In a neural integrator, the variability and topographical organization of neuronal firing-rate persistence can provide information about the circuit's functional architecture. We used optical recording to measure the time constant of decay of persistent firing (persistence time) across a population of neurons comprising the larval zebrafish oculomotor velocity-to-position neural integrator. We found extensive persistence time variation (tenfold; coefficients of variation = 0.58–1.20) across cells in individual larvae. We also found that the similarity in firing between two neurons decreased as the distance between them increased and that a gradient in persistence time was mapped along the rostrocaudal and dorsoventral axes. This topography is consistent with the emergence of persistence time heterogeneity from a circuit architecture in which nearby neurons are more strongly interconnected than distant ones. Integrator circuit models characterized by multiple dimensions of slow firing-rate dynamics can account for our results.
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We thank D. Dombeck for technical advice, F. Collman for motion-correction software, and M. Goldman, A. Kinkhabwala and P. Bradley for helpful discussions. This work was supported by a National Science Foundation predoctoral fellowship (A.M.), a US National Institutes of Health Training grant (EY007138-16, K.D.), a Krevans fellowship (A.B.A.), a Burroughs Wellcome Career Award at the Scientific Interface, a Searle Scholar award, the Frueauff Foundation (E.A.), the Human Frontier Science Program (H.B.), and US National Institutes of Health grants (R01 MH060651 to D.W.T. and R01 NS053358 to H.B.).
The authors declare no competing financial interests.
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Miri, A., Daie, K., Arrenberg, A. et al. Spatial gradients and multidimensional dynamics in a neural integrator circuit. Nat Neurosci 14, 1150–1159 (2011). https://doi.org/10.1038/nn.2888
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