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[Forum] Dr. Andrzej W Przybyszewski PhD, DSc, University of Massachusetts Medical School

“ Dynamical-oscillatory and decision-making attributes of the brain ”

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March 31, 2017 13:30 - 14:30


BSI Central Building 1F Seminar Room


Periodic movements of planets force different rhythms in our lives starting
from our daily rhythm of the rising and setting sun. Each of us has also
many subject - specific individual rhythms related to the hormone
production, physical activity, heart rate, respiratory rhythms, etc.
Interactions between external and internal rhythms determine adaptation
processes in our organisms. I will talk about such interactions in the
structure that is often assumed as a model of the brain – in the retina.
Our model simulates effects of external (rhythm) light shining on the retina
(photoreceptors) and its internal oscillations. Popular assumption is the
internal retinal oscillations are related to the noise, but our experiments
and model demonstrate that these oscillations help to classify attributes of
individual stimuli. On the basis of distinctive retinal circuits, we have
built artificial retina as assembly of couple nonlinear oscillators. Our
model has no noise but has similar stimulus responses and spontaneous
activity as ganglion cells in the cat retina.

In the second part of my talk, I will concentrate on the cognitive
computations of the visual system. Concepts representing objects physical
properties in variable environment are weak (not precise), but
psychophysical space shows precise object categorizations. Our model is
based on the receptive field properties of neurons in different visual
areas: thalamus, V1 and V4, and on feedforward (FF) and feedback (FB)
interactions between them. The FF pathways combine properties extracted in
each area into a vast number of hypothetical objects by using “driver
logical rules”, in contrast to “modulator logical rules” of the FB pathways.
The FB pathways function may help to change weak concepts of objects
physical properties into their crisp classification in psychophysical space.
I will use data mining and machine learning to find rules describing
receptive field properties in the visual area V4.

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Tomoki Fukai [Tomoki Fukai, Neural Circuit Theory ]
Name: Tomoki Fukai