Paired Associative Stimulation Rewired: A Novel Paradigm to Modulate Resting-State Intracortical Connectivity

Recent neuroimaging research has demonstrated that resting-state intracortical connectivity (i.e., the shared communication between two brain regions) can serve as a robust predictor of motor performance and learning. Theoretically, direct modulation of resting-state intracortical connectivity within the motor system could then improve motor performance and learning. However, previous neuromodulation techniques such as repetitive Transcranial Magnetic Stimulation may be limited in the capacity to modulate targeted intracortical connectivity. Paired Associative Stimulation (PAS) has shown efficacy in facilitating connectivity primarily between the central and peripheral nervous system based on the neuroplasticity mechanism of Spike Timing Dependent Plasticity. It may therefore be plausible for a reconfigured corticocortical PAS paradigm to modulate resting-state intracortical connectivity using a dual stimulator methodology over specific cortical nodes. However, potential theoretical and technological considerations of such a paradigm first need to be addressed prior to application for the purposes of manipulating motor behavior. We posit a corticocortical PAS paradigm used in conjunction with resting-state electroencephalography to demonstrate efficacy of potentiating motor learning associated resting-state intracortical connectivity within the human brain. Here we provide a precise PAS/EEG experimental design, details on data analysis, recommendations for maintaining scientific rigor, and preliminary proof of principle within a single-subject.

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Interaction Between Finger Opposition Movements and Aftereffects of 1Hz-rTMS on Ipsilateral Motor Cortex

Journal of Neurophysiology ◽

10.1152/jn.90428.2008 ◽

2009 ◽

Vol 101 (3) ◽

pp. 1690-1694 ◽

Cited By ~ 8

Author(s):

Laura Avanzino ◽

Marco Bove ◽

Andrea Tacchino ◽

Carlo Trompetto ◽

Carla Ogliastro ◽

...

Keyword(s):

Motor Cortex ◽

Motor Performance ◽

Magnetic Stimulation ◽

Voluntary Movement ◽

Motor Behavior ◽

Repetitive Transcranial Magnetic Stimulation ◽

Motor Task ◽

The Other ◽

Experimental Conditions ◽

Opposition Movements

One-hertz repetitive transcranial magnetic stimulation (1Hz-rTMS) over ipsilateral motor cortex is able to modify up to 30 min the motor performance of repetitive finger opposition movements paced with a metronome at 2 Hz. We investigated whether the long-lasting rTMS effect on motor behavior can be modulated by subsequent engagement of the contralateral sensorimotor system. Motor task was performed in different experimental conditions: immediately after rTMS, 30 min after rTMS, or when real rTMS was substituted with sham rTMS. Subjects performing the motor task immediately after rTMS showed modifications in motor behavior ≤30 min after rTMS. On the other hand, when real rTMS was substituted with sham stimulation or when subjects performed the motor task 30 min after the rTMS session, the effect was no longer present. These findings suggest that the combination of ipsilateral 1Hz-rTMS and voluntary movement is crucial to endure the effect of rTMS on the movement itself, probably acting on synaptic plasticity-like mechanism. This finding might provide some useful hints for neurorehabilitation protocols.

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Extracting Reproducible Time-Resolved Resting State Networks using Dynamic Mode Decomposition

10.1101/343061 ◽

2018 ◽

Cited By ~ 3

Author(s):

James M. Kunert-Graf ◽

Kristian M. Eschenburg ◽

David J. Galas ◽

J. Nathan Kutz ◽

Swati D. Rane ◽

...

