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RESEARCH—HUMAN—CLINICAL STUDIES
Modulation of Nigrofugal and Pallidofugal Pathways
in Deep Brain Stimulation for Parkinson Disease
Josue M. Avecillas-Chasin,
MD, PhD∗
Christopher R. Honey, MD,
DPhil‡
∗Department of Neurosurgery, Neurolo-
gical Institute, Cleveland Clinic, Clevel-
and, Ohio; ‡Department of Surgery,
Division of Neurosurgery, University of
British Columbia, Vancouver, Canada
This study was presented as an oral
presentation on September 28, 2018 at
the XXIIIrd European Society of
Stereotactic and Functional
Neurosurgery (ESSFN) Congress in
Edinburgh, United Kingdom.
Correspondence:
Josue M. Avecillas-Chasin, MD, PhD,
Department of Neurosurgery,
Neurological Institute,
Cleveland Clinic,
9500 Euclid Ave,
Cleveland, OH 44195, USA.
Email: josueavecillas@hotmail.com
Received, June 6, 2019.
Accepted, October 13, 2019.
Copyright C
2019 by the
Congress of Neurological Surgeons
BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a well-
established surgical therapy for patients with Parkinson disease (PD).
OBJECTIVE: To dene the role of adjacent white matter stimulation in the eectiveness of
STN-DBS.
METHODS: We retrospectively evaluated 43 patients with PD who received bilateral
STN-DBS. The volumes of activated tissue were analyzed to obtain signicant stimu-
lation clusters predictive of 4 clinical outcomes: improvements in bradykinesia, rigidity,
tremor, and reduction of dopaminergic medication. Tractography of the nigrofugal and
pallidofugal pathways was performed. The signicant clusters were used to calculate the
involvement of the nigrofugal and pallidofugal pathways and the STN.
RESULTS: The clusters predictive of rigidity and tremor improvement were dorsal to the
STN with most of the clusters outside of the STN. These clusters preferentially involved the
pallidofugal pathways. The cluster predictive of bradykinesia improvement was located in
the central part of the STN with an extension outside of the STN. The cluster predictive
of dopaminergic medication reduction was located ventrolateral and caudal to the STN.
These clusters preferentially involved the nigrofugal pathways.
CONCLUSION: Improvements in rigidity and tremor mainly involved the pallidofugal
pathways dorsal to the STN. Improvement in bradykinesia mainly involved the central
part of the STN and the nigrofugal pathways ventrolateral to the STN. Maximal reduction
in dopaminergic medication following STN-DBS was associated with an exclusive
involvement of the nigrofugal pathways.
KEY WORDS: Nigrostriatal, Parkinson disease, Subthalamic nucleus, Deep brain stimulation, Tractography,
Movement disorders, Basal ganglia, Pallidothalamic
Neurosurgery 0:1–11, 2019 DOI:10.1093/neuros/nyz544 www.neurosurgery-online.com
Deep brain stimulation (DBS) of the
subthalamic nucleus (STN) is a well-
established surgical therapy for patients
with Parkinson disease (PD). Current research
suggests that STN-DBS may inhibit or disrupt
aberrant signals between the cortex and the
basal ganglia.1However, this theory cannot fully
explain the diversity of clinical effects of STN-
ABBREVIATIONS: ANT, advance normalization tool; AC-PC, anterior commissure-posterior commissure; ALIC,
anterior limb of the internal capsule; CT, computed tomography; DBS, deep brain stimulation; DWI, diusion-
weighted imaging; GPi, globus pallidus interna; HARDI, high angular resolution diusion imaging; IC, internal
capsule; LEDD, levodopa equivalent dose daily; MRI, magnetic resonance imaging; MNI, Montreal Neuro-
logical Institute; PD, Parkinson disease; PSA, posterior subthalamic area; ROI, region of interest; SIFT, Spherical-
deconvolution Informed Filtering of Tractograms; SN, substantia nigra; STN, subthalamic nucleus; 3D,
3-dimensional; UPDRS, Unied Parkinson Disease Rating Scale; VAT, volume of activated tissue
Supplemental digital content is available for this article at www.neurosurgery-online.com.
DBS in patients with PD. Stimulation of the
adjacent white matter pathways of the basal
ganglia may, therefore, also account for some
of the effects of STN-DBS.2,3The pallidofugal
pathways are described as a connection of the
pallidum with the thalamus, STN, pedunculo-
pontine nucleus, and substantia nigra (SN).4The
nigrofugal pathways (also known as striatofugal
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AVECILLAS-CHASIN AND HONEY
TAB LE 1 . Clinical and Demographic Data of Our Parkinson Disease
(PD) Patient Cohort
Clinical features PD patients
Age: mean ±SD, yr 58 ±10
Gender: men, % 70
Disease duration: mean ±SD, yr 10 ±3
Side of disease onset: left, % 44
UPDRS III OFF medication: mean ±SD, baseline 42 ±11
Levodopa response: mean percentage of
improvement in UPDRS III ±SD, %
73 ±13
SD, standard deviation; yr, years.
or striatonigral) are described as connections of the SN with the
striatum and pallidum.5-7In this study, we investigated the role
of these pathways in the improvement in PD symptoms by STN-
DBS. To this aim, we used the volumes of activated tissue (VAT)
of a cohort of PD patients receiving STN-DBS to find “hotspots”
for each motor outcome. We then calculated the involvement
of the pallidofugal and nigrofugal pathways or the STN by the
hotspot of each motor outcome.
METHODS
Patients
We retrospectively analyzed 55 patients with PD who received
bilateral STN-DBS from 2007 to 2016. Of these, 12 patients were
excluded because of image acquisition issues or a lack of formal
1-yr evaluation (n =43). All patients were deemed surgical candi-
dates for STN-DBS by a movement disorder neurologist, functional
neurosurgeon, and DBS nurses.8,9The patients were videotaped and
evaluated with the Unified Parkinson Disease Rating Scale (UPDRS) III
OFF/ON medication and cognitive assessment. We recorded the clinical
and demographic variables described in Table 1. The ethics board at our
center approved the study (H18-00893). All patients provided written
informed consent for publication.
DBS Surgery and Postoperative Evaluation
The preoperative images were uploaded to the Framelink software
(Medtronic, Dublin, Ireland) and coregistered. We first identified the
anterior commissure-posterior commissure (AC-PC) line and selected
the coordinates of the STN based on the midcommissural point (anterior
–3, lateral 11, and vertical –4). We then used the T2 to adjust the target
for each patient’s unique anatomy (at the anterior border of the red
nucleus and just within the hypointensity of the STN). The entry point
was selected to avoid a trajectory through blood vessels, sulci, ventricles,
or the caudate. The coordinates were loaded onto a cosman roberts wells
stereotactic frame (Radionics, Burlington, Massachusetts). Two frontal
burr holes were performed under local anesthesia, and 3 microelectrodes
(FHC MME, Bowdoin, Maine) were lowered down the trajectory using
a microtargeting drive (Medtronic, Dublin, Ireland). After mapping the
characteristic firing of the STN with microelectrode recording, macros-
timulation was performed. Our criteria for lead implantation were as
follows: rigidity improvement at ≤1 mA and side effects at >3mA.After
both leads were implanted, the patients underwent general anesthesia
and the pulse generator was implanted. In order to verify the correct
implantation of the leads, all patients underwent stereological computed
tomography (CT) scan during the next 24 h after surgery. Six weeks
after surgery, the initial programming began with a monopolar review of
each contact (pulse width: 60 μs, frequency: 130 Hz). The contacts with
the largest therapeutic window were selected for chronic stimulation.
