Recovery from aphasia in the first year after stroke

Brain, Journal Year: 2022, Volume and Issue: 146(3), P. 1021 - 1039

Published: April 7, 2022

Most individuals who experience aphasia after a stroke recover to some extent, with the majority of gains taking place in first year. The nature and time course this recovery process is only partially understood, especially its dependence on lesion location which are most important determinants outcome. aim study was provide comprehensive description patterns from year stroke. We recruited 334 patients acute left hemisphere supratentorial ischaemic or haemorrhagic evaluated their speech language function within 5 days using Quick Aphasia Battery (QAB). At initial point, 218 presented aphasia. Individuals were followed longitudinally, follow-up evaluations at 1 month, 3 months, post-stroke, wherever possible. Lesions manually delineated based clinical MRI CT imaging. Patients without divided into 13 groups similar, commonly occurring brain damage. Trajectories then investigated as group (i.e. extent) speech/language domain (overall function, word comprehension, sentence finding, grammatical construction, phonological encoding, motor programming, execution, reading). found that dynamic, multidimensional, gradated, little explanatory role for subtypes binary concepts such fluency. circumscribed frontal lesions recovered well, consistent previous observations. More surprisingly, larger extending parietal temporal lobes also did relatively temporal, temporoparietal, lesions. Persistent moderate severe deficits common extensive damage throughout middle cerebral artery distribution temporoparietal There striking differences between domains rates relationships overall suggesting specific differ extent they redundantly represented network, opposed depending specialized cortical substrates. Our findings have an immediate application will enable clinicians estimate likely individual patients, well uncertainty these predictions, acutely observable neurological factors.

Language: Английский

---

Disentangling neuroplasticity mechanisms in post-stroke language recovery

Brain and Language, Journal Year: 2024, Volume and Issue: 251, P. 105381 - 105381

Published: Feb. 24, 2024

A major objective in post-stroke aphasia research is to gain a deeper understanding of neuroplastic mechanisms that drive language recovery, with the ultimate goal enhancing treatment outcomes. Subsequent recent advances neuroimaging techniques, we now have ability examine more closely how neural activity patterns change after stroke. However, way these changes relate impairments and recovery still debated. The aim this review provide theoretical framework better investigate interpret neuroplasticity underlying aphasia. We detail two sets observed at synaptic level may explain functional findings network level: feedback-based homeostatic plasticity associative Hebbian plasticity. In conjunction mechanisms, higher-order cognitive control processes dynamically modulate other regions meet communication demands, despite reduced resources. This work provides network-level neurobiological for can be used define guidelines personalized development.

Language: Английский

---

Predicting Early Post-stroke Aphasia Outcome From Initial Aphasia Severity

Frontiers in Neurology, Journal Year: 2020, Volume and Issue: 11

Published: Feb. 21, 2020

Background: The greatest degree of language recovery in post-stroke aphasia takes place within the first weeks. Aphasia severity and lesion measures have been shown to be good predictors long-term outcomes. However, little is known about their implications early spontaneous recovery. present study sought determine which factors better predict outcomes individuals with aphasia. Methods: Twenty were assessed < 72 hours (acute) 10-14 days (subacute) after stroke onset. We developed a composite score (CS) consisting several linguistic sub-tests: repetition, oral comprehension naming. Lesion volume, load diffusion (fractional anisotropy (FA) axial diffusivity (AD)) from both arcuate fasciculi (AF) also extracted using MRI scans performed at same time points. A series regression analyses CS second assessment. Results: Among measures, only FA right AF was found significant predictor subacute outcome. when combined two hierarchical models FA, age either or size, initial account for most variance (R2 = 0.678), similarly complete 0.703 R2 0.73, respectively). Conclusions: Initial best outcome, whereas though highly correlated, show less influence on prediction model. suggest that predicting may differ those involved

Language: Английский

---

Trait Mindfulness and Functional Connectivity in Cognitive and Attentional Resting State Networks

