Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods

Abstract:

Background: Intracranial electrodes are typically localized from post-implantation CT artifacts. Automatic algorithms localizing low signal-to-noise ratio artifacts and high-density electrode arrays are missing. Additionally, implantation of grids/strips introduces brain deformations, resulting in registration errors when fusing post- implantation CT and pre-implantation MR images. Brain-shift compensation methods project electrode coordinates to cortex, but either fail to produce smooth solutions or do not account for brain deformations. New methods: We first introduce GridFit, a model-based fitting approach that simultaneously localizes all electrodes’ CT artifacts in grids, strips, or depth arrays. Second, we present CEPA, a brain-shift compensation algorithm combining orthogonal-based projections, spring-mesh models, and spatial regularization constraints. Results: We tested GridFit on ~6000 simulated scenarios. The localization of CT artifacts showed robust performance under difficult scenarios, such as noise, overlaps, and high-density implants (<1 mm errors). Validation with data from 20 challenging patients showed 99% accurate localization of the electrodes (3160/3192). We tested CEPA brain-shift compensation with data from 15 patients. Projections accounted for simple mechanical deformation principles with <0.4 mm errors. The inter-electrode distances smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. Comparison with existing methods: GridFit succeeded in difficult scenarios that challenged available methods and outperformed visual localization by preserving the inter-electrode distance. CEPA registration errors were smaller than those obtained for well-established alternatives. Additionally, modeling resting-state high-frequency activity in five patients further supported CEPA.

Authors:

• Alejandro Omar Blenkmann

• Sabine Liliana Leske

• Anaïs Llorens

• Jack J. Lin

• Edward F. Chang

• Peter Brunner

• Gerwin Schalk

• Jugoslav Ivanovic

• Pål Gunnar Larsson

• Robert Thomas Knight

• Tor Endestad

• Anne-Kristin Solbakk

Date: 2024

DOI: https://doi.org/10.1016/j.jneumeth.2024.110056

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Decision and response monitoring during working memory are sequentially represented in the human insula

Abstract:

Emerging research supports a role of the insula in human cognition. Here, we used intracranial EEG to investigate the spatiotemporal dynamics in the insula during a verbal working memory (vWM) task. We found robust effects for theta, beta, and high frequency activity (HFA) during probe presentation requiring a decision. Theta band activity showed differential involvement across left and right insulae while sequential HFA modulations were observed along the anteroposterior axis. HFA in anterior insula tracked decision making and subsequent HFA was observed in posterior insula after the behavioral response. Our results provide electrophysiological evidence of engagement of different insula subregions in both decision-making and response monitoring during vWM and expand our knowledge of the role of the insula in complex human behavior.

Authors:

• Anaïs Llorens

• Ludovic Bellier

• Alejandro O. Blenkmann

• Jugoslav Ivanovic

• Pål G. Larsson

• Jack J. Lin

• Tor Endestad

• Anne-Kristin Solbakk

• Robert T. Knight

Date: 2023

DOI: https://doi.org/10.1016/j.isci.2023.107653

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Music can be reconstructed from human auditory cortex activity using nonlinear decoding models

Abstract:

Music is core to human experience, yet the precise neural dynamics underlying music perception remain unknown. We analyzed a unique intracranial electroencephalography (iEEG) dataset of 29 patients who listened to a Pink Floyd song and applied a stimulus reconstruction approach previously used in the speech domain. We successfully reconstructed a recognizable song from direct neural recordings and quantified the impact of different factors on decoding accuracy. Combining encoding and decoding analyses, we found a right-hemisphere dominance for music perception with a primary role of the superior temporal gyrus (STG), evidenced a new STG subregion tuned to musical rhythm, and defined an anterior–posterior STG organization exhibiting sustained and onset responses to musical elements. Our findings show the feasibility of applying predictive modeling on short datasets acquired in single patients, paving the way for adding musical elements to brain–computer interface (BCI) applications.

