# SEEG electrode shaft affects amplitude and latency of potentials evoked with single pulse electrical stimulation

Maciej Jedynak, Anthony Boyer, Manuel Mercier, Blandine Chanteloup-Forêt, Manik Bhattacharjee, Philippe Kahane, Olivier David

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Maciej Jedynak, Anthony Boyer, Manuel Mercier, Blandine Chanteloup-Forêt, Manik Bhattacharjee, et al.. SEEG electrode shaft affects amplitude and latency of potentials evoked with single pulse electrical stimulation. Journal of Neuroscience Methods, 2024, 403, pp.110035. 10.1016/j.jneumeth.2023.110035. hal-04885943

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# SEEG electrode shaft affects amplitude and latency of potentials evoked with single pulse electrical stimulation

Short communication

## Authors, initials and ORCID IDs:

Maciej Jedynak (MJ)¹, 0000-0003-1876-5485

Anthony Boyer (AB)¹

Manuel Mercier (MM)¹, 0000-0001-6358-4734

Blandine Chanteloup-Forêt (BCF)²

Manik Bhattacharjee (MB)¹,², 0000-0002-8183-1521

Philippe Kahane (PK)²,³, 0000-0003-1330-3281

Olivier David (OD)¹, 0000-0003-0776-0216

F-TRACT Consortium

1 Aix Marseille Université, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France

2 Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France

3 Neurology Department, CHU Grenoble Alpes, Grenoble, France

F-TRACT Consortium members: Claude Adam, Vincent Navarro, Arnaud Biraben, Anca Nica, Dominique Menard, Milan Brazdil, Robert Kuba, Jitka Kočvarová, Martin Pail, Irena Doležalová, François Dubeau, Jean Gotman, Philippe Ryvlin, Jean Isnard, Hélène Catenoix, Alexandra Montavont, Sylvain Rheims, Fabrice Bartolomei, Agnès Trébuchon, Aileen McGonigal, Wenjing Zhou, Haixiang Wang, Sinclair Liu, Zhang Wei, Zhu Dan, Guo Qiang, Hu Xiangshu, Li Hua, Hua Gang, Wang Wensheng, Mei Xi, Feng Yigang, Rima Nabbout, Marie Bourgeois, Anna Kamińska, Thomas Blauwblomme, Mercedes Garcés, Antonio Valentin, Rinki Singh, Liisa Metsähonkala, Eija Gaily, Leena Lauronen, Maria Peltola, Francine Chassoux, Elizabeth Landré, Philippe Derambure, William Szurhaj, Maxime Chochois, Edouard Hirsch, Maria Paola Valenti, Julia Scholly, Luc Valton, Marie Denuelle, Jonathan Curot, Rodrigo Rocamora, Alessandro Principe, Miguel Ley, Neurology Department, University Emergency Hospital, Bucharest, Romania: Ioana Mindruta, Andrei Barborica, Stefano Francione, Roberto Mai, Lino Nobili, Ivana Sartori, Laura Tassi, Louis Maillard, Jean-Pierre Vignal, Jacques Jonas, Louise Tyvaert, Mathilde Chipaux, Delphine Taussig, Philippe Kahane, Lorella Minotti, Anne-Sophie Job, Véronique Michel, Marie de Montaudoin, Jérôme Aupy, Viviane Bouilleret, Ana Maria Petrescu, Pascal
Masnou, Claire Dussaule, Marion Quirins, Delphine Taussig, Carmen Barba, Renzo Guerrini, Matteo Lenge and Elisa Nacci.

Corresponding Author: Maciej Jedynak, maciej.jedynak@protonmail.com

CRediT Roles

Maciej Jedynak: Conceptualization; Data curation; Formal analysis, Investigation;

Methodology; Software; Visualization; Writing - original draft;

Anthony Boyer: Software, Data curation

Manuel Mercier: Writing - original draft

Blandine Chanteloup-Forêt: Software, Data curation

Manik Bhattacharjee: Software, Data curation

Philippe Kahane: Conceptualization, Data acquisition

Olivier David: Conceptualization, Funding acquisition; Methodology, Project administration;

Software, Resources, Supervision, Writing - review & editing.

