Journal of cognitive neuroscience
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Our ability to make decisions is predicated upon our knowledge of the outcomes of the actions available to us. Reinforcement learning theory posits that actions followed by a reward or punishment acquire value through the computation of prediction errors-discrepancies between the predicted and the actual reward. A multitude of neuroimaging studies have demonstrated that rewards and punishments evoke neural responses that appear to reflect reinforcement learning prediction errors [e.g., Krigolson, O. ⋯ Furthermore, we demonstrate the existence of a reward positivity at choice presentation, a previously unreported ERP component that has a similar timing and topography as the feedback error-related negativity that increased in amplitude with learning. The pattern of results we observed mirrored the output of a computational model that we implemented to compute reward prediction errors and the changes in amplitude of these prediction errors at the time of choice presentation and reward delivery. Our results provide further support that the computations that underlie human learning and decision-making follow reinforcement learning principles.
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In everyday listening situations, we need to constantly switch between alternative sound sources and engage attention according to cues that match our goals and expectations. The exact neuronal bases of these processes are poorly understood. We investigated oscillatory brain networks controlling auditory attention using cortically constrained fMRI-weighted magnetoencephalography/EEG source estimates. ⋯ Engagement of attention to one ear resulted in a significantly stronger increase of 7.5-15 Hz alpha in the ipsilateral than contralateral parieto-occipital cortices 200-600 msec after the cue onset, possibly reflecting cross-modal modulation of the dorsal visual pathway during audiospatial attention. Comparisons of cortical power patterns also revealed significant increases of sustained right medial frontal cortex theta power, right dorsolateral pFC and anterior insula/inferior frontal cortex beta power, and medial parietal cortex and posterior cingulate cortex gamma activity after cued versus novelty-triggered orienting (600-1400 msec). Our results reveal sustained oscillatory patterns associated with voluntary engagement of auditory spatial attention, with the frontoparietal and temporal gamma increases being best predictors of subsequent behavioral performance.
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Semantic cognition requires a combination of semantic representations and executive control processes to direct activation in a task- and time-appropriate fashion [Jefferies, E., & Lambon Ralph, M. A. Semantic impairment in stroke aphasia versus semantic dementia: A case-series comparison. ⋯ Second, we contrasted executively demanding tasks tapping semantics and phonology. Our findings revealed substantial overlap between the two sets of contrasts within left ventral pFC, suggesting this region underpins domain-general control mechanisms. In contrast, we observed relative specialization for semantic control within pMTG as well as the most ventral aspects of left pFC (BA 47), consistent with our proposal of a distributed network underpinning semantic control.
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It has been proposed that visual attention and consciousness are separate [Koch, C., & Tsuchiya, N. Attention and consciousness: Two distinct brain processes. Trends in Cognitive Sciences, 11, 16-22, 2007] and possibly even orthogonal processes [Lamme, V. ⋯ Behavioral and neural learning effects were found for stimuli presented in the inattention paradigm and not for masked stimuli. Interestingly, the behavioral learning effect only became apparent when performance feedback was given on the task to measure learning, suggesting that the memory trace that is formed during inattention is latent until accessed. The results suggest that learning requires consciousness, and not attention, and further strengthen the idea that consciousness is separate from attention.
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An individual has a mind; a group does not. Yet humans routinely endow groups with mental states irreducible to any of their members (e.g., "scientists hope to understand every aspect of nature"). But are these mental states categorically similar to those we attribute to individuals? In two fMRI experiments, we tested this question against a set of brain regions that are consistently associated with social cognition--medial pFC, anterior temporal lobe, TPJ, and medial parietal cortex. ⋯ Regions previously associated with mentalizing about individuals were also robustly responsive to judgments of groups, suggesting that perceivers deploy the same social-cognitive processes when thinking about the mind of an individual and the "mind" of a group. However, multivariate searchlight analysis revealed that several of these regions showed distinct multivoxel patterns of response to groups and individual people, suggesting that perceivers maintain distinct representations of groups and individuals during mental state inferences. These findings suggest that perceivers mentalize about groups in a manner qualitatively similar to mentalizing about individual people, but that the brain nevertheless maintains important distinctions between the representations of such entities.