Efficacy of a gamified digital therapy for speech production in people with chronic aphasia (iTalkBetter): behavioural and imaging outcomes of a phase II item-randomised clinical trial.

Background: Aphasia is among the most debilitating of symptoms affecting stroke survivors. Speech and language therapy (SLT) is effective, but many hours of practice are required to make clinically meaningful gains. One solution to this 'dosage' problem is to automate therapeutic approaches via self-supporting apps so people with aphasia (PWA) can amass practice as it suits them. However, response to therapy is variable and no clinical trial has yet identified the key brain regions required to engage with word-retrieval therapy. Methods: Between Sep 7, 2020 and Mar 1, 2022 at University College London in the UK, we carried out a phase II, item-randomised clinical trial in 27 PWA using a novel, self-led app, 'iTalkBetter', which utilises confrontation naming therapy. Unlike previously reported apps, it has a real-time utterance verification system that drives its adaptive therapy algorithm. Therapy items were individually randomised to provide balanced lists of 'trained' and 'untrained' items matched on key psycholinguistic variables and baseline performance. PWA practised with iTalkBetter over a 6-week therapy block. Structural and functional MRI data were collected to identify therapy-related changes in brain states. A repeated-measures design was employed. The trial was registered at ClinicalTrials.gov (NCT04566081). Findings: iTalkBetter significantly improved naming ability by 13% for trained items compared with no change for untrained items, an average increase of 29 words (SD = 26) per person; beneficial effects persisted at three months. PWA's propositional speech also significantly improved. iTalkBetter use was associated with brain volume increases in right auditory and left anterior prefrontal cortices. Task-based fMRI identified dose-related activity in the right temporoparietal junction. Interpretation: Our findings suggested that iTalkBetter significantly improves PWAs' naming ability on trained items. The effect size is similar to a previous RCT of computerised therapy, but this is the first study to show transfer to a naturalistic speaking task. iTalkBetter usage and dose caused observable changes in brain structure and function to key parts of the surviving language perception, production and control networks. iTalkBetter is being rolled-out as an app for all PWA and anomia: https://www.ucl.ac.uk/icn/research/research-groups/neurotherapeutics/projects/digital-interventions-neuro-rehabilitation-0 so that they can increase their dosage of practice-based SLT. Funding: National Institute for Health and Care Research, Wellcome Centre for Human Neuroimaging.

Prevalence, patterns, and predictors of patient-reported non-motor outcomes at 30 days after acute stroke: Prospective observational hospital cohort study.

BACKGROUND: Adverse non-motor outcomes are common after acute stroke and likely to substantially affect quality of life, yet few studies have comprehensively assessed their prevalence, patterns, and predictors across multiple health domains. AIMS: We aimed to identify the prevalence, patterns, and the factors associated with non-motor outcomes 30 days after stroke. METHODS: This prospective observational hospital cohort study-Stroke Investigation in North and Central London (SIGNAL)-identified patients with acute ischemic stroke or intracerebral hemorrhage (ICH) admitted to the Hyperacute Stroke Unit (HASU) at University College Hospital (UCH), London, between August 1, 2018 and August 31, 2019. We assessed non-motor outcomes (anxiety, depression, fatigue, sleep, participation in social roles and activities, pain, bowel function, and bladder function) at 30-day follow-up using the Patient-Reported Outcome Measurement Information System-Version 29 (PROMIS-29) scale and Barthel Index scale. RESULTS: We obtained follow-up data for 605/719 (84.1%) eligible patients (mean age 72.0 years; 48.3% female; 521 with ischemic stroke, 84 with ICH). Anxiety (57.0%), fatigue (52.7%), bladder dysfunction (50.2%), reduced social participation (49.2%), and pain (47.9%) were the commonest adverse non-motor outcomes. The rates of adverse non-motor outcomes in ⩾ 1, ⩾ 2 and ⩾ 3 domains were 89%, 66.3%, and 45.8%, respectively; in adjusted analyses, stroke due to ICH (compared to ischemic stroke) and admission stroke severity were the strongest and most consistent predictors. There were significant correlations between bowel dysfunction and bladder dysfunction (κ = 0.908); reduced social participation and bladder dysfunction (κ = 0.844); and anxiety and fatigue (κ = 0.613). We did not identify correlations for other pairs of non-motor domains. CONCLUSION: Adverse non-motor outcomes were very common at 30 days after stroke, affecting nearly 90% of evaluated patients in at least one health domain, about two-thirds in two or more domains, and almost 50% in three or more domains. Stroke due to ICH and admission stroke severity were the strongest and most consistent predictors. Adverse outcomes occurred in pairs of domains, such as with anxiety and fatigue. Our findings emphasize the importance of a multi-domain approach to effectively identify adverse non-motor outcomes after stroke to inform the development of more holistic patient care pathways after stroke.

