Dissociable effects of surprise and model update in parietal and anterior cingulate cortex

Abstract

Brains use predictive models to facilitate the processing of expected stimuli or planned actions. Under a predictive model, surprising (low probability) stimuli or actions necessitate the immediate reallocation of processing resources, but they can also signal the need to update the underlying predictive model to reflect changes in the environment. Surprise and updating are often correlated in experimental paradigms but are, in fact, distinct constructs that can be formally defined as the Shannon information (I S ) and KullbackLeibler divergence (D KL ) associated with an observation. In a saccadic planning task, we observed that distinct behaviors and brain regions are associated with surprise/I S and updating/D KL . Although surprise/I S was associated with behavioral reprogramming as indexed by slower reaction times, as well as with activity in the posterior parietal cortex [human lateral intraparietal area (LIP)], the anterior cingulate cortex (ACC) was specifically activated during updating of the predictive model (D KL ). A second saccade-sensitive region in the inferior posterior parietal cortex (human 7a), which has connections to both LIP and ACC, was activated by surprise and modulated by updating. Pupillometry revealed a further dissociation between surprise and updating with an early positive effect of surprise and late negative effect of updating on pupil area. These results give a computational account of the roles of the ACC and two parietal saccade regions, LIP and 7a, by which their involvement in diverse tasks can be understood mechanistically. The dissociation of functional roles between regions within the reorienting/reprogramming network may also inform models of neurological phenomena, such as extinction and Balint syndrome, and neglect.eye movement | prediction | attention | learning | Bayes I n a nonrandom environment, brains can and should make use of past experience to facilitate the processing of incoming sensory information and the selection of actions, through prediction (1, 2). An important aspect of brain function is therefore the construction and tuning of internal models to represent statistics of the environment that are relevant for future behavior.The use of predictive internal models implies that not only are some events well predicted (high probability under the model) but, conversely, some events (which have a low probability under the model) are surprising (3). Surprising events may be associated with behavioral costs; for example, although valid attentional cues speed reaction times (RTs), invalid cues lengthen them (3, 4). However, surprising events can have a further significance for the observer in that they sometimes provide evidence for a change in the environment, which would imply a need to update the brain's internal models to predict future events accurately.Here, we explore the possibility that the brain carries out at least two distinct operations when a surprising event occurs: (i) within trial reorienting processes evoked by surprise, including reallocation o...

Connectivity reveals relationship of brain areas for reward-guided learning and decision making in human and monkey frontal cortex

“…Other human neuroimaging studies have implicated the ACC in learning and updating values of choices (48)(49)(50). Activity in this region is sometimes described as being in the anterior RCZ (RCZa) (46) (Fig.…”

“…The more anterior RCZa/CMAr is responsive to feedback about motor strategies, especially when this is relevant to changes of behavior in the future both in humans (10,43,49,50,81) and macaques (51,82). This region seems more active whenever there is evidence that the current mode of action is suboptimal and alternative behaviors should be considered.…”

P300 amplitude variations, prior probabilities, and likelihoods: A Bayesian ERP study

“…Whereas likelihood uncertainty activated brain regions along the visuomotor pathway, representations of prior uncertainty were identified in brain areas outside this pathway, including putamen, amygdala, insula, and orbitofrontal cortex. O'Reilly et al (2013) separately modified surprise, that merely reflects the unexpectedness of an observation and shifts in beliefs or Bayesian updating (see Fig. 1), in a saccadic planning task.…”

“…FitzGerald, and Dolan (2016) developed a novel paradigm that allowed decomposing surprise and Bayesian updating (akin to O'Reilly et al, 2013). Using fMRI, they showed that dopamine-rich midbrain regions encode Bayesian updating, whereas surprise is encoded in prefrontal regions, including the presupplementary motor area and dorsal cingulate cortex.…”

Dynamic encoding of structural uncertainty in gradient symbols

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