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

2020 ◽  
Author(s):  
Toby Wise ◽  
Yunzhe Liu ◽  
Fatima Chowdhury ◽  
Raymond J. Dolan
Keyword(s):  
Learning Task ◽  
Harm Avoidance ◽  
Neural Mechanisms ◽  
Avoidance Behaviour ◽  
Potential Candidate ◽  
Trial And Error ◽  
Aversive Learning ◽  
Outcome Valence ◽  
Alternative Future ◽  
Hippocampal Theta

AbstractHarm 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.

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

2021 ◽  
Vol 7 (31) ◽  
pp. eabf9616
Author(s):  
Toby Wise ◽  
Yunzhe Liu ◽  
Fatima Chowdhury ◽  
Raymond J. Dolan
Keyword(s):  
Mental Model ◽  
Learning Task ◽  
Harm Avoidance ◽  
Neural Mechanisms ◽  
Trial And Error ◽  
Aversive Learning ◽  
Theta Power ◽  
Model Based ◽  
Outcome Valence ◽  
Hippocampal Theta

Harm avoidance is critical for survival, yet little is known regarding the neural mechanisms supporting avoidance in the absence of trial-and-error experience. Flexible avoidance may be supported by a mental model (i.e., model-based), a process for which neural reactivation and sequential replay have emerged as candidate mechanisms. During an aversive learning task, combined with magnetoencephalography, we show prospective and retrospective reactivation during planning and learning, respectively, coupled to evidence for sequential replay. Specifically, when individuals plan in an aversive context, we find preferential reactivation of subsequently chosen goal states. Stronger reactivation is associated with greater hippocampal theta power. At outcome receipt, unchosen goal states are reactivated regardless of outcome valence. Replay of paths leading to goal states was modulated by outcome valence, with aversive outcomes associated with stronger reverse replay than safe outcomes. Our findings are suggestive of avoidance involving simulation of unexperienced states through hippocampally mediated reactivation and replay.

Discriminative aversive learning and amygdala responsivity is enhanced in mice with reduced serotonin transporter activity

2017 ◽  
Author(s):  
João Lima ◽  
Trevor Sharp ◽  
Amy M. Taylor ◽  
David M. Bannerman ◽  
Stephen B. McHugh
Keyword(s):  
Discrimination Learning ◽  
Learning Task ◽  
Plasticity Theory ◽  
Fear Learning ◽  
Aversive Learning ◽  
Hemodynamic Responses ◽  
Knock Out ◽  
Auditory Cue ◽  
Network Plasticity ◽  
Knock Out Mice

AbstractThe serotonin (5-HT) transporter (5-HTT) regulates 5-HT availability at the synapse. Low or null 5-HTT expression results in increased 5-HT availability and has been reported to produce anxious and depressive phenotypes, although this remains highly controversial despite two decades of investigation. Paradoxically, SSRIs, which also increase 5-HT availability, reduce the symptoms of anxiety and depression. An emerging ‘network plasticity’ theory of 5-HT function argues that, rather than influencing mood directly, increasing 5-HT availability enhances learning about emotionally-significant events but evidence supporting this theory is inconclusive. Here, we tested one key prediction of this theory: that increased 5-HT availability enhances aversive learning. In experiment 1, we trained 5-HTT knock-out mice (5-HTTKO), which have increased 5-HT availability, and wild-type mice (WT) on an aversive discrimination learning task in which one auditory cue was paired with an aversive outcome whereas a second auditory cue was not. Simultaneously we recorded neuronal and hemodynamic responses from the amygdala, a brain region necessary for aversive learning. 5-HTTKO mice exhibited superior discrimination learning than WTs, and had stronger theta-frequency neuronal oscillations and larger amygdala hemodynamic responses to the aversive cues, which predicted the extent of learning. In experiment 2, we found that acute SSRI treatment (in naïve non-transgenic mice), given specifically before fear learning sessions, enhanced subsequent fear memory recall. Collectively, our data demonstrate that reducing 5-HTT activity (and thereby increasing 5-HT availability) enhances amygdala responsivity to aversive events and facilitates learning for emotionally-relevant cues. Our findings support the network plasticity theory of 5-HT function.

Serotonergic modulation of cognition; An acute challenge

2017 ◽  
Vol 41 (S1) ◽  
pp. S350-S350
Author(s):  
N. Skandali ◽  
J. Rowe ◽  
J. Deakin ◽  
T. Robbins ◽  
B. Sahakian
Keyword(s):  
Instrumental Learning ◽  
Learning Task ◽  
Treated Group ◽  
Stop Signal ◽  
Acute Administration ◽  
Double Blind ◽  
Outcome Valence ◽  
Lower Accuracy ◽  
Relevant Dose ◽  
Stop Signal Reaction Time

AbstractSerotonin is well known to affect the multifaceted construct of impulsivity. Lowering brain serotonin levels is shown to increase impulsive choice in delay-discounting tasks (1) but improves response inhibition in stop-signal paradigms. (2) Administration of the antidepressant citalopram in healthy people increases tendency to perform go choices in a Go/No-Go task independent of outcome valence (3). It is rather unclear thought how serotonergic neurotransmission affects several aspects of cognition. We administered a single dose of 20 mg escitalopram, a selective serotonin reuptake inhibitor, to 66 healthy participants, aged 18–45 years old, in a double-blind, randomized, placebo-controlled, parallel-groups study. Acute escitalopram administration had a beneficial effect on inhibitory control with reduced stop-signal reaction time observed in the treatment group. Participants made significantly more errors in a probabilistic learning task and had lower accuracy during the discrimination stage in an instrumental learning task thus indicating a learning impairment. More errors in the CANTAB intra-extra dimensional set shift task were also observed in the escitalopram-treated group. Our findings following acute administration of a clinically relevant dose of escitalopram show a dissociate role for serotonin in modulating cognition mediated by a potentially differential modulation of fronto-striatal loops.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Dynamic integration of conceptual information during learning

