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A computational account of vocabulary re-acquisition in aphasia


Project Description

Language disorders after stroke can highly restrain communication in every-day life. However, short but intensive delivery of speech therapy has shown to be effective even in the chronic phase of aphasia recovery. The interplay of factors influencing the degree of responsiveness to treatment and the crucial mechanisms promoting therapy effects are still unresolved.

Our previous research revealed that:
(i) Re-acquisition of lexical entries in aphasia is highly effective, but there are yet unspecified boundaries to vocabulary growth (Abel et al., 2014).
(ii) The site of the left-hemisphere brain lesion influences compensatory activations and therapy outcomes, and both hemispheres contribute to recovery (Abel et al., 2015).
(iii) Bilateral contribution to recovery can be well explained in a two-hemisphere computational model (Schapiro et al., 2013; see also Ueno et al., 2013).
(iv) The right hemisphere contribution may be less efficient than the one from the language-dominant left hemisphere as registered by functional magnetic resonance imaging (fMRI) (Abel et al., 2014, 2015).

In the present project, we aim to establish a neuro-computational account of therapy effects in aphasia. Thereby we obtain a much deeper understanding of the factors and mechanisms which determine therapy outcomes.

In order to reach this aim, we will perform a neuroscience based therapy study including 20 healthy controls and 20 patients with aphasia which will be recruited using a current patient database (see Butler et al., 2014). We will use fMRI to detect the origin of impaired lexical processing, assess patient performance and patient characteristics, register therapy-related changes in processing, vary and analyse the size of vocabulary to be learnt, and simulate therapy effects and vocabulary limitations in the two-hemisphere computational model.

We expect to observe enhanced efficiency/ altered brain activations (fMRI) associated with therapy effects and vocabulary size, which may vary individually depending on factors undermined by simulations. The project will further our knowledge on optimal vocabulary size and factors affecting re-acquisition which will feedback into clinical settings.

The successful candidate will be trained in a broad range of research techniques including statistical processing, brain imaging techniques and clinical practices.

Candidates are expected to hold, or about to obtain, an upper second class (or equivalent) in Psychology, Neuroscience, or Speech and Language Therapy. Clinical experience, research experience and/or knowledge on computational modelling are highly appreciated.

This 4-year full-time PhD, due to commence January 2017, is open to candidates able to provide evidence of self-arranged funding/ sponsorship.

Funding Notes

This project has a Band 2 fee. Details of our different fee bands can be found on our website. For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website. Informal enquiries may be made directly to the primary supervisor.

References

1. Abel, S., Weiller, C., Huber, W., & Willmes, K. (2014). Neural underpinnings for model-oriented therapy of aphasic word production. Neuropsychologia, 57, 154-165.
2. Abel, S., Weiller, C., Huber, W., Willmes, K., & Specht, K. (2015). Therapy-induced brain reorganisation patterns in aphasia. Brain, 138, 1097-1112.
3. Butler, R. A., Lambon Ralph, M. A., & Woollams, A. M. (2014). Capturing multidimensionality in stroke aphasia: mapping principal behavioural components to neural structures. Brain, 137, 3248-3266.
4. Schapiro, A. C., McClelland, J. L., Welbourne, S. R., Rogers, T. T., & Lambon Ralph, M. A. (2013). Why bilateral damage is worse than unilateral damage to the brain. J Cogn Neurosci, 25, 2107-2123.
5. Ueno, T. & Lambon Ralph, M. A. (2013). The roles of the "ventral" semantic and "dorsal" pathways in conduite d'approche: a neuroanatomically-constrained computational modeling investigation. Front Hum.Neurosci., 7, 422.

How good is research at University of Manchester in Psychology, Psychiatry and Neuroscience?

FTE Category A staff submitted: 67.70

Research output data provided by the Research Excellence Framework (REF)

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