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Broschard MB, Turner BM, Tranel D, Freeman JH. Dissociable Roles of the Dorsolateral and Ventromedial Prefrontal Cortex in Human Categorization. J Neurosci 2024; 44:e2343232024. [PMID: 38997159 PMCID: PMC11340282 DOI: 10.1523/jneurosci.2343-23.2024] [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] [Received: 11/05/2023] [Revised: 06/21/2024] [Accepted: 06/27/2024] [Indexed: 07/14/2024] Open
Abstract
Models of human categorization predict the prefrontal cortex (PFC) serves a central role in category learning. The dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) have been implicated in categorization; however, it is unclear whether both are critical for categorization and whether they support unique functions. We administered three categorization tasks to patients with PFC lesions (mean age, 69.6 years; 5 men, 5 women) to examine how the prefrontal subregions contribute to categorization. These included a rule-based (RB) task that was solved via a unidimensional rule, an information integration (II) task that was solved by combining information from two stimulus dimensions, and a deterministic/probabilistic (DP) task with stimulus features that had varying amounts of category-predictive information. Compared with healthy comparison participants, both patient groups had impaired performance. Impairments in the dlPFC patients were largest during the RB task, whereas impairments in the vmPFC patients were largest during the DP task. A hierarchical model was fit to the participants' data to assess learning deficits in the patient groups. PFC damage was correlated with a regularization term that limited updates to attention after each trial. Our results suggest that the PFC, as a whole, is important for learning to orient attention to relevant stimulus information. The dlPFC may be especially important for rule-based learning, whereas the vmPFC may be important for focusing attention on deterministic (highly diagnostic) features and ignoring less predictive features. These results support overarching functions of the dlPFC in executive functioning and the vmPFC in value-based decision-making.
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Affiliation(s)
- Matthew B Broschard
- The Picower Institute of Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa 52242
| | - Brandon M Turner
- Department of Psychology, The Ohio State University, Columbus, Ohio 43210
| | - Daniel Tranel
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa 52242
- Department of Neurology, University of Iowa, Iowa City, Iowa 52242
| | - John H Freeman
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa 52242
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2
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Roark CL, Chandrasekaran B. Stable, flexible, common, and distinct behaviors support rule-based and information-integration category learning. NPJ SCIENCE OF LEARNING 2023; 8:14. [PMID: 37179364 PMCID: PMC10183008 DOI: 10.1038/s41539-023-00163-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 04/21/2023] [Indexed: 05/15/2023]
Abstract
The ability to organize variable sensory signals into discrete categories is a fundamental process in human cognition thought to underlie many real-world learning problems. Decades of research suggests that two learning systems may support category learning and that categories with different distributional structures (rule-based, information-integration) optimally rely on different learning systems. However, it remains unclear how the same individual learns these different categories and whether the behaviors that support learning success are common or distinct across different categories. In two experiments, we investigate learning and develop a taxonomy of learning behaviors to investigate which behaviors are stable or flexible as the same individual learns rule-based and information-integration categories and which behaviors are common or distinct to learning success for these different types of categories. We found that some learning behaviors are stable in an individual across category learning tasks (learning success, strategy consistency), while others are flexibly task-modulated (learning speed, strategy, stability). Further, success in rule-based and information-integration category learning was supported by both common (faster learning speeds, higher working memory ability) and distinct factors (learning strategies, strategy consistency). Overall, these results demonstrate that even with highly similar categories and identical training tasks, individuals dynamically adjust some behaviors to fit the task and success in learning different kinds of categories is supported by both common and distinct factors. These results illustrate a need for theoretical perspectives of category learning to include nuances of behavior at the level of an individual learner.
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Affiliation(s)
- Casey L Roark
- Department of Communication Science & Disorders,University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
| | - Bharath Chandrasekaran
- Department of Communication Science & Disorders,University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
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3
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Liu Z, Liao S, Seger CA. Rule and Exemplar-based Transfer in Category Learning. J Cogn Neurosci 2023; 35:628-644. [PMID: 36638230 DOI: 10.1162/jocn_a_01963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
We compared the neural systems involved in transfer to novel stimuli via rule application versus exemplar processing. Participants learned a categorization task involving abstraction of a complex rule and then categorized different types of transfer stimuli without feedback. Rule stimuli used new features and therefore could only be categorized using the rule. Exemplar stimuli included only one of the features necessary to apply the rule and therefore required participants to categorize based on similarity to individual previously learned category members. Consistent and inconsistent stimuli were formed so that both the rule and feature similarity indicated the same category (consistent) or opposite categories (inconsistent). We found that all conditions eliciting rule-based transfer recruited a medial prefrontal-anterior hippocampal network associated with schematic memory. In contrast, exemplar-based transfer recruited areas of the intraparietal sulcus associated with learning and executing stimulus-category mappings along with the posterior hippocampus. These results support theories of categorization that postulate complementary learning and generalization strategies based on schematic and exemplar mechanisms.
