1
|
Chang K, Fine I, Boynton GM. Improving the Reliability and Accuracy of Population Receptive Field Measures Using a Logarithmically Warped Stimulus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598529. [PMID: 38915587 PMCID: PMC11195291 DOI: 10.1101/2024.06.11.598529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The population receptive field method, which measures the region in visual space that elicits a BOLD signal in a voxel in retinotopic cortex, is a powerful tool for investigating the functional organization of human visual cortex with fMRI (Dumoulin & Wandell, 2008). However, recent work has shown that population receptive field (pRF) estimates for early retinotopic visual areas can be biased and unreliable, especially for voxels representing the fovea. Here, we show that a 'log-bar' stimulus that is logarithmically warped along the eccentricity dimension produces more reliable estimates of pRF size and location than the traditional moving bar stimulus. The log-bar stimulus was better able to identify pRFs near the foveal representation, and pRFs were smaller in size, consistent with simulation estimates of receptive field sizes in the fovea.
Collapse
Affiliation(s)
- Kelly Chang
- Department of Psychology, University of Washington Seattle, Washington
| | - Ione Fine
- Department of Psychology, University of Washington Seattle, Washington
| | | |
Collapse
|
2
|
Pawloff M, Linhardt D, Woletz M, Hummer A, Sacu S, Vasileiadi M, Garikoitz LU, Holder G, Schmidt-Erfurth UM, Windischberger C, Ritter M. Comparison of Stimulus Types for Retinotopic Cortical Mapping of Macular Disease. Transl Vis Sci Technol 2023; 12:6. [PMID: 36912591 PMCID: PMC10020948 DOI: 10.1167/tvst.12.3.6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 01/19/2023] [Indexed: 03/14/2023] Open
Abstract
Purpose Retinotopic maps acquired using functional magnetic resonance imaging (fMRI) provide a valuable adjunct in the assessment of macular function at the level of the visual cortex. The present study quantitatively assessed the performance of different visual stimulation approaches for mapping visual field coverage. Methods Twelve patients with geographic atrophy (GA) secondary to age-related macular degeneration (AMD) were examined using high-resolution ultra-high field fMRI (Siemens Magnetom 7T) and microperimetry (MP; Nidek MP-3). The population receptive field (pRF)-based coverage maps obtained with two different stimulus techniques (moving bars, and rotating wedges and expanding rings) were compared with the results of MP. Correspondence between MP and pRF mapping was quantified by calculating the simple matching coefficient (SMC). Results Stimulus choice is shown to bias the spatial distribution of pRF centers and eccentricity values with pRF sizes obtained from wedge/ring or bar stimulation showing systematic differences. Wedge/ring stimulation results show a higher number of pRF centers in foveal areas and strongly reduced pRF sizes compared to bar stimulation runs. A statistical comparison shows significantly higher pRF center numbers in the foveal 2.5 degrees region of the visual field for wedge/ring compared to bar stimuli. However, these differences do not significantly influence SMC values when compared to MP (bar <2.5 degrees: 0.88 ± 0.13; bar >2.5 degrees: 0.88 ± 0.11; wedge/ring <2.5 degrees: 0.89 ± 0.12 wedge/ring; >2.5 degrees: 0.86 ± 0.10) for the peripheral visual field. Conclusions Both visual stimulation designs examined can be applied successfully in patients with GA. Although the two designs show systematic differences in the distribution of pRF center locations, this variability has minimal impact on the SMC when compared to the MP outcome.