Follow-up visits with titration of stimulation and medication occurred
every week until stable and then every 6 mo. We used the 1-yr follow-
up to determine the stimulation parameters, levodopa equivalent dose
daily (LEDD) reduction, UPDRS OFF medications, and OFF medica-
tions/ON stimulation to measure improvements in rigidity, bradyki-
nesia, and tremor. The subscores were determined as follows: bradyki-
nesia (UPDRS III items 19, 23-26, and 31), rigidity (21a and 22b-22e),
and tremor (20a-e and 21a-b).
VAT Generation
The preoperative magnetic resonance imaging (MRI) and postop-
erative CT scan (slice thickness 1 mm) were loaded into the Lead-
DBS software.10 These images were coregistered using advance normal-
ization tools (ANTs) and a 3-dimensional (3D) slicer.11,12 These images
were then normalized to the Montreal Neurological Institute (MNI)
stereotactic space using ANTs and statistical parametric mapping.13
When necessary, brain-shift correction was applied with the Lead-DBS
adaption of a previously reported method.14 Coregistration and transfor-
mation results were carefully checked for errors, and these were repeated
or refined if needed. The electrode placement was reconstructed with
automated prelocalization methods using either the PaCer algorithm15 or
the TRAC/CORE approach.10 After this automated step, the electrode
reconstruction was manually adjusted in the “manual reconstruction”
interface of the software16 as follows. The virtual reconstruction of the
electrodes was compared with the electrode artifact in the postoperative
CT scan (after an adjustment of the window level to better appreciate
the shape of the electrode’s contacts). We then adjusted the virtual recon-
struction of the electrode in each of the 3 dimensions. The aim was to
have reconstructions with precise alignments with the contact’s artifact
in the postoperative CT scan.
We generated the VATs of all patients using the finite-element
method.17,18 These methods were implemented in Lead-DBS using a
novel open-source pipeline16-21 and are described in detail in Horn
et al.16,22 ,23 In short, a 4-compartment model of the area around the
electrode is constructed based on the electrode itself (insulating and
conducting parts) and the gray and white matter of the brain. The regions
within this compartment were defined as follows: the subcortical gray
matter structures were defined by the DISTAL atlas,23 the electrode’s
parts were defined by the virtual electrode models provided by the
software, and the regions not covered by the electrode or gray matter were
modeled as isotropic white matter. The anisotropic conductivity values
for gray and white matter were defined as σ=0.33 and 0.14 S/mm,
respectively. The electric field threshold was set to e =0.2 V/mm, and
the resultant binary VAT was obtained by thresholding the electrical field
strength at the specific voltage and pulse width used for each stimulation
setting.
Tractography Analysis
We obtained the imaging data of 43 age- and gender-
matched PD subjects from the neuroimaging data repository
Parkinson’s Progression Markers Initiative. The data consisted of
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NIGROFUGAL AND PALLIDOFUGAL PATHWAYS IN STN-DBS
FIGURE 1. Pipeline of the study. A, Structural population template based on T1-weighted images of 43 PD patients. The basal ganglia structures were
obtained using the FIRST algorithm on FMRIB Software Library. The STN and SN were transformed from the MNI stereotactic space to the template
space. B, These structures were then linearly registered to the diffusion template space. C, Using a diffusion template based on DWI of 43 PD patients,
the nigrofugal and pallidofugal pathways were traced based on the neuroanatomy of these pathways (see Methods and Methods,Supplemental
Digital Content). D, Conversion of the tracts into probabilistic maps. E, Refinement of the pathways using the probabilistic information of the
map at 90%. F, Whole-brain tractography with 30 million streamlines. G, Combination of the whole-brain tractogram with the nigrofugal and
pallidofugal pathways. H, Filtering of the combined tractogram using the SIFT algorithm. I, Extraction of the pathways of interest after filtering using
the same ROIs used for the generation of the pathway. Finally, the pathways are normalized into MNI space for further analysis.
high-resolution, 3T T1-weighted, and high angular resolution
diffusion imaging (HARDI60); the acquisition protocol is available at
https://www.ppmi-info.org/study-design/research-documents-and-sops/
(for preprocessing details, see Methods,Supplemental Digital
Content). We reconstructed the nigrofugal and pallidofugal pathways
on the PD diffusion template using regions of interest (ROIs) based
on neuroanatomic descriptions.2,6,24-31 The nigrofugal pathway was
generated as follows: seed ROI: SN; target ROIs: putamen, caudate,
and pallidum; and exclusion ROIs: retrolenticular internal capsule (IC),
anterior limb of the IC (ALIC), and STN. The pallidofugal pathway was
generated as follows: seed ROI: pallidum; target ROIs: thalamus and
SN; and exclusion ROIs: retrolenticular IC, ALIC, and putamen. For the
pallidofugal pathway, we also included the white matter located dorsal
to the STN to take into account its known trajectory (see Methods,
Supplemental Digital Content). Since the pallidofugal pathways also
include the pallidosubthalamic bundle, we used the STN ROI to do
“inverse masking”; this way, the streamlines terminating in the STN
would be truncated, but not discarded.32 Several freely available atlases
were used to obtain the ROIs for this study.33 -39 A total of 100 000
streamlines were generated for each pathway. Then, the pathways were
refined using thresholding, masking, and filtering using the Spherical-
deconvolution Informed Filtering of Tractograms (SIFT) algorithm.40
Finally, we normalized the pathways to the MNI stereotactic space
for further analysis (see Methods,Supplemental Digital Content for
details) (Figure 1).
Statistical Methods
The 1-yr follow-up outcome of the clinical variables (UPDRS III
and LEDD) was compared with the baseline using the 2-tailed paired
t-test. Significance level was set at P<.05, and we used SPSS 22.0
(IBM, Armonk, New York). Four clinical outcomes were defined as
follows: improvement in bradykinesia, rigidity, tremor, and LEDD
reduction. The percentage of improvement was defined based on the
relative change comparing the baseline scores and the 1-yr scores of each
outcome for each body side. The VATs of the patients were associated
with the corresponding contralateral percentage of improvement in
bradykinesia, rigidity, and tremor. We also calculated the percentage
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AVECILLAS-CHASIN AND HONEY
of LEDD reduction using the preoperative and postoperative dosages,
and these percentages were assigned to both VATs of the same patient.
The VATs of the right side were flipped to the left, and all VATs
(N =86) were merged into a 4D file for further analysis.36,41 We
performed nonparametric permutation inference42 on the VATs to find
significant stimulation clusters predictive of improvement in bradyki-
nesia, rigidity, or tremor, and LEDD reduction (see Methods,Supple-
mental Digital Content). Then, the significant clusters were used to
calculate the involvement of the pathways and the STN in the standard
MNI space. We defined “involvement of the pathways” as the number of
streamlines (connectivity metric) of each pathway (nigrofugal and pallid-
ofugal) intersecting the cluster mass.43 We defined “involvement of the
STN” as the fraction of the cluster mass overlapping the STN.44,45
RESULTS
The clinical and demographic data of our PD patients are
provided in Tables 1and 2. There was a significant difference
in the total UPDRS III after surgery (P=.000) compared to
baseline. Furthermore, the LEDD was also significantly reduced
after surgery (P=.000) at the 1-yr follow-up.