Frontiers in Human Neuroscience, Journal Year: 2019, Volume and Issue: 13

Published: April 12, 2019

Mindfulness has been described as an orienting of attention to the present moment, with openness and compassion. Individuals displaying high trait mindfulness exhibit this tendency a more permanent personality attribute. Given numerous physical mental health benefits associated mindfulness, there is great interest in understanding neural substrates trait. The purpose current research was examine how individual differences functional connectivity five resting-state networks related cognition attention: default mode network (DMN), salience (SN), central executive (CEN), dorsal ventral (DAN VAN). Twenty-eight undergraduate participants completed Five-Facet Questionnaire (FFMQ), self-report measure which also provides scores on its sub-categories (Observing, Describing, Acting Awareness, Non-judging Inner Experience, Non-reactivity Experience). Participants then underwent structural MRI scan 7-min resting state scan. Resting-state data were analyzed using independent-component analyses. An analysis covariance (ANCOVA) performed determine relationship between each FFMQ score. These analyses indicated that: (1) facets showed increased regions attentional control, interoception, function; (2) decreased self-referential processing mind wandering. patterns are consistent some mindfulness-enhanced attention, self-regulation, focus experience. This study support for notion that non-judgmental moment facilitates integration cognition, sensation.

Language: Английский

---

Neural architectures of music – Insights from acquired amusia

Neuroscience & Biobehavioral Reviews, Journal Year: 2019, Volume and Issue: 107, P. 104 - 114

Published: Aug. 31, 2019

The ability to perceive and produce music is a quintessential element of human life, present in all known cultures. Modern functional neuroimaging has revealed that listening activates large-scale bilateral network cortical subcortical regions the healthy brain. Even most accurate structural studies do not reveal which brain areas are critical causally linked processing. Such questions may be answered by analysing effects focal lesions patients´ music. In this sense, acquired amusia after stroke provides unique opportunity investigate neural architectures crucial for normal Based on first longitudinal stroke-induced using modern multi-modal magnetic resonance imaging (MRI) techniques, such as advanced lesion-symptom mapping, grey white matter morphometry, tractography connectivity, we discuss structures processing, consider processing light dual-stream model right hemisphere, propose amusia.

Language: Английский

---

Cortical and Subcortical Control of Swallowing—Can We Use Information From Lesion Locations to Improve Diagnosis and Treatment for Patients With Stroke?

American Journal of Speech-Language Pathology, Journal Year: 2020, Volume and Issue: 29(2S), P. 1030 - 1043

Published: July 10, 2020

Purpose Swallowing is a complex process, mediated by broad bilateral neural network that spans from the brainstem to subcortical and cortical brain structures. Although cortex's role in swallowing was historically neglected, we now understand, especially through clinical observations research of patients with stroke, it substantially contributes control. Neuroimaging techniques (e.g., magnetic resonance imaging) have helped significantly elucidate areas, general, importance specific areas control healthy individuals stroke. We will review recent discoveries neuroimaging studies their generalizability across discuss potential implications translation dysphagia diagnosis treatment practice. Conclusions Stroke lesion locations been identified are commonly associated occurrence recovery dysphagia, suggesting scans provide useful information for improving However, individual differences structure function limit these relationships emphasize extent motor sensory pathology swallowing, how patient recovers, also depends on patient's constitution. The involvement damaged tissue before stroke health residual, undamaged crucial factors can differ between individuals.

Language: Английский

---

Predictors of Therapy Response in Chronic Aphasia: Building a Foundation for Personalized Aphasia Therapy

Journal of Stroke, Journal Year: 2022, Volume and Issue: 24(2), P. 189 - 206

Published: May 31, 2022

Chronic aphasia, a devastating impairment of language, affects up to third stroke survivors. Speech and language therapy has consistently been shown improve function in prior clinical trials, but few clinicially applicable predictors individual response have identified date. Consequently, clinicians struggle substantially with prognostication the management aphasia. A rising prevalence particular younger populations, emphasized increasing demand for personalized approach aphasia therapy, that is, aimed at maximizing recovery each reference evidence-based recommendations. In this narrative review, we discuss current state literature respect commonly studied particular, focus our discussion on biographical, neuropsychological, neurobiological predictors, emphasize limitations literature, summarize consistent findings, consider how research field can better support development therapy. conclusion, review indicates future efforts should aim recruit larger samples people including by establishing multisite centers.

