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In demanding listening situations, a listener's motivational state may affect their cognitive investment. Here, we aim to delineate how domain-specific sensory processing, domain-general neural alpha power, and pupil size as a proxy for cognitive investment encode influences of motivational state under demanding listening. Participants (male and female) performed an auditory gap-detection task while pupil size and the magnetoencephalogram (MEG) were simultaneously recorded. Task demand and a listener's motivational state were orthogonally manipulated through changes in gap duration and monetary-reward prospect, respectively. Whereas task difficulty impaired performance, reward prospect enhanced it. Pupil size reliably indicated the modulatory impact of an individual's motivational state. At the neural level, the motivational state did not affect auditory sensory processing directly but impacted attentional post-processing of an auditory event as reflected in the late evoked-response field and alpha power change. Both pre-gap pupil dilation and higher parietal alpha power predicted better performance at the single-trial level. The current data support a framework wherein the motivational state acts as an attentional top-down neural means of post-processing the auditory input in challenging listening situations.Significance Statement How does an individual's motivational state affect cognitive investment during effortful listening? In this simultaneous pupillometry and MEG study, participants performed an auditory gap-detection task while their motivational state was manipulated through varying prospect of a monetary reward. The pupil size directly mirrored this motivational modulation of the listening demand. The individual's motivational state also enhanced top-down attentional post-processing of the auditory event but did neither change auditory sensory processing nor pre-gap parietal alpha power. These data suggest that a listener's motivational state acts as a late attentional top-down effect on auditory neural processes in challenging listening situations.

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The generalization of music training to unrelated nonmusical domains is well established and may reflect musicians' superior ability to regulate attention. We investigated the temporal deployment of attention in musicians and nonmusicians using scalp-recording of event-related potentials in an attentional blink (AB) paradigm. Participants listened to rapid sequences of stimuli and identified target and probe sounds. The AB was defined as a probe identification deficit when the probe closely follows the target. The sequence of stimuli was preceded by a neutral or informative cue about the probe position within the sequence. Musicians outperformed nonmusicians in identifying the target and probe. In both groups, cueing improved target and probe identification and reduced the AB. The informative cue elicited a sustained potential, which was more prominent in musicians than nonmusicians over left temporal areas and yielded a larger N1 amplitude elicited by the target. The N1 was larger in musicians than nonmusicians, and its amplitude over the left frontocentral cortex of musicians correlated with accuracy. Together, these results reveal musicians' superior ability to regulate attention, allowing them to prepare for incoming stimuli, thereby improving sound object identification. This capacity to manage attentional resources to optimize task performance may generalize to nonmusical activities.

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Acoustic-phonetic speech training mitigates confusion between consonants and improves phoneme identification in noise. A novel training paradigm addressed two principles of perceptual learning. First, training benefits are often specific to the trained material; therefore, stimulus variability was reduced by training small sets of phonetically similar consonant-vowel-consonant syllables. Second, the training is most efficient at an optimal difficulty level; accordingly, the noise level was adapted to the participant's competency. Fifty-two adults aged between sixty and ninety years with normal hearing or moderate hearing loss participated in five training sessions within two weeks. Training sets of phonetically similar syllables contained voiced and voiceless stop and fricative consonants, as well as voiced nasals and liquids. Listeners identified consonants at the onset or the coda syllable position by matching the syllables with their orthographic equivalent within a closed set of three alternative symbols. The noise level was adjusted in a staircase procedure. Pre-post-training benefits were quantified as increased accuracy and a decrease in the required signal-to-noise ratio (SNR) and analyzed with regard to the stimulus sets and the participant's hearing abilities. The adaptive training was feasible for older adults with various degrees of hearing loss. Normal-hearing listeners performed with high accuracy at lower SNR after the training. Participants with hearing loss improved consonant accuracy but still required a high SNR. Phoneme identification improved for all stimulus sets. However, syllables within a set required noticeably different SNRs. Most significant gains occurred for voiced and voiceless stop and (af)fricative consonants. The training was beneficial for difficult consonants, but the easiest to identify consonants improved most prominently. The training enabled older listeners with different capabilities to train and improve at an individual 'edge of competence'.