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Affiliation(s)
- Zhiya Liu
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
| | - Siyao Liao
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
| | - Carol A Seger
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China.,Colorado State University, Department of Psychology, Molecular, Cellular and Integrative Neurosciences Program, Fort Collins, CO
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4
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Broschard MB, Kim J, Love BC, Freeman JH. Dorsomedial striatum, but not dorsolateral striatum, is necessary for rat category learning. Neurobiol Learn Mem 2023; 199:107732. [PMID: 36764646 DOI: 10.1016/j.nlm.2023.107732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/19/2023] [Accepted: 02/05/2023] [Indexed: 02/11/2023]
Abstract
Categorization is an adaptive cognitive function that allows us to generalize knowledge to novel situations. Converging evidence from neuropsychological, neuroimaging, and neurophysiological studies suggest that categorization is mediated by the basal ganglia; however, there is debate regarding the necessity of each subregion of the basal ganglia and their respective functions. The current experiment examined the roles of the dorsomedial striatum (DMS; homologous to the head of the caudate nucleus) and dorsolateral striatum (DLS; homologous to the body and tail of the caudate nucleus) in category learning by combining selective lesions with computational modeling. Using a touchscreen apparatus, rats were trained to categorize distributions of visual stimuli that varied along two continuous dimensions (i.e., spatial frequency and orientation). The tasks either required attention to one stimulus dimension (spatial frequency or orientation; 1D tasks) or both stimulus dimensions (spatial frequency and orientation; 2D tasks). Rats with NMDA lesions of the DMS were impaired on both the 1D tasks and 2D tasks, whereas rats with DLS lesions showed no impairments. The lesions did not affect performance on a discrimination task that had the same trial structure as the categorization tasks, suggesting that the category impairments effected processes relevant to categorization. Model simulations were conducted using a neural network to assess the effect of the DMS lesions on category learning. Together, the results suggest that the DMS is critical to map category representations to appropriate behavioral responses, whereas the DLS is not necessary for categorization.
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Affiliation(s)
- Matthew B Broschard
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jangjin Kim
- Department of Psychology, Kyungpool National University, Daegu, Republic of Korea
| | - Bradley C Love
- Department of Experimental Psychology and The Alan Turing Institute, University College London, London, UK
| | - John H Freeman
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA.
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5
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Effects of categorical and numerical feedback on category learning. Cognition 2022; 225:105163. [DOI: 10.1016/j.cognition.2022.105163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 05/02/2022] [Accepted: 05/05/2022] [Indexed: 11/23/2022]
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6
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Feng G, Gan Z, Yi HG, Ell SW, Roark CL, Wang S, Wong PCM, Chandrasekaran B. Neural dynamics underlying the acquisition of distinct auditory category structures. Neuroimage 2021; 244:118565. [PMID: 34543762 PMCID: PMC8785192 DOI: 10.1016/j.neuroimage.2021.118565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/05/2021] [Accepted: 09/06/2021] [Indexed: 11/16/2022] Open
Abstract
Despite the multidimensional and temporally fleeting nature of auditory signals we quickly learn to assign novel sounds to behaviorally relevant categories. The neural systems underlying the learning and representation of novel auditory categories are far from understood. Current models argue for a rigid specialization of hierarchically organized core regions that are fine-tuned to extracting and mapping relevant auditory dimensions to meaningful categories. Scaffolded within a dual-learning systems approach, we test a competing hypothesis: the spatial and temporal dynamics of emerging auditory-category representations are not driven by the underlying dimensions but are constrained by category structure and learning strategies. To test these competing models, we used functional Magnetic Resonance Imaging (fMRI) to assess representational dynamics during the feedback-based acquisition of novel non-speech auditory categories with identical dimensions but differing category structures: rule-based (RB) categories, hypothesized to involve an explicit sound-to-rule mapping network, and information integration (II) based categories, involving pre-decisional integration of dimensions via a procedural-based sound-to-reward mapping network. Adults were assigned to either the RB (n = 30, 19 females) or II (n = 30, 22 females) learning tasks. Despite similar behavioral learning accuracies, learning strategies derived from computational modeling and involvements of corticostriatal systems during feedback processing differed across tasks. Spatiotemporal multivariate representational similarity analysis revealed an emerging representation within an auditory sensory-motor pathway exclusively for the II learning task, prominently involving the superior temporal gyrus (STG), inferior frontal gyrus (IFG), and posterior precentral gyrus. In contrast, the RB learning task yielded distributed neural representations within regions involved in cognitive-control and attentional processes that emerged at different time points of learning. Our results unequivocally demonstrate that auditory learners' neural systems are highly flexible and show distinct spatial and temporal patterns that are not dimension-specific but reflect underlying category structures and learning strategies.
