Differences in functional connectivity profiles as a predictor of response to anterior thalamic nucleus deep brain stimulation for epilepsy: a hypothesis for the mechanism of action and a potential biomarker for outcomes

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OBJECTIVE

Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a promising therapy for refractory epilepsy. Unfortunately, the variability in outcomes from ANT DBS is not fully understood. In this pilot study, the authors assess potential differences in functional connectivity related to the volume of tissue activated (VTA) in ANT DBS responders and nonresponders as a means for better understanding the mechanism of action and potentially improving DBS targeting.

METHODS

This retrospective analysis consisted of 6 patients who underwent ANT DBS for refractory epilepsy. Patients were classified as responders (n = 3) if their seizure frequency decreased by at least 50%. The DBS electrodes were localized postoperatively and VTAs were computationally generated based on DBS programming settings. VTAs were used as seed points for resting-state functional MRI connectivity analysis performed using a control dataset. Differences in cortical connectivity to the VTA were assessed between the responder and nonresponder groups.

RESULTS

The ANT DBS responders showed greater positive connectivity with the default mode network compared to nonresponders, including the posterior cingulate cortex, medial prefrontal cortex, inferior parietal lobule, and precuneus. Interestingly, there was also a consistent anticorrelation with the hippocampus seen in responders that was not present in nonresponders.

CONCLUSIONS

Based on their pilot study, the authors observed that successful ANT DBS in patients with epilepsy produces increased connectivity in the default mode network, which the authors hypothesize increases the threshold for seizure propagation. Additionally, an inhibitory effect on the hippocampus mediated through increased hippocampal γ-aminobutyric acid (GABA) concentration may contribute to seizure suppression. Future studies are planned to confirm these findings.

ABBREVIATIONS ACC = anterior cingulate cortex; ANT = anterior nucleus of the thalamus; Cm-PF = centromedian-parafascicular; COG = center of gravity; DBS = deep brain stimulation; DLPFC = dorsolateral prefrontal cortex; DMN = default mode network; fMRI = functional MRI; GABA = γ-aminobutyric acid; MNI = Montreal Neurological Institute; MPRAGE = magnetization-prepared rapid acquisition gradient echo; PCC = posterior cingulate cortex; ROI = region of interest; SANTE = Stimulation of the Anterior Nuclei of Thalamus for Epilepsy; TLE = temporal lobe epilepsy; VTA = volume of tissue activated.

Abstract

OBJECTIVE

Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a promising therapy for refractory epilepsy. Unfortunately, the variability in outcomes from ANT DBS is not fully understood. In this pilot study, the authors assess potential differences in functional connectivity related to the volume of tissue activated (VTA) in ANT DBS responders and nonresponders as a means for better understanding the mechanism of action and potentially improving DBS targeting.

METHODS

This retrospective analysis consisted of 6 patients who underwent ANT DBS for refractory epilepsy. Patients were classified as responders (n = 3) if their seizure frequency decreased by at least 50%. The DBS electrodes were localized postoperatively and VTAs were computationally generated based on DBS programming settings. VTAs were used as seed points for resting-state functional MRI connectivity analysis performed using a control dataset. Differences in cortical connectivity to the VTA were assessed between the responder and nonresponder groups.

RESULTS

The ANT DBS responders showed greater positive connectivity with the default mode network compared to nonresponders, including the posterior cingulate cortex, medial prefrontal cortex, inferior parietal lobule, and precuneus. Interestingly, there was also a consistent anticorrelation with the hippocampus seen in responders that was not present in nonresponders.

CONCLUSIONS

Based on their pilot study, the authors observed that successful ANT DBS in patients with epilepsy produces increased connectivity in the default mode network, which the authors hypothesize increases the threshold for seizure propagation. Additionally, an inhibitory effect on the hippocampus mediated through increased hippocampal γ-aminobutyric acid (GABA) concentration may contribute to seizure suppression. Future studies are planned to confirm these findings.

Epilepsy is a common, worldwide cause of disability and death.15 Unfortunately, approximately 20%–40% of patients with epilepsy have drug-refractory disease.15 Mechanisms underlying drug-resistant epilepsy are poorly understood, which has confounded the ability to adequately treat patients with this type of epilepsy. Whereas early models largely focused on discrete epileptogenic sources,48 many forms of epilepsy, particularly temporal lobe epilepsy (TLE), are becoming increasingly recognized as network diseases with widespread functional and structural changes.11,38 Furthermore, some patients probably have multifocal onset, making localization and resective strategies difficult.

