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Falck J, Zhang L, Raffington L, Mohn JJ, Triesch J, Heim C, Shing YL. Hippocampus and striatum show distinct contributions to longitudinal changes in value-based learning in middle childhood. eLife 2024; 12:RP89483. [PMID: 38953517 PMCID: PMC11219037 DOI: 10.7554/elife.89483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2024] Open
Abstract
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children's learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
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Affiliation(s)
- Johannes Falck
- Department of Psychology, Goethe University FrankfurtFrankfurtGermany
| | - Lei Zhang
- Centre for Human Brain Health, School of Psychology, University of BirminghamBirminghamUnited Kingdom
- Institute for Mental Health, School of Psychology, University of BirminghamBirminghamUnited Kingdom
- Centre for Developmental Science, School of Psychology, University of BirminghamBirminghamUnited Kingdom
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of ViennaViennaAustria
| | - Laurel Raffington
- Max Planck Research Group Biosocial, Max Planck Institute for Human DevelopmentBerlinGermany
| | - Johannes Julius Mohn
- Charité – Universitätsmedizin Berlin, Institute of Medical PsychologyBerlinGermany
- Max Planck School of Cognition, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Jochen Triesch
- Frankfurt Institute for Advanced Studies (FIAS)Frankfurt am MainGermany
| | - Christine Heim
- Charité – Universitätsmedizin Berlin, Institute of Medical PsychologyBerlinGermany
- Center for Safe & Healthy Children, The Pennsylvania State UniversityUniversity ParkUnited States
| | - Yee Lee Shing
- Department of Psychology, Goethe University FrankfurtFrankfurtGermany
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2
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Raab HA, Goldway N, Foord C, Hartley CA. Adolescents flexibly adapt action selection based on controllability inferences. Learn Mem 2024; 31:a053901. [PMID: 38527752 PMCID: PMC11000582 DOI: 10.1101/lm.053901.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 02/19/2024] [Indexed: 03/27/2024]
Abstract
From early in life, we encounter both controllable environments, in which our actions can causally influence the reward outcomes we experience, and uncontrollable environments, in which they cannot. Environmental controllability is theoretically proposed to organize our behavior. In controllable contexts, we can learn to proactively select instrumental actions that bring about desired outcomes. In uncontrollable environments, Pavlovian learning enables hard-wired, reflexive reactions to anticipated, motivationally salient events, providing "default" behavioral responses. Previous studies characterizing the balance between Pavlovian and instrumental learning systems across development have yielded divergent findings, with some studies observing heightened expression of Pavlovian learning during adolescence and others observing a reduced influence of Pavlovian learning during this developmental stage. In this study, we aimed to investigate whether a theoretical model of controllability-dependent arbitration between learning systems might explain these seemingly divergent findings in the developmental literature, with the specific hypothesis that adolescents' action selection might be particularly sensitive to environmental controllability. To test this hypothesis, 90 participants, aged 8-27, performed a probabilistic-learning task that enables estimation of Pavlovian influence on instrumental learning, across both controllable and uncontrollable conditions. We fit participants' data with a reinforcement-learning model in which controllability inferences adaptively modulate the dominance of Pavlovian versus instrumental control. Relative to children and adults, adolescents exhibited greater flexibility in calibrating the expression of Pavlovian bias to the degree of environmental controllability. These findings suggest that sensitivity to environmental reward statistics that organize motivated behavior may be heightened during adolescence.
