Imperial College London

DrFatemehGeranmayeh

Faculty of MedicineDepartment of Brain Sciences

Clinical Research Fellow
 
 
 
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fatemeh.geranmayeh00

 
 
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Commonwealth BuildingHammersmith Campus

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Summary

 

Publications

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41 results found

Gruia D-C, Trender W, Hellyer P, Banerjee S, Kwan J, Zetterberg H, Hampshire A, Geranmayeh Fet al., 2023, IC3 Protocol: a longitudinal observational study of cognition after stroke using novel digital health technology, BMJ Open, Vol: 13, ISSN: 2044-6055

Introduction Stroke is a major cause of death and disability worldwide, frequently resulting in persistent cognitive deficits among survivors. These deficits negatively impact recovery and therapy engagement, and their treatment is consistently rated as high priority by stakeholders and clinicians. Although clinical guidelines endorse cognitive screening for poststroke management, there is currently no gold-standard approach for identifying cognitive deficits after stroke, and clinical stroke services lack the capacity for long-term cognitive monitoring and care. Currently, available assessment tools are either not stroke-specific, not in-depth or lack scalability, leading to heterogeneity in patient assessments.Methods and analysis To address these challenges, a cost-effective, scalable and comprehensive screening tool is needed to provide a stroke-specific assessment of cognition. The current study presents such a novel digital tool, the Imperial Comprehensive Cognitive Assessment in Cerebrovascular Disease (IC3), designed to detect both domain-general and domain-specific cognitive deficits in patients after stroke with minimal input from a health professional. To ensure its reliability, we will use multiple validation approaches, and aim to recruit a large normative sample of age-matched, gender-matched and education-matched UK-based controls. Moreover, the IC3 assessment will be integrated within a larger prospective observational longitudinal clinical trial, where poststroke cognition will be examined in tandem with brain imaging and blood biomarkers to identify novel multimodal biomarkers of recovery after stroke. This study will enable deeper cognitive phenotyping of patients at a large scale, while identifying those with highest risk of progressive cognitive decline, as well as those with greatest potential for recovery.Ethics and dissemination This study has been approved by South West—Frenchay Research Ethics Committee (IRAS 299333) and authorised by

Journal article

Olafson ER, Sperber C, Jamison KW, Bowren MD, Boes AD, Andrushko JW, Borich MR, Boyd LA, Cassidy JM, Conforto AB, Cramer SC, Dula AN, Geranmayeh F, Hordacre B, Jahanshad N, Kautz SA, Lo B, MacIntosh BJ, Piras F, Robertson AD, Seo NJ, Soekadar SR, Thomopoulos SI, Vecchio D, Weng TB, Westlye LT, Winstein CJ, Wittenberg GF, Wong KA, Thompson PM, Liew S-L, Kuceyeski AFet al., 2023, Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes., bioRxiv

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and

Journal article

Sanguedolce G, Naylor PA, Geranmayeh F, 2023, Uncovering the potential for a weakly supervised end-to-end model in recognising speech from patient with post-stroke aphasia, 5th Clinical Natural Language Processing Workshop, Publisher: Association for Computational Linguistics, Pages: 182-190

Post-stroke speech and language deficits (aphasia) significantly impact patients' quality of life. Many with mild symptoms remain undiagnosed, and the majority do not receive the intensive doses of therapy recommended, due to healthcare costs and/or inadequate services. Automatic Speech Recognition (ASR) may help overcome these difficulties by improving diagnostic rates and providing feedback during tailored therapy. However, its performance is often unsatisfactory due to the high variability in speech errors and scarcity of training datasets. This study assessed the performance of Whisper, a recently released end-to-end model, in patients with post-stroke aphasia (PWA). We tuned its hyperparameters to achieve the lowest word error rate (WER) on aphasic speech. WER was significantly higher in PWA compared to age-matched controls (10.3% vs 38.5%, p < 0.001). We demonstrated that worse WER was related to the more severe aphasia as measured by expressive (overt naming, and spontaneous speech production) and receptive (written and spoken comprehension) language assessments. Stroke lesion size did not affect the performance of Whisper. Linear mixed models accounting for demographic factors, therapy duration, and time since stroke, confirmed worse Whisper performance with left hemispheric frontal lesions. We discuss the implications of these findings for how future ASR can be improved in PWA.

