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https://www.readbyqxmd.com/read/28808037/separate-mesocortical-and-mesolimbic-pathways-encode-effort-and-reward-learning-signals
#1
Tobias U Hauser, Eran Eldar, Raymond J Dolan
Optimal decision making mandates organisms learn the relevant features of choice options. Likewise, knowing how much effort we should expend can assume paramount importance. A mesolimbic network supports reward learning, but it is unclear whether other choice features, such as effort learning, rely on this same network. Using computational fMRI, we show parallel encoding of effort and reward prediction errors (PEs) within distinct brain regions, with effort PEs expressed in dorsomedial prefrontal cortex and reward PEs in ventral striatum...
August 14, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28804467/learning-about-expectation-violation-from-prediction-error-paradigms-a-meta-analysis-on-brain-processes-following-a-prediction-error
#2
Lisa D'Astolfo, Winfried Rief
Modifying patients' expectations by exposing them to expectation violation situations (thus maximizing the difference between the expected and the actual situational outcome) is proposed to be a crucial mechanism for therapeutic success for a variety of different mental disorders. However, clinical observations suggest that patients often maintain their expectations regardless of experiences contradicting their expectations. It remains unclear which information processing mechanisms lead to modification or persistence of patients' expectations...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28755237/uncertainty-quantification-and-sensitivity-analysis-of-an-arterial-wall-mechanics-model-for-evaluation-of-vascular-drug-therapies
#3
Maarten H G Heusinkveld, Sjeng Quicken, Robert J Holtackers, Wouter Huberts, Koen D Reesink, Tammo Delhaas, Bart Spronck
Quantification of the uncertainty in constitutive model predictions describing arterial wall mechanics is vital towards non-invasive assessment of vascular drug therapies. Therefore, we perform uncertainty quantification to determine uncertainty in mechanical characteristics describing the vessel wall response upon loading. Furthermore, a global variance-based sensitivity analysis is performed to pinpoint measurements that are most rewarding to be measured more precisely. We used previously published carotid diameter-pressure and intima-media thickness (IMT) data (measured in triplicate), and Holzapfel-Gasser-Ogden models...
July 28, 2017: Biomechanics and Modeling in Mechanobiology
https://www.readbyqxmd.com/read/28753634/dissociating-error-based-and-reinforcement-based-loss-functions-during-sensorimotor-learning
#4
Joshua G A Cashaback, Heather R McGregor, Ayman Mohatarem, Paul L Gribble
It has been proposed that the sensorimotor system uses a loss (cost) function to evaluate potential movements in the presence of random noise. Here we test this idea in the context of both error-based and reinforcement-based learning. In a reaching task, we laterally shifted a cursor relative to true hand position using a skewed probability distribution. This skewed probability distribution had its mean and mode separated, allowing us to dissociate the optimal predictions of an error-based loss function (corresponding to the mean of the lateral shifts) and a reinforcement-based loss function (corresponding to the mode)...
July 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28739583/tonic-or-phasic-stimulation-of-dopaminergic-projections-to-prefrontal-cortex-causes-mice-to-maintain-or-deviate-from-previously-learned-behavioral-strategies
#5
Ian T Ellwood, Tosha Patel, Varun Wadia, Anthony T Lee, Alayna T Liptak, Kevin J Bender, Vikaas S Sohal
Dopamine neurons in the ventral tegmental area (VTA) encode reward prediction errors and can drive reinforcement learning through their projections to striatum, but much less is known about their projections to prefrontal cortex (PFC). Here we studied these projections, and observed phasic VTA-PFC fiber photometry signals following the delivery of rewards. Next, we studied how optogenetic stimulation of these projections affects behavior, using conditioned place preference (CPP), and a task in which mice learn associations between cues and food rewards, then use those associations to make choices...
July 24, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28736133/knockdown-of-zif268-in-the-posterior-dorsolateral-striatum-does-not-enduringly-disrupt-a-response-memory-of-a-rewarded-t-maze-task
#6
Emma N Cahill, George H Vousden, Marc T J Exton-McGuinness, Ian R C Beh, Casey B Swerner, Matej Macak, Sameera Abas, Cameron C Cole, Brian F Kelleher, Barry J Everitt, Amy L Milton
Under certain conditions pavlovian memories undergo reconsolidation, whereby the reactivated memory can be disrupted by manipulations such as knockdown of zif268. For instrumental memories, reconsolidation disruption is less well established. Our previous, preliminary data identified that there was an increase in Zif268 in the posterior dorsolateral striatum (pDLS) after expression of an instrumental habit-like 'response' memory, but not an instrumental goal-directed 'place' memory on a T-maze task. Here, the requirement for Zif268 in the reconsolidation of a response memory was tested by knockdown of Zif268, using antisense oligodeoxynucleotide infusion into the pDLS, at memory reactivation...
