Arvind Kumar

KTH

+46 8 790 62 24

Keywords

brain activity dynamics, Brain diseases, Brain dynamics, Brain models, Brain science, Computational neuroscience, Neural data analysis, neuron diversity, Parkinsons disease, Spiking neural networks, structure dynamics relationship

Key publications

Vlachos I, Deniz T, Aertsen A, Kumar A (2016)
Recovery of dynamics and function in spiking neural networks with closed-loop control
PLoS computational biology
12(2):e1004720

Hahn G, Kumar A, Schmidt H, Knösche TR, Deco G (2022)
Rate and oscillatory switching dynamics of a multilayer visual microcircuit model
eLife 11:e77594
https://doi.org/10.7554/eLife.77594

Tauffer L, Kumar A (2021)
Short-term synaptic plasticity makes neurons sensitive to the distribution of presynaptic population firing rates.
Eneuro. 2021 Mar;8(2).
https://www.eneuro.org/content/eneuro/early/2021/02/11/ENEURO.0297-20.2021.full.pdf

Bahuguna J, Sahasranamam A, Kumar A (2020)
Uncoupling the roles of firing rates and spike bursts in shaping the STN-GPe beta band oscillations.
PLoS Comput Biol 16(3): e1007748.
https://doi.org/10.1371/journal.pcbi.1007748

Spreizer S, Aertsen A, Kumar A (2019)
From space to time: Spatial inhomogeneities lead to the emergence of spatiotemporal sequences in spiking neuronal networks.
PLoS Comput Biol 15(10): e1007432.
https://doi.org/10.1371/journal.pcbi.1007432

Wärnberg E, Kumar A (2019)
Perturbing low dimensional activity manifolds in spiking neuronal networks.
PLoS Comput Biol 15(5): e1007074.
https://doi.org/10.1371/journal.pcbi.1007074

Hahn G, Ponce-Alvarez, Deco , Aertsen A, Kumar A (2019)
Portraits of communication in neuronal networks.
Nature Reviews Neuroscience 20 (2), 117-127
https://www.nature.com/articles/s41583-018-0094-0

SciLifeLab / Contact / Arvind Kumar

Arvind Kumar

We are interested in the dynamics of the brain and how biological neuronal networks process information. Specifically, we are exploring the following questions:

What role do the network connectivity and network dynamics play in the transfer of information from one network to another?
How neuronal and synapse properties interact with network structure to shape the network activity dynamics?
How the activity dynamics of the network and information transfer can be controlled by external stimulation?

Essentially we are interested in how neural hardware shaped brain activity dynamics and neural code which form the basis of cognition and behavior.

We use analytical methods from statistical mechanics, probability theory, graph theory and control systems theory, and combine them with numerical simulations of large-scale neuronal networks of different brain regions.

One of the goals of our research is to develop mathematical models of brain diseases and create a theoretical framework to understand the mechanisms underlying the emergence of disease related aberrant activity dynamics in diseases (e.g. Parkinson’s diseases, epilepsy, anxiety). Eventually such a quantitative understanding of brain diseases would pave the way for the development of novel brain stimulation protocols to control or correct the disease-related brain activity. Therefore, we are neuralizing the control system theory and developing tools to control the dynamics of neuronal networks by external stimulations methods.

Group Members

Dr. Pascal Helson
Lihao Guo
Movitz Lenninger
Dr. Henri Rihiimakii
Hauke Wernecke
Emil Waernberg
Jie Zang