Association between Inhibitory-Excitatory Balance and Brain Activity Response during Cognitive Flexibility in Young and Older Individuals.

Cognitive flexibility represents the capacity to switch among different mental schemes, providing an adaptive advantage to a changing environment. The neural underpinnings of this executive function have been deeply studied in humans through fMRI, showing that the left inferior frontal cortex (IFC) and the left inferior parietal lobule (IPL) are crucial. Here, we investigated the inhibitory-excitatory balance in these regions by means of γ-aminobutyric acid (GABA+) and glutamate + glutamine (Glx), measured with magnetic resonance spectroscopy, during a cognitive flexibility task and its relationship with the performance level and the local task-induced blood oxygenation level-dependent (BOLD) response in 40 young (18-35 years; 26 female) and 40 older (18-35 years; 21 female) human adults. As the IFC and the IPL are richly connected regions, we also examined whole-brain effects associated with their local metabolic activity. Results did not show absolute metabolic modulations associated with flexibility performance, but the performance level was related to the direction of metabolic modulation in the IPL with opposite patterns in young and older individuals. The individual inhibitory-excitatory balance modulation showed an inverse relationship with the local BOLD response in the IPL. Finally, the modulation of inhibitory-excitatory balance in IPL was related to whole-brain effects only in older individuals. These findings show disparities in the metabolic mechanisms underlying cognitive flexibility in young and older adults and their association with the performance level and BOLD response. Such metabolic differences are likely to play a role in executive functioning during aging and specifically in cognitive flexibility.

Combining muscle-computer interface guided training with bihemispheric tDCS improves upper limb function in patients with chronic stroke.

Transcranial direct current stimulation (tDCS) may facilitate neuroplasticity but with a limited effect when administered while patients with stroke are at rest. Muscle-computer interface (MCI) training is a promising approach for training patients with stroke even if they cannot produce overt movements. However, using tDCS to enhance MCI training has not been investigated. We combined bihemispheric tDCS with MCI training of the paretic wrist and examined the effect of this intervention in patients with chronic stroke. A crossover, double-blind, randomized trial was conducted. Twenty-six patients with chronic stroke performed MCI wrist training for three consecutive days at home while receiving either real tDCS or sham tDCS in counterbalanced order and separated by at least 8 mo. The primary outcome measure was the Fugl-Meyer Assessment Upper Extremity Scale (FMA-UE) that was measured 1 wk before training, on the first training day, on the last training day, and 1 wk after training. There was neither a significant difference in the baseline FMA-UE score between groups nor between intervention periods. Patients improved 3.9 ± 0.6 points in FMA-UE score when receiving real tDCS, and 1.0 ± 0.7 points when receiving sham tDCS (P = 0.003). In addition, patients also showed continuous improvement in their motor control of the MCI tasks over the training days. Our study showed that the training paradigm could lead to functional improvement in patients with chronic stroke. We argue that appropriate MCI training in combination with bihemispheric tDCS could be a useful adjuvant for neurorehabilitation in patients with stroke.NEW & NOTEWORTHY Bihemispheric tDCS combined with a novel MCI training for motor control of wrist extensor can improve upper limb function especially a training-specific effect on the wrist movement in patients with chronic stroke. The training regimen can be personalized with adjustments made daily to accommodate the functional change throughout the intervention. This demonstrates that bihemispheric tDCS with MCI training could complement conventional poststroke neurorehabilitation.

Frequency-dependent connectivity in large-scale resting-state brain networks during sleep.

