About

IMG-20171110-WA0012

Professional experience

  • Associate Professor and DBT Ramalingaswami fellow, National Brain Research Centre, Manesar, India (2017 July – Present)

  • Assistant Professor and DBT Ramalingaswami fellow, CBCS, University of Allahabad, India (2016 June – 2017 June)
  • Assistant Professor Cognitive Science Lab IIIT Hyderabad, India (2015 Jan – 2016 May) 

  • Research Associate Charite Hospital Berlin, and MPI Leipzig Neurology Department Brain-modes group (2013-2014) Petra Ritter Lab

  • Postdoctoral Research Associate TU Berlin Neuroinformatics (2011-2013) Klaus Obermayer Lab

  • Postdoctoral Research scientist MIT McGovern Center for Brain and cognitive science Mriganka Sur Lab (2011-13)

 Education

  • Ph.D. CNRS France and FAU USA Computational and Cognitive Neuroscience 2011 Supervisor: Prof. Viktor Jirsa

  • M.S. Dept of Physics (Nonlinear Dynamics), University of Texas USA 2007

Past and ongoing collaborations
  • Petra Ritter  Charité Neurology, Neurosurgery and Psychiatry Department of Neurology 
  • Mriganka Sur  Department of Brain and Cognitive Sciences Mriganka Sur Laboratory, MIT
  • Viktor Jirsa    Directeur adjoint, Institut de Neurosciences des Systèmes UMR INSERM 1106
  • Klaus Obermayer Technical University Berlin and Bernstein center for computational neuroscience
  • Christophe Bernard Director of Research Physionet, Institut de Neurosciences des Systèmes UMR INSERM 1106

Selected Publications

1.  Does the regulation of local excitation-inhibition balance aid in a recovery of functional connectivity? A computational account  Anirudh Vattikonda, Bapi Raju, Arpan Banerjee, Gustavo Deco, Dipanjan Roy Neuroimage. 2016 Aug 1;136:57-67. doi:10.1016/j.neuroimage.2016.05.002. Epub 2016 May 10

2.  Near-infrared spectroscopy (NIRS) – electroencephalography (EEG) based brain-state dependent electrotherapy (BSDE) to facilitate post-stroke neurorehabilitation: inhibition–excitation balance hypothesis Snigdha Dagar, Bapi Raju, Subhajit Raychoudhury, Anirban Dutta, Dipanjan Roy Front. Neurol. 7:123. doi:10.3389/fneur.2016.00123

3. Using the Virtual Brain to reveal the role of oscillations and plasticity in shaping Brain’s dynamical landscape Dipanjan Roy, Rodrigo Sigala, Michael Breakspear, Anthony Randal McIntosh, Viktor K. Jirsa, Gustavo Deco, Petra Ritter Brain Connectivity Journal 01 oct 2014 dx.doi.org/10.1089/brain.2014.0252. 

4. The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models.  Rodrigo Sigala, Sebastian Haufe, Dipanjan Roy, Hubert R. Dinse, Petra Ritter Front. Comput. Neurosci., 04 April 2014 | doi:10.3389/fncom.2014.00036. 

5. Changes in V1 orientation tuning when blocking astrocytic glutamate transporters: models for extra- and Intra synaptic mechanisms. Konstantin Mergenthaler*, Dipanjan Roy, Jeremy Petravicz, Mriganka Sur and Klaus Obermayer BMC Neuroscience 2013, 14(Suppl 1): P298 doi:10.1186/1471-2202-14-S1-P298.

6. Afferent specificity, feature specific connectivity influence orientation selectivity: A computational study in mouse primary visual cortex. Dipanjan Roy, Yenni Tjandra, Konstantin Mergenthaler, JeremyPetravicz, Caroline A. Runyan, Nathan R. Wilson, Mriganka Sur http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:1301.0996 2013 Feb ArXiv preprint

7. Influence of network timescale on network dynamics with fast synapses and parameter dispersion for a mean field model composed of bursting units.  Dipanjan Roy, Viktor K Jirsa.  Frontiers in Computational Neuroscience 2013 March Front. Comput. Neurosci. 7:20. doi: 10.3389/fncom.2013.000208. Brain state dependent post-inhibitory rebound in entorhinal cortex interneurons. Mohit H. Adhikari, Dipanjan Roy, Pascale P. Quelchini, Viktor K. Jirsa, Christophe Bernard. Journal of Neuroscience 2012 May 9;32(19):6501-10.
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3 thoughts on “About”

  1. How do we interface recognition systems using neurocybernetics for the study of neurodynamic activity?The use of radiation to connect to the biological neural network is based on cybernetic principles but the process is not explained properly in books and journals.It is possible today to neural code speech,image and acoustics to the brain using radiation.This establishes a two way signal one being the transmission and the other neurofeedback.This has already been used by the defence forces in certain countries.To have an integration of neurovision/computer vision,Spatial Mental Imagery and neurolinguistics we can process neural signals by feature extraction using a brain control interface.Your research work is truly remarkable and hence I thought your insights into the application development would be extremely helpful.Computational neurodynamics and cognitive informatics are closely related in processing neural information.Computational physics is also used to process neural information.

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    1. Dear Yogesh

      First of all thank you for asking. There are not one easy or direct answers to this question however, multiple possibilities exist depending what is that machine is trying to recognize. For example if it is a digit recognition task then it is not extremely difficult to assume that as one can train Convolutional Neural Networks and use standard classification techniques to label data and subsequently apply training method to see whether recognition reaches sufficient accuracy with the testing data. This can even be done with Spiking Neural Nets. Valence or Emotion classification on the other hand is a hard problem and neuroimaging results are not robust yet. Hence, better success has so far been achieved while dealing with simple input-output relationship for example left-right cursor movement control, finger tapping etc, Lifting an object up-and-down. These visuo-motor tasks are extremely pragmatic and important for developing interface for BCI applications. Neurofeedback also had relatively limited success in terms of controlling thoughts, actions. This is understandable as we are only scratching the tip of the iceberg and the iceberg very deep. Hence, without understanding Brain you will have very little success in decoding how does it solve simple or complex problem categories. You will have even lesser success in controlling those salient signals. Current trend shows that is where the field is going that is the understanding of complex processing in the Brain and trying to relate that to meaningful behaviour.
      I sincerely hope this gives you some additional insights.

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  2. Since I can’t upload pdf files I will paste so that you can see where the development level has already reached.
    United States Patent 1191 [11]
    Malech [45] Apr. 20, 1976
    [54] APPARATUS AND METHOD FOR
    REMOTELY MONITORING AND
    ALTERING BRAIN WAVES
    Inventor: Robert G. Malech, Plainview, NY.
    [75]
    [73] A Assignee: Dome & Margolin Inc., Bohemia,
    3,555,529 1/1971
    3,773,049 11/1973
    3,796,208 3/1974
    3,951,134
    Brown et al ……………….. .. 128/21 R
    Rabichev et a1. . . . . .
    . . . . . ..
    128/1
    C
    Bloice ………………………….. .. 128/2 S
    Primary Examiner—William E. Kamm
    Attorney, Agent, or Firm—-Darby & Darby
    NY.
    [57]
    [22] Filed:
    Aug. 5, 1974
    [21] Appl. No.: 494,518
    ‘APPARATUS AND METHOD FOR REMOTELY
    MONITORING AND ALTERING BRAIN WAVES

    When you read this you will see how defence applications are already connected to recognition systems using multi-disciplinary sciences.These recognition systems are neurovision,spatial mental imagery,BCI,etc but the network is using the above mentioned process which has already been patented.

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