Although many brain networks have been shown to vary in epileptic patients compared to controls,11 perhaps none have been as extensively studied as the default mode network (DMN). The DMN is a widely distributed brain network that is preferentially active during rest and deactivated during the task engagement.9 Core components of the DMN include the posterior cingulate cortex (PCC), precuneus, inferior parietal lobule, superior parietal lobe, medial prefrontal cortex, retrosplenial cortex, hippocampus, parahippocampal cortex, and cerebellum.9,13,46 Prior work has suggested a deactivation of the DMN during interictal epileptiform discharges17 and during seizures,14 when DMN suppression may be related to loss of awareness. Additional resting-state networks implicated in seizures have been studied and may also play a role in the cognitive effects of epilepsy, such as the attention network and the reward/emotion network.11

The shift in the understanding of epilepsy may shed light on the variability in treatment outcomes; however, it also highlights the challenges associated with effective surgical treatment. One emerging potential treatment for refractory epilepsy is deep brain stimulation (DBS). Common targets have historically included the centromedian-parafascicular (Cm-PF) complex, hippocampus, and anterior nucleus of the thalamus (ANT).18,31,44 Results of the Stimulation of the Anterior Nuclei of Thalamus for Epilepsy (SANTE) trial show the long-term efficacy and safety of ANT stimulation in the treatment of focal epilepsy, but significant variability in outcomes exists.18,44 One potential cause for outcome variation is inadequate DBS targeting: for instance, approximately 10% of electrodes were not within the ANT in the SANTE trial and the Medtronic Registry for Epilepsy (MORE) study.30,50 Suggested improvements in direct ANT targeting have been proposed;10,40 however, insufficiencies in direct structural targeting in DBS have been previously illustrated.36,37 In this pilot study, we aimed to assess potential differences in resting-state functional connectivity profiles from volumes of tissue activated (VTAs) after ANT DBS in responders and nonresponders. Given that epileptiform activity has been associated with reduced activity in resting-state networks, we hypothesize that the VTA of the ANT in responders will show increased connectivity with resting-state networks compared with nonresponders.

Methods

The retrospective analysis of patients having received thalamic DBS for epilepsy was deemed exempt from full review by the Mayo Clinic Institutional Review Board. From a database of 8 patients who had undergone ANT DBS, 2 were excluded due to lack of follow-up—6 total patients were included for further analysis. Patients were arbitrarily grouped into 2 categories based on seizure reduction after DBS: the “responder” group had a ≥ 50% reduction in seizure frequency, whereas the “nonresponder” group had a < 50% reduction.

Chart Review

Relative demographic and clinical information was evaluated, including history, age, sex, seizure frequency, electrophysiological data, DBS programming information, and seizure reduction after DBS. Information regarding prior surgical treatments for epilepsy, including additional DBS leads, was also recorded.

Imaging Acquisition

The imaging used for this study consisted of preoperative magnetization-prepared rapid acquisition gradient echo (MPRAGE), T2-weighted sequence, and a postoperative high-resolution noncontrast CT. The preoperative MPRAGE imaging was acquired in the axial plane at 3 T after the administration of intravenous gadolinium-based contrast. Image resolution was 0.5 × 0.5 mm in-plane with a 1.2-mm slice thickness. Additional parameters included a TE of 5.2 msec, TR of 1186 msec, TI of 1000 msec, and flip angle of 8°. The T2-weighted imaging consisted of a turbo spin echo sequence obtained in the axial plane with an in-plane resolution of 0.9 × 0.9 mm and slice thickness of 3 mm, with a TE of 102 msec and a TR of 4633 msec. Postoperative noncontrast CT scanning of the head was performed for electrode localization. The CT parameters were an in-plane resolution of 0.6 × 0.6 mm and slice thickness of 1 mm.

Surgical Procedure

The details of our implantation procedure have been reported previously.49 In brief, with patients under anesthesia, a Leksell (Elekta) frame was placed, and stereotactic MR images were obtained. Using a Schaltenbrand and Wahren atlas overlay and anatomical guidance, we targeted the anterior nucleus by initially using coordinates from Hodaie et al., and modifying as necessary.22 Medtronic 3389 electrodes were then implanted in the anterior nucleus and intraoperative fluoroscopy was used to ensure their accurate placement. Five of the 6 patients had additional bilateral leads placed in the hippocampus (n = 4) and centromedian nucleus (n = 1). Electrode locations were confirmed with a CT scan and the patient was taken back to the operating theater. The leads were then tunneled and connected to lead extensions, which were then connected to a battery placed in the standard subclavicular pocket.22,49