Nigrofugal and Pallidofugal Pathways
The tractography results showed that the nigrofugal pathway
travels in a dorsolateral direction from the SN to the pallidum
and striatum. The pathway crosses the IC in a mediolateral and
inferosuperior direction. While traversing the IC, one segment
enters the dorsal part of the pallidum to terminate in the dorsal
putamen, and the other segment adopts a medial direction to
terminate in the caudate. In its origin, this pathway is located
ventrolateral to the STN, adopting a posterolateral position as the
pathway enters in the IC (Figures 2and 3). On the other hand,
we found 3 segments of the pallidofugal pathway. The dorsal
segment (lenticular fasciculus) originates from the dorsal part of
the pallidum and traverses the IC in a lateromedial and anteropos-
terior direction to reach the area dorsal to the STN. The interme-
diate segment (pallidosubthalamic tract) has the same trajectory
as the dorsal segment, but instead of going dorsal to the STN,
these fibers travel caudal and ventral to the dorsal division to end
in the lateral part of the STN (Figure 2D, white arrow). The
ventral segment (ansa lenticularis) originates in the most ventral
part of the pallidum and travels ventromedially below the ALIC
and curves around the anterior border of the cerebral peduncle. In
the prerubral area, this pathway turns laterally to join the dorsal
segment and terminates in the thalamus (thalamic fascicle). Some
of these fibers surround medially the STN to connect with the SN
and to continue caudally to lower levels of the brainstem (fasci-
culus Q of Sano or pallidotegmental tract) (Figures 2and 3).
Stimulation Clusters Predictive of Clinical Outcomes
The coordinates of the local maxima of the stimulation clusters
are reported in the MNI and AC-PC space46 (Table 3). The
local maxima are defined as being the point with the highest
value compared with all immediate neighbors in a given cluster.
Figure 5shows the relative involvement of each anatomic
structure by each of the significant clusters. The stimulation
cluster predictive of rigidity improvement was located dorsal to
the STN with 13% of the cluster mass within the STN. The
cluster predictive of tremor improvement was also located dorsal
to the STN with 28% of the cluster mass within the STN. These
clusters preferentially involved the pallidofugal pathways with
2983 and 1126 streamlines, respectively. The cluster predictive of
bradykinesia improvement encompassed the STN with a ventro-
lateral extension outside of the nucleus. Thirty-five percent of the
cluster mass was within the central part of the STN. The cluster
predictive of LEDD reduction was located outside of the STN
ventrolateral and caudal to the nucleus. These clusters prefer-
entially involved the nigrofugal pathways with 1670 and 2991
streamlines, respectively (Figures 4and 5).
DISCUSSION
Key Results
The STN is located in a strategic position, tightly surrounded
by white matter tracts related to the input and output of
the basal ganglia.24,47 In this work, we found that the pallid-
ofugal pathways were mainly located dorsal to the STN,
and the nigrofugal pathways were located ventrolateral to the
STN. Therapeutic stimulation from DBS electrodes traversing
this area could affect the nucleus and/or these white matter
tracts. In this study, we correlated various clinical benefits in
PD patients with the degree of stimulation involving these
white matter pathways and the STN. Voxel-based statistical
analysis of the DBS electrical field was used to identify statis-
tically significant clusters (hotspots) for each clinical outcome
within the whole stimulated area.41 The significant cluster for
tremor improvement was dorsal, anterior, and medial to the
STN, and the cluster for rigidity improvement was dorsal and
lateral to the STN. The significant cluster for bradykinesia
improvement was predominantly within the STN with a ventro-
lateral extension. The significant cluster for LEDD reduction
was found ventrolateral to the STN (Figure 4). The pallid-
ofugal pathways were mostly involved by the clusters predictive
of maximal improvements in rigidity and tremor. The nigrofugal
pathways were mainly involved by the clusters predictive of
maximal reduction of dopaminergic medication and bradykinesia
improvement. The STN was mainly involved by the clusters
predictive of maximal improvements in bradykinesia and tremor
(Figure 5).
In this study, we replicated the previously described
neuroanatomy of these pathways.2,4,6,24,25 ,30 Although these
pathways are often referred to as “fugal,” there is evidence
showing reciprocal connectivity between the structures connected
by these pathways.7,48-51 Most of the pallidofugal axons
originate in the Globus pallidus interna (GPi) and project
to the ventral/centromedian thalamus, SN (pars reticulata),
and pedunculopontine tegmental nucleus. Moreover, anatomic
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NIGROFUGAL AND PALLIDOFUGAL PATHWAYS IN STN-DBS
TAB LE 2 . Clinical Data of Our PD Surgical Cohort (Cont.)
Cases
Preop
UPDRS III
Postop
UPDRS III
Preop
LEDD
Postop
LEDD
Asym
index
Parameters
(L)
Parameters
(R)
Coordinates
(L)
Coordinates
(R)
138 18 900 400 51–C/3.5/130/90 1–2+/2.5/130/60 –13/–3/–3 11/–3/–1
2 59 24 1100 350 –2 2–C/2.3/130/90 1+2–/2.4/130/90 –13/–3/–9 13/–4/–9
345 39 1995 1150 –1 0–C/2.1/130/90 0–1+/2.1/130/120 –12/–3/–6 10/–1/–5
4 35 30 2100 800 –4 3–C+/4.3/130/90 1–C+/4.2/130/60 –12/–2/–2 11/–2/–5
532 13 1729 900 03–C+/3.2/130/60 2–C+/2.5/130/60 –11/–4/–1 11/–3/–2
6 62 37 1596 790 1 2–C+/3.8/185/90 2–C+/4.1/185/60 –13/1/–3 13/0/–3
746 19 1700 850 –3 2–C+/3.8/130/60 2–C+/3.8/130/60 –13/0/–2 11/–1/–4
8 27 25 1165 600 7 2–C+/3/130/60 2–C+/3/130/60 –14/–2/–2 10/–1/–4
935 28 2350 1650 –1 2–C+/3.6/185/60 1+2–/4.3/185/90 –15/1/–1 12/–2/–1