Conference paper

Ralph MAL, Stefaniak JD, Halai AD, Geranmayeh Fet al., 2023, Reply: Are recovery of fluency and recovery of phonology antagonistic?, BRAIN, Vol: 146, Pages: E52-E54, ISSN: 0006-8950

Journal article

Liew S-L, Schweighofer N, Cole JH, Zavaliangos-Petropulu A, Lo BP, Han LKM, Hahn T, Schmaal L, Donnelly MR, Jeong JN, Wang Z, Abdullah A, Kim JH, Hutton A, Barisano G, Borich MR, Boyd LA, Brodtmann A, Buetefisch CM, Byblow WD, Cassidy JM, Charalambous CC, Ciullo V, Conforto AB, Dacosta-Aguayo R, DiCarlo JA, Domin M, Dula AN, Egorova-Brumley N, Feng W, Geranmayeh F, Gregory CM, Hanlon CA, Hayward K, Holguin JA, Hordacre B, Jahanshad N, Kautz SA, Khlif MS, Kim H, Kuceyeski A, Lin DJ, Liu J, Lotze M, MacIntosh BJ, Margetis JL, Mataro M, Mohamed FB, Olafson ER, Park G, Piras F, Revill KP, Roberts P, Robertson AD, Sanossian N, Schambra HM, Seo NJ, Soekadar SR, Spalletta G, Stinear CM, Taga M, Tang WK, Thielman GT, Vecchio D, Ward NS, Westlye LT, Winstein CJ, Wittenberg GF, Wolf SL, Wong KA, Yu C, Cramer SC, Thompson PMet al., 2023, Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke, NEUROLOGY, Vol: 100, Pages: E2103-E2113, ISSN: 0028-3878

Journal article

Geranmayeh F, barban A, Leech R, murphy Ket al., 2023, Cerebrovascular reactivity has negligible contribution to haemodynamic lag after stroke: implications for fMRI studies., Stroke, Vol: 54, Pages: 1066-1077, ISSN: 0039-2499

Background: Functional MRI is ubiquitously used to study post-stroke recovery. However, the fMRI-derived haemodynamic responses are vulnerable to vascular insult which can result in reduced magnitude and temporal delays (lag) in the haemodynamic response function (HRF). The aetiology of HRF lag remains controversial, and a better understanding of it is required to ensure accurate interpretation of post-stroke fMRI studies. In this longitudinal study, we investigate the relationship between haemodynamic lag and cerebrovascular reactivity (CVR) following stroke.Methods: Voxelwise lag maps were calculated relative to a mean grey matter reference signal for 27 healthy controls and 59 patients with stroke across two timepoints (~2 weeks and ~4 months post-stroke), and two conditions: resting-state and breath-holding. The breath-holding condition was additionally used to calculate CVR in response to hypercapnia. HRF lag was computed for both conditions across tissue compartments: lesion, perilesional tissue, unaffected tissue of the lesioned hemisphere, and their homologue regions in the unaffected hemisphere. CVR and lag maps were correlated. Group, condition, and time effects were assessed using ANOVA analyses. Results: Compared with the average grey matter signal, a relative haemodynamic lead was observed in the primary sensorimotor cortices in resting-state and bilateral inferior parietal cortices in breath-holding condition. Whole-brain haemodynamic lag was significantly correlated across conditions irrespective of group, with regional differences across conditions suggestive of a neural network pattern. Patients showed relative lag in the lesioned hemisphere which significantly reduced over time. Breath-hold derived lag and CVR had no significant voxel-wise correlation in controls, or patients within the lesioned hemisphere or the homologous regions of the lesion and perilesional tissue in the right hemisphere (mean r<0.1). Conclusion: The contribution of altered

Journal article

Gruia DC, Combrie S, Coghlin J, Trender W, Hellyer P, Kwan J, Banerjee S, Hampshire A, Geranmayeh Fet al., 2023, Large-scale Reliability/Validity Assessments And Quantification Of Cognition Within The Imperial College Comprehensive Assessment For Cerebrovascular Disease (IC3): A Novel In-depth, Self-administered, Online Cognitive Tool, International Stroke Conference (ISC), Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0039-2499

Conference paper

Gruia D, Combrie S, Coghlin J, Trender W, Hellyer P, Kwan J, Banerjee S, Hampshire A, Geranmayeh Fet al., 2023, Large-scale normative data and reliability assessments within the Imperial College Comprehensive assessment for Cerebrovascular Disease (IC3): An in-depth, self-administered, digital cognitive tool, Publisher: SAGE PUBLICATIONS LTD, Pages: 77-78, ISSN: 1747-4930

