Topic: saccades

We use rapid eye, head, and body movements to extract information from a new part of the visual scene upon each new gaze fixation. But the consequences of such visual actions go beyond their intended sensory outcomes. On the one hand, intrinsic consequences accompany movement preparation as covert internal processes (e.g., predictive changes in the deployment of visual attention). On the other hand, visual actions have incidental consequences, side effects of moving the sensory surface to its intended goal (e.g., global motion of the retinal image during saccades). In this talk, I will present

We examine how the saccade mechanism from biological vision can be used to make deep neural networks more efficient for classification and object detection problems. Our proposed approach is based on the ideas of attention-driven visual processing and saccades, miniature eye movements influenced by attention. We conduct experiments by analyzing: i) the robustness of different deep neural network (DNN) feature extractors to partially-sensed images for image classification and object detection, and ii) the utility of saccades in masking image patches for image classification and object tracking.

Saccades are fast eye movements that change gaze direction in a ballistic fashion. Human saccadic behaviour has been studied extensively in neuroscience and several methods have been proposed to model the saccadic system. For example, John et al. (2021) adopted a model-based approach, based on a physical model of the eye plant (eyeball, extraocular muscles, and surrounding tissues). They used feedforward optimal-control principles to replicate human saccadic behaviour. Here, we adopted a model-free approach to study the question: “How to learn saccadic behaviours without prior knowledge of the

In this lecture, I will present our recent progress on three aspects of population responses in the primary visual cortex: encoding local stimulus attributes, electrical microstimulation and higher visual function. In the first part I will focus on population encoding and reconstruction of contour shapes in V1 and the comparison between monkey and mouse visual responses. In the second part of the talk I will present the effects of microstimulation on neural population in V1 and the relation to evoked saccades. In the final part of the talk I will discuss top-down influences in V1 and their re

Human vision relies on rapid eye movements (saccades) 2-3 times every second to bring peripheral targets to central foveal vision for high resolution inspection. This rapid sampling of the world defines the perception-action cycle of natural vision and profoundly impacts our perception. Marmosets have similar visual processing and eye movements as humans, including a fovea that supports high-acuity central vision. Here, I present a novel approach developed in my laboratory for investigating the neural mechanisms of visual processing using naturalistic free viewing and simple target foraging pa

Outside the foveola, visual acuity and other visual functions gradually deteriorate with increasing eccentricity. Humans compensate for these limitations by relying on a tight link between perception and action; rapid gaze shifts (saccades) occur 2-3 times every second, separating brief “fixation” intervals in which visual information is acquired and processed. During fixation, however, the eye is not immobile. Small eye movements incessantly shift the image on the retina even when the attended stimulus is already foveated, suggesting a much deeper coupling between visual functions and oculomo

During smooth pursuit, the oculomotor system needs to multi-task: eye velocity is adjusted to keep the moving stimulus on the fovea; in case of target blanking or loss of foveation, saccades are performed to catch up with the target. Mathematical models can be used to implement a quantitative description of underlying processes. Thus, models can provide insight by identifying parameters related to the physiological mechanisms (like pursuit gain or retinal delay).Here, we adapted a one-dimensional oculomotor model (Marti et al. 2008) to a two-dimensional pursuit task with target blanking (see f

In a complex and mutable environment, animals continuously face scenarios where behavioral decisions determine their survival. These rely primarily on sensory input and the associated cognitive process is known as perceptual decision-making. The decision-making is typically preceded by the gathering of information across time in a process called evidence accumulation. This has been widely studied on various animals; however, in flies, the emphasis has primarily been centered on the subcellular integration mechanisms, overlooking the behavioral impacts and whole-brain neuronal dynamics.Here, we