Krzysztof Gorgolewski

Krzysztof Gorgolewski
Google Inc. | Google · Research Department

PhD, MRes, BSc

About

149
Publications
47,322
Reads
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11,094
Citations
Citations since 2017
83 Research Items
10164 Citations
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
201720182019202020212022202305001,0001,5002,0002,500
Additional affiliations
September 2014 - August 2015
Stanford University
Position
  • PostDoc Position
September 2012 - September 2014
Max Planck Institute for Human Cognitive and Brain Sciences
Position
  • PostDoc Position
September 2009 - September 2012
The University of Edinburgh
Position
  • PhD Student
Education
September 2009 - September 2012
The University of Edinburgh
Field of study
  • Neuroimaging
September 2008 - September 2009
The University of Edinburgh
Field of study
  • Neuroinforamtics
September 2004 - February 2008
Poznan University of Technology
Field of study
  • Computer Science

Publications

Publications (149)
Article
Full-text available
Reference anatomies of the brain (‘templates’) and corresponding atlases are the foundation for reporting standardized neuroimaging results. Currently, there is no registry of templates and atlases; therefore, the redistribution of these resources occurs either bundled within existing software or in ad hoc ways such as downloads from institutional...
Article
Full-text available
The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include p...
Article
Full-text available
The sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. Here we describe OpenNeuro, a BRAIN Initiative data archive that provides the ability to openly share data from a broad range of brain imaging data types following the FAIR principles for data sharing. We highlig...
Preprint
Full-text available
Neuroimaging templates and corresponding atlases play a central role in experimental workflows and are the foundation for reporting standardised results. The proliferation of templates and atlases is one relevant source of methodological variability across studies, which has been recently brought to attention as an important challenge to reproducib...
Preprint
Full-text available
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention...
Preprint
Full-text available
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention...
Article
Full-text available
Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respect...
Article
Full-text available
Animal neuroimaging studies can provide unique insights into brain structure and function, and can be leveraged to bridge the gap between animal and human neuroscience. In part, this power comes from the ability to combine mechanistic interventions with brain-wide neuroimaging. Due to their phylogenetic proximity to humans, nonhuman primate neuroim...
Article
Full-text available
Population imaging markedly increased the size of functional-imaging datasets, shedding new light on the neural basis of inter-individual differences. Analyzing these large data entails new scalability challenges, computational and statistical. For this reason, brain images are typically summarized in a few signals, for instance reducing voxel-leve...
Article
Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc pre...
Article
Full-text available
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exempl...
Preprint
Full-text available
Population imaging markedly increased the size of functional-imaging datasets, shedding new light on the neural basis of inter-individual differences. Analyzing these large data entails new scalability challenges, computational and statistical. For this reason, brain images are typically summarized in a few signals, for instance reducing voxel-leve...
Article
Full-text available
The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and refer...
Article
Full-text available
The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brai...
Preprint
Full-text available
Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fac...
Article
Full-text available
The reproducibility of scientific research has become a point of critical concern. We argue that openness and transparency are critical for reproducibility, and we outline an ecosystem for open and transparent science that has emerged within the human neuroimaging community. We discuss the range of open data-sharing resources that have been develop...
Preprint
Full-text available
Functional magnetic resonance imaging (fMRI) is widely used to investigate the neural correlates of cognition. fMRI non-invasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc prepro...
Article
Full-text available
The neuroimaging community is steering towards increasingly large sample sizes, which are highly heterogeneous because they can only be acquired by multi-site consortia. The visual assessment of every imaging scan is a necessary quality control step, yet arduous and time-consuming. A sizeable body of evidence shows that images of low quality are a...
Article
A laboratory's programming language has wide-ranging implications. As demands towards scientific programming change and languages evolve, investigators may look to change their existing software stack. Following up on a recent online debate, we discuss key considerations and challenges in choosing and changing languages and suggest solutions for in...
Article
We present a publicly available dataset of 228 healthy participants comprising a young (N=154, 25.1±3.1 years, range 20–35 years, 45 female) and an elderly group (N=74, 67.6±4.7 years, range 59–77 years, 37 female) acquired cross-sectionally in Leipzig, Germany, between 2013 and 2015 to study mind-body-emotion interactions. During a two-day assessm...
Article
Full-text available
The dataset enables exploration of higher-order cognitive faculties, self-generated mental experience, and personality features in relation to the intrinsic functional architecture of the brain. We provide multimodal magnetic resonance imaging (MRI) data and a broad set of state and trait phenotypic assessments: mind-wandering, personality traits,...
Article
Full-text available
We present a publicly available dataset of 227 healthy participants comprising a young (N=153, 25.1±3.1 years, range 20–35 years, 45 female) and an elderly group (N=74, 67.6±4.7 years, range 59–77 years, 37 female) acquired cross-sectionally in Leipzig, Germany, between 2013 and 2015 to study mind-body-emotion interactions. During a two-day assessm...
Article
Full-text available
Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to clean and standardize the data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each dataset, building upon a large inventory of available tools. The complexity of these workflows has snowballed with rapid advances i...
Preprint
Full-text available
Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measures of the living human brain. However, data collection is limited to highly specialized clinical environments. To improve internal (re)use and external sharing of these unique data, we present a structure for storing and sharing...
Preprint
Full-text available