Authors:

• Ludovic Bellier

• Anaïs Llorens

• Déborah Marciano

• Aysegul Gunduz

• Gwerwin Schalk

• Peter Brunner

• Robert T. Knight

Date: 2023

DOI: https://doi.org/10.1371/journal.pbio.3002176

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Advances in human intracranial electroencephalography research, guidelines and good practices

Abstract:

Since the second half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Authors:

• Manuel R. Mercier

• Anne-Sophie Dubarry

• François Tadel

• Pietro Avanzini

• Nikolai Axmacher

• Dillan Cellier

• Maria Del Vecchio

• Liberty S. Hamilton

• Dora Hermes

• Michael J. Kahana

• Robert T. Knight

• Anais Llorens

• Pierre Megevand

• Lucia Melloni

• Kai J. Miller

• Vitória Piai

• Aina Puce

• Nick F. Ramsey

• Caspar M. Schwiedrzik

• Sydney E. Smith

• Arjen Stolk

• Nicole C. Swann

• Mariska J Vansteensel

• Bradley Voytek

• Liang Wang

• Jean-Philippe Lachaux

• Robert Oostenveld

Date: 2022

DOI: https://doi.org/10.1016/j.neuroimage.2022.119438

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Encoding and decoding analysis of music perception using intracranial EEG

Abstract:

Music perception engages multiple brain regions, however the neural dynamics of this core human experience remains elusive. We applied predictive models to intracranial EEG data from 29 patients listening to a Pink Floyd song. We investigated the relationship between the song spectrogram and the elicited high-frequency activity (70-150Hz), a marker of local neural activity. Encoding models characterized the spectrotemporal receptive fields (STRFs) of each electrode and decoding models estimated the population-level song representation. Both methods confirmed a crucial role of the right superior temporal gyri (STG) in music perception. A component analysis on STRF coefficients highlighted overlapping neural populations tuned to specific musical elements (vocals, lead guitar, rhythm). An ablation analysis on decoding models revealed the presence of unique musical information concentrated in the right STG and more spatially distributed in the left hemisphere. Lastly, we provided the first song reconstruction decoded from human neural activity.

Authors:

• Ludovic Bellier

• Anaïs Llorens

• Déborah Marciano

• Gerwin Schalk

• Peter Brunner

• Robert T. Knight

• Brian N. Pasley

Date: 2022

DOI: https://doi.org/10.1101/2022.01.27.478085

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Gender bias in academia: A lifetime problem that needs solutions

Summary:

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow, and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in science. Here, we argue that gender bias is not a single problem but manifests as a collection of distinct issues that impact researchers’ lives. We disentangle these facets and propose concrete solutions that can be adopted by individuals, academic institutions, and society.

Authors:

• Anaïs Llorens

• Athina Tzovara

• Ludovic Bellier

• Ilina Bhaya-Grossman

• Aurélie Bidet-Caulet

• William K Chang

• Zachariah R Cross

• Rosa Dominguez-Faus

• Adeen Flinker

• Yvonne Fonken

• Mark A Gorenstein

• Chris Holdgraf

• Colin W Hoy

• Maria V Ivanova

• Richard T Jimenez

• Soyeon Jun

• Julia WY Kam

• Celeste Kidd

• Enitan Marcelle

• Deborah Marciano

• Stephanie Martin

• Nicholas E Myers

• Karita Ojala

• Anat Perry

• Pedro Pinheiro-Chagas

• Stephanie K Riès

• Ignacio Saez

• Ivan Skelin

• Katarina Slama

• Brooke Staveland

• Danielle S Bassett

• Elizabeth A Buffalo

• Adrienne L Fairhall

• Nancy J Kopell

• Laura J Kray

• Jack J Lin

• Anna C Nobre

• Dylan Riley

• Anne-Kristin Solbakk

• Joni D Wallis

• Xiao-Jing Wang

• Shlomit Yuval-Greenberg

• Sabine Kastner

• Robert T Knight

• Nina F Dronkers

Date: 2021

DOI: https://doi.org/10.1016/j.neuron.2021.06.002

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The brain tracks auditory rhythm predictability independent of selective attention

Abstract:

The brain responds to violations of expected rhythms, due to extraction- and prediction of the temporal structure in auditory input. Yet, it is unknown how probability of rhythm violations affects the overall rhythm predictability. Another unresolved question is whether predictive processes are independent of attention processes. In this study, EEG was recorded while subjects listened to rhythmic sequences. Predictability was manipulated by changing the stimulus-onset-asynchrony (SOA deviants) for given tones in the rhythm. When SOA deviants were inserted rarely, predictability remained high, whereas predictability was lower with more frequent SOA deviants. Dichotic tone-presentation allowed for independent manipulation of attention, as specific tones of the rhythm were presented to separate ears. Attention was manipulated by instructing subjects to attend to tones in one ear only, while keeping the rhythmic structure of tones constant. The analyses of event-related potentials revealed an attenuated N1 for tones when rhythm predictability was high, while the N1 was enhanced by attention to tones. Bayesian statistics revealed no interaction between predictability and attention. A right-lateralization of attention effects, but not predictability effects, suggested potentially different cortical processes. This is the first study to show that probability of rhythm violation influences rhythm predictability, independent of attention.

