Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate

Ezra E Smith, Ki Sueng Choi, Ashan Veerakumar, Mosadoluwa Obatusin, Bryan Howell, Andrew H Smith, Vineet Tiruvadi, Andrea L Crowell, Patricio Riva-Posse, Sankaraleengam Alagapan, Christopher J Rozell, Helen S Mayberg, Allison C Waters, Ezra E Smith, Ki Sueng Choi, Ashan Veerakumar, Mosadoluwa Obatusin, Bryan Howell, Andrew H Smith, Vineet Tiruvadi, Andrea L Crowell, Patricio Riva-Posse, Sankaraleengam Alagapan, Christopher J Rozell, Helen S Mayberg, Allison C Waters

Abstract

Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering. We examined these spectral features-evoked power and phase clustering-in a sample of TRD patients (n = 8) with implanted SCC stimulators. Electroencephalogram (EEG) was recorded during wakeful rest. Location of electrical stimulation in the SCC target region was the experimental manipulation. EEG was analyzed at the surface level with an average reference for a cluster of frontal sensors and at a time window identified by prior study (50-150 ms). Morlet wavelets generated indices of evoked power and inter-trial phase clustering. Enhanced phase clustering at theta frequency (4-7 Hz) was observed in every subject and was significantly correlated with SCC-EP magnitude, but only during left SCC stimulation. Stimulation to dorsal SCC evinced stronger phase clustering than ventral SCC. There was a weak correlation between phase clustering and white matter density. An increase in evoked delta power (2-4 Hz) was also coincident with SCC-EP, but was less consistent across participants. DBS evoked time-frequency features index mm-scale changes to the location of stimulation in the SCC target region and correlate with structural characteristics implicated in treatment optimization. Results also imply a shared generative mechanism (inter-trial phase clustering) between evoked potentials evinced by electrical stimulation and evoked potentials evinced by auditory/visual stimuli and behavioral tasks. Understanding how current injection impacts downstream cortical activity is essential to building new technologies that adapt treatment parameters to individual differences in neurophysiology.

Keywords: deep brain stimulation; inter-trial phase clustering; perturbation mapping; single pulse electrical stimulation; stimulation evoked potential; subcallosal cingulate; time frequency analyses; treatment resistant depression (TRD).

Conflict of interest statement

HM received consulting and intellectual property licensing fees from Abbott Labs. KC received consulting fees from Abbott Labs. The terms approved by Emory University and the Icahn School of Medicine in accordance with policies to manage conflict of interest. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Smith, Choi, Veerakumar, Obatusin, Howell, Smith, Tiruvadi, Crowell, Riva-Posse, Alagapan, Rozell, Mayberg and Waters.

Figures

FIGURE 1
FIGURE 1
Single pulse electrical stimulation of the subcallosal cingulate (SCC) target for deep brain stimulation. (A) Four contacts span the SCC target region on bilateral DBS electrodes. (B) EEG was recorded on the head surface during single pulse electrical stimulation at each contact on the DBS leads. (C) Analytic window was coincident with the SCC-EP (∼100 ms) detected in frontal channels.
FIGURE 2
FIGURE 2
Magnitude of unilateral stimulation evoked potentials increases along the ventral-to-dorsal axis of the SCC target region. (A) Grand average waveforms for stimulation-evoked potentials. Shaded areas depict 95% confidence intervals after 1,000 bootstraps. Left panel shows ERPs following left SCC stimulation, and right panel shows ERPs following right SCC stimulation. Topographic plots show ERP magnitude integrated over 50–150 ms time window. (B) Boxplots depicting average ERP amplitudes (averaged across 50–150 ms, electrode montage shown in Figure 1C) separately for stimulation location. Left panel shows averages for left-SCC stimulation, right panel shows averages for right-SCC stimulation.
FIGURE 3
FIGURE 3
ITPC at 4–7 Hz depends on location of DBS in the SCC region. (A) Spectrogram of ITPC across time and frequency. Box denotes time-frequency region-of-interest used for topographic plots. Left panel for left SCC stimulation, right panel for right SCC stimulation. (B) Box plots showing ITPC (50–150 ms, 4–7 Hz) at different stimulation locations. Left panel for left SCC stimulation, right panel for right SCC stimulation. Green = E0/8, Red = E1/9, Blue = E2/10, Black = E3/11.
FIGURE 4
FIGURE 4
ITPC at 4–7 Hz for individual participants. Spectrograms of average ITPC across all stimulation locations from frontal sensors (Figure 1C) for individual participants. Subject order (1–8) shown within panel: right to left column then top to bottom row. (A) Spectrograms show ITPC time-locked to left hemisphere SCC DBS, and (B) to right hemisphere SCC DBS. Stippled box denotes time-frequency region of interest used for group analysis and topographic plots in (B).
FIGURE 5
FIGURE 5
Topography and time course of ITPC at 4–7 Hz for individual participants. (A) ITPC topography for individual participants (4–7 Hz, 50–150 ms) averaged across all stimulation locations. The 8 topomaps on the left are from left SCC stimulation, and 8 topomaps on the right are from right SCC stimulation. Subject order (1–8) of topomaps: top rows (right to left) then bottom rows. (B) ITPC waveforms (4–7 Hz; frontal sensor montage, Figure 1C) from individual participants. Black lines are ITPC waveforms following stimulation at E3/11, green lines are ITPC waveforms following stimulation at E0/8. Left panel is from left SCC stimulation, and right panel is from right SCC stimulation.