Functional connectivity (FC) during sleep has been shown to break down as non-rapid eye movement (NREM) sleep deepens before returning to a state closer to wakefulness during rapid eye movement (REM) sleep. However, the specific spatial and temporal signatures of these fluctuations in connectivity patterns remain poorly understood. This study aimed to investigate how frequency-dependent network-level FC fluctuates during nocturnal sleep in healthy young adults using high-density electroencephalography (hdEEG). Specifically, we examined source-localized FC in resting-state networks during NREM2, NREM3 and REM sleep (sleep stages scored using a semi-automatic procedure) in the first three sleep cycles of 29 participants. Our results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The data also highlighted a complex modulation of connectivity patterns during the transition to REM sleep whereby delta and sigma bands hosted a persistence of the connectivity breakdown in all networks. In contrast, a reconnection occurred in the default mode and the attentional networks in frequency bands characterizing their organization during wake (i.e., alpha and beta bands, respectively). Finally, all network pairs (except the visual network) showed higher gamma-band FC during REM sleep in cycle three compared to earlier sleep cycles. Altogether, our results unravel the spatial and temporal characteristics of the well-known breakdown in connectivity observed as NREM sleep deepens. They also illustrate a complex pattern of connectivity during REM sleep that is consistent with network- and frequency-specific breakdown and reconnection processes.

Baseline GABA+ levels in areas associated with sensorimotor control predict initial and long-term motor learning progress.

Synaptic plasticity relies on the balance between excitation and inhibition in the brain. As the primary inhibitory and excitatory neurotransmitters, gamma-aminobutyric acid (GABA) and glutamate (Glu), play critical roles in synaptic plasticity and learning. However, the role of these neurometabolites in motor learning is still unclear. Furthermore, it remains to be investigated which neurometabolite levels from the regions composing the sensorimotor network predict future learning outcome. Here, we studied the role of baseline neurometabolite levels in four task-related brain areas during different stages of motor skill learning under two different feedback (FB) conditions. Fifty-one healthy participants were trained on a bimanual motor task over 5 days while receiving either concurrent augmented visual FB (CA-VFB group, N = 25) or terminal intrinsic visual FB (TA-VFB group, N = 26) of their performance. Additionally, MRS-measured baseline GABA+ (GABA + macromolecules) and Glx (Glu + glutamine) levels were measured in the primary motor cortex (M1), primary somatosensory cortex (S1), dorsolateral prefrontal cortex (DLPFC), and medial temporal cortex (MT/V5). Behaviorally, our results revealed that the CA-VFB group outperformed the TA-VFB group during task performance in the presence of augmented VFB, while the TA-VFB group outperformed the CA-VFB group in the absence of augmented FB. Moreover, baseline M1 GABA+ levels positively predicted and DLPFC GABA+ levels negatively predicted both initial and long-term motor learning progress in the TA-VFB group. In contrast, baseline S1 GABA+ levels positively predicted initial and long-term motor learning progress in the CA-VFB group. Glx levels did not predict learning progress. Together, these findings suggest that baseline GABA+ levels predict motor learning capability, yet depending on the FB training conditions afforded to the participants.

MRS-assessed brain GABA modulation in response to task performance and learning.

Gamma-aminobutyric acid (GABA), the most important inhibitory neurotransmitter in the human brain, has long been considered essential in human behavior in general and learning in particular. GABA concentration can be quantified using magnetic resonance spectroscopy (MRS). Using this technique, numerous studies have reported associations between baseline GABA levels and various human behaviors. However, regional GABA concentration is not fixed and may exhibit rapid modulation as a function of environmental factors. Hence, quantification of GABA levels at several time points during the performance of tasks can provide insights into the dynamics of GABA levels in distinct brain regions. This review reports on findings from studies using repeated measures (n = 41) examining the dynamic modulation of GABA levels in humans in response to various interventions in the perceptual, motor, and cognitive domains to explore associations between GABA modulation and human behavior. GABA levels in a specific brain area may increase or decrease during task performance or as a function of learning, depending on its precise involvement in the process under investigation. Here, we summarize the available evidence and derive two overarching hypotheses regarding the role of GABA modulation in performance and learning. Firstly, training-induced increases in GABA levels appear to be associated with an improved ability to differentiate minor perceptual differences during perceptual learning. This observation gives rise to the 'GABA increase for better neural distinctiveness hypothesis'. Secondly, converging evidence suggests that reducing GABA levels may play a beneficial role in effectively filtering perceptual noise, enhancing motor learning, and improving performance in visuomotor tasks. Additionally, some studies suggest that the reduction of GABA levels is related to better working memory and successful reinforcement learning. These observations inspire the 'GABA decrease to boost learning hypothesis', which states that decreasing neural inhibition through a reduction of GABA in dedicated brain areas facilitates human learning. Additionally, modulation of GABA levels is also observed after short-term physical exercise. Future work should elucidate which specific circumstances induce robust GABA modulation to enhance neuroplasticity and boost performance.