Imaging Processing

A 2-stage linear registration (rigid followed by affine) was performed to coregister the postoperative CT and preoperative MRI acquisitions by using Advanced Normalization Tools (http://stnava.github.io/ANTs/).2 All coregistered images were then spatially normalized into Montreal Neurological Institute (MNI) ICBM_2009b_NLIN_ASYM space,19 based on a combination of the preoperative MPRAGE and T2-weighted acquisitions, by using the SyN registration approach in Advanced Normalization Tools. Nonlinear deformation into template space was achieved in 5 stages: After 2 linear (rigid followed by affine) steps, a nonlinear (whole brain) SyN registration stage was followed by 2 nonlinear SyN registrations that consecutively focused on the area of interest as defined by subcortical masks in Schönecker et al. in 2009.45 Corrections for brainshift on the postoperative CT were performed by applying a refined affine transform calculated between pre- and postoperative acquisitions that were restricted to a subcortical area of interest by using the brainshift-correction module of Lead-DBS software (http://www.lead-dbs.org).23 Two-dimensional projection images of the most distal cathode contact (K1/K9) were generated and registered to the DBS Intrinsic Template Atlas (DISTAL).16

Image Analysis

Using each patient’s recorded DBS stimulator settings, a VTA was generated using a finite element method solution with tissue-specific conductivity modeling as implemented in Lead-DBS software.23,24 All ANT electrodes were programmed with cathodal stimulation of the middle two contacts and with anodal stimulation of the proximal and distal contacts (a guarded cathode electrode configuration). Voltages for each patient were as follows: patient in case 1 = 5.2 V bilaterally; patient in case 2 = 2 V left and 2.5 V right; patient in case 3 = 5 V bilaterally; patient in case 4 = 6 V bilaterally; patient in case 5 = 6 V bilaterally; and patient in case 6 = 5 V bilaterally.

Each generated VTA was used as a seed point for resting-state functional MRI (fMRI) analysis performed using an averaged group resting-state fMRI database from 15 control patients, as described in Horn et al.24 A t-score map was generated for each patient. The t-score maps were averaged for the 3 responders and the 3 nonresponders and were thresholded to a t-score > 2. To assess differences between the 2 groups, the averaged t-score map from the nonresponder group was subtracted from that of the responder group to assess areas of greater correlation and anticorrelation, and then thresholded to p < 0.05. Cluster analysis of the resultant difference maps was also performed in FMRIB Software Library version 5.0 (http://fsl.fmrib.ox.ac.uk/fsl) to assess cluster size, maximum t-score per cluster, and center of gravity (COG) location by using a weighted-average location based on t-score value. Coordinates were calculated in MNI reference space. Clusters were thresholded to a maximum t-score equating to a p value < 0.05 and cluster size > 30 voxels.

Due to the difficulty of assessing the hippocampus on surface-based models, additional analysis was conducted to assess differences in individual t-scores. A region of interest (ROI) was generated consisting of a 5-mm radius sphere at the hippocampal MNI coordinate of ±30/−26/−11. The mean t-score and SD of all nonzero voxels was obtained for each ROI in all individual patient t-maps.

Results

Patient Information

Patient demographic data and outcomes are listed in Table 1. The clinical follow-up period averaged 29.7 months (range 18–39 months). We identified 3 patients who responded to therapy (≥ 50% reduction in seizure frequency) and 3 patients who were nonresponders (< 50% reduction in seizure frequency). Of our 6 patients, 5 had leads in an additional target (4 hippocampal and 1 Cm-PF complex). Of these 5 patients, 4 had stimulation of both targets (3 patients with ANT + hippocampal stimulation and 1 patient with ANT + Cm-PF complex). Of those 4 patients, 2 were in the responder group and 2 were in the nonresponder group.

TABLE 1.

Demographic data and outcomes in 6 patients who underwent ANT DBS for refractory epilepsy

Case No.SexAge (yrs)Additional LeadsSeizures (no./mo)FU (mos)
Pre-DBSPost-DBS  
1M47None363418
2F32Hippocampus131527
3M39Hippocampus4430
4F33Hippocampus>2009028
5F32Hippocampus20.339
6F30Centromedian90236

FU = follow-up.

Imaging Results

Imaging results highlight potential differences in functional connectivity that result from relatively small differences in the location of the VTA. Normalized electrode locations for all subjects are shown in Fig. 1. In general, the distal cathode contacts of electrodes in the responder group were more posterior and dorsal in location within the thalamus compared with those of nonresponders. The patient in case 4 had a VTA location more ventral on the left compared with other responders; however, the VTA was centered near the junction of the mammillothalamic tract and the ANT. Functional connectivity profiles generated from the VTA for each patient are shown in Supplementary Fig. 1.

FIG. 1.
FIG. 1.

Normalized spatial location of the distal cathode contact (K1/K9) for responders (green asterisks) and nonresponders (red asterisks) for the left thalamus (A and B) and the right thalamus (C and D). All electrodes are Medtronic 3389. Contact locations are registered to the DBS Intrinsic Template Atlas (DISTAL), showing the relationship to the anterior thalamic nucleus (arrows).

