I am a computational neuroscientist studying the dynamics and information processing properties of neuronal networks. In my group we are investigating
- what roles 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.
To this end 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. The overall goal of this line of work 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 quantitive 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. To this end, we are also neuralizing the control system theory and developing tools to control the dynamics of neuronal networks by external stimulations methods.
Before moving to the KTH, I was a group leader at the Bernstein Center Freiburg, Faculty of Biology, University of Freiburg, Germany. I did my post-doctoral training with Prof. Mayank Mehta when he was at the Brown University, Providence, RI. I did my PhD in computational neuroscience at the University of Freiburg, under the supervision of Prof. Ad Aertsen and Prof. Stefan Rotter. I am still associated with the Bernstein Center Freiburg and the University of Freiburg, Germany.
At some point I studied Communication Engineering and then Control Systems. In my spare time I analyze statistics of Cricket games and DNA sequences. And I play Cricket.
Contact me if you are looking for a Masters Thesis project in computational neuroscience.
Computational Neuroscience, Controllability of Neuronal Networks, Network of Networks, Synchrony and Oscillations, Information Flow in Neuronal Networks, Cortico-Basal Ganglia Interactions, Neuromodulation, Epilepsy, Parkinson's disease, Dynamics of Brain Diseases.
For general ineterst
- Balance of excitation and inhibition in the brain [A talk I gave as a part of the 100th year clebration of KTH campus]
- Crippling rhythms of Parkinson's dsease A movie discussing our computational appraoche to understand and possibly manages Parkinson's disease
- Lähmende Rhythmen bei Parkinson Same as above in but in German
Seminars and talks of academic interest
- Network structure and dynamics relationship: relevance of the connectome data.
- Low dimensionality and sequential activity in the neocortex Nordita Conference Dimensionality reduction and population dynamics in neural data
Recent publications [Google profile]
Tauffer Luiz, Kumar Arvind (2021) Short-term synaptic plasticity makes neurons sensitive to the distribution of presynaptic population firing rates. eNEURO, (): Link KTH News: How the brain ignores noise.
Lehr AB, Kumar A, Tetzlaff C, Hafting T, Fyhn M, Stöber TM (2021) CA2 beyond social memory: Evidence for a fundamental role in hippocampal information processing. Neuroscience & Biobehavioral Reviews. 2021 Mar 26. LINK
Stöber Tristan, Lehr Andrew, Hafting Torkel, Kumar Arvind, Fyhn Marriane (2020) Selective neuromodulation and mutual inhibition within the CA3-CA2 system can prioritize sequences for replay. Hippocampus, (022308):
Kim CM, Egert U, Kumar A (2020) Dynamics of multiple interacting excitatory and inhibitory populations with delays. Physical Revews E 2(022308):022308. BioArxiv
Rezaei H, Aertsen A, Kumar A*, Valizadeh A* (2020) Facilitating the propagation of spiking activity in feedforward networks by including feedback. To appear in PloS Comput Biology. BioArxiv *equal cotribution
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 Computational Biology. 2019 Oct 25;15(10):e1007432.[Link] [BioArxiv] [BCF Press Release] [KTH NEWS].
Selected publications [Google profile]
Vlachos I, Deniz T, Aertsen A, Kumar A (2016) Recovery of dynamics and function in spiking neural networks by closed-loop control. PLoS Comput Biol12(2): e1004720. doi:10.1371/journal.pcbi.1004720 [The Promise]
Sahasranamam A, Vlachos I, Aertsen A, Kumar A (2016) Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity. Scientific Reports 6:26029 | DOI: 10.1038/srep26029 [Link] [Neuron vs the Network]
Bujan AF, Aertsen A, Kumar A (2015) Role of input correlations in shaping the variability and noise correlations of evoked the activity in the neocortex. J. Neurosci. 35(22) 8611-8625 10.1523/JNEUROSCI.4536-14.2015 [PDF] [Bring the noise] [Input Matters]
Bahuguna J, Aertsen A, Kumar A (2015) Existence and control of go/no-go decision transition threshold in the striatum. PloS Comput. Biol.11(4): e1004233. doi:10.1371/journal. pcbi.1004233 [PDF] [BCF Press Release][KTH Press Release]
Hahn G, Bujan AF, Fregnac Y, Aertsen A, Kumar A (2014) Communication through resonance in spiking neuronal networks. PLoS Comput Biol 10(8): e1003811. doi:10.1371/journal.pcbi.1003811 [PDF] [Travelling by resonance]
Kumar A, Vlachos I, Aertsen A, & Boucsein C (2013) The challenges of understanding brain function by specific manipulation of neuronal sub-populations. Trends in Neurosci 36(10):579-586. [The real challenge]
Kumar A, Rotter S & Aertsen A (2010) Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding. Nature Reviews Neurosci 11 : 615-627.
Grah G, Kumar A (2014) Wettstreit der Metaphern. Gehirn und Geist, volume: 13, issue: 7, pages: 60 - 65
Grah G, Kumar A (2013) Zittern in Zahlen. Geist und Gehirn 5: 68-73.
Kumar A (2012) The metaphorical brain. Science Reporter 49(10) 45-48.
Grah G, Kremkow K, Aertsen A, Kumar A (2011) Computational Neuroscience: Wie mathematische Modelle helfen koennen, unser Nervensystem zu verstehen. Biospektrum 01.11, 130