Systematic evaluation of high-level visual deficits and lesions in posterior cerebral artery stroke.

Knowledge about the consequences of stroke on high-level vision comes primarily from single case studies of patients selected based on their behavioural profiles, typically patients with specific stroke syndromes like pure alexia or prosopagnosia. There are, however, no systematic, detailed, large-scale evaluations of the more typical clinical behavioural and lesion profiles of impairments in high-level vision after posterior cerebral artery stroke. We present behavioural and lesion data from the Back of the Brain project, to date the largest (N = 64) and most detailed examination of patients with cortical posterior cerebral artery strokes selected based on lesion location. The aim of the current study was to relate behavioural performance with faces, objects and written words to lesion data through two complementary analyses: (i) a multivariate multiple regression analysis to establish the relationships between lesion volume, lesion laterality and the presence of a bilateral lesion with performance and (ii) a voxel-based correlational methodology analysis to establish whether there are distinct or separate regions within the posterior cerebral artery territory that underpin the visual processing of words, faces and objects. Behaviourally, most patients showed more general deficits in high-level vision (n = 22) or no deficits at all (n = 21). Category-selective deficits were rare (n = 6) and were only found for words. Overall, total lesion volume was most strongly related to performance across all three domains. While behavioural impairments in all domains were observed following unilateral left and right as well as bilateral lesions, the regions most strongly related to performance mainly confirmed the pattern reported in more selective cases. For words, these included a left hemisphere cluster extending from the occipital pole along the fusiform and lingual gyri; for objects, bilateral clusters which overlapped with the word cluster in the left occipital lobe. Face performance mainly correlated with a right hemisphere cluster within the white matter, partly overlapping with the object cluster. While the findings provide partial support for the relative laterality of posterior brain regions supporting reading and face processing, the results also suggest that both hemispheres are involved in the visual processing of faces, words and objects.

Colour perception deficits after posterior stroke: Not so rare after all?

Cerebral achromatopsia is an acquired colour perception impairment caused by brain injury, and is generally considered to be rare. Both hemispheres are thought to contribute to colour perception, but most published cases have had bilateral or right hemisphere lesions. In contrast to congenital colour blindness that affects the discrimination between specific hues, cerebral achromatopsia is often described as affecting perception across all colours. Most studies of cerebral achromatopsia have been single cases or case series of patients with colour perception deficits. Here, we explore colour perception deficits in an unbiased sample of patients with stroke affecting the posterior cerebral artery (N = 63) from the Back of the Brain project. Patients were selected based on lesion location only, and not on the presence of a given symptom. All patients were tested with the Farnsworth D-15 Dichotomous Colour Blindness Test and performance compared to matched controls (N = 45) using single case statistics. In patients with abnormal performance, the patterns of colour difficulties were qualitatively analysed. 22% of the patients showed significant problems with colour discrimination (44% of patients with bilateral lesions, 28% with left hemisphere lesions and 5% with right hemisphere lesions). Lesion analyses identified two regions in ventral occipital temporal areas in the left hemisphere as particularly strongly related to impaired performance in colour perception, but also indicated that bilateral lesions are more strongly associated with impaired performance that unilateral lesions. While some patients only had mild deficits, colour perception impairments were in many cases severe. Many patients had selective deficits only affecting the perception of some hues. The results suggest that colour perception difficulties following PCA stroke are common, and that they vary in severity and expression. In addition, the results point towards bilateral processing of colour perception with a left hemispheric domination, contradicting previous reports.

A simple intervention for disorders of consciousness- is there a light at the end of the tunnel?