Collapse
Affiliation(s)
- Maximilian Pawloff
- Department of Ophthalmology, Medical University of Vienna, Vienna, Austria
| | - David Linhardt
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Michael Woletz
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Allan Hummer
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Stefan Sacu
- Department of Ophthalmology, Medical University of Vienna, Vienna, Austria
| | - Maria Vasileiadi
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Lerma Usabiaga Garikoitz
- BCBL Basque Center on Cognition, Brain and Language Donostia, San Sebastian, Gipuzkoa, Spain
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain
| | - Graham Holder
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- UCL Institute of Ophthalmology, London, UK
| | | | - Christian Windischberger
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Markus Ritter
- Department of Ophthalmology, Medical University of Vienna, Vienna, Austria
| |
Collapse
|
3
|
Pitfalls in Post Hoc Analyses of Population Receptive Field Data. Neuroimage 2022; 263:119557. [PMID: 35970472 DOI: 10.1016/j.neuroimage.2022.119557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 08/02/2022] [Accepted: 08/11/2022] [Indexed: 10/31/2022] Open
Abstract
Data binning involves grouping observations into bins and calculating bin-wise summary statistics. It can cope with overplotting and noise, making it a versatile tool for comparing many observations. However, data binning goes awry if the same observations are used for binning (selection) and contrasting (selective analysis). This creates circularity, biasing noise components and resulting in artifactual changes in the form of regression towards the mean. Importantly, these artifactual changes are a statistical necessity. Here, we use (null) simulations and empirical repeat data to expose this flaw in the scope of post hoc analyses of population receptive field data. In doing so, we reveal that the type of data analysis, data properties, and circular data cleaning are factors shaping the appearance of such artifactual changes. We furthermore highlight that circular data cleaning and circular sorting of change scores are selection practices that result in artifactual changes even without circular data binning. These pitfalls might have led to erroneous claims about changes in population receptive fields in previous work and can be mitigated by using independent data for selection purposes. Our evaluations highlight the urgency for us researchers to make the validation of analysis pipelines standard practice.
Collapse
|
4
|
Urale PWB, Puckett AM, York A, Arnold D, Schwarzkopf DS. Highly accurate retinotopic maps of the physiological blind spot in human visual cortex. Hum Brain Mapp 2022; 43:5111-5125. [PMID: 35796159 PMCID: PMC9812231 DOI: 10.1002/hbm.25996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/18/2022] [Accepted: 06/15/2022] [Indexed: 01/15/2023] Open
Abstract
The physiological blind spot is a naturally occurring scotoma corresponding with the optic disc in the retina of each eye. Even during monocular viewing, observers are usually oblivious to the scotoma, in part because the visual system extrapolates information from the surrounding area. Unfortunately, studying this visual field region with neuroimaging has proven difficult, as it occupies only a small part of retinotopic cortex. Here, we used functional magnetic resonance imaging and a novel data-driven method for mapping the retinotopic organization in and around the blind spot representation in V1. Our approach allowed for highly accurate reconstructions of the extent of an observer's blind spot, and out-performed conventional model-based analyses. This method opens exciting opportunities to study the plasticity of receptive fields after visual field loss, and our data add to evidence suggesting that the neural circuitry responsible for impressions of perceptual completion across the physiological blind spot most likely involves regions of extrastriate cortex-beyond V1.
Collapse
Affiliation(s)
- Poutasi W. B. Urale
- School of Optometry & Vision ScienceUniversity of AucklandAucklandNew Zealand
| | - Alexander M. Puckett
- School of PsychologyUniversity of QueenslandBrisbaneQueenslandAustralia
- Queensland Brain InstituteUniversity of QueenslandBrisbaneQueenslandAustralia
| | - Ashley York
- School of PsychologyUniversity of QueenslandBrisbaneQueenslandAustralia
- Queensland Brain InstituteUniversity of QueenslandBrisbaneQueenslandAustralia
| | - Derek Arnold
- School of PsychologyUniversity of QueenslandBrisbaneQueenslandAustralia
- Queensland Brain InstituteUniversity of QueenslandBrisbaneQueenslandAustralia
| | - D. Samuel Schwarzkopf
- School of Optometry & Vision ScienceUniversity of AucklandAucklandNew Zealand
- Experimental PsychologyUniversity College LondonLondonUnited Kingdom
| |
Collapse
|
5
|
Lacy TC, Robinson PA, Aquino KM, Pang JC. Cortical depth-dependent modeling of visual hemodynamic responses. J Theor Biol 2021; 535:110978. [PMID: 34952032 DOI: 10.1016/j.jtbi.2021.110978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 10/18/2021] [Accepted: 12/01/2021] [Indexed: 11/15/2022]
Abstract
A physiologically based three-dimensional (3D) hemodynamic model is developed to predict the experimentally observed blood oxygen level dependent (BOLD) responses versus the cortical depth induced by visual stimuli. Prior 2D approximations are relaxed in order to analyze 3D blood flow dynamics as a function of cortical depth. Comparison of the predictions with experimental data for evoked stimuli demonstrates that the full 3D model performs at least as well as previous approaches while remaining parsimonious. In particular, the 3D model requires significantly fewer assumptions and model parameters than previous models such that there is no longer need to define depth-specific parameter values for spatial spreading, peak amplitude, and hemodynamic velocity.