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Changes in levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) may underlie aging-related changes in brain function. GABA and co-edited macromolecules (GABA+) can be measured with MEGA-PRESS magnetic resonance spectroscopy (MRS). The current study investigated how changes in the aging brain impact the interpretation of GABA+ measures in bilateral auditory cortices of healthy young and older adults. Structural changes during aging appeared as decreasing proportion of grey matter in the MRS volume of interest and corresponding increase in cerebrospinal fluid. GABA+ referenced to H2 O without tissue correction declined in aging. This decline persisted after correcting for tissue differences in MR-visible H2 O and relaxation times but vanished after considering the different abundance of GABA+ in grey and white matter. However, GABA+ referenced to creatine and N-acetyl aspartate (NAA), which showed no dependence on tissue composition, decreased in aging. All GABA+ measures showed hemispheric asymmetry in young but not older adults. The study also considered aging-related effects on tissue segmentation and the impact of co-edited macromolecules. Tissue segmentation differed significantly between commonly used algorithms, but aging-related effects on tissue-corrected GABA+ were consistent across methods. Auditory cortex macromolecule concentration did not change with age, indicating that a decline in GABA caused the decrease in the compound GABA+ measure. Most likely, the macromolecule contribution to GABA+ leads to underestimating an aging-related decrease in GABA. Overall, considering multiple GABA+ measures using different reference signals strengthened the support for an aging-related decline in auditory cortex GABA levels.

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Previous research showed that repetitive sensory stimulation entrains neural oscillations at the stimulation rate, facilitates long-term potentiation like perceptual learning, and improves behavioural performance. For example, short-time repetitive tactile stimulation improved tactile acuity measured with two-point or spatial orientation discrimination tests. The behavioural gain was maximal for a stimulation rate of 20 Hz, the same frequency at which repetitive somatosensory stimulation elicits a steady-state response with maximum amplitude. The current study investigated whether sensory stimulation must be strictly periodic to induce perceptual learning and whether the 20-Hz steady-state response plays a crucial role in the neural mechanisms of perceptual learning. In a crossover-designed experiment, young, healthy adults received sensory stimulation to the fingertip on three subsequent days. The stimulation was either periodic or temporally randomized (aperiodic) with the same number of stimuli. Tactile acuity was assessed with a grating orientation discrimination task, and brain activity was measured with magnetoencephalography (MEG). Stimulus type-by-session interactions were found for behavioural and brain data. Tactile acuity improved more after a session with aperiodic than periodic stimulation. Beta-band 20-Hz steady-state responses were localized in the primary somatosensory cortex contralateral to the stimulated finger and had larger amplitudes after periodic than aperiodic stimulation. Both stimulus types also elicited gamma oscillations, which increased in amplitude more with aperiodic than periodic stimulation. Sensory stimuli caused a phase reset of sensorimotor beta oscillations phase-coupled to alpha oscillations. The system of stimulus-related oscillations was discussed as underlying temporal processing. Learning may result from facilitating the temporal code. More pronounced behavioural gain with aperiodic than periodic stimulation suggests beneficial effects of temporal stimulus variability for perceptual learning.

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Right-ear advantage refers to the observation that when two different speech stimuli are simultaneously presented to both ears, listeners report stimuli more correctly from the right ear than the left. It is assumed to result from prominent projection along the auditory pathways to the contralateral hemisphere and the dominance of the left auditory cortex for the perception of speech elements. Our study aimed to investigate the role of attention in the right-ear advantage. We recorded magnetoencephalography data while participants listened to pairs of Japanese two-syllable words (namely, "/ta/ /ko/" or "/i/ /ka/"). The amplitudes of the stimuli were modulated at 35 Hz in one ear and 45 Hz in the other. Such frequency-tagging allowed the selective quantification of left and right auditory cortex responses to left and right ear stimuli. Behavioral tests confirmed the right-ear advantage, with higher accuracy for stimuli presented to the right ear than to the left. The amplitude of the auditory steady-state response was larger when attending to the stimuli compared to passive listening. We detected a correlation between the attention-related increase in the amplitude of the auditory steady-state response and the laterality index of behavioral accuracy. The right-ear advantage in the free-response dichotic listening was also found in neural activities in the left auditory cortex, suggesting that it was related to the allocation of attention to both ears.