Targeted memory reactivation during post-learning sleep does not enhance motor memory consolidation in older adults.

Targeted memory reactivation (TMR) during sleep enhances memory consolidation in young adults by modulating electrophysiological markers of neuroplasticity. Interestingly, older adults exhibit deficits in motor memory consolidation, an impairment that has been linked to age-related degradations in the same sleep features sensitive to TMR. We hypothesised that TMR would enhance consolidation in older adults via the modulation of these markers. A total of 17 older participants were trained on a motor task involving two auditory-cued sequences. During a post-learning nap, two auditory cues were played: one associated to a learned (i.e., reactivated) sequence and one control. Performance during two delayed re-tests did not differ between reactivated and non-reactivated sequences. Moreover, both associated and control sounds modulated brain responses, yet there were no consistent differences between the auditory cue types. Our results collectively demonstrate that older adults do not benefit from specific reactivation of a motor memory trace by an associated auditory cue during post-learning sleep. Based on previous research, it is possible that auditory stimulation during post-learning sleep could have boosted motor memory consolidation in a non-specific manner.

Neurological soft signs in adolescents are associated with brain structure.

Neurological soft signs (NSS) are minor deviations in motor performance. During childhood and adolescence, NSS are examined for functional motor phenotyping to describe development, to screen for comorbidities, and to identify developmental vulnerabilities. Here, we investigate underlying brain structure alterations in association with NSS in physically trained adolescents. Male adolescent athletes (n = 136, 13-16 years) underwent a standardized neurological examination including 28 tests grouped into 6 functional clusters. Non-optimal performance in at least 1 cluster was rated as NSS (NSS+ group). Participants underwent T1- and diffusion-weighted magnetic resonance imaging. Cortical volume, thickness, and local gyrification were calculated using Freesurfer. Measures of white matter microstructure (Free-water (FW), FW-corrected fractional anisotropy (FAt), axial and radial diffusivity (ADt, RDt)) were calculated using tract-based spatial statistics. General linear models with age and handedness as covariates were applied to assess differences between NSS+ and NSS- group. We found higher gyrification in a large cluster spanning the left superior frontal and parietal areas, and widespread lower FAt and higher RDt compared with the NSS- group. This study shows that NSS in adolescents are associated with brain structure alterations. Underlying mechanisms may include alterations in synaptic pruning and axon myelination, which are hallmark processes of brain maturation.

Task-Related Modulation of Sensorimotor GABA+ Levels in Association with Brain Activity and Motor Performance: A Multimodal MRS-fMRI Study in Young and Older Adults.

