Predicting Language Recovery in Post-Stroke Aphasia using Behavior and Functional MRI

Abstract Background: Language outcomes after speech and language therapy in post-stroke aphasia are challenging to predict. This study examines behavioral language measures and resting state fMRI (rsfMRI) as prognostics for response to language therapy. Methods: Seventy patients with chronic aphasia were recruited and treated for one of three deficits: anomia, agrammatism, or dysgraphia. Treatment effect was measured by performance on a treatment-specific language measure, assessed before and after three months of language therapy. Each patient also underwent an additional 27 language assessments and an fMRI scan at baseline. Patient scans were decomposed into 20 components by group independent component analysis, and each component time series was summarized by its fractional amplitude of low-frequency fluctuations (fALFF). Results: Treatment effects were modelled with elastic net regression, using clinical language measures and fALFF imaging predictors independently. Correlation analyses showed high performance for language measures in anomia (r = 0.958, n = 30) and for fALFF predictors in agrammatism (r = 0.940, n = 11) and dysgraphia (r = 0.925, n = 18). These models are state-of-the-art for aphasia recovery prediction. Conclusion: Predicting aphasia recovery with rsfMRI features may outperform predictions from clinical language measures in some patient populations. This suggests rsfMRI may have prognostic value for chronic aphasia patients undergoing language therapy. Differentiating patients who respond to therapy from those who do not is a first step towards personalized treatment in post-stroke aphasia.

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Predicting language recovery in post-stroke aphasia using behavior and functional MRI

Scientific Reports ◽

10.1038/s41598-021-88022-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Michael Iorga ◽

James Higgins ◽

David Caplan ◽

Richard Zinbarg ◽

Swathi Kiran ◽

...

Keyword(s):

Low Frequency ◽

Resting State Fmri ◽

Language Outcomes ◽

Language Therapy ◽

Post Stroke ◽

Treatment Performance ◽

Before And After ◽

Language Assessments ◽

Pre Treatment ◽

Language Measures

AbstractLanguage outcomes after speech and language therapy in post-stroke aphasia are challenging to predict. This study examines behavioral language measures and resting state fMRI (rsfMRI) as predictors of treatment outcome. Fifty-seven patients with chronic aphasia were recruited and treated for one of three aphasia impairments: anomia, agrammatism, or dysgraphia. Treatment effect was measured by performance on a treatment-specific language measure, assessed before and after three months of language therapy. Each patient also underwent an additional 27 language assessments and a rsfMRI scan at baseline. Patient scans were decomposed into 20 components by group independent component analysis, and the fractional amplitude of low-frequency fluctuations (fALFF) was calculated for each component time series. Post-treatment performance was modelled with elastic net regression, using pre-treatment performance and either behavioral language measures or fALFF imaging predictors. Analysis showed strong performance for behavioral measures in anomia (R2 = 0.948, n = 28) and for fALFF predictors in agrammatism (R2 = 0.876, n = 11) and dysgraphia (R2 = 0.822, n = 18). Models of language outcomes after treatment trained using rsfMRI features may outperform models trained using behavioral language measures in some patient populations. This suggests that rsfMRI may have prognostic value for aphasia therapy outcomes.

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Self-managed, computerised speech and language therapy for patients with chronic aphasia post-stroke compared with usual care or attention control (Big CACTUS): a multicentre, single-blinded, randomised controlled trial

The Lancet Neurology ◽

10.1016/s1474-4422(19)30192-9 ◽

2019 ◽

Vol 18 (9) ◽

pp. 821-833 ◽

Cited By ~ 21

Author(s):

Rebecca Palmer ◽

Munyaradzi Dimairo ◽

Cindy Cooper ◽

Pam Enderby ◽

Marian Brady ◽

...

Keyword(s):

Randomised Controlled Trial ◽

Usual Care ◽

Controlled Trial ◽

Attention Control ◽

Speech And Language ◽

Language Therapy ◽

Speech And Language Therapy ◽

Post Stroke ◽

Chronic Aphasia ◽

Randomised Controlled

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Cognitive Pragmatic Rehabilitation Program in Schizophrenia: A Single Case fMRI Study

Neural Plasticity ◽

10.1155/2017/1612078 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Ilaria Gabbatore ◽

Francesca M. Bosco ◽

Elisabetta Geda ◽

Luigi Gastaldo ◽

Sergio Duca ◽

...

