Computational neuroethology linking neurons networks and behavior Mark

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

TALK OUTLINE Multiscale modeling in computational neuroethology Model system - weakly electric fish Modeling strategies n n Level I: III: IV: Summary Behavior Sensory physics Single neurons Local networks

Multiscale Organization of the Nervous System Delcomyn 1998 Organism 1 m Brain/CNS 10 cm Brain maps 1 cm Networks 1 mm Neurons 100 mm Synapses 1 mm Molecules 1Å Churchland & Sejnowski 1988

Neuroethology: Neural Basis of Behavior Organism Neural Integration Sensory Processing Brain Motor Control Body Sensors Effectors Environment Delcomyn 1998

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)

Electroreceptors mechano ~15, 000 tuberous electroreceptor organs 1 nerve fiber per electroreceptor organ up to 1000 spikes/s per nerve fiber Mac. Iver, from Carr et al. , 1982

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-mediated Prey capture behavior

Prey-capture video analysis

Prey capture behavior

Fish Body Model

Motion capture software

MOVIE: prey capture behavior

Rapid reversal marks putative time-of-detection Velocity Profile (N=116) Acceleration Profile (N=116) Zero-crossing in acceleration is used as detection time

Distribution of detection points Front view Side view

Active motor strategies: Dorsal roll toward prey

Neuroethology: Neural Basis of Behavior Organism Neural Integration Sensory Processing Brain Motor Control Body Sensors Effectors Environment Delcomyn 1998

PHYSICS of electrosensory image formation

Electrosensory Image Reconstruction

Estimating Daphnia signal strength Voltage perturbation at skin Df: fish E-field at prey volume electrical contrast distance from prey to receptor THIS FORMULA CAN BE USED TO COMPUTE THE SIGNAL AT EVERY POINT ON THE BODY SURFACE

Reconstructed Electrosensory Image (Df)

Electrosensory Images

ELECTROPHYSIOLOGY of primary sensory afferents

Electroreceptors mechano ~15, 000 tuberous electroreceptor organs 1 nerve fiber per electroreceptor organ Mac. Iver, from Carr et al. , 1982

Neural coding in electrosensory afferent fibers

Probability coding (P-type) afferent spike trains Phead = 0. 333 Phead = 0. 337 Phead = 0. 333 00010101100101010010100001010

Model of primary afferents Brandman & Nelson Neural Comp. 14, 1575 -1597 (2002)

ELECTROPHYSIOLOGY of CNS electrosensory neurons

ELL Circuitry

ELL histology

Compartmental Modeling

Compartmental Modeling Hodgkin-Huxley Model for voltage-dependent conductances

ELL pyramidal cell

ELECTROPHYSIOLOGY of electrosensory networks

Central Processing in the ELL

Primary Electrosensory Afferents te in m te p gr or at al io n Spatiotemporal processing in 3 parallel ELL maps Centromedial map Space: small RFs Time: low-pass Centrolateral map Space: med. RFs both Time: band-pass l ia n at tio sp gra te in Lateral map Space: large RFs Time: high-pass

Multiresolution filtering in the CNS

Neuroethology: Neural Basis of Behavior Organism Neural Integration Sensory Processing Brain Motor Control Body Sensors Effectors Environment Delcomyn 1998

Acknowledgements Malcolm Mac. Iver Noura Sharabash Relly Brandman Jozien Goense Rama Ratnam Rüdiger Krahe Ling Chen Kevin Christie Jonathan House NIMH and NSF