Biology subjects

Segev, R.

Publications and source records attributed to Segev, R..

10 recordsLinked to original sources

bioRxiv2026

Big-team science reveals that patterns of inhibitory control variation in teleost fishes differ from those in mammals and birds

Understanding the evolution of cognition is fundamental to understanding the origins and nature of our own cognitive abilities, with cross-species comparisons providing a cornerstone of this endeavor. Yet, comparative cognition so far has largely focused on endothermic vertebrates, particularly mammals and birds, while ectotherms--representing a substantial proportion of vertebrate diversity--remain relatively understudied. Moreover, variation in experimental methods makes existing data difficult to compare across species. Big-team science offers a way to overcome these limitations by enabling standardized cognitive testing across broad taxonomic scales. Here, we apply this approach to fishes, using inhibitory control as a proof of concept for standardized comparative testing in 444 individuals across 22 teleost species spanning 19 genera. We demonstrate that standardized cognitive testing across such diversity is feasible, while also revealing substantial heterogeneity in the sample. Performance varied markedly among species, but, strikingly, showed only a weak phylogenetic signal, contrasting with patterns previously reported in mammals and birds. In addition, we detected great within-species variation, including differences across research groups, suggesting that performance may reflect not only species-level evolutionary history but also ontogenetic experience and the capacity to adjust decision rules to local conditions. Together, our findings highlight the importance of both evolutionary and environmental sources of cognitive variation and demonstrate that extending standardized comparative approaches beyond traditionally studied endotherms can reveal a more dynamic and complex picture of cognitive evolution across the vertebrate lineage.

animal behavior and cognition↗

bioRxiv2026

Decision-Making Dynamics Mask the True Psychophysical Capacity of Archerfish

To quantify animals perceptual capabilities, studies typically assess behavioral accuracy, the proportion of correct choices accumulated over trials on a given task. However, recent works on humans and rodents have shown that task decisions exhibit dynamic shifts from trial to trial, thus casting doubt on the reliability of behavioral accuracy as a true measure of capabilities. Here, these decision-making dynamics were tested on archerfish, an animal lacking a fully developed cortex, whose behavioral decisions are easy to read out. We conducted a series of experiments involving a two-alternative choice task where a target and a non-target shape were randomly placed in two possible positions. Fitting dynamic generalized linear models to each fishs binary choice data revealed that target position strongly affected accuracy and that this effect fluctuated over a timescale of [~]100 trials. The archerfish often repeated their choices regardless of the reward: they frequently selected one target or non-target shape on numerous consecutive trials, which is suggestive of high object recognition capacity. Importantly, the findings indicated that similar latent decision variables underlying mammalian decision-making, such as choice history, were also operational in the archerfish. Then, to investigate behavioral accuracy in more detail, we introduced unrewarded probe trials. Unlike the findings reported in rodents, archerfish performance remained stable during these unrewarded trials. Finally, a decision-making paradigm with stimuli at multiple locations yielded results that were consistent with the simpler task variant. More generally, these findings suggest that an animals decision-making dynamics can mask its true perceptual capabilities when performing an object recognition task, with broad implications for the ways in which behavioral assays are designed and animal performance is interpreted across taxa.

neuroscience↗

bioRxiv2026

Limits of optimal decoding under synaptic coarse-tuning

Sensory information propagates through successive processing stages in the brain, where synaptic weight patterns between stations determine how downstream neurons decode information from upstream populations. Although optimized synaptic connectivity can enhance information transmission, it requires precise weight tuning. Recent evidence depicting substantial synaptic volatility raises two fundamental questions: How does coarse-tuning of synaptic connectivity affect information transmission? What strategies could the nervous system employ to maintain reliable communication despite synaptic fluctuations? We addressed these questions by analyzing the signal-to-noise ratio (SNR) for binary stimulus discrimination under two decoding schemes: a naive population average and an optimized linear decoder. For the naive decoder, we found that SNR remains largely insensitive to synaptic imprecision, since performance is already limited by correlated noise in neuronal responses. For the optimal decoder, we identified three distinct regimes, that is, weak, moderate and strong coarse-tuning. Under weak coarse-tuning, SNR2 scales linearly with population size N. Under moderate coarse-tuning, scaling becomes sublinear. Strikingly, under strong coarse-tuning, the regime most consistent with observed neuronal heterogeneity, SNR saturates and can not be improved by recruiting larger populations. This limitation persists even when incorporating feedforward or recurrent network architectures. These findings suggest that in the biologically relevant regime of strong coarse-tuning, naive and optimal decoders can achieve qualitatively similar performance. The analysis shows that effective readout under synaptic volatility is constrained to an invariant low-dimensional manifold aligned with the naive decoder, potentially pointing to a fundamental principle for robust neural computation in the face of ongoing synaptic remodeling.

