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Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia
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In: Stroke (2022)
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Selective Functional Network Changes Following tDCS-Augmented Language Treatment in Primary Progressive Aphasia
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In: Front Aging Neurosci (2021)
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Predicting language recovery in post-stroke aphasia using behavior and functional MRI
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In: Sci Rep (2021)
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Distinct Neural Substrates Support Phonological and Orthographic Working Memory: Implications for Theories of Working Memory
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Distinct Neural Substrates Support Phonological and Orthographic Working Memory: Implications for Theories of Working Memory
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In: Front Neurol (2021)
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A Tool for Automatic Scoring of Spelling Performance
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In: J Speech Lang Hear Res (2020)
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Reading Proficiency Influences the effects of Transcranial Direct Current Stimulation: Evidence from Selective Modulation of Dorsal and Ventral Pathways of reading in Bilinguals
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In: Brain Lang (2020)
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Different patterns of functional network re-organization across the variants of primary progressive aphasia: A graph theoretic analysis
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In: Neurobiol Aging (2020)
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Reliability of BOLD signals in chronic stroke-induced aphasia ...
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Language network re-organization associated with word- and sentence-level language interventions in chronic aphasia ...
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The use of spelling for variant classification in primary progressive aphasia: Theoretical and practical implications
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In: Neuropsychologia (2019)
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Local response heterogeneity indexes experience-based neural differentiation in reading
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Learning in complex, multi-component cognitive systems: Different learning challenges within the same system
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In: J Exp Psychol Learn Mem Cogn (2018)
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Abstract:
Using word learning as an example of a complex system, we investigated how differences in the structure of the subcomponents in which learning occurs can have significant consequences for the challenge of integrating new information within such systems. Learning a new word involves integrating information into the two key stages/subcomponents of processing within the word production system. In the first stage, multiple semantic features are mapped onto a single word. Conversely, in the second stage, a single word is mapped onto multiple segmental features. We tested whether the unitary goal of word learning leads to different local outcomes in these two stages because of their reversed mapping patterns. Neurotypical individuals (N=17) learned names and semantic features for pictures of unfamiliar objects presented in semantically-related, segmentally-related and unrelated blocks. Both similarity types interfered with word learning. However, feature learning was differentially affected within the two main subcomponents of word production. Semantic similarity facilitated learning distinctive semantic features (i.e., features unique to each item), whereas segmental similarity facilitated learning shared segmental features (i.e., features common to several items in a block). These results are compatible with a model of incremental learning in which learning not only strengthens certain associations but also weakens others according to the local goals of each subcomponent. More generally, they demonstrate that the same overall learning goal can lead to opposite learning outcomes in the subcomponents of a complex system. The general principles uncovered here can be extended beyond word learning to other complex systems with multiple subcomponents.
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Keyword:
Article
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URL: https://doi.org/10.1037/xlm0000630 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6344326/ http://www.ncbi.nlm.nih.gov/pubmed/30035563
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Right hemisphere grey matter volume and language functions in stroke aphasia
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Intrahemispheric Perfusion in Chronic Stroke-Induced Aphasia
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Right Hemisphere Grey Matter Volume and Language Functions in Stroke Aphasia
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Intrahemispheric Perfusion in Chronic Stroke-Induced Aphasia
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Right Hemisphere Grey Matter Volume and Language Functions in Stroke Aphasia
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