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Affiliation(s)
- Gangyi Feng
- Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China; Brain and Mind Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China.
| | - Zhenzhong Gan
- Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China; Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China, School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Han Gyol Yi
- Department of Neurological Surgery, University of California, San Francisco, CA 94158, United States
| | - Shawn W Ell
- Department of Psychology, Graduate School of Biomedical Sciences and Engineering, University of Maine, 5742 Little Hall, Room 301, Orono, ME 04469-5742, United States
| | - Casey L Roark
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260, United States; Center for the Neural Basis of Cognition, Pittsburgh, PA 15232, United States
| | - Suiping Wang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China, School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Patrick C M Wong
- Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China; Brain and Mind Institute, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China
| | - Bharath Chandrasekaran
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260, United States; Center for the Neural Basis of Cognition, Pittsburgh, PA 15232, United States.
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7
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Inkster AB, Milton F, Edmunds CER, Benattayallah A, Wills AJ. Neural correlates of the inverse base rate effect. Hum Brain Mapp 2021; 43:1370-1380. [PMID: 34826165 PMCID: PMC8837595 DOI: 10.1002/hbm.25729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 10/16/2021] [Accepted: 11/15/2021] [Indexed: 12/05/2022] Open
Abstract
The inverse base rate effect (IBRE) is a nonrational behavioral phenomenon in predictive learning. Canonically, participants learn that the AB stimulus compound leads to one outcome and that AC leads to another outcome, with AB being presented three times as often as AC. When subsequently presented with BC, the outcome associated with AC is preferentially selected, in opposition to the underlying base rates of the outcomes. The current leading explanation is based on error‐driven learning. A key component of this account is prediction error, a concept previously linked to a number of brain areas including the anterior cingulate, the striatum, and the dorsolateral prefrontal cortex. The present work is the first fMRI study to directly examine the IBRE. Activations were noted in brain areas linked to prediction error, including the caudate body, the anterior cingulate, the ventromedial prefrontal cortex, and the right dorsolateral prefrontal cortex. Analyzing the difference in activations for singular key stimuli (B and C), as well as frequency matched controls, supports the predictions made by the error‐driven learning account.
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Affiliation(s)
- Angus B Inkster
- Brain Research and Imaging Centre, University of Plymouth, Plymouth
| | | | | | | | - Andy J Wills
- Brain Research and Imaging Centre, University of Plymouth, Plymouth
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8
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Wu J, Li Q, Fu Q, Rose M, Jing L. Multisensory Information Facilitates the Categorization of Untrained Stimuli. Multisens Res 2021; 35:79-107. [PMID: 34388699 DOI: 10.1163/22134808-bja10061] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 07/30/2021] [Indexed: 11/19/2022]
Abstract
Although it has been demonstrated that multisensory information can facilitate object recognition and object memory, it remains unclear whether such facilitation effect exists in category learning. To address this issue, comparable car images and sounds were first selected by a discrimination task in Experiment 1. Then, those selected images and sounds were utilized in a prototype category learning task in Experiments 2 and 3, in which participants were trained with auditory, visual, and audiovisual stimuli, and were tested with trained or untrained stimuli within the same categories presented alone or accompanied with a congruent or incongruent stimulus in the other modality. In Experiment 2, when low-distortion stimuli (more similar to the prototypes) were trained, there was higher accuracy for audiovisual trials than visual trials, but no significant difference between audiovisual and auditory trials. During testing, accuracy was significantly higher for congruent trials than unisensory or incongruent trials, and the congruency effect was larger for untrained high-distortion stimuli than trained low-distortion stimuli. In Experiment 3, when high-distortion stimuli (less similar to the prototypes) were trained, there was higher accuracy for audiovisual trials than visual or auditory trials, and the congruency effect was larger for trained high-distortion stimuli than untrained low-distortion stimuli during testing. These findings demonstrated that higher degree of stimuli distortion resulted in more robust multisensory effect, and the categorization of not only trained but also untrained stimuli in one modality could be influenced by an accompanying stimulus in the other modality.
