Publications by authors named "Archy O de Berker"

We are constantly interacting with our environment whilst we encode memories. However, how actions influence memory formation remains poorly understood. Goal-directed movement engages the locus coeruleus (LC), the main source of noradrenaline in the brain.

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People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15-30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly.

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How organisms learn the value of single stimuli through experience is well described. In many decisions, however, value estimates are computed "on the fly" by combining multiple stimulus attributes. The neural basis of this computation is poorly understood.

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Naturalistic decision-making typically involves sequential deployment of attention to choice alternatives to gather information before a decision is made. Attention filters how information enters decision circuits, thus implying that attentional control may shape how decision computations unfold. We recorded neuronal activity from three subregions of the prefrontal cortex (PFC) while monkeys performed an attention-guided decision-making task.

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Oscillatory activity in the beta frequency range (15-30Hz) recorded from human sensorimotor cortex is of increasing interest as a putative biomarker of motor system function and dysfunction. Despite its increasing use in basic and clinical research, surprisingly little is known about the test-retest reliability of spectral power and peak frequency measures of beta oscillatory signals from sensorimotor cortex. Establishing that these beta measures are stable over time in healthy populations is a necessary precursor to their use in the clinic.

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Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty.

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Stress interferes with instrumental learning. However, choice is also influenced by non-instrumental factors, most strikingly by biases arising from Pavlovian associations that facilitate action in pursuit of rewards and inaction in the face of punishment. Whether stress impacts on instrumental learning via these Pavlovian associations is unknown.

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Although social comparison is a known determinant of overall life satisfaction, it is not clear how it affects moment-to-moment variation in subjective emotional state. Using a novel social decision task combined with computational modelling, we show that a participant's subjective emotional state reflects not only the impact of rewards they themselves receive, but also the rewards received by a social partner. Unequal outcomes, whether advantageous or disadvantageous, reduce average momentary happiness.

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The effects of stress are frequently studied, yet its proximal causes remain unclear. Here we demonstrate that subjective estimates of uncertainty predict the dynamics of subjective and physiological stress responses. Subjects learned a probabilistic mapping between visual stimuli and electric shocks.

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Multivariate pattern analysis (MVPA) of fMRI data has become an important technique for cognitive neuroscientists in recent years; however, the relationship between fMRI MVPA and the underlying neural population activity remains unexamined. Here, we performed MVPA of fMRI data and single-unit data in the same species, the macaque monkey. Facial recognition in the macaque is subserved by a well characterized system of cortical patches, which provided the test bed for our comparison.

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Transcranial electrical stimulation (tES) influences neural activity in a way that can elicit behavioural change but may also improve high-level cognition or ameliorate symptoms in neuropsychiatric disorders. However, the current fervour for tES contrasts with the paucity of mechanistically detailed models of how stimulation causes behavioural change. Here we challenge the plausibility of several common assumptions and interpretations of tES and discuss how to bridge the ravines separating our understanding of the behavioural and neural consequences of tES.

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The transcranial application of weak currents to the human brain has enjoyed a decade of widespread use, providing a simple and powerful tool for non-invasively altering human brain function. However, our understanding of current delivery and its impact upon neural circuitry leaves much to be desired. We argue that the credibility of conclusions drawn with transcranial direct current stimulation (tDCS) is contingent upon realistic explanations of how tDCS works, and that our present understanding of tDCS limits the technique's use to localize function in the human brain.

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