Biology subjects

Dolan, R. J.

Publications and source records attributed to Dolan, R. J..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Uncertain Precision: Neurobiological and Physiological Correlates of Conservative Confidence Bias

Correctly estimating the influence of uncertainty on our decisions is a critical metacognitive faculty. However, the relationship between sensory uncertainty (or its inverse, precision), decision accuracy, and subjective confidence is currently unclear. Although some findings indicate that healthy adults exhibit an illusion of over-confidence, under-confidence in response to sensory uncertainty has also been reported. One reason for this ambiguity is that stimulus intensity and precision are typically confounded with one another, limiting the ability to assess their independent contribution to metacognitive biases. Here we report four psychophysical experiments controlling these factors, finding that healthy human participants are systematically under-confident when discriminating low-precision stimuli. This bias remains even when decision accuracy and reaction time are accounted for, indicating that a performance-independent computation partially underpins the influence of sensory precision on confidence. We further show that this influence is linked to fluctuations in arousal and individual differences in the neuroanatomy of the left superior parietal lobe and middle insula. These results illuminate the neural and physiological correlates of precision misperception in metacognition. Significance StatementThe ability to recognize the influence of sensory uncertainty on our decisions underpins the veracity of self-monitoring, or metacognition. In the extreme, a systematic confidence bias can undermine decision accuracy and potentially underpin disordered self-insight in neuropsychiatric illness. Previously it was unclear if metacognition accurately reflects changes in sensory precision, in part due to confounding effects of stimulus intensity and precision. Here we overcome these limitations to repeatedly demonstrate a robust precision-related confidence bias. Further, we reveal novel neuroanatomical and physiological markers underlying this metacognitive bias. These results suggest a unique state-based computational mechanism may drive subjective confidence biases and further provide new avenues for investigating maladaptive awareness of uncertainty in neuropsychiatric disorders.

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bioRxiv2021

Boosting serotonin increases information gathering by reducing subjective cognitive costs

Serotonin is implicated in the valuation of aversive costs, such as delay or physical effort. However, its role in governing sensitivity to cognitive effort, for example deliberation costs during information gathering, is unclear. We show that week-long treatment with a serotonergic antidepressant enhances a willingness to gather information when trying to maximize reward. Using computational modelling, we show this arises from a diminished sensitivity to subjective deliberation costs during the sampling process. This result is consistent with the notion that serotonin alleviates sensitivity to aversive costs in a domain-general fashion, with implications for its potential contribution to a positive impact on motivational deficits in psychiatric disorders.

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bioRxiv2021

Differential replay for reward and punishment paths predicts approach and avoidance

Planning is thought to involve neural replay, where states relevant to a task goal are rapidly reactivated in sequence. It remains unclear if, during planning, replay of a path relates to an actual prospective choice. Here, using magnetoencephalography (MEG), we studied participants while they planned to either approach or avoid an uncertain environment that contained paths leading to reward and to punishment. We show significant planning-related forward sequential replay with state-to-state transitions in the range of 20 to 90 ms. Replay of rewarding paths was boosted prior to a decision to avoid, and attenuated prior to a decision to approach. Crucially, a trial-by-trial bias in replaying punishing paths predicted an irrational choice to approach when a prospective environment was more risky, an effect that was particularly marked in more anxious participants. The findings reveal a coupling between the content of forwards replay and rational choice behaviour, such that replay prioritises an online representation of potential reward.

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bioRxiv2021

Shared responsibility decreases the sense of agency in the human brain

Sharing responsibility in social decision-making helps individuals use the flexibility of the collective context to benefit themselves by claiming credit for good outcomes or avoiding the blame for bad outcomes. Using magnetoencephalography (MEG), we examined the neuronal basis of the impact that social context has on this flexible sense of responsibility. Participants performed a gambling task in various social contexts and reported feeling less responsibility when playing as a member of a team. A reduced MEG outcome processing effect was observed as a function of decreasing responsibility at 200 ms post outcome onset and was centred over parietal and pre-central brain regions. Prior to outcome revelation in socially made decisions, an attenuated motor preparation signature at 500 ms after stimulus onset was found. A boost in reported responsibility for positive outcomes in social contexts was associated with increased activity in regions related to social and reward processing. Together, these results show that sharing responsibility with others reduces agency, influencing pre-outcome motor preparation and post-outcome processing, and provides opportunities to flexibly claim credit for positive outcomes.