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Affiliation(s)
- Jie Wu
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.,Department of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.,NeuroImage Nord, Department for Systems Neuroscience, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
| | - Qitian Li
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.,Department of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.,NeuroImage Nord, Department for Systems Neuroscience, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
| | - Qiufang Fu
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.,Department of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Michael Rose
- NeuroImage Nord, Department for Systems Neuroscience, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
| | - Liping Jing
- Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University, Beijing, China
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9
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The impact of training methodology and representation on rule-based categorization: An fMRI study. COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2021; 21:717-735. [PMID: 33825123 DOI: 10.3758/s13415-021-00882-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/15/2021] [Indexed: 11/08/2022]
Abstract
Hélie, Shamloo, & Ell (2017) showed that regular classification learning instructions (A/B) promote between-category knowledge in rule-based categorization whereas conceptual learning instructions (YES/NO) promote learning within-category knowledge with the same categories. Here we explore how these tasks affect brain activity using fMRI. Participants learned two sets of two categories. Computational models were fit to the behavioral data to determine the type of knowledge learned by each participant. fMRI contrasts were computed to compare BOLD signal between the tasks and between the types of knowledge. The results show that participants in the YES/NO task had more activity in the pre-supplementary motor area, prefrontal cortex, and the angular/supramarginal gyrus. These brain areas are related to working memory and part of the dorsal attention network, which showed increased task-based functional connectivity with the medial temporal lobes. In contrast, participants in the A/B task had more activity in the thalamus and caudate. These results suggest that participants in the YES/NO task used bivalent rules and may have treated each contextual question as a separate task, switching task each time the question changed. Activity in the A/B condition was more consistent with participants applying direct Stimulus → Response rules. With regards to knowledge representation, there was a large shared network of brain areas, but participants learning between-category information showed additional posterior parietal activity, which may be related to the inhibition of incorrect motor programs.
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10
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Zhou X, Fu Q, Rose M. The Role of Edge-Based and Surface-Based Information in Incidental Category Learning: Evidence From Behavior and Event-Related Potentials. Front Integr Neurosci 2020; 14:36. [PMID: 32792919 PMCID: PMC7387683 DOI: 10.3389/fnint.2020.00036] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 06/05/2020] [Indexed: 11/15/2022] Open
Abstract
Although it has been demonstrated that edge-based information is more important than surface-based information in incidental category learning, it remains unclear how the two types of information play different roles in incidental category learning. To address this issue, the present study combined behavioral and event-related potential (ERP) techniques in an incidental category learning task in which the categories were defined by either edge- or surface-based features. The results from Experiment 1 showed that participants could simultaneously learn both edge- and surface-based information in incidental category learning, and importantly, there was a larger learning effect for the edge-based category than for the surface-based category. The behavioral results from Experiment 2 replicated those from Experiment 1, and the ERP results further revealed that the stimuli from the edge-based category elicited larger anterior and posterior P2 components than those from the surface-based category, whereas the stimuli from the surface-based category elicited larger anterior N1 and P3 components than those from the edge-based category. Taken together, the results suggest that, although surface-based information might attract more attention during feature detection, edge-based information plays more important roles in evaluating the relevance of information in making a decision in categorization.
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Affiliation(s)
- Xiaoyan Zhou
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,The Research Center for Psychological Education, University of International Relations, Beijing, China
| | - Qiufang Fu
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Michael Rose
- NeuroImage Nord, Department for Systems Neuroscience, University Medical Center Hamburg Eppendorf, Hamburg, Germany
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11
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Abstract
Polymorphous concepts are hard to learn, and this is perhaps surprising because they, like many natural concepts, have an overall similarity structure. However, the dimensional summation hypothesis (Milton and Wills Journal of Experimental Psychology: Learning, Memory and Cognition, 30, 407-415 2004) predicts this difficulty. It also makes a number of other predictions about polymorphous concept formation, which are tested here. In Experiment 4, we confirm the theory's prediction that polymorphous concept formation should be facilitated by deterministic pretraining on the constituent features of the stimulus. This facilitation is relative to an equivalent amount of training on the polymorphous concept itself. In further experiments, we compare the predictions of the dimensional summation hypothesis with a more general strategic account (Experiment 2), a seriality of training account (Experiment 3), a stimulus decomposition account (also Experiment 3), and an error-based account (Experiment 4). The dimensional summation hypothesis provides the best account of these data. In Experiment 5, a further prediction is confirmed-the single feature pretraining effect is eliminated by a concurrent counting task. The current experiments suggest the hypothesis that natural concepts might be acquired by the deliberate serial summation of evidence. This idea has testable implications for classroom learning.
