Depth-Dependent BOLD Responses to Multi-Frequency Vibrotactile Stimuli and Attention in S1 at 7T
Poster No:
2063
Submission Type:
Abstract Submission
Authors:
Ashley York1, Saskia Bollmann1, Ross Cunnington1, Markus Barth2, Martijn Cloos3, Alexander Puckett4
Institutions:
1The University of Queensland, Brisbane, Queensland, 2The University of Queensland, Brisbane, Australia, 3Radboud University, Nijmegen, Gelderland, 4University of Technology Sydney, Sydney, New South Wales
First Author:
Co-Author(s):
Introduction:
Primary somatosensory cortex (S1) processes tactile information through distinct cortical layers, with middle layers receiving sensory input and superficial/deep layers integrating feedback signals (Zilles & Palomero-Gallagher, 2020). While columnar organisation for different mechanoreceptor-specific frequencies has been demonstrated in S1 (York et al. 2024), evidence for their depth-dependent activation patterns remains mixed (Kim et al. 2021;Yang et al. 2019). Furthermore, although attention enhances tactile processing (Puckett et al. 2017), how it differentially modulates these frequency-specific circuits across cortical depths remains unknown. Despite the critical role of inhibitory processing in tactile perception, previous studies have primarily characterised positive BOLD responses. Here, using 7T fMRI, we extend this to include seemingly negative BOLD responses to query the nature of tactile processing over depth, frequency, and attentional state.
Methods:
Using 7T (Siemens Magnetom) fMRI (3D GRE-EPI, 0.8mm iso), we measured BOLD responses in S1 while 5 participants received stimulation to the right index finger in a blocked design (Fig1A,B). For attention conditions, they performed a one-back frequency discrimination task, identical stimulation was delivered without an explicit task in passive conditions. Stimuli (3/30/240Hz) targeted different mechanoreceptors, with individual frequency discrimination thresholds calibrated pre-scanning. Functional runs alternated between task type, with 3 blocks per run corresponding to the 3 reference frequencies (~70min total; Fig1C). We investigated activation patterns across cortical depth (Fig1D) by 1) spatial distribution of positive and negative responses 2) response consistency across depths and 3) temporal response characteristics. We used GAMs to examine non-linear interactions between depth, task and frequency on the proportions of positive/negative BOLD vertices.
Results:
We observed distinct patterns of positive and negative BOLD responses that varied with frequency and task. Mapping revealed organised clusters of positive and negative responses, with negative BOLD prominent during high-frequency stimulation (Fig1E;2A,B). GAM analysis of positive response proportions showed systematic non-linear relationships between task, frequency, and cortical depth (Fig2D).
Response consistency across depths using Dice coefficients showed substantial spatial correspondence between adjacent depths (~64% overlap;Fig2C), exceeding chance levels from permutation testing.
BOLD timecourses and hemodynamic responses (Fig2E) showed distinct temporal patterns for positive versus negative vertices. Positive responses had consistent peak latencies (Fig2F) under attention, while passive conditions showed more variability. Negative responses showed complex temporal patterns, mainly during passive high-frequency stimulation.
Response consistency across depths using Dice coefficients showed substantial spatial correspondence between adjacent depths (~64% overlap;Fig2C), exceeding chance levels from permutation testing.
BOLD timecourses and hemodynamic responses (Fig2E) showed distinct temporal patterns for positive versus negative vertices. Positive responses had consistent peak latencies (Fig2F) under attention, while passive conditions showed more variability. Negative responses showed complex temporal patterns, mainly during passive high-frequency stimulation.
Conclusions:
Our findings raise important questions about the nature of negative BOLD responses in S1: Do they reflect genuine neural suppression (Shmuel et al. 2002;Goense et al. 2012), center-surround inhibition (Shmuel et al. 2006, 2007), or vascular effects (Logothetis, 2002), or, just noise?The differences between passive and attention conditions may reflect the broader spatial extent of attentional fields compared to sensory receptive fields. The frequency-dependent differences in response patterns may reflect distinct processing requirements for different mechanoreceptor inputs, with attention potentially operating through different mechanisms depending on the type of tactile information being processed. Understanding these spatial and temporal relationships between positive and negative BOLD responses could provide insights into how attention shapes the representation of tactile information.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Perception, Attention and Motor Behavior:
Perception: Tactile/Somatosensory 1
Keywords:
Cognition
Cortical Layers
FUNCTIONAL MRI
HIGH FIELD MR
Perception
Somatosensory
1|2Indicates the priority used for review
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Provide references using APA citation style.
Kim, J., et al. (2021). Laminar representations of vibrotactile stimuli with varying frequency in S1: A 7T fMRI study. Paper presented at the 27th Annual Meeting of the Organization for Human Brain Mapping, June 2021, Glasgow, Scotland. Abstract 3847.
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Puckett, A. M., Bollmann, S., Barth, M., & Cunnington, R. (2017). Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI. Neuroimage, 161, 179-187.
Shmuel, A., Augath, M., Oeltermann, A., & Logothetis, N. K. (2006). Negative functional MRI response in the monkey primary visual cortex and its dependence on stimulus timing. Journal of Neuroscience, 26(40), 10399–10408. https://doi.org/10.1523/JNEUROSCI.2056-06.2006
Shmuel, A., Augath, M., Oeltermann, A., & Logothetis, N. K. (2007). Correspondence of cortical activity and BOLD signal in areas V1 and V2 of the monkey during negative BOLD response. NeuroImage, 35(4), 1157–1167. https://doi.org/10.1016/j.neuroimage.2007.01.093
Shmuel, A., Yacoub, E., Chaimow, D., Logothetis, N. K., & Ugurbil, K. (2002). Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1. Nature Neuroscience, 5(6), 553–560. https://doi.org/10.1038/nn0602-553
Yang, S., et al. (2019). High-resolution fMRI maps of columnar organization in human primary somatosensory cortex. Paper presented at the 27th Annual Meeting of ISMRM, May 2019, Montreal, Canada. Abstract 617.
York, A., et al. (2024). Identifying cortical columns for slow/rapid vibrotactile stimulation in human S1 using 7T fMRI [Poster No. 2535]. Organization for Human Brain Mapping: Abstract Book 6. OHBM 2024 Annual Meeting. Aperture Neuro, 4(Suppl 1). https://doi.org/10.52294/001c.120596
Zilles, K., & Palomero-Gallagher, N. (2020). Cyto-, myelo-, and receptor architectonics of the human parietal cortex. NeuroImage, 220, 117067. https://doi.org/10.1016/j.neuroimage.2020.117067