2018 ◽  
Author(s):  
Marika C. Inhoff ◽  
Laura A. Libby ◽  
Takao Noguchi ◽  
Bradley C. Love ◽  
Charan Ranganath
Keyword(s):  
Computational Model ◽  
Learning Task ◽  
Higher Order ◽  
Neural Mechanisms ◽  
Semantic Features ◽  
Learning Problem ◽  
Conceptual Information ◽  
Conceptual Representations ◽  
Model Based ◽  
Learning Rates

AbstractThe development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

The Event-Related Potentials Responding to Outcome Valence and Expectancy Violation during Feedback Processing

2020 ◽  
Author(s):  
Yan Gu ◽  
Tianliang Liu ◽  
Xuemeng Zhang ◽  
Quanshan Long ◽  
Na Hu ◽  
...  
Keyword(s):  
Prediction Error ◽  
Predictive Accuracy ◽  
Event Related Potentials ◽  
Learning Task ◽  
Absolute Size ◽  
Feedback Processing ◽  
Expectancy Violation ◽  
Outcome Valence ◽  
Related Potentials ◽  
The Impact

Abstract Feedback-related negativity (FRN) is believed to encode reward prediction error (RPE), a term describing whether the outcome is better or worse than expected. However, some studies suggest that it may reflect unsigned prediction error (UPE) instead. Some disagreement remains as to whether FRN is sensitive to the interaction of outcome valence and prediction error (PE) or merely responsive to the absolute size of PE. Moreover, few studies have compared FRN in appetitive and aversive domains to clarify the valence effect or examine PE’s quantitative modulation. To investigate the impact of valence and parametrical PE on FRN, we varied the prediction and feedback magnitudes within a probabilistic learning task in valence (gain and loss domains, Experiment 1) and non-valence contexts (pure digits, Experiment 2). Experiment 3 was identical to Experiment 1 except that some blocks emphasized outcome valence, while others highlighted predictive accuracy. Experiments 1 and 2 revealed a UPE encoder; Experiment 3 found an RPE encoder when valence was emphasized and a UPE encoder when predictive accuracy was highlighted. In this investigation, we demonstrate that FRN is sensitive to outcome valence and expectancy violation, exhibiting a preferential response depending on the dimension that is emphasized.

Neural mechanisms of the nucleus accumbens circuit in reward and aversive learning

2016 ◽  
Vol 108 ◽  
pp. 1-5 ◽  
Author(s):  
Takatoshi Hikida ◽  
Makiko Morita ◽  
Tom Macpherson
Keyword(s):  
Nucleus Accumbens ◽  
Neural Mechanisms ◽  
Aversive Learning

scholarly journals Greater mindful eating practice is associated with better reversal learning

2017 ◽  
Author(s):  
Lieneke Katharina Janssen ◽  
Iris Duif ◽  
Ilke van Loon ◽  
Jeanne de Vries ◽  
Anne Speckens ◽  
...  
Keyword(s):  
Reversal Learning ◽  
Eating Habits ◽  
Behavioral Flexibility ◽  
Learning Task ◽  
Mindfulness Practice ◽  
Clinical Population ◽  
Group Differences ◽  
Mindful Eating ◽  
Outcome Valence ◽  
Control Intervention

Mindfulness-based interventions are thought to reduce compulsive behavior such as overeating by promoting behavioral flexibility. Here the main aim was to provide support for mindfulness-mediated improvements in reversal learning, a direct measure of behavioral flexibility. We investigated whether an 8-week mindful eating intervention improved outcome-based reversal learning relative to an educational cooking (i.e., active control) intervention in a non-clinical population. Sixty-five healthy participants with a wide BMI range (19–35 kg/m2), who were motivated to change their eating habits, performed a deterministic reversal learning task that enabled the investigation of reward- and punishment-based reversal learning at baseline and following the intervention. No group differences in reversal learning were observed. However, time invested in the mindful eating, but not the educational cooking intervention correlated positively with changes in reversal learning, in a manner independent of outcome valence. These findings suggest that greater amount of mindfulness practice can lead to increased behavioral flexibility, which, in turn, might help overcome compulsive eating in clinical populations.

scholarly journals Feedback-related potentials and oscillations during trial and error learning in Parkinson's disease

2021 ◽  
Author(s):  
Laura Vinales ◽  
Rene Quilodran ◽  
Emmanuel Procyk
Keyword(s):  
Parkinson Disease ◽  
Positive Feedback ◽  
Performance Monitoring ◽  
Neurological Diseases ◽  
Learning Task ◽  
Trial And Error ◽  
Time Frequency ◽  
Oscillatory Dynamics ◽  
Related Potentials ◽  
Error Learning

Electrophysiological markers of performance monitoring are thought to reflect functioning of dedicated neural networks and neuromodulatory systems. Whether and how these markers are altered in neurological diseases and whether they can reflect particular cognitive deficits remains to be confirmed. Here we first tested whether the frontal medial feedback-related potential, evoked during a trial and error learning task, is changed in early Parkinson disease patients compared to control subjects. The potential was not changed in amplitude and discriminated negative and positive feedback as in controls. Feedback-related markers in Parkinsons patients also appeared in time-frequency analyses, unaltered in theta (3-7 Hz) band but reduced in beta (20-30 Hz) oscillations for positive feedback. Beta oscillations power appeared to be dramatically globally reduced during the task. Overall, our results show that Beta oscillation markers of performance monitoring captured by EEG are selectively altered in Parkinson disease patients, and that they are accompanied by changes in task-related oscillatory dynamics.

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