Locus Coeruleus tracking of prediction errors optimises cognitive flexibility: An Active Inference model.

Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE

Original Publication: San Francisco, CA : Public Library of Science, [2005]-

Reward*; Learning/*physiology ; Locus Coeruleus/*physiology; Animals ; Cognition/physiology ; Computational Biology ; Models, Neurological ; Norepinephrine/metabolism

The locus coeruleus (LC) in the pons is the major source of noradrenaline (NA) in the brain. Two modes of LC firing have been associated with distinct cognitive states: changes in tonic rates of firing are correlated with global levels of arousal and behavioural flexibility, whilst phasic LC responses are evoked by salient stimuli. Here, we unify these two modes of firing by modelling the response of the LC as a correlate of a prediction error when inferring states for action planning under Active Inference (AI). We simulate a classic Go/No-go reward learning task and a three-arm 'explore/exploit' task and show that, if LC activity is considered to reflect the magnitude of high level 'state-action' prediction errors, then both tonic and phasic modes of firing are emergent features of belief updating. We also demonstrate that when contingencies change, AI agents can update their internal models more quickly by feeding back this state-action prediction error-reflected in LC firing and noradrenaline release-to optimise learning rate, enabling large adjustments over short timescales. We propose that such prediction errors are mediated by cortico-LC connections, whilst ascending input from LC to cortex modulates belief updating in anterior cingulate cortex (ACC). In short, we characterise the LC/ NA system within a general theory of brain function. In doing so, we show that contrasting, behaviour-dependent firing patterns are an emergent property of the LC that translates state-action prediction errors into an optimal balance between plasticity and stability.
Competing Interests: The authors have declared that no competing interests exist.

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108899/Z/15/Z United Kingdom Wellcome Trust; 088130/Z/09/Z United Kingdom Wellcome Trust; 088373/Z/09/A United Kingdom Wellcome Trust

X4W3ENH1CV (Norepinephrine)

Date Created: 20190105 Date Completed: 20190304 Latest Revision: 20200309

20231215

PMC6334975

10.1371/journal.pcbi.1006267

30608922