Keyword(s):

Resting State ◽

Dynamic Properties ◽

Brain Regions ◽

Dynamic Mode Decomposition ◽

Single Subject ◽

Dynamic Mode ◽

Resting State Networks ◽

Time Resolved ◽

Mode Decomposition ◽

Human Connectome Project

AbstractResting state networks (RSNs) extracted from functional magnetic resonance imaging (fMRI) scans are believed to reflect the intrinsic organization and network structure of brain regions. Most traditional methods for computing RSNs typically assume these functional networks are static throughout the duration of a scan lasting 5–15 minutes. However, they are known to vary on timescales ranging from seconds to years; in addition, the dynamic properties of RSNs are affected in a wide variety of neurological disorders. Recently, there has been a proliferation of methods for characterizing RSN dynamics, yet it remains a challenge to extract reproducible time-resolved networks. In this paper, we develop a novel method based on dynamic mode decomposition (DMD) to extract networks from short windows of noisy, high-dimensional fMRI data, allowing RSNs from single scans to be resolved robustly at a temporal resolution of seconds. We demonstrate this method on data from 120 individuals from the Human Connectome Project and show that unsupervised clustering of DMD modes discovers RSNs at both the group (gDMD) and the single subject (sDMD) levels. The gDMD modes closely resemble canonical RSNs. Compared to established methods, sDMD modes capture individualized RSN structure that both better resembles the population RSN and better captures subject-level variation. We further leverage this time-resolved sDMD analysis to infer occupancy and transitions among RSNs with high reproducibility. This automated DMD-based method is a powerful tool to characterize spatial and temporal structures of RSNs in individual subjects.

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The effect of congenital blindness on resting-state functional connectivity revisited

Scientific Reports ◽

10.1038/s41598-021-91976-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Maria J. S. Guerreiro ◽

Madita Linke ◽

Sunitha Lingareddy ◽

Ramesh Kekunnaya ◽

Brigitte Röder

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Visual Experience ◽

Brain Regions ◽

State Condition ◽

Resting State Functional Connectivity ◽

Congenital Blindness ◽

Eyes Closed ◽

Congenitally Blind ◽

Eyes Open

AbstractLower resting-state functional connectivity (RSFC) between ‘visual’ and non-‘visual’ neural circuits has been reported as a hallmark of congenital blindness. In sighted individuals, RSFC between visual and non-visual brain regions has been shown to increase during rest with eyes closed relative to rest with eyes open. To determine the role of visual experience on the modulation of RSFC by resting state condition—as well as to evaluate the effect of resting state condition on group differences in RSFC—, we compared RSFC between visual and somatosensory/auditory regions in congenitally blind individuals (n = 9) and sighted participants (n = 9) during eyes open and eyes closed conditions. In the sighted group, we replicated the increase of RSFC between visual and non-visual areas during rest with eyes closed relative to rest with eyes open. This was not the case in the congenitally blind group, resulting in a lower RSFC between ‘visual’ and non-‘visual’ circuits relative to sighted controls only in the eyes closed condition. These results indicate that visual experience is necessary for the modulation of RSFC by resting state condition and highlight the importance of considering whether sighted controls should be tested with eyes open or closed in studies of functional brain reorganization as a consequence of blindness.

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Functional network topology of the right insula affects emotion dysregulation in hyperactive-impulsive attention-deficit/hyperactivity disorder

Scientific Reports ◽

10.1038/s41598-021-94426-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Tammo Viering ◽

Pieter J. Hoekstra ◽

Alexandra Philipsen ◽

Jilly Naaijen ◽

Andrea Dietrich ◽

...

Keyword(s):