References

    1. Alagapan S., Lustenberger C., Hadar E., Shin H. W., Fröhlich F. (2019). Low-frequency direct cortical stimulation of left superior frontal gyrus enhances working memory performance. Neuroimage 184 697–706. 10.1016/j.neuroimage.2018.09.064
    1. Allen D. P., Stegemoller E. L., Zadikoff C., Rosenow J. M., Mackinnon C. D. (2010). Suppression of deep brain stimulation artifacts from the electroencephalogram by frequency-domain Hampel filtering. Clin. Neurophysiol. 121 1227–1232. 10.1016/j.clinph.2010.02.156
    1. Arns M., Etkin A., Hegerl U., Williams L. M., DeBattista C., Palmer D. M., et al. (2015). Frontal and rostral anterior cingulate (rACC) theta EEG in depression: Implications for treatment outcome? Eur. Neuropsychopharmacol. 25 1190–1200.
    1. Baker K. B., Montgomery E. B., Rezai A. R., Burgess R., Lüders H. O. (2002). Subthalamic nucleus deep brain stimulus evoked potentials: Physiological and therapeutic implications. Mov. Disord. 17 969–983. 10.1002/mds.10206
    1. Basu I., Robertson M. M., Crocker B., Peled N., Farnes K., Vallejo-Lopez D., I, et al. (2019). Consistent linear and non-linear responses to invasive electrical brain stimulation across individuals and primate species with implanted electrodes. Brain Stimul. 12 877–892. 10.1016/j.brs.2019.03.007
    1. Berlim M. T., McGirr A., Dos Santos N. R., Tremblay S., Martins R. (2017). Efficacy of theta burst stimulation (TBS) for major depression: An exploratory meta-analysis of randomized and sham-controlled trials. J. Psychiatr. Res. 90 102–109. 10.1016/j.jpsychires.2017.02.015
    1. Borich M. R., Wheaton L. A., Brodie S. M., Lakhani B., Boyd L. A. (2016). Evaluating interhemispheric cortical responses to transcranial magnetic stimulation in chronic stroke: A TMS-EEG investigation. Neurosci. Lett. 618 25–30. 10.1016/j.neulet.2016.02.047
    1. Broadway J. M., Holtzheimer P. E., Hilimire M. R., Parks N. A., DeVylder J. E., Mayberg H. S., et al. (2012). Frontal theta cordance predicts 6-month antidepressant response to subcallosal cingulate deep brain stimulation for treatment-resistant depression: A pilot study. Neuropsychopharmacology 37:1764. 10.1038/npp.2012.23
    1. Cavanagh J. F., Frank M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends Cogn. Sci. 18 414–421.
    1. Cavanagh J. F., Cohen M. X., Allen J. J. (2009). Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring. J. Neurosci. 29 98–105. 10.1523/JNEUROSCI.4137-08.2009
    1. Cavanagh J. F., Rieger R. E., Wilson J. K., Gill D., Fullerton L., Brandt E., et al. (2020). Joint analysis of frontal theta synchrony and white matter following mild traumatic brain injury. Brain Imaging Behav. 14 2210–2223. 10.1007/s11682-019-00171-y
    1. Chaturvedi A., Luján J. L., McIntyre C. C. (2013). Artificial neural network based characterization of the volume of tissue activated during deep brain stimulation. J. Neural Eng. 10:056023. 10.1088/1741-2560/10/5/056023
    1. Cohen M. X. (2011a). Error-related medial frontal theta activity predicts cingulate-related structural connectivity. Neuroimage 55 1373–1383. 10.1016/j.neuroimage.2010.12.072
    1. Cohen M. X. (2011b). It’s about time. Front. Hum. Neurosci. 5:2. 10.3389/fnhum.2011.00002
    1. Cohen M. X. (2014). Analyzing Neural Time Series Data: Theory and Practice. Cambridge, MA:MIT press.
