Humans are strongly influenced by their environment, a dependence that can lead to errors in judgment. Although a rich literature describes how people are influenced by others, little is known regarding the factors that predict subsequent rectification of misleading influence. Using a mediation model in combination with brain imaging, we propose a model for the correction of misinformation. Specifically, our data suggest that amygdala modulation of hippocampal mnemonic representations, during the time of misleading social influence, is associated with reduced subsequent anterior–lateral prefrontal cortex activity that reflects correction. These findings illuminate the process by which erroneous beliefs are, or fail to be, rectified and highlight how past influence constrains subsequent correction.
brain; fMRI; memory; recovery; social
Action inhibition can globally prevent all motor output or selectively cancel specific actions during concurrent motor output. Here we examine the behavioral and neural basis of selective inhibition focusing on the role of preparation. In 18 healthy human participants we manipulated the extent to which they could prepare for selective inhibition by providing or withholding information on what actions might need to be stopped. We show that, on average, information improves both speed and selectivity of inhibition. Functional magnetic resonance imaging data show that preparation for selective inhibition engages the inferior frontal gyrus, supplementary motor area, and striatum. Examining interindividual differences, we find the benefit of proactive control to speed and selectivity of inhibition trade off against each other, such that an improvement in stopping speed leads to a deterioration of selectivity of inhibition, and vice versa. This trade-off is implemented through engagement of the dorsolateral prefrontal cortex and putamen. Our results suggest proactive selective inhibition is implemented within frontostriatal structures, and we provide evidence that a speed-selectivity trade-off might underlie a range of findings reported previously.
Cognitions and emotions can be influenced by bodily physiology. Here, we investigated whether the processing of brief fear stimuli is selectively gated by their timing in relation to individual heartbeats. Emotional and neutral faces were presented to human volunteers at cardiac systole, when ejection of blood from the heart causes arterial baroreceptors to signal centrally the strength and timing of each heartbeat, and at diastole, the period between heartbeats when baroreceptors are quiescent. Participants performed behavioral and neuroimaging tasks to determine whether these interoceptive signals influence the detection of emotional stimuli at the threshold of conscious awareness and alter judgments of emotionality of fearful and neutral faces. Our results show that fearful faces were detected more easily and were rated as more intense at systole than at diastole. Correspondingly, amygdala responses were greater to fearful faces presented at systole relative to diastole. These novel findings highlight a major channel by which short-term interoceptive fluctuations enhance perceptual and evaluative processes specifically related to the processing of fear and threat and counter the view that baroreceptor afferent signaling is always inhibitory to sensory perception.
amygdala; anxiety; attention; baroreceptor; emotion; fMRI
Prior experience plays a critical role in decision making. It enables explicit representation of potential outcomes and provides training to valuation mechanisms. However, we can also make choices in the absence of prior experience, by merely imagining the consequences of a new experience. Here, using fMRI repetition suppression in humans, we show how neuronal representations of novel rewards can be constructed and evaluated. A likely novel experience is constructed by invoking multiple independent memories within hippocampus and medial prefrontal cortex. This construction persists for only a short time period, during which new associations are observed between the memories for component items. Together these findings suggest that in the absence of direct experience, co-activation of multiple relevant memories can provide a training signal to the valuation system which allows the consequences of new experiences to be imagined and acted upon.
•People may use Bayesian inference to update their own self-representation.•Self- and other-representations may help predict outcomes of social interactions.•The value of an outcome is essentially the prior belief that it can be achieved.•‘Active inference’ uses free-energy-minimization to achieve desirable outcomes.•A positive self-representation may be a desirable outcome of active inference.
Viewing the brain as an organ of approximate Bayesian inference can help us understand how it represents the self. We suggest that inferred representations of the self have a normative function: to predict and optimise the likely outcomes of social interactions. Technically, we cast this predict-and-optimise as maximising the chance of favourable outcomes through active inference. Here the utility of outcomes can be conceptualised as prior beliefs about final states. Actions based on interpersonal representations can therefore be understood as minimising surprise – under the prior belief that one will end up in states with high utility. Interpersonal representations thus serve to render interactions more predictable, while the affective valence of interpersonal inference renders self-perception evaluative. Distortions of self-representation contribute to major psychiatric disorders such as depression, personality disorder and paranoia. The approach we review may therefore operationalise the study of interpersonal representations in pathological states.
