The Lab Streaming Layer for Synchronized Multimodal Recording

Kothe, Christian; Shirazi, Seyed Yahya; Stenner, Tristan; Medine, David; Boulay, Chadwick; Grivich, Matthew I.; Mullen, Tim; Delorme, Arnaud; Makeig, Scott

doi:10.1101/2024.02.13.580071

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…Experimental markers (e.g., sound markers) were generated using the lab streaming layer library 48 (v1.14). The ECG recording laptop and EEG recording computer were connected via Lan.…”

Section: Methodsmentioning

confidence: 99%

Sound perception in realistic surgery scenarios: Towards EEG-based auditory work strain measures for medical personnel

Rosenkranz,

Haupt,

Jaeger

et al. 2024

Preprint

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Surgical personnel face various stressors in the workplace, including environmental sounds. Mobile electroencephalography (EEG) offers a promising approach for objectively measuring how individuals perceive sounds. In this study, we utilized mobile EEG to explore how a realistic soundscape is perceived during simulated laparoscopic surgery. To examine the varying demands placed on personnel in different situations, we manipulated the cognitive demand during the surgical task, using a memory task. To assess responses to the soundscape, we calculated event-related potentials for distinct sound events and temporal response functions for the ongoing soundscape. Although participants reported varying degrees of demand under different conditions, no significant effects were observed on surgical task performance or EEG parameters. However, changes in surgical task performance and EEG parameters over time were noted, while subjective results remained consistent over time. These findings highlight the importance of using multiple measures to fully understand the complex relationship between sound processing and cognitive demand. Furthermore, in the context of combined EEG and audio recordings in real-life scenarios, sparse representations of the soundscape have advantages over more detailed representations. Our results indicate that both types of representations are equally effective in eliciting neural responses. Overall, this study marks a significant step towards objectively investigating sound processing in applied settings.

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“…Experimental markers (e.g., sound markers) were generated using the lab streaming layer library 48 (v1.14). The ECG recording laptop and EEG recording computer were connected via Lan.…”

Section: Methodsmentioning

confidence: 99%

Sound perception in realistic surgery scenarios: Towards EEG-based auditory work strain measures for medical personnel

Rosenkranz,

Haupt,

Jaeger

et al. 2024

Preprint

View full text Add to dashboard Cite

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“…Data from the LUMO device was captured using the LUMO software application from GowerLabs, which streams the fNIRS data over the Lab Streaming Layer (LSL) signal transport protocol (Kothe et al, 2024 ). This LSL data stream was in turn captured by the NeuroPype Experimenter Recorder software from Intheon 6 and recorded to disk in XDF format.…”

Section: Methodsmentioning

confidence: 99%

On decoding of rapid motor imagery in a diverse population using a high-density NIRS device

Kothe,

Hanada,

Mullen

et al. 2024

Front. Neuroergonomics

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IntroductionFunctional near-infrared spectroscopy (fNIRS) aims to infer cognitive states such as the type of movement imagined by a study participant in a given trial using an optical method that can differentiate between oxygenation states of blood in the brain and thereby indirectly between neuronal activity levels. We present findings from an fNIRS study that aimed to test the applicability of a high-density (>3000 channels) NIRS device for use in short-duration (2 s) left/right hand motor imagery decoding in a diverse, but not explicitly balanced, subject population. A side aim was to assess relationships between data quality, self-reported demographic characteristics, and brain-computer interface (BCI) performance, with no subjects rejected from recruitment or analysis.MethodsBCI performance was quantified using several published methods, including subject-specific and subject-independent approaches, along with a high-density fNIRS decoder previously validated in a separate study.ResultsWe found that decoding of motor imagery on this population proved extremely challenging across all tested methods. Overall accuracy of the best-performing method (the high-density decoder) was 59.1 +/– 6.7% after excluding subjects where almost no optode-scalp contact was made over motor cortex and 54.7 +/– 7.6% when all recorded sessions were included. Deeper investigation revealed that signal quality, hemodynamic responses, and BCI performance were all strongly impacted by the hair phenotypical and demographic factors under investigation, with over half of variance in signal quality explained by demographic factors alone.DiscussionOur results contribute to the literature reporting on challenges in using current-generation NIRS devices on subjects with long, dense, dark, and less pliable hair types along with the resulting potential for bias. Our findings confirm the need for increased focus on these populations, accurate reporting of data rejection choices across subject intake, curation, and final analysis in general, and signal a need for NIRS optode designs better optimized for the general population to facilitate more robust and inclusive research outcomes.

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“…A broad experiment framework and term for this—mobile brain/body imaging (MoBI)—was first proposed by one of us 15 years ago (Makeig, 2009 ; Makeig et al, 2009 ). Virtual- and augmented-reality experiment designs, movie- or annotation-viewing and videogame playing experiments also provide new challenges that will require continued development of event annotation methods as well as data recording (Kothe et al, 2012 , 2024 ) and analysis approaches (Logie and Donaldson, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Events in context—The HED framework for the study of brain, experience and behavior

Makeig,

Robbins

2024

Front. Neuroinform.

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The brain is a complex dynamic system whose current state is inextricably coupled to awareness of past, current, and anticipated future threats and opportunities that continually affect awareness and behavioral goals and decisions. Brain activity is driven on multiple time scales by an ever-evolving flow of sensory, proprioceptive, and idiothetic experience. Neuroimaging experiments seek to isolate and focus on some aspect of these complex dynamics to better understand how human experience, cognition, behavior, and health are supported by brain activity. Here we consider an event-related data modeling approach that seeks to parse experience and behavior into a set of time-delimited events. We distinguish between event processes themselves, that unfold through time, and event markers that record the experiment timeline latencies of event onset, offset, and any other event phase transitions. Precise descriptions of experiment events (sensory, motor, or other) allow participant experience and behavior to be interpreted in the context either of the event itself or of all or any experiment events. We discuss how events in neuroimaging experiments have been, are currently, and should best be identified and represented with emphasis on the importance of modeling both events and event context for meaningful interpretation of relationships between brain dynamics, experience, and behavior. We show how text annotation of time series neuroimaging data using the system of Hierarchical Event Descriptors (HED; https://www.hedtags.org) can more adequately model the roles of both events and their ever-evolving context than current data annotation practice and can thereby facilitate data analysis, meta-analysis, and mega-analysis. Finally, we discuss ways in which the HED system must continue to expand to serve the evolving needs of neuroimaging research.

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The Lab Streaming Layer for Synchronized Multimodal Recording

Cited by 5 publications

References 21 publications

Sound perception in realistic surgery scenarios: Towards EEG-based auditory work strain measures for medical personnel

Sound perception in realistic surgery scenarios: Towards EEG-based auditory work strain measures for medical personnel

On decoding of rapid motor imagery in a diverse population using a high-density NIRS device

Events in context—The HED framework for the study of brain, experience and behavior

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