Authors:

• Maja D Foldal

• Alejandro O Blenkmann

• Anaïs Llorens

• Robert T Knight

• Anne-Kristin Solbakk

• Tor Endestad

Date: 2020

DOI: https://doi.org/10.1038/s41598-020-64758-y

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Preservation of Interference Effects in Working Memory After Orbitofrontal Damage

Abstract:

Orbitofrontal cortex (OFC) is implicated in multiple cognitive processes, including inhibitory control, context memory, recency judgment, and choice behavior. Despite an emerging understanding of the role of OFC in memory and executive control, its necessity for core working memory (WM) operations remains undefined. Here, we assessed the impact of OFC damage on interference effects in WM using a Recent Probes task based on the Sternberg item-recognition task (1966). Subjects were asked to memorize a set of letters and then indicate whether a probe letter was presented in a particular set. Four conditions were created according to the forthcoming response (“yes”/“no”) and the recency of the probe (presented in the previous trial set or not). We compared behavioral and electroencephalography (EEG) responses between healthy subjects (n = 14) and patients with bilateral OFC damage (n = 14). Both groups had the same recency pattern of slower reaction time (RT) when the probe was presented in the previous trial but not in the current one, reflecting the proactive interference (PI). The within-group electrophysiological results showed no condition difference during letter encoding and maintenance. In contrast, event-related potentials (ERPs) to probes showed distinct within-group condition effects, and condition by group effects. The response and recency effects for controls occurred within the same time window (300–500 ms after probe onset) and were observed in two distinct spatial groups including right centro-posterior and left frontal electrodes. Both clusters showed ERP differences elicited by the response effect, and one cluster was also sensitive to the recency manipulation. Condition differences for the OFC group involved two different clusters, encompassing only left hemisphere electrodes and occurring during two consecutive time windows (345–463 ms and 565–710 ms). Both clusters were sensitive to the response effect, but no recency effect was found despite the behavioral recency effect. Although the groups had different electrophysiological responses, the maintenance of letters in WM, the evaluation of the context of the probe, and the decision to accept or reject a probed letter were preserved in OFC patients. The results suggest that neural reorganization may contribute to intact recency judgment and response after OFC damage.

Authors:

• Anaïs Llorens

• Ingrid Funderud

• Alejandro O Blenkmann

• James Lubell

• Maja Foldal

• Sabine Leske

• Rene Huster

• Torstein R Meling

• Robert T Knight

• Anne-Kristin Solbakk

• Tor Endestad

Date: 2020

DOI: https://doi.org/10.3389/fnhum.2019.00445

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Auditory deviance detection in the human insula: An intracranial EEG study

Abstract:

The human insula is known to be involved in auditory processing, but knowledge about its precise functional role and the underlying electrophysiology is limited. To assess its role in automatic auditory deviance detection we analyzed the EEG high frequency activity (HFA; 75–145 Hz) and ERPs from 90 intracranial insular channels across 16 patients undergoing pre-surgical intracranial monitoring for epilepsy treatment. Subjects passively listened to a stream of standard and deviant tones differing in four physical dimensions: intensity, frequency, location or time. HFA responses to auditory stimuli were found in the short and long gyri, and the anterior, superior, and inferior segments of the circular sulcus of the insular cortex. Only a subset of channels in the inferior segment of the circular sulcus of the insula showed HFA deviance detection responses, i.e., a greater and longer latency response to specific deviants relative to standards. Auditory deviancy processing was also later in the insula when compared with the superior temporal cortex. ERP results were more widespread and supported the HFA insular findings. These results provide evidence that the human insula is engaged during auditory deviance detection.

Authors:

• Alejandro O Blenkmann

• Santiago Collavini

• James Lubell

• Anaïs Llorens

• Ingrid Funderud

• Jugoslav Ivanovic

• Pål G Larsson

• Torstein R Meling

• Tristan Bekinschtein

• Silvia Kochen

• Tor Endestad

• Robert T Knight

• Anne-Kristin Solbakk

Date: 2019

DOI: https://doi.org/10.1016/j.cortex.2019.09.002

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