July 21, 2017: Neuroscience
https://www.readbyqxmd.com/read/28699296/long-lasting-contribution-of-dopamine-in-the-nucleus-accumbens-core-but-not-dorsal-lateral-striatum-to-sign-tracking
#7
Kurt M Fraser, Patricia H Janak
The attribution of incentive salience to reward-paired cues is dependent on dopamine release in the nucleus accumbens core (NAcC). These dopamine signals conform to traditional reward-prediction error signals and have been shown to diminish with time. Here we examined whether the diminishing dopamine signal in the NAcC has functional implications for the expression of sign-tracking, a Pavlovian conditioned response indicative of the attribution of incentive salience to reward-paired cues. Food-restricted male Sprague Dawley rats were trained in a Pavlovian paradigm in which an insertable lever predicted delivery of food reward in a nearby food cup...
August 2017: European Journal of Neuroscience
https://www.readbyqxmd.com/read/28689983/a-novel-neural-prediction-error-found-in-anterior-cingulate-cortex-ensembles
#8
James Michael Hyman, Clay Brian Holroyd, Jeremy Keith Seamans
The function of the anterior cingulate cortex (ACC) remains controversial, yet many theories suggest a role in behavioral adaptation, partly because a robust event-related potential, the feedback-related negativity (FN), is evoked over the ACC whenever expectations are violated. We recorded from the ACC as rats performed a task identical to one that reliably evokes an FN in humans. A subset of neurons was found that encoded expected outcomes as abstract outcome representations. The degree to which a reward/non-reward outcome representation emerged during a trial depended on the history of outcomes that preceded it...
July 19, 2017: Neuron
https://www.readbyqxmd.com/read/28684734/spatiotemporal-neural-characterization-of-prediction-error-valence-and-surprise-during-reward-learning-in-humans
#9
Elsa Fouragnan, Filippo Queirazza, Chris Retzler, Karen J Mullinger, Marios G Philiastides
Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations)...
July 6, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28678984/association-of-neural-and-emotional-impacts-of-reward-prediction-errors-with-major-depression
#10
Robb B Rutledge, Michael Moutoussis, Peter Smittenaar, Peter Zeidman, Tanja Taylor, Louise Hrynkiewicz, Jordan Lam, Nikolina Skandali, Jenifer Z Siegel, Olga T Ousdal, Gita Prabhu, Peter Dayan, Peter Fonagy, Raymond J Dolan
Importance: Major depressive disorder (MDD) is associated with deficits in representing reward prediction errors (RPEs), which are the difference between experienced and predicted reward. Reward prediction errors underlie learning of values in reinforcement learning models, are represented by phasic dopamine release, and are known to affect momentary mood. Objective: To combine functional neuroimaging, computational modeling, and smartphone-based large-scale data collection to test, in the absence of learning-related concerns, the hypothesis that depression attenuates the impact of RPEs...
August 1, 2017: JAMA Psychiatry
https://www.readbyqxmd.com/read/28676744/trace-conditioning-in-drosophila-induces-associative-plasticity-in-mushroom-body-kenyon-cells-and-dopaminergic-neurons
#11
Kristina V Dylla, Georg Raiser, C Giovanni Galizia, Paul Szyszka
Dopaminergic neurons (DANs) signal punishment and reward during associative learning. In mammals, DANs show associative plasticity that correlates with the discrepancy between predicted and actual reinforcement (prediction error) during classical conditioning. Also in insects, such as Drosophila, DANs show associative plasticity that is, however, less understood. Here, we study associative plasticity in DANs and their synaptic partners, the Kenyon cells (KCs) in the mushroom bodies (MBs), while training Drosophila to associate an odorant with a temporally separated electric shock (trace conditioning)...
2017: Frontiers in Neural Circuits
https://www.readbyqxmd.com/read/28654358/predicting-motivation-computational-models-of-pfc-can-explain-neural-coding-of-motivation-and-effort-based-decision-making-in-health-and-disease
#12
Eliana Vassena, James Deraeve, William H Alexander
Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial pFC (MPFC) and dorsolateral pFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W...
June 27, 2017: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28638322/neural-signals-related-to-outcome-evaluation-are-stronger-in-ca1-than-ca3
#13
Sung-Hyun Lee, Namjung Huh, Jong Won Lee, Jeong-Wook Ghim, Inah Lee, Min W Jung
We have shown previously that CA1 conveys significant neural signals necessary to update value of the chosen target, namely chosen value and reward signals. To better understand hippocampal neural processes related to valuation, we compared chosen value- and reward-related neural activity between the CA3 and CA1 regions. Single units were recorded with tetrodes from the dorsal CA3 and CA1 regions of rats performing a dynamic foraging task, and chosen value- and reward-related neural activity was estimated using a reinforcement learning model and multiple regression analyses...