Conference paper

Geranmayeh F, 2022, Cholinergic neurotransmitter system: a potential marker for post-stroke cognitive recovery (vol 145, pg 1576, 2022), BRAIN, Vol: 145, Pages: E81-E81, ISSN: 0006-8950

Journal article

Liew S-L, Lo BP, Donnelly MR, Zavaliangos-Petropulu A, Jeong JN, Barisano G, Hutton A, Simon JP, Juliano JM, Suri A, Wang Z, Abdullah A, Kim J, Ard T, Banaj N, Borich MR, Boyd LA, Brodtmann A, Buetefisch CM, Cao L, Cassidy JM, Ciullo V, Conforto AB, Cramer SC, Dacosta-Aguayo R, de la Rosa E, Domin M, Dula AN, Feng W, Franco AR, Geranmayeh F, Gramfort A, Gregory CM, Hanlon CA, Hordacre BG, Kautz SA, Khlif MS, Kim H, Kirschke JS, Liu J, Lotze M, MacIntosh BJ, Mataro M, Mohamed FB, Nordvik JE, Park G, Pienta A, Piras F, Redman SM, Revill KP, Reyes M, Robertson AD, Seo NJ, Soekadar SR, Spalletta G, Sweet A, Telenczuk M, Thielman G, Westlye LT, Winstein CJ, Wittenberg GF, Wong KA, Yu Cet al., 2022, A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms, SCIENTIFIC DATA, Vol: 9

Journal article

Stefaniak JD, Geranmayeh F, Ralph MAL, 2022, The multidimensional nature of aphasia recovery post-stroke, BRAIN, Vol: 145, Pages: 1354-1367, ISSN: 0006-8950

Journal article

Zavaliangos-Petropulu A, Lo B, Donnelly MR, Schweighofer N, Lohse K, Jahanshad N, Barisano G, Banaj N, Borich MR, Boyd LA, Buetefisch CM, Byblow WD, Cassidy JM, Charalambous CC, Conforto AB, DiCarlo JA, Dula AN, Egorova-Brumley N, Etherton MR, Feng W, Fercho KA, Geranmayeh F, Hanlon CA, Hayward KS, Hordacre B, Kautz SA, Khlif MS, Kim H, Kuceyeski A, Lin DJ, Liu J, Lotze M, MacIntosh BJ, Margetis JL, Mohamed FB, Piras F, Ramos-Murguialday A, Revill KP, Roberts PS, Robertson AD, Schambra HM, Seo NJ, Shiroishi MS, Stinear CM, Soekadar SR, Spalletta G, Taga M, Tang WK, Thielman GT, Vecchio D, Ward NS, Westlye LT, Werden E, Winstein C, Wittenberg GF, Wolf SL, Wong KA, Yu C, Brodtmann A, Cramer SC, Thompson PM, Liew S-Let al., 2022, Chronic stroke sensorimotor impairment is related to smaller hippocampal volumes: an ENIGMA analysis, Journal of the American Heart Association, Vol: 11, Pages: 1-30, ISSN: 2047-9980

BackgroundPersistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment.Methods and ResultsCross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P<0.025), controlling for age, sex, lesion volume, and lesioned hemisphere. In exploratory analyses, we tested for a sensorimotor impairment and sex interaction and relationships between lesion volume, sensorimotor damage, and hippocampal volume. Greater sensorimotor impairment was significantly associated with ipsilesional (P=0.005; β=0.16) but not contralesional (P=0.96; β=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; β=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; β=−0.26) and contralesional (P=0.006; β=−0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; β=−0.21) and extent of sensorimotor damage (P=0.003; β=−0.15).ConclusionsThe present study

Journal article

Geranmayeh F, 2022, Cholinergic neurotransmitter system: a potential marker for post-stroke cognitive recovery, Brain, Vol: 145, Pages: 1576-1578, ISSN: 0006-8950

This scientific commentary refers to ‘Cholinergic and hippocampalsystems facilitate cross-domain cognitive recovery after stroke’ byO’Sullivan et al. (https://doi.org/10.1093/brain/awac070).