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Affiliation(s)
- Hillary A Raab
- Department of Psychology, New York University, New York, New York 10003, USA
| | - Noam Goldway
- Department of Psychology, New York University, New York, New York 10003, USA
| | - Careen Foord
- Center for Neural Science, New York University, New York, New York 10003, USA
| | - Catherine A Hartley
- Department of Psychology, New York University, New York, New York 10003, USA
- Center for Neural Science, New York University, New York, New York 10003, USA
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3
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Wen T, Geddert RM, Madlon-Kay S, Egner T. Transfer of Learned Cognitive Flexibility to Novel Stimuli and Task Sets. Psychol Sci 2023; 34:435-454. [PMID: 36693129 PMCID: PMC10236430 DOI: 10.1177/09567976221141854] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/03/2022] [Indexed: 01/25/2023] Open
Abstract
Adaptive behavior requires learning about the structure of one's environment to derive optimal action policies, and previous studies have documented transfer of such structural knowledge to bias choices in new environments. Here, we asked whether people could also acquire and transfer more abstract knowledge across different task environments, specifically expectations about cognitive control demands. Over three experiments, participants (Amazon Mechanical Turk workers; N = ~80 adults per group) performed a probabilistic card-sorting task in environments of either a low or high volatility of task rule changes (requiring low or high cognitive flexibility, respectively) before transitioning to a medium-volatility environment. Using reinforcement-learning modeling, we consistently found that previous exposure to high task rule volatilities led to faster adaptation to rule changes in the subsequent transfer phase. These transfers of expectations about cognitive flexibility demands were both task independent (Experiment 2) and stimulus independent (Experiment 3), thus demonstrating the formation and generalization of environmental structure knowledge to guide cognitive control.
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Affiliation(s)
- Tanya Wen
- Center for Cognitive Neuroscience, Duke
University
| | | | - Seth Madlon-Kay
- Department of Biostatistics and
Bioinformatics, Duke University School of Medicine
| | - Tobias Egner
- Center for Cognitive Neuroscience, Duke
University
- Department of Psychology and
Neuroscience, Duke University
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4
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Grahek I, Frömer R, Prater Fahey M, Shenhav A. Learning when effort matters: neural dynamics underlying updating and adaptation to changes in performance efficacy. Cereb Cortex 2023; 33:2395-2411. [PMID: 35695774 PMCID: PMC9977373 DOI: 10.1093/cercor/bhac215] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 05/06/2022] [Accepted: 05/08/2022] [Indexed: 11/13/2022] Open
Abstract
To determine how much cognitive control to invest in a task, people need to consider whether exerting control matters for obtaining rewards. In particular, they need to account for the efficacy of their performance-the degree to which rewards are determined by performance or by independent factors. Yet it remains unclear how people learn about their performance efficacy in an environment. Here we combined computational modeling with measures of task performance and EEG, to provide a mechanistic account of how people (i) learn and update efficacy expectations in a changing environment and (ii) proactively adjust control allocation based on current efficacy expectations. Across 2 studies, subjects performed an incentivized cognitive control task while their performance efficacy (the likelihood that rewards are performance-contingent or random) varied over time. We show that people update their efficacy beliefs based on prediction errors-leveraging similar neural and computational substrates as those that underpin reward learning-and adjust how much control they allocate according to these beliefs. Using computational modeling, we show that these control adjustments reflect changes in information processing, rather than the speed-accuracy tradeoff. These findings demonstrate the neurocomputational mechanism through which people learn how worthwhile their cognitive control is.
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Affiliation(s)
- Ivan Grahek
- Department of Cognitive, Linguistic, & Psychological Sciences, Carney Institute for Brain Science, Brown University, Box 1821, Providence, RI 02912, United States
| | - Romy Frömer
- Department of Cognitive, Linguistic, & Psychological Sciences, Carney Institute for Brain Science, Brown University, Box 1821, Providence, RI 02912, United States
| | - Mahalia Prater Fahey
- Department of Cognitive, Linguistic, & Psychological Sciences, Carney Institute for Brain Science, Brown University, Box 1821, Providence, RI 02912, United States
| | - Amitai Shenhav
- Department of Cognitive, Linguistic, & Psychological Sciences, Carney Institute for Brain Science, Brown University, Box 1821, Providence, RI 02912, United States
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5
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Nussenbaum K, Velez JA, Washington BT, Hamling HE, Hartley CA. Flexibility in valenced reinforcement learning computations across development. Child Dev 2022; 93:1601-1615. [PMID: 35596654 PMCID: PMC9831067 DOI: 10.1111/cdev.13791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Optimal integration of positive and negative outcomes during learning varies depending on an environment's reward statistics. The present study investigated the extent to which children, adolescents, and adults (N = 142 8-25 year-olds, 55% female, 42% White, 31% Asian, 17% mixed race, and 8% Black; data collected in 2021) adapt their weighting of better-than-expected and worse-than-expected outcomes when learning from reinforcement. Participants made choices across two contexts: one in which weighting positive outcomes more heavily than negative outcomes led to better performance, and one in which the reverse was true. Reinforcement learning modeling revealed that across age, participants shifted their valence biases in accordance with environmental structure. Exploratory analyses revealed strengthening of context-dependent flexibility with increasing age.
