Dynamics of Perceptual Bistability

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Dynamics of Perceptual Bistability J Rinzel, NYU
w/ N Rubin, A Shpiro, R Curtu, R Moreno

• Alternations in perception of ambiguous stimulus
  irregular
• Oscillator models mutual inhibition, switches
  due to adaptation
• -- noise gives randomness to period
• Attractor models noise driven, no alternation
  w/o noise
• Constraints from data ltTgt, CV
• Which model is favored?

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Mutual inhibition with slow adaptation
? alternating dominance and suppression
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Oscillator Models for Directly Competing
Populations
Two mutually inhibitory populations,
corresponding to each percept. Firing rate model
r1(t), r2(t) Slow negative feedback adaptation
or synaptic depression.
f
r1
No recurrent excitation half-center oscillator
w/ N Rubin, A Shpiro, R Curtu
Wilson 2003 Laing and Chow 2003
Shpiro et al, J Neurophys 2007
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Alternating firing rates
Adaptation slowly grows/decays
WTA or ATT regime
adaptation LC model
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Analysis of Dynamics
Fast-Slow dissection r1 , r2 fast variables
a1 , a2 slow variables
a1, a2 frozen
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r1-r2 phase plane, slowly drifting nullclines

• At a switch
• saddle-node in fast dynamics.
• dominant r is high while system rides
• near threshold of suppressed populns
• nullcline ? ESCAPE.

r1- nullcline r2- nullcline
ß 0.9, I1I21.4
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Switching due to adaptation release or escape
mechanism
f
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Noise leads to random dominance durations and
eliminates WTA behavior.
t dri/dt -ri f(-ßrj - g ai Ii ni) ta
dai/dt -ai ri
Added to stimulus I1,2 s.d., s 0.03, tn 10
Model with synaptic depression
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Noise-Driven Attractor Models
w/ R Moreno, N Rubin J Neurophys, 2007
No oscillations if noise is absent.
Kramers 1940
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LP-IV in an attractor model
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Compare dynamical skeletons oscillator and
attractor-based models

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Observed variability and mean duration constrain
the model.
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Favored noise-driven attractor with weak
adaptation but not far from oscillator regime.
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Best fit distribution depends on parameter values.
Noise dominated Adaptation dominated
I1 , I2 0.6
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Swartz Foundation and NIH.
SUMMARY

• Experimentally
• Monotonic ltTgt vs I
• ltTgt and CV as constraints
• No correlation between successive cycles
• Models, one framework vary params.
• Mutual, direct inhibition w/o recurrent
  excitation
• Non-monotonic dominance duration vs I1, I2
• Attractor regime, noise dominated
• Better match w/ data.
• Balance between noise level and adaptation
  strength.
• Oscillator regime, adaptation dominated
• Relatively smaller CV.
• Relatively greater correlation between successive
  cycles.
• Moreno model (J Neurophys 2007) local
  inhibition, strong recurrent excitation
  monotonic ltTgt vs I.

w/ N Rubin, A Shpiro, R Curtu, R Moreno