|Year : 2020 | Volume
| Issue : 2 | Page : 106-111
Re-emergent tremor in patients with Parkinson’s disease: an imaging study
Pooja Mailankody1, Lija George1, Rajini M Naduthota1, Jitender Saini2, K Thennarasu3, Ravi Yadav1, Pramod K Pal1
1 Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
2 Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
3 Department of Biostatistics, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
|Date of Submission||15-Dec-2019|
|Date of Decision||08-Feb-2020|
|Date of Acceptance||13-Mar-2020|
|Date of Web Publication||28-Jul-2020|
Prof. Pramod K Pal
Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road, Bengaluru, Karnataka.
Source of Support: None, Conflict of Interest: None
BACKGROUND AND PURPOSE: Re-emergent tremor (ReT) is the tremor that reappears after a variable period of latency while maintaining posture. Little is known about the mechanisms that contribute to the origin of this silent period (SP). Our aim was to compare the imaging characteristics of patients with and without ReT and find the structural correlate of SP if any. MATERIALS AND METHODS: Fifteen patients with ReT (Group 1) and eighteen patients without ReT (patients with rest tremor and postural tremor, but no latency) were evaluated clinically, electrophysiologically, with diffusion tensor imaging (DTI) and voxel-based morphometry (VBM). DTI parameters of different regions of interest were analyzed and compared with that of 37 healthy age- and gender-matched controls. RESULTS: No statistically significant difference was observed between the two groups in terms of age, duration of disease, levodopa equivalent dose, or severity of the disease. However, in the left supplementary motor area (SMA), there was a significant reduction of fractional anisotropy and an increase of radial diffusivity and mean diffusivity in patients with ReT (Group 1) as compared to patients without ReT (Group 2) and healthy controls. The results of the VBM analysis were not significant. CONCLUSION: The presence of abnormality of SMA suggests that patients with ReT have a different pathophysiological mechanism as compared to patients without ReT. This is a novel finding implicating a possible contribution of the frontal lobe to the genesis of SP in ReT. ReT could be a distinct clinical entity within the tremor dominant subtype.
Keywords: Diffusion tensor imaging, magnetic resonance imaging, Parkinson’s disease, re-emergent tremor, rest tremor
|How to cite this article:|
Mailankody P, George L, Naduthota RM, Saini J, Thennarasu K, Yadav R, Pal PK. Re-emergent tremor in patients with Parkinson’s disease: an imaging study. Ann Mov Disord 2020;3:106-11
|How to cite this URL:|
Mailankody P, George L, Naduthota RM, Saini J, Thennarasu K, Yadav R, Pal PK. Re-emergent tremor in patients with Parkinson’s disease: an imaging study. Ann Mov Disord [serial online] 2020 [cited 2023 May 30];3:106-11. Available from: https://www.aomd.in/text.asp?2020/3/2/106/291080
| Introduction|| |
Parkinson’s disease (PD) is a neurodegenerative disorder characterized by rest tremor (RT), rigidity, bradykinesia, and gait impairment. Although RT is the cardinal feature, patients with PD can also have action tremor, which includes postural tremor (PT), kinetic tremor, re-emergent tremor (ReT), and orthostatic tremor. ReT is the tremor that reappears after a variable period of latency while maintaining posture. The term ReT was first coined by Jankovic in 1999 in a short report titled “Re-emergent tremor of PD.” Jankovic, in the same paper, has variably called this an RT and a “postural tremor with latency.” ReT can be present in up to 81% of the patients with tremor dominant PD.,,, Both clinically and electrophysiologically, ReT is similar to RT.,[6-8] The period of latency for the reemergence of tremor can range from 0.79 to 13s.[2-7], Two recent studies that evaluated patients with ReT showed that there are no significant clinical or electrophysiological differences between RT and ReT., Another study by Belvisi et al. showed that patients with ReT have less severe disease in terms of speech, posture, gait involvement, and bradykinesia score as compared to those with PT. However, the origin and significance of the period of latency have remained elusive.
