Topic: running speed

Distinguishing near and far visual cues is an essential computation that animals must carry out to guide behavior using vision. When animals move, self-motion creates motion parallax — an important but poorly understood source of depth information — whereby the speed of optic flow generated by self-motion depends on the depth of visual cues. This enables animals to estimate depth by comparing visual motion and self-motion speeds. As neurons in the mouse primary visual cortex (V1) are broadly modulated by locomotion, we hypothesized that they may integrate visual- and locomotion-related signals

In this study, we aim to broaden our understanding of the mouse’s primary visual cortex by modeling data provided by the datasets from Stringer et al. (2019) and the Allen Institute. We investigated the roles of the different excitatory and inhibitory cell types in the visual cortex whose functions remain unclear. Using the Stringer dataset, we explored the correlation between the activity of excitatory cells in the mouse visual cortex and mouse running behavior without any visual input. Principle Component Analysis (PCA) was applied to reduce the dimension of our neuron activity data of 119

The superior colliculus (SC) is a major recipient of visual input in the mouse and controls innate approach and avoidance behaviours. Neurons in the superficial SC (sSC), which receives direct input from the retina, do not only process visual stimuli, but are also modulated by the animal’s running speed and pupil-linked arousal, similar to modulations observed in the primary visual cortex. While these observations were made during passive viewing of visual stimuli, a major purpose of vision is to guide behaviour. We therefore asked whether, in the context of a behavioural task, visual activity

Imagine that it’s tea time and you’d like to eat a distant cookie. The speed at which you will walk toward this cookie will be modulated by your sensitivities to the energetic cost of movement (e.g., lazy vs. energetic), to the cost of time (e.g., patient vs. impatient), and to the reward (e.g., hungry vs. sated). How these sensitivities modulate behavior and their neural implementation remain poorly understood. Here, we tackled this question by combining experimental and theoretical approaches. We developed an automated foraging task in which rats have to run back and forth on a treadmill to

Neural responses in the visual system are usually not purely visual but depend on behavioural and internal states such as arousal. This dependence is seen both in primary visual cortex (V1) and in subcortical brain structures receiving direct retinal input. In this talk, I will show that modulation by behavioural state arises as early as in the output of the retina.To measure retinal activity in the awake, intact brain, we imaged the synaptic boutons of retinal axons in the superficial superior colliculus (sSC) of mice. The activity of about half of the boutons depended not only on vision but

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

How quickly humans and other animals take decisions and move often covary with the utility of their goals, suggesting the existence of a shared mechanism controlling the speeds of action selection and execution. To test this hypothesis, we developed a self-paced foraging task in which rats run back-and-forth across a motorized treadmill to collect drops of water, and separately manipulated reward and effort. We used simple models to 1) quantify changes in running speed and in the pause between runs (run and inter-run durations) and 2) explore algorithmic and neural principles controlling these

Extraction of relevant stimulus features from the dynamic sensory scene needs to be coupled to the execution of appropriate adaptive responses to ensure survival. A predator needs to evaluate its position with respect to that of moving prey, define an approach strategy and carry out the proper motor commands to execute it. The most efficient strategy will require an estimation of the future position of the target and should account for the predator’s sensorimotor processing delays to make a predictive interception. Mice can hunt moving prey and have been established as a successful model to st