Using high spatial resolution fMRI to understand representation in the auditory network

Moerel, Michelle; Yacoub, Essa; Gulban, Omer Faruk; Lage‐Castellanos, Agustín; Martino, Federico De

doi:10.1016/j.pneurobio.2020.101887

Cited by 20 publications

(17 citation statements)

References 186 publications

(253 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We interpret our results within a framework of feedforward and feedback connectivity across cortical depths ( Fig. 1A ), as proposed by previous UHF imaging studies (e.g., Kok et al, 2016 ; Huber et al, 2017 ; Sharoh et al, 2019 ; Moerel et al, 2020 ). In particular, sensory inputs are known to enter the cortex at the level of the middle layer (layer 4) and output information is fed forward through the superficial layers (layer 2/3).…”

Section: Discussionsupporting

confidence: 81%

“…Here, we tested functional connectivity across visual areas (V1, V3A, V7) to investigate the role of feedforward and feedback processing for stereoscopic perception. While UHF imaging resolution does not support one-to-one mapping between MRI-defined cortical depths and cyto-architectonically defined layers, previous UHF imaging studies (e.g., Kok et al, 2016 ; Huber et al, 2017 ; Sharoh et al, 2019 ; Moerel et al, 2020 ) have provided a framework of feedback and feedforward connections across deeper, middle, and superficial cortical depths ( Fig. 1 ).…”

Section: Resultsmentioning

confidence: 92%

See 1 more Smart Citation

Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception

Jia

Goncalves

et al. 2021

J. Neurosci.

View full text Add to dashboard Cite

Binocular disparity provides critical information about three-dimensional (3D) structure to support perception and action. The past decade has seen significant progress in uncovering human brain areas engaged in the processing of binocular disparity signals. Yet, the fine-scale brain processing underlying 3D perception remains unknown. Here, we use ultra-high field (7T) functional imagining at sub-millimetre resolution to examine fine-scale BOLD-fMRI signals involved in 3D perception. In particular, we sought to interrogate the local circuitry involved in disparity processing by sampling fMRI responses at different positions relative to the cortical surface (i.e., across cortical depths corresponding to layers). We test for representations related to 3D perception by presenting participants (male and female, N = 8) with stimuli that enable stable stereoscopic perception (i.e., correlated random dot stereograms: RDS) vs. those that do not (i.e., anti-correlated RDS). Using multi-voxel pattern analysis (MVPA), we demonstrate cortical depth-specific representations in area V3A and V7 as indicated by stronger pattern responses for correlated than anti-correlated stimuli in upper than deeper layers. Examining informational connectivity, we find higher feedforward layer-to-layer connectivity for correlated than anti-correlated stimuli between V3A and V7. Further, we observe disparity-specific feedback from V3A to V1 and from V7 to V3A. Our findings provide evidence for the role of V3A as a key nexus for disparity processing that is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structure.

show abstract

Section: Discussionsupporting

confidence: 81%

Section: Resultsmentioning

confidence: 92%

Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception

Jia

Goncalves

et al. 2021

J. Neurosci.

View full text Add to dashboard Cite

show abstract

“…We interpret our results within a framework of feedback vs. feedforward connectivity across cortical depths ( Figure 1A ), as proposed by previous UHF imaging studies (e.g. Huber et al, 2017 ; Kok et al, 2016 ; Moerel et al, 2020 ; Sharoh et al, 2019 ). In particular, sensory inputs are known to enter the cortex at the level of the middle layer (middle layer 4) and output information is fed forward through the superficial layer (superficial layer 2/3).…”

Section: Discussionsupporting

confidence: 81%

“…Despite the fact that the UHF imaging resolution does not support one-to-one mapping between MRI-defined cortical depths and cyto-architectonically defined layers, Figure 1A provides a framework of feedback vs. feedforward connections across superficial, middle, and deeper cortical depths, as proposed and tested by previous UHF imaging studies (e.g. Huber et al, 2017 ; Kok et al, 2016 ; Moerel et al, 2020 ; Sharoh et al, 2019 ).…”

Section: Resultsmentioning

confidence: 94%

Fine-scale computations for adaptive processing in the human brain

Zamboni

Kemper

Goncalves

et al. 2020

eLife

View full text Add to dashboard Cite

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

show abstract

“…In this regard, the use of graph-theoretical methods and complex network theory for modeling the brain as an interconnected network of brain regions have been a focus of interest in recent years 7,8 . In most of the studies, the general framework for developing the brain networks include the selection of spatial and temporal scale and resolution of the study data [9][10][11][12][13] , the appropriate atlases that divide the brain into distinct regions 14 , the type of connection among regions (anatomical, functional, or effective connectivity) 15,16 , and finally the methods of estimating these connectivities [17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

The trend of disruption in the functional brain network topology of Alzheimer’s disease

Fathian

Jamali

Raoufy

2021

Preprint

View full text Add to dashboard Cite

Alzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters the brain’s functional connectivity. Assessing these alterations has become a topic of increasing interest. However, a few studies have examined different stages of AD from a complex network perspective that cover different topological scales. This study analyzed the trend of functional connectivity alterations from a cognitively normal (CN) state through early and late mild cognitive impairment (EMCI and LMCI) and to Alzheimer’s disease. The analyses had been done at the local (hubs and activated links and areas), meso (clustering, assortativity, and rich-club), and global (small-world, small-worldness, and efficiency) topological scales. The results showed that the trends of changes in the topological architecture of the functional brain network were not entirely proportional to the AD progression, and these trends behaved differently at the earliest stage of the disease, i.e., EMCI. Further, it has been indicated that the diseased groups engaged somatomotor, frontoparietal, and default mode modules compared to the CN group. The diseased groups also shifted the functional network towards more random architecture. In the end, The methods introduced in this paper enable us to gain an extensive understanding of the pathological changes of the AD process.

show abstract

Using high spatial resolution fMRI to understand representation in the auditory network

Cited by 20 publications

References 186 publications

Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception

Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception

Fine-scale computations for adaptive processing in the human brain

The trend of disruption in the functional brain network topology of Alzheimer’s disease

Contact Info

Product

Resources

About