Magnetic resonance (MR) diffusion tensor imaging (DTI) is an imaging technique used to evaluate the integrity of white matter (WM) tracts by measuring water diffusion and its directionality or anisotropy. It can also be used for studying gray matter (GM) areas. The various DTI parameters estimated are fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). These measurements can either be extracted locally in predefined regions using region of interest (ROI) analysis or tractography or, alternatively, globally using voxel-based analysis or tract-based spatial statistics. Alterations in anisotropy and diffusivity can be detected in neurodegeneration due to the disruption of microstructural integrity.,, Both increased RD and/or reduced AD can cause decreased FA in WM neuropathology. Measurements of the MD may help in a better understanding of how the diffusion tensor is changing. RD is controlled by myelin in WM, whereas the AD is more specific to axonal degeneration. Studies in PD have shown that FA is reduced in the substantia nigra (SN),,,. One study by Zhan et al. evaluated the microstructural changes in different subtypes of PD and also tried to correlate the diffusion changes with disease severity. Voxel-based morphometry (VBM) is an imaging technique that enables the detection of brain volume changes. Higher GM concentration was found in the thalamus contralateral to the side of RT in a VBM study by Kassubek et al. No prior DTI or VBM study has explored the distribution of microstructural alteration in patients with different types of tremor.
The reason why some patients have a period of latency, whereas others do not is not clear. The period of latency, which is otherwise called the silent period (SP), denotes a period where an otherwise symptomatic patient does not have tremor transiently. The duration of the SP is variable. The presence of SP, both clinically and electrophysiologically, suggests that ReT could be a distinct entity. Nevertheless, lack of its consistency in both occurrence and duration raises the possibility that it is only a transient epiphenomenon during the course of illness. The aim of this study was to compare the imaging characteristics of patients with and without ReT. Structural correlates for SP if, any, could suggest that ReT is a distinct clinical entity within the tremor dominant subtype.
| Materials and Methods|| |
This was a prospective, hospital-based case-control study. The protocol was approved by the Institutional Ethics Committee. Written informed consent was taken from all participants. Thirty-three patients with PD as per the United Kingdom Parkinson’s Disease Society Brain Bank Clinical Diagnostic criteria and tremor dominance were recruited from the Neurology outpatient clinics of the National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru. In addition to detailed clinical history and neurological examination, tremor assessment was carried out using the Fahn–Tolosa–Marin Tremor Rating Scale and Unified Parkinson Disease Rating Scale (UPDRS) part III. UPDRS III was carried out both during OFF and ON states. Tremor-dominant PD was defined as an (UPDRS) RT score of ≥2 in at least one hand during the physical examination and a history of RT. The OFF state was defined as the cessation of levodopa for at least 12h and controlled-release levodopa and dopamine agonists for at least 18h.
Patients were divided into two groups. Group 1 consisted of patients with RT and ReT. Group 2 consisted of patients with RT and PT. Thirty-seven age- and gender-matched healthy controls were recruited (Group 0).
The presence of latency for the emergence of ReT was determined clinically and confirmed by tremor recording. The patient was considered to have ReT when there was an SP with no tremor after hands assumed an outstretched position. If the tremor was present immediately when hands were outstretched patient was considered to have a PT. The presence of SP was confirmed by surface tremorogram, the details of which are given below.
Surface electrodes of the monopolar disc type were placed in a tendon-belly arrangement to record electromyography (EMG) activities from the antagonistic muscles. The muscles selected were flexors and extensors of the wrist in the limb, which had the most severe tremor. The tremor was recorded with hands at rest, hands outstretched, and hands close to the chest, in the side in which tremor was more prominent. Once the hands were outstretched, the patient was observed for a period of at least 1 min for the reemergence of tremor which was then recorded. The tremor was analyzed in terms of the pattern (alternate versus synchronous contraction) and frequency (Hz). The duration of the SP was recorded.
Magnetic resonance imaging (MRI) was acquired on an Achieva 3Tesla MR imaging scanner (Philips Medical Systems, Netherlands) with a 32-channel head coil. The DTI data were obtained by using spin-echo echo-planar imaging (EPI) pulse sequences with Repetition time (TR)/Echo time (ET), 7267.6/58.7ms; flip angle, 90°; field of view (FOV), 224 mm × 224 mm; acquisition matrix, 112 × 109; reconstruction matrix, 128 × 128; voxel size, 2 × 2.04 × 2.5, and reconstruction voxel size of 1.75. The whole brain was covered with a slice thickness of 2.5 mm, without any interslice gap. For each subject, DTI images were acquired by using 16 noncollinear diffusion-sensitizing gradients and also with 32 directions with b-values of 0 and 1000s/mm2. Structural images were acquired using three-dimensional T1-weighted Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence covering the whole brain with TR = 1900ms; TE = 2.43ms; FOV = 256 mm × 256 mm × 155 mm; flip angle = 8◦; slice thickness = 1 mm.
