Motor Sequences - Separating The Sequence From The Motor. A longitudinal rsfMRI Study

AbstractIn motor learning, sequence-specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific increases in functional connectivity during fast learning in the sensorimotor territory of the internal segment of right globus pallidus (GPi), and sequence-specific decreases in right supplementary motor area (SMA) in overall learning. We found that connectivity changes in key regions of the motor network including the superior parietal cortex (SPC) and primary motor cortex (M1) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA and GPi that has previously been identified in online task-based learning studies in humans and primates, and extends it to resting state network changes after sequence-specific MSL. Finally, our results shed light on a timing-specific plasticity mechanism between GPi and SMA following MSL.

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Meditation-State Functional Connectivity (msFC): Strengthening of the Dorsal Attention Network and Beyond

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2012/680407 ◽

2012 ◽

Vol 2012 ◽

pp. 1-9 ◽

Cited By ~ 34

Author(s):

Brett Froeliger ◽

Eric L. Garland ◽

Rachel V. Kozink ◽

Leslie A. Modlin ◽

Nan-Kuei Chen ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Control Group ◽

Meditation Practice ◽

Regression Analyses ◽

Resting State Networks ◽

Resting State Functional Connectivity ◽

Attention Network ◽

Dorsal Attention Network ◽

Meditation Experience

Meditation practice alters intrinsic resting-state functional connectivity (rsFC) in the default mode network (DMN). However, little is known regarding the effects of meditation on other resting-state networks. The aim of current study was to investigate the effects of meditation experience and meditation-state functional connectivity (msFC) on multiple resting-state networks (RSNs). Meditation practitioners (MPs) performed two 5-minute scans, one during rest, one while meditating. A meditation naïve control group (CG) underwent one resting-state scan. Exploratory regression analyses of the relations between years of meditation practice and rsFC and msFC were conducted. During resting-state, MP as compared to CG exhibited greater rsFC within the Dorsal Attention Network (DAN). Among MP, meditation, as compared to rest, strengthened FC between the DAN and DMN and Salience network whereas it decreased FC between the DAN, dorsal medial PFC, and insula. Regression analyses revealed positive correlations between the number of years of meditation experience and msFC between DAN, thalamus, and anterior parietal sulcus, whereas negative correlations between DAN, lateral and superior parietal, and insula. These findings suggest that the practice of meditation strengthens FC within the DAN as well as strengthens the coupling between distributed networks that are involved in attention, self-referential processes, and affective response.

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Fatigue in multiple sclerosis: The contribution of resting-state functional connectivity reorganization

Multiple Sclerosis Journal ◽

10.1177/1352458517730932 ◽

2017 ◽

Vol 24 (13) ◽

pp. 1696-1705 ◽

Cited By ~ 23

Author(s):

Alvino Bisecco ◽

Federica Di Nardo ◽

Renato Docimo ◽

Giuseppina Caiazzo ◽

Alessandro d’Ambrosio ◽

...

Keyword(s):

Multiple Sclerosis ◽

Regression Analysis ◽

Functional Connectivity ◽

Motor Cortex ◽

Resting State ◽

Primary Motor Cortex ◽

Linear Regression Analysis ◽

Posterior Cingulate Cortex ◽

Resting State Functional Connectivity ◽

Sensorimotor Network

Objectives: To investigate resting-state functional connectivity (RS-FC) of the default-mode network (DMN) and of sensorimotor network (SMN) network in relapsing remitting (RR) multiple sclerosis (MS) patients with fatigue (F) and without fatigue(NF). Methods: In all, 59 RRMS patients and 29 healthy controls (HC) underwent magnetic resonance imaging (MRI) protocol including resting-state fMRI (RS-fMRI). Functional connectivity of the DMN and SMN was evaluated by independent component analysis (ICA). A linear regression analysis was performed to explore whether fatigue was mainly driven by changes observed in the DMN or in the SMN. Regional gray matter atrophy was assessed by voxel-based morphometry (VBM). Results: Compared to HC, F-MS patients showed a stronger RS-FC in the posterior cingulate cortex (PCC) and a reduced RS-FC in the anterior cingulated cortex (ACC) of the DMN. F-MS patients, compared to NF-MS patients, revealed (1) an increased RS-FC in the PCC and a reduced RS-FC in the ACC of the DMN and (2) an increased RS-FC in the primary motor cortex and in the supplementary motor cortex of the SMN. The regression analysis suggested that fatigue is mainly driven by RS-FC changes of the DMN. Conclusions: Fatigue in RRMS is mainly associated to a functional rearrangement of non-motor RS networks.

