Inside Salk - October 2009 - page 13

Inside SalkOctober 2009
I’m also attracted to different
theoretical models and theoretical
questions. One of those is
optimization of information
transfer in networks.
frame, it actually becomes possible when you analyze responses from
10,000 different images, taking into considerationwhich combination
of features produced spikes andwhich did not. Together withmy
postdoctoral advisors, we worked to develop an algorithm that can do
this correctly regardless of which frames were presented. It is very
important with natural stimuli because they are often poorly controlled.
To illustrate themain idea of themethods let’s say an image contains
three elements, and the next image contains these elements in different
positions or perhaps even different elements. Then as you do your analy-
sis, you start to see, a-ha, this one caused a spike, and this one didn’t
when the elements weremoved apart. So you start getting statistics of
themost likely feature that is associatedwith a neuron’s response.
Using advanced statistical techniques, we can create templates for
neuron activity from natural visual stimuli.
Does your work focus solely on visual stimuli?
We also use auditory stimuli to learnmore about the auditory cortex,
which is not as well known or studied as the primary visual cortex.
Auditory studies in some ways aremore complicated, and some argue
that primary auditory cortex ismore equivalent to high-level visual
neurons than to the primary visual cortex. We know that a given neuron
will prefer a certain frequency in the tone or maybe it’ll have a sweep
up frequency or a sweep down frequency, but that’s about it. But
through the auditory experiments, we learn about a different brain area
and as theorists we try tomake parallels between different senses, such
as vision or audition, and search for overarching principles.
What does your lab hope to learn by these types
of experiments?
One goal is to learn how signals are integrated in the visual cortex to
allow us to perceive objects and shapes. I’m also attracted to theoreti-
cal questions of optimization of information transfer in networks. There
is an emerging viewpoint that the primary function of many biological
networks, either within a cell or between cells, as in neural networks,
is the transfer and processing of information. So for example, through
phosphorylation a given protein can integratemultiple inputs into a
single output that is a graded function of the combination of inputs.
At least mathematically, this operation is verymuch analogous to the
integration of signals in the nervous systemwhere a given neuronwould
sum its synaptic inputs, and produce a spike if the result of integration
exceeds a certain threshold. In our recent work (currently in press), we
have described how networks of such graded nodes can be set up to
convey themaximal amount of information. Assuming the network is
optimal, our theoretical analysis also provides a way to infer the strength
of interactions with unmeasured parts of the network. This is important
because only rarely do we havemeasurements on a complete circuit in
the nervous system. We are looking forward to seeing how these ideas
will fare against experimental data.
You grew up in the Soviet Union. Wherewere you in your
academic life during the dissolution period? Andwas a
career in science encouraged for women during that time?
That was around 1992, so I was graduating from high school. The
official policy of the Soviet Unionwas equality for all, to quote a slogan
from a classic Soviet film “woman is a human being too.” So I think the
government tried to promote participation of women. But there’s the
official language and then there’s reality. I wasn’t always comfortable
based on the peer pressure, but I think at least at the early stages of
their careers women participationwas encouraged.
Was there anyone inparticular who encouraged you to get
into science?
Yeah, there were lots of people. I had a very good physics teacher in
high school, Anatoliy Israilevich Shapiro, who had interesting techniques
for teaching students. For example, he would provide very small blank
sheets of paper, just several square inches, and give us problems to
solve. He thought that having to express ones thoughts on the small
sheets promoted creativity when you really had to think about what
to write in such a small space. And a problem could be, for example:
“Write 10ways to speed up the drying process of a wet umbrella.”He
always emphasized that it was better to solve one problem10 different
ways than to solve 10 problems the same way. My family also influenced
me. My grandfather and grandmother aremathematicians andmy
parents are physicists, so even though I thought I had a choice, in
reality I didn’t. I was gently steered into this field.
You work in a field that’s dominated by men. Do you ever
feel the need to encourage other women to consider
a career in computational neurobiology?
I re ently gave a presentation for Women Scientists in Action at the
RuebenH. Fleet Science Center where I spoke to the girls there, but
they are so little. I haven’t talked to fifth and sixth graders in like 20
years (laughs). So I was trying to tell them about all of the advantages
of being a scientist, but I am afraid that my presentation could have
been way out of their interests. But it was a learning experience for me
as well, somaybe next time I’ll be able to connect better with the girls.
You’ve received several prestigious fellowships in the last
year. Howwill you use the funds to expand your research?
At the genetic level, we know the code inDNA is universal whether it’s a
fly, amouse or a human, and that’s a great success of molecular biology.
In neuroscience, we don’t even know exactly what the code is, other than
the spikes are important. For example, we don’t know to what extent the
precise timing of individual spikesmatters, and the answer might turn
out to be different for neurons in different systems or species. So one
of the grants ismeant to helpmy lab search for universal symbols in
neurotransmission, comparing the structure of neural code in visual or
auditory neurons inmammals, birds, and/or flies.
What would finding these universal codes tell us?
Disorders of the nervous system are devastating. Unfortunately, the
cures that are available are rather blunt or nonexistent, and often do
not take into account the fine scale organization of the nervous system.
Understanding details of communication with spikes is a pre-requisite
for developing better cures.
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