Sleep is a physiological state necessary for memory processing, learning and brain plasticity. Patients with disorders of consciousness (DOC) show none or minimal sign of awareness of themselves or their environment but appear to have sleep-wake cycles. The aim of our study was to assess baseline circadian rhythms and sleep in patients with DOC; to optimize circadian rhythm using an intervention combining blue light, melatonin and caffeine, and to identify the impact of this intervention on brain function using event related potentials. We evaluated baseline circadian rhythms and sleep in 17 patients with DOC with 24-h polysomnography (PSG) and 4-hourly saliva melatonin measurements for 48 h. Ten of the 17 patients (5 female, age 30-71) were then treated for 5 weeks with melatonin each night and blue light and caffeine treatment in the mornings. Behavioral assessment of arousal and awareness [Coma recovery scale-revised (CRS-R)], 24-h polysomnography and 4-hourly saliva melatonin measurements, oddball mismatch negativity (MMN) and subject's own name (SON) experiments were performed twice at baseline and following intervention. Baseline sleep was abnormal in all patients. Cosinor analysis of saliva melatonin results revealed that averaged baseline % rhythmicity was low (M: 31%, Range: 13-66.4%, SD: 18.4). However, increase in % Melatonin Rhythm following intervention was statistically significant (p = 0.012). 7 patients showed improvement of CRS-R scores with intervention and this was statistically significant (p = 0.034). All the patients who had improvement of clinical scores also had statistically significant improvement of neurophysiological responses on MMN and SON experiments at group level (p = 0.001). Our study shows that sleep and circadian rhythms are severely deranged in DOC but optimization is possible with melatonin, caffeine and blue light treatment. Clinical and physiological parameters improved with this simple and inexpensive intervention. Optimization of sleep and circadian rhythms should be integrated into rehabilitation programs for people with DOC.

Exploring the use of dopaminergic medication to treat hemispatial inattention during in-patient post-stroke neurorehabilitation.

Hemispatial inattention (HSI), a lateralised impairment of spatial processing, is a common consequence of stroke. It is a poor prognostic indicator for functional recovery and interferes with the progress during in-patient neurorehabilitation. Dopaminergic medication has shown promise in improving HSI in the chronic post-stroke period but is untested in more acute settings, e.g. during in-patient neurorehabilitation. We audited the use of dopaminergic medication in ten sequential patients with post-stroke HSI, on an open-label exploratory basis. Patients' response to medication was assessed individually, using a three-week Off-On-Off protocol. We employed a mixture of bedside and functional measures, and made a multidisciplinary judgement of efficacy in individual patients. In six out of 10 patients, there was a convincing improvement of HSI while on medication, which reversed when it was paused. There was a mean 57% relative increase in target detection in the star cancellation test on the most affected side (on vs. off medication). In the six responders, medication was therefore continued throughout their admission without adverse effects. The star cancellation test was sensitive to HSI in most patients but in two cases failed to detect changes that were picked up by a functional assessment (Kessler Functional Neglect Assessment Protocol). We found this multidisciplinary approach to be feasible in an in-patient neurorehabilitation setting. We suggest further research to explore the efficacy of dopaminergic medication in improving neurorehabilitation outcomes for patients with post-stroke HSI. We suggest that more detailed N-of-1 assessments of treatment response, with internal blinding, may be a productive approach.

The impact of the UK COVID-19 pandemic on patient-reported health outcomes after stroke: a retrospective sequential comparison.

BACKGROUND AND PURPOSE: The COVID-19 pandemic and related social isolation measures are likely to have adverse consequences on community healthcare provision and outcome after acute illnesses treated in hospital, including stroke. We aimed to evaluate the impact of the COVID-19 pandemic on patient-reported health outcomes after hospital admission for acute stroke. METHODS: This retrospective study included adults with acute stroke admitted to the University College Hospital NHS Foundation Trust Hyperacute Stroke Unit. We included two separate cohorts of consecutively enrolled patients from the same geographical population at two time points: 16th March-16th May 2018 (pre-COVID-19 pandemic); and 16th March-16th May 2020 (during the COVID-19 pandemic). Patients in both cohorts completed the validated Patient Reported Outcomes Measurement Information System-29 (PROMIS-29 version 2.0) at 30 days after stroke. RESULTS: We included 205 patients who were alive at 30 days (106 admitted before and 99 admitted during the COVID-19 pandemic), of whom 201/205 (98%) provided patient-reported health outcomes. After adjustment for confounding factors, admission with acute stroke during the COVID-19 pandemic was independently associated with increased anxiety (ß = 28.0, p < 0.001), fatigue (ß = 9.3, p < 0.001), depression (ß = 4.5, p = 0.002), sleep disturbance (ß = 2.3, p = 0.018), pain interference (ß = 10.8, p < 0.001); and reduced physical function (ß = 5.2, p < 0.001) and participation in social roles and activities (ß = 6.9, p < 0.001). CONCLUSION: Compared with the pre-pandemic cohort, patients admitted with acute stroke during the first wave of the COVID-19 pandemic reported poorer health outcomes at 30 day follow-up in all domains. Stroke service planning for any future pandemic should include measures to mitigate this major adverse impact on patient health.