    1. Conner C. R., Ellmore T. M., DiSano M. A., Pieters T. A., Potter A. W., Tandon N. (2011). Anatomic and electro-physiologic connectivity of the language system: A combined DTI-CCEP study. Comput. Biol. Med. 41 1100–1109. 10.1016/j.compbiomed.2011.07.008
    1. Cooper P. S., Karayanidis F., McKewen M., McLellan-Hall S., Wong A. S. W., Skippen P., et al. (2019). Frontal theta predicts specific cognitive control-induced behavioural changes beyond general reaction time slowing. Neuroimage 189, 130–140. 10.1016/j.neuroimage.2019.01.022
    1. Cox R. W. (1996). AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29 162–173. 10.1006/cbmr.1996.0014
    1. Dede A. J., Marzban N., Mishra A., Reichert R., Anderson P. M., Cohen M. X. (2021). Prefrontal, striatal, and VTA subnetwork dynamics during novelty and exploration. bioRxiv[preprint]. 10.1101/2021.11.24.469851
    1. Duprez J., Gulbinaite R., Cohen M. X. (2020). Midfrontal theta phase coordinates behaviorally relevant brain computations during cognitive control. NeuroImage 207, 116340. 10.1016/j.neuroimage.2019.116340
    1. Entz L., Tóth E., Keller C. J., Bickel S., Groppe D. M., Fabó D., et al. (2014). Evoked effective connectivity of the human neocortex. Hum. Brain Mapp. 35 5736–5753.
    1. Fox M. D., Buckner R. L., White M. P., Greicius M. D., Pascual-Leone A. (2012). Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate. Biol. Psychiatry 72 595–603.
    1. Fuentemilla L., Marco-Pallarés J., Grau C. (2006). Modulation of spectral power and of phase resetting of EEG contributes differentially to the generation of auditory event-related potentials. Neuroimage 30 909–916. 10.1016/j.neuroimage.2005.10.036
    1. Hamilton M. (1960). A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23:56.
    1. Hanslmayr S., Klimesch W., Sauseng P., Gruber W., Doppelmayr M., Freunberger R., et al. (2007). Alpha phase reset contributes to the generation of ERPs. Cereb. Cortex 17 1–8. 10.1093/cercor/bhj129
    1. Herweg N. A., Apitz T., Leicht G., Mulert C., Fuentemilla L., Bunzeck N. (2016). Theta-alpha oscillations bind the hippocampus, prefrontal cortex, and striatum during recollection: Evidence from simultaneous EEG–fMRI. J. Neurosci. 36 3579–3587. 10.1523/JNEUROSCI.3629-15.2016
    1. Holtzheimer P. E., Kelley M. E., Gross R. E., Filkowski M. M., Garlow S. J., Barrocas A., et al. (2012). Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression. Arch. Gene. Psychiatry 69 150–158.
    1. Howell B., Choi K. S., Gunalan K., Rajendra J., Mayberg H. S., McIntyre C. C. (2019). Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation. Hum. Brain Mapp. 40 889–903. 10.1002/hbm.24419
    1. Keller C. J., Honey C. J., Mégevand P., Entz L., Ulbert I., Mehta A. D. (2014). Mapping human brain networks with cortico-cortical evoked potentials. Philos. Trans. R. Soc. B 369:20130528
    1. Keller C. J., Huang Y., Herrero J. L., Fini M. E., Du V., Lado F. A., et al. (2018). Induction and quantification of excitability changes in human cortical networks. J. Neurosci. 1088–1017.
    1. Kimiskidis V. K. (2016). Transcranial magnetic stimulation (TMS) coupled with electroencephalography (EEG): Biomarker of the future. Revue Neurol. 172 123–126.
    1. Klimesch W., Sauseng P., Hanslmayr S., Gruber W., Freunberger R. (2007). Event-related phase reorganization may explain evoked neural dynamics. Neurosci. Biobehav. Rev. 31 1003–1016. 10.1016/j.neubiorev.2007.03.005