Recent studies suggest an important role of the principal inhibitory neurotransmitter GABA for motor performance in the context of aging. Nonetheless, as previous magnetic resonance spectroscopy (MRS) studies primarily reported resting-state GABA levels, much less is known about transient changes in GABA levels during motor task performance and how these relate to behavior and brain activity patterns. Therefore, we investigated GABA+ levels of left primary sensorimotor cortex (SM1) acquired before, during, and after execution of a unimanual/bimanual action selection task in 30 (human) young adults (YA; age 24.5 ± 4.1, 15 male) and 30 older adults (OA; age 67.8 ± 4.9, 14 male). In addition to task-related MRS data, task-related functional magnetic resonance imaging (fMRI) data were acquired. Behavioral results indicated lower motor performance in OA as opposed to YA, particularly in complex task conditions. MRS results demonstrated lower GABA+ levels in OA as compared with YA. Furthermore, a transient task-related decrease of GABA+ levels was observed, regardless of age. Notably, this task-induced modulation of GABA+ levels was linked to task-related brain activity patterns in SM1 such that a more profound task-induced instantaneous lowering of GABA+ was related to higher SM1 activity. Additionally, higher brain activity was related to better performance in the bimanual conditions, despite some age-related differences. Finally, the modulatory capacity of GABA+ was positively related to motor performance in OA but not YA. Together, these results underscore the importance of transient dynamical changes in neurochemical content for brain function and behavior, particularly in the context of aging.SIGNIFICANCE STATEMENT Emerging evidence designates an important role to regional GABA levels in motor control, especially in the context of aging. However, it remains unclear whether changes in GABA levels emerge when executing a motor task and how these changes relate to brain activity patterns and performance. Here, we identified a transient decrease of sensorimotor GABA+ levels during performance of an action selection task across young adults (YA) and older adults (OA). Interestingly, whereas a more profound GABA+ modulation related to higher brain activity across age groups, its association with motor performance differed across age groups. Within OA, our results highlighted a functional merit of a task-related release from inhibitory tone, i.e. lowering regional GABA+ levels was associated with task-relevant brain activity.

Organization of neurochemical interactions in young and older brains as revealed with a network approach: Evidence from proton magnetic resonance spectroscopy (1H-MRS).

Aging is associated with alterations in the brain including structural and metabolic changes. Previous research has focused on neurometabolite level differences associated to age in a variety of brain regions, but the relationship among metabolites across the brain has been much less studied. Investigating these relationships can reveal underlying neurometabolic processes, their interdependency, and their progress throughout the lifespan. Using 1H-MRS, we investigated the relationship among metabolite concentrations of N-acetylaspartate (NAA), creatine (Cr), choline (Cho), myo-Inositol (mIns) and glutamate-glutamine complex (Glx) in seven voxel locations, i.e., bilateral sensorimotor cortex, bilateral striatum, pre-supplementary motor area, right inferior frontal gyrus and occipital cortex. These measurements were performed on 59 human participants divided in two age groups: young adults (YA: 23.2 ± 4.3; 18-34 years) and older adults (OA: 67.5 ± 3.9; 61-74 years). Our results showed age-related differences in NAA, Cho, and mIns across brain regions, suggesting the presence of neurodegeneration and altered gliosis. Moreover, associative patterns among NAA, Cho and Cr were observed across the selected brain regions, which differed between young and older adults. Whereas most of metabolite concentrations were inhomogeneous across different brain regions, Cho levels were shown to be strongly related across brain regions in both age groups. Finally, we found metabolic associations between homologous brain regions (SM1 and striatum) in the OA group, with NAA showing a significant correlation between bilateral sensorimotor cortices (SM1) and mIns levels being correlated between the bilateral striata. We posit that a network perspective provides important insights regarding the potential interactions among neurochemicals underlying metabolic processes at a local and global level and their relationship with aging.

High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model.

The human brain generates a rich repertoire of spatio-temporal activity patterns, which support a wide variety of motor and cognitive functions. These patterns of activity change with age in a multi-factorial manner. One of these factors is the variations in the brain's connectomics that occurs along the lifespan. However, the precise relationship between high-order functional interactions and connnectomics, as well as their variations with age are largely unknown, in part due to the absence of mechanistic models that can efficiently map brain connnectomics to functional connectivity in aging. To investigate this issue, we have built a neurobiologically-realistic whole-brain computational model using both anatomical and functional MRI data from 161 participants ranging from 10 to 80 years old. We show that the differences in high-order functional interactions between age groups can be largely explained by variations in the connectome. Based on this finding, we propose a simple neurodegeneration model that is representative of normal physiological aging. As such, when applied to connectomes of young participant it reproduces the age-variations that occur in the high-order structure of the functional data. Overall, these results begin to disentangle the mechanisms by which structural changes in the connectome lead to functional differences in the ageing brain. Our model can also serve as a starting point for modeling more complex forms of pathological ageing or cognitive deficits.

