Work

1:2 entrainment is not a device-induced artefact, except when it is

Year: 2024

Type: article

Abstract: Dear Editor, Deep Brain Stimulation (DBS) is a well-established invasive therapeutic approach for Parkinson's disease (PD). However, the mechanisms of DBS remain unclear. A transition from the established open-loop paradigm to closed-loop DBS holds promise for enhancing therapeutic outcomes and optimising device efficiency [1Simon Little, Alex Pogosyan, Spencer Neal, Baltazar Zavala, Ludvic Zrinzo, Marwan Hariz, Thomas Foltynie, Patricia Limousin, Keyoumars Ashkan, James FitzGerald, Alexander L. Green, Tipu Z. Aziz, and Peter Brown. Adaptive deep brain stimulation in advanced parkinson disease. Annals of neurology, 74, 2013.Google Scholar, 2Carina R Oehrn, Stephanie Cernera, Lauren H Hammer, Maria Shcherbakova, Jiaang Yao, Amelia Hahn, Sarah Wang, Jill L Ostrem, Simon Little, and Philip A Starr. Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in parkinson's disease. medRxiv, 2023.Google Scholar]. This transition requires identifying reliable biomarkers for the closed-loop algorithm. Recent studies suggest that biomarkers associated with harmonics of stimulation frequency may offer viable options for adaptive DBS (aDBS) and provide mechanistic insights [2Carina R Oehrn, Stephanie Cernera, Lauren H Hammer, Maria Shcherbakova, Jiaang Yao, Amelia Hahn, Sarah Wang, Jill L Ostrem, Simon Little, and Philip A Starr. Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in parkinson's disease. medRxiv, 2023.Google Scholar, 3James J. Sermon, Maria Olaru, Juan Anso, Stephanie Cernera, Simon Little, Maria Shcherbakova, Rafal Bogacz, Philip A. Starr, Timothy Denison, and Benoit Duchet. Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in parkinson's disease: Model based predictions and validation in three human subjects. Brain Stimulation, 2023.Google Scholar]. Previously subharmonic biomarkers have been avoided, often dismissed as artefactual. This is partly due to there being no clear physiological/non-physiological differentiating factor when considering steady signals during short time periods. To advance sense-stimulation therapies and aDBS, it is imperative to identify artefact-free frequency bands for effective biomarker monitoring. Here, we present a framework for discerning artefacts at the half harmonic of stimulation frequency. Do We Expect Entrainment? Yes! It should be noted that theoretically we expect to see subharmonic entrainment to periodic perturbations in certain nonlinear systems [[4]Namiko Mitarai, Uri Alon, and Mogens H. Jensen. Entrainment of noise-induced and limit cycle oscillators under weak noise. Chaos, 23:023125, 6 2013.Google Scholar]. Cortical 1:2 entrainment of finely tuned gamma (FTG) through DBS has been demonstrated to occur in a predictable manner in PD [[3]James J. Sermon, Maria Olaru, Juan Anso, Stephanie Cernera, Simon Little, Maria Shcherbakova, Rafal Bogacz, Philip A. Starr, Timothy Denison, and Benoit Duchet. Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in parkinson's disease: Model based predictions and validation in three human subjects. Brain Stimulation, 2023.Google Scholar] (Fig. 1A). A key requirement is believed to be neuronal ensembles with a natural frequency close to harmonics of stimulation frequency (discussed in [[3]James J. Sermon, Maria Olaru, Juan Anso, Stephanie Cernera, Simon Little, Maria Shcherbakova, Rafal Bogacz, Philip A. Starr, Timothy Denison, and Benoit Duchet. Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in parkinson's disease: Model based predictions and validation in three human subjects. Brain Stimulation, 2023.Google Scholar]). This can be seen in Fig. 1C where 1:2 entrainment is only observed in the cortex which displays FTG activity at approximately 75 Hz off-stimulation, unlike the pallidum where there is no activity around the half harmonic of stimulation. Theory can account for entrainment as a neurophysiological phenomenon but further checks are required to rule out the presence of artefacts. Physiological Confirmation Steps Initially, it is important to treat subharmonic activity cautiously and as an artefact. However, when evidence demonstrates physiological origin we must be open to exploit the potential clinical implications. We can demonstrate physiological origin by considering how subharmonic entrainment evolves around independent perturbations to physiology or stimulation. 1) Medication dependent: 1:2 FTG entrainment is modulated by medication and is only present in on-medication states [2Carina R Oehrn, Stephanie Cernera, Lauren H Hammer, Maria Shcherbakova, Jiaang Yao, Amelia Hahn, Sarah Wang, Jill L Ostrem, Simon Little, and Philip A Starr. Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in parkinson's disease. medRxiv, 2023.Google Scholar, 5Nicole C. Swann, Coralie De Hemptinne, Svjetlana Miocinovic, Salman Qasim, Sarah S. Wang, Nathan Ziman, Jill L. Ostrem, Marta San Luciano, Nicholas B. Galifianakis, and Philip A. Starr. Gamma oscillations in the hyperkinetic state detected with chronic human brain recordings in parkinson's disease. Journal of Neuroscience, 36:6445–6458, 6 2016.Google Scholar] (Fig. 1B). 