Abstract

**Background:**

Long and thin shaft electrodes are implanted intracerebrally for stereoelectroencephalography (SEEG) in patients with pharmacoresistant focal epilepsies. Two adjacent contacts of one of such electrodes can deliver a train of single pulse electrical stimulations (SPES), and evoked potentials (EPs) are recorded on other contacts. In this study we assess if stimulating and recording on the same shaft, as opposed to different shafts, has an impact on common EP features.

**New Method**

We leverage the large volume of SEEG data gathered in the F-TRACT database and analyze data from nearly one thousand SEEG implantations in order to verify whether stimulation and recording from the same shaft influence the EP pattern.

**Results**

We found that when the stimulated and the recording contacts were located on the same shaft, the mean and median amplitudes of a EP are greater, and its mean and median latencies are smaller than when the contacts were located on different shafts. This effect is small (Cohen's d ~ 0.1), but robust (p-value < 10⁻³) across the SEEG database.

**Comparison with Existing Method(s)**

Our study is the first one to address this question. Due to the choice of commonly used EP features, our method is congruent with other studies.

**Conclusions**

The magnitude of the reported effect does not obligate all standard analyses to correct for it, unless they aim at high precision. The source of the effect is not clear. Manufacturers of SEEG electrodes could examine it and potentially minimize the effect in their future products.
# Introduction

Stereotactic electroencephalography (SEEG) is used in the presurgical evaluation of patients with epilepsy and it recently underwent an expansion of use in medical centers worldwide. The SEEG electrodes are used not only for recording, but also for single pulse electrical stimulation (SPES) of neuronal tissue to perform functional brain mapping and to elicit seizures. It is known that such stimulation can evoke brain activity in regions that are connected to the stimulated site, which e.g. can lead to the development of connectivity atlases using large group analyses (Donos et al., 2016; Trebaul et al., 2018; Lemaréchal et al., 2022; Jedynak, et al., 2023). It is known, however, that the detailed specifics of such connectivities may depend on the particularities of the stimulation protocol.

A number of studies were dedicated to the placement of the SEEG electrodes (Vakharia et al., 2017) as well as to exploring how stimulation parameters affect the measurements (Donos et al., 2016; Kundu et al., 2020). In particular, Jedynak, et al. (2023) and Trebaul et al. (2018) studied how distance between the stimulating and the recording site influences measurement readouts. Parmigiani et al. (2022) studied the placement and angle of an electrode with respect to the white/gray matter interface. Note that not only these factors can influence experiments, but possibly also merely the presence of an electrode shaft itself.

This can be especially relevant when the stimulation and the recording are associated with the same shaft that therefore occupies the space between them where potential interaction could take place. The rationale for studying the potential impact of the shaft is therefore to scrutinize the SEEG methodology and validate if it needs a dedicated correction, either applied in the data analysis stage, or possibly electrodes manufacturing process.

Furthermore, knowing how the shaft itself affects the results, would be valuable for theoretical studies of electro-physiological processes.

To our knowledge, no study investigated how the SEEG measurements are affected by whether stimulating and recording contact points are situated on the same electrode shaft or two different shafts. We address this question in our study, by checking if characteristics of the averaged first component of recorded neural response to stimulation, termed here an evoked potential, (EP) vary significantly between the two above-mentioned conditions. To this end, we analyze a large number of SEEG recordings aggregated and preprocessed by the F-TRACT project (Trebaul et al., 2018; Lemaréchal et al., 2022; Jedynak et al., 2023).

This project, by gathering a high volume of data, allowed for whole-brain anatomo-functional connectivity studies providing maps of a number of EP features characterizing stimulation between any two given brain parcels (Trebaul et al., 2018; Lemaréchal et al., 2022; Jedynak et al., 2023). The main provided maps inform about the probability of observing a significant EP, its amplitude and latency. In what follows, in order to conform to these earlier studies, we will focus on these three EP features, while answering the question, whether association of the stimulation and recording to the same electrode shaft affects the results.