Distinctly different connectivity profiles were present in the averaged group maps for the responders (Fig. 2 left) and nonresponders (Fig. 2 right). When comparing responders to nonresponders, group mean differences (Fig. 3) showed higher positive correlation in responders, with several areas in the DMN having t-score differences > 3, including the bilateral PCC, medial prefrontal cortex, and inferior parietal lobule (Table 2). In contradistinction, the nonresponders showed poor positive correlation with nodes in the DMN. The cluster with the greatest t-score difference between responders and nonresponders was the PCC (maximum t-score difference of 7.6 on the right and 8.6 on the left).

FIG. 2.
FIG. 2.

Group average t-score maps for responders (left) and nonresponders (right) showing areas of positive correlation (red-yellow on map) and anticorrelation (blue-green on map).

FIG. 3.
FIG. 3.

Connectivity maps representing areas of connectivity that are higher in responders than in nonresponders (responders > nonresponders) for the left and right hemispheres. Areas with higher “positive” correlation in responders compared to nonresponders are shown in red-orange and areas of higher “negative” correlation, or anticorrelation, are shown in blue-green. Maps are generated from differences in mean group maps and thresholded to p value < 0.05, corrected for degrees of freedom.

TABLE 2.

Cluster statistics for group average t-score differences (responders > nonresponders)

Rt HemisphereLt Hemisphere
Cluster COG (MNI coordinate)Anatomical ReferenceCluster Size (mm3)Cluster Max t-Score DiffCluster COG (MNI coordinate)Anatomical ReferenceCluster Size (mm3)Cluster Max t-Score Diff
50/−34/28Inferior parietal lobule16294.0−62/−36/36Inferior parietal lobule16705.3
4/−26/34Posterior cingulate13397.6−4/−22/32Posterior cingulate15838.6
58/18/12Inferior frontal10864.2−34/48/29Dorsolateral prefrontal11494.3
2/28/20Anterior cingulate6123.8−2/30/30Anterior cingulate9653.7
4/30/44Medial prefrontal5813.7−60/2/10Inferior frontal8993.8
30/50/16Dorsolateral prefrontal4113.4−4/34/38Medial prefrontal5053.6
10/−68/40Precuneus2922.2−32/0/−12Amygdala1773.2
62/−28/−24Inferior temporal1473.5−32/48/−16Orbitofrontal1492.8
20/−2/−32Amygdala1413.2−34/16/−36Temporal pole1292.4
42/−12/−38Temporal pole1192.50/−70/42Precuneus1092.0
44/−10/0Insula352.84/−10/−16Hypothalamus722.5
−64/−42/−18Inferior temporal522.2

Diff = difference; max = maximum.

Additional areas with a maximum t-score difference > 3 between responders and nonresponders included the bilateral anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), amygdala, and inferior frontal regions, as well as the right inferior temporal gyrus. Similar distribution of clusters was present in both hemispheres, with the exception of a cluster in the right insula, left hypothalamus, and left orbitofrontal regions.

Interestingly, there was also a greater anticorrelation with the hippocampus seen in responders (Fig. 4). Additional significant clusters of anticorrelation that were greater in responders than in nonresponders were noted, including the left lingual gyrus (cluster MNI COG −14/−68/−8; maximum t-score difference 4.0), right lingual gyrus (COG 16/−72/0; maximum t-score difference 3.6), and left fusiform gyrus (COG −44/−72/−16; maximum t-score difference 3.1). Last, anticorrelation with the ventral striatum was also present (cluster MNI COG −2/12/−4; maximum t-score difference 3.1).

FIG. 4.
FIG. 4.

Coronal images through the hippocampus (y = −26; MNI template space) show the mean degree of anticorrelation in nonresponders (A) and responders (B). The mean difference (responders > nonresponders) is also shown (C). The ROI analysis (lower panel) at the hippocampal MNI coordinate of ±30/−26/−11 is shown for each patient (mean t-score and SD of all nonzero voxels with the ROI). L = left; R = right.

Discussion

To our knowledge, our study is the first to illustrate potential differences in epilepsy outcomes after ANT DBS based on resting-state connectivity profiles defined by the VTA location. Specifically, we found that patients responsive to therapy had VTAs located in ANT regions more positively correlated with the DMN when compared to nonresponders. Our findings highlight the importance of precise ANT targeting and suggest that a potential mechanism of ANT DBS is modulation of the DMN. If confirmed in larger studies, this information may allow more accurate preoperative targeting to maximize outcomes in ANT DBS for epilepsy.