2) Sleep-wake state dependent: Neural activity may selectively entrain at subharmonics of stimulation frequency according to sleep state [[6]Clay Smyth, Md Fahim Anjum, Shravanan Ravi, Timothy Denison, Philip Starr, and Simon Little. Adaptive deep brain stimulation for sleep stage targeting in parkinson's disease. Brain Stimulation, 16(5):1292–1296, 2023.Google Scholar]. In a system where stimulation and signal processing remain unchanged, for subharmonic entrainment to appear or disappear solely reflects a change in underlying neural circuitry. 3) Clinical observations: FTG power entrained at half stimulation frequency has been shown to predict prokinetic states in PD patients, and was identified as the optimal control signal for aDBS for reducing residual motor fluctuation [[2]Carina R Oehrn, Stephanie Cernera, Lauren H Hammer, Maria Shcherbakova, Jiaang Yao, Amelia Hahn, Sarah Wang, Jill L Ostrem, Simon Little, and Philip A Starr. Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in parkinson's disease. medRxiv, 2023.Google Scholar]. 4) Location Specific: 1:2 entrainment is only observed in specific neural structures (Fig 1C, from RCS10 as reported in [[3]James J. Sermon, Maria Olaru, Juan Anso, Stephanie Cernera, Simon Little, Maria Shcherbakova, Rafal Bogacz, Philip A. Starr, Timothy Denison, and Benoit Duchet. Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in parkinson's disease: Model based predictions and validation in three human subjects. Brain Stimulation, 2023.Google Scholar]). The observation of 1:2 entrainment in response to pallidal stimulation is limited to cortical contacts. These contacts are not close to the stimulating electrode. This indicates that volume conduction of a stimulation artefact from the stimulating electrode is not the source of cortical half harmonic activity. 5) Nonlinear response to stimulation: 1:2 entrainment is also modulated by stimulation parameters [[3]James J. Sermon, Maria Olaru, Juan Anso, Stephanie Cernera, Simon Little, Maria Shcherbakova, Rafal Bogacz, Philip A. Starr, Timothy Denison, and Benoit Duchet. Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in parkinson's disease: Model based predictions and validation in three human subjects. Brain Stimulation, 2023.Google Scholar] (Fig. 1D). Entrainment is lost at higher stimulation amplitudes, demonstrating that we are not simply observing an aliased signal; amplifier saturation might have some effect, but it can be monitored. Additionally, 1:2 entrainment results line up closely with the predictions from the computational model [[3]James J. Sermon, Maria Olaru, Juan Anso, Stephanie Cernera, Simon Little, Maria Shcherbakova, Rafal Bogacz, Philip A. Starr, Timothy Denison, and Benoit Duchet. Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in parkinson's disease: Model based predictions and validation in three human subjects. Brain Stimulation, 2023.Google Scholar]. Electrical Signal Chain Checklist When there's physiological evidence, we can proceed to eliminate the most commonly hypothesised sources of artefacts through benchtop testing and simulations. We begin our checklist with the most difficult to change potential sources, through to the easiest to modulate. 1) Tissue-electrode-interfaces (TEIs): TEIs have been hypothesised as a potential cause of subharmonic artefacts [[7]Yue Chen, Bozhi Ma, Hongwei Hao, and Luming Li. Cause of subharmonics in local field potentials recorded by sensing-enabled neurostimulator. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2021.Google Scholar], but can be eliminated through simulations. We simulate the output of 130 Hz monophasic square wave pulses at 130 Hz applied to the resistor network TEI (Fig. 1F, TEI from [[7]Yue Chen, Bozhi Ma, Hongwei Hao, and Luming Li. Cause of subharmonics in local field potentials recorded by sensing-enabled neurostimulator. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2021.Google Scholar]) and the commonly used TEI of a resistor and capacitor in parallel (Fig. 1E). We did not see subharmonic artefacts induced from either TEI. This is not surprising considering these network models are only made up of linear time-invariant components. A nonlinear element is required to produce anything other than a scaled or phase-shifted output. 