Attention Deficit Hyperactivity Disorder ◽

Network Topology ◽

Resting State ◽

Latent Variable ◽

Emotion Dysregulation ◽

Adult Adhd ◽

Brain Regions ◽

Graph Analysis ◽

Hyperactivity Disorder ◽

The Right

AbstractEmotion dysregulation is common in attention-deficit/hyperactivity disorder (ADHD). It is highly prevalent in young adult ADHD and related to reduced well-being and social impairments. Neuroimaging studies reported neural activity changes in ADHD in brain regions associated with emotion processing and regulation. It is however unknown whether deficits in emotion regulation relate to changes in functional brain network topology in these regions. We used a combination of graph analysis and structural equation modelling (SEM) to analyze resting-state functional connectivity in 147 well-characterized young adults with ADHD and age-matched healthy controls from the NeuroIMAGE database. Emotion dysregulation was gauged with four scales obtained from questionnaires and operationalized through a latent variable derived from SEM. Graph analysis was applied to resting-state data and network topology measures were entered into SEM models to identify brain regions whose local network integration and connectedness differed between subjects and was associated with emotion dysregulation. The latent variable of emotion dysregulation was characterized by scales gauging emotional distress, emotional symptoms, conduct symptoms, and emotional lability. In individuals with ADHD characterized by prominent hyperactivity-impulsivity, the latent emotion dysregulation variable was related to an increased clustering and local efficiency of the right insula. Thus, in the presence of hyperactivity-impulsivity, clustered network formation of the right insula may underpin emotion dysregulation in young adult ADHD.

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Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

Brain Topography ◽

10.1007/s10548-021-00835-3 ◽

2021 ◽

Author(s):

Adeline Jabès ◽

Giuliana Klencklen ◽

Paolo Ruggeri ◽

Christoph M. Michel ◽

Pamela Banta Lavenex ◽

...

Keyword(s):

Older Adults ◽

Working Memory ◽

Resting State ◽

Cognitive Aging ◽

Temporal Dynamics ◽

Spatial Working Memory ◽

Brain Activity ◽

Memory Performance ◽

Brain Regions ◽

Age Related

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

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Distinguishing hypochondriasis and schizophrenia using regional homogeneity: a resting-state fMRI study and support vector machine analysis

Acta Neuropsychiatrica ◽

10.1017/neu.2021.9 ◽

2021 ◽

pp. 1-29

Author(s):

Kangyu Jin ◽

Zhe Shen ◽

Guoxun Feng ◽

Zhiyong Zhao ◽

Jing Lu ◽

...

Keyword(s):

Cognitive Function ◽

Resting State ◽

Parietal Lobe ◽

Brain Activity ◽

Resting State Fmri ◽

Brain Regions ◽

Regional Homogeneity ◽

Middle Temporal Gyrus ◽

Support Vector ◽

Fmri Study

Abstract Objective: A few former studies suggested there are partial overlaps in abnormal brain structure and cognitive function between Hypochondriasis (HS) and schizophrenia (SZ). But their differences in brain activity and cognitive function were unclear. Methods: 21 HS patients, 23 SZ patients, and 24 healthy controls (HC) underwent Resting-state functional magnetic resonance imaging (rs-fMRI) with the regional homogeneity analysis (ReHo), subsequently exploring the relationship between ReHo value and cognitive functions. The support vector machines (SVM) were used on effectiveness evaluation of ReHo for differentiating HS from SZ. Results: Compared with HC, HS showed significantly increased ReHo values in right middle temporal gyrus (MTG), left inferior parietal lobe (IPL) and right fusiform gyrus (FG), while SZ showed increased ReHo in left insula, decreased ReHo values in right paracentral lobule. Additionally, HS showed significantly higher ReHo values in FG, MTG and left paracentral lobule but lower in insula than SZ. The higher ReHo values in insula were associated with worse performance in MCCB in HS group. SVM analysis showed a combination of the ReHo values in insula and FG was able to satisfactorily distinguish the HS and SZ patients. Conclusion: our results suggested the altered default mode network (DMN), of which abnormal spontaneous neural activity occurs in multiple brain regions, might play a key role in the pathogenesis of HS, and the resting-state alterations of insula closely related to cognitive dysfunction in HS. Furthermore, the combination of the ReHo in FG and insula was a relatively ideal indicator to distinguish HS from SZ.

