David Brang @dbrang.bsky.social · 04/02/2026Independent Component Analysis (ICA) is important for signal processing but isn't always intuitive. I made a demo to generate EEG, run ICA, and remove blink components, that also works with wav files, letting you move the speakers/mics around to control mixing. dbrang.github.io/EEG-ICA-Demo/ 041
David Brang @dbrang.bsky.social · 26/01/2026EEG requires many neurons aligned so that their electric fields can positively sum to spread up to the scalp. I made a browser-based simulator for my EEG class to visualize how "open fields" contribute to EEG recordings. dbrang.github.io/Open-Closed-... Github: github.com/dbrang/Open-... 0276
David Brang @dbrang.bsky.social · 20/01/2026Interpreting EEG requires understanding how the skull smears electrical fields as they propagate from the cortex. I made a browser-based simulator for my EEG class to visualize how dipole depth/orientation change the topomap. dbrang.github.io/EEG-Dipole-D... Github page: github.com/dbrang/EEG-D... 412749
David Brang @dbrang.bsky.social · 16/07/2025Our department is recruiting! New tenure-track, open rank faculty position in the Department of Psychology at the University of Michigan (emphasis on human cognition and artificial intelligence). apply.interfolio.com/169170 21510
David Brang @dbrang.bsky.social · 06/07/2025New paper with @herveyjumper.bsky.social and Vardhaan Ambati! It shows that causal (DCS+) language cortex in glioma patients has greater ECoG information encoding (higher entropy and linguistic decoding). DCS+ sites showed stronger oscillations and high gamma, enabling prediction of DCS sites. 0123
David Brang @dbrang.bsky.social · 24/05/2025Tissue samples were from healthy cortex (e.g., insular tumor resection), allowing transcriptionally defined neuronal subclasses, including numbers of glutamatergic + GABAergic neurons. This link better enables aperiodic (1/f) slope from EEG/ECoG to be used as a surrogate for cortical excitability. 021
David Brang @dbrang.bsky.social · 24/05/2025New paper with Shawn Hervey-Jumper's lab! As only PART of this project, it validates the relationship between aperiodic slope and cortical excitability using ECoG and single-nuc RNA sequencing in humans. Tissue samples with more excitatory neurons showed flatter aperiodic slope. 2154
David Brang @dbrang.bsky.social · 08/05/2025No other tools currently exist specifically for intraOp ECoG registration. This was a multi-year collaboration with the amazing lab of Shawn Hervey-Jumper and included @senaoten.bsky.social, @sanjeevherr.bsky.social, Vardhaan Ambati, @ysibih.bsky.social, Katie Lu, and Jasleen Kaur. 010
David Brang @dbrang.bsky.social · 08/05/2025Localizing ECoG electrodes from photos alone is challenging (particularly with small craniotomies) and novice undergrads/medical students showed high variability (mean error = 16mm, ICC = .40), compared to experts with neuroanatomy training (mean error = 4mm, ICC = .93). 100
David Brang @dbrang.bsky.social · 08/05/2025ExtraOp ECoG/sEEG localization require a postOp MRI or CT that are unavailable in intraOp contexts. As an alternative, we used preOp MRI imaging, vascular reconstructions, and intraOp photos to place grids along cortical reconstructions, in conforming electrodes to the brain. 130
David Brang @dbrang.bsky.social · 31/03/2025Fourier Wave Explorer lets you create a waveform from 5 sine waves that vary in frequency and amplitude, then shows the individual and composite waveforms, along with the PSD. Github pages: github.com/dbrang/Fouri... github.com/dbrang/Fouri... Features inspired by: github.com/Jezzamonn/fo... 030
David Brang @dbrang.bsky.social · 31/03/2025Fourier Wave Creator lets you either select example waveforms (e.g., square wave, 10hz + 3hz sine wave) or draw your own waveform, then shows the sine waves needed to reconstruct that complex waveform, along with the PSD. You can suppress frequencies to show the effects on reconstruction accuracy. 120
David Brang @dbrang.bsky.social · 31/03/2025I'm teaching an undergrad EEG/MEG/iEEG methods course and created a pair of interactive webpages to help build intuition about the Fourier Transform. dbrang.github.io/Fourier-Wave... dbrang.github.io/Fourier-Wave... 3326
David Brang @dbrang.bsky.social · 04/12/2024Transition GIF showing the photos with and without the grid registered together. {Warning: these are intraoperative photos} 000
David Brang @dbrang.bsky.social · 14/02/2023First R01 for the lab! Grateful to have such amazing lab members and collaborators. We’re recruiting postdocs for this work and for an NSF grant (salary 65-70k; the postdoc could potentially live out of state and work remotely). More info at... 030
David Brang @dbrang.bsky.social · 12/11/2022These data also emphasize that silent visual speech increases neural activity (increased BOLD and iEEG HGp) at the posterior STG and STS, but suppresses activity elsewhere in the STG (including A1). Visemes could be classified from both regions suggesting two mechanisms. (5/7) 100
David Brang @dbrang.bsky.social · 12/11/2022Classifiers were also run at individual time-points to test when viseme information is encoded in the auditory system, showing similar onsets across phonemes and visemes (potentially starting earlier for visemes). For context, vis information can precede speech by 50-200ms. (4/7) 100
David Brang @dbrang.bsky.social · 12/11/2022We extended this result in patients using iEEG with different phonemes and visemes. Classification was strongest for ERP signals (reflecting oscillatory phase and power) but also present in broadband power (70-150 Hz). (3/7) 100
David Brang @dbrang.bsky.social · 12/11/2022During silent visual speech, visemes could be classified from the STG (bilaterally) and the left pSTS using fMRI. Classification was driven by distributed spatial information, consistent with the population-coded nature of phonemic representations. (2/7) 100
David Brang @dbrang.bsky.social · 12/11/2022New preprint from the lab! "Auditory cortex encodes lipreading information through spatially distributed activity." We used fMRI (n=64) and intracranial recordings (n=6) to study how the auditory system represents lipreading information.... 110
David Brang @dbrang.bsky.social · 22/08/2022These were lightly photoshopped and lovely, but came in second place to the one up at sites.lsa.umich.edu/brang-lab 000
David Brang @dbrang.bsky.social · 03/06/2022But, visual responses did not differ according to the rate of the amplitude modulated sound in terms of phase or power. In contrast, auditory electrodes showed strong phase-based entrainment at each rhythmic sound rate. (4/5) 110
David Brang @dbrang.bsky.social · 03/06/2022We found that 41 out of 178 (23%) visual electrodes responded to the onset of a sound (clustered largely around hMT+ and V1), with 10 of these 41 electrodes (24%) also generating a second response to the offset of a sound. (3/5) 100
David Brang @dbrang.bsky.social · 03/06/2022New iEEG paper from the lab testing what auditory features visual cortex is sensitive to (we've previously found that the auditory system sends sound onset timing and some coarse spatial information, but anything else?). journals.physiology.org/doi/full/10…... 120
David Brang @dbrang.bsky.social · 27/04/2021The classic model (the race model) assumes that the senses are independent, and that faster RTs are due to the presence of 2 stimuli vs 1. Multisensory efftects are those that exceed the race model. This works well but fails to explain slower RTs (2/3) 100