Self-representation; Other-representation; Free energy minimisation; Active inference; Personality disorder; Paranoia
•Action awareness can shift retrospectively at the time of an action-outcome.•In principle, this could reflect bottom-up interference and not subjective agency.•We keep bottom-up drive constant and manipulate temporal outcome variability instead.•Action awareness is shifted retrospectively in a context of variable outcome timing.•This top-down process may bias subjective agency when an outcome is unpredictable.
The subjective time of an instrumental action is shifted towards its outcome. This temporal binding effect is partially retrospective, i.e., occurs upon outcome perception. Retrospective binding is thought to reflect post-hoc inference on agency based on sensory evidence of the action – outcome association. However, many previous binding paradigms cannot exclude the possibility that retrospective binding results from bottom-up interference of sensory outcome processing with action awareness and is functionally unrelated to the processing of the action – outcome association. Here, we keep bottom-up interference constant and use a contextual manipulation instead. We demonstrate a shift of subjective action time by its outcome in a context of variable outcome timing. Crucially, this shift is absent when there is no such variability. Thus, retrospective action binding reflects a context-dependent, model-based phenomenon. Such top-down re-construction of action awareness seems to bias agency attribution when outcome predictability is low.
Action awareness; Temporal binding; Sense of agency
Animal models of human anxiety often invoke a conflict between approach and avoidance [1, 2]. In these, a key behavioral assay comprises passive avoidance of potential threat and inhibition, both thought to be controlled by ventral hippocampus [2–6]. Efforts to translate these approaches to clinical contexts [7, 8] are hampered by the fact that it is not known whether humans manifest analogous approach-avoidance dispositions and, if so, whether they share a homologous neurobiological substrate . Here, we developed a paradigm to investigate the role of human hippocampus in arbitrating an approach-avoidance conflict under varying levels of potential threat. Across four experiments, subjects showed analogous behavior by adapting both passive avoidance behavior and behavioral inhibition to threat level. Using functional magnetic resonance imaging (fMRI), we observe that threat level engages the anterior hippocampus, the human homolog of rodent ventral hippocampus . Testing patients with selective hippocampal lesions, we demonstrate a causal role for the hippocampus with patients showing reduced passive avoidance behavior and inhibition across all threat levels. Our data provide the first human assay for approach-avoidance conflict akin to that of animal anxiety models. The findings bridge rodent and human research on passive avoidance and behavioral inhibition and furnish a framework for addressing the neuronal underpinnings of human anxiety disorders, where our data indicate a major role for the hippocampus.
•Human behavior in a spatial approach-avoidance conflict resembles animal behavior•Threat level in this context specifically engages anterior hippocampus•Hippocampal lesions reduce passive avoidance and inhibition•The study provides human evidence for an anterior hippocampus role in anxiety
Using a combined functional magnetic resonance imaging and hippocampus lesion approach, Bach et al. demonstrate that the human anterior hippocampus is engaged in monitoring threat level during approach-avoidance conflict, replicating and extending a rodent literature on models of anxiety.
The effects of striatal dopamine (DA) on behavior have been widely investigated over the past decades, with “phasic” burst firings considered as the key expression of a reward prediction error responsible for reinforcement learning. Less well studied is “tonic” DA, where putative functions include the idea that it is a regulator of vigor, incentive salience, disposition to exert an effort and a modulator of approach strategies. We present a model combining tonic and phasic DA to show how different outflows triggered by either intrinsically or extrinsically motivating stimuli dynamically affect the basal ganglia by impacting on a selection process this system performs on its cortical input. The model, which has been tested on the simulated humanoid robot iCub interacting with a mechatronic board, shows the putative functions ascribed to DA emerging from the combination of a standard computational mechanism coupled to a differential sensitivity to the presence of DA across the striatum.
basal ganglia; dopamine; selection; novelty; iCub; intrinsic motivation
•In theory, the motor system attenuates action-outcome perception to signal agency.•We use subliminal motor priming to test for the predicted motor locus of this effect.•The perceived intensity of an action-outcome is attenuated by compatible priming.•Compatible priming is known to enhance explicit agency judgements.•Sensory attenuation and agency inference depend on overlapping motoric signals.