Collapse
Affiliation(s)
- Thomas C Lacy
- School of Physics, University of Sydney, New South Wales, Australia; Center for Integrative Brain Function, University of Sydney, New South Wales, Australia
| | - Peter A Robinson
- School of Physics, University of Sydney, New South Wales, Australia; Center for Integrative Brain Function, University of Sydney, New South Wales, Australia
| | - Kevin M Aquino
- School of Physics, University of Sydney, New South Wales, Australia; The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - James C Pang
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; QIMR Berghofer Medical Research Institute, Queensland, Australia.
| |
Collapse
|
6
|
Halbertsma HN, Bridge H, Carvalho J, Cornelissen FW, Ajina S. Visual Field Reconstruction in Hemianopia Using fMRI Based Mapping Techniques. Front Hum Neurosci 2021; 15:713114. [PMID: 34447301 PMCID: PMC8382851 DOI: 10.3389/fnhum.2021.713114] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 07/21/2021] [Indexed: 11/21/2022] Open
Abstract
PURPOSE A stroke that includes the primary visual cortex unilaterally leads to a loss of visual field (VF) representation in the hemifield contralateral to the damage. While behavioral procedures for measuring the VF, such as perimetry, may indicate that a patient cannot see in a particular area, detailed psychophysical testing often detects the ability to perform detection or discrimination of visual stimuli ("blindsight"). The aim of this study was to determine whether functional magnetic resonance imaging (fMRI) could be used to determine whether perimetrically blind regions of the VF were still represented in VF maps reconstructed on the basis of visually evoked neural activity. METHODS Thirteen patients with hemianopia and nine control participants were scanned using 3T MRI while presented with visual stimulation. Two runs of a dynamic "wedge and ring" mapping stimulus, totaling approximately 10 min, were performed while participants fixated centrally. Two different analysis approaches were taken: the conventional population receptive field (pRF) analysis and micro-probing (MP). The latter is a variant of the former that makes fewer assumptions when modeling the visually evoked neural activity. Both methods were used to reconstruct the VF by projecting modeled activity back onto the VF. Following a normalization step, these "coverage maps" can be compared to the VF sensitivity plots obtained using perimetry. RESULTS While both fMRI-based approaches revealed regions of neural activity within the perimetrically "blind" sections of the VF, the MP approach uncovered more voxels in the lesioned hemisphere in which a modest degree of visual sensitivity was retained. Furthermore, MP-based analysis indicated that both early (V1/V2) and extrastriate visual areas contributed equally to the retained sensitivity in both patients and controls. CONCLUSION In hemianopic patients, fMRI-based approaches for reconstructing the VF can pick up activity in perimetrically blind regions of the VF. Such regions of the VF may be particularly amenable for rehabilitation to regain visual function. Compared to conventional pRF modeling, MP reveals more voxels with retained visual sensitivity, suggesting it is a more sensitive approach for VF reconstruction.
