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Article ; Online: Visual encoding: Principles and software.

Wandell, Brian A / Brainard, David H / Cottaris, Nicolas P

2022 Volume 273, Issue 1, Page(s) 199–229

Abstract: For more than two centuries scientists and engineers have worked to understand and model how the eye encodes electromagnetic radiation (light). We now understand the principles of how light is transmitted through the optics of the eye and encoded by ... ...

Abstract	For more than two centuries scientists and engineers have worked to understand and model how the eye encodes electromagnetic radiation (light). We now understand the principles of how light is transmitted through the optics of the eye and encoded by retinal photoreceptors and light-sensitive neurons. In recent years, new instrumentation has enabled scientists to measure the specific parameters of the optics and photoreceptor encoding. We implemented the principles and parameter estimates that characterize the human eye in an open-source software toolbox. This chapter describes the principles behind these tools and illustrates how to use them to compute the initial visual encoding.
MeSH term(s)	Humans ; Optics and Photonics ; Photoreceptor Cells, Vertebrate ; Retina/physiology ; Retinal Cone Photoreceptor Cells ; Software
Language	English
Publishing date	2022-06-29
Publishing country	Netherlands
Document type	Journal Article
ISSN	1875-7855 ; 0079-6123
ISSN (online)	1875-7855
ISSN	0079-6123
DOI	10.1016/bs.pbr.2022.04.006
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Clarifying Human White Matter.

Wandell, Brian A

Annual review of neuroscience

2016 Volume 39, Page(s) 103–128

Abstract: Progress in magnetic resonance imaging (MRI) now makes it possible to identify the major white matter tracts in the living human brain. These tracts are important because they carry many of the signals communicated between different brain regions. MRI ... ...

Abstract	Progress in magnetic resonance imaging (MRI) now makes it possible to identify the major white matter tracts in the living human brain. These tracts are important because they carry many of the signals communicated between different brain regions. MRI methods coupled with biophysical modeling can measure the tissue properties and structural features of the tracts that impact our ability to think, feel, and perceive. This review describes the fundamental ideas of the MRI methods used to identify the major white matter tracts in the living human brain.
Language	English
Publishing date	2016-07-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	282459-0
ISSN	1545-4126 ; 0147-006X
ISSN (online)	1545-4126
ISSN	0147-006X
DOI	10.1146/annurev-neuro-070815-013815
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Article ; Online: Reproducible Tract Profiles 2 (RTP2) suite, from diffusion MRI acquisition to clinical practice and research.

Lerma-Usabiaga, Garikoitz / Liu, Mengxing / Paz-Alonso, Pedro M / Wandell, Brian A

Scientific reports

2023 Volume 13, Issue 1, Page(s) 6010

Abstract: Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In ...

Abstract	Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In the present work we introduce Reproducible Tract Profiles 2 (RTP2), a set of flexible and automated methods to analyze anatomical MRI and diffusion weighted imaging (DWI) data for reproducible tractography. RTP2 reads structural MRI data and processes them through a succession of serialized containerized analyses. We describe the DWI algorithms used to identify white-matter tracts and their summary metrics, the flexible architecture of the platform, and the tools to programmatically access and control the computations. The combination of these three components provides an easy-to-use automatized tool developed and tested over 20 years, to obtain usable and reliable state-of-the-art diffusion metrics at the individual and group levels for basic research and clinical practice.
MeSH term(s)	Brain/diagnostic imaging ; Diffusion Magnetic Resonance Imaging/methods ; White Matter ; Magnetic Resonance Imaging ; Algorithms
Language	English
Publishing date	2023-04-12
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-32924-7
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Article ; Online: Measuring brain beats: Cardiac-aligned fast functional magnetic resonance imaging signals.

Hermes, Dora / Wu, Hua / Kerr, Adam B / Wandell, Brian A

Human brain mapping

2022 Volume 44, Issue 1, Page(s) 280–294

Abstract: Blood and cerebrospinal fluid (CSF) pulse and flow throughout the brain, driven by the cardiac cycle. These fluid dynamics, which are essential to healthy brain function, are characterized by several noninvasive magnetic resonance imaging (MRI) methods. ... ...