neuroscience↗

bioRxiv2023

The archerfish can use motor adaptation to correct for light refraction at the water air interface

The archerfish is unique in its ability to hunt by shooting a jet of water from its mouth that hits insects situated above the waters surface. To aim accurately, the fish needs to overcome physical factors including changes in light refraction at the air-water interface. Nevertheless, archerfish can still hit the target with a high success rate under changing conditions. One possible explanation for this extraordinary ability is that it is learned by trial and error through a motor adaptation process. We tested this possibility by characterizing the ability of the archerfish to adapt to perturbations in the environment to make appropriate adjustments to its shots. We introduced a perturbing airflow above the water tank of archerfish trained to shoot at a target. For each trial shot, we measured the error; i.e., the distance between the center of the target and the center of the water jet produced by the fish. Immediately after the airflow perturbation, there was an increase in shot error. Then, over the course of several trials, the error was reduced and eventually plateaued. After the removal of the perturbation, there was an aftereffect, where the error was in the opposite direction but washed out after several trials. These results indicate that archerfish can adapt to the airflow perturbation. Testing the fish with two opposite airflow directions indicated that adaptation took place within an egocentric frame of reference. These results thus suggest that the archerfish is capable of motor adaptation, as indicated by data showing that the fish produced motor commands that anticipated the perturbation.

animal behavior and cognition↗

bioRxiv2023

Winner-take-all fails to account for pop out accuracy

Visual search involves active scanning of the environment to locate objects of interest against a background of irrelevant distractors. One widely accepted theory posits that pop out visual search is computed by a winner-take-all (WTA) competition between contextually modulated cells that form a saliency map. However, previous studies have shown that the ability of WTA mechanisms to accumulate information from large populations of neurons is limited, thus raising the question of whether WTA can underlie pop out visual search. To address this question, we conducted a modeling study to investigate how accurately the WTA mechanism can detect the deviant stimulus in a pop out task. We analyzed two architectures of WTA networks: single-best-cell WTA, where the decision is made based on a single winning cell, and a generalized population-based WTA, where the decision is based on the winning population of similarly tuned cells. Our results show that WTA performance cannot account for the high accuracy found in behavioral experiments. On the one hand, inherent neuronal heterogeneity prevents the single-best-cell WTA from accumulating information even from large populations. On the other, the accuracy of the generalized population-based WTA algorithm is negatively affected by the widely reported noise correlations. These findings suggest the need for revisiting current understandings of the underlying mechanism of pop out visual search put forward to account for observed behavior.

neuroscience↗

bioRxiv2023

A telencephalon cell type atlas for goldfish reveals diversity in the evolution of spatial structure and cell types

Teleost fish form the largest group of vertebrates, making them critically important for the study on the mechanisms of brain evolution. In fact, teleosts show a tremendous variety of adaptive behaviors similar to birds and mammals, however, the neural basis mediating these behaviors remains elusive. We performed a systematic comparative survey of the goldfish telencephalon; the seat of plastic behavior, learning and memory in vertebrates. We delineated and mapped goldfish telencephalon cell types using single-cell RNA-seq and spatial transcriptomics, resulting in de novo molecular neuroanatomy parcellation. Glial cells were highly conserved across 450 million years of evolution separating mouse and goldfish, while neurons showed diversity and modularity in gene expression. Specifically, somatostatin (SST) interneurons, famously interspersed in the mammalian isocortex for local inhibitory input, were curiously aggregated in a single goldfish telencephalon nucleus, but molecularly conserved. Cerebral nuclei including the striatum, a hub for motivated behavior in amniotes, had molecularly and spatially conserved goldfish homologues. We further suggest different elements of a hippocampal formation across the goldfish pallium. Together, our atlas provides new insights to organization and evolution of vertebrate forebrains and may serve as a resource for the functional study underlying cognition in teleost fish. TeaserDetailed mapping of goldfish forebrain cells unwraps how 450 million years of evolution may have impacted brain function

neuroscience↗

bioRxiv2022

Figure-ground segmentation based on motion in the archerfish

Object detection and recognition is a complex computational task that is thought to rely critically on the ability to segment an object from the background. Mammals exhibit varying figure-ground segmentation capabilities, ranging from primates that can perform well on figure-ground segmentation tasks to rodents that perform poorly. To explore figure-ground segmentation capabilities in teleost fish, we studied how the archerfish, an expert visual hunter, performs figure-ground segmentation. We trained archerfish to discriminate foreground objects from the background, where the figures were defined by motion as well as by discontinuities in intensity and texture. Specifically, the figures were defined by grating, naturalistic texture, and random noise moving in counterphase with the background. The archerfish performed the task well and could distinguish between all three types of figures and grounds. Their performance was comparable to that of primates and outperformed rodents. These findings suggest the existence of a complex visual process in the archerfish visual system that enables the delineation of figures as distinct from backgrounds, and provide insights into object recognition in this animal.

