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Addressing patients’ communication support needs through speech-language pathologist-nurse information-sharing: Employing ethnography to understand the acute stroke context
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A Systematic Review of Studies Describing the Effectiveness, Acceptability, and Potential Harms of Place-Based Interventions to Address Loneliness and Mental Health Problems
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Time for talk: The work of reflexivity in developing empirical understanding of speech and language therapist and nursing interaction on stroke wards
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Family history of FXTAS is associated with age-related cognitive-linguistic decline among mothers with the FMR1 premutation.
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In: Journal of neurodevelopmental disorders, vol 14, iss 1 (2022)
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Computational Models in Electroencephalography.
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In: Brain topography, vol 35, iss 1 (2022)
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Abstract:
Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses in silico and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by "computational model" is understood in many different ways by researchers in different fields of neuroscience and psychology, hindering communication and collaboration. In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level models, and behavior. On the one hand, computational models serve to investigate the mechanisms that generate brain activity, for example measured with EEG, such as the transient emergence of oscillations at different frequency bands and/or with different spatial topographies. On the other hand, computational models serve to design experiments and test hypotheses in silico. The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal. This is crucial for an accurate interpretation of EEG measurements that may ultimately serve in the development of novel clinical applications.
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Keyword:
1.1 Normal biological development and functioning; Bioengineering; Clinical applications; Clinical Sciences; Cognitive Sciences; Computational modeling; Electroencephalography; Experimental Psychology; Mental Health; Multiscale modeling; Networking and Information Technology R&D; Neurological; Neurosciences
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URL: https://escholarship.org/uc/item/16r8k9f0
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Supplemental Materials from Long-range sequential dependencies precede complex syntactic production in language acquisition ...
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Supplemental Materials from Long-range sequential dependencies precede complex syntactic production in language acquisition ...
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Investigating the Folk Concept of Pain: Implication & Projection ...
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Nasal rustle perception without secretion bubbling (Oren et al., 2022) ...
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Nasal rustle perception without secretion bubbling (Oren et al., 2022) ...
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| 11 |
Supplementary material from "Gesture is the primary modality for language creation" ...
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Supplementary material from "Gesture is the primary modality for language creation" ...
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| 13 |
Supplementary material from "Long-range sequential dependencies precede complex syntactic production in language acquisition" ...
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| 14 |
Supplementary material from "Long-range sequential dependencies precede complex syntactic production in language acquisition" ...
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| 15 |
Decoding verbal working memory representations of Chinese characters from Broca's area
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Creating a theoretical framework to underpin discourse assessment and intervention in aphasia
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| 17 |
When forgetting fosters learning: A neural network model for Statistical Learning
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Early bilingual experience is associated with change detection ability in adults
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FFA and OFA encode distinct types of face identity information
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Patient experiences of therapy for borderline personality disorder: Commonalities and differences between dialectical behaviour therapy and mentalization-based therapy and relation to outcomes
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