ReviewProgress in neurobiology2021
Using high spatial resolution fMRI to understand representation in the auditory network.
Review in Progress in neurobiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed, 29 citations in OpenAlex.
- Predictive acoustical processing in human cortical layers.Nature communications · 2026Article
- Category learning drives cortical attentional gain to diagnostic dimensions.bioRxiv : the preprint server for biology · 2025Article
- Lethal Interactions of neuronal networks in epilepsy mediated by both synaptic and volume transmission indicate approaches to prevention.Progress in neurobiology · 2025Review
- Review
- Multilayer network analysis across cortical depths in 7-T resting-state fMRI.Network neuroscience (Cambridge, Mass.) · 2025Article
- Individual connectivity-based parcellations reflect functional properties of human auditory cortex.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI.bioRxiv : the preprint server for biology · 2024Article
- Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC.bioRxiv : the preprint server for biology · 2024Article
- Functional connectivity across the human subcortical auditory system using an autoregressive matrix-Gaussian copula graphical model approach with partial correlations.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Layer-specific correlates of detected and undetected auditory targets during attention.Current research in neurobiology · 2023Article
- Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities.PloS one · 2023Article
- Fast cortical surface reconstruction from MRI using deep learning.Brain informatics · 2022Article
- Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
Abstract
Following rapid methodological advances, ultra-high field (UHF) functional and anatomical magnetic resonance imaging (MRI) has been repeatedly and successfully used for the investigation of the human auditory system in recent years. Here, we review this work and argue that UHF MRI is uniquely suited to shed light on how sounds are represented throughout the network of auditory brain regions. That is, the provided gain in spatial resolution at UHF can be used to study the functional role of the small subcortical auditory processing stages and details of cortical processing. Further, by combining high spatial resolution with the versatility of MRI contrasts, UHF MRI has the potential to localize the primary auditory cortex in individual hemispheres. This is a prerequisite to study how sound representation in higher-level auditory cortex evolves from that in early (primary) auditory cortex. Finally, the access to independent signals across auditory cortical depths, as afforded by UHF, may reveal the computations that underlie the emergence of an abstract, categorical sound representation based on low-level acoustic feature processing. Efforts on these research topics are underway. Here we discuss promises as well as challenges that come with studying these research questions using UHF MRI, and provide a future outlook.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.