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12
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Arroyo-Anlló EM, Sánchez JC, Ventola ARM, Ingrand P, Neau JP, Gil R. Procedural Learning Improves Cognition in Multiple Sclerosis. J Alzheimers Dis 2020; 74:913-924. [PMID: 32116252 PMCID: PMC7242853 DOI: 10.3233/jad-191083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Multiple sclerosis (MS) is considered a neurodegenerative disease and an inflammatory demyelinating neuropathology in young population. Procedural memory has been poorly investigated in MS. Objective: We assessed whether the MS group was able to develop a motor-cognitive skill, using a procedural task (PLSC) developed in our laboratory, applying a manual and serial reaction time (RT) paradigm to semantic categorization. Methods: We evaluated 26 MS patients and 26 socio-demographic matched control participants using the PLSC task. Results: Using non-parametric statistical analyses, we observed a significant improvement of semantic categorization RTs with practice (p = 0.002), even with new verbal material to categorize in MS patients (p = 0.006), despite their motor and executive moderate deficits. This same profile of semantic procedural learning in MS was observed in previous studies carried out with Alzheimer’s and Parkinson’s diseases. Moreover, the visual-motor RTs remained stable or slightly improved over the five blocks in both groups, as well as in the AD groups of previous studies. The MS group showed longer visual-motor reaction times than those of the control group (p < 0.042), except in motor initiation aspect (p = 0.064). Both groups showed no significant differences for any type of error. Additionally, disability level and cognitive performances were not associated with the ratio of semantic procedural learning. Conclusion: The present results support the notion that MS patients may be capable of acquiring semantic skill, despite their motor disabilities and executive troubles. This work also addresses the possibilities to improve motor-cognitive skill RTs in neurodegenerative diseases.
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Affiliation(s)
- Eva M Arroyo-Anlló
- Department of Psychobiology, University of Salamanca, Neuroscience Institute of Castilla-León, Spain
| | | | | | - Pierre Ingrand
- Department of Biostatistics, University of Poitiers, Poitiers, France
| | - Jean-Philippe Neau
- Department of Neurology, University Hospital, CHU La Milétrie, Poitiers, France
| | - Roger Gil
- Emeriti Professor of Neurology, University Hospital, Poitiers, France
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13
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Li Y, Seger C, Chen Q, Mo L. Left Inferior Frontal Gyrus Integrates Multisensory Information in Category Learning. Cereb Cortex 2020; 30:4410-4423. [DOI: 10.1093/cercor/bhaa029] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 12/31/2019] [Accepted: 01/22/2020] [Indexed: 12/12/2022] Open
Abstract
Abstract
Humans are able to categorize things they encounter in the world (e.g., a cat) by integrating multisensory information from the auditory and visual modalities with ease and speed. However, how the brain learns multisensory categories remains elusive. The present study used functional magnetic resonance imaging to investigate, for the first time, the neural mechanisms underpinning multisensory information-integration (II) category learning. A sensory-modality-general network, including the left insula, right inferior frontal gyrus (IFG), supplementary motor area, left precentral gyrus, bilateral parietal cortex, and right caudate and globus pallidus, was recruited for II categorization, regardless of whether the information came from a single modality or from multiple modalities. Putamen activity was higher in correct categorization than incorrect categorization. Critically, the left IFG and left body and tail of the caudate were activated in multisensory II categorization but not in unisensory II categorization, which suggests this network plays a specific role in integrating multisensory information during category learning. The present results extend our understanding of the role of the left IFG in multisensory processing from the linguistic domain to a broader role in audiovisual learning.
