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BackgroundConsiderable evidence indicates that the functional connectome of the healthy human brain is highly stable, analogous to a fingerprint.ObjectiveWe investigated the stability of functional connectivity across tasks and sessions in a cohort of individuals with chronic stroke using a supervised machine learning approach.MethodsTwelve individuals with chronic stroke underwent functional magnetic resonance imaging (fMRI) seven times over 18 weeks. The middle 6 weeks consisted of intensive aphasia therapy. We collected fMRI data during rest and performance of 2 tasks. We calculated functional connectivity metrics for each imaging run, then applied a support vector machine to classify data on the basis of participant, task, and time point (pre- or posttherapy). Permutation testing established statistical significance.ResultsWhole brain functional connectivity matrices could be classified at levels significantly greater than chance on the basis of participant (87.1% accuracy; P < .0001), task (68.1% accuracy; P = .002), and time point (72.1% accuracy; P = .015). All significant effects were reproduced using only the contralesional right hemisphere; the left hemisphere revealed significant effects for participant and task, but not time point. Resting state data could also be used to classify task-based data according to subject (66.0%; P < .0001). While the strongest posttherapy changes occurred among regions outside putative language networks, connections with traditional language-associated regions were significantly more positively correlated with behavioral outcome measures, and other regions had more negative correlations and intrahemispheric connections.ConclusionsFindings suggest the profound importance of considering interindividual variability when interpreting mechanisms of recovery in studies of functional connectivity in stroke.

Cortical reorganization after stroke is thought to underlie functional improvement. Patterns of reorganization may differ depending on the amount of time since the stroke or the degree of improvement. We investigated these issues in a study of brain connectivity changes with aphasia therapy. Twelve individuals with chronic aphasia participated in a 6-week trial of imitation-based speech therapy. We assessed improvement on a repetition test and analyzed effective connectivity during functional magnetic resonance imaging of a speech observation task before and after therapy. Using structural equation modeling, patient networks were compared with a model derived from healthy controls performing the same task. Independent of the amount of time since the stroke, patients demonstrating behavioral improvement had networks that reorganized to be more similar to controls in two functional pathways in the left hemisphere. Independent of behavioral improvement, patients with remote infarcts (2-7 years poststroke; n = 5) also reorganized to more closely resemble controls in one of these pathways. Patients with far removed injury (>10 years poststroke; n = 3) did not show behavioral improvement and, despite similarities to the normative model and overall network heterogeneity, reorganized to be less similar to controls following therapy in a distinct right-lateralized pathway. Behavioral improvement following aphasia therapy was associated with connectivity more closely approximating that of healthy controls. Individuals who had a stroke more than a decade before testing also showed plasticity, with a few pathways becoming less like controls, possibly representing compensation. Better understanding of these mechanisms may help direct targeted brain stimulation.

ObjectiveTo test the generalization of an intensive imitation-based aphasia therapy to an unrelated narrative production task.DesignABA design study (A= no treatment; B= treatment) comparing imitation therapy to a baseline condition (pre-therapy). Participants produced narratives at two pre-therapy and two post-therapy time points. Narratives were analyzed for correct information units to determine the number and percent of communicative words produced.SettingA rehabilitation clinic and participants' homes.ParticipantsNineteen people with chronic aphasia following left hemisphere stroke.InterventionsSix weeks of intensive imitation therapy (3 x 30 minutes/day; 6 days/week) of words and phrases delivered via dedicated laptop.Main measuresWe performed t-tests to assess post-therapy changes in narrative production, as well as for intervals during which no intervention was provided. We used stepwise regression to examine the predictive value of demographic, behavioral, and neurological variables in determining treatment outcome.ResultsSignificant gains were made on the narrative production task in both the number (mean = 34.36; p = 0.009) and percent (mean = 3.99; p = 0.023) of correct information units produced. For percent of correct information units, the number of therapy sessions completed was the sole predictor of changes in production following therapy (r= +0.542; p = 0.020). No variables predicted change in number of correct information units produced. There were no significant differences between the two pre-therapy or the two post-therapy time points ( p > 0.294).ConclusionsIntensive imitation-based aphasia therapy may promote generalization to an unrelated narrative production task. Further investigation is indicated.

BackgroundPerformance variability in individuals with aphasia is typically regarded as a nuisance factor complicating assessment and treatment.ObjectiveWe present the alternative hypothesis that intraindividual variability represents a fundamental characteristic of an individual's functioning and an important biomarker for therapeutic selection and prognosis.MethodsA total of 19 individuals with chronic aphasia participated in a 6-week trial of imitation-based speech therapy. We assessed improvement both on overall language functioning and repetition ability. Furthermore, we determined which pretreatment variables best predicted improvement on the repetition test.ResultsSignificant gains were made on the Western Aphasia Battery-Revised (WAB) Aphasia Quotient, Cortical Quotient, and 2 subtests as well as on a separate repetition test. Using stepwise regression, we found that pretreatment intraindividual variability was the only predictor of improvement in performance on the repetition test, with greater pretreatment variability predicting greater improvement. Furthermore, the degree of reduction in this variability over the course of treatment was positively correlated with the degree of improvement.ConclusionsIntraindividual variability may be indicative of potential for improvement on a given task, with more uniform performance suggesting functioning at or near peak potential.

