1. NEUROBIOLOGY OF DECISION-MAKING, CSHL, May 2005 Choice, decision and action investigated with visually guided saccades. Jeffrey D. Schall With Leanne Boucher, Gordon Logan & Tom Palmeri

2. Choice – action in the context of alternatives to satisfy a goal, desire or preference Action – movements with consequences that can be explained by referring to preferences, goals and beliefs Decision – deliberation when alternatives are vague, payoffs are unclear and habits are reversed Definitions “I look forward to playing and hopefully I can get to that point where I can make that decision.” — Michael Jordan on his anticipated return to professional basketball. Associated Press, 19 July 2001. "I feel that way right now. Ask me in two or three months and I may change. I don't think I will. I'm pretty sure that's my decision." — Michael Jordan on his retirement from professional basketball. Associated Press, 17 July 1998.

3. Distinguish two uses of “decision” As characteristic of behavior (e.g., Decision Theory) But measures of outcome do not specify mechanism As process producing behavior Mechanism with particular architecture Decision as process has two distinct meanings Decide to -- Alternative actions (can be identified with choosing) Decide that -- Alternative categories (not identified with choosing) Further defining “decision”

4. The properties of neurons do not reveal function Formal (computational) theories of performance explain function But distinct models cannot be distinguished from behavior testing, e.g., diffusion or race Properties of neurons might provide constraints to distinguish between models … … if and only if the neural activity measured is the instantiation of the cognitive process in question, which constitutes a linking proposition Necessity of formal linking propositions Teller DY. 1984. Vision Research 24:1233-1246 Schall JD. 2004. Ann Rev Psychol 55:23-50

5. Linking propositions for decision making Time from stimulus (sec) Activation 0.00.10.2 Hanes & Schall (1996) described neural activity that looked like an accumulator. They identified this activity with form of sequential sampling models.

6. Time from stimulus (sec) Activation 0.00.10.2 Linking propositions for decision making RT = Decision time + Residual time Residual time = Encoding time + Preparation time Stimulus encoding Sequential sampling Response preparation Time from stimulus (sec) Activation 0.00.10.2

7. Countermanding task

8. Countermanding performance

9. Countermanding paradigm: Race model Logan, G.D. & Cowan, W.B. (1984) On the ability to inhibit thought and action: A theory of an act of control. Psychological Review 91:295-327. Hanes DP and Schall JD (1995) Countermanding saccades in macaque.Visual Neuroscience 12:929-937 Reaction Time Stop Signal Delay CANCELLED “GO” “STOP” NON-CANCELLED “GO” “STOP”

10. Visual Cortex LGN RF Saccade Thalamus Cerebellum SCs SCi Frontal cortex (DLPFC, ACC, SEF ) Parietal Cortex (LIP) Retina Temporal Cortex (TEO) FEF Basal Ganglia Munoz DP, Schall JD (2003) Concurrent distributed control of saccade initiation in the frontal eye field and superior colliculus. In The Oculomotor System: New Approaches for Studying Sensorimotor Integration. Edited by WC Hall, AK Moschovakis. CRC Press, Boca Raton, FL. Pages 55-82. Saccades are produced by a distributed network

11. Countermanding physiology No stop trials Non-canceled trials No stop trials Canceled trials STOPSSRTSTOPSSRT Hanes, D.P., W.F. Patterson, J.D. Schall (1998) The role of frontal eye field in countermanding saccades: Visual, movement and fixation activity. Journal of Neurophysiology 79:817-834. Pare M, Hanes DP (2003) Controlled movement processing: superior colliculus activity associated with countermanded saccades. Journal of Neuroscience 23:6480-6489.

12. 1 - The race model of countermanding performance assumes that the GO and the STOP processes have independent finish times (Logan & Cowan, 1984). Mapping the race model onto neural processes 2 – Saccades are produced by a network of interacting neurons. Paradox – How can a network of interacting neurons produce behavior that looks like the outcome of race between independent processes?

13. Explore properties of simple network of GO and STOP units. Mapping the race model onto neural processes Constrained by the characteristics of countermanding behavior and by the form of activation of neurons L.Boucher, G.D.Logan, T.J.Palmeri, J.D.Schall. An interactive race model of countermanding saccades. Program No. 72.10. 2003 Abstract Viewer/Itinerary Planner.

14. Complete independence STOPGO L.Boucher, G.D.Logan, T.J.Palmeri, J.D.Schall. An interactive race model of countermanding saccades. Program No. 72.10. 2003 Abstract Viewer/Itinerary Planner.

15. Complete independence Reproduces countermanding behavior… STOPGO L.Boucher, G.D.Logan, T.J.Palmeri, J.D.Schall. An interactive race model of countermanding saccades. Program No. 72.10. 2003 Abstract Viewer/Itinerary Planner.

16. Complete independence Stop SignalSSRT Stop SignalSSRT … but does not produce correct activations. The GO process is never interrupted! STOPGO

17. Key insight – the inhibition of STOP on GO cannot be uniform and instantaneous; it must be late and potent STOPGO Δt

18. Delayed potent STOP STOPGO Δt STOPSSRT

19. Delayed potent STOP Reproduces countermanding behavior… STOPGO Δt

20. Delayed potent STOP … and reproduces neural activation The GO process is not modulated in non-canceled trials The GO process is modulated within SSRT in canceled trials STOPGO Δt

21. Countermanding performance is produced by pool of neurons the prepare movements (GO process) and pool of neurons that interrupt preparation (STOP process). The STOP process is composed of an early (afferent) stochastic stage and a late potent interruption stage. Specific conclusions

22. Redundant but distinct models cannot be distinguished based on behavior data (Moore, 1956, in Automata Studies, ed. CE Shannon, J McCarthy. Princeton Univ. Press) Properties of neurons can distinguish between alternative architectures … but only if neurons instantiate the processes in question. GO process identified with pool of “movement” neurons. STOP process identified with pool of “movement inhibition” neurons. General conclusions

23. Stochastic response preparation process necessary to explain countermanding performance. If so, response preparation must be more or less stochastic during all tasks. Therefore, the proper form of response preparation variability must be incorporated into sequential sampling models of perceptual or memory decisions. This and much other evidence indicates that RT is the expression of at least two distinct but not necessarily discrete stages of processing – encoding+categorization (decide that) and response preparation (decide to). General conclusions continued

24. It is possible now to determine the duration of intermediate stages with invasive measures of neural states. However, this depends on proper linking propositions. Information about process durations and transitions is necessary to elucidate how stimulus ambiguity, prior probability and reward history influence choices. "[Since] we cannot break up the reaction into successive acts and obtain the time of each act, of what use is the reaction time?" – R.S. Woodworth (1938) in Experimental Psychology [quoted in Luce (1986)]

25. Rees et al. Nature Neuroscience 3, 716 - 723 (2000) An empirical basis for distinguishing between choosing and deciding It is deciding when anterior cingulate cortex is engaged. Area MT fMRI amplitude 0%100% Motion strength Anterior cingulate cortex 0%100% Motion strength

28. Time from target (ms) 0 200 400 SSRTStop Signal SSRTStop Signal 400200 0 100 Time from target (ms) Activation (Spikes/sec) Fixation cell activity from FEF & SC Hanes, D.P., W.F. Patterson, J.D. Schall (1998) The role of frontal eye field in countermanding saccades: Visual, movement and fixation activity. Journal of Neurophysiology 79:817-834. Pare M, Hanes DP (2003) Controlled movement processing: superior colliculus activity associated with countermanded saccades. Journal of Neuroscience 23:6480-6489.