The functional connectivity in the motor loop of human basal ganglia

Rodriguez-Sabate, Clara; Sabaté, Magdalena; Llanos, Catalina; Moráles, Ingrid; Sánchez, Ana María Sánchez; Rodrı́guez, Manuel

doi:10.1007/s11682-016-9512-y

Cited by 12 publications

(17 citation statements)

References 90 publications

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“…The M1 was located in the precentral gyrus posterior to the junction of the superior frontal sulcus with the precentral sulcus, and according to a previously reported procedure (Rodriguez et al, 2004). Additional comments about the ROI identification can be found in previous studies (Rodriguez et al, 2004; Rodriguez-Sabate et al, 2015, 2016). …”

Section: Methodsmentioning

confidence: 94%

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia

et al. 2017

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The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

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Section: Methodsmentioning

confidence: 94%

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia

et al. 2017

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“…The basic experimental procedures were similar to those reported in recent studies (Rodriguez-Sabate et al, 2015; Rodriguez-Sabate et al, 2017), but using two experimental conditions, motor-resting (subjects did not perform any planned task) and motor-task (subjects performed a repetitive sequence of finger extensions/flexions with the right-hand). BOLD-contrast images (4x4x4 mm voxels in-plane resolution; echo-planar imaging with repetition time 1.6 s; echo time 21.6 msec; flip angle 90°) were recorded in blocks of 100 volumes in the following sequence: motor block → resting block → motor block → resting block (400 total volumes / subject = 100 volumes × 2 motor-blocks × 2 resting-blocks).…”

Section: Methodsmentioning

confidence: 99%

The organization of the basal ganglia functional connectivity network is non-linear in Parkinson's disease

Rodriguez-Sabate

Moráles

Lorenzo³

et al. 2019

NeuroImage: Clinical

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The motor symptoms in Parkinson's disease (PD) have been linked to changes in the excitatory/inhibitory interactions of centers involved in the cortical-subcortical closed-loop circuits which connect basal ganglia (BG) and the brain cortex. This approach may explain some motor symptoms of PD but not others, which has driven the study of BG from new perspectives. Besides their cortical-subcortical linear circuits, BG have a number of subcortical circuits which directly or indirectly connect each BG with all the others. This suggests that BG may work as a complex network whose output is the result of massive functional interactions between all of their nuclei (decentralized network; DCN), more than the result of the linear excitatory/inhibitory interactions of the cortical-subcortical closed-loops. The aim of this work was to study BG as a DCN, and to test whether the DCN behavior of BG changes in PD. BG activity was recorded with MRI methods and their complex interactions were studied with a procedure based on multiple correspondence analysis, a data-driven multifactorial method which can work with non-linear multiple interactions. The functional connectivity of twenty parkinsonian patients and eighteen age-matched controls were studied during resting and when they were performing sequential hand movements. Seven functional configurations were identified in the control subjects during resting, and some of these interactions changed with motor activity. Five of the seven interactions found in control subjects changed in Parkinson's disease. The BG response to the motor task was also different in PD patients and controls. These data show the basal ganglia as a decentralized network where each region can perform multiple functions and each function is performed by multiple regions. This framework of BG interactions may provide new explanations concerning motor symptoms of PD which are not explained by current BG models.

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“…The basic experimental procedures were similar to those reported in recent studies ( Rodriguez-Sabate et al , 2015 , 2017 b ). Blood-oxygen-level-dependent imaging (BOLD) contrast images (4 mm × 4 mm × 4 mm voxels in-plane resolution; echo-planar imaging with repetition time 1.6 s; echo time 21.6 ms; flip angle 90°) were recorded in a block of 200 volumes (volumes 1–10 of the block were removed).…”

Section: Methodsmentioning

confidence: 60%

“…A representative region of interest of each BG was located on a subject-by-subject basis by considering: (i) the Talairach coordinates, (ii) the shape of the nucleus and (iii) the anatomical relationship of the nucleus with neighbouring structures. All regions were identified in coronal slices located 4–27 mm posterior to the anterior commissure and according to a previously reported procedure ( Rodriguez-Sabate et al , 2017 b ). All data sets were normalized to the Talairach space.…”

Section: Methodsmentioning

confidence: 99%

“…This approach can be directly performed in the human brain by using magnetic resonance imaging (MRI) methods (functional connectivity MRI, fcMRI; Raichle, 1998 ; Arthurs and Boniface, 2002 ; Logothetis, 2002 ; Logothetis and Wandell, 2004 ; Raichle and Mintun, 2006 ; Rodriguez-Sabate et al , 2017 b , 2019 a ). Correlation methods are the most common procedures used to analyse fcMRI data ( Fox and Raichle, 2007 ; Zhang et al , 2010 ; Rodriguez-Sabate et al , 2017 b , 2019 b ), but they need some requirements (e.g. linear behaviour, normality and stationarity of data) that are not always met in neuronal networks ( Eklund et al , 2018 ; Olszowy et al , 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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The dynamic of basal ganglia activity with a multiple covariance method: influences of Parkinson’s disease

Rodriguez-Sabate

Moráles

Puertas-Avendaño

et al. 2019

Brain Communications

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The closed-loop cortico-subcortical pathways of basal ganglia have been extensively used to describe the physiology of these centres and to justify the functional disorders of basal ganglia diseases. This approach justifies some experimental and clinical data but not others, and furthermore, it does not include a number of subcortical circuits that may produce a more complex basal ganglia dynamic than that expected for closed-loop linear networks. This work studied the functional connectivity of the main regions of the basal ganglia motor circuit with magnetic resonance imaging and a new method (functional profile method), which can analyse the multiple covariant activity of human basal ganglia. The functional profile method identified the most frequent covariant functional status (profiles) of the basal ganglia motor circuit, ordering them according to their relative frequency and identifying the most frequent successions between profiles (profile transitions). The functional profile method classified profiles as input profiles that accept the information coming from other networks, output profiles involved in the output of processed information to other networks and highly interconnected internal profiles that accept transitions from input profiles and send transitions to output profiles. Profile transitions showed a previously unobserved functional dynamic of human basal ganglia, suggesting that the basal ganglia motor circuit may work as a dynamic multiple covariance network. The number of internal profiles and internal transitions showed a striking decrease in patients with Parkinson’s disease, a fact not observed for input and output profiles. This suggests that basal ganglia of patients with Parkinson’s disease respond to requirements coming from other neuronal networks, but because the internal processing of information is drastically weakened, its response will be insufficient and perhaps also self-defeating. These marked effects were found in patients with few motor disorders, suggesting that the functional profile method may be an early procedure to detect the first stages of the Parkinson’s disease when the motor disorders are not very evident. The multiple covariance activity found presents a complementary point of view to the cortico-subcortical closed-loop model of basal ganglia. The functional profile method may be easily applied to other brain networks, and it may provide additional explanations for the clinical manifestations of other basal ganglia disorders.

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The functional connectivity in the motor loop of human basal ganglia

Cited by 12 publications

References 90 publications

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia

The organization of the basal ganglia functional connectivity network is non-linear in Parkinson's disease

The dynamic of basal ganglia activity with a multiple covariance method: influences of Parkinson’s disease

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