Differential modulation of visual responses by distractor or target expectations

Discriminating relevant from irrelevant information in a busy visual scene is supported by statistical regularities in the environment. However, it is unclear to what extent immediate stimulus repetitions and higher order expectations (whether a repetition is statistically probable or not) are supported by the same neural mechanisms. Moreover, it is also unclear whether target and distractor-related processing are mediated by the same or different underlying neural mechanisms. Using a speeded target discrimination task, the present study implicitly cued subjects to the location of the target or the distractor via manipulations in the underlying stimulus predictability. In separate studies, we collected EEG and MEG alongside behavioural data. Results showed that reaction times were reduced with increased expectations for both types of stimuli and that these effects were driven by expected repetitions in both cases. Despite the similar behavioural pattern across target and distractors, neurophysiological measures distinguished the two stimuli. Specifically, the amplitude of the P1 was modulated by stimulus relevance, being reduced for repeated distractors and increased for repeated targets. The P1 was not, however, modulated by higher order stimulus expectations. These expectations were instead reflected in modulations in ERP amplitude and theta power in frontocentral electrodes. Finally, we observed that a single repetition of a distractor was sufficient to reduce decodability of stimulus spatial location and was also accompanied by diminished representation of stimulus features. Our results highlight the unique mechanisms involved in distractor expectation and suppression and underline the importance of studying these processes distinctly from target-related attentional control

On the relationship between the “default mode network” and the “social brain”

The default mode network (DMN) of the brain consists of areas that are typically more active during rest than during active task performance. Recently however, this network has been shown to be activated by certain types of tasks. Social cognition, particularly higher-order tasks such as attributing mental states to others, has been suggested to activate a network of areas at least partly overlapping with the DMN. Here, we explore this claim, drawing on evidence from meta-analyses of functional MRI data and recent studies investigating the structural and functional connectivity of the social brain. In addition, we discuss recent evidence for the existence of a DMN in non-human primates. We conclude by discussing some of the implications of these observations

Behavioral flexibility is associated with changes in structure and function distributed across a frontal cortical network in macaques

One of the most influential accounts of central orbitofrontal cortex-that it mediates behavioral flexibility-has been challenged by the finding that discrimination reversal in macaques, the classic test of behavioral flexibility, is unaffected when lesions are made by excitotoxin injection rather than aspiration. This suggests that the critical brain circuit mediating behavioral flexibility in reversal tasks lies beyond the central orbitofrontal cortex. To determine its identity, a group of nine macaques were taught discrimination reversal learning tasks, and its impact on gray matter was measured. Magnetic resonance imaging scans were taken before and after learning and compared with scans from two control groups, each comprising 10 animals. One control group learned discrimination tasks that were similar but lacked any reversal component, and the other control group engaged in no learning. Gray matter changes were prominent in posterior orbitofrontal cortex/anterior insula but were also found in three other frontal cortical regions: lateral orbitofrontal cortex (orbital part of area 12 [12o]), cingulate cortex, and lateral prefrontal cortex. In a second analysis, neural activity in posterior orbitofrontal cortex/anterior insula was measured at rest, and its pattern of coupling with the other frontal cortical regions was assessed. Activity coupling increased significantly in the reversal learning group in comparison with controls. In a final set of experiments, we used similar structural imaging procedures and analyses to demonstrate that aspiration lesion of central orbitofrontal cortex, of the type known to affect discrimination learning, affected structure and activity in the same frontal cortical circuit. The results identify a distributed frontal cortical circuit associated with behavioral flexibility

Lesions to the mediodorsal thalamus, but not orbitofrontal cortex, enhance volatility beliefs linked to paranoia

Beliefs—attitudes toward some state of the environment—guide action selection and should be robust to variability but sensitive to meaningful change. Beliefs about volatility (expectation of change) are associated with paranoia in humans, but the brain regions responsible for volatility beliefs remain unknown. The orbitofrontal cortex (OFC) is central to adaptive behavior, whereas the magnocellular mediodorsal thalamus (MDmc) is essential for arbitrating between perceptions and action policies. We assessed belief updating in a three-choice probabilistic reversal learning task following excitotoxic lesions of the MDmc (n = 3) or OFC (n = 3) and compared performance with that of unoperated monkeys (n = 14). Computational analyses indicated a double dissociation: MDmc, but not OFC, lesions were associated with erratic switching behavior and heightened volatility belief (as in paranoia in humans), whereas OFC, but not MDmc, lesions were associated with increased lose-stay behavior and reward learning rates. Given the consilience across species and models, these results have implications for understanding paranoia

Local and global reward learning in the lateral frontal cortex show differential development during human adolescence.

Funder: Wellcome TrustReward-guided choice is fundamental for adaptive behaviour and depends on several component processes supported by prefrontal cortex. Here, across three studies, we show that two such component processes, linking reward to specific choices and estimating the global reward state, develop during human adolescence and are linked to the lateral portions of the prefrontal cortex. These processes reflect the assignment of rewards contingently to local choices, or noncontingently, to choices that make up the global reward history. Using matched experimental tasks and analysis platforms, we show the influence of both mechanisms increase during adolescence (study 1) and that lesions to lateral frontal cortex (that included and/or disconnected both orbitofrontal and insula cortex) in human adult patients (study 2) and macaque monkeys (study 3) impair both local and global reward learning. Developmental effects were distinguishable from the influence of a decision bias on choice behaviour, known to depend on medial prefrontal cortex. Differences in local and global assignments of reward to choices across adolescence, in the context of delayed grey matter maturation of the lateral orbitofrontal and anterior insula cortex, may underlie changes in adaptive behaviour

Differential Modulation of Visual Responses by Distractor or Target Expectations

A study to investigate the contribution of stimulus repetition and stimulus expectation to target and distractor processin

Frontal Cortex and Reward-Guided Learning and Decision-Making

Reward-guided decision-making and learning depends on distributed neural circuits with many components. Here we focus on recent evidence that suggests four frontal lobe regions make distinct contributions to reward-guided learning and decision-making: the lateral orbitofrontal cortex, the ventromedial prefrontal cortex and adjacent medial orbitofrontal cortex, anterior cingulate cortex, and the anterior lateral prefrontal cortex. We attempt to identify common themes in experiments with human participants and with animal models, which suggest roles that the areas play in learning about reward associations, selecting reward goals, choosing actions to obtain reward, and monitoring the potential value of switching to alternative courses of action