# Materials and Methods

The data analyzed in this study come from the F-TRACT database that gathers SEEG recordings during low-frequency (1 Hz) SPES performed in the awake state (David et al., 2013; Trebaul et al., 2018). All patients gave consent to undergo this procedure and to share
their data for research purposes under ethical guidelines of the International Review Board
at INSERM (protocol number: INSERM IRB 14–140) for performing international multicenter
post-processing of clinical data.

The results brought about in this study differentiate between contact pairs located either on
the same or on different electrode shafts and also the results are presented in a function of
distance between these contacts. In order to provide that considered distances have
sufficiently high statistics, we chose electrode models with consistent geometry, in particular
having contacts separated by a multiplicative of a constant spacing distance (3.5 mm). This
requirement motivated our choice for a short list of electrode producers, being Alcis
(http://www.alcis.net/en), Dixi (https://diximedical.com) and PMT
(http://www.pmtcorp.com/seeg.html). The following electrode models were used: Alcys:
2069-EPC-15E-20; Dixi: D08-12AM, D08-15AM, D08-18AM, D08-10AM, D08-08AM, D08-
05AM; PMT: D08-16A, D08-14A.

The data registered with electrodes of the chosen type were collected from 20 medical
centers from 966 implantations in 920 patients, 458 male, 460 female, 2 unspecified. The
average age of patients was 24 +/- std 14 and the average number of contact points per
implantation 111 +/- std 33. We considered in total (i.e. in the whole range of distance
between the stimulation and the recording) 6,148,278 recordings from 55,836 stimulations
performed in 78% (22%) cases with biphasic (monophasic) pulses with average width ~1
ms, current intensity 3.2 mA +/- std 1.2 and charge 3.3 uC +/- std 1.5.

The exact signal processing procedure is described in (Trebaul et al., 2018). In short, first we
identified bad channels with a machine learning algorithm (Tuyisenge et al., 2018)
supervised by trained personnel. Second, signals were re-referenced to bipolar montage.
Therefore, each single signal to be further analyzed, followed from recordings performed
with two adjacent contacts. Similarly, two neighboring contacts were involved in a
stimulation, since they served as a cathode and an anode. Third, stimulation artifacts were
removed and band-pass filtering between 1 Hz and 45 Hz was applied. Then, signals were
baseline corrected and z-scored with respect to [-400, -10] ms interval before stimulation. A
response was considered a significant EP if its absolute value exceeded a z-score threshold
Z=5 within 800 ms after stimulation. If it was the case, the time elapsed until the occurrence
of the first peak exceeding the threshold was considered the EP latency. The frequentist
probability of connectivity is defined as the proportion of evoked potentials exceeding the z-
score threshold, over all evoked potentials. We computed the mean and median amplitude
and latency along with probability as the function of distance between the stimulating and the
recording sites, considering fine bins of 0.5 mm length that allow to well capture contact
spacing on electrode shafts. We presented data falling into the inter-site distance range from
zero to ~5 cm. By a site, we mean an averaged position (point in between) of the two
electrode contacts involved in stimulation or recording. This introduction of spatial
dependence is motivated by the fact that probability, amplitude and latency all strongly
depend on distance (Trebaul et al., 2018; Jedynak, et al., 2023), so we verify if the studied
effect depends on it too. Then, we compare the computed values, corresponding to the
same distance, but derived from two different conditions: when stimulating contact points
were located on the same electrode shaft as the recording contacts points (condition
"same") and when they were located on different shafts (condition "different"). We compute
p-values in order to assess whether the null hypothesis of equality between the conditions
can be rejected. To this end we employ Welch's t-test in the case of amplitudes and
latencies. When comparing probabilities, we use the test of proportions comparison. Its Z-statistics is given by:

$$Z = \frac{|p_1 - p_2|}{\sqrt{p(1-p)(1/n_1 + 1/n_2)}}$$

where $p_1$ and $p_2$ are the two probabilities in the two conditions, $n_1$ and $n_2$ are the corresponding total numbers of measurements, and $p = (p_1 * n_1) + (p_2 * n_2) / (n_1 + n_2)$. With the assumption of normality, from the Z-statistics we derive p-values that we correct for false discovery with the Benjamini-Hochberg method. When these values are very small, we report them thresholded, e.g. when $p \sim 10^{-30}$, we write $p < 1E-9$. Finally, to quantify the effect size, we provide Cohen's d.

