scholarly journals A neuronal mechanism underlying decision-making deficits during hyperdopaminergic states

2017 ◽  
Author(s):  
Jeroen P.H. Verharen ◽  
Johannes W. de Jong ◽  
Theresia J.M. Roelofs ◽  
Christiaan F.M. Huffels ◽  
Ruud van Zessen ◽  
...  
Keyword(s):  
Decision Making ◽  
Substance Abuse ◽  
Prefrontal Cortex ◽  
Nucleus Accumbens ◽  
Multidisciplinary Approach ◽  
Prediction Errors ◽  
Risky Decision ◽  
Reward Prediction ◽  
Decision Making Processes ◽  
Mesencephalic Dopamine

AbstractHyperdopaminergic states in mental disorders are associated with disruptive deficits in decision-making. However, the precise contribution of topographically distinct mesencephalic dopamine pathways to decision-making processes remains elusive. Here we show, using a multidisciplinary approach, how hyperactivity of ascending projections from the ventral tegmental area (VTA) contributes to faulty decision-making in rats. Activation of the VTA-nucleus accumbens pathway leads to insensitivity to loss and punishment due to impaired processing of negative reward prediction errors. In contrast, activation of the VTA-prefrontal cortex pathway promotes risky decision-making without affecting the ability to choose the economically most beneficial option. Together, these findings show how malfunction of ascending VTA projections affects value-based decision-making, providing a mechanistic understanding of the reckless behaviors seen in substance abuse, mania, and after dopamine replacement therapy in Parkinson’s disease.

scholarly journals No unified reward prediction error in local field potentials from the human nucleus accumbens: evidence from epilepsy patients

2015 ◽  
Vol 114 (2) ◽  
pp. 781-792 ◽  
Author(s):  
Max-Philipp Stenner ◽  
Robb B. Rutledge ◽  
Tino Zaehle ◽  
Friedhelm C. Schmitt ◽  
Klaus Kopitzki ◽  
...  
Keyword(s):  
Decision Making ◽  
Nucleus Accumbens ◽  
Local Field ◽  
Local Field Potentials ◽  
Prediction Errors ◽  
Field Potentials ◽  
Reward Prediction ◽  
Outcome Valence ◽  
Economic Decision Making ◽  
The Difference

Functional magnetic resonance imaging (fMRI), cyclic voltammetry, and single-unit electrophysiology studies suggest that signals measured in the nucleus accumbens (Nacc) during value-based decision making represent reward prediction errors (RPEs), the difference between actual and predicted rewards. Here, we studied the precise temporal and spectral pattern of reward-related signals in the human Nacc. We recorded local field potentials (LFPs) from the Nacc of six epilepsy patients during an economic decision-making task. On each trial, patients decided whether to accept or reject a gamble with equal probabilities of a monetary gain or loss. The behavior of four patients was consistent with choices being guided by value expectations. Expected value signals before outcome onset were observed in three of those patients, at varying latencies and with nonoverlapping spectral patterns. Signals after outcome onset were correlated with RPE regressors in all subjects. However, further analysis revealed that these signals were better explained as outcome valence rather than RPE signals, with gamble gains and losses differing in the power of beta oscillations and in evoked response amplitudes. Taken together, our results do not support the idea that postsynaptic potentials in the Nacc represent a RPE that unifies outcome magnitude and prior value expectation. We discuss the generalizability of our findings to healthy individuals and the relation of our results to measurements of RPE signals obtained from the Nacc with other methods.

Emotion prediction errors guide socially adaptive behavior

2021 ◽  
Author(s):  
Joseph Heffner ◽  
Jae-Young Son ◽  
Oriel FeldmanHall
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Adaptive Behavior ◽  
Emotional Response ◽  
New Method ◽  
Prediction Errors ◽  
Emotional Experiences ◽  
Past Work ◽  
Reward Prediction ◽  
Expected Outcomes

People make decisions based on deviations from expected outcomes, known as prediction errors. Past work has focused on reward prediction errors, largely ignoring violations of expected emotional experiences—emotion prediction errors. We leverage a new method to measure real-time fluctuations in emotion as people decide to punish or forgive others. Across four studies (N=1,016), we reveal that emotion and reward prediction errors have distinguishable contributions to choice, such that emotion prediction errors exert the strongest impact during decision-making. We additionally find that a choice to punish or forgive can be decoded in less than a second from an evolving emotional response, suggesting emotions swiftly influence choice. Finally, individuals reporting significant levels of depression exhibit selective impairments in using emotion—but not reward—prediction errors. Evidence for emotion prediction errors potently guiding social behaviors challenge standard decision-making models that have focused solely on reward.