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bioRxiv2021

Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference

Dopamine is implicated in signalling model-free (MF) reward prediction errors and various aspects of model-based (MB) credit assignment and choice. Recently, we showed that cooperative interactions between MB and MF systems include guidance of MF credit assignment by MB inference. Here, we used a double-blind, placebo-controlled, within-subjects design to test the hypothesis that enhancing dopamine levels, using levodopa, boosts the guidance of MF credit assignment by MB inference. We found that levodopa enhanced retrospective guidance of MF credit assignment by MB inference, without impacting on MF and MB influences per se. This drug effect positively correlated with working memory, but only in a context where reward needed to be recalled for MF credit assignment. The dopaminergic enhancement in MB-MF interactions correlated negatively with a dopamine-dependent change in MB credit assignment, possibly reflecting a potential trade-off between these two components of behavioural control. Thus, our findings demonstrate that dopamine boosts MB inference during guidance of MF learning, supported in part by working memory, but trading-off with a dopaminergic enhancement of MB credit assignment. The findings highlight a novel role for a DA influence on MB-MF interactions.

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bioRxiv2020

Model-based aversive learning in humans is supported by preferential task state reactivation

Harm avoidance is critical for survival, yet little is known regarding the underlying neural mechanisms supporting avoidance when we cannot rely on direct trial and error experience. Neural reactivation, and sequential replay, have emerged as potential candidate mechanisms. Here, during an aversive learning task, in conjunction with magnetoencephalography, we show prospective and retrospective reactivation for planning and learning respectively, coupled to evidence for sequential replay. Specifically, when subjects plan in an aversive context, we find preferential reactivation of subsequently chosen goal states and sequential replay of the preceding path. This reactivation was associated with greater hippocampal theta power. At outcome receipt, unchosen goal states are reactivated regardless of outcome valence. However, replay of paths leading to goal states was directionally modulated by outcome valence, with aversive outcomes leading to stronger reverse replay compared to safe outcomes. Our findings suggest that avoidance behaviour involves simulation of alternative future and past outcome states through hippocampally-mediated reactivation and replay.

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bioRxiv2020

Experience replay supports non-local learning

To make effective decisions we need to consider the relationship between actions and outcomes. They are, however, often separated by time and space. The biological mechanism capable of spanning those gaps remains unknown. One promising, albeit hypothetical, mechanism involves neural replay of non-local experience. Using a novel task, that segregates direct from indirect learning, combined with magnetoencephalography (MEG), we tested the role of neural replay in non-local learning in humans. Following reward receipt, we found significant backward replay of non-local experience, with a 160 msec state-to-state time lag, and this replay facilitated learning of action values. This backward replay, combined with behavioural evidence of non-local learning, was more pronounced in experiences that were of greater benefit for future behavior, as predicted by theories of prioritization. These findings establish rationally targeted non-local replay as a neural mechanism for solving complex credit assignment problems during learning. One Sentence SummaryReverse sequential replay is found, for the first time, to support non-local reinforcement learning in humans and is prioritized according to utility.