## Results

<figure><img src="image_2.png" /><figcaption>Figure 1. The effect that the electrode shaft has on EP statistics. In all panels black (gray) refers to the setup where the stimulating and the recording contacts were located on the same (different) electrode shaft(s). Panel A shows stacked histograms of the number of recordings as a function of the Euclidean distance between the stimulating and the recording sites. Panel B shows the frequentist probability for observing a significant EP at the recording site after stimulation at the stimulation site. Panel C (D) shows statistics of the amplitude (latency) of the first peaks of significant EPs. In two last panels means are marked with dots and medians with stars. p-values ("p") and Cohen's d ("d") are shown where applicable. All panels share the abscissa axis indicating distance between the stimulating and the recording sites.</figcaption></figure>
In this section we present a comparison of descriptive statistics (such as mean and median) of features of EPs. The results are presented in Figure 1. Panel A of this figure shows histograms of the number of recordings (the number of recorded responses to stimulations that may show an EP) as a function of distance between the stimulating and the recording sites. The two histograms in panel A are stacked. The black histogram shows, as anticipated, that contact pairs located on the same electrode implant are distant by a multiplicative of 3.5 mm. Panel B shows probability for observing a significant EP at the recording site (see Materials and Methods for details). This probability is greater in the "same" condition, for example for distance dist = 10.5 mm, the probability obtained in the "same" condition p<sub>same</sub> = 0.9 whereas the probability obtained in the "diff" condition p<sub>diff</sub> = 0.83. Similarly, for dist = 21 mm it is p<sub>same</sub> = 0.66, p<sub>diff</sub> = 0.57 and for dist = 31.5 mm, p<sub>same</sub> = 0.41, p<sub>diff</sub> = 0.37. Over these distance bins where this condition had significant inferential statistics, we indicate p-values, being very small (< 10<sup>-9</sup>) for all distances smaller than 49 mm.

Panel C displays means (dots) and medians (stars) of amplitudes of significant EPs. Overally, both these statistics are greater for the “same” condition. For example, for distance dist = 10.5 mm, median amplitude obtained in the “same” condition is A<sub>same</sub> = 10.8 and A<sub>diff</sub> = 9.6; for dist = 21 mm, A<sub>same</sub> = 8 and A<sub>diff</sub> = 7.66; for dist = 31.5 mm, A<sub>same</sub> = 7 and A<sub>diff</sub> = 6.9. Numbers of measurements considered per each bin equal the total number of recordings (shown in panel A) multiplied by the fraction of the significant ones (frequentist probability shown in panel B). Additionally, we provide p-values informing about the significance of the difference between setups. Except for one distance bin (dist = 35 mm), they indicate significance of the reported effect. We also specify Cohen's d values informing about the effect size. To do that, we subtract the mean obtained in the “different” condition from the one corresponding to the “same” condition. These values indicate small effects (d ~ 0.1) for distances dist < 20 mm or dist > 40 mm, and very small elsewhere (d ~ 0.05). Panel D follows the same convention as panel C, but it shows latencies of appearances of significant EPs. In the “same” condition the mean and median are smaller than in the “different” condition. For example, for distance dist = 10.5 mm, median latency obtained in the “same” condition is L<sub>same</sub> = 25 ms and L<sub>diff</sub> = 26 ms; for dist = 21 mm, L<sub>same</sub> = 34 ms and L<sub>diff</sub> = 43 ms; for dist = 31.5 mm, L<sub>same</sub> = 44 ms and L<sub>diff</sub> = 54 ms and for dist = 49 mm, L<sub>same</sub> = 74 ms and L<sub>diff</sub> = 95 ms. In the latency case, the p-values are smallest, indicating significant differences regardless of the distance, and Cohen's d has largest absolute values ~ (0.1, 0.2). We verified that excluding from analysis signals in which response appeared very early (< 10 ms) or late (> 50 ms) does not abrogate the presented effect (Figures S1 and S2 in Supplementary Materials). Similarly considering very late peaks (> 200 ms) insignificant (Figure S3). The effect is considerably reduced when signals with early responses (< 50 ms) are excluded (Figure S4).

