Learn to interpret voltage maps: an atlas of topographies

Foged, Mette Thrane; Scherg, Michael; Fabricius, Martin; Beniczky, Sándor

doi:10.1684/epd.2021.1396

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…At the same time, since the weighted RDM matrix entries appear in the form of non-linearly transformed channel data (squared distances, functions of classification accuracy, etc.) the coefficients of such a mixing can not be transformed into electromagnetically meaningful patterns and are therefore difficult to interpret (Foged et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Representational dissimilarity component analysis (ReDisCA)

Ossadtchi,

Semenkov,

Zhuravleva

et al. 2024

Preprint

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The principle of Representational Similarity Analysis (RSA) posits that neural representations reflect the structure of encoded information, allowing exploration of spatial and temporal organization in brain information processing. Traditional RSA when applied to EEG or MEG data faces challenges in accessing activation timeseries at the brain source level due to modeling complexities and insufficient geometric/anatomical data. To address this, we introduce Representational Dissimilarity Component Analysis (ReDisCA), a method for estimating spatial-temporal components in EEG or MEG responses aligned with a target representational dissimilarity matrix (RDM). ReDisCA yields informative spatial filters and associated topographies, offering insights into the location of "representationally relevant" sources. Applied to evoked response timeseries, ReDisCA produces temporal source activation profiles with the desired RDM. Importantly, while ReDisCA does not require inverse modeling its output is consistent with EEG and MEG observation equation and can be used as an input to rigorous source localization procedures. Demonstrating ReDisCA's efficacy through simulations and comparison with conventional methods, we show superior source localization accuracy and apply the method to a real EEG dataset, revealing physiologically plausible representational structures without inverse modeling. ReDisCA adds to the family of inverse modeling free methods such as independent component analysis (Makeig et al., 1995), Spatial spectral decomposition (Nikulin et al., 2011) and Source power comodulation (Dahne et al., 2014) designed for extraction sources with desired properties from EEG or MEG data. Extending its utility beyond EEG and MEG analysis, ReDisCA is likely to find application in fMRI data analysis and exploration of representational structures emerging in multilayered artificial neural networks.

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Section: Discussionmentioning

confidence: 99%

Representational dissimilarity component analysis (ReDisCA)

Ossadtchi,

Semenkov,

Zhuravleva

et al. 2024

Preprint

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“…In our everyday thinking and cognitive activities, the frontal and parietal lobes are typically the most active brain regions (Sammer et al, 2007). Electroencephalography (EEG) is an important tool used to assess brain function by visualizing fluctuating brain activity on a two-dimensional plane (Foged et al, 2022;Lassagne et al, 2022). It records the spontaneous electrical activity of pyramidal dendrites in the brain cortex, effectively reflecting the degree of brain fatigue and cortical excitability (Lin et al, 2015).…”

Section: Physiological Methodologymentioning

confidence: 99%

Effects of indoor lighting environments on paper reading efficiency and brain fatigue: an experimental study

Zhou,

Pan

2023

Front. Built Environ.

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Introduction: This study investigated the influence of indoor lighting environments on paper reading efficiency and brain fatigue to explore lighting parameters that benefit users during various reading durations.Methods: The study was conducted in the Smart Lighting Lab, where 12 participants were tested under different illuminance levels and correlated color temperatures (CCT) for three distinct reading durations. Reading efficiency during the task tests and objective measures of brain activity by monitoring participants’ electroencephalograms (EEGs) were used as key factors to assess participants’ fatigue levels.Results: By analyzing the subjective and objective results, we found that paper reading efficiency was significantly affected by changes in the lighting environment. Also, based on the results of this study, we propose lighting recommendations for paper reading tasks of different durations. For a 15 min reading task, the lighting condition of 500 lux-6,500 K were the most efficient for reading; for a 30 min reading task, 500 lux-4,000 K lighting environments were found to be the most effective; and 750 lux-6,500 K was the best lighting environment for a 60 min reading duration.Discussion: These suggestions can serve as a reference for designing indoor lighting environment. In addition, they provide guidance to researchers and reviewers conducting similar studies.

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“…Furthermore, predominant tangentially orientated neuronal populations generate a voltage distribution with negativities distant from the generators in (common) reference montages. 5 Corresponding phase reversals in bipolar montages then also appear over distant, sometimes contralateral regions. Taking the complete voltage distribution into account, however, reveals a location that again might be much closer to the seizure onset or epileptogenic zone.…”

Section: Interictal Eegmentioning

confidence: 99%

“…The positivity, however, is sometimes subtle and spreads over contralateral contacts especially in radially oriented sources. 5 ESI benefits from having sufficient information available on both components. If only a partial voltage distribution is sampled with incomplete coverage, the resulting ESI may be inaccurate.…”

Section: Electrode Coveragementioning

confidence: 99%

Interictal Electrical Source Imaging

Rampp,

Müller-Voggel,

Hamer

et al. 2023

Journal of Clinical Neurophysiology

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Summary: Interictal electrical source imaging (ESI) determines the neuronal generators of epileptic activity in EEG occurring outside of seizures. It uses computational models to take anatomic and neuronal characteristics of the individual patient into account. The presented article provides an overview of application and clinical value of interictal ESI in patients with pharmacoresistant focal epilepsies undergoing evaluation for surgery. Neurophysiological constraints of interictal data are discussed and technical considerations are summarized. Typical indications are covered as well as issues of integration into clinical routine. Finally, an outlook on novel markers of epilepsy for interictal source analysis is presented. Interictal ESI provides diagnostic performance on par with other established methods, such as MRI, PET, or SPECT. Although its accuracy benefits from high-density recordings, it provides valuable information already when applied to EEG with only a limited number of electrodes with complete coverage. Novel oscillatory markers and the integration of frequency coupling and connectivity may further improve accuracy and efficiency.

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Learn to interpret voltage maps: an atlas of topographies

Cited by 5 publications

References 9 publications

Representational dissimilarity component analysis (ReDisCA)

Representational dissimilarity component analysis (ReDisCA)

Effects of indoor lighting environments on paper reading efficiency and brain fatigue: an experimental study

Interictal Electrical Source Imaging

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