Keyword(s):

Single Case ◽

Low Frequency ◽

Resting State Fmri ◽

Rehabilitation Program ◽

Functional Changes ◽

Cognitive Components ◽

Communicative Performance ◽

Fmri Study ◽

Before And After ◽

Almost All

Introduction. The present study was intended to evaluate the effects of a rehabilitative training, the Cognitive Pragmatic Treatment (CPT), aimed at improving communicative-pragmatic abilities and the related cognitive components, on the cerebral modifications of a single case patient diagnosed with schizophrenia. Methods. The patient underwent two functional magnetic resonance imaging (fMRI) sessions, before and after the treatment. In order to assess brain changes, we calculated the Amplitude of Low Frequency Fluctuation (ALFF) index of the resting-state fMRI signal, which is interpreted as reflecting the intensity of the spontaneous regional activity of the brain. Behavioural measures of the patient’s communicative performance were also gathered before and after training and at follow-up. Results. The patient improved his communicative performance in almost all tests. Posttraining stronger ALFF signal emerged in the superior, inferior, and medial frontal gyri, as well as the superior temporal gyri. Conclusions. Even if based on a single case study, these preliminary results show functional changes at the cerebral level that seem to support the patient’s behavioural improvements.

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Post-stroke fatigue is linked to resting state posterior hypoactivity and prefrontal hyperactivity

10.1101/2021.03.17.21253777 ◽

2021 ◽

Author(s):

Georgia Mary Cotter ◽

Mohamed Salah Khlif ◽

Laura Bird ◽

Mark E Howard ◽

Amy Brodtmann ◽

...

Keyword(s):

Ischaemic Stroke ◽

Resting State ◽

Large Scale ◽

Brain Activity ◽

Low Frequency ◽

Resting State Fmri ◽

Stroke Severity ◽

Stroke Survivors ◽

Whole Brain ◽

Post Stroke

Background and Purpose. Fatigue is associated with poor functional outcomes and increased mortality following stroke. Survivors identify fatigue as one of their key unmet needs. Despite the growing body of research into post-stroke fatigue, the specific neural mechanisms remain largely unknown. Methods. This observational study included 63 stroke survivors (22 women; age 30-89 years; mean 67.5 years) from the Cognition And Neocortical Volume After Stroke (CANVAS) study, a cohort study examining cognition, mood, and brain volume in stroke survivors following ischaemic stroke. Participants underwent brain imaging 3 months post-stroke, including a 7-minute resting state fMRI echoplanar sequence. We calculated the fractional amplitude of low-frequency fluctuations, a measure of resting state brain activity at the whole-brain level. Results. Forty-five participants reported experiencing post-stroke fatigue as measured by an item on the Patient Health Questionnaire-9. A generalised linear regression model analysis with age, sex, and stroke severity covariates was conducted to compare resting state brain activity in the 0.01-0.08 Hz range, as well as its subcomponents - slow-5 (0.01-0.027 Hz), and slow-4 (0.027-0.073 Hz) frequency bands between fatigued and non-fatigued participants. We found no significant associations between post-stroke fatigue and ischaemic stroke lesion location or stroke volume. However, in the overall 0.01-0.08 Hz band, participants with post-stroke fatigue demonstrated significantly lower resting-state activity in the calcarine cortex (p<0.001, cluster-corrected pFDR=0.009, k=63) and lingual gyrus (p<0.001, cluster-corrected pFDR=0.025, k=42) and significantly higher activity in the medial prefrontal cortex (p<0.001, cluster-corrected pFDR=0.03, k=45), attributed to slow-4 and slow-5 oscillations, respectively. Conclusions. Post-stroke fatigue is associated with posterior hypoactivity and prefrontal hyperactivity, reflecting dysfunction within large-scale brain systems such as fronto-striatal-thalamic and frontal-occipital networks. These systems in turn might reflect a relationship between post-stroke fatigue and abnormalities in executive and visual functioning. This first whole-brain resting-state study provides new targets for further investigation of post-stroke fatigue beyond the lesion approach.

