Topic: direction selectivity

Detecting the direction of image motion is important for visual navigation, predator avoidance and prey capture, and thus essential for the survival of all animals that have eyes. However, the direction of motion is not explicitly represented at the level of the photoreceptors: it rather needs to be computed by subsequent neural circuits, involving a comparison of the signals from neighboring photoreceptors over time. The exact nature of this process represents a classic example of neural computation and has been a longstanding question in the field. Much progress has been made in recent years

Detecting the direction of image motion is important for visual navigation, predator avoidance and prey capture, and thus essential for the survival of all animals that have eyes. However, the direction of motion is not explicitly represented at the level of the photoreceptors: it rather needs to be computed by subsequent neural circuits. The exact nature of this process represents a classic example of neural computation and has been a longstanding question in the field. Our results obtained in the fruit fly Drosophila demonstrate that the local direction of motion is computed in two parallel

Cells preferentially responding to visual motion in a particular direction are said to be direction-selective, and these were first identified in the primary visual cortex. Since then, direction-selective responses have been observed in the retina of several species, including mice, indicating motion analysis begins at the earliest stage of the visual hierarchy. Yet little is known about how retinal direction selectivity contributes to motion processing in the visual cortex. In this talk, I will present our experimental efforts to narrow this gap in our knowledge. To this end, we used genetic

The upper visual layers of the mouse superior colliculus (SC) exhibit an orientation preference map (OPM) with a retinotopy-based concentric pattern (Ahmadlou and Heimel, 2015; Feinberg and Meister, 2015; but see Chen et al., 2020). The underlying developmental mechanisms that give rise to this concentric OPM in the mouse SC are still unclear. During visual system development, the stage III (S3) retinal waves are known to play important roles in circuit formation. Specifically, the S3 waves that tend to propagate towards the caudal direction (Gribizis et al., 2019) have impacts on the directio

Despite the recent success of deep learning in artificial intelligence, the lack of biological plausibility and labeled data in natural learning still poses a challenge in understanding biological learning. At the other extreme lies Hebbian learning, the simplest local and unsupervised one, yet considered to be computationally less efficient. In this talk, I would introduce a novel method to infer the form of Hebbian learning from in vivo data. Applying the method to the data obtained from the monkey inferior temporal cortex for the recognition task indicates how Hebbian learning changes th

The ability to encode the direction of image motion is fundamental to our sense of vision. Direction selectivity along the four cardinal directions is thought to originate in direction-selective ganglion cells (DSGCs), due to directionally-tuned GABAergic suppression by starburst cells. Here, by utilizing two-photon glutamate imaging to measure synaptic release, we reveal that direction selectivity along all four directions arises earlier than expected, at bipolar cell outputs. Thus, DSGCs receive directionally-aligned glutamatergic inputs from bipolar cell boutons. We further show that this b

Feedback mechanisms are pervasive across the nervous system, regulating neural networks through the backpropagation of information at different levels. Neuroanatomical data have shown the presence of feedback neurons within the visual system of $\textit{Drosophila}$, where information such as visual motion is extracted. However, prevailing models of motion detection, as well as other visual features, rely on feedforward networks, so far neglecting feedback adjustments originating from higher hierarchical levels. The functional significance of feedback circuits, particularly inhibitory feedback

Activity of sensory neurons is driven not only by stimuli but also by the behavior of the animal. For example, in the primary visual cortex (V1) of a mouse, the gain of sensory responses is modulated by the speed of movement [1]. On average, the response strength increases with running speed - this effect is prominent and systematic. Individual neurons can, however, reveal distinctive patterns of gain modulation. This diversity raises questions about how nuanced the impact of behavior on sensory coding is, whether it is limited to coarse gain changes, and what its computational function might

A primary goal in systems neuroscience is to understand how neuronal connectivity impacts the activity and dynamics in mechanistic models of neural processing. New connectome datasets of the fruit fly provide access to the connectivity of every neuron in its neural circuits. However, the functional role of recurrent connections in the fruit fly remains incompletely understood. For instance, although its visual system is predominantly feedforward, strong feedback connections have been identified in its motion detecting pathways [1]. What is the role of recurrent connections in the visual percep