The sense of control over the consequences of one’s actions depends on predictions about these consequences. According to an influential computational model, consistency between predicted and observed action consequences attenuates perceived stimulus intensity, which might provide a marker of agentic control. An important assumption of this model is that these predictions are generated within the motor system. However, previous studies of sensory attenuation have typically confounded motor-specific perceptual modulation with perceptual effects of stimulus predictability that are not specific to motor action. As a result, these studies cannot unambiguously attribute sensory attenuation to a motor locus. We present a psychophysical experiment on auditory attenuation that avoids this pitfall. Subliminal masked priming of motor actions with compatible prime–target pairs has previously been shown to modulate both reaction times and the explicit feeling of control over action consequences. Here, we demonstrate reduced perceived loudness of tones caused by compatibly primed actions. Importantly, this modulation results from a manipulation of motor processing and is not confounded by stimulus predictability. We discuss our results with respect to theoretical models of the mechanisms underlying sensory attenuation and subliminal motor priming.
NCE, negative compatibility effect; PCE, positive compatibility effect; Sensory attenuation; Sense of agency; Motor predictions; Subliminal motor priming; Negative compatibility effect
The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses—including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects—from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.
While studies of aging are widely framed in terms of their demarcation of degenerative processes, the brain provides a unique opportunity to uncover the adaptive effects of getting older. Though intuitively reasonable, that life-experience and wisdom should reside somewhere in human cortex, these features have eluded neuroscientific explanation. The present study utilizes a “Bayesian Brain” framework to motivate an analysis of cortical circuit processing. From a Bayesian perspective, the brain represents a model of its environment and offers predictions about the world, while responding, through changing synaptic strengths to novel interactions and experiences. We hypothesized that these predictive and updating processes are modified as we age, representing an optimization of neuronal architecture. Using novel sensory stimuli we demonstrate that synaptic connections of older brains resist trial by trial learning to provide a robust model of their sensory environment. These older brains are capable of processing a wider range of sensory inputs – representing experienced generalists. We thus explain how, contrary to a singularly degenerative point-of-view, aging neurobiological effects may be understood, in sanguine terms, as adaptive and useful.
The tendency to make unhealthy choices is hypothesized to be related to an individual's temporal discount rate, the theoretical rate at which they devalue delayed rewards. Furthermore, a particular form of temporal discounting, hyperbolic discounting, has been proposed to explain why unhealthy behavior can occur despite healthy intentions. We examine these two hypotheses in turn. We first systematically review studies which investigate whether discount rates can predict unhealthy behavior. These studies reveal that high discount rates for money (and in some instances food or drug rewards) are associated with several unhealthy behaviors and markers of health status, establishing discounting as a promising predictive measure. We secondly examine whether intention-incongruent unhealthy actions are consistent with hyperbolic discounting. We conclude that intention-incongruent actions are often triggered by environmental cues or changes in motivational state, whose effects are not parameterized by hyperbolic discounting. We propose a framework for understanding these state-based effects in terms of the interplay of two distinct reinforcement learning mechanisms: a “model-based” (or goal-directed) system and a “model-free” (or habitual) system. Under this framework, while discounting of delayed health may contribute to the initiation of unhealthy behavior, with repetition, many unhealthy behaviors become habitual; if health goals then change, habitual behavior can still arise in response to environmental cues. We propose that the burgeoning development of computational models of these processes will permit further identification of health decision-making phenotypes.
discounting; health; addiction; model-based; model-free; habit; preference reversal; hyperbolic
Introduction: We propose that active Bayesian inference—a general framework for decision-making—can equally be applied to interpersonal exchanges. Social cognition, however, entails special challenges. We address these challenges through a novel formulation of a formal model and demonstrate its psychological significance.
Method: We review relevant literature, especially with regards to interpersonal representations, formulate a mathematical model and present a simulation study. The model accommodates normative models from utility theory and places them within the broader setting of Bayesian inference. Crucially, we endow people's prior beliefs, into which utilities are absorbed, with preferences of self and others. The simulation illustrates the model's dynamics and furnishes elementary predictions of the theory.
Results: (1) Because beliefs about self and others inform both the desirability and plausibility of outcomes, in this framework interpersonal representations become beliefs that have to be actively inferred. This inference, akin to “mentalizing” in the psychological literature, is based upon the outcomes of interpersonal exchanges. (2) We show how some well-known social-psychological phenomena (e.g., self-serving biases) can be explained in terms of active interpersonal inference. (3) Mentalizing naturally entails Bayesian updating of how people value social outcomes. Crucially this includes inference about one's own qualities and preferences.
