Direction-Selective Circuits Shape Noise to Ensure a Precise Population Code

Abstract

Summary Neural responses are noisy, and circuit structure can correlate this noise across neurons. Theoretical studies show that noise correlations can have diverse effects on population coding, but these studies rarely explore stimulus dependence of noise correlations. Here, we show that noise correlations in responses of ON-OFF direction-selective retinal ganglion cells are strongly stimulus dependent and we uncover the circuit mechanisms producing this stimulus dependence. A population model based on these mechanistic studies shows that stimulus-dependent noise correlations improve the encoding of motion direction two-fold compared to independent noise. This work demonstrates a mechanism by which a neural circuit effectively shapes its signal and noise in concert, minimizing corruption of signal by noise. Finally, we generalize our findings beyond direction coding in the retina and show that stimulus-dependent correlations will generally enhance information coding in populations of diversely tuned neurons.

“Silent” NMDA Synapses Enhance Motion Sensitivity in a Mature Retinal Circuit

“…Fourth, the neighboring DSGCs receive common input from bipolar cells (∼ 50% dyadic connections are shared with other DSGCs; Figure 4), regardless of the direction they code. This suggests that NMDA modulation would occur in a correlated way across the four types of DSGCs, helping to preserve the population code (Zylberberg et al, 2016). Thus, it appears that silent synapses engage with diverse mechanisms to produce a robust DS code, down to threshold levels.…”

Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory

“…For example, synaptic failures (Branco & Staras 2009), ion channel fluctuations (Goldwyn & Shea-Brown 2011, White et al 2000), and ongoing noisy inputs from other brain areas (Churchland et al 2010) or from the sense organs (Field et al 2005, Zylberberg et al 2016a) can cause random changes in the inputs experienced by cortical neurons. For perfectly tuned bump attractors, this noise will cause the activity bump to move randomly, changing the remembered position; similar statements apply to other types of continuous attractors.…”

Parallel Computations in Insect and Mammalian Visual Motion Processing

“…This organization may be useful for downstream computations [132,133]. In particular, these direction-selective neurons may be organized to accurately encode direction information in the presence of noise [134,135]. …”