The neuron as a functional unit inputprocessingoutput shape

The neuron as a functional unit: input=>processing=>output shape - anatomy – excitability – neurotransmitter excitatory vs. inhibitory

Neuron types • Classification by anatomical features (“the face” of dendrites and axons) • Classification – functional (e. g. , Excitatory vs. Inhibitory neurons) • Classification using electrical/spiking activity pattern • Classification using chemical characteristics • Classification using gene expression

The neuron computes: input=>processing=>output (as is the whole brain - inspired from computer science) - Integrate & fire model of the neuron - Activation function (non-linear, probabilistic threshold) - Logistic regression (probs, odds and logit function)

Direction selectivity in retina ganglion cells: how is it computed? (modeling at the circuit level) light DS Ganglion Cells (optic nerve) Receptors bipolar cells amacrine cells

The brain computes (e. g. , direction of visual motion)

The Reichardt motion detector

The “Reichard detector” (possible connectivity that implements DS in retina ganglion cells) Based on asymmetry of E + I connection onto the GCs Preferred direction Null direction

Inhibition connects asymmetrically onto dendrites of DS retina ganglion cells Preferred direction Amacrine (inhibitory) cell DS Ganglion cell

The Brain Computes (Computational Neuroscience) How do the neuronal ingredients, synapses, neurons their electrical and chemical signals, and the distributed, interacting, networks that they form, represent and process information (compute)? David Marr’s 3 levels of understanding (the mind): 1. What are the problems needed to be solved by the brain? 2. What are the algorithm used to solve these problems? 3. And how do these algorithms implemented by the various brain regions? Why Model (the details? ) 1. Correct interpretation of experimental results (provides expt. predictions!) 2. Gain insights into key biophysical parameters (enables compact description of the physiological behavior studied capturing the essence e. g. , HH model for the AP) 3. Suggest possible computational (functional) role for the modeled system

A comment about “granularity of models” and their utility Detailed “realistic) model “Psychic” cell Kiss - detailed (model – simulation) Rodin “Point Neuron” Then carefully reduce (capture the essence) Kiss - reduced model (theory) Brancusi

Cerebral cortex - functional map (each region with its specific computational role) Movement Touch Vision Coordination Associations Hearing

The brain computes: During movement (crossing the street; reaching a cup) requires the computation of elementary variables (location of object, distance, movement direction and speed, etc. )

The brain computes: Computing image correlation and binding different parts of the image (figure – ground separation) is essential for the organism

The Brain Computes – active vision (“scanning algorithms”)

The brain computes

Ramon Y Cajal on Theorists “Advice for a young scientist” “Theorists are highly cultivated, wonderfully endowed minds whose wills suffer from a particular form of lethargy…” “They claim to view things in the grand scale, they live in clouds” “When faced with a difficult problem, they feel the irresistible urge to formulate a theory rather than question the nature…. ” “The essential thing for them is the beauty of the concept. It matters very little to them if the concept is based on thin air” “Basically, theorist is a lazy person masquerading as a diligent one. He unconsciously obeys the law of minimum effort because it is easier to fashion a theory than to discover a phenomenon”