Conclusion: We inaugurate a Bayes optimal framework for modeling intersubject variability in mentalizing during interpersonal exchanges. Here, interpersonal representations are endowed with explicit functional and affective properties. We suggest the active inference framework lends itself to the study of psychiatric conditions where mentalizing is distorted.
free energy; active inference; value; evidence; surprise; self-organization; interpersonal; Bayesian
Asymmetry in distributions of potential outcomes (i.e. skewness), and whether those potential outcomes reflect gains or losses (i.e. their valence), both exert a powerful influence on value-based choice. How valence affects the impact of skewness on choice is unknown. Here by orthogonally manipulating the skewness and valence of economic stimuli we show that both have an influence on choice. We show that the influence of skewness on choice is independent of valence, both across and within subjects. fMRI data revealed skew-related activity in bilateral anterior insula and dorsomedial prefrontal cortex, which shows no interaction with valence. Further, the expression of skew-related activity depends on an individual’s preference for skewness, and this was again independent of valence-related preference. Our findings highlight the importance of skewness in choice and show that its influence, both behaviourally and neurally, is distinct from an influence of valence.
Fluid intelligence represents the capacity for flexible problem solving and rapid behavioral adaptation. Rewards drive flexible behavioral adaptation, in part via a teaching signal expressed as reward prediction errors in the ventral striatum, which has been associated with phasic dopamine release in animal studies. We examined a sample of 28 healthy male adults using multimodal imaging and biological parametric mapping with 1) functional magnetic resonance imaging during a reversal learning task and 2) in a subsample of 17 subjects also with positron emission tomography using 6-[18F]fluoro-L-DOPA to assess dopamine synthesis capacity. Fluid intelligence was measured using a battery of nine standard neuropsychological tests. Ventral striatal BOLD correlates of reward prediction errors were positively correlated with fluid intelligence and, in the right ventral striatum, also inversely correlated with dopamine synthesis capacity (FDOPA Kinapp). When exploring aspects of fluid intelligence, we observed that prediction error signaling correlates with complex attention and reasoning. These findings indicate that individual differences in the capacity for flexible problem solving may be driven by ventral striatal activation during reward-related learning, which in turn proved to be inversely associated with ventral striatal dopamine synthesis capacity.
prediction error; dopamine synthesis; fluid intelligence; ventral striatum; fMRI; PET
•We improve predictive validity of a general linear convolution method to analyse evoked SCR.•A constrained individual response function provides highest predictive validity.•This IRF is realised by a canonical SCRF together with its time derivative.•A high pass filter of 0.05 Hz cut-off frequency is optimal for analysis.•Non-linear models better reconstruct the observed time-series but have lower predictive validity.
Model-based analysis of psychophysiological signals is more robust to noise – compared to standard approaches – and may furnish better predictors of psychological state, given a physiological signal. We have previously established the improved predictive validity of model-based analysis of evoked skin conductance responses to brief stimuli, relative to standard approaches. Here, we consider some technical aspects of the underlying generative model and demonstrate further improvements. Most importantly, harvesting between-subject variability in response shape can improve predictive validity, but only under constraints on plausible response forms. A further improvement is achieved by conditioning the physiological signal with high pass filtering. A general conclusion is that precise modelling of physiological time series does not markedly increase predictive validity; instead, it appears that a more constrained model and optimised data features provide better results, probably through a suppression of physiological fluctuation that is not caused by the experiment.
Skin conductance responses (SCR); Galvanic skin response (GSR); Electrodermal activity (EDA); General linear convolution model (GLM); Generative model; Model inversion
Reward outcome signalling in the sensory cortex is held as important for linking stimuli to their consequences and for modulating perceptual learning in response to incentives. Evidence for reward outcome signalling has been found in sensory regions including the visual, auditory and somatosensory cortices across a range of different paradigms, but it is unknown whether the population of neurons signalling rewarding outcomes are the same as those processing predictive stimuli. We addressed this question using a multivariate analysis of high-resolution functional magnetic resonance imaging (fMRI), in a task where subjects were engaged in instrumental learning with visual predictive cues and auditory signalled reward feedback. We found evidence that outcome signals in sensory regions localise to the same areas involved in stimulus processing. These outcome signals are non-specific and we show that the neuronal populations involved in stimulus representation are not their exclusive target, in keeping with theoretical models of value learning. Thus, our results reveal one likely mechanism through which rewarding outcomes are linked to predictive sensory stimuli, a link that may be key for both reward and perceptual learning.