The reproducibility of scientific research has become a point of critical concern. We argue that openness and transparency are critical for reproducibility, and we outline an ecosystem for open and transparent science that has emerged within the human neuroimaging community. We discuss the range of open data sharing resources that have been develop...
Preprint
Full-text available
The neuroimaging community is steering towards increasingly large sample sizes, which are highly heterogeneous because they can only be acquired by multi-site consortia. The visual assessment of every imaging scan is a necessary quality control step, yet arduous and time-consuming. A sizeable body of evidence shows that images of low quality are a...
Chapter
MRIQC is a quality control tool that predicts the binary rating (accept/exclude) that human experts would assign to T1-weighted MR images of the human brain. For such prediction, a random forests classifier performs on a vector of image quality metrics (IQMs) extracted from each image. Although MRIQC achieved an out-of-sample accuracy of \(\sim \)7...
Article
Full-text available
Over the past few decades, neuroscience research has illuminated the neural mechanisms supporting learning from reward feedback. Learning paradigms are increasingly being extended to study mood and psychiatric disorders as well as addiction. However, one potentially critical characteristic that this research ignores is the effect of time on learnin...
Article
Full-text available
Making replication studies widely conducted and published requires new incentives. Academic awards can provide such incentives by highlighting the best and most important replications. The Organization for Human Brain Mapping (OHBM) has led such efforts by recently introducing the OHBM Replication Award. Other communities can adopt this approach to...
Preprint
Full-text available
Over the past few decades, neuroscience research has illuminated the neural mechanisms supporting learning from reward feedback. Learning paradigms are increasingly being extended to study mood and psychiatric disorders as well as addiction. However, one potentially critical characteristic that this research ignores is the effect of time on learnin...
Article
Full-text available
We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acq...
Preprint
Full-text available
Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available for each step. The complexity of these workflows has snowballed with rapid advances in MR data...
Article
Full-text available
We present Boutiques, a system to automatically publish, integrate and execute command-line applications across computational platforms. Boutiques applications are installed through software containers described in a rich and flexible JSON language. A set of core tools facilitate the construction, validation, import, execution, and publishing of ap...
Preprint
Full-text available
Synopsis The MRIQC Web-API is a resource for scientists to train new automatic quality classifiers. The MRIQC Web-API has collected more than 30K sets of image quality measures automatically extracted from BOLD and T1-weighted scans using MRIQC. MRIQC is an automated MRI Quality Control tool, and here we present an extension to crowdsource these qu...
Article
Full-text available
We present Boutiques, a system to automatically publish, integrate and execute applications across computational platforms. Boutiques applications are installed through software containers described in a rich and flexible JSON language. A set of core tools facilitate the construction, validation, import, execution, and publishing of applications. B...
Article
Full-text available
Author summary A central goal of cognitive neuroscience is to decode human brain activity—i.e., to be able to infer mental processes from observed patterns of whole-brain activity. However, existing approaches to brain decoding suffer from a number of important limitations—for example, they often work only in one narrow domain of cognition, and can...
Data
Whole-brain image reconstruction using learned GC-LDA topics. (PDF)
Data
Topic-based reconstruction of whole-brain activity maps. Representative examples from (A) the set of 20 BrainMap ICA components reported in Smith et al. [15]. (B) the NeuroVault whole-brain image repository [2], and (C) single-subject contrast maps from the emotion processing task in the Human Connectome Project dataset (face vs. shape contrast). E...
Data
Topic reconstruction of 100 random maps extracted from the NeuroVault whole-brain image repository. Labels in white indicate human-annotated cognitive atlas paradigm, when available. (JPG)
Data
Full results for all topics learned by the GC-LDA model. Each row represents a single topic. For each topic, the word cloud displays the top semantic associates (the size of each term is roughly proportional to the strength of its loading, and the orthviews display all hard assignments of activations to that topic (each point represents a single ac...
Data
Topic-based decoding of 20 BrainMap-derived ICA components reported in Smith et al. [15]. (JPG)
Data
Topic-based decoding of 12 “cognitive components” reported in Yeo et al. [33]. (JPG)
Data
Topic reconstruction of 12 “cognitive components” reported in Yeo et al. [33]. (JPG)
Data
Reconstruction of 20 BrainMap ICA components reported in Smith et al. [15]. (JPG)
Article
Full-text available
Quality control of MRI is essential for excluding problematic acquisitions and avoiding bias in subsequent image processing and analysis. Visual inspection is subjective and impractical for large scale datasets. Although automated quality assessments have been demonstrated on single-site datasets, it is unclear that solutions can generalize to unse...
Data
Supporting information. All supporting information has been included in one file. (PDF)
Article
Full-text available
Here we present preprocessed MRI data of 265 participants from the Consortium for Neuropsychiatric Phenomics (CNP) dataset. The preprocessed dataset includes minimally preprocessed data in the native, MNI and surface spaces accompanied with potential confound regressors, tissue probability masks, brain masks and transformations. In addition the pre...
Preprint
Full-text available
We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG provides direct measurement of brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS has provided a solution to structure the organization of magne...
Article
Full-text available
Here we present preprocessed MRI data of 265 participants from the Consortium for Neuropsychiatric Phenomics (CNP) dataset. The preprocessed dataset includes minimally preprocessed data in the native, MNI and surface spaces accompanied with potential confound regressors, tissue probability masks, brain masks and transformations. In addition the pre...
Preprint
Full-text available
The dataset enables exploration of higher-order cognitive faculties, self-generated mental experience, and personality features in relation to the intrinsic functional architecture of the brain. We provide multimodal magnetic resonance imaging (MRI) data and a broad set of state and trait phenotypic assessments: mind-wandering, personality traits,...
Article
Full-text available
The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and d...