedings of International Conference on Biotechnology for Innovative Applications, 2013. (link)
  • H. Parasuram & S. Diwakar, Constraining extracellular matrix by modeling local field potential , INCF workshop – India, Nov. 5-7, 2012.
  • H. Parasuram ,B. Nair ,S. Diwakar, Using detailed biophysical models to reconstruct cerebellar post-synaptic evoked local field potential reveals single neuron effects in population code, Proceedings of the International symposium on `Recent Trends in Neurosciences & XXIX Annual Conference of Indian Academy of Neurosciences, Oct 30-Nov 1, 2011.
  • S. Diwakar , H. Parasuram , C. Medini , M. Nair , N. Melethadathil , G. Naldi , E. D’Angelo , B. Nair .Modeling evoked local field potentials in the cerebellum granular layer and plasticity changes reveal single neuron effects in neural ensembles . Acta Physiologica, September 2011, Volume 203, Supplement 688.
  • H. Parasuram, B. Nair, K. Achuthan, S. Diwakar. Taking Project Tiger to the Classroom: A Virtual Lab Case Study, Springer Communications in Computer and Information Science, 2011. (PDF)
  • H. Parasuram, N. Abdulmanaph, B. Nair, S. Diwakar, Modeling granular layer local field potential using single neuron and network based approaches to predict ltp/ltd in extracellular recordings, Proceedings of Neurocomp, 2010.
  • H. Parasuram, N. Abdulmanaph, B. Nair, S. Diwakar, Reconstructing extracellular local field potential in cerebellar granular layer networks Proceedings of BIC-TA, Sept 8-10, 2010.(link)
  • M. Parangan,C. Aravind, H. Parasuram, K. Achuthan,B. Nair and S. Diwakar.Action potential and bursting phenomena using analog electrical neuron. Proceedings of 1st Amrita ACM-W Celebration on Women in Computing in India,2010.
  • H. Parasuram., S. Krishna. A., V. Gopal K., K. Namboori, “Machine Learning Approaches to Determine the “Drug-Likeness” of the Proteomic Targets”, Proc. Of Int. Conf. on Control, Communication and Power Engineering-ACEEE. 253-255..

Book Chapter

  • S. Diwakar, C. Medini, M. Nair, H. Parasuram, A. Vijayan, B. Nair, Computational Neuroscience of Timing, Plasticity and Function in Cerebellar Microcircuits, in Computational Neurology and Psychiatry, Volume 6, Springer Series in Bio-/Neuroinformatics, pp 343-371, 02 Feb 2017.

Theoretical and Analytical tools

  • EPI-Rank – Quantification of epileptogenic network from Stereo EEG recordings using Epileptogenicity Ranking method
  • LFPsim – Modeling tool for computing electric potential of neurons and networks.
  • HHsim – Web based Hodgkin and Huxley model developed for MHRD Virtual Labs in Neurophysiology.