•Rewarding outcomes reactivate sensory regions involved in stimulus representation.•Within these regions reward is not directed specifically to stimulus-coding neurons.•This resembles a teaching signal predicted by reinforcement learning models.
Credit assignment; Reward; Value learning; fMRI adaptation
Standard theories of decision-making involving delayed outcomes predict that people should defer a punishment, whilst advancing a reward. In some cases, such as pain, people seem to prefer to expedite punishment, implying that its anticipation carries a cost, often conceptualized as ‘dread’. Despite empirical support for the existence of dread, whether and how it depends on prospective delay is unknown. Furthermore, it is unclear whether dread represents a stable component of value, or is modulated by biases such as framing effects. Here, we examine choices made between different numbers of painful shocks to be delivered faithfully at different time points up to 15 minutes in the future, as well as choices between hypothetical painful dental appointments at time points of up to approximately eight months in the future, to test alternative models for how future pain is disvalued. We show that future pain initially becomes increasingly aversive with increasing delay, but does so at a decreasing rate. This is consistent with a value model in which moment-by-moment dread increases up to the time of expected pain, such that dread becomes equivalent to the discounted expectation of pain. For a minority of individuals pain has maximum negative value at intermediate delay, suggesting that the dread function may itself be prospectively discounted in time. Framing an outcome as relief reduces the overall preference to expedite pain, which can be parameterized by reducing the rate of the dread-discounting function. Our data support an account of disvaluation for primary punishments such as pain, which differs fundamentally from existing models applied to financial punishments, in which dread exerts a powerful but time-dependent influence over choice.
People often prefer to ‘get pain out of the way’, treating pain in the future as more significant than pain now. One explanation, termed ‘dread’, is that anticipating pain is unpleasant or disadvantageous, rather like pain itself. Human brain imaging studies support the existence of dread, though it is unknown whether and how dread depends on the timing of future pain. We address this question by offering people decisions between moderately painful stimuli, and separately between imagined painful dental appointments occurring at different time points in the future, and use their choices to estimate dread. We show that future pain initially becomes more unpleasant when it is delayed, but as pain is moved further into the future, the effect of delay decreases. This is consistent with dread increasing as anticipated pain draws nearer, which is then combined with a general (and opposing) tendency to down-weight the significance of future events. We also show that dread can be attenuated by describing pain in terms of relief from an imagined even more severe pain. These observations reveal important principles about how people estimate the value of anticipated pain – relevant to a diverse range of human emotion and behavior.
Human choice behavior often reflects a competition between inflexible computationally efficient control on the one hand and a slower more flexible system of control on the other. This distinction is well captured by model-free and model-based reinforcement learning algorithms. Here, studying human subjects, we show it is possible to shift the balance of control between these systems by disruption of right dorsolateral prefrontal cortex, such that participants manifest a dominance of the less optimal model-free control. In contrast, disruption of left dorsolateral prefrontal cortex impaired model-based performance only in those participants with low working memory capacity.
•Disrupting right dorsolateral prefrontal cortex impairs flexible model-based choice•This drives behavior toward simpler, model-free control•Results provide causal evidence for neural underpinnings of flexible choice
Choices are governed by computationally simple as well as complex systems that compete with each other. In this Report, Smittenaar et al. present causal evidence that the dorsolateral prefrontal cortex is required for such complex, goal-directed decision making.
Decision-making involves two fundamental axes of control namely valence, spanning reward and punishment, and action, spanning invigoration and inhibition. We recently exploited a go/no-go task whose contingencies explicitly decouple valence and action to show that these axes are inextricably coupled during learning. This results in a disadvantage in learning to go to avoid punishment and in learning to no-go to obtain a reward. The neuromodulators dopamine and serotonin are likely to play a role in these asymmetries: Dopamine signals anticipation of future rewards and is also involved in an invigoration of motor responses leading to reward, but it also arbitrates between different forms of control. Conversely, serotonin is implicated in motor inhibition and punishment processing.
To investigate the role of dopamine and serotonin in the interaction between action and valence during learning.
We combined computational modeling with pharmacological manipulation in 90 healthy human volunteers, using levodopa and citalopram to affect dopamine and serotonin, respectively.
We found that, after administration of levodopa, action learning was less affected by outcome valence when compared with the placebo and citalopram groups. This highlights in this context a predominant effect of levodopa in controlling the balance between different forms of control. Citalopram had distinct effects, increasing participants’ tendency to perform active responses independent of outcome valence, consistent with a role in decreasing motor inhibition.