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Affiliation(s)
- You Li
- School of Psychology and Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, Guangdong, China
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, Guangdong, China
| | - Carol Seger
- School of Psychology and Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, Guangdong, China
- Department of Psychology, Colorado State University, Fort Collins, CO 80521 USA
| | - Qi Chen
- School of Psychology and Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, Guangdong, China
| | - Lei Mo
- School of Psychology and Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, Guangdong, China
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14
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Wu J, Fu Q, Rose M. Stimulus modality influences the acquisition and use of the rule-based strategy and the similarity-based strategy in category learning. Neurobiol Learn Mem 2019; 168:107152. [PMID: 31881353 DOI: 10.1016/j.nlm.2019.107152] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 12/05/2019] [Accepted: 12/23/2019] [Indexed: 10/25/2022]
Abstract
This study aimed to investigate whether stimulus modality influenced the acquisition and use of the rule-based strategy and the similarity-based strategy in category learning and whether the use of the two strategies was supported by shared or separate neural substrates. To address these issues, we combined behavioral and fNIRS methods in a modified prototype distortion task in which each category member has one rule feature and ten similarity features, and each type of feature can be presented in either the visual modality or the auditory modality. The results in Experiment 1 revealed that the learning effect in the "auditory rule-visual similarity" condition was the highest among all four conditions; further analysis revealed that in the "auditory rule-visual similarity" condition, the number of participants who used the rule-based strategy was more than the number of participants who used the similarity-based strategy, and the learning effect was always much higher for the rule-based strategy than for the similarity-based strategy. The behavioral results in Experiment 2 replicated the main findings in Experiment 1, and the fNIRS results showed that the use of the visual rule-based strategy was mediated by the dorsolateral prefrontal cortex, whereas the use of the auditory similarity-based strategy mainly engaged in the superior temporal gyrus, and the use of the visual similarity-based strategy mainly engaged in the inferior temporal gyrus. The results in Experiment 3 revealed that when the stimuli had only one type of feature, the visual rule rather than the auditory rule was learned more easily. The results provide new evidence that the stimulus modality can influence the acquisition and use of the rule-based strategy and the similarity-based strategy in category learning and that the use of the two types of strategies is supported by separate neural substrates both in the auditory modality and the visual modality.
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Affiliation(s)
- Jie Wu
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Qiufang Fu
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
| | - Michael Rose
- NeuroImage Nord, Department of Systems Neuroscience, University Medical Center Hamburg Eppendorf, Hamburg, Germany
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15
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Dissociable learning processes, associative theory, and testimonial reviews: A comment on Smith and Church (2018). Psychon Bull Rev 2019; 26:1988-1993. [PMID: 31410739 DOI: 10.3758/s13423-019-01644-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Smith and Church (Psychonomic Bulletin & Review, 25, 1565-1584 2018) present a "testimonial" review of dissociable learning processes in comparative and cognitive psychology, by which we mean they include only the portion of the available evidence that is consistent with their conclusions. For example, they conclude that learning the information-integration category-learning task with immediate feedback is implicit, but do not consider the evidence that people readily report explicit strategies in this task, nor that this task can be accommodated by accounts that make no distinction between implicit and explicit processes. They also consider some of the neuroscience relating to information-integration category learning, but do not report those aspects that are more consistent with an explicit than an implicit account. They further conclude that delay conditioning in humans is implicit, but do not report evidence that delay conditioning requires awareness; nor do they present the evidence that conditioned taste aversion, which should be explicit under their account, can be implicit. We agree with Smith and Church that it is helpful to have a clear definition of associative theory, but suggest that their definition may be unnecessarily restrictive. We propose an alternative definition of associative theory and briefly describe an experimental procedure that we think may better distinguish between associative and non-associative processes.
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16
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Zhou X, Fu Q, Rose M, Sun Y. Which Matters More in Incidental Category Learning: Edge-Based Versus Surface-Based Features. Front Psychol 2019; 10:183. [PMID: 30792675 PMCID: PMC6375183 DOI: 10.3389/fpsyg.2019.00183] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 01/18/2019] [Indexed: 11/13/2022] Open
Abstract
Although many researches have shown that edge-based information is more important than surface-based information in object recognition, it remains unclear whether edge-based features play a more crucial role than surface-based features in category learning. To address this issue, a modified prototype distortion task was adopted in the present study, in which each category was defined by a rule or a similarity about either the edge-based features (i.e., contours or shapes) or the corresponding surface-based features (i.e., color and textures). The results of Experiments 1 and 2 showed that when the category was defined by a rule, the performance was significantly better in the edge-based condition than in the surface-based condition in the testing phase, and increasing the defined dimensions enhanced rather than reduced performance in the edge-based condition but not in the surface-based condition. The results of Experiment 3 showed that when each category was defined by a similarity, there was also a larger learning effect when the category was defined by edge-based dimensions than by surface-based dimensions in the testing phase. The current study is the first to provide convergent evidence that the edge-based information matters more than surface-based information in incidental category learning.