Collapse
Affiliation(s)
- Hinke N. Halbertsma
- Laboratory for Experimental Ophthalmology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Holly Bridge
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Joana Carvalho
- Champalimaud Centre for the Unknown, Champalimaud Foundation, Lisbon, Portugal
| | - Frans W. Cornelissen
- Laboratory for Experimental Ophthalmology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Sara Ajina
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Neurorehabilitation, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| |
Collapse
|
7
|
de Haas B, Sereno MI, Schwarzkopf DS. Inferior Occipital Gyrus Is Organized along Common Gradients of Spatial and Face-Part Selectivity. J Neurosci 2021; 41:5511-5521. [PMID: 34016715 PMCID: PMC8221599 DOI: 10.1523/jneurosci.2415-20.2021] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 04/02/2021] [Accepted: 04/05/2021] [Indexed: 11/21/2022] Open
Abstract
The ventral visual stream of the human brain is subdivided into patches with categorical stimulus preferences, like faces or scenes. However, the functional organization within these areas is less clear. Here, we used functional magnetic resonance imaging and vertex-wise tuning models to independently probe spatial and face-part preferences in the inferior occipital gyrus (IOG) of healthy adult males and females. The majority of responses were well explained by Gaussian population tuning curves for both retinotopic location and the preferred relative position within a face. Parameter maps revealed a common gradient of spatial and face-part selectivity, with the width of tuning curves drastically increasing from posterior to anterior IOG. Tuning peaks clustered more idiosyncratically but were also correlated across maps of visual and face space. Preferences for the upper visual field went along with significantly increased coverage of the upper half of the face, matching recently discovered biases in human perception. Our findings reveal a broad range of neural face-part selectivity in IOG, ranging from narrow to "holistic." IOG is functionally organized along this gradient, which in turn is correlated with retinotopy.SIGNIFICANCE STATEMENT Brain imaging has revealed a lot about the large-scale organization of the human brain and visual system. For example, occipital cortex contains map-like representations of the visual field, while neurons in ventral areas cluster into patches with categorical preferences, like faces or scenes. Much less is known about the functional organization within these areas. Here, we focused on a well established face-preferring area-the inferior occipital gyrus (IOG). A novel neuroimaging paradigm allowed us to map the retinotopic and face-part tuning of many recording sites in IOG independently. We found a steep posterior-anterior gradient of decreasing face-part selectivity, which correlated with retinotopy. This suggests the functional role of ventral areas is not uniform and may follow retinotopic "protomaps."
Collapse
Affiliation(s)
- Benjamin de Haas
- Department of Psychology, Justus Liebig Universität, 35394 Giessen, Germany
- Experimental Psychology, University College London, London WC1E 6BT, United Kingdom
| | - Martin I Sereno
- Experimental Psychology, University College London, London WC1E 6BT, United Kingdom
- SDSU Imaging Center, San Diego State University, San Diego, California 92182
| | - D Samuel Schwarzkopf
- Experimental Psychology, University College London, London WC1E 6BT, United Kingdom
- School of Optometry and Vision Science, University of Auckland, Auckland 1142, New Zealand
| |
Collapse
|
8
|
Linhardt D, Pawloff M, Hummer A, Woletz M, Tik M, Ritter M, Schmidt-Erfurth U, Windischberger C. Combining stimulus types for improved coverage in population receptive field mapping. Neuroimage 2021; 238:118240. [PMID: 34116157 DOI: 10.1016/j.neuroimage.2021.118240] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 06/04/2021] [Indexed: 10/21/2022] Open
Abstract
Retinotopy experiments using population receptive field (pRF) mapping are ideal for assigning regions in the visual field to cortical brain areas. While various designs for visual stimulation were suggested in the literature, all have specific shortcomings regarding visual field coverage. Here we acquired high-resolution 7 Tesla fMRI data to compare pRF-based coverage maps obtained with the two most commonly used stimulus variants: moving bars; rotating wedges and expanding rings. We find that stimulus selection biases the spatial distribution of pRF centres. In addition, eccentricity values and pRF sizes obtained from wedge/ring or bar stimulation runs show systematic differences. Wedge/ring stimulation results show lower eccentricity values and strongly reduced pRF sizes compared to bar stimulation runs. Statistical comparison shows significantly higher pRF centre numbers in the foveal 2° region of the visual field for wedge/ring compared to bar stimuli. We suggest and evaluate approaches for combining pRF data from different visual stimulus patterns to obtain improved mapping results.