    1. Lio G., Thobois S., Ballanger B., Lau B., Boulinguez P. (2018). Removing deep brain stimulation artifacts from the electroencephalogram: Issues, recommendations and an open-source toolbox. Clin. Neurophysiol. 129 2170–2185. 10.1016/j.clinph.2018.07.023
    1. Liu L. D., Prescott I. A., Dostrovsky J. O., Hodaie M., Lozano A. M., Hutchison W. D. (2012). Frequency-dependent effects of electrical stimulation in the globus pallidus of dystonia patients. J. Neurophysiol. 108 5–17. 10.1152/jn.00527.2011
    1. Luu P., Tucker D. M., Makeig S. (2004). Frontal midline theta and the error-related negativity: Neurophysiological mechanisms of action regulation. Clin. Neurophysiol. 115 1821–1835.
    1. Makeig S., Debener S., Onton J., Delorme A. (2004). Mining event-related brain dynamics. Trends Cogn. Sci. 8 204–210.
    1. Marawar R. A., Yeh H. J., Carnabatu C. J., Stern J. M. (2017). Functional MRI correlates of resting-state temporal theta and delta EEG rhythms. J. Clin. Neurophysiol. 34 69–76.
    1. Massimini M., Ferrarelli F., Huber R., Esser S. K., Singh H., Tononi G. (2005). Breakdown of cortical effective connectivity during sleep. Science 309 2228–2232.
    1. Nakae T., Matsumoto R., Kunieda T., Arakawa Y., Kobayashi K., Shimotake A., et al. (2019). Connectivity Gradient in the Human Left Inferior Frontal Gyrus: Intraoperative Cortico-Cortical Evoked Potential Study. Cereb. Cortex 30 4633–4650. 10.1093/cercor/bhaa065
    1. Narayanan N. S., Cavanagh J. F., Frank M. J., Laubach M. (2013). Common medial frontal mechanisms of adaptive control in humans and rodents. Nat. Neurosci. 16 1888–1895. 10.1038/nn.3549
    1. Narushima K., McCormick L. M., Yamada T., Thatcher R. W., Robinson R. G. (2010). Subgenual cingulate theta activity predicts treatment response of repetitive transcranial magnetic stimulation in participants with vascular depression. J. Neuropsychiatry Clin. Neurosci. 22 75–84. 10.1176/jnp.2010.22.1.75
    1. Noecker A. M., Choi K. S., Riva-Posse P., Gross R. E., Mayberg H. S., McIntyre C. C. (2018). StimVision software: Examples and applications in subcallosal cingulate deep brain stimulation for depression. Neuromodulation 21 191–196. 10.1111/ner.12625
    1. Noecker A. M., Choi K. S., Riva-Posse P., Gross R. E., Mayberg H. S., McIntyre C. C. (2017). StimVision Software: Examples and Applications in Subcallosal Cingulate Deep Brain Stimulation for Depression. Neuromodulation 21 191–196.
    1. Penny W. D., Kiebel S. J., Kilner J. M., Rugg M. D. (2002). Event-related brain dynamics. Trends Neurosci. 25 387–389.
    1. Pizzagalli D. A., Webb C. A., Dillon D. G., Tenke C. E., Kayser J., Goer F., et al. (2018). Pretreatment rostral anterior cingulate cortex theta activity in relation to symptom improvement in depression: A randomized clinical trial. JAMA Psychiatry 75 547–554. 10.1001/jamapsychiatry.2018.0252
    1. Reinhart R. M. G., Nguyen J. A. (2019). Working memory revived in older adults by synchronizing rhythmic brain circuits. Nat. Neurosci. 22 820–827. 10.1038/s41593-019-0371-x
    1. Riva-Posse P., Choi K. S., Holtzheimer P. E., McIntyre C. C., Gross R. E., Chaturvedi A., et al. (2014). Defining Critical White Matter Pathways Mediating Successful Subcallosal Cingulate Deep Brain Stimulation for Treatment-Resistant Depression. Biological Psychiatry 76 963–9. 10.1016/j.biopsych.2014.03.029
    1. Riva-Posse P., Choi K., Holtzheimer P. E., Crowell A. L., Garlow S. J., Rajendra J. K., et al. (2018). A connectomic approach for subcallosal cingulate deep brain stimulation surgery: Prospective targeting in treatment-resistant depression. Mol. Psychiatry 23 843–849. 10.1038/mp.2017.59