In summary, our results show that the probability for observing a significant EP, and its
related amplitude are greater on average when the stimulating and the recording contact
points are located on the same electrode shaft. Moreover, the mean latency of EPs in this
condition is smaller than when stimulation and recording are performed between two
different electrode shafts. These observations lead to the conclusion that the implanted
material affects the measured EP characteristics. In the following section, we discuss
potential scenarios that could underlie this effect.
Discussion

In this study, we investigated if the intracranial electrode implant has an impact on EP responses. To that aim we analyzed nearly one thousand SEEG human implantations gathered in the F-TRACT dataset (Trebaul et al., 2018; Lemaréchal et al., 2022; Jedynak et al., 2023). We computed typical aggregated features characterizing EPs, namely the probability of observing a significant EP, as well as its amplitude and latency. We carried out pairwise comparisons of measurement means corresponding to these two conditions but having the same distance between the stimulating and the recording sites. For each EP feature, we performed 13 such comparisons covering the distance from 0 to 5 cm. In the “same shaft” condition, the probability and amplitude were systematically greater. Since the probability is computed from amplitude values, concordance between changes to these two features could have been expected, but was not certain, since these two measures capture different group properties of the EP sample. Similarly, the latency of the first peak in the “same” condition was lower than in the “different” condition. We showed that this effect is strongly statistically significant (as indicated by low p-values), but small for latencies and very small for amplitudes (as indicated by Cohen’s d values).

Drawing these conclusions was aided by the large number of available measurements
counting in tens of thousands per one distance bin (Figure 1A). Such a big volume of data
allowed us to report a subtle group-level effect with high confidence. In this section we
suggest and discuss a number of factors that could explain our result. Before we list them,
however, we note that the fact that we observe smaller, but non-zero mean and median
latencies in the “same” condition (than in the “different” condition) does not necessarily mean
that all the measured latencies were much greater than zero. Some individual
measurements could be close to or even equal to zero. If in the “same” condition there were
more such measurements than in the “different” condition, then the mean and the median in
the former case would be smaller than in the latter case, just as we observe it here. Hence,
we consider it purposeful to discuss potential mechanisms underlying the observed effect,
even if they classify as zero-lag interactions.

Current leakage could be one of the factors accounting for a fast interaction. We consider it unlikely that it could occur through the electrode implant shaft, because it would mean that the insulation provided between the contact points is insufficient. Moreover, in such a scenario, the leakage would primarily appear between the stimulating contacts, without affecting any recording ones. Charge transfer through the electrode-electrolyte interface is more likely, although expected to be small (Machado et al., 2023). Finally, extracellular fluid electrolyte ions, in response to stimulation, could move along the electrode shaft not only locally between the stimulating contacts, but also the recording ones.

Furthermore, an instantaneous interaction could pertain to the stimulation artifact, caused
not by charge displacement, like in the previous case, but by electrodynamic interaction.
According to theory, a non-stationary current flowing along an implant shaft would emit an
electromagnetic wave with highest energy radiated perpendicularly to the shaft and no
energy emitted axially. In such a case, contacts on the same electrode implant should not be
affected by the stimulation pulse. Nevertheless, all contacts located on the same implant
may be electrodynamically coupled via the stimulating and recording hardware, e.g.
connecting wires, that due to the small size of the electrode implant might not be efficiently shielded. Therefore, an artifact arising between contact points on the same electrode shaft could be larger and it could evince different properties than an artifact observed between different implants and hence could be removed less effectively by our algorithm.