scholarly journals Differential effects of insular and ventromedial prefrontal cortex lesions on risky decision-making

Brain ◽  
2008 ◽  
Vol 131 (5) ◽  
pp. 1311-1322 ◽  
Author(s):  
L. Clark ◽  
A. Bechara ◽  
H. Damasio ◽  
M. R. F. Aitken ◽  
B. J. Sahakian ◽  
...  
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Ventromedial Prefrontal Cortex ◽  
Risky Decision Making ◽  
Risky Decision ◽  
Differential Effects

Abnormal prefrontal cortex processing of reward prediction errors in recently diagnosed patients with bipolar disorder and their unaffected relatives

2020 ◽  
Vol 22 (8) ◽  
pp. 849-859
Author(s):  
Julian Macoveanu ◽  
Hanne L. Kjærstad ◽  
Henry W. Chase ◽  
Sophia Frangou ◽  
Gitte M. Knudsen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Prefrontal Cortex ◽  
Prediction Errors ◽  
Reward Prediction

scholarly journals Positive reward prediction errors during decision-making strengthen memory encoding

2019 ◽  
Vol 3 (7) ◽  
pp. 719-732 ◽  
Author(s):  
Anthony I. Jang ◽  
Matthew R. Nassar ◽  
Daniel G. Dillon ◽  
Michael J. Frank
Keyword(s):  
Decision Making ◽  
Prediction Errors ◽  
Memory Encoding ◽  
Reward Prediction

scholarly journals The contribution of striatal pseudo-reward prediction errors to value-based decision-making

NeuroImage ◽  
2019 ◽  
Vol 193 ◽  
pp. 67-74 ◽  
Author(s):  
Ernest Mas-Herrero ◽  
Guillaume Sescousse ◽  
Roshan Cools ◽  
Josep Marco-Pallarés
Keyword(s):  
Decision Making ◽  
Prediction Errors ◽  
Reward Prediction

scholarly journals History of Suicide Attempt Is Associated with Reduced Medial Prefrontal Cortex Activity during Emotional Decision-Making among Men with Schizophrenia: An Exploratory fMRI Study

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Stéphane Potvin ◽  
Andràs Tikàsz ◽  
Stéphane Richard-Devantoy ◽  
Ovidiu Lungu ◽  
Alexandre Dumais
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Suicide Attempt ◽  
Medial Prefrontal Cortex ◽  
Suicidal Attempt ◽  
Risky Decision ◽  
Fmri Study ◽  
History Of ◽  
Brain Reward ◽  
Suicidal Ideas

Despite the high prevalence of suicidal ideas/attempts in schizophrenia, only a handful of neuroimaging studies have examined the neurobiological differences associated with suicide risk in this population. The main objective of the current exploratory study is to examine the neurofunctional correlates associated with a history of suicide attempt in schizophrenia, using a risky decision-making task, in order to show alterations in brain reward regions in this population. Thirty-two male outpatients with schizophrenia were recruited: 13 patients with (SCZ + S) and 19 without a history of suicidal attempt (SCZ − S). Twenty-one healthy men with no history of mental disorders or suicidal attempt/idea were also recruited. Participants were scanned using fMRI while performing the Balloon Analogue Risk Task. A rapid event-related fMRI paradigm was used, separating decision and outcome events, and the explosion probabilities were included as parametric modulators. The most important finding of this study is that SCZ + S patients had reduced activations of the medial prefrontal cortex during the success outcome event (with parametric modulation), relative to both SCZ − S patients and controls, as illustrated by a spatial conjunction analysis. These exploratory results suggest that a history of suicidal attempt in schizophrenia is associated with blunted brain reward activity during emotional decision-making.