Journal article

Lorenz R, Johal M, Dick F, Hampshire A, Leech R, Geranmayeh Fet al., 2021, A Bayesian optimization approach for rapidly mapping residual network function in stroke, BRAIN, Vol: 144, Pages: 2120-2134, ISSN: 0006-8950

Journal article

Liew SL, Zavaliangos-Petropulu A, Schweighofer N, Jahanshad N, Lang CE, Lohse KR, Banaj N, Barisano G, Baugh LA, Bhattacharya AK, Bigjahan B, Borich MR, Boyd LA, Brodtmann A, Buetefisch CM, Byblow WD, Cassidy JM, Charalambous CC, Ciullo V, Conforto AB, Craddock RC, Dula AN, Egorova N, Feng W, Fercho KA, Gregory CM, Hanlon CA, Hayward KS, Holguin JA, Hordacre B, Hwang DH, Kautz SA, Khlif MS, Kim B, Kim H, Kuceyeski A, Lo B, Liu J, Lin D, Lotze M, MacIntosh BJ, Margetis JL, Mohamed FB, Nordvik JE, Petoe MA, Piras F, Raju S, Ramos-Murguialday A, Revill KP, Roberts P, Robertson AD, Schambra HM, Seo NJ, Shiroish MS, Soekadar SR, Spalletta G, Stinear CM, Suri A, Tang WK, Thielman GT, Thijs VN, Vecchio D, Ward NS, Westlye LT, Winstein CJ, Wittenberg GF, Wong KA, Yu C, Wolf SL, Cramer SC, Thompson PM, Gallaguet AB, Brown T, Cloutier A, Cole J, Aguayo RD, DiCarlo J, Dimyan M, Domin M, Donnellly M, Edwardson M, Ermer E, Etherton M, Ferris J, Geranmayeh F, Hadidchi S, Hayes L, Jamison K, Juliano J, Margulies D, Mataro M, McGregor K, Olafson E, Perera-LLuna A, Phillips A, Rondina J, Rost N, Sanossian N, Sepehrband F, Shiroishi Met al., 2021, Smaller spared subcortical nuclei are associated with worse post-stroke sensorimotor outcomes in 28 cohorts worldwide, Brain Communications, Vol: 3

Up to two-thirds of stroke survivors experience persistent sensorimotor impairments. Recovery relies on the integrity of spared brain areas to compensate for damaged tissue. Deep grey matter structures play a critical role in the control and regulation of sensorimotor circuits. The goal of this work is to identify associations between volumes of spared subcortical nuclei and sensorimotor behaviour at different timepoints after stroke. We pooled high-resolution T1-weighted MRI brain scans and behavioural data in 828 individuals with unilateral stroke from 28 cohorts worldwide. Cross-sectional analyses using linear mixed-effects models related post-stroke sensorimotor behaviour to non-lesioned subcortical volumes (Bonferroni-corrected, P<0.004). We tested subacute (≤90 days) and chronic (≥180 days) stroke subgroups separately, with exploratory analyses in early stroke (≤21 days) and across all time. Sub-analyses in chronic stroke were also performed based on class of sensorimotor deficits (impairment, activity limitations) and side of lesioned hemisphere. Worse sensorimotor behaviour was associated with a smaller ipsilesional thalamic volume in both early (n=179; d=0.68) and subacute (n=274, d=0.46) stroke. In chronic stroke (n=404), worse sensorimotor behaviour was associated with smaller ipsilesional putamen (d=0.52) and nucleus accumbens (d=0.39) volumes, and a larger ipsilesional lateral ventricle (d=-0.42). Worse chronic sensorimotor impairment specifically (measured by the Fugl-Meyer Assessment; n=256) was associated with smaller ipsilesional putamen (d=0.72) and larger lateral ventricle (d=-0.41) volumes, while several measures of activity limitations (n=116) showed no significant relationships. In the full cohort across all time (n=828), sensorimotor behaviour was associated with the volumes of the ipsilesional nucleus accumbens (d=0.23), putamen (d=0.33), thalamus (d=0.33) and lateral ventricle (d=0.23). We demonstrate significant relationships be

Journal article

Cole JH, Lorenz R, Geranmayeh F, Wood T, Hellyer P, Williams S, Turkheimer F, Leech Ret al., 2019, Active Acquisition for multimodal neuroimaging, Wellcome Open Research, Vol: 3, Pages: 145-145

<ns4:p>In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field<ns4:bold>-</ns4:bold>of<ns4:bold>-</ns4:bold>view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.</ns4:p>

Journal article

Cole JH, Lorenz R, Geranmayeh F, Wood T, Hellyer P, Williams S, Turkheimer F, Leech Ret al., 2018, Active Acquisition for multimodal neuroimaging., Wellcome open research, Vol: 3, ISSN: 2398-502X

In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field <b>-</b>of <b>-</b>view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.