ANT DBS is a promising technique for treatment of refractory epilepsy; however, outcomes thus far have been variable.18,44 The basis of such variation is complex and probably multifactorial. One potential confounder is related to seizure type and origin. For example, patients with extratemporal or multifocal seizure onset zones have been shown to have a less efficacious response to ANT DBS compared with patients in whom onset is in the temporal lobes.18,42 Another potential contributor to variable outcomes is variability in electrode localization. To date, the ideal coordinates for ANT DBS placement have not been well defined.50 It is also known that thalamic functional anatomy varies substantially compared to rigid atlas-based coordinates.36 Since the SANTE trial, others have proposed potential methods of direct targeting; however, the ideal target remains elusive.10,40 Given the movement toward functionally defined targets in other forms of DBS as an independent biomarker, such a functional target may also prove beneficial to ANT DBS.1,24,37

The development of functional preoperative targets requires an improved understanding of the mechanism of ANT DBS in treating epilepsy. Previously, the ACC has been implicated as a central core network hub in both ANT and thalamic centromedian nucleus DBS.25,26,52 Additionally, hippocampal connectivity has also been implicated as a potential mediator of ANT effect.20 Interestingly, Gibson et al. showed BOLD activation related to ANT stimulation in a swine model involving ACC, hippocampus, amygdala, insula, and prefrontal cortex, among others. However, these prior studies did not assess potential differences in connectivity between ANT DBS responders and nonresponders. Our study further supports prior findings illustrating a more robust connectivity profile largely corresponding to the ACC and DMN in responders compared to nonresponders.

The DMN has been extensively studied in patients with epilepsy, with numerous studies highlighting DMN abnormalities in various forms of the disease, including TLE,34,51 absence seizures,33 and reflex epilepsy,6 among others. Baseline decreased DMN connectivity is a common feature of epilepsy, and the degree of decreased connectivity has been shown to correlate with seizure frequency.6,33,34,51 However, not all DMN nodes show such decreased connectivity; in particular, the hippocampus has been shown to exhibit increased connectivity in epilepsy.4–6,39 In fact, Bettus et al. reported that an increase in connectivity of the hippocampus and amygdala contralateral to the side of the seizure onset zone had the highest specificity for epileptogenic zone localization.5 Additional prognostic value of these findings has been shown by Bharath et al., who found hippocampal increased connectivity only in patients with frequent seizures and not in the infrequent seizure group or controls, suggesting that this connectivity profile may be an indicator of drug-resistant seizures.6 This is also supported by evidence that patients with greater disturbance in the DMN, including the hippocampus, were less likely to respond to anterior temporal lobectomy.8

In addition to baseline disturbances in DMN connectivity, studies have also evaluated dynamic changes in the DMN during a seizure event. An intriguing finding is that seizure onset coincides with deactivation of components of the DMN, whereas seizure termination corresponds to increased activation in the DMN.3,7,27,29 Given the proposed role of the DMN in consciousness, these findings would seemingly fit clinical observations. Importantly, these findings suggest a role of the DMN in propagation and cessation of seizure activity.

In our study, we found that patients responding to ANT DBS had VTAs in thalamic regions with connectivity to the DMN. The profile of responders differed from that of nonresponders whose VTAs had less correlation with the DMN. In particular, we found a positive correlation with the PCC, medial prefrontal cortex, inferior parietal lobule, and precuneus. Based on previous evidence that decreased DMN connectivity preceded seizure onset, we propose that modulation of the DMN potentially underlies the therapeutic effect of ANT DBS by raising the threshold for DMN suppression and propagation of seizures.3,7,27,29 Last, greater connectivity between the VTA and the ACC and DLPFC was found; these are traditionally considered part of the working memory network. The role of the working memory network in seizures is not well studied, but these findings may still be related to DMN connectivity given the described frequent coactivation of the DMN and working memory network during task preparation.28

Our results also show an anticorrelation between thalamic VTAs and the hippocampus of responders that was not present in nonresponders. The etiology of resting-state blood oxygen level–dependent anticorrelations is not entirely clear. Initially, these anticorrelations were thought to be artifactual and related to the application of global signal regression in data preprocessing; however, subsequent work has shown that anticorrelations are indeed likely to be of biological origin.12 Current evidence suggests that resting-state anticorrelations are related to neuronal inhibition, probably mediated through increased γ-aminobutyric acid (GABA) concentration.32,41 The presence of hippocampal anticorrelation in our responders is an intriguing finding given the evidence of baseline increased connectivity in the hippocampus in patients with frequent seizures.4–6,39 Our results suggest that VTAs in the ANT DBS responder group may create a suppression of baseline hippocampal hyperconnectivity. This is further supported by animal studies showing sustained increases in GABA levels in the hippocampus after ANT stimulation.35,47

Additional areas of anticorrelation were found within the occipital lobes that were greater in responders compared with nonresponders. It has been previously shown that patients with epilepsy have increased intralobe connectivity within the occipital lobe.43 The etiology is uncertain but has been proposed as visual overactivation in epileptic patients.43 Along these lines, the observation of increased connectivity between the temporal lobe and occipital lobe during seizure propagation suggests that the occipital lobe may play a role in several forms of epilepsy.21 To date, this effect is not fully understood; therefore, the anticorrelation found in our study is of uncertain importance.

