Computational neuroethology: linking neurons, networks and behavior Mark E. Nelson Beckman Institute Univ. of Illinois, Urbana-Champaign.

Computational neuroethology:

linking neurons, networks and behavior

Mark E. Nelson

Beckman InstituteUniv. of Illinois, Urbana-Champaign

TALK OUTLINE

Multiscale modeling in computational neuroethologyModel system - weakly electric fishModeling strategies Level I: Behavior Level II: Sensory physics Level III: Single neurons Level IV: Local networks

Summary

MultiscaleOrganization of

theNervous System

Organism

Brain/CNS

Networks

Neurons

Synapses

Molecules

Brain maps

1 m

10 cm

1 mm

100 m

1 m

1 Å

1 cm

Churchland & Sejnowski 1988Delcomyn 1998

Neuroethology:Neural Basis of

Behavior

EnvironmentDelcomyn 1998

Sensors Effectors

Organism

SensoryProcessing

MotorControl

NeuralIntegration

Brain

Body

Neuroethology of Electrolocation

Big picture: What are the neural mechanisms and computational principles of active sensing?

Small picture: How do weakly electric fish capture prey? What computations take place in the CNS during prey capture behavior?

BACKGROUND

Weakly Electric Fish

Distribution of Electric Fish

Black ghost knifefish (Apteronotus albifrons)

mech

an

o

MacIver, fromCarr et al., 1982

Electroreceptors ~15,000 tuberous electroreceptor organs1 nerve fiber per electroreceptor organ

up to 1000 spikes/s per nerve fiber

Ecology & Ethology of A. albifrons

inhabits tropical freshwater rivers and streams in South America

nocturnal; hunts at night for aquatic insect larvae and small crustaceans in turbid water

uses electric sense for prey detection, navigation, social interactions

ribbon fin propulsion – forward/reverse/hover

Self-generated Electric Field

Principle of active electrolocation

Prey-capture Behavior

Daphnia magna(water flea)

1 mm

BEHAVIOR

Electrosensory-mediatedPrey capture behavior

Prey-capture video analysis

Prey capture behavior

Fish Body Model

Motion capture softwareMotion capturesoftware

MOVIE: prey capture behavior

Rapid reversal marks putative time-of-detection

Velocity

Profile(N=116)

Acceleration

Profile(N=116)

Zero-crossingin acceleration

is used asdetection time

Distribution of detection points

Front view Side view

Active motor strategies:

Dorsal roll toward prey

Neuroethology:Neural Basis of

Behavior

EnvironmentDelcomyn 1998

Sensors Effectors

Organism

SensoryProcessing

MotorControl

NeuralIntegration

Brain

Body

PHYSICSof

electrosensory image formation

Electrosensory Image Reconstruction

Voltage perturbation at skin :

Estimating Daphnia signal strength

waterprey

waterpreyfish ar

rE

/21

/133

electrical contrastprey volume

fish E-field at prey

distance from prey to receptor

THIS FORMULA CAN BE USED TO COMPUTE THE SIGNAL AT EVERY POINT ON THE BODY

SURFACE

Reconstructed Electrosensory Image ()

Electrosensory Images

ELECTROPHYSIOLOGYof

primary sensory afferents

mech

an

o

MacIver, fromCarr et al., 1982

Electroreceptors ~15,000 tuberous electroreceptor organs1 nerve fiber per electroreceptor organ

Neural coding inelectrosensory afferent fibers

Probability coding(P-type) afferent spike trains

00010101100101010011001010000101001010

Phead = 0.333

Phead = 0.337 Phead =

0.333

Model of primary afferents

Brandman & Nelson Neural Comp. 14, 1575-1597 (2002)

ELECTROPHYSIOLOGYof

CNS electrosensory neurons

ELL Circuitry

ELL histology

Compartmental Modeling

Compartmental ModelingHodgkin-Huxley Model for

voltage-dependent conductances

Compartmental Modeling

)()()( 43LmLKmKNamNaion EVgEVngEVhmgI

mVmVdt

dmmm )()1)((

hVhVdt

dhhh )()1)((

nVnVdt

dnnn )()1)((

Hodgkin-Huxley Model forvoltage-dependent

conductances

ELL pyramidal cell

ELECTROPHYSIOLOGYof

electrosensory networks

Central Processing in the ELL

Spatiotemporal processing in 3 parallel ELL maps

Primary Electrosensor

y Afferents

Centromedial map Space: small RFs Time: low-pass

Centrolateral map Space: med. RFs Time: band-pass

Lateral map Space: large RFs Time: high-pass

tem

pora

l

inte

grat

ion

bothspatial

integration

Multiresolutionfiltering in the CNS

Neuroethology:Neural Basis of

Behavior

EnvironmentDelcomyn 1998

Sensors Effectors

Organism

SensoryProcessing

MotorControl

NeuralIntegration

Brain

Body

Acknowledgements Malcolm MacIver Noura Sharabash Relly Brandman Jozien Goense Rama Ratnam Rüdiger Krahe Ling Chen Kevin Christie Jonathan House

NIMH and NSF