    1. Robble M. A., Schroder H. S., Kangas B. D., Nickels S., Breiger M., Iturra-Mena A. M., et al. (2021). Concordant neurophysiological signatures of cognitive control in humans and rats. Neuropsychopharmacology 46 1252–1262. 10.1038/s41386-021-00998-4
    1. Sarasso S., Boly M., Napolitani M., Gosseries O., Charland-Verville V., Casarotto S., et al. (2015). Consciousness and complexity during unresponsiveness induced by propofol, xenon, and ketamine. Curr. Biol. 25 3099–3105.
    1. Shah A. S., Bressler S. L., Knuth K. H., Ding M., Mehta A. D., Ulbert I., et al. (2004). Neural dynamics and the fundamental mechanisms of event-related brain potentials. Cereb. Cortex 14 476–483.
    1. Smith E. E., Reznik S. J., Stewart J. L., Allen J. J. (2017). Assessing and conceptualizing frontal EEG asymmetry: An updated primer on recording, processing, analyzing, and interpreting frontal alpha asymmetry. Int. J. Psychophysiol. 111, 98–114. 10.1016/j.ijpsycho.2016.11.005
    1. Smith E. E., Tenke C. E., Deldin P. J., Trivedi M. H., Weissman M. M., Auerbach R. P., et al. (2020). Frontal theta and posterior alpha in resting EEG: A critical examination of convergent and discriminant validity. Psychophysiology 57:e13483.
    1. Solomon E. A., Kragel J. E., Gross R., Lega B., Sperling M. R., Worrell G., et al. (2018). Medial temporal lobe functional connectivity predicts stimulation-induced theta power. Nat. Commun. 9:4437. 10.1038/s41467-018-06876-w
    1. Trujillo L. T., Allen J. J. (2007). Theta EEG dynamics of the error-related negativity. Clin. Neurophysiol. 118 645–668.
    1. Van Gompel J. J., Klassen B. T., Worrell G. A., Lee K. H., Shin C., Zhao C. Z., et al. (2015). Anterior nuclear deep brain stimulation guided by concordant hippocampal recording. Neurosurg. Focus 38:E9. 10.3171/2015.3.FOCUS1541
    1. Vergani F., Martino J., Morris C., Attems J., Ashkan K., Dell’Acqua F. (2016). Anatomic connections of the subgenual cingulate region. Neurosurgery 79 465–472.
    1. Waters A. C., Veerakumar A., Choi K. S., Howell B., Tiruvadi V., Bijanki K. R., et al. (2018). Test-retest reliability of a stimulation-locked evoked response to deep brain stimulation in subcallosal cingulate for treatment resistant depression. Hum. Brain Mapp. 39 4844–4856. 10.1002/hbm.24327
    1. Whitton A. E., Webb C. A., Dillon D. G., Kayser J., Rutherford A., Goer F., et al. (2019). Pretreatment Rostral Anterior Cingulate Cortex Connectivity With Salience Network Predicts Depression Recovery: Findings From the EMBARC Randomized Clinical Trial. Biol. Psychiatry 85 872–880. 10.1016/j.biopsych.2018.12.007
    1. Yamao Y., Suzuki K., Kunieda T., Matsumoto R., Arakawa Y., Nakae T., et al. (2017). Clinical impact of intraoperative CCEP monitoring in evaluating the dorsal language white matter pathway. Hum. Brain Mapp. 38 1977–1991. 10.1002/hbm.23498
    1. Yu X., Ding P., Yuan L., Zhang J., Liang S., Zhang S., et al. (2019). Cortico-cortical evoked potentials in tuberous sclerosis complex children using stereo-electroencephalography. Front. Neurol. 10:1093. 10.3389/fneur.2019.01093
    1. Zumsteg D., Lozano A. M., Wieser H. G., Wennberg R. A. (2006). Cortical activation with deep brain stimulation of the anterior thalamus for epilepsy. Clinical Neurophysiology 117 192–207.

Source: PubMed

3
Abonnieren