10 42 17 1850 1000 –6 2–3+/2.8/130/120 1+2–/4.3/130/90 –11/–1/–2 11/–4/–5
11 42 27 1250 650 –5 1+2–/2.3/185/90 2+3–/3.5/185/90 –13/–2/–3 10/–1/–4
12 37 16 825 425 –6 2+3–/4.2/130/60 1–C+/4.3/130/60 –12/0/–2 13/–2/–4
13 20 18 2525 2200 1 1+2–/4.1/185/60 1+2–/3.6/185/60 –10/–2–3 10/–2/–2
14 52 12 2603 1250 0 0+3–/4.3/130/120 0+3–/3.6/130/120 –11/–1/–4 11/–1/–5
15 52 28 1400 450 4 1+2–/4/185/90 1+2–/4/185/60 –11/0/–2 12/0/–5
16 51 20 2061.5 900 0 0+1–2–/4/130/90 0+1–2–3.5/130/120 –11/–3/–4 9/–1/–5
17 30 22 1550 1150 –7 1–3+/3.5//150/120 1–C+/2.7/150/120 –10/–4/–5 10/–2/–3
18 66 13 765 264 9 1–C+/2.7/185/90 1–C+/2.5/185/90 –10/–1/–5 11/–2/–4
19 50 15 1400 1200 7 2–3–/4/185/90 1+2–/3.7/185/60 –9/1/–6 12/–1/6
20 48 26 1050 750 16 0+1–/4.2/185/90 3–C+/1.9/185/60 –13/0/–5 11/2/1
21 48 17 2550 250 –1 2–3+/4.6/185/90 3–C+/3.6/185/60 –13/–1/–2 11/–1/0
22 36 6 1550 825 –11 1–C+/2.2/130/60 1+2–/2.9/130/60 –10/–1/–5 10/–3/–4
23 74 24 2100 1300 –1 0+1–/4/185/90 2–C+/3.3/185/90 –10/–3/–6 10/–1/–4
24 34 15 1660 1400 –2 2+3–/3.4/185/60 2–3+/3.5/185/120 –13/–3/–1 11/0/–2
25 51 32840 0–2 1–C+/3.2/130/60 2–C+/2.1/130/60 –12/–1/–4 12/2/0
26 26 23 2100 1050 –1 2–C+/2.1/130/60 1–C+/2.1/130/60 –14/–2/–3 12/–2/–4
27 53 31 2295.5 450 01–C+/3.3/130/90 1–C+/3.3/130/60 –11/1/–5 11/0/–4
28 43 22 3310.5 1625 –1 2–C+/1.6/130/60 3–C+/3.6/130/60 –15/–2/0 12/1/0
29 41 20 659.25 150 –5 3–C+/3.2/180/90 2–3–/3.8/180/60 –13/0/1 8/1/0
30 38 17 1350 800 1 0–C+/3.1/130/60 1–C+/1.5/130/60 –13/–2/–1 11/–1/–4
31 24 91900 500 22–C+/3.5/185/60 1–C+/3.5/185/60 –11/–3/-4 11/–1/–5
32 51 17 1250 300 –10 1–C+/3.6/130/90 1–C+/3.8/130/60 –11/–1/–3 12/0/–3
33 37 23 1460 870 11–C+/4.6/130/90 1–C+/4.4/130/90 –10/2/–2 10/3/–3
34 38 48 2029 1240 –7 1–C+/2/130/60 1–C+/2/130/60 –11/0–5 12/–2/–5
35 69 19 2005 600 02–C+/2.4/130/60 2–C+/1.9/130/60 –11/–1/–3 12/0/–3
36 56 30 600 0 –9 0+1–/3/185/90 0+1–/3.5/185/90 –10/–1/–8 10/–1/–8
37 40 14 800 500 12–C+/3.7/185/90 1–2+/3.0/185/90 –13/0/–4 9/–2/–4
38 24 23 940 680 –4 1–C+/3.2/130/60 0+1–4.1/130/60 –15/–2/–5 12/–2/–6
39 33 27 1600 600 –2 2–C+/1.8/130/60 1–C+/1.8/130/60 –13/–3/–6 11/–1/–7
40 38 20 1996 1200 5 2–C+/4.3/185/60 1–C+/3.5/185/60 –9/0/–4 13/–1/–4
41 51 17 1625 800 –1 1–C+/3/130/60 1–C+/2.5/130/60 –12/–2/–2 12/–3/–4
42 43 8 2650 825 –2 1–C+/2.2/185/90 1–C+/2.4/185/90 –10/0/–4 12/1/–5
43 34 81300 1120 43–C+/3.5/130/60 3–C+/3.3/130/60 –12/–3/–2 14/0/–1
Preop, preoperative; postop, postoperative; LEDD, levodopa equivalent dose daily; Asym index, asymmetry index: the asymmetry index was calculated as the absolute value
of the right minus left-sided scores from the UPDRS motor score. A UPDRS motor asymmetry index of at least 2 points dierence is generally used as the threshold for
dening clinical asymmetry. Positive values indicate right-sided asymmetry, and negative values indicate left-sided asymmetry. Coordinates: AC-PC space x/y/z. Parameters: active
contacts/voltage/Hz/pulse width. L, left; R, right.
evidence has shown that the pallidosubthalamic tract originates
in the globus pallidus externa.2,4The nigrofugal and pallidofugal
pathways have been classically described as “the fields of Sano”
or “the comb system of Edinger” because of their appearance as
they go through the IC.28,52 ,53 Several authors have reported that
effective STN-DBS also activates some fibers of the IC.3,54-56
Because the nigrofugal and pallidofugal fibers travel through the
IC, it is possible that these pathways (rather than the pyramidal
or frontopontine pathways) are activated by effective STN-DBS.
Other studies have demonstrated that therapeutic stimulation
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AVECILLAS-CHASIN AND HONEY
FIGURE 2. Nigrofugal and pallidofugal pathways (yellow fibers). A, The nigrofugal pathway (caudate segment) traverses the internal capsule and turns
medially to reach the caudate nucleus (black asterisk). STN (white asterisk). B, Axial image at the most ventral part of the STN (asterisk). The nigrofugal
pathways are located ventrolateral to the STN. SN (black arrow). C, Coronal image showing the trajectory of the nigrofugal pathways through the most dorsal
area of the pallidum and putamen. D, The dorsal segment of the pallidofugal pathways (lenticular fascicle) originating in the dorsomedial part of the pallidum
traversing the internal capsule to reach the area dorsal to the STN (black arrows), The intermediate segment (pallidosubthalamic) terminates in the lateral
part of the STN (white arrow). E, The ventral segment (ansa lenticularis) travels below the internal capsule and turns around the cerebral peduncle traveling
medial and caudal to the STN to connect with the SN (white arrows) and also continue caudally to lower levels of the brainstem (pallidotegmental) (black
arrows). F, Some of the fibers of the ventral segment turns dorsolateral to join the dorsal segment and terminate in the thalamus (arrows). The background
image was obtained from the BigBrain project (https://bigbrain.loris.ca/main.php),85 under CC-BY-NC-SA 4.0.
FIGURE 3. Artistic illustration of the nigrofugal and pallidofugal pathways. A,Frontview;B, top view. The nigrofugal pathways (green) originate
in the SN (navy blue) and travel through the internal capsule (white) to reach the dorsal part of the pallidum (brown) and connect with the putamen
(dark green) and caudate (gray). B, The pallidofugal pathways (purple). The dorsal segment originates in the dorsomedial part of the pallidum,
traverses the internal capsule, and travels dorsal to the STN (blue) to end in the most ventral part of the thalamus. The ventral segment Btravels
below the anterior limb of the internal capsule to reach lower levels of the brainstem. Some fibers join the dorsal segment to end in the thalamus. C
Vicky Earle, Medical Illustrator, used with permission.