Reduced autonomic responsiveness to gambling task losses in Huntington's disease

2004 ◽  
Vol 10 (2) ◽  
pp. 239-245 ◽  
Author(s):  
MEGHAN C. CAMPBELL ◽  
JULIE C. STOUT ◽  
PETER R. FINN
Keyword(s):  
Decision Making ◽  
Huntington's Disease ◽  
Huntington’S Disease ◽  
Decision Task ◽  
Healthy Controls ◽  
Gambling Task ◽  
Risky Decision ◽  
Skin Conductance Responses ◽  
Decision Making Processes

We examined the possible role of autonomic activity in Huntington's disease (HD) during a risky decision making task. Skin conductance responses (SCRs) of 15 HD participants and 16 healthy controls were measured while they performed a computerized version of the Simulated Gambling Task (SGT). The results replicated our previous finding of a performance decrement in HD, and showed that HD was associated with an altered pattern of SCRs during the risky decision task. Specifically, the healthy controls produced increased SCRs following selections from the disadvantageous decks and following losing selections. In contrast, the SCRs of the HD group did not differentiate between wins and losses. These findings indicate a reduced impact of loss on decision-making processes under risky conditions in HD. (JINS, 2004, 10, 239–245.)

scholarly journals Increased fronto-striatal reward prediction errors moderate decision making in obsessive–compulsive disorder

2017 ◽  
Vol 47 (7) ◽  
pp. 1246-1258 ◽  
Author(s):  
T. U. Hauser ◽  
R. Iannaccone ◽  
R. J. Dolan ◽  
J. Ball ◽  
J. Hättenschwiler ◽  
...  
Keyword(s):  
Decision Making ◽  
Obsessive Compulsive Disorder ◽  
Late Onset ◽  
Anterior Cingulate ◽  
Prediction Errors ◽  
Learning Mechanisms ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Reward Prediction ◽  
Reinforcement Learning Models

BackgroundObsessive–compulsive disorder (OCD) has been linked to functional abnormalities in fronto-striatal networks as well as impairments in decision making and learning. Little is known about the neurocognitive mechanisms causing these decision-making and learning deficits in OCD, and how they relate to dysfunction in fronto-striatal networks.MethodWe investigated neural mechanisms of decision making in OCD patients, including early and late onset of disorder, in terms of reward prediction errors (RPEs) using functional magnetic resonance imaging. RPEs index a mismatch between expected and received outcomes, encoded by the dopaminergic system, and are known to drive learning and decision making in humans and animals. We used reinforcement learning models and RPE signals to infer the learning mechanisms and to compare behavioural parameters and neural RPE responses of the OCD patients with those of healthy matched controls.ResultsPatients with OCD showed significantly increased RPE responses in the anterior cingulate cortex (ACC) and the putamen compared with controls. OCD patients also had a significantly lower perseveration parameter than controls.ConclusionsEnhanced RPE signals in the ACC and putamen extend previous findings of fronto-striatal deficits in OCD. These abnormally strong RPEs suggest a hyper-responsive learning network in patients with OCD, which might explain their indecisiveness and intolerance of uncertainty.

scholarly journals Phase of Firing Coding of Learning Variables across Prefrontal Cortex, Anterior Cingulate Cortex and Striatum during Feature Learning

2019 ◽  
Author(s):  
Benjamin Voloh ◽  
Mariann Oemisch ◽  
Thilo Womelsdorf
Keyword(s):  
Prefrontal Cortex ◽  
Anterior Cingulate Cortex ◽  
Long Range ◽  
Cingulate Cortex ◽  
Temporal Coding ◽  
Anterior Cingulate ◽  
Prediction Errors ◽  
Lateral Prefrontal Cortex ◽  
Firing Rates ◽  
Reward Prediction

AbstractThe prefrontal cortex and striatum form a recurrent network whose spiking activity encodes multiple types of learning-relevant information. This spike-encoded information is evident in average firing rates, but finer temporal coding might allow multiplexing and enhanced readout across the connected the network. We tested this hypothesis in the fronto-striatal network of nonhuman primates during reversal learning of feature values. We found that neurons encoding current choice outcomes, outcome prediction errors, and outcome history in their firing rates also carried significant information in their phase-of-firing at a 10-25 Hz beta frequency at which they synchronized across lateral prefrontal cortex, anterior cingulate cortex and striatum. The phase-of-firing code exceeded information that could be obtained from firing rates alone, was strong for inter-areal connections, and multiplexed information at three different phases of the beta cycle that were offset from the preferred spiking phase of neurons. Taken together, these findings document the multiplexing of three different types of information in the phase-of-firing at an interareally shared beta oscillation frequency during goal-directed behavior.HighlightsLateral prefrontal cortex, anterior cingulate cortex and striatum show phase-of-firing encoding for outcome, outcome history and reward prediction errors.Neurons with phase-of-firing code synchronize long-range at 10-25 Hz.Spike phases encoding reward prediction errors deviate from preferred synchronization phases.Anterior cingulate cortex neurons show strongest long-range effects.

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