David Brang

David Brang

@dbrang.bsky.social

Associate Professor of Psychology UMich. Cognitive neuroscience of multisensory perception, neural oscillations, and brain tumor physiology. ๐Ÿณ๏ธโ€๐ŸŒˆ sites.lsa.umich.edu/brang-lab/

399 followers112 following43 posts

David Brang reposted

Super excited that this work it out! If you care about inhibitory control or aging and cognition check out Jacob's explainer for details!

Jacob Sellers@jacobsellers.bsky.social

Out now in Psych Science! With @hanzhang.bsky.social John Jonides and @tarazlee.bsky.social We show that apparent age-related deficits in inhibitory control (often measured by RT congruency effects) can be explained by age differences in processing speed journals.sagepub.com/doi/10.1177/...

David Brang reposted

Super excited by this manuscript led by the amazing @brissend.bsky.social By combining fMRI, TMS, and modeling, we finally have causal evidence that the cerebellum is contributing to brain-wide working memory representations and recall performance! 1/n

bioRxiv Neuroscience@biorxiv-neursci.bsky.social

Cerebellar perturbation impairs human working memory and degrades spatial tuning throughout cortex https://www.biorxiv.org/content/10.64898/2026.05.14.724968v1

David Brang reposted

The data is in: the NIH goalposts have shifted. What were once almost certain fundable scores have become coin flips and what used to be likely grants have become aspirational, leading to fewer awards. Another manifestation of how HHS policies have led to fewer awards and less science.

Independent 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/

David Brang reposted

New 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.

bioRxivpreprint@biorxivpreprint.bsky.social

Electrocorticographic Detection of Speech Networks in Glioma-infiltrated Cortex https://www.biorxiv.org/content/10.1101/2025.07.04.663249v1

David Brang reposted

Experimentology is out today!!! A group of us wrote a free online textbook for experimental methods, available at experimentology.io - the idea was to integrate open science into all aspects of the experimental workflow from planning to design, analysis, and writing.

New 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.

bioRxivpreprint@biorxivpreprint.bsky.social

Aperiodic neural dynamics define a novel signature of glioma-induced excitation-inhibition dysregulation https://www.biorxiv.org/content/10.1101/2025.05.23.655626v1

Tissue 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.

Localizing 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).

ExtraOp 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.

Fourier 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.

David Brang reposted

At #CNS2025? Come by our posters from the Cognition, Control, and Action Lab! SAT 3-5pm A126 Modeling the temporal dynamics of cognitive control A149 Cognition-Action links in Parkinson disease (TMS-fMRI) SUN 8-10am B30 Causal role of the cerebellum in spatial working memory (TMS-fMRI)

New study from my PostDoc Emily Cunningham! We used ECoG with stimulation of the STG to test for direct (potentially monosynaptic) A-to-V connections in humans. 112 out of 231 visual electrodes (across 19/23 patients) exhibited early responses to STG stimulation (as early as 18ms after stimulation).

Emily Cunningham@e-cunningham.bsky.social

A new preprint (brief report) with @dbrang.bsky.social is now live, examining CCEP evidence for direct projections between auditory and visual cortices in humans. (1/3) www.biorxiv.org/content/10.1...

David Brang reposted

Helpful table to determine how much your University or health system is set to lose if the NIH indirect cap is suddenly lowered to 15%. For SJSU it is $374k which is on the smaller end but devastating considering our other budget issues. datawrapper.dwcdn.net/l0ZqA/8/

datawrapper.dwcdn.netEstimated Single Year Loss of NIH Funding if 15% Indirect Cost Rate is ImposedBased on analysis of 2024 NIH funding data. Sums are totals of losses in funding to programs if indirect costs had been capped at 15%

David Brang reposted

Replying to @jeremymberg.bsky.social

ATTENTION If you are someone who had an F31-Diversity (or similar) application submitted this cycle, please DM me here, contact me on signal (jeremymberg.78), or email me at jeremymberg@gmail.com. I will keep all information confidential. 2/n

David Brang reposted

Posted some of the lab's Open-Source Image Registration scripts onto github, useful for identifying where ECoG electrodes are located based on intraoperative photography alone, by registering/warping pictures of the brain with and without the ECoG grid. github.com/dbrang/Intra...

github.comGitHub - dbrang/IntraOp_Image_Registration_Tools: Open-source tools for aligning intraoperative photos based on automatic and manual control point selectionOpen-source tools for aligning intraoperative photos based on automatic and manual control point selection - dbrang/IntraOp_Image_Registration_Tools

David Brang reposted

my first preprint with @dbrang.bsky.social is now live. we tested whether mouth movement improves auditory speech onset encoding and ongoing speech envelope tracking with distinct or overlapping mechanisms (1/7)

First R01 for the lab! Grateful to have such amazing lab members and collaborators. Weโ€™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...

New 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....

View full thread

This was a massive project that was years in the making, spearheaded by @tnagarKaRaja and made possible by an amazing group: @neurocow, @DemidenkoMI, and the twitterless Andy Jahn, Bill Stacey, and Vibha Wasade. Data soon to be freely available at...

New 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....

View full thread

These 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)

Finally, phoneme and viseme representations overlapped in the STG (e.g., the spatial activity of auditory /fa/ was more similar to visual /fa/ than to visual /ma/), and visemes showed similar patterns of confusability in iEEG data (/ba/ and /da/ more confusable than /fa/) (6/7)

New 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....

View full thread

We 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)

Classifiers 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)

New 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....

During 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)