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Role of beta-band resting-state functional connectivity as a predictor of motor learning ability

NeuroImage ◽

10.1016/j.neuroimage.2020.116562 ◽

2020 ◽

Vol 210 ◽

pp. 116562 ◽

Cited By ~ 1

Author(s):

Hisato Sugata ◽

Kazuhiro Yagi ◽

Shogo Yazawa ◽

Yasunori Nagase ◽

Kazuhito Tsuruta ◽

...

Keyword(s):

Functional Connectivity ◽

Motor Learning ◽

Resting State ◽

Learning Ability ◽

Beta Band ◽

Resting State Functional Connectivity

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The link between resting-state functional connectivity and cognition in MS patients

Multiple Sclerosis Journal ◽

10.1177/1352458513495584 ◽

2013 ◽

Vol 20 (3) ◽

pp. 338-348 ◽

Cited By ~ 42

Author(s):

Álvaro J Cruz-Gómez ◽

Noelia Ventura-Campos ◽

Antonio Belenguer ◽

Cesar Ávila ◽

Cristina Forn

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Cognitive Status ◽

Control Group ◽

Cognitively Impaired ◽

Lesion Volume ◽

Resting State Functional Connectivity ◽

Frontoparietal Network ◽

Brain Parenchymal Fraction ◽

Brain Parenchymal

Objective: The objective of this paper is to explore differences in resting-state functional connectivity between cognitively impaired and preserved multiple sclerosis (MS) patients. Methods: Sixty MS patients and 18 controls were assessed with the Brief Repeatable Battery of Neuropsychological Tests (BRB-N). A global Z score of the BRB-N was obtained and allowed us to classify MS patients as cognitively impaired and cognitively preserved ( n = 30 per group). Functional connectivity was assessed by independent component analysis of resting-state networks (RSNs) related to cognition: the default mode network, left and right frontoparietal and salience network. Between-group differences were evaluated and a regression analysis was performed to describe relationships among cognitive status, functional connectivity and radiological variables. Results: Compared to cognitively preserved patients and healthy controls, cognitively impaired patients showed a lesser degree of functional connectivity in all RSNs explored. Cognitively preserved patients presented less connectivity than the control group in the left frontoparietal network. Global Z scores were positively and negatively correlated with brain parenchymal fraction and lesion volume, respectively. Conclusion: Decreased cognitive performance is accompanied by reduced resting state functional connectivity and directly related to brain damage. These results support the use of connectivity as a powerful tool to monitor and predict cognitive impairment in MS patients.

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Primary motor cortex mapping in brain-lesioned patients using MEG resting-state functional connectivity

Frontiers in Human Neuroscience ◽

10.3389/conf.fnhum.2014.214.00007 ◽

2014 ◽

Vol 8 ◽

Author(s):

Coquelet Nicolas ◽

Wens Vincent ◽

Bourguignon Mathieu ◽

Carrette Evelien ◽

Op De Beeck Marc ◽

...

Keyword(s):

Functional Connectivity ◽

Motor Cortex ◽

Resting State ◽

Primary Motor Cortex ◽

Resting State Functional Connectivity ◽

Motor Cortex Mapping

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Impact of self-designed Ningxin Anshen Decoction on the resting-state network functional connectivity in patients with mild to moderate generalized anxiety disorders: a Clinical Trial (Preprint)

10.2196/preprints.17931 ◽

2020 ◽

Author(s):

Wenjing He ◽

Hang Xiong ◽

Jiangshan Fang ◽

Hao Gu ◽

Rongjuan Guo

Keyword(s):