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NIGROFUGAL AND PALLIDOFUGAL PATHWAYS IN STN-DBS
TAB LE 3 . Coordinates (mm) of the Local Maxima of the Predictive Clusters of the 4 Outcomes in MNI and AC-PC Space
Local maxima coordinates
MNI space AC-PC space
Clusters X Y Z X Y Z
Rigidity –14.5 (–10/–17.5) –13.5 (–9.7/–17.6) –3 (–1.8/–6.7) –14 (–10/–17) –2 (2/–6) 1 (2/–3)
Tremor –11.5 (–10/–13.6) –12 (–9.5/–15.7) –5.5 (2.7/–6.6) –11 (–10/–14) 0 (1.5/–5) –1 (1/–3)
Bradykinesia –13.4 (–11.5/–16.5) –11.5 (–9.7/–14.5) –7.5 (–4.7/–8.8) –13 (–12/–17) 1 (2/–3) –3 (1/–5)
LEDD –14 (–10.4/–15.8) –14 (–11.2/–17.3) –11 (–8.3/–16.4) –14 (–10/–16) –1 (1/–6) –7 (–5/–13)
AC-PC, anterior commissure-posterior commissure; LEDD, levodopa equivalent dose daily; MNI, Montreal Neurological Institute.
The ranges of coordinates (mm) of the whole signicant cluster are shown in parentheses.
FIGURE 4. STN-DBS stimulation clusters predictive of motor outcomes. A, Coronal and axial view of the cluster predictive of rigidity improvement located
in the dorsal subthalamic area. B, Coronal and axial view of the cluster predictive of tremor also located in the dorsal subthalamic area slightly medial to
the STN and anterior to the rigidity cluster (axial view). C, Coronal and axial view of the cluster predictive of bradykinesia located in the central part of
the STN (axial view) with ventrolateral extension (coronal view). D, Coronal and axial view of the cluster predictive of LEDD reduction located ventral
and caudal to the STN. The background image was obtained from the BigBrain project (https://bigbrain.loris.ca/main.php),85 under CC-BY-NC-SA 4.0.
E, Color bar for reference.
may also activate the lenticular fasciculus.57 Our work corrobo-
rates these findings but adds the involvement of the pallidofugal
pathway (dorsal to the STN), particularly for the amelioration
of rigidity and tremor, and the nigrofugal pathway (ventral to
the STN) for the amelioration of bradykinesia. Similar findings
have been described in GPi-DBS, but in opposite directions,
stimulation of the most ventral part of the pallidum produces
an “anti-levodopa effect” on akinesia associated with improve-
ments in rigidity and dyskineisas.58 In contrast, stimulation of
the dorsal part of the pallidum produces a “pro-levodopa effect”
with improvements in motor fluctuations and bradykinesia.55,58
In the pallidal area, the pallidofugal pathways originate ventral
and medial to the GPi, and the nigrofugal pathways travel dorsal
to the GPi (Figure 3).
Interpretation/Generalizability
Differential clinical effects of DBS have been demonstrated
with both STN and pallidal stimulation. During STN-DBS, in
some cases, there is an improvement in rigidity at the expense of
worsening bradykinesia.54 Some authors have also reported that
different spots within the STN were associated with improve-
ments in the 3 cardinal symptoms of PD.41,59 These different
or competing benefits may follow from the fact that the pallid-
ofugal pathways travel dorsal to the STN and benefit rigidity
and tremor, whereas the nigrofugal pathways travel ventral to
the STN and benefit bradykinesia. The effect on medications
is also different between targets. Higher doses of levodopa are
often required after ventral pallidal stimulation,60 whereas lower
doses are typically needed following STN-DBS. The stimulation
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AVECILLAS-CHASIN AND HONEY
FIGURE 5. Bar plots showing the degree of involvement of the neuroanatomical structures. A, The nigrofugal pathways were largely involved by the
clusters predictive of LEDD reduction and bradykinesia improvement. B, The pallidofugal pathways were mainly involved by the cluster predictive
of rigidity, followed by the cluster predictive of tremor. C, The STN was mainly involved by the cluster predictive of bradykinesia, followed by
tremor with little involvement of rigidity and no involvement of LEDD reduction.
site resulting in maximal reduction in dopaminergic medication
is outside of the STN involving the nigrofugal pathways. Other
authors have also found that ventral and lateral stimulation
in the subthalamic area is associated with maximal reduction
of LEDD and motor benefit.61,62 Since reduction of LEDD
is a function of bradykinesia improvement, these findings also
explain why the improvement in bradykinesia also involved
the nigrofugal pathways more than the other motor outcomes.
Although there is no definitive answer for these opposite effects,
based on our findings, we can speculate that dorsal stimu-
lation in the subthalamic area would improve rigidity and
tremor by modulating the pallidal efferent to the thalamus. Also,
ventrolateral stimulation would improve bradykinesia and reduce
the dopaminergic medication needs by modulating the nigral
connections with the striatum.63-66 We postulate that modulation
of nigrofugal pathways would increase the facilitation of the basal
ganglia for movement execution67 and modulation of the pallid-
ofugal pathways would increase the inhibition of undesired motor
activity.68,69 This concept would also explain why dyskinesias can
be improved by dorsal stimulation in the subthalamic area.70,71
Given the potential influence of the electrical stimulation on
downstream targets of these pathways, these concepts need to
be confirmed with neurophysiological studies investigating the
response of those targets to effective STN-DBS.
Some authors have found the beneficial effects of STN-DBS on
PD symptoms may involve other structures.72-75 Recent evidence
suggests that stimulation of the central part of the STN receiving
hyperdirect projections from the supplementary motor area corre-
lates with bradykinesia improvement, but not with other motor
outcomes.45 Inthepresentwork,wealsofoundthatthecentral
STN was mostly involved by the cluster predictive of bradykinesia
improvement. The modulation of the cerebellothalamic pathway
has also been implicated in tremor reduction for PD patients.76-78
The pallidothalamic and cerebellothalamic pathways travel dorsal
to the STN, and the cerebellothalamic is located in the posterior
subthalamic area (PSA), whereas the pallidothalamic is anterior
to this pathway.79 In our cohort, the cluster predictive for
tremor improvement was located in the anteromedial part of the
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NIGROFUGAL AND PALLIDOFUGAL PATHWAYS IN STN-DBS
subthalamic area involving the pallidofugal pathways. Our
targeting strategy did not include the PSA, and therefore, we were
not able to correlate the stimulation of this area with the motor
outcomes. Further tractography studies would be necessary to
define the role of these 2 pathways in tremor reduction.
Limitations
We used constrained spherical deconvolution-probabilistic
tractography that reconstructs pathways with complex fiber orien-
tations.80 However, it is also well known the existence of “false-
positives connections” from spurious peaks in the fiber orien-
tation distributions.81,82 In order to minimize false-positive
connections, we employed 3 sequential strategies as follows.
(1) We first performed targeted tractography based on the
known neuroanatomy of these pathways. (2) We then refined
the pathway based on the probabilistic information of the
tractogram generated. (3) Finally, we filtered the pathways to fit
the streamline reconstruction with the water diffusion measured
in every voxel. Although our approach is time-consuming, we
believe that the consistent application of neuroanatomy prior to
the pathway reconstruction would highly enhance the tractog-
raphy results.