Several limitations of our study are noteworthy. First, the small sample size limits the ability to assess the robustness of the findings, and reflects the pilot nature of this study. Second, the use of atlas-based functional data may not fully account for variability in single-subject functional anatomy. Third, some patients also had additional DBS leads, such as Cm-PF complex or hippocampal leads, which could confound the results because of lesion effects. In addition to the potential lesional effect of having a lead in another target, 4 patients had simultaneous stimulation of the ANT and another target, and our activation data do not account for stimulation at multiple sites. Our preliminary study serves to introduce a concept and posit a potential mechanism of ANT stimulation, but it must be validated in a controlled and prospective manner. Last, it is also known that variation in stimulation parameters and lead type affect activation patterns.20 As such, further understanding is needed to generalize these findings to other devices and programming, given that all patients in our group had the same lead implants and stimulation profiles. Nevertheless, the results of our pilot study may help shed light on the potential mechanism of ANT DBS and help guide preoperative targeting in the future.

Conclusions

Based on our pilot study, we hypothesize that successful ANT DBS in epilepsy produces increased connectivity in the DMN and increases the threshold for seizure propagation. Additionally, an inhibitory effect on the hippocampus may contribute to seizure suppression. Determining which of these effects is the dominant driver of seizure suppression, or whether they are complementary effects, will require further study. Identification of this connectivity profile related to the thalamic VTA may aid in better definition of functional preoperative targets for ANT DBS. These findings will have to be confirmed in future studies.

Disclosures

Drs. Stead, Worrell, and Van Gompel report support from an NIH-funded public-private partnership grant (UH2-NS095495: Neurophysiologically Based Brain State Tracking & Modulation in Focal Epilepsy) between Mayo Clinic and Medtronic, and from a Medtronic-supported investigational device exemption study (Chronically-recorded deep brain nuclei/hippocampal high frequency oscillations as biomarkers of neurologic disease). The patients in this report received treatment based on compassionate, off-label use of commercially available, FDA-approved devices.

Author Contributions

Conception and design: all authors. Acquisition of data: Middlebrooks, Grewal, Stead, Lundstrom, Worrell. Analysis and interpretation of data: all authors. Drafting the article: Middlebrooks, Grewal, Stead. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Middlebrooks. Statistical analysis: Middlebrooks.

Supplemental Information

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    Lehtimäki KCoenen VAGonçalves Ferreira ABoon PElger CTaylor RS: The surgical approach to the anterior nucleus of thalamus in patients with refractory epilepsy: experience from the International Multicenter Registry (MORE). Neurosurgery [epub ahead of print] 2018

  • 31

    Li MCHCook MJ: Deep brain stimulation for drug-resistant epilepsy. Epilepsia 59:2732902018

  • 32

    Liang ZKing JZhang N: Anticorrelated resting-state functional connectivity in awake rat brain. Neuroimage 59:119011992012

  • 33

    Liao WZhang ZMantini DXu QJi GJZhang H: Dynamical intrinsic functional architecture of the brain during absence seizures. Brain Struct Funct 219:200120152014

  • 34

    Liao WZhang ZPan ZMantini DDing JDuan X: Altered functional connectivity and small-world in mesial temporal lobe epilepsy. PLoS One 5:e85252010

  • 35

    Liu HGYang ACMeng DWChen NZhang JG: Stimulation of the anterior nucleus of the thalamus induces changes in amino acids in the hippocampi of epileptic rats. Brain Res 1477:37442012

  • 36

    Middlebrooks EHHolanda VMTuna ISDeshpande HDBredel MAlmeida L: A method for pre-operative single-subject thalamic segmentation based on probabilistic tractography for essential tremor deep brain stimulation. Neuroradiology 60:3033092018

  • 37

    Middlebrooks EHTuna ISGrewal SSAlmeida LHeckman MLesser E: Segmentation of the globus pallidus internus using probabilistic diffusion tractography for deep brain stimulation targeting in Parkinson’s disease. AJNR Am J Neuroradiol [epub ahead of print] 2018

  • 38

    Middlebrooks EHVer Hoef LSzaflarski JP: Neuroimaging in epilepsy. Curr Neurol Neurosci Rep 17:322017

  • 39

    Morgan VLRogers BPSonmezturk HHGore JCAbou-Khalil B: Cross hippocampal influence in mesial temporal lobe epilepsy measured with high temporal resolution functional magnetic resonance imaging. Epilepsia 52:174117492011

  • 40

    Möttönen TKatisko JHaapasalo JTähtinen TKiekara TKähärä V: Defining the anterior nucleus of the thalamus (ANT) as a deep brain stimulation target in refractory epilepsy: delineation using 3 T MRI and intraoperative microelectrode recording. Neuroimage Clin 7:8238292015