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Speech-in-noise (SIN) understanding in older age is affected by hearing loss, impaired central auditory processing, and cognitive deficits. SIN-tests measure these factors' compound effects by a speech reception threshold, defined as the signal-to-noise ratio required for 50% word understanding (SNR50). This study compared two standard SIN tests, QuickSIN (n = 354) in young and older adults and BKB-SIN (n = 139) in older adults (>60 years). The effects of hearing loss and age on SIN understanding were analyzed to identify auditory and nonauditory contributions to SIN loss. Word recognition in noise was modelled with individual psychometric functions using a logistic fit with three parameters: the midpoint (SNRα), slope (ß), and asymptotic word-recognition deficit at high SNR (λ). The parameters SNRα and λ formally separate SIN loss into two components. SNRα characterizes the steep slope of the psychometric function at which a slight SNR increase provides a considerable improvement in SIN understanding. SNRα was discussed as being predominantly affected by audibility and low-level central auditory processing. The parameter λ describes a shallow segment of the psychometric function at which a further increase in the SNR provides modest improvement in SIN understanding. Cognitive factors in aging may contribute to the SIN loss indicated by λ.

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Speech-in-noise (SIN) understanding often becomes difficult for older adults because of impaired hearing and aging-related changes in central auditory processing. Central auditory processing depends on a fine balance between excitatory and inhibitory neural mechanisms, which may be upset in older age by a change in the level of the inhibitory neurotransmitter gamma-aminobutyric acid (GABA). In this study, we used MEGA-PRESS magnetic resonance spectroscopy (MRS) to estimate GABA levels in both the left and right auditory cortices of young and older adults. We found that total auditory GABA levels were lower in older compared to young adults. To understand the relationship between GABA and hearing function, we correlated GABA levels with hearing loss and SIN performance. In older adults, the GABA level in the right auditory cortex was correlated with age and SIN performance. The relationship between chronological age and SIN loss was partially mediated by the GABA level in the right auditory cortex. These findings support the hypothesis that inhibitory mechanisms in the auditory system are reduced in aging, and this reduction relates to functional impairments.

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We addressed how rhythm complexity influences auditory-motor synchronization in musically trained individuals who perceived and produced complex rhythms while EEG was recorded. Participants first listened to two-part auditory sequences (Listen condition). Each part featured a single pitch presented at a fixed rate; the integer ratio formed between the two rates varied in rhythmic complexity from low (1:1) to moderate (1:2) to high (3:2). One of the two parts occurred at a constant rate across conditions. Then, participants heard the same rhythms as they synchronized their tapping at a fixed rate (Synchronize condition). Finally, they tapped at the same fixed rate (Motor condition). Auditory feedback from their taps was present in all conditions. Behavioral effects of rhythmic complexity were evidenced in all tasks; detection of missing beats (Listen) worsened in the most complex (3:2) rhythm condition, and tap durations (Synchronize) were most variable and least synchronous with stimulus onsets in the 3:2 condition. EEG power spectral density was lowest at the fixed rate during the 3:2 rhythm and greatest during the 1:1 rhythm (Listen and Synchronize). ERP amplitudes corresponding to an N1 time window were smallest for the 3:2 rhythm and greatest for the 1:1 rhythm (Listen). Finally, synchronization accuracy (Synchronize) decreased as amplitudes in the N1 time window became more positive during the high rhythmic complexity condition (3:2). Thus, measures of neural entrainment corresponded to synchronization accuracy, and rhythmic complexity modulated the behavioral and neural measures similarly.