The networks that emerge in the analysis of resting state functional magnetic resonance imaging (rsfMRI) data are believed to reflect the intrinsic organization of the brain. One key property of such complex biological networks is modularity, a measure of community structure. This topological characteristic changes in neurological disease and recovery. Nineteen subjects with language disorders after stroke (aphasia) underwent neuroimaging and behavioral assessment at multiple time points before (baseline) and after an imitation-based therapy. Language was assessed with a narrative production task. Group independent component analysis was performed on the rsfMRI data to identify resting state networks (RSNs). For each participant and each rsfMRI acquisition, we constructed a graph comprising all RSNs. We assigned nodal community based on a region's RSN membership, calculated the modularity score, and then correlated changes in modularity and therapeutic gains on the narrative task. We repeated this comparison controlling for pretherapy performance and using a community structure not based on RSN membership. Increased RSN modularity was positively correlated with improvement on the narrative task immediately post-therapy. This finding remained significant when controlling for pretherapy performance. There were no significant findings for network modularity and behavior when nodal community was assigned without consideration of RSN membership. We interpret these findings as support for the adaptive role of network segregation in behavioral improvement in aphasia therapy. This has important clinical implications for the targeting of noninvasive brain stimulation in poststroke remediation and suggests potential for further insight into the processes underlying such changes through computational modeling.

To characterize the untrained performance of people with aphasia (PWA) in finding symbols (single words) on two symbol-based augmentative and alternative communication applications (AAC apps). Nine individuals with aphasia and no previous experience with AAC searched for five symbols on two grid display apps with differing representation systems and vocabulary (Proloquo2Go and Speak for Yourself) following a brief demonstration. Participants were allowed two minutes to locate each symbol on each app (Trial 1), following which the process was repeated with the same symbols (Trial 2) for both apps. Measured variables included total number of symbols found as well as average efficiency score, search time per symbol, and number of cell selections per second for successful trials. Participants were interviewed about their stated app preferences. In the absence of training, participants performed significantly better using Proloquo2Go for average search time (p <.001), and rate of cell selection (p <.001). No significant differences were found across trials. Seven of the nine participants expressed a preference for Proloquo2Go. Participant performance and stated preferences appeared to favour the layout found in Proloquo2Go, possibly suggestive of greater intuitiveness in the absence of training. However, significant learning was not observed across two trials, suggesting the importance of training and increased exposure. Individuals who are diagnosed with aphasia may have long-term communication difficulties that require alternative means of communication. There are numerous commercially available augmentative and alternative communication applications (AAC apps) which may be beneficial for this population. However, there is limited research examining their usefulness. This study with a small sample of individuals with aphasia found that in the absence of training some apps may be easier to use than others. Additionally, the study found that learning may not occur in the absence of training highlighting the importance of treatment. [ABSTRACT FROM AUTHOR]

Background: Transcranial direct current stimulation (tDCS) is a safe, portable, and inexpensive form of noninvasive brain stimulation that appears to augment the effects of concurrent therapy. However, several methodological issues in existing studies distance tDCS from current clinical practice. In this study, we offered (and administered) tDCS to individuals seeking typical behavioral aphasia therapy on an outpatient basis. Methods: We approached clients (n = 10) planning to receive standard aphasia therapy at a university clinic. Following a brief description of tDCS, we offered to provide stimulation during their therapy. Those interested and without contraindications participated in a double-blind, sham-controlled crossover study of tDCS paired with speech-language therapy provided twice weekly. Participants received active (2 mA) or sham tDCS during two eight-week therapy phases (separated by ten weeks) with the anode over Broca's area and the cathode on the contralateral forehead. Stimulation was provided for the first 20 minutes of each one-hour session. Prior to and following each phase, participants were video recorded telling the Cinderella narrative. Recordings were transcribed and analyzed for correct information units (CIUs). Results: Seven individuals (70%) were interested in and eligible for tDCS. Data from four participants who completed the study indicated a large effect size favoring active over sham tDCS (Cohen's d = 1.32). The participant with the most severe deficits did not benefit from therapy in either condition. Conclusion: There is potential for tDCS to enhance meaningful communication outcomes in standard clinical practice. Further investigation is needed to replicate findings and determine individual characteristics predictive of treatment response. [ABSTRACT FROM AUTHOR]