Region of interest-based analysis
ROI-based analysis was performed for all the subjects. The ROIs selected for analysis were supplementary motor area (SMA), putamen, thalamus, caudate, SN, red nucleus, cerebellar hemispheres, and superior cerebellar peduncle (SCP)., The ROIs were identified bilaterally for each subject on the FA map. They were drawn independently by an experienced neuroradiologist who was blinded to the clinical data. The FA, RD, AD, and MD values were acquired for each area using Philips IntelliSpace Software (IntelliSpace Portal, Philips Healthcare Nederland B.V. Veenpluis 4-6, The Netherlands) [Figure 1]. Total brain volumes were calculated using statistical parametric mapping (SPM8) software.
|Figure 1: Fractional anisotropy map showing region of interest (ROI) at subcortical white matter close to supplementary motor area (SMA) denoted by the black circle|
Click here to view
Structural MRI data analysis was carried out on voxel-based morphometry [VBM8] toolbox in SPM8 software (Wellcome Trust Centre for Neuroimaging, London, UK) using MATLAB R2013a. The raw T1-weighted anatomical data of all the subjects in DICOM format were imported to SPM8 and saved as SPM compatible NIFTI format. Before preprocessing, all the subjects’ data were manually reoriented to their respective anterior commissure–posterior commissure (AC–PC) plane. VBM involves a voxel-wise comparison of the local concentration of GM between two groups of subjects. The procedure involves preprocessing, smoothing, and statistical analysis (available from http://www.fil.ion.ucl.ac.uk /spm/).
This involved spatially normalizing high-resolution T1-weighted anatomical images from all the subjects in both the groups in the study into the same stereotactic space. This was followed by segmenting the GM from the spatially normalized images.
Before entering the spatially normalized GM segments in to a statistical model, the image data were smoothed.
In addition to the VBM analysis of structural data, voxel-based analysis of FA maps was also performed. The Functional MRI of the Brain (FMRIB) Software Library (FSL; http://www.fmrib.ox.ac.uk/fsl/fdt/index.html) was used for generating the FA maps following preprocessing steps including eddy current correction, motion correction (by linear registering to the nondiffusion-weighted image using FLIRT), and brain extraction tool (BET) brain extraction.
Descriptive statistics such as mean, standard deviation, frequency, and percentages have been used to express data. Data were tested for normal distribution. A comparison of imaging parameters was made using the general linear model. Gender was the fixed factor, and age and total brain volume were the covariates. Voxel-wise parametric statistical tests that compare the smoothed GM images from the two groups were performed using two sample t tests. General linear model was applied with a height threshold of T = 4.2 (P < 0.001 uncorrected) and an extend threshold of 20 voxels. The output from the procedure was a statistical parametric map showing regions where GM concentrations did not vary significantly between the two groups.
The relationship between clinical, imaging, and electrophysiological parameters was established by Spearman correlation coefficients. A value of P < 0.05 was considered statistically significant. Data were analyzed using Statistical Package for the Social Sciences (SPSS) software program, version 15.0.1.
| Results|| |
The majority of the patients were males (86.7%). The mean age of onset of PD in these 33 patients was 48.73 ± 11.20 years, and the mean duration of illness was 5.72 ± 4.18 years. The mean mini mental state examination (MMSE) score was 29.25 ± 2.03. The clinical features and the UDPRS scores did not differ significantly between the two groups [Table 1]. Sixty percent of the patients in Group 1 had left-sided onset, whereas 72% of the patients in Group 2 had a right sided onset of tremor.
