Biology subjects

Tsubo, Y.

Publications and source records attributed to Tsubo, Y..

3 recordsLinked to original sources

bioRxiv2024

Formation of brain-wide neural geometry during visual item recognition in monkeys

Neural dynamics assumes to reflect computations that relay and transform information in the brain. Previous studies have identified the neural population dynamics in many individual brain regions as a trajectory geometry, preserving a manifest of computational motifs. However, whether these populations share particular geometric patterns across brain-wide neural populations remains unclear. Here, by mapping neural dynamics widely across temporal/frontal/limbic regions in the cortical and subcortical structures of monkeys, we show that 10 neural populations, including 2,500 neurons, propagate visual item information in a stochastic manner. We found that visual inputs predominantly evoked rotational dynamics in the higher-order visual area, TE and its downstream striatum tail, while curvy/straight dynamics appeared frequently downstream in the orbitofrontal/hippocampal network. These geometric changes were not deterministic but rather stochastic according to their respective emergence rates. Our meta-analysis results indicated that visual information propagates as a heterogeneous mixture of stochastic neural population signals in the brain.

neuroscience↗

bioRxiv2023

Non-differentiable activity in the brain

Spike rasters of multiple neurons show vertical stripes, indicating that neurons exhibit synchronous activity in the brain. We seek to determine whether these coherent dynamics are caused by smooth brainwave activity or by something else. By analyzing biological data, we find that their cross-correlograms exhibit not only slow undulation but also a cusp at the origin, in addition to possible signs of monosynaptic connectivity. Here we show that undulation emerges if neurons are subject to smooth brainwave oscillations while a cusp results from non-differentiable fluctuations. While modern analysis methods have achieved good connectivity estimation by adapting the models to slow undulation, they still make false inferences due to the cusp. We devise a new analysis method that may solve both problems. We also demonstrate that oscillations and non-differentiable fluctuations may emerge in simulations of large-scale neural networks.

neuroscience↗

bioRxiv2021

A neuronal prospect theory model in the brain reward circuitry

Prospect theory, arguably the most prominent theory of choice, is an obvious candidate for neural valuation models. How the activity of individual neurons, a possible computational unit, reflects prospect theory remains unknown. Here, we show with theoretical accuracy equivalent to that of human neuroimaging studies that single-neuron activity in four core reward-related cortical and subcortical regions represents the subjective valuation of risky gambles in monkeys. The activity of individual neurons in monkeys passively viewing a lottery reflects the desirability of probabilistic rewards, parameterized as a multiplicative combination of a utility and probability weighting functions in the prospect theory framework. The diverse patterns of valuation signals were not localized but distributed throughout most parts of the reward circuitry. A network model aggregating these signals reliably reconstructed risk preferences and subjective probability perceptions revealed by the animals choices. Thus, distributed neural coding explains the computation of subjective valuations under risk.

neuroscience↗