Biology subjects

Serrano-Pedraza, I.

Publications and source records attributed to Serrano-Pedraza, I..

5 recordsLinked to original sources

bioRxiv2026

A canonical neural circuit for motion direction estimation

Abundant experimental data support the view that motion detection is a canonical neural operation, common to a wide variety of species and different stages in the visual stream. However, existing motion models lack this generality, as their predictive power tends to be restricted to some specific visual phenomena, brain regions, or animal taxa. Here, we introduce a neural circuit model that only uses cells selective to cardinal directions, with elements that can be interpreted as emulating some dendritic processes, and we show how it is able to predict a wide range of visual motion data, from basic properties to hitherto unexplained phenomena, surpassing state-of-the-art models implemented as deep neural networks with millions of parameters. The direction-selective cells that our model relies on are present in the visual systems of many classes of animals, from insects to primates, and in visual pathway structures going from the retina to the cortex, suggesting that the proposed model could serve as a canonical neural circuit for estimating motion direction.

neuroscience↗

bioRxiv2024

Suppression of optokinesis in the reafferent direction during pursuit eye movements

When tracking with the eyes an object moving against a textured background, the background retinal image moves in the opposite direction to the smooth pursuit eye movement. Optokinetic responses, such as optokinetic nystagmus (OKN) or ocular tracking, to this reafferent signal must be suppressed to sustain pursuit of the object-of-interest. We varied the contrast of a brief background motion to tell apart two plausible accounts of the suppression of optokinesis during pursuit; a visuomotor gain modulation account, which predicts that ocular tracking of background motion is suppressed in the same proportion at irrespective of contrast, and a sensory attenuation account, which predicts that larger contrasts are needed to elicit the same response. Unexpectedly, neither account fits ocular tracking in the reafferent signal direction. The combination of contrast-dependent gating, with maximal suppression observed with higher contrasts, and visuomotor gain modulation, provides a good fit for most observers data. Contrast-dependent gating promotes visuomotor stability in response to most salient signals, as a likely adaptation to the statistics of the environment. Significance statementFor humans to be able to track small moving objects, there is a need for a mechanism to cancel optokinesis, that is reflexive eye movements towards prevalent visual motion. We show that this cancellation is not a simple "volume-control" reduction of responses to motion signals, as expected. This suppression also involves contrast-dependent gating, meaning that most salient signals are not allowed to modify the ongoing movement. This additional component could have arisen from an adaptation to image statistics of motion signals prevalent in natural environments.

neuroscience↗

bioRxiv2024

Overcoming the limitations of motion sensor models by considering dendritic computations

The estimation of motion is a fundamental process for any sighted animal. Computational models for motion sensors have a long and successful history but they still suffer from fundamental shortcomings, as they disagree with physiological evidence and each model is dedicated to a specific type of motion, which is controversial from a biological standpoint. In this work we propose a new approach for modeling motion sensors that considers dendritic computations, a key aspect for predicting single-neuron responses that had previously been absent from motion models. We show how, by taking into account the dynamic and input-dependent nature of dendritic nonlinearities, our motion sensor model is able to overcome the fundamental limitations of standard approaches.

neuroscience↗

bioRxiv2017

Contrast Thresholds Reveal Different Visual Masking Functions In Humans And Praying Mantises

Recently, we showed a novel property of the Hassenstein-Reichardt detector: namely, that insect motion detection can be masked by \"invisible\" noise, i.e. visual noise presented at spatial frequencies to which the animals do not respond when presented as a signal. While this study compared the effect of noise on human and insect motion perception, it used different ways of quantifying masking in two species. This was because the human studies measured contrast thresholds, which were too time-consuming to acquire in the insect given the large number of stimulus parameters examined. Here, we run longer experiments in which we obtained contrast thresholds at just two signal and two noise frequencies. We examine the increase in threshold produced by noise at either the same frequency as the signal, or a different frequency. We do this in both humans and praying mantises (Sphodromantis lineola), enabling us to compare these species directly in the same paradigm. Our results confirm our earlier finding: whereas in humans, visual noise masks much more effectively when presented at the signal spatial frequency, in insects, noise is roughly equivalently effective whether presented at the same frequency or a lower frequency. In both species, visual noise presented at a higher spatial frequency is a less effective mask.\n\nSummary StatementWe here show that despite having similar motion detection systems, insects and humans differ in the effect of low and high spatial frequency noise on their contrast thresholds.

neuroscience↗

bioRxiv2017

When invisible noise obscures the signal: the consequences of nonlinearity in motion detection

1The motion energy model is the standard account of motion detection in animals from beetles to humans. Despite this common basis, we show here that a difference in the early stages of visual processing between mammals and insects leads this model to make radically different behavioural predictions. In insects, early filtering is spatially lowpass, which makes the surprising prediction that motion detection can be impaired by \"invisible\" noise, i.e. noise at a spatial frequency that elicits no response when presented on its own as a signal. We confirm this prediction using the optomotor response of praying mantis Sphodromantis lineola. This does not occur in mammals, where spatially bandpass early filtering means that linear systems techniques, such as deriving channel sensitivity from masking functions, remain approximately valid. Counter-intuitive effects such as masking by invisible noise may occur in neural circuits wherever a nonlinearity is followed by a difference operation.

neuroscience↗