Publications
32 results found
Geranmayeh F, barban A, Leech R, et al., 2022, Cerebrovascular reactivity has negligible contribution to haemodynamic lag after stroke: implications for fMRI studies., Stroke, 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
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
Liew S-L, Lo BP, Donnelly MR, et al., 2022, A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms, SCIENTIFIC DATA, Vol: 9
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- Citations: 4
Zavaliangos-Petropulu A, Lo B, Donnelly MR, et 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
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).
Stefaniak JD, Geranmayeh F, Ralph MAL, 2022, The multidimensional nature of aphasia recovery post-stroke, BRAIN, Vol: 145, Pages: 1354-1367, ISSN: 0006-8950
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- Citations: 5
Lorenz R, Johal M, Dick F, et al., 2021, A Bayesian optimization approach for rapidly mapping residual network function in stroke, BRAIN, Vol: 144, Pages: 2120-2134, ISSN: 0006-8950
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- Citations: 4
Cole JH, Lorenz R, Geranmayeh F, et 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>
Cole JH, Lorenz R, Geranmayeh F, et 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.
Cole JH, Lorenz R, Geranmayeh F, et 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.
Sliwinska M, Ribeiro Violante I, Wise R, et 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.
Geranmayeh F, Wing Chau T, Wise RJS, et 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
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.
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
Patterson K, Kopelman MD, Woollams AM, et al., 2015, Semantic memory: Which side are you on?, NEUROPSYCHOLOGIA, Vol: 76, Pages: 182-191, ISSN: 0028-3932
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- Citations: 14
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
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- Citations: 18
Geranmayeh F, Wise RJS, Leech R, et 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.
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
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- Citations: 141
Geranmayeh F, Wise RJS, Mehta A, et al., 2014, Overlapping Networks Engaged during Spoken Language Production and Its Cognitive Control, JOURNAL OF NEUROSCIENCE, Vol: 34, Pages: 8728-8740, ISSN: 0270-6474
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- Citations: 89
Brownsett SLE, Warren JE, Geranmayeh F, et al., 2014, Cognitive control and its impact on recovery from aphasic stroke, BRAIN, Vol: 137, Pages: 242-254, ISSN: 0006-8950
Wilkinson T, Geranmayeh F, Dassan P, et al., 2013, Neuroimaging in transient global amnesia., Pract Neurol, Vol: 13, Pages: 56-57
Dassan P, Geranmayeh F, Davies N, et al., 2012, INPATIENT OBSTETRIC REFERRALS TO NEUROLOGY SERVICES: A CROSS-SECTIONAL SURVEY, Annual Meeting of the Association-of-British-Neurologists, Publisher: BMJ PUBLISHING GROUP, ISSN: 0022-3050
Geranmayeh F, Pritchard J, Janssen JC, 2012, Recurrent sensory and motor neuropathy., Pract Neurol, Vol: 12, Pages: 253-256
Geranmayeh F, Brownsett SLE, Leech R, et al., 2012, The contribution of the inferior parietal cortex to spoken language production, BRAIN AND LANGUAGE, Vol: 121, Pages: 47-57, ISSN: 0093-934X
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- Citations: 44
Lyons OTA, Smith C, Winston JS, et al., 2010, Impact of UK academic foundation programmes on aspirations to pursue a career in academia, MEDICAL EDUCATION, Vol: 44, Pages: 996-1005, ISSN: 0308-0110
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- Citations: 20
Geranmayeh F, Clement E, Feng LH, et al., 2010, Genotype-phenotype correlation in a large population of muscular dystrophy patients with LAMA2 mutations, NEUROMUSCULAR DISORDERS, Vol: 20, Pages: 241-250, ISSN: 0960-8966
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- Citations: 111
Geranmayeh F, Waters K, Takon I, et al., 2008, Chromosome 10q26.3 deletion associated with neurodevelopmental impairment and dysmorphic features, British Human Genetics Conference, Publisher: B M J PUBLISHING GROUP, Pages: S61-S61, ISSN: 0022-2593
Geranmayeh F, Usman S, Bhutiani R, 2008, Jejunal ischaemia - rare aetiologies and a surgical dilemma, ACTA GASTRO-ENTEROLOGICA BELGICA, Vol: 71, Pages: 263-266, ISSN: 1784-3227
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- Citations: 1
Geranmayeh F, Ashkan K, 2008, Mind on canvas: anatomy, signs and neurosurgery in art, BRITISH JOURNAL OF NEUROSURGERY, Vol: 22, Pages: 1-12, ISSN: 0268-8697
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- Citations: 8
Geranmayeh F, Scheithauer BW, Spitzer C, et al., 2007, Microglia in gemistocytic astrocytomas, NEUROSURGERY, Vol: 60, Pages: 159-166, ISSN: 0148-396X
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- Citations: 20
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