Literature DB >> 31811903

Micro-probing enables fine-grained mapping of neuronal populations using fMRI.

Joana Carvalho1, Azzurra Invernizzi2, Khazar Ahmadi3, Michael B Hoffmann4, Remco J Renken5, Frans W Cornelissen2.   

Abstract

The characterization of receptive field (RF) properties is fundamental to understanding the neural basis of sensory and cognitive behaviour. The combination of non-invasive imaging, such as fMRI, with biologically inspired neural modelling has enabled the estimation of population RFs directly in humans. However, current approaches require making numerous a priori assumptions, so these cannot reveal unpredicted properties, such as fragmented RFs or subpopulations. This is a critical limitation in studies on adaptation, pathology or reorganization. Here, we introduce micro-probing (MP), a technique for fine-grained and largely assumption free characterization of multiple pRFs within a voxel. It overcomes many limitations of current approaches by enabling detection of unexpected RF shapes, properties and subpopulations, by enhancing the spatial detail with which we analyze the data. MP is based on tiny, fixed-size, Gaussian models that efficiently sample the entire visual space and create fine-grained probe maps. Subsequently, we derived population receptive fields (pRFs) from these maps. We demonstrate the scope of our method through simulations and by mapping the visual fields of healthy participants and of a patient group with highly abnormal RFs due to a congenital pathway disorder. Without using specific stimuli or adapted models, MP mapped the bilateral pRFs characteristic of observers with albinism. In healthy observers, MP revealed that voxels may capture the activity of multiple subpopulations RFs that sample distinct regions of the visual field. Thus, MP provides a versatile framework to visualize, analyze and model, without restrictions, the diverse RFs of cortical subpopulations in health and disease.
Copyright © 2019. Published by Elsevier Inc.

Entities:  

Keywords:  Computational modelling; Receptive field; Visual field mapping; fMRI

Mesh:

Year:  2019        PMID: 31811903     DOI: 10.1016/j.neuroimage.2019.116423

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  5 in total

1.  Visual Field Reconstruction in Hemianopia Using fMRI Based Mapping Techniques.

Authors:  Hinke N Halbertsma; Holly Bridge; Joana Carvalho; Frans W Cornelissen; Sara Ajina
Journal:  Front Hum Neurosci       Date:  2021-08-10       Impact factor: 3.169

Review 2.  [Neuro-computational approaches for objective assessment of visual function].

Authors:  Michael B Hoffmann; Lars Choritz; Hagen Thieme; Gokulraj T Prabhakaran; Robert J Puzniak
Journal:  Ophthalmologe       Date:  2021-05-25       Impact factor: 1.059

3.  Aberrant visual population receptive fields in human albinism.

Authors:  Ethan J Duwell; Erica N Woertz; Jedidiah Mathis; Joseph Carroll; Edgar A DeYoe
Journal:  J Vis       Date:  2021-05-03       Impact factor: 2.240

4.  Visual Field Reconstruction Using fMRI-Based Techniques.

Authors:  Joana Carvalho; Azzurra Invernizzi; Joana Martins; Nomdo M Jansonius; Remco J Renken; Frans W Cornelissen
Journal:  Transl Vis Sci Technol       Date:  2021-01-13       Impact factor: 3.283

5.  Divisive normalization unifies disparate response signatures throughout the human visual hierarchy.

Authors:  Marco Aqil; Tomas Knapen; Serge O Dumoulin
Journal:  Proc Natl Acad Sci U S A       Date:  2021-11-16       Impact factor: 12.779

  5 in total

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