Lesions that do or do not impair digit span: a study of 816 stroke survivors.

Prior studies have reported inconsistency in the lesion sites associated with verbal short-term memory impairments. Here we asked: How many different lesion sites can account for selective impairments in verbal short-term memory that persist over time, and how consistently do these lesion sites impair verbal short-term memory? We assessed verbal short-term memory impairments using a forward digit span task from the Comprehensive Aphasia Test. First, we identified the incidence of digit span impairments in a sample of 816 stroke survivors (541 males/275 females; age at stroke onset 56 ± 13 years; time post-stroke 4.4 ± 5.2 years). Second, we studied the lesion sites in a subgroup of these patients (n = 39) with left hemisphere damage and selective digit span impairment-defined as impaired digit span with unimpaired spoken picture naming and spoken word comprehension (tests of speech production and speech perception, respectively). Third, we examined how often these lesion sites were observed in patients who either had no digit span impairments or digit span impairments that co-occurred with difficulties in speech perception and/or production tasks. Digit span impairments were observed in 222/816 patients. Almost all (199/222 = 90%) had left hemisphere damage to five small regions in basal ganglia and/or temporo-parietal areas. Even complete damage to one or more of these five regions was not consistently associated with persistent digit span impairment. However, when the same regions were spared, only 5% (23/455) presented with digit span impairments. These data suggest that verbal short-term memory impairments are most consistently associated with damage to left temporo-parietal and basal ganglia structures. Sparing of these regions very rarely results in persistently poor verbal short-term memory. These findings have clinical implications for predicting recovery of verbal short-term memory after stroke.

Category-selective deficits are the exception and not the rule: Evidence from a case-series of 64 patients with ventral occipito-temporal cortex damage.

The organisational principles of the visual ventral stream are still highly debated, particularly the relative association/dissociation between word and face recognition and the degree of lateralisation of the underlying processes. Reports of dissociations between word and face recognition stem from single case-studies of category selective impairments, and neuroimaging investigations of healthy participants. Despite the historical reliance on single case-studies, more recent group studies have highlighted a greater commonality between word and face recognition. Studying individual patients with rare selective deficits misses (a) important variability between patients, (b) systematic associations between task performance, and (c) patients with mild, severe and/or non-selective impairments; meaning that the full spectrum of deficits is unknown. The Back of the Brain project assessed the range and specificity of visual perceptual impairment in 64 patients with posterior cerebral artery stroke recruited based on lesion localization and not behavioural performance. Word, object, and face processing were measured with comparable tests across different levels of processing to investigate associations and dissociations across domains. We present two complementary analyses of the extensive behavioural battery: (1) a data-driven analysis of the whole patient group, and (2) a single-subject case-series analysis testing for deficits and dissociations in each individual patient. In both analyses, the general organisational principle was of associations between words, objects, and faces even following unilateral lesions. The majority of patients either showed deficits across all domains or in no domain, suggesting a spectrum of visuo-perceptual deficits post stroke. Dissociations were observed, but they were the exception and not the rule: Category-selective impairments were found in only a minority of patients, all of whom showed disproportionate deficits for words. Interestingly, such selective word impairments were found following both left and right hemisphere lesions. This large-scale investigation of posterior cerebral artery stroke patients highlights the bilateral representation of visual perceptual function.

The Architect Who Lost the Ability to Imagine: The Cerebral Basis of Visual Imagery.

While the loss of mental imagery following brain lesions was first described more than a century ago, the key cerebral areas involved remain elusive. Here we report neuropsychological data from an architect (PL518) who lost his ability for visual imagery following a bilateral posterior cerebral artery (PCA) stroke. We compare his profile to three other patients with bilateral PCA stroke and another architect with a large PCA lesion confined to the right hemisphere. We also compare structural images of their lesions, aiming to delineate cerebral areas selectively lesioned in acquired aphantasia. When comparing the neuropsychological profile and structural magnetic resonance imaging (MRI) for the aphantasic architect PL518 to patients with either a comparable background (an architect) or bilateral PCA lesions, we find: (1) there is a large overlap of cognitive deficits between patients, with the very notable exception of aphantasia which only occurs in PL518, and (2) there is large overlap of the patients' lesions. The only areas of selective lesion in PL518 is a small patch in the left fusiform gyrus as well as part of the right lingual gyrus. We suggest that these areas, and perhaps in particular the region in the left fusiform gyrus, play an important role in the cerebral network involved in visual imagery.

