[Seminar]"Patterned optical stimulation to interrogate summation and E/I balance in the hippocampus" by Prof. Upinder Bhalla

Speker: Prof. Upinder Bhalla

Institution: National Center for Biological Sciences

Title: Patterned optical stimulation to interrogate summation and E/I balance in the
hippocampus

Abstract:

Many neural circuits are believed to be in close excitatory-inhibitory (E-I)
balance. This makes it possible for neurons to have a very broad latent pool of
inputs, but 'pay attention' only to a few whose inhibitory balance is reduced.
Thus E-I balance has important implications for excitability, input gating,
and neuronal summation. While global balance is well-established, it is
unclear how closely E and I balance out at the level of few synapses, and
how precisely the timings of the E and I inputs match up. We used optogenetic
stimuli in CA3, delivered using a DMD projector, to sample a very wide
stimulus space with tight control over timing and number of cells.
We monitored responses in CA1, with and without inhibitory blockers, to
determine the nature and mechanism of balance. We find that E and I are
balanced down to a few inputs, and with a timing profile that leads to
a distinct form of summation we call subthreshold divisive normalization.
This has interesting implications for gating and input windows, and
we speculate that this may be a general property of feedforward networks
in the brain.


Bibliography:

I studied Physics at IIT Kanpur and Cambridge, and then did my PhD at
Caltech in the lab of James Bower. I worked on computational as well as
experimental neuroscience there, participating in the development of the
GENESIS simulator and working on rat olfaction. For my post-doc I went to
Mount Sinai School of Medicine in New York, with Ravi Iyengar. There I branched
into looking at subcellular computation through molecular signaling. I took up
a faculty positon in the new National Centre for Biological Sciences in 1996,
and have been there ever since. I continue to work on experiments and models.
My major current interests are subcellular and network sequence recognition,
memory, and multiscale neuronal computation.