Abstract	Blood and cerebrospinal fluid (CSF) pulse and flow throughout the brain, driven by the cardiac cycle. These fluid dynamics, which are essential to healthy brain function, are characterized by several noninvasive magnetic resonance imaging (MRI) methods. Recent developments in fast MRI, specifically simultaneous multislice acquisition methods, provide a new opportunity to rapidly and broadly assess cardiac-driven flow, including CSF spaces, surface vessels and parenchymal vessels. We use these techniques to assess blood and CSF flow dynamics in brief (3.5 min) scans on a conventional 3 T MRI scanner in five subjects. Cardiac pulses are measured with a photoplethysmography (PPG) on the index finger, along with functional MRI (fMRI) signals in the brain. We, retrospectively, align the fMRI signals to the heartbeat. Highly reliable cardiac-gated fMRI temporal signals are observed in CSF and blood on the timescale of one heartbeat (test-retest reliability within subjects R
MeSH term(s)	Humans ; Reproducibility of Results ; Retrospective Studies ; Brain/physiology ; Magnetic Resonance Imaging/methods ; Heart/diagnostic imaging
Language	English
Publishing date	2022-10-29
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1197207-5
ISSN	1097-0193 ; 1065-9471
ISSN (online)	1097-0193
ISSN	1065-9471
DOI	10.1002/hbm.26128
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Zs.A 4028: Show issues

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Article ; Online: Population Receptive Field Shapes in Early Visual Cortex Are Nearly Circular.

Lerma-Usabiaga, Garikoitz / Winawer, Jonathan / Wandell, Brian A

The Journal of neuroscience : the official journal of the Society for Neuroscience

2021 Volume 41, Issue 11, Page(s) 2420–2427

Abstract: The visual field region where a stimulus evokes a neural response is called the receptive field (RF). Analytical tools combined with functional MRI (fMRI) can estimate the RF of the population of neurons within a voxel. Circular population RF (pRF) ... ...

Abstract	The visual field region where a stimulus evokes a neural response is called the receptive field (RF). Analytical tools combined with functional MRI (fMRI) can estimate the RF of the population of neurons within a voxel. Circular population RF (pRF) methods accurately specify the central position of the pRF and provide some information about the spatial extent (diameter) of the RF. A number of investigators developed methods to further estimate the shape of the pRF, for example, whether the shape is more circular or elliptical. There is a report that there are many pRFs with highly elliptical pRFs in early visual cortex (V1-V3; Silson et al., 2018). Large aspect ratios (>2) are difficult to reconcile with the spatial scale of orientation columns or visual field map properties in early visual cortex. We started to replicate the experiments and found that the software used in the publication does not accurately estimate RF shape: it produces elliptical fits to circular ground-truth data. We analyzed an independent data set with a different software package that was validated over a specific range of measurement conditions, to show that in early visual cortex the aspect ratios are <2. Furthermore, current empirical and theoretical methods do not have enough precision to discriminate ellipses with aspect ratios of 1.5 from circles. Through simulation we identify methods for improving sensitivity that may estimate ellipses with smaller aspect ratios. The results we present are quantitatively consistent with prior assessments using other methodologies.
MeSH term(s)	Algorithms ; Brain Mapping/methods ; Computer Simulation ; Humans ; Models, Neurological ; Software ; Visual Cortex/physiology
Language	English
Publishing date	2021-02-02
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	604637-x
ISSN	1529-2401 ; 0270-6474
ISSN (online)	1529-2401
ISSN	0270-6474
DOI	10.1523/JNEUROSCI.3052-20.2021
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Article ; Online: Reproducible Tract Profiles 2 (RTP2) suite, from diffusion MRI acquisition to clinical practice and research

Garikoitz Lerma-Usabiaga / Mengxing Liu / Pedro M. Paz-Alonso / Brian A. Wandell

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 13

Abstract: Abstract Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary ... ...

Abstract	Abstract Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In the present work we introduce Reproducible Tract Profiles 2 (RTP2), a set of flexible and automated methods to analyze anatomical MRI and diffusion weighted imaging (DWI) data for reproducible tractography. RTP2 reads structural MRI data and processes them through a succession of serialized containerized analyses. We describe the DWI algorithms used to identify white-matter tracts and their summary metrics, the flexible architecture of the platform, and the tools to programmatically access and control the computations. The combination of these three components provides an easy-to-use automatized tool developed and tested over 20 years, to obtain usable and reliable state-of-the-art diffusion metrics at the individual and group levels for basic research and clinical practice.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Diagnosing the Neural Circuitry of Reading.

