Mapping the principal components of aphasic language recovery onto brain structure and function

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Stroke is unfortunately a major global health problem, with a person somewhere in the world having their first stroke everytwo seconds. The greatest risk factor for stroke is age, hence it represents a significant healthcare challenge in countrieslike the UK with an aging population. Cognitive deficits (problems with memory, attention, and language) are very commonafter stroke. Problems with language, known as aphasia, are seen in one in every three stroke cases soon after the stroke,and persist for more than a year after stroke in one in five cases. At present, we do not understand why some people makea good recovery from aphasia after stroke while others are left with chronic language problems. Nor do we understand whysome people respond well to speech and language therapy while others fail to benefit. The goal of this project is tocombine advanced neuroimaging with sophisticated neuropsychology to answer these questions.Ideally, we would like to be able to determine from initial brain scans whether someone is likely to recover well from theircurrent stroke induced impairments. We need to determine prognosis for stroke aphasic patients accurately so we can thendirect therapeutic resources effectively to those who need them most. We also need to understand what aspects of brainstructure and function predict a person's response to standard interventions, as then we can focus on alternative strategieswhere needed. To achieve these goals, we need to develop neural biomarkers that can reliably be used to determineprognosis over recovery and rehabilitation. Previous attempts to achieve prognosis over the course of recovery have hadlimited success as they have not used the most advanced measures of neural integrity not have they focussed on the mostrelevant aspects of neural function.This project will exploit the Anatomical Connectivity Mapping (ACM) method developed and patented by Bioxydyn, aprovider of high value quantitative imaging services and diagnostic tools to the pharmaceutical industry, healthcare andacademia. ACM provides a unique measure of long range connectivity across the whole brain, and therefore allows us tosearch for changes in brain structure associated with improved performance over recovery and rehabilitation. Our currentwork on a cohort of over 65 chronic stroke aphasic patients has shown increases in right hemisphere connectivity that arenot apparent on any other structural measure of brain integrity. Moreover, our recently published work (Butler, Lambon Ralph, & Woollams, 2014, Brain) has adopted a novel approach to lesion symptom mapping by using PrincipleComponents Analysis (PCA) to identify key cognitive dimensions and their neural correlates. Current work has shown thattissue concentration in these areas significantly improves prediction of performance in our chronic stroke aphasic sample.This project will involve firstly using the ACM information from the neural regions associated with specific languagefunctions identified using PCA (phonology, semantics, fluency; Halai, Woollams, & Lambon Ralph, in press, Cortex) in ourchronic stroke cohort of more than 65 patients to demonstrate that consideration of long range connectivity improvesprediction of performance. We will also obtain functional imaging data from a subset of 20 of these patients to demonstratethat activation in the PCA defined regions offers additional predictive power. We will then test out the prognostic power ofthese predictive models directly by recruiting 20 participants for testing and scanning in the subacute stage after stroke. Wewill use their ACM and functional activation in the PCA derived regions to predict their recovery outcomes at retest afterone year. To the extent this approach proves effective, placement with Bioxydyn will facilitate its translation into clinicalpractice for prognosis and to provide baseline recovery trajectories for use in clinical trials.