The subthalamic area poses the following challenges for
neuroimaging analyses: (1) the STN and SN are close together
with no clear borders to differentiate each other. (2) There
are white matter pathways with the same magnetic suscepti-
bility contrast as the STN and SN.52 To account for this, we
obtained the STN and SN from an unbiased multitissue contrast
population-averaged template of 25 PD patients.39 This strategy
will minimize the bias of manual segmentation and also provide
a disease-specific anatomic atlas obtained by the differences in
tissue contrast from different MRI sequences. Another limitation
is the use of diffusion-weighted imaging (DWI) of other PD
subjects. However, this limitation is overcome by the practical
advantage of analyzing large number of patients without the need
of individually collected clinically expensive high-quality DWI
data. Several works have demonstrated the utility of this approach
to analyze the role of brain connectivity in a large cohort of DBS
patients.16,22 Finally, The VAT models are widely used in clinical
and research practices because of the easy interpretation and avail-
ability.83-84 Despite being a limited model, when the VAT is used
to model typical stimulation parameters with pathways such as
the IC, the model can minimize the error in the predictions.18,43
In order to minimize potential errors in the interpretation of the
results, we first generated the pathways based on neuroanatomy
and then we correlated the cluster predictive of a given motor
outcome.
CONCLUSION
In our patients with PD receiving DBS, the “hotspots”
for different motor outcomes and dopaminergic medication
reduction were found in a dorsoventral gradient in the subtha-
lamic area. Improvement in rigidity and tremor mainly involved
the pallidofugal pathways dorsal to the STN. Improvement in
bradykinesia mainly involved the central part of the STN and the
nigrofugal pathways ventrolateral to the STN. Maximal reduction
in dopaminergic medication following STN-DBS correlated with
exclusive involvement of the nigrofugal pathways.
Disclosures
The authors have no personal, financial, or institutional interest in any of the
drugs, materials, or devices described in this article.
REFERENCES
1. Chiken S, Nambu A. Mechanism of deep brain stimulation? Neuroscientist.
2016;22(3):313-322.
2. Parent M, Parent A. The pallidofugal motor fiber system in primates. Parkinsonism
Relat Disord. 2004;10(4):203-211.
3. Miocinovic S, Parent M, Butson CR, et al. Computational analysis of subthalamic
nucleus and lenticular fasciculus activation during therapeutic deep brain stimu-
lation. JNeurophysiol. 2006;96(3):1569-1580.
4. Nauta WJH, Mehler WR. Projections of the lentiform nucleus in the monkey.
Brain Res. 1966;1(1):3-42.
5. Mettler FA. Nigrofugal connections in the primate brain. JCompNeurol.
1970;138(3):291-319.
6. Rundles RW. Connections between the striatum and the substantia nigra in a
human brain. Arch NeurPsych. 1937;38(3):550-563.
7. Hedreen JC, DeLong MR. Organization of striatopallidal, striatonigral, and nigros-
triatal projections in the macaque. JCompNeurol. 1991;304(4):569-595.
8. Panisset M, Picillo M, Jodoin N, et al. Establishing a standardof care for deep brain
stimulation centers in Canada. Can J Neurol Sci. 2017;44(2):132-138.
9. Defer GL, Widner H, Marié RM, Rémy P, Levivier M. Core assessment program
for surgical interventional therapies in Parkinson’s disease (CAPSIT-PD). Mov
Disord. 1999;14(4):572-584.
10. Horn A, Kühn AA. Lead-DBS: a toolbox for deep brain stimulation electrode local-
izations and visualizations. Neuroimage. 2015;107:127-135.
11. Avants BB, Tustison NJ, Wu J, Cook PA, Gee JC. An open source multivariate
framework for n-tissue segmentation with evaluation on public data. Neuroinfor-
matics. 2011;9(4):381-400.
12. Tustison NJ, Avants BB, Cook PA, et al. N4ITK: improved N3 bias correction.
IEEE Trans Med Imaging. 2010;29(6):1310-1320.
13. Ashburner J, Friston KJ. Diffeomorphic registration using geodesic shooting and
Gauss-Newton optimisation. Neuroimage. 2011;55(3):954-967.
14. Schönecker T, Kupsch A, Kühn AA, Schneider G-H, Hoffmann K-T. Automated
optimization of subcortical cerebral MR imaging-atlas coregistration for improved
postoperative electrode localization in deep brain stimulation. AJNR Am J Neuro-
radiol. 2009;30(10):1914-1921.
15. Husch A, V Petersen M, Gemmar P, Goncalves J, Hertel F. PaCER—a fully
automated method for electrode trajectory and contact reconstruction in deep
brain stimulation. Neuroimage Clin. 2018;17:80-89.
16. Horn A, Li N, Dembek TA, et al. Lead-DBS v2: towards a comprehensive pipeline
for deep brain stimulation imaging. Neuroimage. 2019;184:293-316.
17. Aström M, Zrinzo LU, Tisch S, Tripoliti E, Hariz MI, Wårdell K. Method for
patient-specific finite element modeling and simulation of deep brain stimulation.
Med Biol Eng Comput. 2009;47(1):21-28.
18. Chaturvedi A, Butson CR, Lempka SF, Cooper SE, McIntyre CC. Patient-specific
models of deep brain stimulation: influence of field model complexity on neural
activation predictions. Brain Stimulation. 2010;3(2):65-77.
19. Maks CB, Butson CR, Walter BL, Vitek JL, McIntyre CC. Deep brain stimu-
lation activation volumes and their association with neurophysiological mapping
and therapeutic outcomes. J Neurol Neurosurg Psychiatry. 2009;80(6):659-666.
20. Wolters CH, Lew S, Macleod RS, Hämäläinen M. Combined EEG/MEG source
analysis using calibrated finite element head models. Biomed Tech. 2010;55(suppl
1):64-67.
21. Oostenveld R, Fries P, Maris E, Schoffelen J-M. FieldTrip: open source software for
advanced analysis of MEG, EEG, and invasive electrophysiological data. Computat
Intell Neurosci. 2011;2011:1-9.
NEUROSURGERY VOLUME 0 | NUMBER 0 | 2019 | 9
Downloaded from https://academic.oup.com/neurosurgery/advance-article-abstract/doi/10.1093/neuros/nyz544/5674972 by Cleveland Clinic Alumni Library user on 13 December 2019
AVECILLAS-CHASIN AND HONEY
22. Horn A, Reich M, Vorwerk J, et al. Connectivity predicts deep brain stimulation
outcome in Parkinson disease. Ann Neurol. 2017;82(1):67-78.
23. Ewert S, Plettig P, Li N, et al. Toward defining deep brain stimulation targets in
MNI space: a subcortical atlas based on multimodal MRI, histology and structural
connectivity. Neuroimage. 2018;170(1):271-282.
24. Roberts PA. Motor systems—extra pyramidal or basal ganglia system. In:
Neuroanatomy. New York, NY: Springer;1987:24-27.
25. Feltz P, Albe-Fessard D. A study of an ascending nigro-caudate pathway. Electroen-
cephalogr Clin Neurophysiol. 1972;33(2):179-193.
26. Beukema P, Yeh F-C, Verstynen T. In vivo characterization of the connectivity and
subcomponents of the human globus pallidus. Neuroimage. 2015;120:382-393.