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Auditory long-term memory has been shown to facilitate signal detection. However, the nature and timing of the cognitive processes supporting such benefits remain equivocal. We measured neuroelectric brain activity while young adults were presented with a contextual memory cue designed to assist with the detection of a faint pure tone target embedded in an audio clip of an everyday environmental scene (e.g., the soundtrack of a restaurant). During an initial familiarization task, participants heard such audio clips, half of which included a target sound (memory cue trials) at a specific time and location (left or right ear), as well as audio clips without a target (neutral trials). Following a 1-h or 24-h retention interval, the same audio clips were presented, but now all included a target. Participants were asked to press a button as soon as they heard the pure tone target. Overall, participants were faster and more accurate during memory than neutral cue trials. The auditory contextual memory effects on performance coincided with three temporally and spatially distinct neural modulations, which encompassed changes in the amplitude of event-related potential as well as changes in theta, alpha, beta and gamma power. Brain electrical source analyses revealed greater source activity in memory than neutral cue trials in the right superior temporal gyrus and left parietal cortex. Conversely, neutral trials were associated with greater source activity than memory cue trials in the left posterior medial temporal lobe. Target detection was associated with increased negativity (N2), and a late positive (P3b) wave at frontal and parietal sites, respectively. The effect of auditory contextual memory on brain activity preceding target onset showed little lateralization. Together, these results are consistent with contextual memory facilitating retrieval of target-context associations and deployment and management of auditory attentional resources to when the target occurred. The results also suggest that the auditory cortices, parietal cortex, and medial temporal lobe may be parts of a neural network enabling memory-guided attention during auditory scene analysis.

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This study investigated whether binaural beat stimulation could accelerate the training outcome in an attentional blink (AB) task. The AB refers to the lapse in detecting a target T2 in rapid serial visual presentation (RSVP) after the identification of a preceding target T1. Binaural beats (BB) are assumed to entrain neural oscillations and support cognitive function. Participants were assigned into two groups and presented with BB sounds while performing the AB task on three subsequent days in a cross-over design. Group A was presented with 40-Hz BB during the first day and 16 Hz during the second day, while the order of beat frequencies was reversed in Group B. No sound was presented on the third day. MEG recordings confirmed a strong entrainment of gamma oscillations during 40-Hz BB stimulation and smaller gamma entrainment with 16-Hz BB. The rhythm of the visual stimulation elicited 10-Hz oscillations in occipital MEG sensors which were of similar magnitude for both BB frequencies. The AB performance did not increase within a session. However, participants improved between sessions, with overall improvement equal in both groups. Group A improved more after the first day than the second day. In contrast, group B gained more from the 40 Hz stimulation on the second day than from 16-Hz stimulation on the first day. Taken together, 40-Hz BB stimulation during training accelerates the training outcome. The improvement becomes evident not immediately, but after consolidation during sleep. Therefore, auditory beats stimulation is a promising method of non-invasive brain stimulation for enhancing training and learning which is well-suited to rehabilitation training.

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OBJECTIVE: Stroke lesions in non-auditory areas may affect higher-order central auditory processing. We sought to characterize auditory functions in chronic stroke survivors with unilateral arm/hand impairment using auditory evoked responses (AERs) with lesion and perception metrics. METHODS: The AERs in 29 stroke survivors and 14 controls were recorded with single tones, active and passive frequency-oddballs, and a dual-oddball with pitch-contour and time-interval deviants. Performance in speech-in-noise, mistuning detection, and moving-sound detection was assessed. Relationships between AERs, behaviour, and lesion overlap with functional networks, were examined. RESULTS: Despite their normal hearing, eight patients showed unilateral AER in the hemisphere ipsilateral to the affected hand with reduced amplitude compared to those with bilateral AERs. Both groups showed increasing attenuation of later components. Hemispheric asymmetry of AER sources was reduced in bilateral-AER patients. The N1 wave (100 ms latency) and P2 (200 ms) were delayed in individuals with lesions in the basal-ganglia and white-matter, while lesions in the attention network reduced the frequency-MMN (mismatch negativity) responses and increased the pitch-contour P3a response. Patients' impaired speech-in-noise perception was explained by AER measures and frequency-deviant detection performance with multiple regression. CONCLUSION: AERs reflect disruption of auditory functions due to damage outside of temporal lobe, and further explain complexity of neural mechanisms underlying higher-order auditory perception. SIGNIFICANCE: Stroke survivors without obvious hearing problems may benefit from rehabilitation for central auditory processing.