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Post-Training Sleep Modulates Topographical Relearning-Dependent Resting State Activity

Brain Sciences ◽

10.3390/brainsci11040476 ◽

2021 ◽

Vol 11 (4) ◽

pp. 476

Author(s):

Michele Deantoni ◽

Thomas Villemonteix ◽

Evelyne Balteau ◽

Christina Schmidt ◽

Philippe Peigneux

Keyword(s):

Resting State ◽

Low Frequency ◽

Brain Structures ◽

Resting State Fmri ◽

Related Activity ◽

State Activity ◽

Before And After ◽

Task Practice ◽

Behavioural Performance ◽

The Town

Continuation of experience-dependent neural activity during offline sleep and wakefulness episodes is a critical component of memory consolidation. Using functional magnetic resonance imaging (fMRI), offline consolidation effects have been evidenced probing behavioural and neurophysiological changes during memory retrieval, i.e., in the context of task practice. Resting state fMRI (rsfMRI) further allows investigating the offline evolution of recently learned information without the confounds of online task-related effects. We used rsfMRI to investigate sleep-related changes in seed-based resting functional connectivity (FC) and amplitude of low frequency fluctuations (ALFF) after spatial navigation learning and relearning. On Day 1, offline resting state activity was measured immediately before and after topographical learning in a virtual town. On Day 4, it was measured again before and after relearning in an extended version of the town. Navigation-related activity was also recorded during target retrieval, i.e., online. Participants spent the first post-training night under regular sleep (RS) or sleep deprivation (SD) conditions. Results evidence FC and ALFF changes in task-related neural networks, indicating the continuation of navigation-related activity in the resting state. Although post-training sleep did not modulate behavioural performance, connectivity analyses evidenced increased FC after post-training SD between navigation-related brain structures during relearning in the extended environment. These results suggest that memory traces were less efficiently consolidated after post-learning SD, eventually resulting in the use of compensatory brain resources to link previously stored spatial elements with the newly presented information.

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Capturing Neuroplastic Changes after iTBS in Patients with Post-Stroke Aphasia: A Pilot fMRI Study

Brain Sciences ◽

10.3390/brainsci11111451 ◽

2021 ◽

Vol 11 (11) ◽

pp. 1451

Author(s):

Shuo Xu ◽

Qing Yang ◽

Mengye Chen ◽

Panmo Deng ◽

Ren Zhuang ◽

...

Keyword(s):

Functional Connectivity ◽

Primary Motor Cortex ◽

High Efficiency ◽

Parietal Lobe ◽

Low Frequency ◽

Brain Regions ◽

Post Stroke ◽

Before And After ◽

Mri Scans ◽

The Right

Intermittent theta-burst stimulation (iTBS) is a high-efficiency transcranial magnetic stimulation (TMS) paradigm that has been applied to post-stroke aphasia (PSA). However, its efficacy mechanisms have not been clarified. This study aimed to explore the immediate effects of iTBS of the primary motor cortex (M1) of the affected hemisphere, on the functional activities and connectivity of the brains of PSA patients. A total of 16 patients with aphasia after stroke received iTBS with 800 pulses for 300 s. All patients underwent motor, language, and cognitive assessments and resting-state functional MRI scans immediately before and after the iTBS intervention. Regional, seed-based connectivity, and graph-based measures were used to test the immediate functional effects of the iTBS intervention, including the fractional amplitude of low-frequency fluctuation (fALFF), degree centrality (DC), and functional connectivity (FC) of the left M1 area throughout the whole brain. The results showed that after one session of iTBS intervention, the fALFF, DC, and FC values changed significantly in the patients’ brains. Specifically, the DC values were significantly higher in the right middle frontal gyrus and parts of the left parietal lobe (p < 0.05), while fALFF values were significantly lower in the right medial frontal lobe and parts of the left intracalcarine cortex (p < 0.05), and the strength of the functional connectivity between the left M1 area and the left superior frontal gyrus was reduced (p < 0.05). Our findings provided preliminary evidences that the iTBS on the ipsilesional M1 could induce neural activity and functional connectivity changes in the motor, language, and other brain regions in patients with PSA, which may promote neuroplasticity and functional recovery.

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