Collapse
Affiliation(s)
- David Linhardt
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Maximilian Pawloff
- Department of Ophthalmology, Medical University of Vienna, Vienna, Austria
| | - Allan Hummer
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Michael Woletz
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Martin Tik
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Markus Ritter
- Department of Ophthalmology, Medical University of Vienna, Vienna, Austria
| | | | - Christian Windischberger
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
| |
Collapse
|
9
|
Lerma-Usabiaga G, Benson N, Winawer J, Wandell BA. A validation framework for neuroimaging software: The case of population receptive fields. PLoS Comput Biol 2020; 16:e1007924. [PMID: 32584808 PMCID: PMC7343185 DOI: 10.1371/journal.pcbi.1007924] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 07/08/2020] [Accepted: 05/03/2020] [Indexed: 12/29/2022] Open
Abstract
Neuroimaging software methods are complex, making it a near certainty that some implementations will contain errors. Modern computational techniques (i.e., public code and data repositories, continuous integration, containerization) enable the reproducibility of the analyses and reduce coding errors, but they do not guarantee the scientific validity of the results. It is difficult, nay impossible, for researchers to check the accuracy of software by reading the source code; ground truth test datasets are needed. Computational reproducibility means providing software so that for the same input anyone obtains the same result, right or wrong. Computational validity means obtaining the right result for the ground-truth test data. We describe a framework for validating and sharing software implementations, and we illustrate its usage with an example application: population receptive field (pRF) methods for functional MRI data. The framework is composed of three main components implemented with containerization methods to guarantee computational reproducibility. In our example pRF application, those components are: (1) synthesis of fMRI time series from ground-truth pRF parameters, (2) implementation of four public pRF analysis tools and standardization of inputs and outputs, and (3) report creation to compare the results with the ground truth parameters. The framework was useful in identifying realistic conditions that lead to imperfect parameter recovery in all four pRF implementations, that would remain undetected using classic validation methods. We provide means to mitigate these problems in future experiments. A computational validation framework supports scientific rigor and creativity, as opposed to the oft-repeated suggestion that investigators rely upon a few agreed upon packages. We hope that the framework will be helpful to validate other critical neuroimaging algorithms, as having a validation framework helps (1) developers to build new software, (2) research scientists to verify the software's accuracy, and (3) reviewers to evaluate the methods used in publications and grants.
Collapse
Affiliation(s)
- Garikoitz Lerma-Usabiaga
- Department of Psychology, Stanford University, Stanford, California, United States of America
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, United States of America
- BCBL, Basque Center on Cognition, Brain and Language, Mikeletegi Pasealekua, Donostia—San Sebastián, Gipuzkoa, Spain
| | - Noah Benson
- Department of Psychology and Center for Neural Science, New York University, Washington Pl, New York, New York, United States of America
| | - Jonathan Winawer
- Department of Psychology and Center for Neural Science, New York University, Washington Pl, New York, New York, United States of America
| | - Brian A. Wandell
- Department of Psychology, Stanford University, Stanford, California, United States of America
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, California, United States of America
| |
Collapse
|
10
|
Morgan C, Schwarzkopf DS. Comparison of human population receptive field estimates between scanners and the effect of temporal filtering. F1000Res 2019; 8:1681. [PMID: 31885863 PMCID: PMC6913234 DOI: 10.12688/f1000research.20496.2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/24/2020] [Indexed: 11/30/2022] Open
Abstract
Background: Population receptive field (pRF) analysis with functional magnetic resonance imaging (fMRI) is an increasingly popular method for mapping visual field representations and estimating the spatial selectivity of voxels in human visual cortex. However, the multitude of experimental setups and processing methods used makes comparisons of results between studies difficult. Methods: Here, we compared pRF maps acquired in the same three individuals using comparable scanning parameters on a 1.5 and a 3 Tesla scanner located in two different countries. We also tested the effect of low-pass filtering of the time series on pRF estimates. Results: As expected, the signal-to-noise ratio for the 3 Tesla data was superior; critically, however, estimates of pRF size and cortical magnification did not reveal any systematic differences between the sites. Unsurprisingly, low-pass filtering enhanced goodness-of-fit, presumably by removing high-frequency noise. However, there was no substantial increase in the number of voxels containing meaningful retinotopic signals after low-pass filtering. Importantly, filtering also increased estimates of pRF size in the early visual areas which could substantially skew interpretations of spatial tuning properties. Conclusion: Our results therefore suggest that pRF estimates are generally comparable between scanners of different field strengths, but temporal filtering should be used with caution.
Collapse
Affiliation(s)
- Catherine Morgan
- School of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Auckland, New Zealand
- School of Optometry & Vision Science, University of Auckland, Auckland, New Zealand
| | - D. Samuel Schwarzkopf
- School of Optometry & Vision Science, University of Auckland, Auckland, New Zealand
- Experimental Psychology, University College London, London, UK
| |
Collapse
|