neuromatch

In Steinmetz et al., 2019 mice performed a visual discrimination task while their brain activity was captured using Neuropixel probes. The primary sensory input of the mice was the visual cue for which the first processing station in the brain is the primary visual cortex. Mice with different (something?)could perform the task with different speed. We think that the first step of sensory processing in the primary visual cortex plays a key role determining the reaction time of the animal. Making predictions about surroundings and adjusting behavior accordingly is a mental process to ensure survival. Being able to predict behaviors of individuals on a larger scale will reduce risk factors in a more global structure. One can imagine many individuals in traffic including vehicles as a global surrounding, that can pose dangers on the population. To create a safe space in traffic, individuals with - voluntary or involuntary - dangerous behaviors should be identified. Predicting reaction time upon visual perception is a reliable way of identifying individuals with behaviors that are endangering traffic. Since the visual cortex is the initial brain area, where visual stimuli are processed, its neuronal activity shall be a target to predict the individual’s reaction time. But how can you predict the reaction time from this brain area? To tackle this question, we build a model that decodes visual cortex activity and predicts the subject’s reaction time. It’s developed based on a dataset from Steinmetz et al., 2019, where neuronal activity from mice was recorded during a perceptual decision task. We study reaction time as a behavior that is connected to neuronal responses in the visual cortex. For investigation of this relationship, we perform principal component analysis. In order to predict the reaction times from visual cortex activity, we build a generalized linear model. A model that is able to reliably predict the animals reaction time from visual cortex activity will help to develop an application for humans, where individuals’ reaction times can be predicted. Our approach is limited, considering that further factors such as motivational and emotional states as well as engagement in the task affect the reaction time. Nevertheless, laying the groundwork for a model that predicts behaviors from activity of a single brain region will advance the field. For example some kind of reaction time evaluation could create a more safe environment in traffic and this model could be further developed for other applications.