In order to test for the presence of quasi-instantaneous interactions in the reported effect, we discarded from analysis signals in which peaks appeared within the first 10 ms after stimulation, where we expect stimulation artifacts to appear (David et al., 2013). We noted that this data selection did not abolish the presented effect (Figure S1). Neither did considering insignificant peaks appearing later than 200 ms (Figure S3). The latter verification we performed also in order to confirm if the reported effect is present in EP-derived brain connectivity atlases computed with this rule (Trebaul et al., 2018; Lemaréchal et al., 2022; Jedynak et al., 2023). Due to the small size of the presented here effect and high statistics utilized in these atlases, it does not appear likely that the effect could introduce spurious links to connectivity maps. It could, nevertheless, enhance connectivity of close parcels. Finally, considering separately signals with early (< 50 ms, Figure S2) and late (> 50 ms, Figure S4) responses shows that the effect originates in the former ones, thus affecting N1 rather than N2 components.

The results introduced in this and other works (e.g. Crowther et al., 2019, Kundu et al., 2020, Jedynak et al., 2023) are often presented as a function of distance between the stimulating and the recording sites. Their positions are approximated, e.g. as in our case, by centers of masses of the stimulating and the recording contacts. Such procedure disregards the spatial extension of contacts that in the case of the here considered electrodes equals 2 mm with 1.5 mm wide gap between them. Effectively, it means that two contacts located on the same electrode shaft have their extremities closer than two contacts located on e.g. parallel shafts and separated by the same distance as in the first condition. This effect is even stronger for bipolar (and thus more spatially extended) contacts. Even if the interaction between the stimulation and the recording sites is not direct, but rather mediated by studied neuronal activity, the reduced distance between contact extremities (with respect to their centers) could contribute to the decrease of latency as well as the increase of amplitude and probability because all these quantities change in this way with distance between contact points (Trebaul et al., 2018; 2022; Jedynak et al., 2023). On the other hand, in this scenario we could expect approximately constant latency shift between the "same" and "different" conditions, whereas here we reported a shift that grows with distance (Figure 1D).

In this short report we demonstrated that SEEG recordings of evoked potentials are influenced when the stimulating and the recording sites are located on the same electrode shaft. We do not attribute this effect to a particular electrode manufacturer or model. This effect is small, so correcting for it in a conventional SEEG analysis does not seem obligatory. Nevertheless, it may be useful to consider it in meticulous research aiming at high precision and/or studies presenting EP features in a function of distance (the above-mentioned connectivity atlases, (Crowther et al., 2019, Kundu et al., 2020). If individual recordings are considered, e.g. in the clinical context, then those registered on the stimulating shaft could be considered with lower confidence and classified as potential false positives. Finally, we see the application of our findings for modeling studies (Carvallo et al., 2019; Mercadal et al., 2023; Alonso et al., 2023) that could verify if their theoretical approach reproduces and
explains our findings, the exact extent of which, provided by our study, would help to
improve their theoretical frameworks.

Acknowledgements

We acknowledge the work of the following people, involved in the past in preparation of the
F-TRACT dataset: François Tadel, Lena Trebaul, Pierre Deman, Viateur Tuyisenge, Jean-
Didier Lemarechal, Carole Saubat, Raouf Zouglech, Maëlle Gueguen, Gina Catalina Reyes
Mejia, Leila Ayoubian, Etienne Hugues.

Competing Interests

The authors declare no conflict of interest.

Funding

The research leading to these results has received funding from the European Research
Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC
Grant Agreement no. 616268 F-TRACT, the European Union's Horizon 2020 Framework
Programme for Research and Innovation under Specific Grant Agreement No. 785907 and
945539 (Human Brain Project SGA2 and SGA3), and from the Agence Nationale de la
Recherche grant number ANR-21-NEUC-0005-01.

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