How Does iReadMore Therapy Change the Reading Network of Patients with Central Alexia?

Central alexia (CA) is an acquired reading disorder co-occurring with a generalized language deficit (aphasia). The roles of perilesional and ipsilesional tissue in recovery from poststroke aphasia are unclear. We investigated the impact of reading training (using iReadMore, a therapy app) on the connections within and between the right and left hemisphere of the reading network of patients with CA. In patients with pure alexia, iReadMore increased feedback from left inferior frontal gyrus (IFG) region to the left occipital (OCC) region. We aimed to identify whether iReadMore therapy was effective through a similar mechanism in patients with CA. Participants with chronic poststroke CA (n = 23) completed 35 h of iReadMore training over 4 weeks. Reading accuracy for trained and untrained words was assessed before and after therapy. The neural response to reading trained and untrained words in the left and right OCC, ventral occipitotemporal, and IFG regions was examined using event-related magnetoencephalography. The training-related modulation in effective connectivity between regions was modeled at the group level with dynamic causal modeling. iReadMore training improved participants' reading accuracy by an average of 8.4% (range, -2.77 to 31.66) while accuracy for untrained words was stable. Training increased regional sensitivity in bilateral frontal and occipital regions, and strengthened feedforward connections within the left hemisphere. Our data suggest that iReadMore training in these patients modulates lower-order visual representations, as opposed to higher-order, more abstract representations, to improve word-reading accuracy.SIGNIFICANCE STATEMENT This is the first study to conduct a network-level analysis of therapy effects in participants with poststroke central alexia. When patients trained with iReadMore (a multimodal, behavioral, mass practice, computer-based therapy), reading accuracy improved by an average 8.4% on trained items. A network analysis of the magnetoencephalography data associated with this improvement revealed an increase in regional sensitivity in bilateral frontal and occipital regions and strengthening of feedforward connections within the left hemisphere. This indicates that in patients with CA iReadMore engages lower-order, intact resources within the left hemisphere (posterior to their lesion locations) to improve word reading. This provides a foundation for future research to investigate reading network modulation in different CA subtypes, or for sentence-level therapy.

Recovery after stroke: not so proportional after all?

The proportional recovery rule asserts that most stroke survivors recover a fixed proportion of lost function. To the extent that this is true, recovery from stroke can be predicted accurately from baseline measures of acute post-stroke impairment alone. Reports that baseline scores explain more than 80%, and sometimes more than 90%, of the variance in the patients' recoveries, are rapidly accumulating. Here, we show that these headline effect sizes are likely inflated. The key effects in this literature are typically expressed as, or reducible to, correlation coefficients between baseline scores and recovery (outcome scores minus baseline scores). Using formal analyses and simulations, we show that these correlations will be extreme when outcomes are significantly less variable than baselines, which they often will be in practice regardless of the real relationship between outcomes and baselines. We show that these effect sizes are likely to be over-optimistic in every empirical study that we found that reported enough information for us to make the judgement, and argue that the same is likely to be true in other studies as well. The implication is that recovery after stroke may not be as proportional as recent studies suggest.

How right hemisphere damage after stroke can impair speech comprehension.