Prefronto-Striatal Structural Connectivity Mediates Adult Age Differences in Action Selection.

In complex everyday environments, action selection is critical for optimal goal-directed behavior. This refers to the process of choosing a proper action from the range of possible alternatives. The neural mechanisms underlying action selection and how these are affected by normal aging remain to be elucidated. In the present cross-sectional study, we studied processes of effector selection during a multilimb reaction time task in a lifespan sample of healthy human adults (N = 89; 20-75 years; 48 males, 41 females). Participants were instructed to react as quickly and accurately as possible to visually cued stimuli representing single-limb or combined upper and/or lower limb motions. Diffusion MRI was used to study structural connectivity between prefrontal and striatal regions as critical nodes for action selection. Behavioral findings revealed that increasing age was associated with slowing of action selection performance. At the neural level, aging had a negative impact on prefronto-striatal connectivity. Importantly, mediation analyses revealed that the negative association between action selection performance and age was mediated by prefronto-striatal connectivity, specifically the connections between left rostral medial frontal gyrus and left nucleus accumbens as well as right frontal pole and left caudate. These results highlight the potential role of prefronto-striatal white matter decline in poorer action selection performance of older adults.SIGNIFICANCE STATEMENT As a result of enhanced life expectancy, researchers have devoted increasing attention to the study of age-related alterations in cognitive and motor functions. Here we study associations between brain structure and behavior to reveal the impact of central neural white matter changes as a function of normal aging on action selection performance. We demonstrate the critical role of a reduction in prefronto-striatal structural connectivity in accounting for action selection performance deficits in healthy older adults. Preserving this cortico-subcortical pathway may be critical for behavioral flexibility and functional independence in older age.

Inhibition, Shifting and Updating: Inter and intra-domain commonalities and differences from an executive functions activation likelihood estimation meta-analysis.

Executive functions are higher-order mental processes that support goal-directed behavior. Among these processes, Inhibition, Updating, and Shifting have been considered core executive domains. In this meta-analysis, we comprehensively investigate the neural networks of these executive domains and we synthesize for the first time the neural convergences and divergences among the most frequently used executive paradigms within those domains. A systematic search yielded 1055 published neuroimaging studies (including 26,191 participants in total). Our study revealed that a fronto-parietal network was shared by the three main domains. Furthermore, we executed conjunction analyses among the paradigms of the same domain to extract the core distinctive components of the main executive domains. This approach showed that Inhibition and Shifting are characterized by a strongly lateralized neural activation in the right and left hemisphere, respectively. In addition, both networks overlapped with the Updating network but not with each other. Remarkably, our study detected heterogeneity among the paradigms from the same domain. More specifically, analysis of Inhibition tasks revealed differing activations for Response Inhibition compared to Interference Control paradigms, suggesting that Inhibition encompasses relatively heterogeneous sub-functions. Shifting analyses revealed a bilateral overlap of the Wisconsin Card Sorting Task with the Updating network, but this pattern was absent for Rule Switching and Dual Task paradigms. Moreover, our Updating meta-analyses revealed the neural signatures associated with the specific modules of the Working Memory model from Baddeley and Hitch. To our knowledge, this is the most comprehensive meta-analysis of executive functions to date. Its paradigm-driven analyses provide a unique contribution to a better understanding of the neural convergences and divergences among executive processes that are relevant for clinical applications, such as cognitive enhancement and neurorehabilitation interventions.

Cross-site harmonization of multi-shell diffusion MRI measures based on rotational invariant spherical harmonics (RISH).

