Biology subjects

Pashakhanloo, F.

Publications and source records attributed to Pashakhanloo, F..

3 recordsLinked to original sources

bioRxiv2026

Sparse input representations explain odor discrimination in complex, concentration-varying mixtures

In natural environments, animals must detect behaviorally relevant odors despite variability in both odor mixture composition and stimulus intensity. Although mice can identify salient odors embedded in complex mixtures, how target concentration and background complexity jointly constrain discrimination remains unclear. We trained mice in a two-alternative forced choice task to identify target odors embedded in mixtures containing up to 16 background components. After performance stabilized, we systematically varied target odor concentration. Discrimination accuracy declined with decreasing target concentration but showed little additional dependence on background complexity. Using a biophysically grounded model of olfactory bulb glomerular responses, we show that linear decoding reproduces behavioral performance when intrinsic neural noise dominates over background-driven variability. Manifold capacity analysis revealed that neural representations remain efficiently structured for odor discrimination despite variation in background complexity. These results define a noise-limited regime of olfactory discrimination in which target detectability is primarily constrained by neural sensitivity rather than background interference.

neuroscience↗

bioRxiv2025

Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding

The architecture of early olfactory processing is a striking example of convergent evolution. Typically, a panel of broadly tuned receptors is selectively expressed in sensory neurons (each neuron expressing only one receptor), and each glomerulus receives projections from just one neuron type. Taken together, these three motifs--broad receptors, selective expression, and glomerular convergence--constitute "canonical olfaction," since a number of model organisms including mice and flies exhibit these features. The emergence of this distinctive architecture across evolutionary lineages suggests that it may be optimized for information processing, an idea known as efficient coding. In this work, we show that by maximizing mutual information one layer at a time, efficient coding recovers several features of canonical olfactory processing under realistic biophysical assumptions. We also explore the settings in which noncanonical olfaction may be advantageous. Along the way, we make several predictions relating olfactory circuits to features of receptor families and the olfactory environment.

neuroscience↗

bioRxiv2025

Perception and neural representation of intermittent odor stimuli in mice

Odor cues in nature are sparse and highly fluctuating due to turbulent transport. To investigate how animals perceive these intermittent cues, we developed a behavioral task in which head-restrained mice made binary decisions based on the total number of discrete odor pulses presented stochastically over several seconds. Mice readily learned this task, and their performance was well-described by widely used decision models. Logistic regression of binary choices against the timing of odor pulses within the respiratory cycle revealed that mice placed higher perceptual weight to stimuli arriving during inhalation than exhalation, a phase dependency that strongly correlated with the magnitude of responses in olfactory sensory neurons. The population response of anterior piriform cortex (APCx) neurons to odor pulses was also modulated by respiration phase, although individual neurons displayed varying levels of phase-dependence. Single APCx neurons responded stochastically and transiently to odor pulses, leading to a representation that carries signatures of sensory evidence, but not its accumulation. Our study reveals that mice can integrate intermittent odor signals across dozens of breaths, but respiratory modulation of sensory inputs imposes limits on information acquisition that cortical circuits cannot overcome to improve behavior.

neuroscience↗