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Affiliation(s)
- Xiaoyan Zhou
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Qiufang Fu
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Michael Rose
- NeuroImage Nord, Department for Systems Neuroscience, University Medical Center Hamburg Eppendorf, Hamburg, Germany
| | - Yuqi Sun
- State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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17
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Wirebring LK, Stillesjö S, Eriksson J, Juslin P, Nyberg L. A Similarity-Based Process for Human Judgment in the Parietal Cortex. Front Hum Neurosci 2018; 12:481. [PMID: 30631267 PMCID: PMC6315133 DOI: 10.3389/fnhum.2018.00481] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Accepted: 11/16/2018] [Indexed: 11/24/2022] Open
Abstract
One important distinction in psychology is between inferences based on associative memory and inferences based on analysis and rules. Much previous empirical work conceive of associative and analytical processes as two exclusive ways of addressing a judgment task, where only one process is selected and engaged at a time, in an either-or fashion. However, related work indicate that the processes are better understood as being in interplay and simultaneously engaged. Based on computational modeling and brain imaging of spontaneously adopted judgment strategies together with analyses of brain activity elicited in tasks where participants were explicitly instructed to perform similarity-based associative judgments or rule-based judgments (n = 74), we identified brain regions related to the two types of processes. We observed considerable overlap in activity patterns. The precuneus was activated for both types of judgments, and its activity predicted how well a similarity-based model fit the judgments. Activity in the superior frontal gyrus predicted the fit of a rule-based judgment model. The results suggest the precuneus as a key node for similarity-based judgments, engaged both when overt responses are guided by similarity-based and rule-based processes. These results are interpreted such that similarity-based processes are engaged in parallel to rule-based-processes, a finding with direct implications for cognitive theories of judgment.
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Affiliation(s)
- Linnea Karlsson Wirebring
- Department of Psychology, Umeå University, Umeå, Sweden
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Sara Stillesjö
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Johan Eriksson
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Peter Juslin
- Department of Psychology, Uppsala University, Uppsala, Sweden
| | - Lars Nyberg
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
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18
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Quam C, Wang A, Maddox WT, Golisch K, Lotto A. Procedural-Memory, Working-Memory, and Declarative-Memory Skills Are Each Associated With Dimensional Integration in Sound-Category Learning. Front Psychol 2018; 9:1828. [PMID: 30333772 PMCID: PMC6175975 DOI: 10.3389/fpsyg.2018.01828] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 09/07/2018] [Indexed: 11/25/2022] Open
Abstract
This paper investigates relationships between procedural-memory, declarative-memory, and working-memory skills and adult native English speakers' novel sound-category learning. Participants completed a sound-categorization task that required integrating two dimensions: one native (vowel quality), one non-native (pitch). Similar information-integration category structures in the visual and auditory domains have been shown to be best learned implicitly (e.g., Maddox et al., 2006). Thus, we predicted that individuals with greater procedural-memory capacity would better learn sound categories, because procedural memory appears to support implicit learning of new information and integration of dimensions. Seventy undergraduates were tested across two experiments. Procedural memory was assessed using a linguistic adaptation of the serial-reaction-time task (Misyak et al., 2010a,b). Declarative memory was assessed using the logical-memory subtest of the Wechsler Memory Scale-4th edition (WMS-IV; Wechsler, 2009). Working memory was assessed using an auditory version of the reading-span task (Kane et al., 2004). Experiment 1 revealed contributions of only declarative memory to dimensional integration, which might indicate not enough time or motivation to shift over to a procedural/integrative strategy. Experiment 2 gave twice the speech-sound training, distributed over 2 days, and also attempted to train at the category boundary. As predicted, effects of declarative memory were removed and effects of procedural memory emerged, but, unexpectedly, new effects of working memory surfaced. The results may be compatible with a multiple-systems account in which declarative and working memory facilitate transfer of control to the procedural system.
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Affiliation(s)
- Carolyn Quam
- Department of Speech and Hearing Sciences, Portland State University, Portland, OR, United States
- Department of Speech, Language, and Hearing Sciences, University of Arizona, Tucson, AZ, United States
- Department of Psychology, University of Arizona, Tucson, AZ, United States
| | - Alisa Wang
- Department of Speech, Language, and Hearing Sciences, University of Arizona, Tucson, AZ, United States
| | - W. Todd Maddox
- Cognitive Design and Statistical Consulting, LLC., Austin, TX, United States
| | - Kimberly Golisch
- Department of Psychology, University of Arizona, Tucson, AZ, United States
- College of Medicine–Tucson, University of Arizona, Tucson, AZ, United States
| | - Andrew Lotto
- Department of Speech, Language, and Hearing Sciences, University of Arizona, Tucson, AZ, United States
- Department of Speech, Language, and Hearing Sciences, University of Florida, Gainesville, FL, United States
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19
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Dien J, Karuzis V, Haarmann HJ. Probing culture in the head: the neural correlates of relational models. Soc Neurosci 2018; 13:648-666. [PMID: 29614912 DOI: 10.1080/17470919.2018.1459313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Relational Models Theory or RMT proposes that there are four universal ways in which socio-economic relations can be organized. According to the RMT, each of its four relational models (Communal Sharing, Authority Ranking, Equality Matching, and Market Pricing) is associated with a distinct cognitive representation, with a cumulative pattern in which each relational model is a superset of the next lower model. This report for the first time uses a combination of cognitive and the social neuroscience to put this model to the test. RMT proposes that members of every culture use all four relational models, just in different proportions. It should therefore be possible to study their neural correlates in a mono-cultural sample. In this study, thirty-nine European-American students were imaged in a 3T Siemens Trio with a 24-channel head coil while rating the extent to which each relational model organized relationships with each of thirty-two acquaintances/friend/relatives in a boxcar design. FreeSurfer Functional Analysis Stream (FS-FAST) analyses revealed distinct patterns of activation for each of the relational models. The activations did not follow a cumulative hierarchical pattern, suggestive that this aspect of the RMT model should be revised.
