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 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.

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 Prefrontal Cortex Fails to Learn from Reward Prediction Errors in Alcohol Dependence

2010 ◽  
Vol 30 (22) ◽  
pp. 7749-7753 ◽  
Author(s):  
S. Q. Park ◽  
T. Kahnt ◽  
A. Beck ◽  
M. X. Cohen ◽  
R. J. Dolan ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Alcohol Dependence ◽  
Prediction Errors ◽  
Reward Prediction

scholarly journals Behavioural variability and cortical electrophysiological signals depend on recent outcomes during human reinforcement motor learning

2021 ◽  
Author(s):  
Patrick Wiegel ◽  
Meaghan Elizabeth Spedden ◽  
Christina Ramsenthaler ◽  
Mikkel Malling Beck ◽  
Jesper Lundbye-Jensen
Keyword(s):  
Prefrontal Cortex ◽  
Motor Learning ◽  
Potential Role ◽  
Neural Oscillations ◽  
Prediction Errors ◽  
Movement Variability ◽  
Reward Prediction ◽  
Electrophysiological Signals ◽  
History Of ◽  
High Beta

AbstractThe history of our actions and the outcomes of these represent important information, which can inform choices, and efficiently guide future behaviour. While unsuccessful (S-) outcomes are expected to lead to more explorative motor states and increased behavioural variability, successful (S+) outcomes lead to reinforcement of the previous action and thus exploitation. Here, we show that during reinforcement motor learning, humans attribute different values to previous actions when they experience S- vs. S+ outcomes. Behavioural variability after S- outcomes is influenced more by the previous outcomes compared to what is observed after S+ outcomes. Using electroencephalography, we show that neural oscillations of the prefrontal cortex encode the level of reinforcement (high beta frequencies) and reflect the detection of reward prediction errors (theta frequencies). The results suggest that S+ experiences ‘overwrite’ previous motor states to a greater extent than S- experiences and that modulations in neural oscillations in the prefrontal cortex play a potential role in encoding the (changes in) movement variability state during reinforcement motor learning.

scholarly journals The Medial Prefrontal Cortex Shapes Dopamine Reward Prediction Errors under State Uncertainty

Neuron ◽  
2018 ◽  
Vol 98 (3) ◽  
pp. 616-629.e6 ◽  
Author(s):  
Clara Kwon Starkweather ◽  
Samuel J. Gershman ◽  
Naoshige Uchida
Keyword(s):  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Prediction Errors ◽  
Reward Prediction ◽  
State Uncertainty

scholarly journals Subgoal- and Goal-related Reward Prediction Errors in Medial Prefrontal Cortex

2019 ◽  
Vol 31 (1) ◽  
pp. 8-23 ◽  
Author(s):  
José J. F. Ribas-Fernandes ◽  
Danesh Shahnazian ◽  
Clay B. Holroyd ◽  
Matthew M. Botvinick
Keyword(s):  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Animal Behavior ◽  
Prediction Error ◽  
Prediction Errors ◽  
Task Context ◽  
Reward Prediction ◽  
Human Participants ◽  
Superordinate Goals ◽  
Different Levels

A longstanding view of the organization of human and animal behavior holds that behavior is hierarchically organized—in other words, directed toward achieving superordinate goals through the achievement of subordinate goals or subgoals. However, most research in neuroscience has focused on tasks without hierarchical structure. In past work, we have shown that negative reward prediction error (RPE) signals in medial prefrontal cortex (mPFC) can be linked not only to superordinate goals but also to subgoals. This suggests that mPFC tracks impediments in the progression toward subgoals. Using fMRI of human participants engaged in a hierarchical navigation task, here we found that mPFC also processes positive prediction errors at the level of subgoals, indicating that this brain region is sensitive to advances in subgoal completion. However, when subgoal RPEs were elicited alongside with goal-related RPEs, mPFC responses reflected only the goal-related RPEs. These findings suggest that information from different levels of hierarchy is processed selectively, depending on the task context.

Reward Prediction Errors Drive Declarative Learning Irrespective of Agency

2020 ◽  
Author(s):  
Kate Ergo ◽  
Luna De Vilder ◽  
Esther De Loof ◽  
Tom Verguts
Keyword(s):  
Learning Theory ◽  
Learning Effect ◽  
Steady Increase ◽  
Prediction Errors ◽  
Experimental Paradigm ◽  
Reward Prediction ◽  
Declarative Learning

Recent years have witnessed a steady increase in the number of studies investigating the role of reward prediction errors (RPEs) in declarative learning. Specifically, in several experimental paradigms RPEs drive declarative learning; with larger and more positive RPEs enhancing declarative learning. However, it is unknown whether this RPE must derive from the participant’s own response, or whether instead any RPE is sufficient to obtain the learning effect. To test this, we generated RPEs in the same experimental paradigm where we combined an agency and a non-agency condition. We observed no interaction between RPE and agency, suggesting that any RPE (irrespective of its source) can drive declarative learning. This result holds implications for declarative learning theory.

scholarly journals Involvement of the nuclear factor-κB transcriptional complex in prefrontal cortex immune activation in bipolar disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kaitlyn M. Roman ◽  
Aaron K. Jenkins ◽  
David A. Lewis ◽  
David W. Volk
Keyword(s):  
Bipolar Disorder ◽  
Prefrontal Cortex ◽  
Immune Activation ◽  
Family Members ◽  
Nuclear Factor Κb ◽  
Nuclear Factor ◽  
Transcript Levels ◽  
Immune Related Genes ◽  
Transcriptional Complex ◽  
Shared Risk

AbstractBipolar disorder and schizophrenia have multiple clinical and genetic features in common, including shared risk associated with overlapping susceptibility loci in immune-related genes. Higher activity of the nuclear factor-κB (NF-κB) transcription factor complex, which regulates the transcription of multiple immune markers, has been reported to contribute to immune activation in the prefrontal cortex in schizophrenia. These findings suggest the hypothesis that elevated NF-κB activity is present in the prefrontal cortex in bipolar disorder in a manner similar to that seen in schizophrenia. Therefore, we quantified levels of NF-κB-related mRNAs in the prefrontal cortex of 35 matched pairs of bipolar disorder and unaffected comparison subjects using quantitative PCR. We found that transcript levels were higher in the prefrontal cortex of bipolar disorder subjects for several NF-κB family members, NF-κB activation receptors, and NF-κB-regulated mRNAs, and were lower for an NF-κB inhibitor. Transcript levels for NF-κB family members, NF-κB activation receptors, and NF-κB-regulated mRNAs levels were also highly correlated with each other. This pattern of elevated transcript levels for NF-κB-related markers in bipolar disorder is similar to that previously reported in schizophrenia, suggesting that cortical immune activation is a shared pathophysiological feature between the two disorders.

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