Electrophysiological evaluation of tremor
No statistically significant difference was observed between the frequencies of RT and ReT (4.8 ± 0.59 Hz vs. 4.9 ± 0.74 Hz). The frequencies of RT between the two groups did not vary significantly (4.8 ± 0.59 Hz vs. 4.9 ± 0.72 Hz). All the patients had an alternating pattern of contraction for both RT and ReT, except for one patient who had a synchronous pattern for both RT and ReT. The pattern of contraction of RT did not differ significantly between the two groups. The mean SP was 6.3 ± 2.9s (range 1–11s).
Diffusion tensor imaging analysis
The FA, RD, AD, and MD values were compared between Group 1, Group 2, and controls (with age, gender, and total brain volume as covariates). The left SMA was found to have a decreased FA value and increased RD and MD values as compared to controls as well as Group 2 [Figure 1] and [Table 2]. Other regions of the brain were similar for patients and controls. No significant correlation was found between the UPDRS scores and the FA values [Table 3].
|Table 2: Comparison of supplementary motor area between Group 1, Group 2, and controls|
Click here to view
|Table 3: Correlation of fractional anisotropy values with Unified Parkinson’s Disease Rating Scale (UPDRS) OFF scores|
Click here to view
Voxel-based morphometry analysis
The analysis of GM segments of patients with ReT versus those with PT using two sample t tests revealed no significant changes in GM density. GLM model was made using the theory of Gaussian random fields with a height threshold of T = 4. 2 (P < 0.001 uncorrected) and an extend threshold of 20 voxels.
VBM analysis did not yield any significant results.
Voxel-based analysis of fractional anisotropy maps
Voxel-based analysis of the FA maps did not reveal any significant changes in either group as compared to the control group.
| Discussion|| |
The entity of ReT in PD has never been evaluated in detail. The objective electrophysiological evidence of SP suggests that it could be a distinct clinical entity. With the help of DTI and VBM studies, we have attempted to delineate the possible anatomical substrates responsible for the generation of SP.
Left SMA was found to have significantly decreased FA in ROI-based analysis in Group 1 as compared to that of Group 2 and controls. This implies a decreased coherence of fibers in the connecting tracts. Frontal lobe dysfunction can be present in PD even in the absence of dementia., In a DTI study of 12 patients with nondemented PD, Karagulle Kendi et al. found signal changes in the SMA. SMA was found to have decreased activation during the performance of sequential finger movements in a positron emission tomography (PET) study of six patients with PD.
The initiation of voluntary movements requires the participation of SMA in both patients with PD as well as healthy volunteers., SMA receives inputs from globus pallidus and cerebellum and has projections to the motor cortex., A functional MRI study by Pochon et al. suggested that SMA may be required for the planning of actions. A task-based PET study revealed defective activation of the SMA in patients with PD while trying to initiate movement. In another PET study, Fukuda et al. found that decreasing the tremor amplitude by ventral intermediate thalamic DBS decreased the regional cerebral blood flow in the ipsilateral SMA and contralateral cerebellum. The same study suggested that the regional blood flow in SMA was modelled by tremor amplitude and that in the cerebellum was modelled by tremor frequency.
Naros et al. evaluated local field potentials and EMG during DBS and showed that there was an increased flow of information between the subthalamic nucleus (STN) and muscle in patients with tremor dominant PD. The proprioceptive inputs during voluntary movement are responsible for the reduction in the amplitude of tremor and this is mediated by the cerebello–thalamo–cortical network. Muthuraman et al. concluded that the flow of activity to the muscle is through the cerebello–thalamo–corticospinal pathway underscoring the contribution of the cortex to the generation of pathological tremor. STN is an essential component of the hyperdirect pathway and receives inputs from the SMA, primary motor and the premotor areas. The hyperdirect pathway, which is faster than the direct and the indirect pathways, results in widespread inhibition of the motor programs., The findings of our study and the study by Naros et al. suggest the involvement of SMA and STN, respectively, in the pathogenesis of ReT. Hence, we hypothesize that the activity of the hyperdirect pathway in patients with ReT is different as compared to the patients with no ReT.