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Affiliation(s)
- Joseph Dien
- a Maryland Neuroimaging Center , University of Maryland , College Park , MD , USA
| | - Valerie Karuzis
- b Center for Advanced Study of Language , University of Maryland , College Park , Maryland , USA
| | - Henk J Haarmann
- b Center for Advanced Study of Language , University of Maryland , College Park , Maryland , USA
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20
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Edmunds CER, Milton F, Wills AJ. Due Process in Dual Process: Model-Recovery Simulations of Decision-Bound Strategy Analysis in Category Learning. Cogn Sci 2018; 42 Suppl 3:833-860. [PMID: 29570837 DOI: 10.1111/cogs.12607] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 01/18/2018] [Accepted: 02/15/2018] [Indexed: 11/28/2022]
Abstract
Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, ). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to Decision Bound analysis (Maddox & Ashby, ). Here, we examine the accuracy of this analysis in a series of model-recovery simulations. In Simulation 1, over a third of simulated participants using an Explicit (conjunctive) strategy were misidentified as using a Procedural strategy. In Simulation 2, nearly all simulated participants using a Procedural strategy were misidentified as using an Explicit strategy. In Simulation 3, we re-examined a recently reported COVIS-supporting dissociation (Smith et al., ) and found that these misidentification errors permit an alternative, single-process, explanation of the results. Implications for due process in the future evaluation of dual-process theories, including recommendations for future practice, are discussed.
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Edmunds C, Wills AJ, Milton F. Initial training with difficult items does not facilitate category learning. Q J Exp Psychol (Hove) 2018; 72:151-167. [PMID: 28847234 DOI: 10.1080/17470218.2017.1370477] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
In the phenomenon of transfer along a continuum (TAC), initial training on easy items facilitates later learning of a harder discrimination. TAC is a widely replicated cross-species phenomenon that is well predicted by certain kinds of associative theory. A recent report of an approximately opposite phenomenon (i.e., facilitation by initial training on hard items) poses a puzzle for such theories, but is predicted by a dual-system model (COVIS). However, across four experiments, we present substantial evidence that this counterintuitive finding was in error. Rather, the result appears to be a false positive and, as such, should not form part of the evidence base for COVIS nor be considered as a counter-example to the pervasive TAC phenomenon.
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22
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Loonis RF, Brincat SL, Antzoulatos EG, Miller EK. A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning. Neuron 2017; 96:521-534.e7. [PMID: 29024670 PMCID: PMC5662212 DOI: 10.1016/j.neuron.2017.09.032] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Revised: 08/07/2017] [Accepted: 09/20/2017] [Indexed: 10/18/2022]
Abstract
A meta-analysis of non-human primates performing three different tasks (Object-Match, Category-Match, and Category-Saccade associations) revealed signatures of explicit and implicit learning. Performance improved equally following correct and error trials in the Match (explicit) tasks, but it improved more after correct trials in the Saccade (implicit) task, a signature of explicit versus implicit learning. Likewise, error-related negativity, a marker for error processing, was greater in the Match (explicit) tasks. All tasks showed an increase in alpha/beta (10-30 Hz) synchrony after correct choices. However, only the implicit task showed an increase in theta (3-7 Hz) synchrony after correct choices that decreased with learning. In contrast, in the explicit tasks, alpha/beta synchrony increased with learning and decreased thereafter. Our results suggest that explicit versus implicit learning engages different neural mechanisms that rely on different patterns of oscillatory synchrony.
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Affiliation(s)
- Roman F Loonis
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Anatomy and Neurobiology, Boston University, Boston MA, 02118, USA
| | - Scott L Brincat
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Evan G Antzoulatos
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Neuroscience, Department of Neurobiology, Physiology and Behavior, University of California Davis, Davis, CA 95616, USA
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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