Wandell, Brian A / Le, Rosemary K

Neuron

2017 Volume 96, Issue 2, Page(s) 298–311

Abstract: We summarize the current state of knowledge of the brain's reading circuits, and then we describe opportunities to use quantitative and reproducible methods for diagnosing these circuits. Neural circuit diagnostics-by which we mean identifying the ... ...

Abstract	We summarize the current state of knowledge of the brain's reading circuits, and then we describe opportunities to use quantitative and reproducible methods for diagnosing these circuits. Neural circuit diagnostics-by which we mean identifying the locations and responses in an individual that differ significantly from measurements in good readers-can help parents and educators select the best remediation strategy. A sustained effort to develop and share diagnostic methods can support the societal goal of improving literacy.
MeSH term(s)	Brain/diagnostic imaging ; Brain/physiology ; Brain Mapping/methods ; Humans ; Magnetic Resonance Imaging/methods ; Nerve Net/diagnostic imaging ; Nerve Net/physiology ; Reading ; Retinal Ganglion Cells/physiology
Language	English
Publishing date	2017-10-11
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	808167-0
ISSN	1097-4199 ; 0896-6273
ISSN (online)	1097-4199
ISSN	0896-6273
DOI	10.1016/j.neuron.2017.08.007
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Zs.A 2496: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MG 92: Show issues

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Book ; Online: Using simulation to quantify the performance of automotive perception systems

Liu, Zhenyi / Shah, Devesh / Rahimpour, Alireza / Upadhyay, Devesh / Farrell, Joyce / Wandell, Brian A

2023

Abstract: The design and evaluation of complex systems can benefit from a software simulation - sometimes called a digital twin. The simulation can be used to characterize system performance or to test its performance under conditions that are difficult to measure ...

Abstract	The design and evaluation of complex systems can benefit from a software simulation - sometimes called a digital twin. The simulation can be used to characterize system performance or to test its performance under conditions that are difficult to measure (e.g., nighttime for automotive perception systems). We describe the image system simulation software tools that we use to evaluate the performance of image systems for object (automobile) detection. We describe experiments with 13 different cameras with a variety of optics and pixel sizes. To measure the impact of camera spatial resolution, we designed a collection of driving scenes that had cars at many different distances. We quantified system performance by measuring average precision and we report a trend relating system resolution and object detection performance. We also quantified the large performance degradation under nighttime conditions, compared to daytime, for all cameras and a COCO pre-trained network.
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Graphics ; Electrical Engineering and Systems Science - Image and Video Processing
Subject code	006
Publishing date	2023-03-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A convolutional neural network reaches optimal sensitivity for detecting some, but not all, patterns

Reith, Fabian H. / Wandell, Brian A.

2019

Abstract: We investigate the performance of modern convolutional neural networks (CNN) and a linear support vector machine (SVM) with respect to spatial contrast sensitivity. Specifically, we compare CNN sensitivity to that of a Bayesian ideal observer (IO) with ... ...

Abstract	We investigate the performance of modern convolutional neural networks (CNN) and a linear support vector machine (SVM) with respect to spatial contrast sensitivity. Specifically, we compare CNN sensitivity to that of a Bayesian ideal observer (IO) with the signal-known-exactly and noise known statistically. A ResNet-18 reaches optimal performance for harmonic patterns, as well as several classes of real world signals including faces. For these stimuli the CNN substantially outperforms the SVM. We further analyzed the case in which the signal might appear in one of multiple locations and found that CNN spatial sensitivity continues to match the IO. However, the CNN sensitivity was far below optimal at detecting certain complex texture patterns. These measurements show that CNNs can have very large performance differences when detecting the presence of spatial patterns. These differences may have a significant impact on the performance of an imaging system designed to detect low contrast spatial patterns. Comment: 22 pages, 8 figures, pre-print
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2019-11-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A validation framework for neuroimaging software: The case of population receptive fields.

Lerma-Usabiaga, Garikoitz / Benson, Noah / Winawer, Jonathan / Wandell, Brian A

PLoS computational biology

2020 Volume 16, Issue 6, Page(s) e1007924

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 ... ...

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.
MeSH term(s)	Humans ; Magnetic Resonance Imaging ; Nervous System/diagnostic imaging ; Software
Language	English
Publishing date	2020-06-25
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Validation Study
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1007924
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