Acquired language disorders after stroke are strongly associated with left hemisphere damage. When language difficulties are observed in the context of right hemisphere strokes, patients are usually considered to have atypical functional anatomy. By systematically integrating behavioural and lesion data from brain damaged patients with functional MRI data from neurologically normal participants, we investigated when and why right hemisphere strokes cause language disorders. Experiment 1 studied right-handed patients with unilateral strokes that damaged the right (n = 109) or left (n = 369) hemispheres. The most frequently impaired language task was: auditory sentence-to-picture matching after right hemisphere strokes; and spoken picture description after left hemisphere strokes. For those with auditory sentence-to-picture matching impairments after right hemisphere strokes, the majority (n = 9) had normal performance on tests of perceptual (visual or auditory) and linguistic (semantic, phonological or syntactic) processing. Experiment 2 found that these nine patients had significantly more damage to dorsal parts of the superior longitudinal fasciculus and the right inferior frontal sulcus compared to 75 other patients who also had right hemisphere strokes but were not impaired on the auditory sentence-to-picture matching task. Damage to these right hemisphere regions caused long-term speech comprehension difficulties in 67% of patients. Experiments 3 and 4 used functional MRI in two groups of 25 neurologically normal individuals to show that within the regions identified by Experiment 2, the right inferior frontal sulcus was normally activated by (i) auditory sentence-to-picture matching; and (ii) one-back matching when the demands on linguistic and non-linguistic working memory were high. Together, these experiments demonstrate that the right inferior frontal cortex contributes to linguistic and non-linguistic working memory capacity (executive function) that is needed for normal speech comprehension. Our results link previously unrelated literatures on the role of the right inferior frontal cortex in executive processing and the role of executive processing in sentence comprehension; which in turn helps to explain why right inferior frontal activity has previously been reported to increase during recovery of language function after left hemisphere stroke. The clinical relevance of our findings is that the detrimental effect of right hemisphere strokes on language is (i) much greater than expected; (ii) frequently observed after damage to the right inferior frontal sulcus; (iii) task dependent; (iv) different to the type of impairments observed after left hemisphere strokes; and (v) can result in long-lasting deficits that are (vi) not the consequence of atypical language lateralization.

Aphasia Recovery: When, How and Who to Treat?

PURPOSE OF REVIEW: We now know that speech and language therapy (SALT) is effective in the rehabilitation of aphasia; however, there remains much individual variability in the response to interventions. So, what works for whom, when and how? RECENT FINDINGS: This review evaluates the current evidence for the efficacy of predominantly impairment-focused aphasia interventions with respect to optimal dose, intensity, timing and distribution or spacing of treatment. We conclude that sufficient dose of treatment is required to enable clinical gains and that e-therapies are a promising and practical way to achieve this goal. In addition, aphasia can be associated with other cognitive deficits and may lead to secondary effects such as low mood and social isolation. In order to personalise individual treatments to optimise recovery, we need to develop a greater understanding of the interactions between these factors.

Variational Bayesian inversion for hierarchical unsupervised generative embedding (HUGE).

A recently introduced hierarchical generative model unified the inference of effective connectivity in individual subjects and the unsupervised identification of subgroups defined by connectivity patterns. This hierarchical unsupervised generative embedding (HUGE) approach combined a hierarchical formulation of dynamic causal modelling (DCM) for fMRI with Gaussian mixture models and relied on Markov chain Monte Carlo (MCMC) sampling for inference. While well suited for the inversion of complex hierarchical models, MCMC-based sampling suffers from a computational burden that is prohibitive for many applications. To address this problem, this paper derives an efficient variational Bayesian (VB) inversion scheme for HUGE that simultaneously provides approximations to the posterior distribution over model parameters and to the log model evidence. The face validity of the VB scheme was tested using two synthetic fMRI datasets with known ground truth. Additionally, an empirical fMRI dataset of stroke patients and healthy controls was used to evaluate the practical utility of the method in application to real-world problems. Our analyses demonstrate good performance of our VB scheme, with a marked speed-up of model inversion by two orders of magnitude compared to MCMC, while maintaining a similar level of accuracy. Notably, additional acceleration would be possible if parallel computing techniques were applied. Generally, our VB implementation of HUGE is fast enough to support multi-start procedures for whole-group analyses, a useful strategy to ameliorate problems with local extrema. HUGE thus represents a potentially useful practical solution for an important problem in clinical neuromodeling and computational psychiatry, i.e., the unsupervised detection of subgroups in heterogeneous populations that are defined by effective connectivity.

Predicting language outcomes after stroke: Is structural disconnection a useful predictor?