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Affiliation(s)
| | | | | | | | - Catherine A. Hartley
- Corresponding Author: Catherine A. Hartley, Department of Psychology, New York University, 6 Washington Place, Room 871A, New York, NY, 10003.
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6
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Harlé KM, Ho TC, Connolly CG, Simmons AN, Yang TT. The effect of obstructed action efficacy on reward-based decision-making in healthy adolescents: a novel functional MRI task to assay frustration. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2022; 22:542-556. [PMID: 34966980 PMCID: PMC9090962 DOI: 10.3758/s13415-021-00975-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 12/01/2021] [Indexed: 06/03/2023]
Abstract
Frustration is common in adolescence and often interferes with executive functioning, particularly reward-based decision-making, and yet very little is known about how incidental frustrating events (independent of task-based feedback) disrupt the neural circuitry of reward processing in this important age group. While undergoing functional magnetic resonance imaging (fMRI), 45 healthy adolescents played a card game in which they had to guess between two options to earn points, in low- and high-stake conditions. Functioning of button presses through which they made decisions was intermittently blocked, thereby increasing frustration potential. Neural deactivation of the precuneus, a Default Mode Network region, was observed during obstructed action blocks across stake conditions, but less so on high- relative to low-stake trials. Moreover, less deactivation in goal-directed reward processing regions (i.e., caudate), frontoparietal "task control" regions, and interoceptive processing regions (i.e., somatosensory cortex, thalamus) were observed on high-stake relative to low-stake trials. These findings are consistent with less disruption of goal-directed reward seeking during blocked action efficacy in high-stake conditions among healthy adolescents. These results provide a roadmap of neural systems critical to the processing of frustrating events during reward-based decision-making in youths and could help to characterize how frustration regulation is altered in a range of pediatric psychopathologies.
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Affiliation(s)
- Katia M Harlé
- VA San Diego Healthcare System, 3350 La Jolla Village Drive, San Diego, CA, 92161, USA.
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
| | - Tiffany C Ho
- Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Colm G Connolly
- Department of Biomedical Sciences, Florida State University, Tallahassee, FL, USA
| | - Alan N Simmons
- VA San Diego Healthcare System, 3350 La Jolla Village Drive, San Diego, CA, 92161, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Tony T Yang
- Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
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7
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Raab HA, Foord C, Ligneul R, Hartley CA. Developmental shifts in computations used to detect environmental controllability. PLoS Comput Biol 2022; 18:e1010120. [PMID: 35648788 PMCID: PMC9191713 DOI: 10.1371/journal.pcbi.1010120] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 06/13/2022] [Accepted: 04/19/2022] [Indexed: 12/13/2022] Open
Abstract
Accurate assessment of environmental controllability enables individuals to adaptively adjust their behavior—exploiting rewards when desirable outcomes are contingent upon their actions and minimizing costly deliberation when their actions are inconsequential. However, it remains unclear how estimation of environmental controllability changes from childhood to adulthood. Ninety participants (ages 8–25) completed a task that covertly alternated between controllable and uncontrollable conditions, requiring them to explore different actions to discover the current degree of environmental controllability. We found that while children were able to distinguish controllable and uncontrollable conditions, accuracy of controllability assessments improved with age. Computational modeling revealed that whereas younger participants’ controllability assessments relied on evidence gleaned through random exploration, older participants more effectively recruited their task structure knowledge to make highly informative interventions. Age-related improvements in working memory mediated this qualitative shift toward increased use of an inferential strategy. Collectively, these findings reveal an age-related shift in the cognitive processes engaged to assess environmental controllability. Improved detection of environmental controllability may foster increasingly adaptive behavior over development by revealing when actions can be leveraged for one’s benefit. The ability to determine when one’s actions are consequential organizes learning and decision making across the lifespan. However, few studies have examined how the ability to detect control over our environment changes from childhood to adulthood. Here, we leveraged a computational modeling framework to characterize the component learning processes underlying controllability assessment in children, adolescents, and adults. We observed age-related improvements in controllability assessment that stemmed from an increasing ability to represent contingencies between states and actions and to use that knowledge to make informative interventions that yield diagnostic evidence of the current degree of control. Increasing ability to accurately assess environmental controllability may confer greater recognition of opportunities to adaptively pursue rewards through goal-directed action across development.