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bioRxiv2020

Explaining distortions in metacognition with an attractor network model of decision uncertainty

Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. Here, we develop a biologically-plausible model of decision uncertainty in an attempt to bridge this gap. We first relate the models uncertainty in perceptual decisions to standard metrics of metacognition, namely mean confidence level (bias) and the accuracy of metacognitive judgments (sensitivity). We show that dissociable shifts in metacognition are associated with isolated disturbances at higher-order levels of a circuit associated with self-monitoring, akin to neuropsychological findings that highlight the detrimental effect of prefrontal brain lesions on metacognitive performance. Notably, we are able to account for empirical confidence judgements by fitting the parameters of our biophysical model to first-order performance data, specifically choice and response times. Lastly, in a reanalysis of existing data we show that self-reported mental health symptoms relate to disturbances in an uncertainty-monitoring component of the network. By bridging a gap between a biologically-plausible model of confidence formation and observed disturbances of metacognition in mental health disorders we provide a first step towards mapping theoretical constructs of metacognition onto dynamical models of decision uncertainty. In doing so, we provide a computational framework for modelling metacognitive performance in settings where access to explicit confidence reports is not possible. Author SummaryIn this work, we use a biologically-plausible model of decision uncertainty to show that shifts in metacognition are associated with disturbances in the interaction between decision-making and higher-order uncertainty-monitoring networks. Specifically, we show that stronger uncertainty modulation is associated with decreased metacognitive bias, sensitivity, and efficiency, with no effect on perceptual sensitivity. Our approach not only enables inferences about uncertainty modulation (and, in turn, these facets of metacognition) from fits to first-order performance data alone - but also provides a first step towards relating dynamical models of decision-making to metacognition. We also relate our models uncertainty modulation to psychopathology, and show that it can offer an implicit, low-dimensional marker of metacognitive (dys)function - opening the door to richer analysis of the interaction between metacognitive performance and psychopathology from first-order performance data.

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bioRxiv2020

A generic decision-making ability predicts psychopathology in adolescents and young adults and is reflected in distinct brain connectivity patterns

Decision-making underpins many important facets of our lives. Here, we assessed if a general ability factor underpins decision-making abilities. Using factor analysis of 32 decision-making measures in 830 adolescents and young adults, we identified a common factor we refer to as decision acuity that was distinct from IQ and reflected advantageous decision-making abilities. Decision acuity decreased with low general social functioning and aberrant thinking. Crucially, decision acuity and IQ had dissociable neural signatures in terms of resting-state functional connectivity involving specific neural networks. Finally, decision acuity was reliable and its relationship with functional connectivity was stable when measured in the same individuals 18 months later. We conclude that our behavioural and brain data demonstrate a new cognitive construct encapsulating ability to perform decision-making across distinct domains, and that the expression of this construct may be important for understanding psychopathology.

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bioRxiv2020

Sexually dimorphic development of depression-related brain networks during healthy human adolescence

We hypothesized that there are sexual differences in human brain network development underlying the female > male divergence in adolescent depression. We tested for sex differences in parameters of brain network development (accelerated longitudinal fMRI, N=298 healthy adolescents, each scanned 1 to 3 times). Sexually divergent development of functional connectivity was located in default mode network (DMN), limbic cortex, and subcortical nuclei. Females had a more "disruptive" pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of divergent adolescent development was co-located with (i) a map of functional dysconnectivity associated with adult major depressive disorder (MDD); and (ii) an adult brain gene expression pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. Sexual divergence in disruptive development of DMN, limbic and subcortical functional networks is potentially relevant to the increased risk of depression in adolescent females.

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bioRxiv2020

Replay bursts coincide with activation of the default mode and parietal alpha network

Our brains at rest spontaneously replay recently acquired information, but how this process is orchestrated to avoid interference with ongoing cognition is an open question. We investigated whether replay coincided with spontaneous patterns of whole brain activity. We found, in two separate datasets, that replay sequences were packaged into transient bursts occurring selectively during activation of the default mode network (DMN) and parietal alpha network. These networks were characterized by widespread synchronized oscillations coupled to increases in ripple band power, mechanisms that coordinate information flow between disparate cortical areas. Our data show a tight correspondence between two widely studied phenomena of neural physiology and suggest the DMN may coordinate replay bursts in a manner that minimizes interference with ongoing cognition.

