Coding of object location by heterogeneous neural populations with spatially dependent correlations in weakly electric fish

Myriah Haggard and Maurice J Chacron

PLOS Computational Biology, 2023, vol. 19, issue 3, 1-29

Abstract: Understanding how neural populations encode sensory stimuli remains a central problem in neuroscience. Here we performed multi-unit recordings from sensory neural populations in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus in response to stimuli located at different positions along the rostro-caudal axis. Our results reveal that the spatial dependence of correlated activity along receptive fields can help mitigate the deleterious effects that these correlations would otherwise have if they were spatially independent. Moreover, using mathematical modeling, we show that experimentally observed heterogeneities in the receptive fields of neurons help optimize information transmission as to object location. Taken together, our results have important implications for understanding how sensory neurons whose receptive fields display antagonistic center-surround organization encode location. Important similarities between the electrosensory system and other sensory systems suggest that our results will be applicable elsewhere.Author summary: Despite decades of research, the functional roles of neural heterogeneities towards understanding how sensory inputs are encoded by neural populations remains poorly understood. Here we use multi-unit recordings from sensory neural populations using high-density arrays (i.e., Neuropixels probes) and mathematical modeling to understand how a heterogeneous neural population with antagonistic center-surround receptive field organization encodes object location. We recorded the activities of pyramidal cells within the electrosensory lateral line lobe of weakly electric fish in response to a prey-like stimulus. Overall, we found that the receptive fields were highly heterogeneous even when they overlap considerably. We also found that correlated trial-to-trial variabilities of neural responses (i.e., spike-count correlations) varied along the receptive field. Specifically, correlation magnitude was highest towards the receptive field edges and dropped sharply near the midpoint. Using Fisher information analysis, we determined that the spike-count correlations introduced redundancy, but that the deleterious effect was in part mitigated by their spatial dependence. To better understand how heterogeneities within the receptive field, as well as spatially dependent correlations, influence information transmission, we built a mathematical model. Overall, our model reproduced experimental data and predicted that the level of heterogeneity in receptive field position seen experimentally is optimal for information transmission. Given that there are important parallels between the electrosensory system and other senses (e.g., vision), it is likely that our results will be applicable elsewhere.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1010938

DOI: 10.1371/journal.pcbi.1010938

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