Functional Connectivity ◽

Resting State ◽

The Self ◽

Control Group ◽

Generalized Anxiety ◽

Resting State Functional Connectivity ◽

Before And After ◽

Generalized Anxiety Disorders ◽

Hamilton Anxiety Scale ◽

The Right

BACKGROUND Generalized anxiety disorder (GAD) is a persistent chronic excessive anxiety that is hard to control. Our previous study indicated that self-designed Ningxin Anshen Formula (NXAS) was effective to improve the symptoms and Hamilton anxiety scale (HAMA) of mild to moderate GAD patients. OBJECTIVE This study aimed to investigate the imapct of self-designed NXAS on the resting-state functional connectivity (RSFC) in patients with mild to moderate GAD and explore the potential mechanisms. METHODS A total of 61 patients diagnosed with mild to moderate GAD were recruited and divided into two groups: NXAS group (n=31) and placebo group (n=30). Before and after treatment, the RSFC was examined by resting-state functional MRI (rs-fMRI), the anxiety was assessed with HAMA, and the independent component analysis (ICA) was used to analyze the resting-state functional connectivity (RSFC). The correlation between HAMA score and abnormal RSFC was further evaluated. RESULTS The default mode network (DMN) showed evident RSFC interaction in the PCUN in both groups before and after therapy. The salience network (SN) showed obvious RSFC interaction in the bilateral gyrus frontalis inferiors and bilateral gyri temporalis superiors before and after therapy. In the NXAS group, the RSFC interction reduced significantly in the left gyrus frontalis inferior, but remained unchanged in the right gyrus frontalis inferior and bilateral gyri temporalis superiors after therapy. In the control group, the RSFC interaction increased dramatically after treatment. In addition, the abnormal RSFC had no relationship with HAMA score. CONCLUSIONS The self-designed NXAS can increase the RSFC in the PUCN on DMN and reduce RSFC in the orbIFG.L on SN to exert anti-anxiety effect. CLINICALTRIAL The study was registered on the Clinical Trials (NO. ChiCTR-OCC-12002329).

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Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing

Journal of Neurophysiology ◽

10.1152/jn.00286.2015 ◽

2015 ◽

Vol 114 (1) ◽

pp. 677-688 ◽

Cited By ~ 20

Author(s):

Heather R. McGregor ◽

Paul L. Gribble

Keyword(s):

Functional Connectivity ◽

Motor Learning ◽

Resting State ◽

Action Observation ◽

Resting State Fmri ◽

Learning Task ◽

Brain Regions ◽

Neural Systems ◽

Resting State Functional Connectivity ◽

Somatosensory Cortices

Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153–160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493–1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289–2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989–994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400–404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526–2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769–771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning.

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Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing

Journal of Neurophysiology ◽

10.1152/jn.00275.2017 ◽

2017 ◽

Vol 118 (2) ◽

pp. 1235-1243 ◽

Cited By ~ 15

Author(s):

Heather R. McGregor ◽

Paul L. Gribble

Keyword(s):

Individual Differences ◽

Functional Connectivity ◽

Motor Learning ◽

Resting State ◽

Brain Function ◽

Motor Recovery ◽

Resting State Functional Connectivity ◽

Brain Areas ◽

Motor Network ◽

Sensory Motor

We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke.

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Bedside functional monitoring of the dynamic brain connectivity in human neonates

Nature Communications ◽

10.1038/s41467-021-21387-x ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Jerome Baranger ◽

Charlie Demene ◽

Alice Frerot ◽

Flora Faure ◽

Catherine Delanoë ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Brain Connectivity ◽

Preterm Neonates ◽

Control Group ◽

Resting State Functional Connectivity ◽

Very Preterm ◽

Fine Grain ◽

Term Newborns ◽

Human Neonates

AbstractClinicians have long been interested in functional brain monitoring, as reversible functional losses often precedes observable irreversible structural insults. By characterizing neonatal functional cerebral networks, resting-state functional connectivity is envisioned to provide early markers of cognitive impairments. Here we present a pioneering bedside deep brain resting-state functional connectivity imaging at 250-μm resolution on human neonates using functional ultrasound. Signal correlations between cerebral regions unveil interhemispheric connectivity in very preterm newborns. Furthermore, fine-grain correlations between homologous pixels are consistent with white/grey matter organization. Finally, dynamic resting-state connectivity reveals a significant occurrence decrease of thalamo-cortical networks for very preterm neonates as compared to control term newborns. The same method also shows abnormal patterns in a congenital seizure disorder case compared with the control group. These results pave the way to infants’ brain continuous monitoring and may enable the identification of abnormal brain development at the bedside.

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