Simultaneous integration versus sequential sampling in multiple-choice decision making

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Simultaneous integration versus sequential
sampling in multiple-choice decision making

• Nate Smith
• July 20, 2008

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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

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Decision makingSimultaneous integration
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Decision makingSequential Sampling
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Decision makingSequential Sampling
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Decision makingSequential Sampling
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Decision makingSequential Sampling
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Simultaneous Integration
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Accumulator models used in perceptual decision
making
Diffusion Model
Leaky Competing Accumulator Model

• Does not easily extend to N-choice

• Does not retain early information

• Can a network of neurons produce N-choice
  behavior?

Smith and Ratcliffe, 2004
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Reduced 2 variable model for perceptual
discrimination
Mean field approx.
Simplified F-I curves Constant NS activity
Slow NMDA gating variable
Reduced two variable model
Wong and Wang, 2006
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Generalized N-choice model for perceptual
decisions
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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
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Performance dependent on overall motion
Niwa and Ditterich, 2008

• Psychometric and reaction time data are more
  complex
• Simpler mechanism for describing choice behavior?

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Research aims

• 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?

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Neural data produces variable reaction times and
decisions
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3-choice model fits human psychophysics data

• Neural model is able to reproduce findings from
  3-choice simultaneous integration task

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Theoretical psychometric softmax function fits
data

• Plotting for different coherence values matches
  up vs. softmax function

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Reaction time data
Possible lateral inhibition/modulation in area MT
responsible for scaling of input with multiple
signals?
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Sequential Sampling
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Neural activity integrates information from each
gaze
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Neural activity integrates information from each
gaze
A
B
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Neural activity integrates information from each
gaze
A
B
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Neural activity integrates information from each
gaze
A
B
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Neural activity integrates information from each
gaze
A
B
25
Neural activity integrates information from each
gaze
A
B
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Neural activity integrates information from each
gaze
A
B
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Neural activity integrates information from each
gaze
A
B
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Neural activity integrates information from each
gaze
A
B
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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

Mean reaction time (ms)
Probability
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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

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Acknowledgments

• Wang Lab
• Xiao-Jing Wang
• Alberto Bernacchia
• Tatiana Engel
• Morrie Furman
• John Murray
• Chung-Chuan Lo
• Christian Luhmann
• Jacinto Pereira
• Dahui Wang