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The Role of the Parietal Lobe in Visual Extinction Studied with Transcranial Magnetic Stimulation

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2008.21149 ◽

2009 ◽

Vol 21 (10) ◽

pp. 1946-1955 ◽

Cited By ~ 49

Author(s):

Lorella Battelli ◽

George A. Alvarez ◽

Thomas Carlson ◽

Alvaro Pascual-Leone

Keyword(s):

Transcranial Magnetic Stimulation ◽

Visual Tracking ◽

Magnetic Stimulation ◽

Posterior Parietal Cortex ◽

Parietal Lobe ◽

Repetitive Transcranial Magnetic Stimulation ◽

Visual Fields ◽

Brain Regions ◽

Visual Extinction ◽

Interhemispheric Competition

Interhemispheric competition between homologous areas in the human brain is believed to be involved in a wide variety of human behaviors from motor activity to visual perception and particularly attention. For example, patients with lesions in the posterior parietal cortex are unable to selectively track objects in the contralesional side of visual space when targets are simultaneously present in the ipsilesional visual field, a form of visual extinction. Visual extinction may arise due to an imbalance in the normal interhemispheric competition. To directly assess the issue of reciprocal inhibition, we used fMRI to localize those brain regions active during attention-based visual tracking and then applied low-frequency repetitive transcranial magnetic stimulation over identified areas in the left and right intraparietal sulcus to asses the behavioral effects on visual tracking. We induced a severe impairment in visual tracking that was selective for conditions of simultaneous tracking in both visual fields. Our data show that the parietal lobe is essential for visual tracking and that the two hemispheres compete for attentional resources during tracking. Our results provide a neuronal basis for visual extinction in patients with parietal lobe damage.

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Interhemispheric Competition After Stroke: Brain Stimulation to Enhance Recovery of Function of the Affected Hand

Neurorehabilitation and Neural Repair ◽

10.1177/1545968309336661 ◽

2009 ◽

Vol 23 (7) ◽

pp. 641-656 ◽

Cited By ~ 275

Author(s):

Dennis A. Nowak ◽

Christian Grefkes ◽

Mitra Ameli ◽

Gereon R. Fink

Keyword(s):

Brain Stimulation ◽

Motor Behavior ◽

Cortical Excitability ◽

Recovery Of Function ◽

Repetitive Transcranial Magnetic Stimulation ◽

Hand Function ◽

Clinical Effects ◽

Sensorimotor Network ◽

Interhemispheric Competition ◽

Plastic Changes

Background and purpose. Within the concept of interhemispheric competition, technical modulation of the excitability of motor areas in the contralesional and ipsilesional hemisphere has been applied in an attempt to enhance recovery of hand function following stroke. This review critically summarizes the data supporting the use of novel electrophysiological concepts in the rehabilitation of hand function after stroke. Summary of review. Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) are powerful tools to inhibit or facilitate cortical excitability. Modulation of cortical excitability may instantaneously induce plastic changes within the cortical network of sensorimotor areas, thereby improving motor function of the affected hand after stroke. No significant adverse effects have been noted when applying brain stimulation in stroke patients. To date, however, the clinical effects are small to moderate and short lived. Future work should elucidate whether repetitive administration of rTMS or tDCS over several days and the combination of these techniques with behavioral training (ie, physiotherapy) could result in an enhanced effectiveness. Conclusion. Brain stimulation is a safe and promising tool to induce plastic changes in the cortical sensorimotor network to improve motor behavior after stroke. However, several methodological issues remain to be answered to further improve the effectiveness of these new approaches.

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Globally conditioned Granger causality in brain–brain and brain–heart interactions: a combined heart rate variability/ultra-high-field (7 T) functional magnetic resonance imaging study

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2015.0185 ◽

2016 ◽

Vol 374 (2067) ◽

pp. 20150185 ◽

Cited By ~ 30

Author(s):

Andrea Duggento ◽

Marta Bianciardi ◽

Luca Passamonti ◽

Lawrence L. Wald ◽

Maria Guerrisi ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Resting State ◽

High Field ◽

Brain Activity ◽

Brain Regions ◽

Sympathovagal Balance ◽

Functional Magnetic Resonance ◽

Resonance Imaging ◽

Ultra High Field ◽

Conditioned Approach

The causal, directed interactions between brain regions at rest (brain–brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain–heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain–brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain–brain and brain–heart interactions reflecting central modulation of ANS outflow.

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