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Background: Recovery of walking post-stroke is highly variable. Accurately measuring and documenting functional brain activation characteristics during walking can help guide rehabilitation. Previous work in this area has been limited to investigations of frontal brain regions and have not utilized recent technological and analytical advances for more accurate measurements. There were three aims for this study: to characterize the hemodynamic profile during walking post-stroke, to investigate regional changes in brain activation during different phases of walking, and to related brain changes to clinical measures. Methods: Functional near-infrared spectroscopy (fNIRS) along the pre-frontal, premotor, sensorimotor, and posterior parietal cortices was used on twenty individuals greater than six months post-stroke. Individual fNIRS optodes were digitized and used to estimate channel locations on each participant and short separation channels were used to control for extracerebral hemodynamic changes. Participants walked at their comfortable pace several times along a hallway while brain activation was recorded. Exploratory cluster analysis was conducted to determine if there was a link between brain activation and clinical measures. Results: Sustained activation was observed in the pre-frontal cortex with the ipsilesional hemisphere showing greater activation compared to the contralesional side. Sensorimotor cortex was active during the early, acceleration stage of walking only. Posterior parietal cortex showed changes in activation during the later, steady-state stage of walking. Faster gait speeds also related to increased activation in contralesional sensorimotor and posterior parietal cortices. Exploratory analysis clustered participants into two distinct groups based on their brain activation profiles and generally showed that individuals with greater activation tended to have better physical outcomes. Conclusions: These findings can guide future research for obtaining adequate power and determining factors that can be used as effect modifiers to reduce inter-subject variability. Overall, this is the first study to report specific oxygenated and deoxygenated hemoglobin changes in frontal to parietal regions during walking in the stroke population. Our results shed light on the importance of measuring brain activation across the cortex and show the importance of pre-frontal, sensorimotor, and posterior parietal cortices in walking after a stroke. [ABSTRACT FROM AUTHOR]

BackgroundRecovery of walking post-stroke is highly variable. Accurately measuring and documenting functional brain activation characteristics during walking can help guide rehabilitation. Previous work in this area has been limited to investigations of frontal brain regions and have not utilized recent technological and analytical advances for more accurate measurements. There were three aims for this study: to characterize the hemodynamic profile during walking post-stroke, to investigate regional changes in brain activation during different phases of walking, and to related brain changes to clinical measures.MethodsFunctional near-infrared spectroscopy (fNIRS) along the pre-frontal, premotor, sensorimotor, and posterior parietal cortices was used on twenty individuals greater than six months post-stroke. Individual fNIRS optodes were digitized and used to estimate channel locations on each participant and short separation channels were used to control for extracerebral hemodynamic changes. Participants walked at their comfortable pace several times along a hallway while brain activation was recorded. Exploratory cluster analysis was conducted to determine if there was a link between brain activation and clinical measures.ResultsSustained activation was observed in the pre-frontal cortex with the ipsilesional hemisphere showing greater activation compared to the contralesional side. Sensorimotor cortex was active during the early, acceleration stage of walking only. Posterior parietal cortex showed changes in activation during the later, steady-state stage of walking. Faster gait speeds also related to increased activation in contralesional sensorimotor and posterior parietal cortices. Exploratory analysis clustered participants into two distinct groups based on their brain activation profiles and generally showed that individuals with greater activation tended to have better physical outcomes.ConclusionsThese findings can guide future research for obtaining adequate power and determining factors that can be used as effect modifiers to reduce inter-subject variability. Overall, this is the first study to report specific oxygenated and deoxygenated hemoglobin changes in frontal to parietal regions during walking in the stroke population. Our results shed light on the importance of measuring brain activation across the cortex and show the importance of pre-frontal, sensorimotor, and posterior parietal cortices in walking after a stroke.

Background: Walking within the community requires the ability to walk while simultaneously completing other tasks. After a stroke, completing an additional task while walking is significantly impaired, and it is unclear how the functional activity of the brain may impact this. Methods: Twenty individual in the chronic stage post-stroke participated in this study. Functional near-infrared spectroscopy (fNIRS) was used to measure prefrontal, pre-motor, sensorimotor, and posterior parietal cortices during walking and walking while completing secondary verbal tasks of varying difficulty. Changes in brain activity during these tasks were measured and relationships were accessed between brain activation changes and cognitive or motor abilities. Results: Significantly larger activations were found for prefrontal, pre-motor, and posterior parietal cortices during dual-task walking. Increasing dual-task walking challenge did not result in an increase in brain activation in these regions. Higher general cognition related to lower increases in activation during the easier dual-task. With the harder dual-task, a trend was also found for higher activation and less motor impairment. Conclusions: This is the first study to show that executive function, motor preparation/planning, and sensorimotor integration areas are all important for dual-task walking post-stroke. A lack of further brain activation increase with increasing challenge suggests a point at which a trade-off between brain activation and performance occurs. Further research is needed to determine if training would result in further increases in brain activity or improved performance. [ABSTRACT FROM AUTHOR]

BackgroundWalking within the community requires the ability to walk while simultaneously completing other tasks. After a stroke, completing an additional task while walking is significantly impaired, and it is unclear how the functional activity of the brain may impact this.MethodsTwenty individual in the chronic stage post-stroke participated in this study. Functional near-infrared spectroscopy (fNIRS) was used to measure prefrontal, pre-motor, sensorimotor, and posterior parietal cortices during walking and walking while completing secondary verbal tasks of varying difficulty. Changes in brain activity during these tasks were measured and relationships were accessed between brain activation changes and cognitive or motor abilities.ResultsSignificantly larger activations were found for prefrontal, pre-motor, and posterior parietal cortices during dual-task walking. Increasing dual-task walking challenge did not result in an increase in brain activation in these regions. Higher general cognition related to lower increases in activation during the easier dual-task. With the harder dual-task, a trend was also found for higher activation and less motor impairment.ConclusionsThis is the first study to show that executive function, motor preparation/planning, and sensorimotor integration areas are all important for dual-task walking post-stroke. A lack of further brain activation increase with increasing challenge suggests a point at which a trade-off between brain activation and performance occurs. Further research is needed to determine if training would result in further increases in brain activity or improved performance.