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bioRxiv2020

SSRIs modulate asymmetric learning from reward and punishment

Human instrumental learning is driven by a history of outcome success and failure. We demonstrate that week-long treatment with a serotonergic antidepressant modulates a valence-dependent asymmetry in learning from reinforcement. In particular, we show that prolonged boosting of central serotonin reduces reward learning, and enhances punishment learning. This treatment induced learning asymmetry can result in lowered positive and enhanced negative expectations. A consequential effect is more rewarding, and less disappointing, experiences and this may, in part, explain the slow temporal evolution of serotonins well-established antidepressant effects.

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bioRxiv2020

The roles of online and offline replay in planning

Animals and humans replay neural patterns encoding trajectories through their environment, both whilst they solve decision-making tasks and during rest. Both on-task and off-task replay are believed to contribute to flexible decision making, though how their relative contributions differ remains unclear. We investigated this question by using magnetoencephalography to study human subjects while they performed a decision-making task that was designed to reveal the decision algorithms employed. We characterized subjects in terms of how flexibly each adjusted their choices to changes in temporal, spatial and reward structure. The more flexible a subject, the more they replayed trajectories during task performance, and this replay was coupled with re-planning of the encoded trajectories. The less flexible a subject, the more they replayed previously and subsequently preferred trajectories during rest periods between task epochs. The data suggest that online and offline replay both participate in planning but support distinct decision strategies.

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bioRxiv2019

A neurocomputational model for intrinsic reward

Standard economic indicators provide an incomplete picture of what we value both as individuals and as a society. Furthermore, canonical macroeconomic measures, such as GDP, do not account for non-market activities (e.g., cooking, childcare) that nevertheless impact well-being. Here, we introduce a computational tool that measures the affective value of experiences (e.g., playing a musical instrument without errors). We go on to validate this tool with neural data, using fMRI to measure neural activity in male and female human subjects performing a reinforcement learning task that incorporated periodic ratings of subjective affective state. Learning performance determined level of payment (i.e., extrinsic reward). Crucially, the task also incorporated a skilled performance component (i.e., intrinsic reward) which did not influence payment. Both extrinsic and intrinsic rewards influenced affective dynamics, and their relative influence could be captured in our computational model. Individuals for whom intrinsic rewards had a greater influence on affective state than extrinsic rewards had greater ventromedial prefrontal cortex (vmPFC) activity for intrinsic than extrinsic rewards. Thus, we show that computational modelling of affective dynamics can index the subjective value of intrinsic relative to extrinsic rewards, a computational hedonometer that reflects both behavior and neural activity that quantifies the affective value of experience. SIGNIFICANCE STATEMENTTraditional economic indicators are increasingly recognized to provide an incomplete picture of what we value as a society. Standard economic approaches struggle to accurately assign values to non-market activities that nevertheless may be intrinsically rewarding, prompting a need for new tools to measure what really matters to individuals. Using a combination of neuroimaging and computational modeling, we show that despite their lack of instrumental value, intrinsic rewards influence subjective affective state and ventromedial prefrontal cortex activity. The relative degree to which extrinsic and intrinsic rewards influence affective state is predictive of their relative impacts on neural activity, confirming the utility of our approach for measuring the affective value of experiences and other non-market activities in individuals.

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bioRxiv2019

Associations between aversive learning processes and transdiagnostic psychiatric symptoms revealed by large-scale phenotyping

BackgroundSymptom expression in a range of psychiatric conditions is linked to altered threat perception, manifesting particularly in uncertain environments. How precise computational mechanisms that support aversive learning, and uncertainty estimation, relate to the presence of specific psychiatric symptoms remains undetermined. 400 subjects completed an online game-based aversive learning task, requiring avoidance of negative outcomes, in conjunction with completing measures of common psychiatric symptoms. We used a probabilistic computational model to measure distinct processes involved in learning, in addition to inferred estimates of safety likelihood and uncertainty, and tested for associations between these variables and traditional psychiatric constructs alongside transdiagnostic dimensions. We used partial least squares regression to identify components of psychopathology grounded in both aversive learning behaviour and symptom self-report. We show that state anxiety and a transdiagnostic compulsivity-related factor are associated with enhanced learning from safety, and data-driven analysis indicated the presence of two separable components across our behavioural and questionnaire data: one linked enhanced safety learning and lower estimated uncertainty to physiological anxiety, compulsivity, and impulsivity; the other linked enhanced threat learning, and heightened uncertainty estimation, to symptoms of depression and social anxiety. Our findings implicate distinct aversive learning processes in the expression of psychiatric symptoms that transcend traditional diagnostic boundaries.