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Studies of central auditory processing underlying speech-in-noise (SIN) recognition in aging have mainly concerned the degrading neural representation of speech sound in the auditory brainstem and cortex. Less attention has been paid to the aging-related decline of inhibitory function, which reduces the ability to suppress distraction from irrelevant sensory input. In a response suppression paradigm, young and older adults listened to sequences of three short sounds during MEG recording. The amplitudes of the cortical P30 response and the 40-Hz transient gamma response were compared with age, hearing loss and SIN performance. Sensory gating, indicated by the P30 amplitude ratio between the last and the first responses, was reduced in older compared to young listeners. Sensory gating was correlated with age in the older adults but not with hearing loss nor with SIN understanding. The transient gamma response expressed less response suppression. However, the gamma amplitude increased with age and SIN loss. Comparisons of linear multi-variable modeling showed a stronger brain-behavior relationship between the gamma amplitude and SIN performance than between gamma and age or hearing loss. The findings support the hypothesis that aging-related changes in the balance between inhibitory and excitatory neural mechanisms modify the generation of gamma oscillations, which impacts on perceptual binding and consequently on SIN understanding abilities. In conclusion, SIN recognition in older age is less affected by central auditory processing at the level of sensation, indicated by sensory gating, but is strongly affected at the level of perceptual organization, indicated by the correlation with the gamma responses.

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The frequency-following response with origin in the auditory brainstem represents the pitch contour of voice and can be recorded with electrodes from the scalp. MEG studies also revealed a cortical contribution to the high gamma oscillations at the fundamental frequency (f0) of a vowel stimulus. Therefore, studying the cortical component of the frequency-following response could provide insights into how pitch information is encoded at the cortical level. Comparing how aging affects the different responses may help to uncover the neural mechanisms underlying speech understanding deficits in older age. We simultaneously recorded EEG and MEG responses to the syllable /ba/. MEG beamformer analysis localized sources in bilateral auditory cortices and the midbrain. Time-frequency analysis showed a faithful representation of the pitch contour between 106 Hz and 138 Hz in the cortical activity. A cross-correlation revealed a latency of 20 ms. Furthermore, stimulus onsets elicited cortical 40-Hz responses. Both the 40-Hz and the f0 response amplitudes increased in older age and were larger in the right hemisphere. The effects of aging and laterality of the f0 response were evident in the MEG only, suggesting that both effects were characteristics of the cortical response. After comparing f0 and N1 responses in EEG and MEG, we estimated that approximately one-third of the scalp-recorded f0 response could be cortical in origin. We attributed the significance of the cortical f0 response to the precise timing of cortical neurons that serve as a time-sensitive code for pitch.

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INTRODUCTION: Brain processes of working memory involve oscillatory activities at multiple frequencies in local and long-range neural networks. The current study addressed the specific roles of alpha oscillations during memory encoding and retention, supporting the hypothesis that multiple functional mechanisms of alpha oscillations exist in parallel. METHOD: We recorded magnetoencephalography (MEG) in 25 healthy young adults, who performed a variant of a Sternberg working memory task. A sequential list of five consonant letters was visually presented and was followed after a 2.0 s retention interval by a probe of a pair of two letters from the study list. Participants responded whether the probe pair was in same or reversed order in the list. RESULT: Reaction time (RT) was shortest for the first letters in the list, increased with increasing serial position, and shorter for the last position. RT was substantially longer for the probe in reversed order. Time-frequency analysis of the MEG revealed event-related desynchronization (ERD) of alpha oscillations during the encoding interval and an alpha power increase (ERS) during memory retention. Alpha ERD during encoding occurred at 10 Hz and ERS during retention at 12 Hz, suggesting different alpha mechanisms. Analysis of alpha coherence and alpha-gamma cross-spectral coupling, applied to MEG beamformer source activity, revealed connectivity across brain areas. Additionally, alpha-gamma coupling identified centers of local computation. The connectivity between occipital and frontotemporal areas was correlated with alpha ERS during memory retention. Cross-frequency coupling between alpha phase and gamma amplitude depicted a hierarchy of information flow from frontal to temporal and occipital brain areas. CONCLUSION: Alpha decrease during encoding indicates an active state of visual processing, while subsequent ERS indicates inhibition of further visual input for protecting the memory, and phasic timing of temporal and occipital gamma oscillations is related to a long-range working memory networks.

