Vision Science ePosters

The accuracy of behavior is constrained by the encoding of sensory information. However little is known about how reliable encoding emerges as animals develop during early life. A better understanding of these developmental processes has the potential to aid in the design of artificial learning systems, and help…

The fact that the eyes are constantly in motion, even during ‘fixation’, implies that retinal ganglion cells' spike times carry information about the visual scene even when the scene is static. Moreover, this motion implies that fine details of the visual scene could not be decoded from pure spatial retinal…

Spatial navigation relies on external cues, such as visual objects, to anchor internal representations of space. In rodents, moving a visual landmark results in a corresponding shift in the tuning of head direction (HD) cells1. However, little is known about where visual objects are encoded in the mouse brain2 or how…

Animals must infer the three-dimensional structure of the surrounding world from two-dimensional images on their retinas. For instance, animals use visual cues like motion parallax and binocular disparity to judge distances to objects as they navigate their environment. Although studies in several vision models have…

Many animals use visual motion cues to track and pursue small, fast-moving prey or to track conspecifics. The pursuit of small visual targets is a hard problem and understanding the underlying neural circuits will inform similar studies in other animals and open avenues for bio-inspired robotics. In dragonflies and…

Sensory systems continuously adapt their responses based on the frequency of stimuli they encounter. Our goal is to develop a clear understanding of how populations of cortical neurons adapt to varying sensory environments. Recent experiments in the mouse primary visual cortex (V1) have shown a remarkable finding: the…

Animals rely on sensory inputs to navigate complex, dynamic environments. Understanding how the brain integrates these inputs to guide behavior remains a central question in neuroscience. Training AI and animals on the same task offers a unique opportunity to uncover both similarities and critical differences in the…

Traveling waves (TWs) in the brain are a form of neural synchrony. They have been observed across various regions, including the visual cortex and hippocampus, during both spontaneous and task-related activities. These waves are believed to play crucial roles in cognitive processes such as sensory perception and…

In systems neuroscience, animals are often trained until they saturate the psychometric function, producing stereotypical behaviors. This may obscure important system properties, such as generalization and neural correlates. In this study, we trained and tested mice on visual texture classification problems, where…

Higher brain regions are thought to use the computational advantages of sitting closer to a critical point to support more complex cognitive functions. Finding evidence for this hypothesis from neural data is challenging, requiring robust and accurate measures of the distance to criticality (DTC). Many existing…

Human perception is significantly influenced by sensory context. A classic demonstration is the tilt illusion, in which the perceived orientation of a center stimulus is altered by the orientation of a surround (Gibson \& Radner 1937). Previous research on the tilt illusion has primarily focused on how surround…

Sensory information is first processed by various thalamic nuclei before reaching the pallium in amniotes, where it is used for higher-order computations such as integrating diverse sensory information that can be utilized to form associations. In teleost fish, the dorsal thalamic nuclei, believed to be analogous to…

How the activity of sensory neurons supports perceptual decisions remains one of the central questions of systems neuroscience. Two primary frameworks guide the field’s thinking on this question. One framework, guided by ideas of information maximization, redundancy reduction, and efficient coding, focuses on the…

The relationship between morphology, connectivity, and function is a central challenge in neuroscience. The possibility of predicting neuronal function from morphology and connectivity has motivated the field to produce connectomes for increasingly complex organisms. With the recent completion of multiple connectomes…

Introduction: Spontaneous activity in visual cortex is high-dimensional and state-dependent, yet its organizing principles are unclear (Stringer et al. Science 2019; Berkes et al. Science 2011). We combine large-scale imaging, modelling, and theory to ask: 1. Does spontaneous activity share the structure of evoked…

Our ability to see and interact with the world heavily relies on the efficient and precise processing of visual information, consisting of multiple features continuously in flux. Visual perception arises from signals propagating through parallel neuronal pathways wiring the retina to both cortical (primary visual…

Mental imagery refers to our remarkable capacity to generate percepts, emotions, and thoughts in the absence of external stimuli. This ability allows us to generate art, simulate actions and outcomes, remember previous experiences, and imagine new ones. Little is known about the mechanisms that enable mental imagery.…

Visual attention enhances the neural representation of salient stimuli within the visual cortex. Although it is generally thought that this enhancement is driven by glutamatergic feedback from frontal cortical areas, cortically released neuromodulators are also believed to play a major uncharacterized role. Here we…

Practicing a visual task leads to long-lasting perceptual improvements in humans and other animals. However, the generalization of Visual Learning (VL) to unseen conditions varies across different tasks. Particularly, it has been shown that learning ‘easy’ visual tasks leads to better generalization than learning…

When we feel confident in a perceptual decision, that decision is more likely to be correct. How does the brain assess the quality of perceptual decisions? Here, we test two connected hypotheses. First, that perceptual confidence relates to the structure of population activity in the sensory cortex. And second, that…

Predicting sensory input responses to update an internal ``world model'' is a core principle in cognitive learning theories that try to explain mechanisms behind representation learning in the brain [1,2]. Recent machine learning methods have also adopted predictive world modeling for self-supervised representation…

Primates visually identify objects primarily by shape and also by texture. Models of primate vision based on convolutional neural networks (CNNs) achieve high object recognition performance but, unlike primates, emphasize texture over shape. Overcoming this texture bias and making models more brain-like requires data…

Cortical neurons exhibit a high degree of trial-to-trial variability in response to repeated presentations of the same stimulus. We propose that this variability serves a useful computational purpose: allowing the brain to generalize from a small number of examples. To formalize this theory, we consider a Gaussian…

Dwarf cuttlefish, like octopus, are masters of camouflage. To camouflage the cuttlefish brain must solve a hard computational problem; the brain needs to process the visual environment, compute an appropriate pattern, and then orchestrate the expansion and contraction of hundreds of thousands of pigment filled sacs to…