Biology subjects

Saldanha, P.

Publications and source records attributed to Saldanha, P..

3 recordsLinked to original sources

bioRxiv2026

Active pursuit gates egocentric coding in Retrosplenial Cortex

Spatial navigation is commonly studied in static environments, but adaptive behavior frequently hinges on tracking moving goals in real time. Active pursuit exemplifies this challenge: it is an inherently egocentric spatial behavior requiring continuous localization of a moving target, yet the neural coding schemes supporting it remain poorly understood. We therefore performed Neuropixels recordings in the retrosplenial cortex (RSC), a hub for egocentric-to-allocentric reference frame transformations, during naturalistic bait-chasing. We identified head-centered target-encoding neurons that were functionally distinct from cells encoding environmental boundaries or static objects. Whereas egocentric boundary encoding was task-invariant, target-coding cells were specific to chasing and exhibited task-dependent retuning, characterized by enhanced ego-centric representation and reduced allocentric head-direction signaling during pursuit. Together, these findings demonstrate that classical egocentric and allocentric codes coexist with novel target tuning in the RSC, where target-coding neurons dynamically reweight their reference frames according to behavioral demands during pursuit.

neuroscience↗

bioRxiv2025

Egocentric body-axis-related and allocentric clover-like tuning of object vector representations supports human spatial cognition

Vector-based spatial coding has been demonstrated in rodents, yet its neural basis in humans and its contribution to navigation remain poorly understood. Using a novel spatial updating task, we show that egocentric directional signals peak when objects are located behind the navigator, while distance signals emerge only when objects are out of view, suggesting a mnemonic role for vision-independent spatial mapping. Allocentric signals form a clover-shaped, four-axis pattern aligned to visual features, with improved navigation accuracy along its axes. Parallel rodent recordings further show the clover pattern arises from averaged activity of allocentric vectorial neurons, suggesting conserved cross-species mechanisms. Together, our findings uncover vector-based representations in the human brain, potentially serving as a neural reference axis to anchor objects to internal maps and support navigation.

neuroscience↗

bioRxiv2021

TRACER: A toolkit to register and visualize anatomical coordinates in the rat brain

Recording technologies for rodents have seen huge advances in the last decade, allowing users to sample thousands of neurons simultaneously from multiple brain regions. This has prompted the need for digital tool kits to aid in curating anatomical data, however, existing tools either provide limited functionality or require users to be proficient in coding to use them. To address this we created HERBS, a comprehensive new tool for rodent users that offers a broad range of functionalities through a user-friendly graphical user interface. Prior to experiments, HERBS can be used to plan coordinates for implanting electrodes, targeting viral injections or tracers. After experiments, users can register recording electrode locations (e.g. Neuropixels, tetrodes), viral expression or other anatomical features, and visualize the results in 2D or 3D. Additionally, HERBS can delineate expression from multiple injections across tissue sections and obtain individual cell counts. Regional delineations in HERBS are based either on annotated 3D volumes from the Waxholm Space Atlas of the Sprague Dawley Rat Brain or the Allen Mouse Brain Atlas. HERBS allows users to scroll through the digital brain atlases and provides custom-angle slice cuts through the volumes, and supports free-transformation of tissue sections to atlas slices. Furthermore, HERBS allows users to reconstruct a 3D brain mesh with tissue from individual animals. HERBS is a multi-platform open-source Python package that is available on PyPI and GitHub.

neuroscience↗