Biology subjects

Murlidaran, S.

Publications and source records attributed to Murlidaran, S..

3 recordsLinked to original sources

bioRxiv2025

Distinct Roles of Central and Peripheral Vision in Rapid Scene Understanding

Central and peripheral vision loss, caused by conditions such as age-related macular degeneration and retinitis pigmentosa, disrupt visual processing in distinct ways, yet their impact on natural scene perception remains poorly understood. Here, we used a real-time, gaze-contingent simulation to examine how central vision loss and peripheral vision loss alter eye movements and scene understanding. Sighted participants (n = 32, 5 males) viewed 120 natural scenes under one- or three-saccade constraints and described each scene; description quality was quantified via semantic similarity to ground-truth responses. Peripheral vision loss observers produced significantly less informative descriptions than both central vision loss and control participants, particularly for social interaction scenes, suggesting that peripheral vision is critical for rapid extraction of scene semantics. In contrast, central vision loss primarily disrupted oculomotor behavior, including increased saccade amplitudes, delayed saccade initiation, and reduced inter-subject fixation consistency. Description quality was not predicted by fixation similarity to controls, but by fixations to annotated humans and critical objects, underscoring the role of semantically informative sampling. These results reveal a dissociation between perceptual and oculomotor consequences of vision loss and highlight the neural importance of peripheral input for natural scene understanding. Significance statementUnderstanding how vision loss affects real-world perception requires disentangling the distinct contributions of central and peripheral vision. Using gaze-contingent simulations of biologically plausible scotomas, we show that peripheral vision loss degrades scene understanding more severely than central loss, particularly for socially meaningful content. In contrast, central vision loss led to more pronounced changes in eye movement planning, including larger and delayed saccades. These findings reveal a dissociation between perceptual and oculomotor consequences of visual field loss, suggesting that peripheral input plays a critical role in rapid semantic processing of natural scenes. Our results underscore the importance of evaluating functional vision using ecologically valid tasks and could inform future strategies in low vision rehabilitation.

neuroscience↗

bioRxiv2025

A Deep Learning Framework for Predicting Functional Visual Performance in Bionic Eye Users

AO_SCPLOWBSTRACTC_SCPLOWEfforts to restore vision via neural implants have outpaced the ability to predict what users will perceive, leaving patients and clinicians without reliable tools for surgical planning or device selection. To bridge this critical gap, we introduce a computational virtual patient (CVP) pipeline that integrates anatomically grounded phosphene simulation with task-optimized deep neural networks (DNNs) to forecast patient perceptual capabilities across diverse prosthetic designs and tasks. We evaluate performance across six visual tasks, six electrode configurations, and two artificial vision models, establishing our CVP approach as a scalable pre-implantation method. Several chosen tasks align with the Functional Low-Vision Observer Rated Assessment (FLORA), revealing correspondence between model-predicted difficulty and real-world patient outcomes. Further, the CVP paradigm exhibited strong correspondence with psychophysical data collected from normally sighted subjects viewing phosphene simulations, capturing both overall task difficulty and performance variation across implant configurations. Comparing frozen-feature linear probing with full end-to-end fine-tuning reveals that preserving natural-image representations--rather than adapting them to phosphene-specific statistics--better reproduces human perceptual behavior, consistent with the constrained plasticity of adult visual cortex. The findings position CVP as a scientific tool for probing perception under prosthetic vision, an engine to inform device development, and a clinically relevant framework for pre-surgical forecasting.

neuroscience↗

bioRxiv2019

Competitive dewetting underlies site-specific binding of general anesthetics to GABA(A) receptors

GABA(A) receptors are pentameric ligand-gated ion channels playing a critical role in the modulation of neuronal excitability. These inhibitory receptors, gated by{gamma} -aminobutyric acid (GABA), can be potentiated and even directly activated by intravenous and inhalational anesthetics. Intersubunit cavities in the transmembrane domain have been consistently identified as putative binding sites by numerous experiment and simulation results. Synaptic GABA(A) receptors are predominantly found in a 2:2{beta}:1{gamma} stoichiometry, with four unique inter-subunit interfaces. Experimental and computational results have suggested a perplexing specificity, given that cavity-lining residues are highly conserved, and the functional effects of general anesthetics are only weakly sensitive to most mutations of cavity residues. Here we use Molecular Dynamics simulations and thermodynamically rigorous alchemical free energy perturbation (AFEP) techniques to calculate affinities of the intravenous anesthetic propofol and the inhaled anesthetic sevoflurane to all intersubunit sites in a heteromeric GABA(A) receptor. We find that the best predictor of general anesthetic affinity for the intersubunit cavity sites is water displacement: combinations of anesthetic and binding site that displace more water molecules have higher affinities than those that displace fewer. The amount of water displacement is, in turn, a function of size of the general anesthetic, successful competition of the general anesthetic with water for the few hydrogen bonding partners in the site, and inaccessibility of the site to lipid acyl chains. The latter explains the surprisingly low affinity of GAs for the{gamma} - intersubunit site, which is missing a bulky methionine residue at the cavity entrance and can be occupied by acyl chains in the unbound state. Simulations also identify sevoflurane binding sites in the {beta} subunit centers and in the pore, but predict that these are lower affinity than the intersubunit sites.\n\nSignificanceAfter over a century of research, it is established that general anesthetics interact directly with hydrophobic cavities in proteins. We still do not know why not all small hydrophobic molecules can act as general anesthetics, or why not all hydrophobic cavities bind these molecules. General anesthetics can even select among homologous sites on one critical target, the GABA(A) heteropentamer, although the origins of selectivity are unknown. Here we used rigorous free energy calculations to find that binding affinity correlates with the number of released water molecules, which in turn depends upon the lipid content of the cavity without bound anesthetic. Results suggest a mechanism that reconciles lipid-centered and protein-centered theories, and which can directly inform design of new anesthetics.

biophysics↗