Exposure to a real-life adversity, such as the COVID-19 pandemic, reduced the optimism bias typically observed in belief updating about future life events, shifting behavior toward more rational, Bayesian-like learning.
Gemechu Bekele Tolossa, Aidan M Schneider ... Keith B Hengen
Machine learning analysis reveals that individual neurons throughout the brain embed information about their anatomical location in their spike trains, a feature that generalizes across animals, experimental conditions, and laboratories.
Studying a decision in archerfish reveals an impressive potential of learning capacities and cognitive aspects that are unexpected for decisions made at reflex speed.
Anne C Trutti, Zsuzsika Sjoerds ... Birte U Forstmann
Neuroimaging evidence enhances understanding of the subcortex’s role in the neural mechanisms of working memory updating, providing new insights into midbrain function.
Reversible cerebellar disruption in non-human primates reveals an acute muscle torque deficit and an adaptive slowing strategy to manage limb dynamics, underscoring distinct primary, and compensatory mechanisms underlying motor impairment.
Self-supervised deep learning models can accurately perform 3D segmentation of cell nuclei in complex biological tissues, enabling scalable analysis in settings with limited or no ground truth annotations.
Jonas Karolis Degutis, Simon Weber ... John-Dylan Haynes
Dynamic shifts in neural coding combined with stable population subspaces enable visual areas to concurrently represent sensory inputs and working memory without mutual interference.
