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Chemically based mathematical model for development of cerebral cortical folding patterns

PLoS computational biology, 2009-09, Vol.5 (9), p.e1000524-e1000524

2009

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Cortical cartography using the discrete conformal approach of circle packings

NeuroImage (Orlando, Fla.), 2004, Vol.23, p.S119-S128

2004

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Analysis of the Trojan Y chromosome model for eradication of invasive species in a dendritic riverine system

Journal of mathematical biology, 2012, Vol.64 (1-2), p.319-340

2012

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A Mathematical Model of Cerebral Cortical Folding Development

Biophysical journal, 2020-02, Vol.118 (3), p.289a-289a

2020

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Estimating linear cortical magnification in human primary visual cortex via dynamic programming

NeuroImage (Orlando, Fla.), 2006-05, Vol.31 (1), p.125-138

2006

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Quantitative evaluation of three cortical surface flattening methods

NeuroImage (Orlando, Fla.), 2005-12, Vol.28 (4), p.869-880

2005

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Growth in a Turing Model of Cortical Folding

Biomath (Sofia, Bulgaria), 2012-09, Vol.1 (1)

2012

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Turing models of cortical folding on exponentially and logistically growing domains

Computers & mathematics with applications (1987), 2013-11, Vol.66 (9), p.1627-1642

2013

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Shape analysis for automated sulcal classification and parcellation of MRI data

Journal of combinatorial optimization, 2008-04, Vol.15 (3), p.257-275

2008

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Pattern Formation in Turing Systems on Domains with Exponentially Growing Structures

Journal of dynamics and differential equations, 2014-06, Vol.26 (2), p.315-332

2014

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Clustering of Dependent Components: A New Paradigm for fMRI Signal Detection

EURASIP journal on advances in signal processing, 2005-11, Vol.2005 (19), p.490821-490821

2005

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Chemically Based Mathematical Model for Development of Cerebral Cortical Folding Patterns: e1000524

PLoS computational biology, 2009-09, Vol.5 (9)

2009

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Clustering of Dependent Components: A New Paradigm for fMRI Signal Detection

EURASIP Journal on Applied Signal Processing, 2005-01, Vol.2005 (19), p.3089-3102, Article 490821

2005

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Coordinate systems for conformal cerebellar flat maps

NeuroImage (Orlando, Fla.), 2000-05, Vol.11 (5), p.S467-S467

2000

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Shape analysis for automated sulcal classification and parcellation of MRI data: Combinatorial Optimization in Data Mining

Journal of combinatorial optimization, 2008, Vol.15 (3), p.257-275

2008

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Visual evoked potentials to small stimuli presented along a vertical meridian: Individual differences and dipole modelling

Australian journal of psychology, 1994-08, Vol.46 (2), p.87-94

1994

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Mathematical and computer modelling of the human brain with reference to cortical magnification and dipole source localisation in the visual cortex

Journal and proceedings of the Royal Society of New South Wales, 2000-12, Vol.133 (3-4), p.94-94

Hurdal, Monica K

2000

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Geometric invariants for classification of cortical sulci

2008 15th IEEE International Conference on Image Processing, 2008, p.1156-1159

2008

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Comparison of three cortical flat mapping techniques using simulated cerebella

NeuroImage (Orlando, Fla.), 2001-06, Vol.13 (6), p.157-157

2001

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Quasi-Conformally Flat Mapping the Human Cerebellum

Medical Image Computing and Computer-Assisted Intervention – MICCAI’99, p.279-286

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A Biomechanical Model of Cortical Folding

Research in Shape Modeling, p.41-55

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Dipole modelling for the localization of human visual evoked scalp potential sources

Journal and proceedings of the Royal Society of New South Wales, 1995-06, Vol.128 (1-2), p.36-38

Hurdal, Monica K

1995

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Case study: interacting with cortical flat maps of the human brain

Proceedings of the conference on Visualization '01, 2001, p.469-472

2001

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Dipole modelling for the localization of human visual evoked scalp potential sources

Hurdal, Monica K

1994

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Clustering of dependent components : A new paradigm for fMRI signal detection: Trends in brain-computer interfaces

EURASIP journal on applied signal processing, 2005, Vol.2005 (19), p.3089-3102

2005

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Chemically based mathematical model for development of cerebral cortical folding patterns

Cortical cartography using the discrete conformal approach of circle packings

Analysis of the Trojan Y chromosome model for eradication of invasive species in a dendritic riverine system

A Mathematical Model of Cerebral Cortical Folding Development

Estimating linear cortical magnification in human primary visual cortex via dynamic programming

Quantitative evaluation of three cortical surface flattening methods

Growth in a Turing Model of Cortical Folding

Turing models of cortical folding on exponentially and logistically growing domains

Shape analysis for automated sulcal classification and parcellation of MRI data

Pattern Formation in Turing Systems on Domains with Exponentially Growing Structures

Clustering of Dependent Components: A New Paradigm for fMRI Signal Detection

Chemically Based Mathematical Model for Development of Cerebral Cortical Folding Patterns: e1000524

Clustering of Dependent Components: A New Paradigm for fMRI Signal Detection

Coordinate systems for conformal cerebellar flat maps

Shape analysis for automated sulcal classification and parcellation of MRI data: Combinatorial Optimization in Data Mining

Visual evoked potentials to small stimuli presented along a vertical meridian: Individual differences and dipole modelling

Mathematical and computer modelling of the human brain with reference to cortical magnification and dipole source localisation in the visual cortex

Geometric invariants for classification of cortical sulci

Comparison of three cortical flat mapping techniques using simulated cerebella

Quasi-Conformally Flat Mapping the Human Cerebellum

A Biomechanical Model of Cortical Folding

Dipole modelling for the localization of human visual evoked scalp potential sources

Case study: interacting with cortical flat maps of the human brain

Dipole modelling for the localization of human visual evoked scalp potential sources

Clustering of dependent components : A new paradigm for fMRI signal detection: Trends in brain-computer interfaces

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