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Interaural time and intensity differences (ITD and IID) are important cues in binaural hearing and allow for sound localization, improving speech understanding in noise and reverberation, and integrating sound sources in the auditory scene. Whereas previous research showed that the upper-frequency limit for ITD detection in the fine structure of sound declines in aging, the processing of envelope ITD in low-frequency amplitude modulated (AM) sound and the related brain responses are less understood. This study investigated the cortical processing of envelope ITD and compared the results with previous findings about the fine-structure ITD. In two experiments, participants listened to 40-Hz AM tones containing sudden changes in the envelope ITD. Multiple MEG responses were analyzed, including the auditory evoked N1 responses, elicited both by sound onsets and ITD changes, and 40-Hz responses, elicited by the AM. The first experiment with healthy young adults revealed a substantial decline in the magnitudes of the ITD change N1 response, and the 40-Hz phase resets at higher carrier frequencies, suggesting a similar frequency characteristic as observed for fine structure ITD. The amplitude of the 40-Hz ASSR declined only gradually with increasing carrier frequency, and it was excluded as a confounding factor in the decline in the ITD response. Larger responses to outward ITD changes than inward changes, here first reported for envelope ITD, were another characteristics that were similar to fine-structure ITD. A second experiment with groups of young and older listeners examined the effects of aging and concurrent noise on the cortical envelope ITD responses. One important research question was, whether binaural cues are accessible in noise. Behavioural tests showed an age-related hearing loss in the older group and decreased performance in envelope ITD detection and speech-in-noise (SIN) understanding. Binaural hearing and SIN performance were correlated with one other, but not with hearing loss. The frequency limit for envelope ITD was reduced in older listeners similarly as previously found for fine structure ITD, and older listeners were more susceptible to concurrent multi-talker noise. The similarities between responses to envelope ITD and to fine structure ITD suggest that a common cortical code exists for the envelope and fine structure ITD. The dependency on the carrier frequency suggests that envelope ITD processing at the subcortical level requires stimulus phase locking, which might be reduced in aging.

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Biomarkers that represent the structural and functional integrity of the motor system enable us to better assess motor outcome post-stroke. The degree of overlap between the stroke lesion and corticospinal tract (CST Injury) is a measure of the structural integrity of the motor system, whereas the left-to-right motor cortex resting state connectivity (LM1-RM1 rs-connectivity) is a measure of its functional integrity. CST Injury and LM1-RM1 rs-connectivity each individually correlate with motor outcome post-stroke, but less is understood about the relationship between these biomarkers. Thus, this study investigates the relationship between CST Injury and LM1-RM1 rs-connectivity, individually and together, with motor outcome. Twenty-seven participants with upper limb motor deficits post-stroke completed motor assessments and underwent MRI at one time point. CST Injury and LM1-RM1 rs-connectivity were derived from T1-weighted and resting state functional MRI scans, respectively. We performed hierarchical multiple regression analyses to determine the contribution of each biomarker in explaining motor outcome. The interaction between CST Injury and LM1-RM1 rs-connectivity does not significantly contribute to the variability in motor outcome. However, inclusion of both CST Injury and LM1-RM1 rs-connectivity explains more variability in motor outcome, than either alone. We suggest both biomarkers provide distinct information about an individual's motor outcome.

