Alexander M. Puckett
Alexander M. Puckett
School of Psychology, University of Queensland
Adresse e-mail validée de alumni.msoe.edu
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Serial correlations in single-subject fMRI with sub-second TR
S Bollmann, AM Puckett, R Cunnington, M Barth
NeuroImage 166, 152-166, 2018
352018
The attentional field revealed by single-voxel modeling of fMRI time courses
AM Puckett, EA DeYoe
Journal of Neuroscience 35 (12), 5030-5042, 2015
332015
The spatiotemporal hemodynamic response function for depth-dependent functional imaging of human cortex
AM Puckett, KM Aquino, PA Robinson, M Breakspear, MM Schira
Neuroimage 139, 240-248, 2016
302016
Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI
AM Puckett, S Bollmann, M Barth, R Cunnington
Neuroimage 161, 179-187, 2017
262017
An investigation of positive and inverted hemodynamic response functions across multiple visual areas
AM Puckett, JR Mathis, EA DeYoe
Human brain mapping 35 (11), 5550-5564, 2014
192014
Using multi-echo simultaneous multi-slice (SMS) EPI to improve functional MRI of the subcortical nuclei of the basal ganglia at ultra-high field (7T)
AM Puckett, S Bollmann, BA Poser, J Palmer, M Barth, R Cunnington
Neuroimage 172, 886-895, 2018
142018
Bayesian population receptive field modeling in human somatosensory cortex
AM Puckett, S Bollmann, K Junday, M Barth, R Cunnington
Neuroimage 208, 116465, 2020
122020
Susceptibility artifact correction for sub-millimeter fMRI using inverse phase encoding registration and T1 weighted regularization
STM Duong, SL Phung, A Bouzerdoum, HGB Taylor, AM Puckett, ...
Journal of neuroscience methods 336, 108625, 2020
22020
Non-linear Realignment Using Minimum Deformation Averaging for Single-subject fMRI at Ultra-high Field
S Bollmann, S Bollmann, A Puckett, AL Janke, M Barth
Proc. Intl. Soc. Mag. Reson. Med 25, 2017
22017
Manipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain
AM Puckett, MM Schira, ZJ Isherwood, JD Victor, JA Roberts, ...
NeuroImage 221, 117173, 2020
12020
Predicting brain function from anatomy using geometric deep learning
FL Ribeiro, S Bollmann, AM Puckett
BioRXiv, 2020
12020
Population Attentional Field Modeling
E DeYoe, A Puckett, Y Ma
Journal of Vision 13 (9), 232-232, 2013
12013
Predicting the functional organization of human visual cortex from anatomy using geometric deep learning
A Puckett, S Bollmann, F Ribeiro
Journal of Vision 20 (11), 928-928, 2020
2020
DeepRetinotopy: Predicting the Functional Organization of Human Visual Cortex from Structural MRI Data using Geometric Deep Learning
FL Ribeiro, S Bollmann, AM Puckett
arXiv preprint arXiv:2005.12513, 2020
2020
Vascular effects on the BOLD response and the retinotopic mapping of hV4
HG Boyd Taylor, AM Puckett, ZJ Isherwood, MM Schira
PloS one 14 (6), e0204388, 2019
2019
Anatomy-guided Inverse-phase-encoding Registration Method for Correcting Susceptibility Artifacts in Sub-millimeter fMRI
STM Duong, SL Phung, A Bouzerdoum, HGB Taylor, AM Puckett, ...
bioRxiv, 779272, 2019
2019
Why are hV4 maps incomplete in the left visual cortex but complete in the right hemisphere?
HB Taylor, M Schira, Z Isherwood, A Puckett
Journal of Vision 18 (10), 578-578, 2018
2018
Mapping human V4: Correcting artefact reveals hemifield organisation
H Taylor, AM Puckett, ZJ Isherwood, MM Schira
2015
Measuring the attentional field throughout human visual cortex
AM Puckett, EA DeYoe
Conference Abstract: ACNS-2013 Australasian Cognitive Neuroscience Society …, 2013
2013
Towards concrete, in-depth and applicable predictions of BOLD responses; modelling the complete cascade from visual stimulus to neuronal response to vascular hemodynamics
MM Schira, AM Puckett, M Breakspear, P Robinson, KM Aquino
Conference Abstract: ACNS-2013 Australasian Cognitive Neuroscience Society …, 2013
2013
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