An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications
Cordella, C., Marte, M. J., Liu, H., & Kiran, S. (2024). An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications. Perspectives of the ASHA Special Interest Groups. https://doi.org/10.1044/2024_PERSP-24-00037 Purpose The purpose of this article is to orient clinicians and researchers to machine learning (ML) approaches, as applied to the field […]
Machine learning predictions of recovery in bilingual post-stroke aphasia: Aligning insights with clinical evidence
Authors: Manuel Marte, Erin Carpenter, Michael Scimeca, Marissa Russell-Meill, Claudia Peñaloza, Uli Grasemann, Risto Miikkulainen, and Swathi Kiran, Accepted in the Journal Stroke Q&A with Manuel Marte What is this paper about? The paper examines how well machine learning models can predict language recovery outcomes in bilingual stroke survivors with aphasia. The study analyzed data […]
Impaired semantic control in the logopenic variant of primary progressive aphasia
Authors: Shalom K Henderson, Siddharth Ramanan, Matthew A Rouse, Thomas E Cope, Ajay D Halai, Karalyn E Patterson, James B Rowe, Matthew A Lambon Ralph. Q&A with Shalom Henderson What is this paper about? Even though the absence of object knowledge loss/semantic representation deficits constitutes ancillary diagnostic criteria for the logopenic variant of primary progressive […]
From the Annual Review of Linguistics, Charting the Course of Aphasia
Authors: Manuel Jose Marte, Marissa Russell-Meill, Nicole Carvalho, and Swathi Kiran Figure 1. Brain regions involved in various language tasks. Colors indicate specific tasks associated with each region. The medial frontal gyrus (red) is involved in working memory. The pars triangularis (magenta), pars opercularis (yellow), and pars orbitalis (tan) are involved in speech, language production, […]
Semantic processing in bilingual people with aphasia: An eye-tracking study examining cross-language semantic facilitation and interference.
About the Author: Sophie Blankenheim conducted her master’s thesis on this work under the supervision of Maria Varkanitsa Summary Bilingual lexical processing involves simultaneous activation of both languages, with encountering a word in one language priming the equivalent word in the other. Previous research on healthy individuals has shown that naming responses are slowed down […]
Evolution of word production errors after typicality-based semantic naming treatment in individuals with aphasia
Authors: Ran Li, Natalie Gilmore, Mia O’Connell, Swathi Kiran Q&A with Ran Li What is this paper about and why are the results important? This study implemented an error coding scale to assess changes in word production errors following a semantic-based naming therapy in individuals with chronic aphasia. It provides insights into the linguistic mechanisms that […]
Pars opercularis underlies efferent predictions and successful auditory feedback processing in speech: Evidence from left-hemisphere stroke
Interview with collaborators of the Center for Brain Recovery and publication authors Sarah Beach (MIT) and Caroline Niziolek (University of Wisconsin Madison) Abstract Hearing one’s own speech allows for acoustic self-monitoring in real time. Left-hemisphere motor planning regions are thought to give rise to efferent predictions that can be compared to true feedback in sensory cortices, resulting […]
Quantifying Dosage in Self-Managed Speech-Language Therapy: Exploring Components of Cumulative Intervention Intensity in a Real-World Mobile Health Data Set
Q&A with Claire Cordella What is the purpose of your research? Cumulative Intervention Intensity (CII; Baker 2012) is a proposed framework for conceptualizing and calculating dose which has been used to quantify intensity of speech-language therapy (SLT) in highly controlled laboratory studies and clinical trials. However, it is unknown whether CII can be applied to characterize […]
Resting-state brain network connectivity is an independent predictor of responsiveness to language therapy in chronic post-stroke aphasia
Recent paper by CBR’s researcher Isaac Falconer examines the brain network connectivity as a predictor of responsiveness to language therapy in people with aphasia. Features Q&A with author and link to full publication.