Neural keyword spotting could form the basis of a speech brain-computer-interface for menu-navigation if it can be done with low latency and high specificity comparable to the “wake-word” functionality of modern voice-activated AI assistant technologies. This study investigated neural keyword spotting using motor representations of speech via invasively-recorded electrocorticographic signals as a proof-of-concept. Neural matched filters were created from monosyllabic consonant-vowel utterances: one keyword utterance, and 11 similar non-keyword utterances. These filters were used in an analog to the acoustic keyword spotting problem, applied for the first time to neural data. The filter templates were cross-correlated with the neural signal, capturing temporal dynamics of neural activation across cortical sites. Neural vocal activity detection (VAD) was used to identify utterance times and a discriminative classifier was used to determine if these utterances were the keyword or non-keyword speech. Model performance appeared to be highly related to electrode placement and spatial density. Vowel height (/a/ vs /i/) was poorly discriminated in recordings from sensorimotor cortex, but was highly discriminable using neural features from superior temporal gyrus during self-monitoring. The best performing neural keyword detection (5 keyword detections with two false-positives across 60 utterances) and neural VAD (100% sensitivity, ~1 false detection per 10 utterances) came from high-density (2 mm electrode diameter and 5 mm pitch) recordings from ventral sensorimotor cortex, suggesting the spatial fidelity and extent of high-density ECoG arrays may be sufficient for the purpose of speech brain-computer-interfaces.

Neural keyword spotting could form the basis of a speech brain-computer-interface for menu-navigation if it can be done with low latency and high specificity comparable to the "wake-word" functionality of modern voice-activated AI assistant technologies. This study investigated neural keyword spotting using motor representations of speech via invasively-recorded electrocorticographic signals as a proof-of-concept. Neural matched filters were created from monosyllabic consonant-vowel utterances: one keyword utterance, and 11 similar non-keyword utterances. These filters were used in an analog to the acoustic keyword spotting problem, applied for the first time to neural data. The filter templates were cross-correlated with the neural signal, capturing temporal dynamics of neural activation across cortical sites. Neural vocal activity detection (VAD) was used to identify utterance times and a discriminative classifier was used to determine if these utterances were the keyword or non-keyword speech. Model performance appeared to be highly related to electrode placement and spatial density. Vowel height (/a/ vs /i/) was poorly discriminated in recordings from sensorimotor cortex, but was highly discriminable using neural features from superior temporal gyrus during self-monitoring. The best performing neural keyword detection (5 keyword detections with two false-positives across 60 utterances) and neural VAD (100% sensitivity, ~1 false detection per 10 utterances) came from high-density (2 mm electrode diameter and 5 mm pitch) recordings from ventral sensorimotor cortex, suggesting the spatial fidelity and extent of high-density ECoG arrays may be sufficient for the purpose of speech brain-computer-interfaces. [ABSTRACT FROM AUTHOR]

Abstract: The use of canonical functions to model BOLD-fMRI data in people post-stroke may lead to inaccurate descriptions of task-related brain activity. The purpose of this study was to determine whether the spatiotemporal profile of hemodynamic responses (HDRs) obtained from stroke survivors during an event-related experiment could be used to develop individualized HDR functions that would enhance BOLD-fMRI signal detection in block experiments. Our long term goal was to use this information to develop individualized HDR functions for stroke survivors that could be used to analyze brain activity associated with locomotor-like movements. We also aimed to examine the reproducibility of HDRs obtained across two scan sessions in order to determine whether data from a single event-related session could be used to analyze block data obtained in subsequent sessions. Results indicate that the spatiotemporal profile of HDRs measured with BOLD-fMRI in stroke survivors was not the same as that observed in individuals without stroke. We observed small between-group differences in the rates of rise and decline of HDRs that were more apparent in individuals with cortical as compared to subcortical stroke. There were no differences in the peak or time to peak of HDRs in people with and without stroke. Of interest, differences in HDRs were not as substantial as expected from previous reports and were not large enough to necessitate the use of individualized HDR functions to obtain valid measures of movement-related brain activity. We conclude that all strokes do not affect the spatiotemporal characteristics of HDRs in such a way as to produce inaccurate representations of brain activity as measured by BOLD-fMRI. However, care should be taken to identify individuals whose BOLD-fMRI data may not provide an accurate representation of underlying brain activation when canonical models are used. Examination of HDRs need not be done for each scan session, as our data suggest that the characteristics of HDRs in stroke survivors are reproducible across days. [Copyright &y& Elsevier]

In order to clarify asymmetry of functional activation in the sensorimotor cortex (SMC), we scanned 12 right-handed healthy subjects with functional MRI while they performed self-initiated sequential opposition movements of the thumb to each finger every I second with the right and left hands. Movement of the left hand resulted in greater activation of the SMC contralateral to the movements than that of the right hand (Mean BOLD signals: 11.68 with right hand, 16.82 with left hand. p<0.05). With respect to spatial distribution of activated SMC, finger movements activated contralateral SMC with the right hand, whereas bilateral SMC was activated with the left hand. These results support the hypothesis that unskillful movements, as with left hand in this study, require more neural participation than skillful movements. [ABSTRACT FROM AUTHOR]