Title: Computational neuroethology: linking neurons, networks and behavior
1Computational neuroethologylinking neurons,
networks and behavior
- Mark E. Nelson
- Beckman Institute
- Univ. of Illinois, Urbana-Champaign
2TALK OUTLINE
- Multiscale modeling in computational
neuroethology - Model system - weakly electric fish
- Modeling strategies
- Level I Behavior
- Level II Sensory physics
- Level III Single neurons
- Level IV Local networks
- Summary
3MultiscaleOrganization of theNervous System
Organism
1 m
Brain/CNS
10 cm
Brain maps
1 cm
Networks
1 mm
Neurons
100 mm
Synapses
1 mm
Molecules
1 Å
Churchland Sejnowski 1988
Delcomyn 1998
4NeuroethologyNeural Basis of Behavior
Organism
Neural Integration
Brain
Sensory Processing
Motor Control
Body
Sensors
Effectors
Environment
Delcomyn 1998
5Neuroethology 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?
6BACKGROUNDWeakly Electric Fish
7Distribution of Electric Fish
8Black ghost knifefish (Apteronotus albifrons)
9Electroreceptors 15,000 tuberous
electroreceptor organs1 nerve fiber per
electroreceptor organup to 1000 spikes/s per
nerve fiber
mechano
MacIver, from Carr et al., 1982
10Ecology 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
11Self-generated Electric Field
12Principle of active electrolocation
13Prey-capture Behavior
Daphnia magna (water flea)
1 mm
14BEHAVIORElectrosensory-mediatedPrey capture
behavior
15Prey-capture video analysis
16Prey capture behavior
17Fish Body Model
18Motion capture software
Motion capturesoftware
19MOVIE prey capture behavior
20Rapid reversal marks putative time-of-detection
Velocity Profile (N116)
Zero-crossingin accelerationis used
asdetection time
Acceleration Profile (N116)
21Distribution of detection points
Front view
Side view
22Active motor strategies Dorsal roll toward prey
23NeuroethologyNeural Basis of Behavior
Organism
Neural Integration
Brain
Sensory Processing
Motor Control
Body
Sensors
Effectors
Environment
Delcomyn 1998
24PHYSICSofelectrosensory image formation
25Electrosensory Image Reconstruction
26Estimating Daphnia signal strength
- Voltage perturbation at skin Df
prey volume
electrical contrast
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
27(No Transcript)
28Reconstructed Electrosensory Image (Df)
29Electrosensory Images
30ELECTROPHYSIOLOGYofprimary sensory afferents
31Electroreceptors 15,000 tuberous
electroreceptor organs1 nerve fiber per
electroreceptor organ
mechano
MacIver, from Carr et al., 1982
32Neural coding inelectrosensory afferent fibers
33Probability coding(P-type) afferent spike trains
?Phead? 0.337
Phead 0.333
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00010101100101010011001010000101001010
34Model of primary afferents
Brandman Nelson Neural Comp. 14, 1575-1597
(2002)
35ELECTROPHYSIOLOGYofCNS electrosensory neurons
36ELL Circuitry
37ELL histology
38Compartmental Modeling
39Compartmental Modeling
Hodgkin-Huxley Model for voltage-dependent
conductances
40Compartmental Modeling
Hodgkin-Huxley Model for voltage-dependent
conductances
41ELL pyramidal cell
42ELECTROPHYSIOLOGYofelectrosensory networks
43Central Processing in the ELL
44Spatiotemporal processing in 3 parallel ELL maps
Centromedial map Space small RFs Time low-pass
temporal integration
Centrolateral map Space med. RFs Time band-pass
Primary Electrosensory Afferents
both
spatial integration
Lateral map Space large RFs Time high-pass
45Multiresolutionfiltering in the CNS
46NeuroethologyNeural Basis of Behavior
Organism
Neural Integration
Brain
Sensory Processing
Motor Control
Body
Sensors
Effectors
Environment
Delcomyn 1998
47Acknowledgements
- Malcolm MacIver
- Noura Sharabash
- Relly Brandman
- Jozien Goense
- Rama Ratnam
- Rüdiger Krahe
- Ling Chen
- Kevin Christie
- Jonathan House
-
- NIMH and NSF