Our findings highlight the rich complexities of the roles played by dopamine and serotonin during instrumental learning.
Electronic supplementary material
The online version of this article (doi:10.1007/s00213-013-3313-4) contains supplementary material, which is available to authorized users.
Pavlovian; Instrumental; Reinforcement learning; Dopamine; Serotonin; Control
Senescence affects the ability to utilize information about the likelihood of rewards for optimal decision-making. In a human functional magnetic resonance imaging (fMRI) study, we show that healthy older adults have an abnormal signature of expected value resulting in an incomplete reward prediction error signal in the nucleus accumbens, a brain region receiving rich input projections from substantia nigra/ventral tegmental area (SN/VTA) dopaminergic neurons. Structural connectivity between SN/VTA and striatum measured with diffusion tensor imaging (DTI) was tightly coupled to inter-individual differences in the expression of this expected reward value signal. The dopamine precursor levodopa (L-DOPA) increased the task-based learning rate and task performance in some older adults to a level shown by young adults. Critically this drug-effect was linked to restoration of a canonical neural reward prediction error. Thus we identify a neurochemical signature underlying abnormal reward processing in older adults and show this can be modulated by L-DOPA.
Neural encoding of value-based stimuli is suggested to involve representations of summary statistics, including risk and expected value (EV). A more complex, but ecologically more common, context is when multiple risky options are evaluated together. However, it is unknown whether encoding related to option evaluation in these situations involves similar principles. Here we employed fMRI during a task that parametrically manipulated EV and risk in two simultaneously presented lotteries, both of which contained either gains or losses. We found representations of EV in medial prefrontal cortex and anterior insula, an encoding that was dependent on which option was chosen (i.e. chosen and unchosen EV) and whether the choice was over gains or losses. Parietal activity reflected whether the riskier or surer option was selected, whilst activity in a network of regions that also included parietal cortex reflected both combined risk and difference in risk for the two options. Our findings provide support for the idea that summary statistics underpin a representation of value-based stimuli, and further that these summary statistics undergo distinct forms of encoding.
•We examine choice between multiple risky options.•fMRI revealed encoding of value-based stimuli as expected value (EV) and risk.•Risk and EV underwent distinct types of encoding in distinct brain regions.•Neural and RT data were also consistent with model-free influences on choice.
Risk; Loss; fMRI; Approach–avoidance
Substantia nigra/ventral tegmental area (SN/VTA) subregions, defined by dopaminergic projections to the striatum, are differentially affected by health (e.g. normal aging) and disease (e.g. Parkinson's disease). This may have an impact on reward processing which relies on dopaminergic regions and circuits. We acquired diffusion tensor imaging (DTI) with probabilistic tractography in 30 healthy older adults to determine whether subregions of the SN/VTA could be delineated based on anatomical connectivity to the striatum. We found that a dorsomedial region of the SN/VTA preferentially connected to the ventral striatum whereas a more ventrolateral region connected to the dorsal striatum. These SN/VTA subregions could be characterised by differences in quantitative structural imaging parameters, suggesting different underlying tissue properties. We also observed that these connectivity patterns differentially mapped onto reward dependence personality trait. We show that tractography can be used to parcellate the SN/VTA into anatomically plausible and behaviourally meaningful compartments, an approach that may help future studies to provide a more fine-grained synopsis of pathological changes in the dopaminergic midbrain and their functional impact.
•We use DTI to segment the substantia nigra/ventral tegmental area (SN/VTA).•Dorsomedial and ventrolateral SN/VTA regions were defined by striatal connectivity.•R2* and fractional anisotropy values differed between SN/VTA subregions.•Connectivity patterns differentially mapped onto a reward personality trait.
Connectivity; Diffusion-weighted imaging; Reward; Segmentation; Substantia nigra
The idea that decisions alter preferences has had a considerable influence on the field of psychology and underpins cognitive dissonance theory. Yet it is unknown whether choice-induced changes in preferences are long lasting or are transient manifestations seen in the immediate aftermath of decisions. In the research reported here, we investigated whether these changes in preferences are fleeting or stable. Participants rated vacation destinations immediately after making hypothetical choices between destinations and 2.5 to 3 years later. We found that choices altered preferences both immediately and after the delay. These changes could not be accounted for by participants’ preexisting preferences, and they occurred only when participants made the choices themselves. Our findings provide evidence that making a decision can lead to enduring change in preferences.
decision making; cognitive dissonance; preferences; social cognition