Patients with PD who have ReT, compared to those who do not have ReT, probably have different pathophysiology, which involves the SMA. Apart from the presence of SP, the two groups of patients did not differ in terms of demographic features or electrophysiological characteristics. Our DTI studies suggest a possible contribution of the frontal lobe especially SMA, to the genesis of SP in ReT. However, VBM analysis did not yield any significant results. The presence of structural correlate for SP also suggests that ReT could be a distinct clinical entity within the tremor dominant subtype. A larger cohort of patients and prospective studies with follow up imaging will be needed for confirmation of this novel finding.
| Conclusion|| |
This is the first study that has evaluated the anatomical substrate responsible for the SP in ReT in PD. Abnormality of SMA found in the DTI studies suggests a different pathophysiological mechanism in patients with ReT as compared to patients without ReT. This is a novel finding implicating a possible contribution of the frontal lobe to the genesis of the SP in ReT and also suggests that ReT could be a distinct clinical entity.
Financial support and sponsorship
This work was partially supported by a grant from Department of Biotechnology (DBT), Government of India [grant number NO. BT/PR14315/MED/30/474/2010].
Conflicts of interest
There are no conflicts of interest.
| References|| |
Samii A Cardinal features of early Parkinson’s disease. In: Factor SA, Weiner WJ, editors. Parkinson’s Disease: Diagnosis and Clinical Management. 2nd ed. New York: Demos Medical Publishing; 2002. pp. 45-51.
Jankovic J, Schwartz KS, Ondo W Re-emergent tremor of Parkinson’s disease. J Neurol Neurosurg Psychiatry 1999;67:646-50.
Schwingenschuh P, Ruge D, Edwards MJ, Terranova C, Katschnig P, Carrillo F, et al
. Distinguishing SWEDDs patients with asymmetric resting tremor from Parkinson’s disease: A clinical and electrophysiological study. Mov Disord 2010;25:560-9.
Uchida K, Hirayama M, Yamashita F, Hori N, Nakamura T, Sobue G Tremor is attenuated during walking in essential tremor with resting tremor but not Parkinsonian tremor. J Clin Neurosci 2011;18:1224-8.
Onofrj M, Varanese S, Bonanni L, Taylor JP, Antonini A, Valente EM, et al
. Cohort study of prevalence and phenomenology of tremor in dementia with Lewy bodies. J Neurol 2013;260:1731-42.
Fekete R, Li J Clinical differentiation of essential tremor and Parkinson’s disease. Clin Med Insights Case Rep 2013;6:67-74.
Mailankody P, Thennarasu K, Nagaraju BC, Yadav R, Pal PK Re-emergent tremor in Parkinson’s disease: A clinical and electromyographic study. J Neurol Sci 2016;366:33-6.
Aytürk Z, Yilmaz R, Akbostanci MC Re-emergent tremor in Parkinson’s disease: Clinical and accelerometric properties. J Clin Neurosci 2017;37:31-3.
Belvisi D, Conte A, Bologna M, Bloise MC, Suppa A, Formica A, et al
. Re-emergent tremor in Parkinson’s disease. Parkinsonism Relat Disord 2017;36:41-6.
Cochrane CJ, Ebmeier KP Diffusion tensor imaging in Parkinsonian syndromes: A systematic review and meta-analysis. Neurology 2013;80:857-64.
Le Bihan D Looking into the functional architecture of the brain with diffusion MRI. Nat Rev Neurosci 2003;4:469-80.
Assaf Y, Pasternak O Diffusion tensor imaging (DTI)-based white matter mapping in brain research: A review. J Mol Neurosci 2008;34:51-61.
Alexander AL, Lee JE, Lazar M, Field AS Diffusion tensor imaging of the brain. Neurotherapeutics 2007;4:316-29.
Song SK, Sun SW, Ramsbottom MJ, Chang C, Russell J, Cross AH Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage 2002;17: 1429-36.
Chan LL, Rumpel H, Yap K, Lee E, Loo HV, Ho GL, et al
. Case control study of diffusion tensor imaging in Parkinson’s disease. J Neurol Neurosurg Psychiatry 2007;78:1383-6.
Lang AE, Mikulis D A new sensitive imaging biomarker for Parkinson disease? Neurology 2009;72:1374-5.
Vaillancourt DE, Spraker MB, Prodoehl J, Abraham I, Corcos DM, Zhou XJ, et al
. High-resolution diffusion tensor imaging in the substantia nigra of de novo Parkinson disease. Neurology 2009;72:1378-84.
