brain and computation

1. Paper Review
Combining Feature Selection and Integration
—A Neural Model for MT Motion Selectivity
Interaction Science
정동녘

2. Introduction
• MT (Middle Temporal visual area,V5)

3. Introduction
<visual process pathway>
<Visual parallel processing>

4. Introduction
< Integrationist vs. Selectionist >
<Aperture problem>

5. Introduction
• “Integrationist” vs. “Selectionist”
• Aperture problem
• Any motion detecting device with a field
of view which is small relative to an edge
moving through it can only detect the
component of velocity at right angles to
the edge, while the component parallel to
the edge is invisible.

6. Introduction
• Psycholphysical and neurophysiological experiments
• The theory of integration of localized movement
signals
• Movshon JA, Adelson EJ, Gizzi MS, Newsome WT
(1985) The analysis of moving visual
patterns. In: Pattern recognition mechanisms
Chagas C, Gattass R, Gross C, eds. New York:
Springer. pp 117–151.

7. Methods
• 4 neural subpopulations in area V1, MT
• motion estimates independently
• weight, sharper tuning
• feed forward to MT contrast
• feedback

8. Methods
• Complex cells
• Respond most to movement directions
orthogonal to the local contrast orientation.
• Speed selectivity is achieved by filters of
increasing spatial size for neurons tuned to
higher speeds.
• Endstopped cells
• The direction of movement is computed

9. Methods
<Three processing steps>

10. Results
• Experiment 1 : Moving elongated bar

11. Results
• Experiment II : Plaid type I

12. Results
• Experiment III : Plaid type II

13. Results
• Experiment IV : Individual bars in one receptive field

14. Results
• Experiment V : Lesion experiments

15. Discussion
• Integrationist concept
• Albright TD (1984) Direction and
orientation selectivity of neurons in
visual area MT of the macaque. J
Neurophysiol 52: 1106–1130.
• But.. not enough
• Mingolla E, Todd JT, Norman JF (1992) The
perception of globally coherent motion.
Vis Research 32: 1015–1031.

16. Discussion
• Process of computing pattern motion
• Temporal dynamics that gradually
change from a tuning to the vector
average to a tuning to the IOC
direction

17. Discussion
Feature integration + feature selection in neural behavior
a) Two neural subpopulations in area V1 that perform distinct
computations of motion providing both the normal flow and the
flow at 2D features.
b) A subpopulation in MT that integrates the input of both V1
subpopulations with a more pronounced influence of the 2D
(endstopped) features.
c) Feedback connections between MT subpopulations and from MT
motion integration stage to V1 subpopulations that allow the
propagation and enhancement of salient motion.