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Affiliation(s)
- Hillary A. Raab
- Department of Psychology, New York University, New York, New York, United States of America
| | - Careen Foord
- Center for Neural Science, New York University, New York, New York, United States of America
| | - Romain Ligneul
- Champalimaud Research, Champalimaud Center for the Unknown, Lisbon, Portugal
| | - Catherine A. Hartley
- Department of Psychology, New York University, New York, New York, United States of America
- Center for Neural Science, New York University, New York, New York, United States of America
- * E-mail:
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8
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Pruning recurrent neural networks replicates adolescent changes in working memory and reinforcement learning. Proc Natl Acad Sci U S A 2022; 119:e2121331119. [PMID: 35622896 DOI: 10.1073/pnas.2121331119] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
SignificanceAdolescence is a period during which there are important changes in behavior and the structure of the brain. In this manuscript, we use theoretical modeling to show how improvements in working memory and reinforcement learning that occur during adolescence can be explained by the reduction in synaptic connectivity in prefrontal cortex that occurs during a similar period. We train recurrent neural networks to solve working memory and reinforcement learning tasks and show that when we prune connectivity in these networks, they perform the tasks better. The improvement in task performance, however, can come at the cost of flexibility as the pruned networks are not able to learn some new tasks as well.
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9
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Ma I, Westhoff B, van Duijvenvoorde ACK. Uncertainty about others' trustworthiness increases during adolescence and guides social information sampling. Sci Rep 2022; 12:7634. [PMID: 35538170 PMCID: PMC9091231 DOI: 10.1038/s41598-022-09477-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 03/15/2022] [Indexed: 01/11/2023] Open
Abstract
Adolescence is a key life phase for developing well-adjusted social behaviour. An essential component of well-adjusted social behaviour is the ability to update our beliefs about the trustworthiness of others based on gathered information. Here, we examined how adolescents (n = 157, 10-24 years) sequentially sampled information about the trustworthiness of peers and how they used this information to update their beliefs about others' trustworthiness. Our Bayesian computational modelling approach revealed an adolescence-emergent increase in uncertainty of prior beliefs about others' trustworthiness. As a consequence, early to mid-adolescents (ages 10-16) gradually relied less on their prior beliefs and more on the gathered evidence when deciding to sample more information, and when deciding to trust. We propose that these age-related differences could be adaptive to the rapidly changing social environment of early and mid-adolescents. Together, these findings contribute to the understanding of adolescent social development by revealing adolescent-emergent flexibility in prior beliefs about others that drives adolescents' information sampling and trust decisions.
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Affiliation(s)
- I Ma
- Department of Psychology, New York University, New York, USA.
- Institute of Psychology, Leiden University, Leiden, The Netherlands.
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands.
