Biology subjects

Ajith, S.

Publications and source records attributed to Ajith, S..

3 recordsLinked to original sources

bioRxiv2026

Cortical alpha rhythms predictively track occluded motion trajectories

Objects in the real world frequently move along complex, non-linear trajectories shaped by their environment. As they do, they often pass temporarily out of sight, occluded by the surrounding environment. Yet humans can maintain representations of object position and motion even when objects are no longer visible. Here, we investigate the neural basis of tracking objects undergoing non-linear, environmentally constrained motion during occlusion. We recorded EEG while participants mentally tracked the position of a ball falling through differently curved pipes (Pipe condition). The pipe condition was compared to conditions in which only the ball trajectory was visible (Ball-only condition) or in which the pipe was completely covered by an occluder (Occluder condition). On occasional probe trials, the video was terminated at randomized time points and participants had to indicate the ball's last position using the mouse cursor. Behaviorally, participants systematically reported the ball ahead of its true position, with the strongest forward displacement in the occluded conditions. Neurally, multivariate decoding analysis on the EEG data revealed that alpha-band activity carried direction-specific motion information within and across conditions. Critically, cross-condition decoding revealed shared representations between perceived (Ball-only) and mentally tracked (Occluder) motion with representations in the occluder condition anticipating later representations in the ball-only condition. Together, our behavioral and neural findings provide convergent evidence that during non-linear motion tracking under occlusion, the brain codes object motion ahead of its current position, an 'ahead of time' strategy that may underlie temporal precision when tracking objects in a dynamically changing world.

neuroscience↗

bioRxiv2026

Visual search is constrained by the variability of object-category templates

Real-world visual search is often performed at the category level: we search for shoes or bags without knowing their exact features in advance. This requires categorical search templates that accommodate the inherent variability within the target category. Here, we examine how the variability in search templates across categories constrains visual search performance. We quantify template variability by measuring variability in object drawings from a large online dataset (Experiment 1) and from a controlled lab-based drawing task (Experiment 2) and in turn relate this variability to performance in categorical search. Across both experiments, higher category variability, and thus broader search templates, were associated with slower responses. Moreover, the observers most prioritized object template predicted their search performance better than other observers templates, indicating that individual differences in template variability shape visual search. Together, our findings demonstrate that naturalistic visual search is governed by structured variability across both object categories and observers.

neuroscience↗

bioRxiv2025

Object representations drive emotion schemas across a large and diverse set of daily-life scenes

The rapid emotional evaluation of objects and events is essential in daily life. While visual scenes reliably evoke emotions, it remains unclear whether emotion schemas evoked by daily-life scenes depend on object processing systems or are extracted independently. To explore this, we collected emotion ratings for 4913 daily-life scenes from 300 participants, and predicted these ratings from representations in deep neural networks and fMRI activity patterns in visual cortex. AlexNet, an object-based model, outperformed EmoNet, an emotion-based model, in predicting emotion ratings for everyday scenes, while EmoNet excelled for explicitly evocative stimuli. Emotion information was processed hierarchically within the object recognition system, consistent with the visual cortexs organization. Activity patterns in the lateral occipital complex (LOC), an object-selective region, reliably predicted emotion ratings and outperformed other visual regions. These findings suggest that emotion processing in everyday scenes follows visual object recognition, with additional mechanisms engaged when object content is uninformative.

neuroscience↗