Our visual perception is remarkably accurate. However, the visual input that enters our brains is often ambiguous, due to factors such as eye movements and biological noise. A major challenge in neuroscience is to understand how our brains are able to make accurate visual decisions based on such ambiguous sensory input.
Luckily, our visual world often changes in predictable, regular ways over time. These temporal regularities can be exploited to predict the future from the recent past, thereby facilitating visual decisions. For instance, your computer will not suddenly disappear in front of you, enabling you to predict that it will still be there after briefly looking up from your desk. Crucially however, natural environments exhibit a multitude of different temporal regularities. For example, a traffic light that recently turned green can be expected to remain green for a while, allowing you to maintain speed while passing a junction. Conversely, a yellow traffic light can rapidly change to red, thus prompting you to decelerate. The exploitation of these temporal regularities therefore necessitates adaptation of perceptual decisions to such sequential patterns. Thus far, it has been unclear how brains can achieve this.
In a new paper published in Nature Communications, Dr Matthias Fritsche, HFSP fellow, and colleagues have demonstrated for the first time that mice can adapt their visual decisions to temporal regularities, enabling the researchers to probe the computational principles and neural circuits underlying this adaptation. The results led to the surprising discovery that seemingly complex adaptations to temporal regularities can be explained by relatively simple learning algorithms, commonly known as reinforcement learning algorithms. Furthermore, the researchers revealed that the neurotransmitter dopamine, which plays a pivotal role in learning from reward, tracked the behavioural adaptations and signalled key components of the reinforcement learning algorithm.
'This study provides important insights into the computational principles and neural mechanisms underlying the brain’s ability to exploit temporal patterns in the environment in order to make accurate visual decisions', added Professor Armin Lak, senior author of the paper. While such processes appear to function effortlessly in healthy individuals, they are impaired in several psychiatric disorders, such as autism, schizophrenia, as well as Parkinson’s disease, in which the dramatic loss of dopamine neurons not only causes a wide range of motor deficits, but also perceptual hallucinations and impaired decision-making. The current study therefore contributes to an exciting developing picture of how accurate perception and decisions are shaped by our environment and how these processes may go awry in clinical conditions.
The paper ‘Temporal regularities shape perceptual decisions and striatal dopamine signals’ can be read in full here.