| | - B Westhoff
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - A C K van Duijvenvoorde
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
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10
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Dorfman HM, Tomov MS, Cheung B, Clarke D, Gershman SJ, Hughes BL. Causal Inference Gates Corticostriatal Learning. J Neurosci 2021; 41:6892-6904. [PMID: 34244363 PMCID: PMC8360688 DOI: 10.1523/jneurosci.2796-20.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 06/29/2021] [Accepted: 07/01/2021] [Indexed: 11/21/2022] Open
Abstract
Attributing outcomes to your own actions or to external causes is essential for appropriately learning which actions lead to reward and which actions do not. Our previous work showed that this type of credit assignment is best explained by a Bayesian reinforcement learning model which posits that beliefs about the causal structure of the environment modulate reward prediction errors (RPEs) during action value updating. In this study, we investigated the brain networks underlying reinforcement learning that are influenced by causal beliefs using functional magnetic resonance imaging while human participants (n = 31; 13 males, 18 females) completed a behavioral task that manipulated beliefs about causal structure. We found evidence that RPEs modulated by causal beliefs are represented in dorsal striatum, while standard (unmodulated) RPEs are represented in ventral striatum. Further analyses revealed that beliefs about causal structure are represented in anterior insula and inferior frontal gyrus. Finally, structural equation modeling revealed effective connectivity from anterior insula to dorsal striatum. Together, these results are consistent with a possible neural architecture in which causal beliefs in anterior insula are integrated with prediction error signals in dorsal striatum to update action values.SIGNIFICANCE STATEMENT Learning which actions lead to reward-a process known as reinforcement learning-is essential for survival. Inferring the causes of observed outcomes-a process known as causal inference-is crucial for appropriately assigning credit to one's own actions and restricting learning to effective action-outcome contingencies. Previous studies have linked reinforcement learning to the striatum, and causal inference to prefrontal regions, yet how these neural processes interact to guide adaptive behavior remains poorly understood. Here, we found evidence that causal beliefs represented in the prefrontal cortex modulate action value updating in posterior striatum, separately from the unmodulated action value update in ventral striatum posited by standard reinforcement learning models.
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Affiliation(s)
- Hayley M Dorfman
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts 02138
| | - Momchil S Tomov
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts 02138
- Program in Neuroscience, Harvard Medical School, Boston, Massachusetts 02115
| | - Bernice Cheung
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | - Dennis Clarke
- Department of Psychology, University of California, Riverside, Riverside, California 92521
| | - Samuel J Gershman
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts 02138
- Center for Brains, Minds and Machines, MIT, Cambridge, Massachusetts 02139
| | - Brent L Hughes
- Department of Psychology, University of California, Riverside, Riverside, California 92521
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11
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Tabas A, von Kriegstein K. Adjudicating Between Local and Global Architectures of Predictive Processing in the Subcortical Auditory Pathway. Front Neural Circuits 2021; 15:644743. [PMID: 33776657 PMCID: PMC7994860 DOI: 10.3389/fncir.2021.644743] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/16/2021] [Indexed: 11/13/2022] Open
Abstract
Predictive processing, a leading theoretical framework for sensory processing, suggests that the brain constantly generates predictions on the sensory world and that perception emerges from the comparison between these predictions and the actual sensory input. This requires two distinct neural elements: generative units, which encode the model of the sensory world; and prediction error units, which compare these predictions against the sensory input. Although predictive processing is generally portrayed as a theory of cerebral cortex function, animal and human studies over the last decade have robustly shown the ubiquitous presence of prediction error responses in several nuclei of the auditory, somatosensory, and visual subcortical pathways. In the auditory modality, prediction error is typically elicited using so-called oddball paradigms, where sequences of repeated pure tones with the same pitch are at unpredictable intervals substituted by a tone of deviant frequency. Repeated sounds become predictable promptly and elicit decreasing prediction error; deviant tones break these predictions and elicit large prediction errors. The simplicity of the rules inducing predictability make oddball paradigms agnostic about the origin of the predictions. Here, we introduce two possible models of the organizational topology of the predictive processing auditory network: (1) the global view, that assumes that predictions on the sensory input are generated at high-order levels of the cerebral cortex and transmitted in a cascade of generative models to the subcortical sensory pathways; and (2) the local view, that assumes that independent local models, computed using local information, are used to perform predictions at each processing stage. In the global view information encoding is optimized globally but biases sensory representations along the entire brain according to the subjective views of the observer. The local view results in a diminished coding efficiency, but guarantees in return a robust encoding of the features of sensory input at each processing stage. Although most experimental results to-date are ambiguous in this respect, recent evidence favors the global model.
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Affiliation(s)
- Alejandro Tabas
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Katharina von Kriegstein
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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