Neuronal tuning

…towards understanding the link between neuronal activity and behaviour.$^1$ On the one hand, focusing on single-neuron responses highlighted that a few functional properties, such as neuronal tuning$^2$ or selectivity,$^3$ often characterise individual responses. These properties determine each neuron's “position” in an abstract space, which we call the “(functional) similarity space”: for example, each cell's preferred head direction (HD) in the mouse HD system determines its position on an abstract ring.$^4$ It is commonly h

Neuronal tuning changes over time, even in the absence of obvious signs of learning or changes in behaviour. This representational drift causes fixed readouts from a neural population to gradually deteriorate, suggesting that downstream populations adapt to these tuning changes. Many statistical distributions of tuning curve changes can produce comparable population-wide drift. We argue that heavy-tailed drift statistics, in which populations exhibit sparse and sudden changes in neuronal tuning, are relatively easy to adapt to. We present preliminary evidence that neural populations favour suc

…as systematically characterizing voxel tuning properties. We leverage the unprecedented scale of the Natural Scenes Dataset to constrain parametriz

…inhibitory and their consequences on neuronal tun

Dr Jennifer Lawlor Title: Tracking changes in complex auditory scenes along the cortical pathway Complex acoustic environments, such as a busy street, are characterised by their everchanging dynamics. Despite their complexity, listeners can readily tease apart relevant changes from irrelevant variations. This requires continuously tracking the appropriate sensory evidence while discarding noisy acoustic variations. Despite the apparent simplicity of this perceptual phenomenon, the neural basis of the extraction of relevant information in complex continuous streams for goal-directed behavior is

Cognitive tasks typically require the integration of working memory, contextual processing, and planning to be carried out in close coordination. However, these computations are typically studied within neuroscience as independent modular processes in the brain. In this talk I will present an alternative view, that neural representations of mappings between expected stimuli and contingent goal actions can unify working memory and planning computations. We term these stored maps contingency representations. We developed a "conditional delayed logic" task capable of disambiguating the types of r