Biophysically based method to deconvolve spatiotemporal neurovascular signals from fMRI data

Pang, James C.; Aquino, Kevin; Robinson, P. A.; Lacy, T. C.; Schira, Mark M.

doi:10.1016/j.jneumeth.2018.07.009

Cited by 7 publications

(15 citation statements)

References 63 publications

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“…Solving the equations of the model allows the calculation of the stHRF that relates the BOLD signal and the input neural activity. Full details and derivations of equations of the model are described in the relevant literature [25, 26, 28, 32].…”

Section: Methodsmentioning

confidence: 99%

“…The stHRF in frequency space H ( k , ω ) is the transfer function that can be directly derived from the model ( H ( k , ω ) = T Y , ϕ ( k , ω )) [28]. It describes the change in BOLD signal per unit change in neural activity at the same k and ω .…”

Section: Methodsmentioning

confidence: 99%

“…Recent physiology-based modeling has enabled the link between neural activity and BOLD to be made quantitative, including spatial spreading and temporal dynamics [25, 26]. Conversely, this model has been used as the basis of Wiener deconvolution to estimate the underlying neural signal from the BOLD response, thereby enabling sharper images to be obtained even in the presence of noise [27, 28].…”

Section: Introductionmentioning

confidence: 99%

“…This work aims to explore the feasibility of detecting OD and OP in V1 using fMRI, either directly or via deconvolution, and to determine the short-bar stimulus orientation that maximizes detectability within a particular OD column organization, laying the basis for testing experimental designs of optimal stimuli. To achieve this, the above mentioned quantitative hemodynamic model is employed [24–28] to calculate the response to a patchy neural activity [29]. The model is used to estimate the BOLD response to the spatially patchy neural activity that results from visual stimuli, then the imaging requirements for OD-OP detection are estimated.…”

Section: Introductionmentioning

confidence: 99%

“…The model is used to estimate the BOLD response to the spatially patchy neural activity that results from visual stimuli, then the imaging requirements for OD-OP detection are estimated. Finally, deconvolution is applied to sharpen the images and the resulting detection criteria are determined [25–28].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Feasibility of functional magnetic resonance imaging of ocular dominance and orientation preference in primary visual cortex

et al. 2019

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A recent hemodynamic model is extended and applied to simulate and explore the feasibility of detecting ocular dominance (OD) and orientation preference (OP) columns in primary visual cortex by means of functional magnetic resonance imaging (fMRI). The stimulation entails a short oriented bar stimulus being presented to one eye and mapped to cortical neurons with corresponding OD and OP selectivity. Activated neurons project via patchy connectivity to excite other neurons with similar OP in nearby visual fields located preferentially along the direction of stimulus orientation. The resulting blood oxygen level dependent (BOLD) response is estimated numerically via the model’s spatiotemporal hemodynamic response function. The results are then used to explore the feasibility of detecting spatial OD-OP modulation, either directly measuring BOLD or by using Wiener deconvolution to filter the image and estimate the underlying neural activity. The effect of noise is also considered and it is estimated that direct detection can be robust for fMRI resolution of around 0.5 mm, whereas detection with Wiener deconvolution is possible at a broader range from 0.125 mm to 1 mm resolution. The detection of OD-OP features is strongly dependent on hemodynamic parameters, such as low velocity and high damping reduce response spreads and result in less blurring. The short-bar stimulus that gives the most detectable response is found to occur when neural projections are at 45 relative to the edge of local OD boundaries, which provides a constraint on the OD-OP architecture even when it is not fully resolved.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Feasibility of functional magnetic resonance imaging of ocular dominance and orientation preference in primary visual cortex

et al. 2019

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Cortical depth-dependent modeling of visual hemodynamic responses

Lacy

Robinson

Aquino

et al. 2022

Journal of Theoretical Biology

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Latency analysis of resting-state BOLD-fMRI reveals traveling waves in visual cortex linking task-positive and task-negative networks

et al. 2019

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Due to the low temporal resolution of BOLD-fMRI, imaging studies on human brain function have almost exclusively focused on instantaneous correlations within the data. Developments in hardware and acquisition protocols, however, are offering data with higher sampling rates that allow investigating the latency structure of BOLD-fMRI data. In this study we describe a method for analyzing the latency structure within BOLD-fMRI data and apply it to resting-state data of 94 participants from the Human Connectome Project. The method shows that task-positive and task-negative networks are integrated through traveling BOLD waves within early visual cortex. The waves are initiated at the periphery of the visual field and propagate towards the fovea. This observation suggests a mechanism for the functional integration of task-positive and task-negative networks, argues for an eccentricity-based view on visual information processing, and contributes to the emerging view that resting-state BOLD-fMRI fluctuations are superpositions of inherently spatiotemporal patterns.

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Biophysically based method to deconvolve spatiotemporal neurovascular signals from fMRI data

Abstract: The method provides new testable predictions of the spatiotemporal relations of the deconvolved signals for future studies. This demonstrates the ability of the method to quantify and analyze the neurovascular mechanisms that underlie fMRI, thereby expanding its potential uses.

Cited by 7 publications

References 63 publications

Feasibility of functional magnetic resonance imaging of ocular dominance and orientation preference in primary visual cortex

Feasibility of functional magnetic resonance imaging of ocular dominance and orientation preference in primary visual cortex

Cortical depth-dependent modeling of visual hemodynamic responses

Latency analysis of resting-state BOLD-fMRI reveals traveling waves in visual cortex linking task-positive and task-negative networks

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