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bioRxiv2019

Episodic memory retrieval is supported by rapid replay of episode content

Memory for everyday experience shapes our representation of the structure of the world, while retrieval of these experiences is fundamental for informing our future decisions. The fine-grained neurophysiological mechanisms that support such retrieval are largely unknown. We studied participants who first experienced, without repetition, unique multi-component episodes. One day later, they engaged in cued retrieval of these episodes whilst undergoing magnetoencephalography (MEG). By decoding individual episode elements, we found that trial-by-trial successful retrieval was supported by sequential replay of episode elements, with a temporal compression factor greater than 60. The direction of replay supporting this retrieval, either backward or forward, depended on whether a participants goal was to retrieve elements of an episode that followed or preceded a retrieval cue, respectively. This sequential replay was weaker in very high performing participants, where instead we found evidence for simultaneous clustered reactivation. Our results demonstrate that memory-mediated decisions are supported by a rapid replay mechanism that can flexibly shift in direction in response to task requirements. One Sentence SummaryRecall of extended episodes of experience is supported by compressed replay of memory elements that flexibly changes direction depending on task temporal orientation.

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bioRxiv2019

Conservative and disruptive modes of adolescent change in brain functional connectivity

Adolescent changes in human brain function are not entirely understood. Here we used multi-echo functional magnetic resonance imaging (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in N=298 healthy adolescents. Participants were aged 14-26 years and were scanned on two or more occasions at least 6 months apart. We found two distinct modes of age-related change in FC: \"conservative\" and \"disruptive\". Conservative development was characteristic of primary cortex, which was strongly connected at 14 years and became even more connected in the period 14-26 years. Disruptive development was characteristic of association cortex, hippocampus and amygdala, which were not strongly connected at 14 years but became more strongly connected during adolescence. We defined the maturational index (MI) as the signed coefficient of the linear relationship between baseline FC (at 14 years, FC14) and adolescent change in FC ({triangleup}FC14-26). Disruptive systems (with negative MI) were functionally specialised for social cognition and autobiographical memory and were significantly co-located with prior maps of aerobic glycolysis (AG), AG-related gene expression, post-natal expansion of cortical surface area, and adolescent shrinkage of cortical depth. We conclude that human brain organization is disrupted during adolescence by the emergence of strong functional connectivity of subcortical nuclei and association cortical areas, representing metabolically expensive re-modelling of synaptic connectivity between brain regions that were not strongly connected in childhood. We suggest that this re-modelling process may support emergence of social skills and self-awareness during healthy human adolescence.

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bioRxiv2019

Childhood socio-economic disadvantage predicts reduced myelin growth across adolescence and young adulthood

Socio-economic disadvantage (SED) increases exposure to life stressors. Animal research suggests early life stressors affect later neurodevelopment, including myelin developmental growth. To determine whether human childhood SED affects myelination in adolescence and early adulthood we measured the developmental increase of a sensitive myelin marker, magnetization transfer (MT), in a longitudinal study. Childhood SED was associated with globally reduced MT, as well as slower intra-cortical MT increase in widespread sensory-motor, cingulate, insular and prefrontal areas and subcortical areas. Parental education partially accounted for the SED effects on MT increase, while positive parenting provided a partial protection against the impact of SED. Thus, early socio-economic disadvantage, a vulnerability factor for a range of ill-health outcomes, is a risk factor for aberrant myelin growth during a critical developmental period that is associated with a high risk of psychiatric disorder.

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