My earlier academic work has focused on the dynamics of brain activity recorded using multielectrode arrays in various systems from organotypic slice cultures (2D brain networks in a dish) to electrodes implanted in awake monkeys and human patients undergoing surgical resection to treat epilepsy. The most interesting discovery was of a phenomenon called ‘Coherence Potentials’, network level waveforms with complex temporal structures that traveled through the network without distortion. Recently we were able to relate these coherence potentials to simple motor behaviors in a human patient.
Tipping Points in the Brain (Scientific American India) 2010
Coherence potentials encode simple human sensorimotor behavior. Parameshwaran D, Crone NE, Thiagarajan TC.PLoS One. 2012;7(2):e30514.
Coherence potentials: loss-less, all-or-none network events in the cortex.Thiagarajan TC, Lebedev MA, Nicolelis MA, Plenz D. PLoS Biol. 2010 Jan12;8(1)
Comments/Blogs on this work
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This section provides a detailed description of coherence potentials.
A coherence potential is a complex negative-positive waveform in the local field potential with a duration between 50 and 250 ms, reflecting aggregate neuronal activity in the local field that has exceeded a particular amplitude threshold and is therefore able to propagate to a large number of sites in the cortex without distortion of its temporal structure or substantial loss of amplitude. This is seen as a synaptic transmission dependent occurrence of the identical LFP waveform at different sites in the cortex with millisecond delays. In stark contrast, waveforms with peak amplitudes below the threshold traverse through the cortex with progressive distortion.
The path of propagation of coherence potentials is not wave like but rather jumps across the cortex to non-contiguous regions and stops abruptly. Generally they can start anywhere and will travel … Read More »
My doctoral work was focused on understanding of the individual neuron, specifically on how it responded to changes in activity in its environment and to blocking of specific channels of input. We discovered a tuning mechanism that allowed an adjusted response depending on the level of activity and also qualitative changes in the way the neuron communicated after long periods of activity deprivation (neuron neurosis?).
I also spent many years looking for evidence of presynaptic protein translation, a finding that would suggest that synapses are more autonomous than previously thought and that neurons therefore have a much more expanded computational capability. We found some really strong evidence but couldn’t nail it down all the way so the work remains yet unpublished….
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