2) Stimulator Circuits: We demonstrate the findings from our characterisation of the Picostim DyNeuMo-2 in a saline tank (Fig. 1H), which shows no subharmonic artefacts for the range of frequencies used. This is in agreement with saline tank results from both the Medtronic Percept PC [[8]Yohann Thenaisie, Chiara Palmisano, Andrea Canessa, Bart J. Keulen, Philipp Capetian, Mayte Castro Jiménez, Julien F. Bally, Elena Manferlotti, Laura Beccaria, Rodi Zutt, Grégoire Courtine, Jocelyne Bloch, Niels A. Van Der Gaag, Carel F. Hoffmann, Eduardo Martin Moraud, Ioannis U. Isaias, and M. Fiorella Contarino. Towards adaptive deep brain stimulation: Clinical and technical notes on a novel commercial device for chronic brain sensing, 2021.Google Scholar] and the Medtronic Summit RC+S [[9]Scott Stanslaski, Jeffrey Herron, Tom Chouinard, Duane Bourget, Ben Isaacson, Vaclav Kremen, Enrico Opri, William Drew, Benjamin H. Brinkmann, Aysegul Gunduz, Tom Adamski, Gregory A. Worrell, and Timothy Denison. A chronically implantable neural coprocessor for investigating the treatment of neurological disorders. IEEE Transactions on Biomedical Circuits and Systems, 12, 2018.Google Scholar] (Fig. 1G). Subharmonic artefacts can arise from stimulators, as demonstrated in the PINS device from residual and structured noise [[7]Yue Chen, Bozhi Ma, Hongwei Hao, and Luming Li. Cause of subharmonics in local field potentials recorded by sensing-enabled neurostimulator. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2021.Google Scholar]. More researchers should characterise their signal chain (as in [[7]Yue Chen, Bozhi Ma, Hongwei Hao, and Luming Li. Cause of subharmonics in local field potentials recorded by sensing-enabled neurostimulator. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2021.Google Scholar]) when they observe subharmonic activity of suspected physiological origin instead of ruling responses out as artefacts without further investigation. 3) Analogue-to-digital converters (ADCs): The ADC is the primary suspect from external signal processing and is easily simulated. We simulate the output of both a conventional downsampled ADC (Fig. 1K) as well as a delta-sigma ADC (Fig. 1L, the more common ADC used in sense-stimulation devices) in response to monophasic square wave pulses of 130 Hz for variable sampling rates. It is possible to observe prominent artefacts at the half harmonic of 130 Hz (Fig. 1I). However, these artefacts occur at precise sampling frequencies and can be predicted (Github ADC Artefact Calculator). Stimulation frequencies of stimulators in use today are already constrained by certain factors [[10]Juan Ansó, Moaad Benjaber, Brandon Parks, Samuel Parker, Carina Renate Oehrn, Matthew Petrucci, Ro'Ee Gilron, Simon Little, Robert Wilt, Helen Bronte-Stewart, Aysegul Gunduz, David Borton, Philip A. Starr, and Timothy Denison. Concurrent stimulation and sensing in bi-directional brain interfaces: A multi-site translational experience. Journal of Neural Engineering, 19, 2022.Google Scholar] and this should be included as another constraint. Looking to the future, manufacturers should characterise and design their electrical signal chain to avoid masking biomarkers. In summary, through characterisation of the stimulating device and ADC through benchtop testing and simulations in combination with the modulation of biomarkers by state, location and stimulation, we can effectively rule out the presence of subharmonic artefacts. Detailed study of subharmonic entrainment is still limited to a few research groups, and replication of these findings will further increase confidence that subharmonic activity does not have to be artefactual. By better understanding the system that we are stimulating, we may be able to predict neural responses to stimulation, obtain mechanistic insights into therapy and design robust adaptive algorithms. PS receives research support from Medtronic Inc (providing investigational devices free of charge). TD is a founder, director, and shareholder of Amber Therapeutics, Ltd, which also has a controlling interest in Bioinduction Ltd and Finetech Medical Ltd, the respective designers and manufacturers of the Picostim DyNeuMo system. TD is also an advisor for Synchron and Cortec Neuro. James J. Sermon: Data curation, Methodology, Software, Validation, Writing – review & editing, Conceptualization, Formal analysis, Investigation, Visualization, Writing – original draft. Moaad Benjaber: Data curation, Methodology, Resources, Software, Validation, Writing – review & editing. Benoit Duchet: Conceptualization, Data curation, Funding acquisition, Methodology, Supervision, Writing – review & editing. Juan Anso: Data curation, Writing – review & editing. Maria Olaru: Data curation, Writing – review & editing. Philip A. Starr: Funding acquisition, Resources, Supervision, Writing – review & editing. Timothy Denison: Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Writing – review & editing. JS and TD are supported by DARPA HR0011- 20-2-0028 Manipulating and Optimising Brain Rhythms for Enhancement of Sleep (Morpheus) and the UK Medical Research Council grant MC UU 00003/3. MO and PS are supported by NIH/NINDS award R01NS090913. JA is supported by Swiss National Science Foundation (Early Postdoc Mobility – P2BEP3 188140). BD is jointly supported by the Royal Academy of Engineering and Rosetrees under the Research Fellowship programme, and was also supported by Medical Research Council grant MC UU 00003/1. Content represents views of the authors and not the funders.

Source: Brain stimulation

DOI: 10.1016/j.brs.2024.01.010