Research Division (Krembil Brain Institute): Clinical and Computational Neuroscience
My research program at the Neural Systems and Brain Signal Processing Lab (NSBSPL) currently has three prongs as follow.
Neural Information Processing
We develop multi-scale brain models and machine learning algorithms to understand mechanisms of information processing and coding in neural systems like Basal Ganglia Network.
Neuro-technology and Wearable Devices
We closely collaborate with industrial companies to develop multi-channel wearable devices that can simultaneously sense and process various electrophysiological signals like ECG, EMG, EEG.
We focus on the development and implementation of neuromorphic circuits. Neuromorphic chips are computer chips with electronic circuits that mimic aspects of biological neurons and their connections. They use efﬁcient, parallel and low-power computational principles and can be used to directly emulate neuronal networks on hardware rather than simulating them on a general-purpose computer.
Collaborators: Drs. Frances Skinner, Steve Prescott, Luka Milosevic, Milos Popovic, William Hutchison, Robert Chen
Idir Mellal (PDF)
Yupeng Tian (PhD student)
Mohammad Reza Rezaei (PhD student)
Alireza Ghadimi (MSc student)
David Crompton (Undergraduate student)
Aman Bhargava (Undergraduate student)
JP Grewal Rezaei (Undergraduate student)
Matthew Murphy (Undergraduate student)
Mohammadreza Rezaei, Milos R. Popovic, and M. Lankarany (2020),“ A Time-Varying Information Measure for Tracking Dynmics of Neural Codes in a Neural Ensemble,” In-press, Journal of Entropy, 22 (8), 880.
Milosevic L, Kalia SK, Hodaie M, Lozano AM, Popovic MR, Hutchison WD*, Lankarany M*, “A theoretical framework for the site-specific and frequency-dependent neuronal effects of deep brain stimulation,” BioRxiv, doi: https://doi.org/10.1101/2020.11.30.404269.
Navid Hasanzadeh, Mohammadreza Rezaei, Sayan Faraz, Milos R. Popovic, and M. Lankarany (2020),“ Necessary Conditions for Reliable Propagation of Time-Varying Firing Rate,” Frontiers in Computational Neuroscience, 14:64, doi: 10.3389/fncom.
Sayan Faraz, Idir Mellal, and M. Lankarany (2020), “Impact of Synaptic Strength on Propagation of Asynchronous Spikes in Biologically Realistic Feed-Forward Neural Network”, IEEE Journal of Selected Topics in Signal Processing (JSTSP), doi: 10.1109/JSTSP.2020.2983607.
M. Lankarany, Dhekra Al-Basha, S. Ratte, and S. A. Prescott (2019), “Synchrony-Division Multiplexing: Simultaneous Representation of Distinct Stimulus Features using Synchronous and Asynchronous spikes,” Proceedings of the National Academy of Science (PNAS), 116(20):10097-10102
Scientist, Krembil Brain Institute – University Health Network (UHN)
Affiliate Scientist, KITE, Toronto Rehabilitation Institute, UHN
Assistant Professor (status-only) Primary: Institute of Biomedical Engineering, Cross-appointment: Department of Physiology, University of Toronto