Some concepts from Cognitive Psychology to review:

1. Some concepts from Cognitive Psychology to review: • Shadowing • Visual Search • Cue-target Paradigm Hint: you’ll find these in Chapter 12

2. Read this article for next week: A Neural Basis for Visual Search in Inferior Temporal Cortex Leonardo Chelazzi et al. (1993) Nature

3. Attention Solves an Ambiguity Problem • Sensory Input Ambiguity Cell “tuned” to red. Should it fire? Area V4 Receptive field = ~4 deg visual angle

4. Attention Solves an Ambiguity Problem • Visual search is the process of seeking a target from a complex scene • Should the cell tuned to “red” fire: • whenever red is present in RF? • In proportion to how much red is present? • In a more sophisticated way? Area V4 Receptive field = ~4 deg visual angle

5. Attention Solves an Ambiguity Problem • Response Mapping Ambiguity (e.g. Stroop Task) B L U E Cell “tuned” to line orientation. Should it affect your response? If you do computational neuroscience, This is why you should think about attention. Area V4 Receptive field = ~4 deg visual angle

6. Attention Solves a Network Complexity Problem • The brain is a massively interconnected network - each neuron makes ~ 1000 connections Gordon Kindlmann & Andrew Alexander University of Wisconsin Van Essen, Andersen & Felleman (1992)

7. Attention Solves a Network Complexity Problem • On the time scale of behaviour, the network is anatomically hard-wired • Fast functional reconfiguration

8. Attention Solves a Network Complexity Problem • Point to the red horizontal line

9. Attention Solves a Network Complexity Problem • Point to the red horizontal line Visual stimulus drives visual neurons Motor plan is executed Black Brain Box

10. Attention Solves a Network Complexity Problem • Point to the red horizontal line Visual stimulus drives visual neurons Motor plan is executed Black Brain Box

11. Attention Solves a Network Complexity Problem • Point to the red horizontal line • Notice the mapping is selective:

12. Attention Solves a Network Complexity Problem • Point to the red horizontal line • Notice the mapping is selective:

13. Attention Solves a Network Complexity Problem • Now point to the green vertical line • Notice the mapping is easily reconfigured

14. Attention Solves a Network Complexity Problem

15. Attention Solves a Network Complexity Problem • Thus sensory neurons are in some sense omnipotent • each one’s contribution to cognitive and motor networks is not determined by anatomical connectivity • it is determined dynamically by some control system

16. Attention Solves a Network Complexity Problem • Notice this is an extension of the “binding problem” • Cells representing features of the same objects must contribute to a “reconstituted” whole object representation • These cells must be “bound” to all the other cells mediating the current cognitive or motor behaviour If you study the “connectome”, this is why you should think about attention.

17. Attention Solves a Network Complexity Problem • The brain is a massively interconnected network - each neuron makes ~ 1000 connections

18. Attention Solves a Network Complexity Problem • The brain is a massively interconnected network - each neuron makes ~ 1000 connections X 1000

19. Attention Solves a Network Complexity Problem • The brain is a massively interconnected network - each neuron makes ~ 1000 connections X 1000 X 1000

20. Attention Solves a Network Complexity Problem • The brain is a massively interconnected network - each neuron makes ~ 1000 connections X 1000 X 1000 X 1000 X 1000 X 1000

21. Attention Solves a Network Complexity Problem • Crude Analogy • By 4 synapses the tree comprises more than 10 Billion cells! • Attention prevents runaway connectivity: • Clearly the brain must have a system by which information is routed appropriately through the network

22. Attention Solves a Network Complexity Problem • What does runaway connectivity look like? • Here’s a hint: the “feed forward” sweep of signal following a visual event is relatively unconstrained by attention Red = earliest response at this latency Yellow = has already responded Lamme (2000) By ~115 ms post-stimulus, much of the cortex has responded to the visual event

23. Attention Solves a Network Complexity Problem • What would be the consequence if attention did not select cell assemblies? Neural Gridlock? Maybe not the right concept.

24. Attention Solves a Network Complexity Problem • The brain is a system of coupled oscillators • Driving such systems can trigger unexpected synchronization

25. Attention Solves a Network Complexity Problem • Classic Example of spontaneous synchronization

26. Attention Solves a Network Complexity Problem • See a fabulous TED talk about synchronization by Steven Strogatz at: www.ted.com/talks/steven_strogatz_on_sync.html

27. Attention Solves a Network Complexity Problem • Do brains exhibit runaway global synchronization? • Yes, this is characteristic of certain kinds of epileptic seizures. 3 Hz “Spike and Wave” EEG pattern during absence seizure

28. Attention Solves a Network Complexity Problem • OK so how might a brain solve this problem? How might the attention system facilitate a dominant cell assembly and suppress others? • “Neuronal communication through neuronal coherence” - Pascal Fries, TINS (2005)

29. Attention Solves a Network Complexity Problem • Individual oscillators coupled to a central oscillator

30. Attention Solves a Network Complexity Problem • Role of the “central oscillator” has been called the “dominant network” • Communication-through-coherence suggests that oscillations within cell assemblies become phase locked • One set of such assemblies achieves global dominance by having their individual phases nudged into coherence