27. Connor JD. Electrophysiology of the nigro-caudate dopamine pathway. Pharmacol
Ther B. 1975;1(3):357-370.
28. Grofová I. Ansa and fasciculus lenticularis of carnivora. J Comp Neurol.
1970;138(2):195-207.
29. Smith Y, Lavoie B, Dumas J, Parent A. Evidence for a distinct nigropallidal
dopaminergic projection in the squirrel monkey. Brain Res. 1989;482(2):381-386.
30. Carpenter MB. Anatomy of the basal ganglia and related nuclei: a review. Adv
Neurol. 1976;14:7-48.
31. Hassler R. Fiber connections within the extrapyramidal system. Stereotact Funct
Neurosurg. 1974;36(4-6):237-255.
32. Tournier JD, Calamante F, Connelly A. MRtrix: diffusion tractography in crossing
fiber regions. Int J Imaging Syst Technol. 2012;22(1):53-66.
33. Rorden C, Karnath H-O, Bonilha L. Improving lesion-symptom mapping. J Cogn
Neurosci. 2007;19(7):1081-1088.
34. Mori S, Oishi K, Jiang H, et al. Stereotaxic white matter atlas based on diffusion
tensor imaging in an ICBM template. Neuroimage. 2008;40(2):570-582.
35. Hua K, Zhang J, Wakana S, et al. Tract probability maps in stereotaxic spaces:
analyses of white matter anatomy and tract-specific quantification. Neuro image.
2008;39(1):336-347.
36. Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM. FSL.
Neuroimage. 2012;62(2):782-790.
37. Edlow BL, Takahashi E, Wu O, et al. Neuroanatomic connectivity of the human
ascending arousal system critical to consciousness and its disorders. JNeuropathol
Exp Neurol. 2012;71(6):531-546.
38. Keuken MC, Bazin P-L, Crown L, et al. Quantifying inter-individual anatomical
variability in the subcortex using 7 T structural MRI. Neuroimage. 2014;94:40-46.
39. Xiao Y, Fonov V, Chakravarty MM, et al. A dataset of multi-contrast
population-averaged brain MRI atlases of a Parkinson’s disease cohort. Data Brief.
2017;12:370-379.
40. Smith RE, Tournier J-D, Calamante F, Connelly A. The effects of SIFT on the
reproducibility and biological accuracy of the structural connectome. Neuroimage.
2015;104:253-265.
41. Akram H, Sotiropoulos SN, Jbabdi S, et al. Subthalamic deep brain stimu-
lation sweet spots and hyperdirect cortical connectivity in Parkinson’s disease.
Neuroimage. 2017;158(7):332-345.
42. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation
inference for the general linear model. Neuroimage. 2014;92:381-397.
43. Gunalan K, Howell B, McIntyre CC. Quantifying axonal responses in patient-
specific models of subthalamic deep brain stimulation. Neuroimage. 2018;172:263-
277.
44. Bolte S, Cordelières FP. A guided tour into subcellular colocalization analysis in
light microscopy. JMicrosc. 2006;224(3):213-232.
45. Avecillas-Chasin JM, Alonso-Frech F, Nombela C, Villanueva C, Barcia JA. Stimu-
lation of the tractography-defined subthalamic nucleus regions correlates with
clinical outcomes. Neurosurgery. 2019;85(2):E294-E303.
46. Horn A, Kühn AA, Merkl A, Shih L, Alterman R, Fox M. Probabilistic conversion
of neurosurgical DBS electrode coordinates into MNI space. Neuroimage.
2017;150:395-404.
47. Kawasaki T, Shin M, Kimura Y, et al. Topographic anatomy of the subtha-
lamic nucleus localized by high-resolution human brain atlas superimposing digital
images of cross-sectioned surfaces and histological images of microscopic sections
from frozen cadaveric brains. J Clin Neurosci. 2018;53:193-202.
48. Frigyesi TL, Purpura DP. Electrophysiological analysis of reciprocal caudato-nigral
relations. Brain Res. 1967;6(3):440-456.
49. Papez JW. Reciprocal connections of the striatum and pallidum in the brain of
Pithecus (Macacus) rhesus. JCompNeurol. 1938;69(2):329-349.
50. Carpenter MB, Peter P. Nigrostriatal and nigrothalamic fibers in the rhesus
monkey. JCompNeurol. 1972;144(1):93-115.
51. Carpenter MB, Mcmasters RE. Lesions of the substantia nigra in the rhesus
monkey. Efferent fiber degeneration and behavioral observations. Am J Anat.
1964;114 (2):293-319.
52. Schneider TM, Deistung A, Biedermann U, et al. Susceptibility sensitive magnetic
resonance imaging displays pallidofugal and striatonigral fiber tracts. Oper
Neurosurg. 2016;12(4):330-338.
53. Marani E, Heida T, Lakke EAJF, Usunoff KG. The subthalamic nucleus. Part I:
development, cytology, topography and connections. Adv Anat Embryol Cell Biol.
2008;198:1-113, vii.
54. Xu W, Miocinovic S, Zhang J, Baker KB, McIntyre CC, Vitek JL. Dissociation of
motor symptoms during deep brain stimulation of the subthalamic nucleus in the
region of the internal capsule. Exp Neurol. 2011;228(2):294-297.
55. Johnson MD, Zhang J, Ghosh D, McIntyre CC, Vitek JL. Neural targets for
relieving parkinsonian rigidity and bradykinesia with pallidal deep brain stimu-
lation. JNeurophysiol. 2012;108(2):567-577.
56. Mahlknecht P, Akram H, Georgiev D, et al. Pyramidal tract activation due
to subthalamic deep brain stimulation in Parkinson’s disease. Mov Disord.
2017;32(8):1174-1182.
57. Chaturvedi A, Foutz TJ, McIntyre CC. Current steering to activate targeted neural
pathways during deep brain stimulation of the subthalamic region. Brain Stimu-
lation. 2012;5(3):369-377.
58. Krack P, Pollak P, Limousin P, et al. Opposite motor effects of pallidal stimulation
in Parkinson’s disease. Ann Neurol. 1998;43(2):180-192.
59. Hilliard JD, Frysinger RC, Elias WJ. Effective subthalamic nucleus deep brain
stimulation sites may differ for tremor, bradykinesia and gait disturbances in
Parkinson’s disease. Stereotact Funct Neurosurg. 2011;89(6):357-364.
60. Krack P, Pollak P, Limousin P, Hoffmann D, Benazzouz A, Benabid AL. Inhibition
of levodopa effects by internal pallidal stimulation. Mov Disord. 1998;13(4):648-
652.
61. Wodarg F, Herzog J, Reese R, et al. Stimulation site within the MRI-defined STN
predicts postoperative motor outcome. Mov Disord. 2012;27(7):874-879.
62. Gourisankar A, Eisenstein SA, Trapp NT, et al. Mapping movement, mood,
motivation and mentation in the subthalamic nucleus. R Soc Open Sci. 2018;
5(7):171177.
63. Bergmann O, Winter C, Meissner W, et al. Subthalamic high frequency stimu-
lation induced rotations are differentially mediated by D1 and D2 receptors.
Neuropharmacology. 2004;46(7):974-983.