For many years, researchers have sought to understand whether and when stroke survivors with acquired language impairment (aphasia) will recover. There is broad agreement that lesion location information should play some role in these predictions, but still no consensus on the best or right way to encode that information. Here, we address the emerging emphasis on the structural connectome in this work - specifically the claim that disrupted white matter connectivity conveys important, unique prognostic information for stroke survivors with aphasia. Our sample included 818 stroke patients extracted from the PLORAS database, which associates structural MRI from stroke patients with language assessment scores from the Comprehensive Aphasia Test (CAT) and basic demographic. Patients were excluded when their lesions were too diffuse or small (<1 cm3) to be detected by the Automatic Lesion Identification toolbox, which we used to encode patients' lesions as binary lesion images in standard space. Lesions were encoded using the 116 regions defined by the Automatic Anatomical Labelling atlas. We examined prognostic models driven by both "lesion load" in these regions (i.e. the proportion of each region destroyed by each patient's lesion), and by the disconnection of the white matter connections between them which was calculated via the Network Modification toolbox. Using these data, we build a series of prognostic models to predict first one ("naming"), and then all of the language scores defined by the CAT. We found no consistent evidence that connectivity disruption data in these models improved our ability to predict any language score. This may be because the connectivity disruption variables are strongly correlated with the lesion load variables: correlations which we measure both between pairs of variables in their original form, and between principal components of both datasets. Our conclusion is that, while both types of structural brain data do convey useful, prognostic information in this domain, they also appear to convey largely the same variance. We conclude that connectivity disruption variables do not help us to predict patients' language skills more accurately than lesion location (load) data alone.

Randomized trial of iReadMore word reading training and brain stimulation in central alexia.

Central alexia is an acquired reading disorder co-occurring with a generalized language deficit (aphasia). We tested the impact of a novel training app, 'iReadMore', and anodal transcranial direct current stimulation of the left inferior frontal gyrus, on word reading ability in central alexia. The trial was registered at www.clinicaltrials.gov (NCT02062619). Twenty-one chronic stroke patients with central alexia participated. A baseline-controlled, repeated-measures, crossover design was used. Participants completed two 4-week blocks of iReadMore training, one with anodal stimulation and one with sham stimulation (order counterbalanced between participants). Each block comprised 34 h of iReadMore training and 11 stimulation sessions. Outcome measures were assessed before, between and after the two blocks. The primary outcome measures were reading ability for trained and untrained words. Secondary outcome measures included semantic word matching, sentence reading, text reading and a self-report measure. iReadMore training resulted in an 8.7% improvement in reading accuracy for trained words (95% confidence interval 6.0 to 11.4; Cohen's d = 1.38) but did not generalize to untrained words. Reaction times also improved. Reading accuracy gains were still significant (but reduced) 3 months after training cessation. Anodal transcranial direct current stimulation (compared to sham), delivered concurrently with iReadMore, resulted in a 2.6% (95% confidence interval -0.1 to 5.3; d = 0.41) facilitation for reading accuracy, both for trained and untrained words. iReadMore also improved performance on the semantic word-matching test. There was a non-significant trend towards improved self-reported reading ability. However, no significant changes were seen at the sentence or text reading level. In summary, iReadMore training in post-stroke central alexia improved reading ability for trained words, with good maintenance of the therapy effect. Anodal stimulation resulted in a small facilitation (d = 0.41) of learning and also generalized to untrained items.10.1093/brain/awy138_video1awy138media15796149281001.

A generative model of whole-brain effective connectivity.

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure.

How distributed processing produces false negatives in voxel-based lesion-deficit analyses.

In this study, we hypothesized that if the same deficit can be caused by damage to one or another part of a distributed neural system, then voxel-based analyses might miss critical lesion sites because preservation of each site will not be consistently associated with preserved function. The first part of our investigation used voxel-based multiple regression analyses of data from 359 right-handed stroke survivors to identify brain regions where lesion load is associated with picture naming abilities after factoring out variance related to object recognition, semantics and speech articulation so as to focus on deficits arising at the word retrieval level. A highly significant lesion-deficit relationship was identified in left temporal and frontal/premotor regions. Post-hoc analyses showed that damage to either of these sites caused the deficit of interest in less than half the affected patients (76/162 = 47%). After excluding all patients with damage to one or both of the identified regions, our second analysis revealed a new region, in the anterior part of the left putamen, which had not been previously detected because many patients had the deficit of interest after temporal or frontal damage that preserved the left putamen. The results illustrate how (i) false negative results arise when the same deficit can be caused by different lesion sites; (ii) some of the missed effects can be unveiled by adopting an iterative approach that systematically excludes patients with lesions to the areas identified in previous analyses, (iii) statistically significant voxel-based lesion-deficit mappings can be driven by a subset of patients; (iv) focal lesions to the identified regions are needed to determine whether the deficit of interest is the consequence of focal damage or much more extensive damage that includes the identified region; and, finally, (v) univariate voxel-based lesion-deficit mappings cannot, in isolation, be used to predict outcome in other patients.