Quantification methods based on the acquisition of diffusion magnetic resonance imaging (dMRI) with multiple diffusion weightings (e.g., multi-shell) are becoming increasingly applied to study the in-vivo brain. Compared to single-shell data for diffusion tensor imaging (DTI), multi-shell data allows to apply more complex models such as diffusion kurtosis imaging (DKI), which attempts to capture both diffusion hindrance and restriction effects, or biophysical models such as NODDI, which attempt to increase specificity by separating biophysical components. Because of the strong dependence of the dMRI signal on the measurement hardware, DKI and NODDI metrics show scanner and site differences, much like other dMRI metrics. These effects limit the implementation of multi-shell approaches in multicenter studies, which are needed to collect large sample sizes for robust analyses. Recently, a post-processing technique based on rotation invariant spherical harmonics (RISH) features was introduced to mitigate cross-scanner differences in DTI metrics. Unlike statistical harmonization methods, which require repeated application to every dMRI metric of choice, RISH harmonization is applied once on the raw data, and can be followed by any analysis. RISH features harmonization has been tested on DTI features but not its generalizability to harmonize multi-shell dMRI. In this work, we investigated whether performing the RISH features harmonization of multi-shell dMRI data removes cross-site differences in DKI and NODDI metrics while retaining longitudinal effects. To this end, 46 subjects underwent a longitudinal (up to 3 time points) two-shell dMRI protocol at 3 imaging sites. DKI and NODDI metrics were derived before and after harmonization and compared both at the whole brain level and at the voxel level. Then, the harmonization effects on cross-sectional and on longitudinal group differences were evaluated. RISH features averaged for each of the 3 sites exhibited prominent between-site differences in the frontal and posterior part of the brain. Statistically significant differences in fractional anisotropy, mean diffusivity and mean kurtosis were observed both at the whole brain and voxel level between all the acquisition sites before harmonization, but not after. The RISH method also proved effective to harmonize NODDI metrics, particularly in white matter. The RISH based harmonization maintained the magnitude and variance of longitudinal changes as compared to the non-harmonized data of all considered metrics. In conclusion, the application of RISH feature based harmonization to multi-shell dMRI data can be used to remove cross-site differences in DKI metrics and NODDI analyses, while retaining inherent relations between longitudinal acquisitions.

Normal aging affects unconstrained three-dimensional reaching against gravity with reduced vertical precision and increased co-contraction: a pilot study.

Reaching for an object in space forms the basis for many activities of daily living and is important in rehabilitation after stroke and in other neurological and orthopedic conditions. It has been the object of motor control and neuroscience research for over a century, but studies often constrain movement to eliminate the effect of gravity or reduce the degrees of freedom. In some studies, aging has been shown to reduce target accuracy, with a mechanism suggested to be impaired corrective movements. We sought to explore how such changes in accuracy relate to changes in finger, shoulder and elbow movements during performance of reaching movements with the normal effects of gravity, unconstrained hand movement, and stable target locations. Three-dimensional kinematic data and electromyography were collected in 14 young (25 ± 6 years) and 10 older adults (68 ± 3 years) during second-long reaches to 3 targets aligned vertically in front of the participants. Older adults took longer to initiate a movement than the young adults and were more variable and inaccurate in their initial and final movements. Target height had greater effect on trajectory curvature variability in older than young adults, with angle variability relative to target position being greater in older adults around the time of peak speed. There were significant age-related differences in use of the multiple degrees of freedom of the upper extremity, with less variability in shoulder abduction in the older group. Muscle activation patterns were similar, except for a higher biceps-triceps co-contraction and tonic levels of some proximal muscle activation. These results show an age-related deficit in the motor planning and online correction of reaching movements against a predictable force (i.e., gravity) when it is not compensated by mechanical support.

GABA levels are differentially associated with bimanual motor performance in older as compared to young adults.