Language: Английский

---

Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia

Stroke, Journal Year: 2022, Volume and Issue: 53(5), P. 1606 - 1614

Published: Jan. 26, 2022

Poststroke recovery depends on multiple factors and varies greatly across individuals. Using machine learning models, this study investigated the independent complementary prognostic role of different patient-related in predicting response to language rehabilitation after a stroke.Fifty-five individuals with chronic poststroke aphasia underwent battery standardized assessments structural functional magnetic resonance imaging scans, received 12 weeks treatment. Support vector random forest models were constructed predict responsiveness treatment using pretreatment behavioral, demographic, neuroimaging data.The best prediction performance was achieved by support model trained severity, demographics, measures anatomic integrity resting-state connectivity (F1=0.94). This resulted significantly superior compared all feature sets (F1=0.82, P<0.001) or single set (F1 range=0.68-0.84, P<0.001). Across training data yielded F1 score (F1=0.87).While multimodal demographic information carry aphasia, brain at rest stroke is particularly important predictor treatment, both alone combined other factors.

Language: Английский

---

Stroke lesion size – Still a useful biomarker for stroke severity and outcome in times of high-dimensional models

NeuroImage Clinical, Journal Year: 2023, Volume and Issue: 40, P. 103511 - 103511

Published: Jan. 1, 2023

The volumetric size of a brain lesion is frequently used stroke biomarker. It stands out among most imaging biomarkers for being one-dimensional variable that applicable in simple statistical models. In times machine learning algorithms, the question arises whether such still useful, or high-dimensional models on spatial information are superior. We included 753 first-ever anterior circulation ischemic patients (age 68.4±15.2 years; NIHSS at 24h 4.4±5.1; modified Rankin Scale (mRS) 3-months median[IQR] 1[0.75;3]) and traced lesions diffusion-weighted MRI. an out-of-sample model validation scheme, we predicted severity as measured by functional outcome mRS 3 months either from features size. For severity, best regression based performed significantly above chance (p<0.0001) with R2 = 0.322, but better 0.363 (t(752) 2.889; p=0.004). outcome, classification again accuracy 62.8%, which was not different (62.6%, p=0.80). With smaller training data sets only 150 50 patients, performance decreased up to point equivalent even inferior trained combination one did improve predictions. Lesion decent biomarker slightly particularly suited studies small samples. When low-dimensional desired, provides viable proxy features, whereas high-precision prediction personalised prognostic medicine should operate large

Language: Английский

---

Brain age predicts long-term recovery in post-stroke aphasia

Brain Communications, Journal Year: 2022, Volume and Issue: 4(5)

Published: Sept. 1, 2022

The association between age and language recovery in stroke remains unclear. Here, we used neuroimaging data to estimate brain age, a measure of structural integrity, examined the extent which at onset is associated with (i) cross-sectional performance, (ii) longitudinal function, beyond chronological alone. A total 49 participants (age: 65.2 ± 12.2 years, 25 female) underwent routine clinical (T1) bedside evaluation performance (Bedside Evaluation Screening Test-2) left hemisphere stroke. Brain was estimated from enantiomorphically reconstructed scans using machine learning algorithm trained on large sample healthy adults. subsample 30 returned for follow-up assessments least 2 years after onset. To account variability stroke, calculated proportional difference, i.e. difference age. Multiple regression models were constructed test effects outcomes. Lesion volume included as covariates all models. Accelerated compared worse overall aphasia severity (F(1, 48) = 5.65,

Language: Английский

---