P156 Population decoding of visual motion direction in V1 marmoset monkey : effects of uncertainty
Alexandre C. Lainé*1, Sophie Denève1, Nicholas J. Priebe2, Guillaume S. Masson1, Laurent U. Perrinet1
1Institut de Neurosciences de la Timone, UMR 7289, CNRS - Aix-Marseille University, Marseille, France. 2Section of Neurobiology, School of Biological Sciences, University of Texas at Austin, Austin, TX, USA.
*Email: alexandre.laine@univ-amu.fr Introduction
Studying the internal representation of information in the primary visual cortex (V1) is crucial to understand how we perceive the external world. Research on 2D motion direction in non-human primates [1,2,3] in particular when displaying naturalistic stimuli like MotionClouds [4] reveals substantial diversity and multiple mechanisms within the neuronal population [5]. This project aims to examine how a large population of V1 neurons encodes stimulus direction by explicitly titrating the precision in the orientation and spatial frequency domains.
Methods Activity of several hundreds of neurons was recorded using Neuropixel 2.0 technology [6] in area V1 of an anesthetized marmoset monkey during which MotionClouds were presented for eight directions and two precision levels. We use a decoding method to analyze the representation of motion direction in the marmoset V1, focusing on the effects of uncertainty on the population code. The decoding method optimizes the weights of a logistic regression to achieve optimal decoding accuracy on a training set. Training can be conducted (1) on a broad time window, (2) by applying temporal generalization [7], or (3) after reducing dimensionality with dPCA [8]. Results After training on broad windows, analysis of the optimised weights revealed two types of population representations: transient and sustained. These representations differ in their distributions across cortical layers, confirming earlier results obtained in another species [5], and are modulated by the level of orientation precision. The accuracy measured on the test set revealed first that a broad spatial frequency distribution leads to a better decoding performance, and second that the precision of the orientation is a critical factor in the representation of motion direction. Indeed, a high precision in orientation leads to the aperture problem, and thus to an ambiguity in the representation of motion direction. Temporal generalization confirm a stable representation. Projection of neuronal activity using dPCA onto 10 components without affect accuracy demonstrate that the information may be represented in a low-dimensional manifold.
Discussion In summary, this decoding method clarifies how directional information is represented and modulated by precision in marmoset V1. The coexistence of transient and sustained representations indicates distinct functional roles across cortical layers. Temporal generalization confirms that the neuronal population maintains a stable encoding of direction. Reducing dimensionality while preserving precision implies that a small set of components can capture the essential features of neuronal activity, enabling the exploration of various projection methods to optimize decoding. Moreover, the results suggest that orientation precision could be a major factor in shaping the interplay between orientation and direction.
Acknowledgements This work was supported by ANR-NSF CRCNS grant “PrioSens” N° ANR-20-NEUC-0002 attributed to G.S.M, N.J.P. and L.U.P. and by a doctoral grant from the French Ministry of Higher Education and Research, awarded by the Doctoral School 62 of Aix-Marseille University to A.L. References[1] https://doi.org/10.1113/jphysiol.1959.sp006308 [2] https://doi.org/10.1113/jphysiol.1968.sp008455 [3] https://doi.org/10.1523/JNEUROSCI.1335-12.2012 [4] https://doi.org/10.1152/jn.00737.2011 [5] https://doi.org/10.1038/s42003-023-05042-3 [6] https://doi.org/10.1126/science.abf4588 [7] https://doi.org/10.1016/j.tics.2014.01.002 [8] https://doi.org/10.7554/eLife.10989