Skorpil M, Söderlund V, Sundin A, Svenningsson P MRI diffusion in Parkinson’s disease: Using the technique’s inherent directional information to study the olfactory bulb and substantia nigra. J Parkinsons Dis 2012;2:171-80.
Zhan W, Kang GA, Glass GA, Zhang Y, Shirley C, Millin R, et al
. Regional alterations of brain microstructure in Parkinson’s disease using diffusion tensor imaging. Mov Disord 2012;27:90-7.
Ashburner J, Friston KJ Voxel-based morphometry––the methods. Neuroimage 2000;11:805-21.
Kassubek J, Juengling FD, Hellwig B, Spreer J, Lücking CH Thalamic gray matter changes in unilateral Parkinsonian resting tremor: A voxel-based morphometric analysis of 3-dimensional magnetic resonance imaging. Neurosci Lett 2002;323:29-32.
Helmich RC, Janssen MJ, Oyen WJ, Bloem BR, Toni I Pallidal dysfunction drives a cerebellothalamic circuit into Parkinson tremor. Ann Neurol 2011;69:269-81.
Langston JW, Widner H, Goetz CG, Brooks D, Fahn S, Freeman T, et al
. Core assessment program for intracerebral transplantations (CAPIT). Mov Disord 1992;7:2-13.
Burton EJ, McKeith IG, Burn DJ, Williams ED, O’Brien JT Cerebral atrophy in Parkinson’s disease with and without dementia: A comparison with Alzheimer’s disease, dementia with Lewy bodies and controls. Brain 2004;127:791-800.
Karagulle Kendi AT, Lehericy S, Luciana M, Ugurbil K, Tuite P Altered diffusion in the frontal lobe in Parkinson disease. AJNR Am J Neuroradiol 2008;29:501-5.
Samuel M, Ceballos-Baumann AO, Blin J, Uema T, Boecker H, Passingham RE, et al
. Evidence for lateral premotor and parietal overactivity in Parkinson’s disease during sequential and bimanual movements. A PET study. Brain 1997;120:963-76.
Tanji J, Hoshi E Behavioral planning in the prefrontal cortex. Curr Opin Neurobiol 2001;11:164-70.
Duffau H, Tzourio N, Caparros-Lefebvre D, Parker F, Mazoyer B Tremor and voluntary repetitive movement in Parkinson’s disease: Comparison before and after L-dopa with positron emission tomography. Exp Brain Res 1996;107:453-62.
Akkal D, Dum RP, Strick PL Supplementary motor area and presupplementary motor area: Targets of basal ganglia and cerebellar output. J Neurosci 2007;27:10659-73.
Rizzolatti G, Luppino G The cortical motor system. Neuron 2001;31:889-901.
Pochon JB, Levy R, Poline JB, Crozier S, Lehéricy S, Pillon B, et al
. The role of dorsolateral prefrontal cortex in the preparation of forthcoming actions: An FMRI study. Cereb Cortex 2001;11:260-6.
Playford ED, Jenkins IH, Passingham RE, Nutt J, Frackowiak RS, Brooks DJ Impaired mesial frontal and putamen activation in Parkinson’s disease: A positron emission tomography study. Ann Neurol 1992;32:151-61.
Fukuda M, Barnes A, Simon ES, Holmes A, Dhawan V, Giladi N, et al
. Thalamic stimulation for Parkinsonian tremor: Correlation between regional cerebral blood flow and physiological tremor characteristics. Neuroimage 2004;21:608-15.
Naros G, Grimm F, Weiss D, Gharabaghi A Directional communication during movement execution interferes with tremor in Parkinson’s disease. Mov Disord 2018;33:251-61.
Muthuraman M, Raethjen J, Koirala N, Anwar AR, Mideksa KG, Elble R, et al
. Cerebello-cortical network fingerprints differ between essential, Parkinson’s and mimicked tremors. Brain 2018;141:1770-81.
Nambu A Seven problems on the basal ganglia. Curr Opin Neurobiol 2008;18:595-604.
Nambu A, Tokuno H, Takada M Functional significance of the cortico-subthalamo-pallidal “hyperdirect” pathway. Neurosci Res 2002;43:111-7.
[Table 1], [Table 2], [Table 3]