2017: Frontiers in Neural Circuits
https://www.readbyqxmd.com/read/28633363/development-initial-testing-and-challenges-of-an-ecologically-valid-reward-prediction-error-fmri-task-for-alcoholism
#14
Anita Cservenka, Kelly E Courtney, Dara G Ghahremani, Kent E Hutchison, Lara A Ray
Aims: To advance translational studies of the role of reward prediction error (PE) in alcohol use disorder, the present study sought to develop and conduct an initial test of an alcohol-specific PE task paradigm using functional magnetic resonance imaging in humans. Methods: Alcohol dependent or social drinkers received small tastes of their preferred alcohol beverage or control beverage, with preceding visual cues indicating whether alcohol (or water) would be delivered...
June 14, 2017: Alcohol and Alcoholism: International Journal of the Medical Council on Alcoholism
https://www.readbyqxmd.com/read/28601965/event-related-potentials-reflect-impaired-temporal-interval-learning-following-haloperidol-administration
#15
Sarah E Forster, Patrick Zirnheld, Anantha Shekhar, Stuart R Steinhauer, Brian F O'Donnell, William P Hetrick
BACKGROUND: Signals carried by the mesencephalic dopamine system and conveyed to anterior cingulate cortex are critically implicated in probabilistic reward learning and performance monitoring. A common evaluative mechanism purportedly subserves both functions, giving rise to homologous medial frontal negativities in feedback- and response-locked event-related brain potentials (the feedback-related negativity (FRN) and the error-related negativity (ERN), respectively), reflecting dopamine-dependent prediction error signals to unexpectedly negative events...
June 10, 2017: Psychopharmacology
https://www.readbyqxmd.com/read/28579691/does-prediction-error-drive-one-shot-declarative-learning
#16
Andrea Greve, Elisa Cooper, Alexander Kaula, Michael C Anderson, Richard Henson
The role of prediction error (PE) in driving learning is well-established in fields such as classical and instrumental conditioning, reward learning and procedural memory; however, its role in human one-shot declarative encoding is less clear. According to one recent hypothesis, PE reflects the divergence between two probability distributions: one reflecting the prior probability (from previous experiences) and the other reflecting the sensory evidence (from the current experience). Assuming unimodal probability distributions, PE can be manipulated in three ways: (1) the distance between the mode of the prior and evidence, (2) the precision of the prior, and (3) the precision of the evidence...
June 2017: Journal of Memory and Language
https://www.readbyqxmd.com/read/28575424/association-between-habenula-dysfunction-and-motivational-symptoms-in-unmedicated-major-depressive-disorder
#17
Wen-Hua Liu, Vincent Valton, Ling-Zhi Wang, Yu-Hua Zhu, Jonathan P Roiser
The lateral habenula plays a central role in reward and punishment processing and has been suggested to drive the cardinal symptom of anhedonia in depression. This hypothesis is largely based on observations of habenula hypermetabolism in animal models of depression, but the activity of habenula and its relationship with clinical symptoms in patients with depression remains unclear. High-resolution functional magnetic resonance imaging (fMRI) and computational modelling were used to investigate the activity of the habenula during a probabilistic reinforcement learning task with rewarding and punishing outcomes in 21 unmedicated patients with major depression and 17 healthy participants...
May 29, 2017: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/28547127/the-relationship-between-outcome-prediction-and-cognitive-fatigue-a-convergence-of-paradigms
#18
G R Wylie, H M Genova, J DeLuca, E Dobryakova
Cognitive fatigue is common after strenuous cognitive effort. A large body of literature has implicated a network of brain areas in fatigue, including the basal ganglia and cortical areas including ventro-medal prefrontal cortex and anterior cingulate cortex (ACC). Furthermore, the ACC has been shown to be involved in processes such as error and conflict monitoring, outcome prediction, and effort processing. Thus, the ACC appears to be one common denominator between clinical work on fatigue and research on outcome prediction and effort...
May 25, 2017: Cognitive, Affective & Behavioral Neuroscience
https://www.readbyqxmd.com/read/28536046/neural-substrates-of-updating-the-prediction-through-prediction-error-during-decision-making
#19
Ying Wang, Ning Ma, Xiaosong He, Nan Li, Zhengde Wei, Lizhuang Yang, Rujing Zha, Long Han, Xiaoming Li, Daren Zhang, Ying Liu, Xiaochu Zhang
Learning of prediction error (PE), including reward PE and risk PE, is crucial for updating the prediction in reinforcement learning (RL). Neurobiological and computational models of RL have reported extensive brain activations related to PE. However, the occurrence of PE does not necessarily predict updating the prediction, e.g., in a probability-known event. Therefore, the brain regions specifically engaged in updating the prediction remain unknown. Here, we conducted two functional magnetic resonance imaging (fMRI) experiments, the probability-unknown Iowa Gambling Task (IGT) and the probability-known risk decision task (RDT)...
May 20, 2017: NeuroImage
https://www.readbyqxmd.com/read/28535383/reward-prediction-error
#20
Wolfram Schultz
In this quick guide, Wolfram Schultz provides an introduction of reward prediction error, exploring the signal of dopamine neurons and describing its potential role in reward accumulation, decision-making and everyday life.
May 22, 2017: Current Biology: CB
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