Simultaneous integration versus sequential sampling in multiple-choice decision making Nate Smith July 20, 2008
Decision making A cognitive process of choosing an opinion or action between ≥2 choices Simultaneous integration accumulates evidence for both choices Sequential sampling dependent upon active changes in attention for choice action
Decision making Simultaneous integration
Decision making Sequential Sampling
Simultaneous Integration
Accumulator models used in perceptual decision making Smith and Ratcliffe, 2004 Diffusion ModelLeaky Competing Accumulator Model Does not easily extend to N-choiceDoes not retain ‘early’ information Can a network of neurons produce N-choice behavior?
Reduced 2 variable model for perceptual discrimination Reduced two variable model Mean field approx. Simplified F-I curves Constant NS activity Slow NMDA gating variable Wong and Wang, 2006
Generalized N-choice model for perceptual decisions
Multiple alternative simultaneous integration decision making Similar to previous random-dot motion tasks Three directions of coherent motion Subject has to saccade in direction of highest perceived motion (highest coherence) Niwa and Ditterich, 2008
Performance dependent on overall motion Niwa and Ditterich, 2008 Psychometric and reaction time data are more complex Simpler mechanism for describing choice behavior?
Can a biophysically realistic neural mechanism reproduce results similar to the human psychophysics study? Investigate whether the psychometric softmax function holds for N-choice tasks What dynamics underlie N-choice decision making? Research aims
Neural data produces variable reaction times and decisions
3-choice model fits human psychophysics data Neural model is able to reproduce findings from 3- choice simultaneous integration task
Theoretical psychometric softmax function fits data Plotting for different coherence values matches up vs. softmax function
Reaction time data Possible lateral inhibition/modulation in area MT responsible for scaling of input with multiple signals?
Sequential Sampling
Neural activity integrates information from each gaze
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First gaze biases selection and reaction time First gaze increases chance of choosing an option when objects have equivalent value Reaction time for objects with first gaze faster Probability Mean reaction time (ms)
Conclusions Biophysically realistic reduced model replicates experimental data Softmax function can work as a general underlying framework for decision making in neural circuits Neural pools can retain and integrate information even in absence of fixation
Acknowledgments Wang Lab Xiao-Jing Wang Alberto Bernacchia Tatiana Engel Morrie Furman John Murray Chung-Chuan Lo Christian Luhmann Jacinto Pereira Dahui Wang