  • 41

    Northoff GWalter MSchulte RFBeck JDydak UHenning A: GABA concentrations in the human anterior cingulate cortex predict negative BOLD responses in fMRI. Nat Neurosci 10:151515172007

  • 42

    Osorio IOverman JGiftakis JWilkinson SB: High frequency thalamic stimulation for inoperable mesial temporal epilepsy. Epilepsia 48:156115712007

  • 43

    Rajpoot KRiaz AMajeed WRajpoot N: Functional connectivity alterations in epilepsy from resting-state functional MRI. PLoS One 10:e01349442015

  • 44

    Salanova VWitt TWorth RHenry TRGross RENazzaro JM: Long-term efficacy and safety of thalamic stimulation for drug-resistant partial epilepsy. Neurology 84:101710252015

  • 45

    Schönecker TKupsch AKühn AASchneider GHHoffmann KT: Automated optimization of subcortical cerebral MR imaging-atlas coregistration for improved postoperative electrode localization in deep brain stimulation. AJNR Am J Neuroradiol 30:191419212009

  • 46

    Sheline YIBarch DMPrice JLRundle MMVaishnavi SNSnyder AZ: The default mode network and self-referential processes in depression. Proc Natl Acad Sci U S A 106:194219472009

  • 47

    Shi LYang ACLi JJMeng DWJiang BZhang JG: Favorable modulation in neurotransmitters: effects of chronic anterior thalamic nuclei stimulation observed in epileptic monkeys. Exp Neurol 265:941012015

  • 48

    Tatum WO IV: Mesial temporal lobe epilepsy. J Clin Neurophysiol 29:3563652012

  • 49

    Van Gompel JJKlassen BTWorrell GALee KHShin CZhao CZ: Anterior nuclear deep brain stimulation guided by concordant hippocampal recording. Neurosurg Focus 38(6):E92015

  • 50

    Wu CD’Haese PFPallavaram SDawant BMKonrad PSharan AD: Variations in thalamic anatomy affect targeting in deep brain stimulation for epilepsy. Stereotact Funct Neurosurg 94:3873962016

  • 51

    Zhang ZLu GZhong YTan QLiao WWang Z: Altered spontaneous neuronal activity of the default-mode network in mesial temporal lobe epilepsy. Brain Res 1323:1521602010

  • 52

    Zumsteg DLozano AMWieser HGWennberg RA: Cortical activation with deep brain stimulation of the anterior thalamus for epilepsy. Clin Neurophysiol 117:1922072006

If the inline PDF is not rendering correctly, you can download the PDF file here.

Article Information

Correspondence Erik H. Middlebrooks: Mayo Clinic, Jacksonville, FL. middlebrooks.erik@mayo.edu.

INCLUDE WHEN CITING DOI: 10.3171/2018.5.FOCUS18151.

E.H.M. and S.S.G. contributed equally to the study.

Disclosures Drs. Stead, Worrell, and Van Gompel report support from an NIH-funded public-private partnership grant (UH2-NS095495: Neurophysiologically Based Brain State Tracking & Modulation in Focal Epilepsy) between Mayo Clinic and Medtronic, and from a Medtronic-supported investigational device exemption study (Chronically-recorded deep brain nuclei/hippocampal high frequency oscillations as biomarkers of neurologic disease). The patients in this report received treatment based on compassionate, off-label use of commercially available, FDA-approved devices.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    Normalized spatial location of the distal cathode contact (K1/K9) for responders (green asterisks) and nonresponders (red asterisks) for the left thalamus (A and B) and the right thalamus (C and D). All electrodes are Medtronic 3389. Contact locations are registered to the DBS Intrinsic Template Atlas (DISTAL), showing the relationship to the anterior thalamic nucleus (arrows).

  • View in gallery

    Group average t-score maps for responders (left) and nonresponders (right) showing areas of positive correlation (red-yellow on map) and anticorrelation (blue-green on map).

  • View in gallery

    Connectivity maps representing areas of connectivity that are higher in responders than in nonresponders (responders > nonresponders) for the left and right hemispheres. Areas with higher “positive” correlation in responders compared to nonresponders are shown in red-orange and areas of higher “negative” correlation, or anticorrelation, are shown in blue-green. Maps are generated from differences in mean group maps and thresholded to p value < 0.05, corrected for degrees of freedom.

  • View in gallery

    Coronal images through the hippocampus (y = −26; MNI template space) show the mean degree of anticorrelation in nonresponders (A) and responders (B). The mean difference (responders > nonresponders) is also shown (C). The ROI analysis (lower panel) at the hippocampal MNI coordinate of ±30/−26/−11 is shown for each patient (mean t-score and SD of all nonzero voxels with the ROI). L = left; R = right.