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Neuroplasticity accompanying learning is a key mediator of stroke rehabilitation. Training in playing music in healthy populations and patients with movement disorders requires resources within motor, sensory, cognitive, and affective systems, and coordination among these systems. We investigated effects of music-supported therapy (MST) in chronic stroke on motor, cognitive, and psychosocial functions compared to conventional physical training (GRASP). Twenty-eight adults with unilateral arm and hand impairment were randomly assigned to MST (n = 14) and GRASP (n = 14) and received 30 h of training over a 10-week period. The assessment was conducted at four time points: before intervention, after 5 weeks, after 10 weeks, and 3 months after training completion. As for two of our three primary outcome measures concerning motor function, all patients slightly improved in Chedoke-McMaster Stroke Assessment hand score, while the time to complete Action Research Arm Test became shorter in the MST group. The third primary outcome measure for well-being, Stroke Impact Scale, was improved for emotion and social communication earlier in MST and coincided with the improved executive function for task switching and music rhythm perception. The results confirmed previous findings and expanded the potential usage of MST for enhancing quality of life in community-dwelling chronic-stage survivors.

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Movement is traditionally viewed as a process that involves motor brain regions. However, movement also implicates non-motor regions such as prefrontal and parietal cortex, regions whose integrity may thus be important for motor recovery after stroke. Importantly, focal brain damage can affect neural functioning within and between distinct brain networks implicated in the damage. The aim of this study is to investigate how resting state connectivity (rs-connectivity) within and between motor and frontoparietal networks are affected post-stroke in correlation with motor outcome. Twenty-seven participants with chronic stroke with unilateral upper limb deficits underwent motor assessments and magnetic resonance imaging. Participants completed the Chedoke-McMaster Stroke Assessment as a measure of arm (CMSA-Arm) and hand (CMSA-Hand) impairment and the Action Research Arm Test (ARAT) as a measure of motor function. We used a seed-based rs-connectivity approach defining the motor (seed=contralesional primary motor cortex (M1)) and frontoparietal (seed=contralesional dorsolateral prefrontal cortex (DLPFC)) networks. We analyzed the rs-connectivity within each network (intra-network connectivity) and between both networks (inter-network connectivity), and performed correlations between: a) intra-network connectivity and motor assessment scores; b) inter-network connectivity and motor assessment scores. We found: a) Participants with high rs-connectivity within the motor network (between M1 and supplementary motor area) have higher CMSA-Hand stage (z=3.62, p=0.003) and higher ARAT score (z=3.41, p=0.02). Rs-connectivity within the motor network was not significantly correlated with CMSA-Arm stage (z=1.83, p>0.05); b) Participants with high rs-connectivity within the frontoparietal network (between DLPFC and mid-ventrolateral prefrontal cortex) have higher CMSA-Hand stage (z=3.64, p=0.01). Rs-connectivity within the frontoparietal network was not significantly correlated with CMSA-Arm stage (z=0.93, p=0.03) or ARAT score (z=2.53, p=0.05); and c) Participants with high rs-connectivity between motor and frontoparietal networks have higher CMSA-Hand stage (rs=0.54, p=0.01) and higher ARAT score (rs=0.54, p=0.009). Rs-connectivity between the motor and frontoparietal networks was not significantly correlated with CMSA-Arm stage (rs=0.34, p=0.13). Taken together, the connectivity within and between the motor and frontoparietal networks correlate with motor outcome post-stroke. The integrity of these regions may be important for an individual's motor outcome. Motor-frontoparietal connectivity may be a potential biomarker of motor recovery post-stroke.

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Methods of functional connectivity are applied ubiquitously in studies involving non-invasive whole-brain signals, but may be not optimal for exploring the propagation of the steady-state responses, which are strong oscillatory patterns of neurodynamics evoked by periodic stimulation. In our study, we explore a functional network underlying the somatosensory steady-state response using methods of effective connectivity. Human magnetoencephalographic (MEG) data were collected in 10 young healthy adults during 23-Hz vibro-tactile stimulation of the right hand index finger. The whole-brain dynamics of MEG source activity was reconstructed with a linearly-constrained minimum variance beamformer. We applied information-theoretic tools to quantify asymmetries in information flows between primary somatosensory area SI and the rest of the brain. Our analysis identified a pattern of coupling, leading from area SI to a source in the secondary somato-sensory area SII, thalamus, and motor cortex all contralateral to stimuli as well as to a source in the cerebellum ipsilateral to the stimuli. Our results support previously reported empirical evidence collected both in in vitro and in vivo, indicating critical areas of activation of the somatosensory system at the level of systems neuroscience.

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