Although gamma aminobutyric acid (GABA) is of particular importance for efficient motor functioning, very little is known about the relationship between regional GABA levels and motor performance. Some studies suggest this relation to be subject to age-related differences even though literature is scarce. To clarify this matter, we employed a comprehensive approach and investigated GABA levels within young and older adults across multiple motor tasks as well as multiple brain regions. Specifically, 30 young and 30 older adults completed a task battery of three different bimanual tasks. Furthermore, GABA levels were obtained within bilateral primary sensorimotor cortex (SM1), bilateral dorsal premotor cortex, the supplementary motor area and bilateral dorsolateral prefrontal cortex (DLPFC) using magnetic resonance spectroscopy. Results indicated that older adults, as compared to their younger counterparts, performed worse on all bimanual tasks and exhibited lower GABA levels in bilateral SM1 only. Moreover, GABA levels across the motor network and DLPFC were differentially associated with performance in young as opposed to older adults on a manual dexterity and bimanual coordination task but not a finger tapping task. Specifically, whereas higher GABA levels related to better manual dexterity within older adults, higher GABA levels predicted poorer bimanual coordination performance in young adults. By determining a task-specific and age-dependent association between GABA levels across the cortical motor network and performance on distinct bimanual tasks, the current study advances insights in the role of GABA for motor performance in the context of aging.

Neurophysiological modulations in the (pre)motor-motor network underlying age-related increases in reaction time and the role of GABA levels - a bimodal TMS-MRS study.

It has been argued that age-related changes in the neurochemical and neurophysiological properties of the GABAergic system may underlie increases in reaction time (RT) in older adults. However, the role of GABA levels within the sensorimotor cortices (SMC) in mediating interhemispheric interactions (IHi) during the processing stage of a fast motor response, as well as how both properties explain interindividual differences in RT, are not yet fully understood. In this study, edited magnetic resonance spectroscopy (MRS) was combined with dual-site transcranial magnetic stimulation (dsTMS) for probing GABA+ levels in bilateral SMC and task-related neurophysiological modulations in corticospinal excitability (CSE), and primary motor cortex (M1)-M1 and dorsal premotor cortex (PMd)-M1 IHi, respectively. Both CSE and IHi were assessed during the preparatory and premotor period of a delayed choice RT task. Data were collected from 25 young (aged 18-33 years) and 28 older (aged 60-74 years) healthy adults. Our results demonstrated that older as compared to younger adults exhibited a reduced bilateral CSE suppression, as well as a reduced magnitude of long latency M1-M1 and PMd-M1 disinhibition during the preparatory period, irrespective of the direction of the IHi. Importantly, in older adults, the GABA+ levels in bilateral SMC partially accounted for task-related neurophysiological modulations as well as individual differences in RT. In contrast, in young adults, neither task-related neurophysiological modulations, nor individual differences in RT were associated with SMC GABA+ levels. In conclusion, this study contributes to a comprehensive initial understanding of how age-related differences in neurochemical properties and neurophysiological processes are related to increases in RT.

Age-related GABAergic differences in the primary sensorimotor cortex: A multimodal approach combining PET, MRS and TMS.

Healthy aging is associated with mechanistic changes in gamma-aminobutyric acid (GABA), the most abundant inhibitory neurotransmitter in the human brain. While previous work mainly focused on magnetic resonance spectroscopy (MRS)-based GABA+ levels and transcranial magnetic stimulation (TMS)-based GABAA receptor (GABAAR) activity in the primary sensorimotor (SM1) cortex, the aim of the current study was to identify age-related differences in positron emission tomography (PET)-based GABAAR availability and its relationship with GABA+ levels (i.e. GABA with the contribution of macromolecules) and GABAAR activity. For this purpose, fifteen young (aged 20-28 years) and fifteen older (aged 65-80 years) participants were recruited. PET and MRS images were acquired using simultaneous time-of-flight PET/MR to evaluate age-related differences in GABAAR availability (distribution volume ratio with pons as reference region) and GABA+ levels. TMS was applied to identify age-related differences in GABAAR activity by measuring short-interval intracortical inhibition (SICI). Whereas GABAAR availability was significantly higher in the SM cortex of older as compared to young adults (18.5%), there were neither age-related differences in GABA+ levels nor SICI. A correlation analysis revealed no significant associations between GABAAR availability, GABAAR activity and GABA+ levels. Although the exact mechanisms need to be further elucidated, it is possible that a higher GABAAR availability in older adults is a compensatory mechanism to ensure optimal inhibitory functionality during the aging process.

Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation.

While it is widely accepted that motor sequence learning (MSL) is supported by a prefrontal-mediated interaction between hippocampal and striatal networks, it remains unknown whether the functional responses of these networks can be modulated in humans with targeted experimental interventions. The present proof-of-concept study employed a multimodal neuroimaging approach, including functional magnetic resonance (MR) imaging and MR spectroscopy, to investigate whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex can modulate responses in the hippocampus and the basal ganglia during motor learning. Our results indicate that while stimulation did not modulate motor performance nor task-related brain activity, it influenced connectivity patterns within hippocampo-frontal and striatal networks. Stimulation also altered the relationship between the levels of gamma-aminobutyric acid (GABA) in the stimulated prefrontal cortex and learning-related changes in both activity and connectivity in fronto-striato-hippocampal networks. This study provides the first experimental evidence, to the best of our knowledge, that brain stimulation can alter motor learning-related functional responses in the striatum and hippocampus.

Perturbation of cortical activity elicits regional and age-dependent effects on unconstrained reaching behavior: a pilot study.

Contributions from premotor and supplementary motor areas to reaching behavior in aging humans are not well understood. The objective of these experiments was to examine effects of perturbations to specific cortical areas on the control of unconstrained reaches against gravity by younger and older adults. Double-pulse transcranial magnetic stimulation (TMS) was applied to scalp locations targeting primary motor cortex (M1), dorsal premotor area (PMA), supplementary motor area (SMA), or dorsolateral prefrontal cortex (DLPFC). Stimulation was intended to perturb ongoing activity in the targeted cortical region before or after a visual cue to initiate moderately paced reaches to one of three vertical target locations. Regional effects were observed in movement amplitude both early and late in the reach. Perturbation of PMA increased reach distance before the time of peak velocity to a greater extent than all other regions. Reaches showed greater deviation from a straight-line path around the time of peak velocity and greater overall curvature with perturbation of PMA and M1 relative to SMA and DLPFC. The perturbation increased positional variability of the reach path at the time of peak velocity and the time elapsing after peak velocity. Although perturbations had stronger effects on reaches by younger subjects, this group exhibited less reach path variability at the time of peak velocity and required less time to adjust the movement trajectory thereafter. These findings support the role of PMA in visually guided reaching and suggest an age-related change in sensorimotor processing, possibly due to a loss of cortical inhibitory control.

Reduced Modulation of Task-Related Connectivity Mediates Age-Related Declines in Bimanual Performance.

Aging is accompanied by marked changes in motor behavior and its neural correlates. At the behavioral level, age-related declines in motor performance manifest, for example, as a reduced capacity to inhibit interference between hands during bimanual movements, particularly when task complexity increases. At the neural level, aging is associated with reduced differentiation between distinct functional systems. Functional connectivity (FC) dedifferentiation is characterized by more homogeneous connectivity patterns across various tasks or task conditions, reflecting a reduced ability of the aging adult to modulate brain activity according to changing task demands. It is currently unknown, however, how whole-brain dedifferentiation interacts with increasing task complexity. In the present study, we investigated age- and task-related FC in a group of 96 human adults across a wide age range (19.9-74.5 years of age) during the performance of a bimanual coordination task of varying complexity. Our findings indicated stronger task complexity-related differentiation between visuomotor- and nonvisuomotor-related networks, though modulation capability decreased with increasing age. Decreased FC modulation mediated larger complexity-related increases in between-hand interference, reflective of worse bimanual coordination. Thus, the ability to maintain high motor performance levels in older adults is related to the capability to properly segregate and modulate functional networks.