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Laufs HHamandi KSalek-Haddadi AKleinschmidt AKDuncan JSLemieux L: Temporal lobe interictal epileptic discharges affect cerebral activity in “default mode” brain regions. Hum Brain Mapp 28:102310322007

30

Lehtimäki KCoenen VAGonçalves Ferreira ABoon PElger CTaylor RS: The surgical approach to the anterior nucleus of thalamus in patients with refractory epilepsy: experience from the International Multicenter Registry (MORE). Neurosurgery [epub ahead of print] 2018

31

Li MCHCook MJ: Deep brain stimulation for drug-resistant epilepsy. Epilepsia 59:2732902018

32

Liang ZKing JZhang N: Anticorrelated resting-state functional connectivity in awake rat brain. Neuroimage 59:119011992012

33

Liao WZhang ZMantini DXu QJi GJZhang H: Dynamical intrinsic functional architecture of the brain during absence seizures. Brain Struct Funct 219:200120152014

34

Liao WZhang ZPan ZMantini DDing JDuan X: Altered functional connectivity and small-world in mesial temporal lobe epilepsy. PLoS One 5:e85252010

35

Liu HGYang ACMeng DWChen NZhang JG: Stimulation of the anterior nucleus of the thalamus induces changes in amino acids in the hippocampi of epileptic rats. Brain Res 1477:37442012

36

Middlebrooks EHHolanda VMTuna ISDeshpande HDBredel MAlmeida L: A method for pre-operative single-subject thalamic segmentation based on probabilistic tractography for essential tremor deep brain stimulation. Neuroradiology 60:3033092018

37

Middlebrooks EHTuna ISGrewal SSAlmeida LHeckman MLesser E: Segmentation of the globus pallidus internus using probabilistic diffusion tractography for deep brain stimulation targeting in Parkinson’s disease. AJNR Am J Neuroradiol [epub ahead of print] 2018

38

Middlebrooks EHVer Hoef LSzaflarski JP: Neuroimaging in epilepsy. Curr Neurol Neurosci Rep 17:322017

39

Morgan VLRogers BPSonmezturk HHGore JCAbou-Khalil B: Cross hippocampal influence in mesial temporal lobe epilepsy measured with high temporal resolution functional magnetic resonance imaging. Epilepsia 52:174117492011

40

Möttönen TKatisko JHaapasalo JTähtinen TKiekara TKähärä V: Defining the anterior nucleus of the thalamus (ANT) as a deep brain stimulation target in refractory epilepsy: delineation using 3 T MRI and intraoperative microelectrode recording. Neuroimage Clin 7:8238292015

41

Northoff GWalter MSchulte RFBeck JDydak UHenning A: GABA concentrations in the human anterior cingulate cortex predict negative BOLD responses in fMRI. Nat Neurosci 10:151515172007

42

Osorio IOverman JGiftakis JWilkinson SB: High frequency thalamic stimulation for inoperable mesial temporal epilepsy. Epilepsia 48:156115712007

43

Rajpoot KRiaz AMajeed WRajpoot N: Functional connectivity alterations in epilepsy from resting-state functional MRI. PLoS One 10:e01349442015

44

Salanova VWitt TWorth RHenry TRGross RENazzaro JM: Long-term efficacy and safety of thalamic stimulation for drug-resistant partial epilepsy. Neurology 84:101710252015

45

Schönecker TKupsch AKühn AASchneider GHHoffmann KT: Automated optimization of subcortical cerebral MR imaging-atlas coregistration for improved postoperative electrode localization in deep brain stimulation. AJNR Am J Neuroradiol 30:191419212009

46

Sheline YIBarch DMPrice JLRundle MMVaishnavi SNSnyder AZ: The default mode network and self-referential processes in depression. Proc Natl Acad Sci U S A 106:194219472009

47

Shi LYang ACLi JJMeng DWJiang BZhang JG: Favorable modulation in neurotransmitters: effects of chronic anterior thalamic nuclei stimulation observed in epileptic monkeys. Exp Neurol 265:941012015

48

Tatum WO IV: Mesial temporal lobe epilepsy. J Clin Neurophysiol 29:3563652012

49

Van Gompel JJKlassen BTWorrell GALee KHShin CZhao CZ: Anterior nuclear deep brain stimulation guided by concordant hippocampal recording. Neurosurg Focus 38(6):E92015

50

Wu CD’Haese PFPallavaram SDawant BMKonrad PSharan AD: Variations in thalamic anatomy affect targeting in deep brain stimulation for epilepsy. Stereotact Funct Neurosurg 94:3873962016

51

Zhang ZLu GZhong YTan QLiao WWang Z: Altered spontaneous neuronal activity of the default-mode network in mesial temporal lobe epilepsy. Brain Res 1323:1521602010

52

Zumsteg DLozano AMWieser HGWennberg RA: Cortical activation with deep brain stimulation of the anterior thalamus for epilepsy. Clin Neurophysiol 117:1922072006

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