Journal article

Cole JH, Lorenz R, Geranmayeh F, Wood T, Hellyer P, Williams S, Turkheimer F, Leech Ret al., 2018, Active Acquisition for multimodal neuroimaging., Wellcome Open Res, Vol: 3, ISSN: 2398-502X

In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field -of -view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.

Journal article

Sliwinska M, Ribeiro Violante I, Wise R, Leech R, Devlin J, Geranmayeh F, Hampshire Aet al., 2017, Stimulating Multiple-Demand Cortex Enhances Vocabulary Learning, Journal of Neuroscience, Vol: 37, Pages: 7606-7618, ISSN: 1529-2401

It is well established that domain general networks (DGNs) in the human brain become active when diverse novel skills and behaviors are being learnt. However, their causal role in learning remains to be established. In the present study, we first performed functional magnetic resonance imaging on healthy participants to confirm that DGNs were most active in the initial stages of learning a novel vocabulary, consisting of pronounceable nonwords (pseudowords), each associated with a picture of a real object. We then examined, in healthy participants, whether repetitive transcranial magnetic stimulation of a frontal midline node of the cingulo-opercular DGN affected learning rates during the initial stages of learning. We report that stimulation of this node, but not a control brain region, substantially improved both accuracy and response times during the earliest stage of learning pseudowords-object associations. This stimulation had no effect on the processing of established vocabulary, tested by the accuracy and response times when participants decided whether a real word was accurately paired with a picture of an object. These results provide evidence that non-invasive stimulation to DGN nodes can enhance learning rates, thereby demonstrating their causal role in the learning process. We propose that this causal role makes DGNs candidate targets for experimental therapeutics; for example, in stroke patients with aphasia attempting to reacquire a vocabulary.

Journal article

Geranmayeh F, Wing Chau T, Wise RJS, Leech R, Hampshire Aet al., 2017, Domain-general subregions of the medial prefrontal cortex contribute to recovery of language after stroke, Brain, Vol: 140, Pages: 1947-1958, ISSN: 1460-2156

We hypothesized that the recovery of speech production after left hemisphere stroke not only depends on the integrity of language-specialized brain systems, but also on ‘domain-general’ brain systems that have much broader functional roles. The presupplementary motor area/dorsal anterior cingulate forms part of the cingular-opercular network, which has a broad role in cognition and learning. Consequently, we have previously suggested that variability in the recovery of speech production after aphasic stroke may relate in part to differences in patients’ abilities to engage this domain-general brain region. To test our hypothesis, 27 patients (aged 59 ± 11 years) with a left hemisphere stroke performed behavioural assessments and event-related functional magnetic resonance imaging tasks at two time points; first in the early phase (∼2 weeks) and then ∼4 months after the ictus. The functional magnetic resonance imaging tasks were designed to differentiate between activation related to language production (sentential overt speech production—Speech task) and activation related to cognitive processing (non-verbal decision making). Simple rest and counting conditions were also included in the design. Task-evoked regional brain activations during the early and late phases were compared with a longitudinal measure of recovery of language production. In accordance with a role in cognitive processing, substantial activity was observed within the presupplementary motor area/dorsal anterior cingulate during the decision-making task. Critically, the level of activation within this region during speech production correlated positively with the longitudinal recovery of speech production across the two time points (as measured by the in-scanner performance in the Speech task). This relationship was observed for activation in both the early phase (r = 0.363, P = 0.03 one-tailed) and the late phase (r = 0.538, P = 0.004). Furthermore, presupplem

Journal article

Geranmayeh F, Leech R, Wise RJS, 2016, Network dysfunction predicts speech production after left hemisphere stroke, Neurology, Vol: 86, Pages: 1296-1305, ISSN: 0028-3878

Objective: To investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke.Methods: We conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses.Results: Although activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production.Conclusions: Speech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior.

