Ultra-high field fMRI reveals cortical depth specificity for adaptation in the human visual cortex

Poster No:


Submission Type:

Abstract Submission 


Elisa Zamboni1, Valentin Kemper2, Nuno Goncalves1, Ke Jia1, Rainer Goebel2, Zoe Kourtzi1


1University of Cambridge, Cambridge, United Kingdom, 2Maastricht University, Maastricht, Netherlands



Adaptation is a key sensory plasticity mechanism that involves changes in perceptual sensitivity and brain activity due to continuous sensory stimulation. Yet, the neural circuitry that mediates adaptive processing in the human brain remains largely unknown. Ultra-high field 7T imaging affords us with higher resolution to examine adaptive processing at the finer scale of laminar layers in the human visual cortex. Here, we tested whether adaptation results in brain activity changes in input compared to deeper layers of the visual cortex, consistent with local vs. feedback processing, respectively.


We used high-resolution 7T fMRI (0.80mm isotropic resolution; 56 slices; TR = 2000ms; TE = 25ms; Multi Band: 2). Participants (n=15) were presented with oriented gratings and performed an attentional task at fixation. Using a blocked fMRI design (Figure 1a), participants were presented with two conditions: a) adaptation: gratings of the same orientation were presented 16 times per block, b) non-adaptation: gratings were presented with orientations randomly selected from a uniform distribution (i.e. +85 to -85º); each orientation was presented once per block. For each participant, we mapped visual cortex regions using retinotopic mapping. Perceptual bias in orientation judgments due to adaptation was measured on a subset of participants (n=7) outside the scanner (Figure 1b). Preprocessing of functional images (distortion correction, slice scan time correction, temporal filtering, and 3D motion correction) was performed using BrainVoyager v20.6. FreeSurfer was used to obtain the cortical segmentation that was further manually adjusted using ITK-Snap v3.6.


Participants showed a perceptual bias (i.e. reduced sensitivity to the adapted orientation; Figure 1b), as indicated by an adaptation index significantly higher than 1 (t(6)=-10.72, p<0.0005). We next, computed cortical depth-dependent activation profiles in V1 for both stimulus conditions (adaptation, non-adaptation). Large draining veins are known to result in higher signal towards the grey matter surface (4). To improve spatial BOLD specificity across layers and reduce venous-related artefacts in superficial layers, we: a) computed the mean tSNR value for each V1 voxel, b) measured BOLD in V1 during an independent scan (i.e. flickering checkerboard). Voxels with low tSNR (5) and voxels with z-scored values higher than two standard deviations from the mean (6) were removed from further analysis. Figure 2a shows a significant interaction between BOLD signal (before vs. after correction) and cortical depth (F(2,28)=58.556, p<0.0005). This venous artefact correction resulted in decreased BOLD across layers that was evident more strongly in middle and superficial layers. Figure 2b shows cortical depth-dependent activation profiles for the adaptation and non-adaptation conditions. BOLD activation was lower for the adaptation compared to the non-adaptation condition (F(1,14)=17.959, p=0.001). Further, we found a significant interaction (F(2,28)=3.387, p=0.048) between condition (adaptation, non-adaptation) and cortical depth (deep, middle, superficial). Post-hoc comparisons showed that the difference in BOLD between conditions was significantly different for deep vs. middle (F(1,14)=10.119, p=0.007) and deep vs. superficial (F(1,14)=12.259, p=0.004) layers, but not for middle vs. superficial (F(1,14)=0.015, p=0.904) layers.
Supporting Image: hbm_1ab_revised_3.jpg
Supporting Image: hbm_2ab_revised_2.jpg


Our results demonstrate that visual adaptation relates to stronger decrease in BOLD activation in middle and superficial rather than deeper layers of V1. This finding is consistent with the proposal that processing in superficial layers relates to prediction error (1, 2). It is likely that the difference between prediction (i.e. expected stimulus) and sensory input decreases during adaptation (i.e. same stimulus presentation), resulting in decreased BOLD activation in superficial than deeper layers.

Imaging Methods:



Cortical Anatomy and Brain Mapping 2

Perception and Attention:

Perception: Visual 1


Cortical Layers
Other - adaptation

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My abstract is being submitted as a Software Demonstration.


Please indicate below if your study was a "resting state" or "task-activation” study.


Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Was any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.


Was any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Functional MRI
Structural MRI

For human MRI, what field strength scanner do you use?


Which processing packages did you use for your study?

Brain Voyager
Free Surfer

Provide references using author date format

1) Auksztulewicz, R., & Friston, K.J. (2016), 'Repetition suppression and its contextual determinants in predictive coding', Cortex, 80, pp. 125-140
2) Bastos, A.M., Usrey, W.M., Adams, R.A., Mangung, G.R., Fries, P., Friston, K.J. (2012), 'Canonical microcircuits of predictive coding', Neuron, vol. 76, no. 4, pp. 695-711
3) Boynton, G.M., & Finney. E.M. (2003), 'Orientation-specific adaptation in human visual cortex', The Journal of Neuroscience, vol. 23, no. 25, pp. 8781-8787
4) Duvernoy, H.M., Delon, S., Vannson, J.M. (1981), 'Cortical blood vessels of the human brain', Brain Research Bulletin, vol. 7, no. 5, pp. 519-579
5) Olman, C.A., Inati, S., Heeger, D.J. (2007), 'The effect of large veins on spatial localization with GE BOLD at 3T: displacement, not blurring', NeuroImage, vol. 168, pp. 332-344
6) Polimeni, J.R., Fischl, B., Greve, D.N., Wald, L.L. (2010a), 'Laminar analysis of 7T BOLD using an imposed spatial activation pattern in human V1', NeuroImage, vol. 52, pp. 1334-1346