Complementary congruent and opposite neurons achieve concurrent multisensory integration and segregation

  1. Wen-Hao Zhang
  2. He Wang
  3. Aihua Chen
  4. Yong Gu
  5. Tai Sing Lee
  6. KY Michael Wong  Is a corresponding author
  7. Si Wu  Is a corresponding author
  1. Hong Kong University of Science and Technology
  2. Carnegie Mellon University, United States
  3. East China Normal University, China
  4. Institute of Neuroscience, Chinese Academy of Sciences, China
  5. Peking University, China
8 figures and 1 additional file

Figures

Figure 1 with 1 supplement
Multisensory integration and segregation.

(A) Multisensory integration versus segregation. Two underlying stimulus features s1 and s2 independently generate two noisy cues x1 and x2, respectively. If the two cues are from the same stimulus, …

https://doi.org/10.7554/eLife.43753.002
Figure 1—figure supplement 1
Cue disparity information is lost after integration.

(A) Cue information is lost after integration. The information of cue 1 decreases with the extent of integration, which is controlled by κs, measuring the correlation between s1 and s2. (B) The …

https://doi.org/10.7554/eLife.43753.003
Congruent and opposite neurons in MSTd.

Similar results were found in VIP (Chen et al., 2011). (A–B) Tuning curves of a congruent neuron (A) and an opposite neuron (B). The preferred visual and vestibular directions are similar in (A) but …

https://doi.org/10.7554/eLife.43753.004
Geometric interpretation of multisensory processing of circular variables.

(A) Two von Mises distributions plotted in the polar coordinate (bottom-left) and their corresponding geometric representations (top-right). A von Mises distribution can be represented as a vector, …

https://doi.org/10.7554/eLife.43753.005
The decentralized neural circuit model for multisensory processing.

(A) The network consists of two modules, which can be regarded as MSTd and VIP respectively. Each module has two groups of excitatory neurons, congruent (blue circles) and opposite neurons (red …

https://doi.org/10.7554/eLife.43753.006
Tuning properties of congruent and opposite neurons in the network model.

(A–B) The tuning curves of an example congruent neuron (A) and an example opposite neuron (B) in module 1 under three cueing conditions. (C–D) The bimodal tuning properties of the example congruent …

https://doi.org/10.7554/eLife.43753.007
Figure 6 with 2 supplements
Optimal cue integration and segregation collectively emerge in the neural population activities in the network model.

(A) Illustration of the population response of congruent neurons in module 1 when both cues are presented. Color indicates firing rate. Right panel is the temporal average firing rates of the neural …

https://doi.org/10.7554/eLife.43753.008
Figure 6—figure supplement 1
Illustration of decoded joint distributions from congruent and opposite neurons.

Illustration of decoded joint distributions from congruent and opposite neurons respectively in two network modules under three cueing conditions, with the marginal distributions plotted in the …

https://doi.org/10.7554/eLife.43753.009
Figure 6—figure supplement 2
Test of network’s performance.

Comparison of the mean and concentration of network’s estimate with theoretical prediction. (A-B) The mean (A) and the concentration (B) of the congruent neurons in two network modules versus the …

https://doi.org/10.7554/eLife.43753.010
Concurrent multisensory processing with congruent and opposite neurons.

(A–B) Accessing integration versus segregation through the joint activity of congruent and opposite neurons. (A) The firing rate of congruent and opposite neurons exhibit complementary changes with …

https://doi.org/10.7554/eLife.43753.011
Figure 8 with 1 supplement
Discrimination of cue disparity by single neurons.

(A) The tuning curve of an example congruent (blue) and opposite (red) neuron with respect to cue disparity x1-x2. In the tuning with respect to cue disparity, the mean of two cues was always at 0°, …

https://doi.org/10.7554/eLife.43753.012
Figure 8—figure supplement 1
Discrimination of heading direction by single neurons.

Discrimination of heading direction by single neurons. The directions of the two cues are always the same. (A and D) The tuning curve of the example congruent (A) and opposite (D) neurons with cue …

https://doi.org/10.7554/eLife.43753.013

Additional files

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