Journal article

Geranmayeh F, Wise R, 2015, NETWORK DYSFUNCTION IN POST-STROKE APHASIA, Annual Meeting of the Association-of-British-Neurologists (ABN), Publisher: BMJ PUBLISHING GROUP, ISSN: 0022-3050

Conference paper

Patterson K, Kopelman MD, Woollams AM, Brownsett SLE, Geranmayeh F, Wise RJSet al., 2015, Semantic memory: Which side are you on?, NEUROPSYCHOLOGIA, Vol: 76, Pages: 182-191, ISSN: 0028-3932

Journal article

Geranmayeh F, Leech R, Wise RJS, 2015, Semantic retrieval during overt picture description: Left anterior temporal or the parietal lobe?, NEUROPSYCHOLOGIA, Vol: 76, Pages: 125-135, ISSN: 0028-3932

Journal article

Geranmayeh F, Wise RJS, Leech R, Murphy Ket al., 2015, Measuring vascular reactivity with breath-holds after stroke: a method to aid interpretation of group-level BOLD signal changes in longitudinal fMRI studies, Human Brain Mapping, Vol: 36, Pages: 1755-1771, ISSN: 1097-0193

Blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) is a widely used technique to map brain function, and to monitor its recovery after stroke. Since stroke has a vascular etiology, the neurovascular coupling between cerebral blood flow and neural activity may be altered, resulting in uncertainties when interpreting longitudinal BOLD signal changes. The purpose of this study was to demonstrate the feasibility of using a recently validated breath-hold task in patients with stroke, both to assess group level changes in cerebrovascular reactivity (CVR) and to determine if alterations in regional CVR over time will adversely affect interpretation of task-related BOLD signal changes. Three methods of analyzing the breath-hold data were evaluated. The CVR measures were compared over healthy tissue, infarcted tissue and the peri-infarct tissue, both sub-acutely (∼2 weeks) and chronically (∼4 months). In this cohort, a lack of CVR differences in healthy tissue between the patients and controls indicates that any group level BOLD signal change observed in these regions over time is unlikely to be related to vascular alterations. CVR was reduced in the peri-infarct tissue but remained unchanged over time. Therefore, although a lack of activation in this region compared with the controls may be confounded by a reduced CVR, longitudinal group-level BOLD changes may be more confidently attributed to neural activity changes in this cohort. By including this breath-hold-based CVR assessment protocol in future studies of stroke recovery, researchers can be more assured that longitudinal changes in BOLD signal reflect true alterations in neural activity.

Journal article

Wise RJS, Geranmayeh F, 2015, Sentence and Narrative Speech Production: Investigations with PET and fMRI, Neurobiology of Language, Pages: 751-762, ISBN: 9780124077942

The ability to speak is one of the most important functions that humans possess, and its loss as a consequence of brain disease is devastating. Therefore, it must rank as one of the most important functions to study using modern functional imaging techniques. However, artifacts generated during overt speech create problems. Further, it is not clear whether speech production can be addressed, from a functional-anatomical perspective, as an organization based on separate specialized linguistic modules or as a distributed network with limited local embedded specialization. Beyond that, speech production is nothing without retrieval of personal and semantic memories and, depending on the communicative context, cognitive control. This chapter discusses the progress to date, the techniques to acquire data that are relatively free of artifact, and the use of multivariate analytical techniques to separate language, memory, and cognitive control networks from one another during the production of meaningful sentences.

Book chapter

Geranmayeh F, Brownsett SLE, Wise RJS, 2014, Task-induced brain activity in aphasic stroke patients: what is driving recovery?, BRAIN, Vol: 137, Pages: 2632-2648, ISSN: 0006-8950

Journal article

Geranmayeh F, Wise RJS, Mehta A, Leech Ret al., 2014, Overlapping Networks Engaged during Spoken Language Production and Its Cognitive Control, JOURNAL OF NEUROSCIENCE, Vol: 34, Pages: 8728-8740, ISSN: 0270-6474

Journal article

Brownsett SLE, Warren JE, Geranmayeh F, Woodhead Z, Leech R, Wise RJSet al., 2014, Cognitive control and its impact on recovery from aphasic stroke, BRAIN, Vol: 137, Pages: 242-254, ISSN: 0006-8950

Journal article

Wilkinson T, Geranmayeh F, Dassan P, Janssen JCet al., 2013, Neuroimaging in transient global amnesia., Pract Neurol, Vol: 13, Pages: 56-57

Journal article

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