Every day we make decisions critical for adaptation and survival. We repeat actions with known consequences. But we also draw on loosely related events, to infer and imagine the outcome of entirely novel choices. These inferential decisions are thought to engage a number of brain regions, however the underlying neuronal computation remains unknown. In this talk I will show how a cross-species approach in humans and mice can be used to reveal the functional anatomy and neuronal computation underlying inferential decisions. I will show that during successful inference, the mammalian brain uses a hippocampal prospective code to forecast temporally-structured learned associations. Moreover, during resting behaviour, short-timescale coactivation of hippocampal cells represent inferred relationships in sharp-wave/ripples, thereby “joining-the-dots” between events that have not been observed together but lead to profitable outcomes. Computing mnemonic links in this manner may provide a general mechanism to build a cognitive map that stretches beyond direct experience, thus supporting flexible behavior.
Helen Barron is a postdoctoral researcher at the MRC Brain Network Dynamics Unit, University of Oxford. Her research focuses on investigating how memories support adaptive behaviour, with particular interest in the interaction between the hippocampus and neocortex and the role of inhibition. She recently completed a Junior Research Fellowship under supervision from Professor David Dupret, where she developed a cross-species approach to gain insight into neural circuit mechanisms in the living human brain. Helen's research now combines non-invasive Magnetic Resonance Imaging (MRI) and brain stimulation in humans with invasive electrophysiology and optogenetic manipulations in mice. Before moving to Oxford in 2015, Helen studied Natural Sciences (MA Cantab) at the University of Cambridge followed by a 4-Year MRC funded PhD program in Neuroscience at University College London (UCL) under supervision from Professors Tim Behrens and Ray Dolan.
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