neuroscience↗

bioRxiv2022

Axial encoding schematics of neural representations of 3D space in freely navigating goldfish

Navigation is one of the most fundamental cognitive skills for the survival of fish, the largest vertebrate class, and almost all other animal classes. A critical component of the neural basis of navigation is the encoding of space in the activity of single neurons. To study this basic cognitive component in fish, we recorded the activity of single neurons in the central area of the goldfish telencephalon while the fish were freely navigating in a 3D water tank. We found neurons with firing patterns that gradually increased or decreased along spatial axes distributed in all directions. Some of these cells exhibited beta rhythm oscillations. This type of axial coding for spatial representation in the brains of fish is unique among space encoding cells in vertebrates and provides insights into spatial cognition in this lineage.

neuroscience↗

bioRxiv2021

Recognition of natural objects in the archerfish

Recognition of individual objects and their categorization is a complex computational task. Nevertheless, visual systems are able to perform this task in a rapid and accurate manner. Humans and other animals can efficiently recognize objects despite countless variations in their projection on the retina due to different viewing angles, distance, illumination conditions, and other parameters. Numerous studies conducted in mammals have associated the recognition process with cortical activity. Although the ability to recognize objects is not limited to mammals and has been well-documented in other vertebrates that lack a cortex, the mechanism remains elusive. To address this gap, we explored object recognition in the archerfish, which lack a fully developed cortex. Archerfish hunt by shooting a jet of water at aerial targets. We leveraged this unique skill to monitor visual behavior in archerfish by presenting fish with a set of images on a computer screen above the water tank and observing the behavioral response. This methodology served to characterize the ability of the archerfish to perform ecologically relevant recognition of natural objects. We found that archerfish can recognize an individual object presented under different conditions and that they can also categorize novel objects into known categories. Manipulating features of these objects revealed that the fish were more sensitive to object contours than texture and that a small number of features was sufficient for categorization. Our findings suggest the existence of a complex visual process in the archerfish visual system that enables object recognition and categorization.

animal behavior and cognition↗

bioRxiv2018

Representation of Border, Velocity and Speed in the Goldfish Brain

Like most animals, the survival of fish depends crucially on navigation in space. This capacity has been documented in numerous behavioral studies that have revealed navigation strategies and the sensory modalities used for navigation. However, virtually nothing is known about how freely swimming fish represent space and locomotion in the brain to enable successful navigation. Using a novel wireless neural recording system, we measured the activity of single neurons in the goldfish lateral pallium, a brain region known to be involved in spatial memory and navigation, while the fish swam freely in a two-dimensional water tank. Four cell types were identified: border cells, head direction cells, speed cells and conjunction head direction with speed. Border cells were active when the fish was near the boundary of the environment. Head direction cells were shown to encode head direction. Speed cells only encoded the absolute speed independent of direction suggestive of an odometry signal. Finally, the conjunction of head direction with speed cells represented the velocity of the fish. This study thus sheds light on how information related to navigation is represented in the brain of swimming fish, and addresses the fundamental question of the neural basis of navigation in this diverse group of vertebrates. The similarities between our observations in fish and earlier findings in mammals may indicate that the networks controlling navigation in vertebrate originate from an ancient circuit common across vertebrates.\n\nSummaryNavigation is a fundamental behavioral capacity facilitating survival in many animal species. Fish is one lineage where navigation has been explored behaviorally, but it remains unclear how freely swimming fish represent space and locomotion in the brain. This is a key open question in our understanding of navigation in fish and more generally in understanding the evolutionary origin of the brains navigation system. To address this issue, we recorded neuronal signals from the brain of freely swimming goldfish and successfully identified representations of border and swimming kinematics in a brain region known to be associated with navigation. Our findings thus provide a glimpse into the building blocks of the neural representation underlying fish navigation. The similarity of the representation in fish with that of mammals may be key evidence supporting a preserved ancient mechanism across brain evolution.

neuroscience↗