64. Min H-K, Ross EK, Jo HJ, et al. Dopamine release in the nonhuman primate
caudate and putamen depends upon site of stimulation in the subthalamic nucleus.
JNeurosci. 2016;36(22):6022-6029.
65. Gross RE. The paradoxical role of dopamine after subthalamic nucleus deep
brain stimulation—downstream is upstream in a circuit diagram. Stereotact Funct
Neurosurg. 2008;86(3):189-190.
66. Gale JT, Lee KH, Amirnovin R, et al. Electrical stimulation-evoked dopamine
release in the primate striatum. Stereotact Funct Neurosurg. 2013;91(6):355-363.
67. Kitai ST, Sugimori M, Kocsis JD. Excitatory nature of dopamine in the nigro-
caudate pathway. Exp Brain Res. 1976;24(4):351-363.
68. Luoma J, Pekkonen E, Airaksinen K, et al. Spontaneous sensorimotor cortical
activity is suppressed by deep brain stimulation in patients with advanced
Parkinson’s disease. Neurosci Lett. 2018;683:48-53.
69. Zimnik AJ, Nora GJ, Desmurget M, Turner RS. Movement-related discharge in
the macaque globus pallidus during high-frequency stimulation of the subthalamic
nucleus. JNeurosci. 2015;35(9):3978-3989.
70. Herzog J, Pinsker M, Wasner M, et al. Stimulation of subthalamic fibre tracts
reduces dyskinesias in STN-DBS. Mov Disord. 2007;22(5):679-684.
71. Wu YR, Levy R, Ashby P, Tasker RR, Dostrovsky JO. Does stimulation of the GPi
control dyskinesia by activating inhibitory axons? Mov Disord. 2001;16(2):208-
216.
72. Blomstedt P, Sandvik U, Fytagoridis A, Tisch S. The posterior subthalamic area
in the treatment of movement disorders. Neurosurgery. 2009;64(6):1029-1042;
discussion 1038-1042.
73. Plaha P, Ben-Shlomo Y, Patel NK, Gill SS. Stimulation of the caudal zona incerta
is superior to stimulation of the subthalamic nucleus in improving contralateral
parkinsonism. Brain. 2006;129(7):1732-1747.
74. Castro G, Carrillo-Ruiz JD, Salcido V, et al. Optimizing prelemniscal radiations
as a target for motor symptoms in Parkinson’s disease treatment. Stereotact Funct
Neurosurg. 2015;93(4):282-291.
75. Avecillas-Chasin JM, Alonso-Frech F, Parras O, Del Prado N, Barcia JA.
Assessment of a method to determine deep brain stimulation targets using
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NIGROFUGAL AND PALLIDOFUGAL PATHWAYS IN STN-DBS
deterministic tractography in a navigation system. Neurosurg Rev. 2015;38(4):739-
750.
76. Coenen VA, Allert N, Paus S, Kronenbürger M, Urbach H, Mädler B. Modulation
of the cerebello-thalamo-cortical network in thalamic deep brain stimulation for
tremor. Neurosurgery. 2014;75(6):657-670; discussion 669-670.
77. Xie T, Bernard J, Warnke P. Post subthalamic area deep brain stimulation for
tremors: a mini-review. Transl Neurodegener. 2012;1(1):20.
78. Avecillas-Chasin JM, Rascón-Ramírez F, Barcia JA. Tractographical model of the
cortico-basal ganglia and corticothalamic connections. Clin Anat. 2016;29(4):481-
492.
79. Gallay MN, Jeanmonod D, Liu J, Morel A. Human pallidothalamic and cerebel-
lothalamic tracts: anatomical basis for functional stereotactic neurosurgery. Brain
Struct Funct. 2008;212(6):443-463.
80. Jeurissen B, Leemans A, Tournier J-D, Jones DK, Sijbers J. Investigating the preva-
lence of complex fiber configurations in white matter tissue with diffusion magnetic
resonance imaging. Hum Brain Mapp. 2013;34(11):2747-2766.
81. Sinke MRT, Otte WM, Christiaens D, et al. Diffusion MRI-based cortical
connectome reconstruction: dependency on tractography procedures and
neuroanatomical characteristics. Brain Struct Funct. 2018;223(5):2269-2285.
82. Schilling KG, Nath V, Hansen C, et al. Limits to anatomical accuracy of diffusion
tractography using modern approaches. Neuroimage. 2019;185:1-11.
83. Shamir RR, Dolber T, Noecker AM, Walter BL, McIntyre CC. Machine learning
approach to optimizing combined stimulation and medication therapies for
Parkinson’s disease. Brain Stimulation. 2015;8(6):1025-1032.
84. Noecker AM, Choi KS, Riva-Posse P, Gross RE, Mayberg HS, McIntyre CC.
StimVision software: examples and applications in subcallosal cingulate deep brain
stimulation for depression. Neuromodulation. 2018;21(2):191-196.
85. Amunts K, Lepage C, Borgeat L, et al. BigBrain: an ultrahigh-resolution 3D human
brain model. Science. 2013;340(6139):1472-1475.
Acknowledgments
The authors thank Vicky Earle for the artistic illustration of this work. The
data used in the preparation of this article were obtained from the Parkinson’s
Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data). For
up-to-date information on the study, visit www.ppmi-info.org. PPMI is sponsored
by the Michael J. Fox Foundation for Parkinson’s Research (MJFF) and is
cofunded by MJFF, Abbot, Avid Radiopharmaceuticals, Biogen Idec, Bristol-
Myers Squibb, Covance, Elan Corporation, Eli Lilly & Co, F. Hoffman-La Roche
Ltd, GE Healthcare, Genentech, GlaxoSmithKline, Lundbeck,Merck, MesoScale,
and Pfizer and UCB.
Supplemental digital content is available for this article at www.neurosurgery-
online.com.
Supplemental Digital Content. Methods. The Supplemental Digital Content
expands on the methods provided.
COMMENT
The notion of different anatomical targets improving different
symptoms of PD is not new – every DBS practitioner knows that
one almost always has to choose between beneficial effects of stimu-
lation and program the implanted system in such a way that it provides
the most needed benefits for each individual patient. This has been
routinely explained by a complex anatomy and physiology of the STN
and surrounding neural tracks with frequent overlap and close proximity
of different pathways that are involved in each of the addressed clinical
symptoms.
The authors of this paper came up with a very elegant explanation
of this clinical observation based on high-resolution tractography and
detailed analysis of fiber tracking findings. Their tedious work resulted
in defining a correlation between control of rigidity and tremor with
pathways that originate (or end) in the pallidum and bradykinesia – with
STN and nigral pathways. Since the first group of pathways travels dorsal
to the STN and the second is located ventrolateral to the STN, it may be
difficult to use the same stimulation contacts (or even the same electrode
lead) to control all symptoms at once.
These findings will have to be validated and, if confirmed, may be
used for surgical target optimization, perhaps specifically aiming at one
location or another based on the patient’s dominant symptoms. Another
option would be to use multiple electrodes from the beginning, but this
may make DBS surgery too complex and therefore unfeasible.
Konstantin V. Slavin
Chicago, Illinois
NEUROSURGERY VOLUME 0 | NUMBER 0 | 2019 | 11
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