
Michael HankeForschungszentrum Jülich · Institute of Neurosciences and Medicine (INM)
Michael Hanke
Dr. rer. nat.
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91
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Introduction
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August 2013 - present
August 2009 - July 2011
Publications
Publications (91)
Research data management has become an indispensable skill in modern neuroscience. Researchers can benefit from following good practices as well as from having proficiency in using particular software solutions. But as these domain-agnostic skills are commonly not included in domain-specific graduate education, community efforts increasingly provid...
OHBM Brainhack 2022 took place in June 2022. The first hybrid OHBM hackathon, it had an in-person component taking place in Glasgow and three hubs around the globe to improve inclusivity and fit as many timezones as possible. In the buzzing setting of the Queen Margaret Union and of the virtual platform, 23 projects were presented after development...
Neuroimaging research faces a crisis of reproducibility. With massive sample sizes and greater data complexity, this problem becomes more acute. Software that operates on imaging data defined using the Brain Imaging Data Structure (BIDS)—the BIDS App—has provided a substantial advance. However, even using BIDS Apps, a full audit trail of data proce...
Neuroimaging research faces a crisis of reproducibility. With massive sample sizes and greater data complexity, this problem becomes more acute. Software that operates on imaging data defined using the Brain Imaging Data Structure (BIDS) - BIDS Apps - have provided a substantial advance. However, even using BIDS Apps, a full audit trail of data pro...
An increasing number of studies have investigated the relationships between inter-individual variability in brain regions’ connectivity and behavioral phenotypes, making use of large population neuroimaging datasets. However, the replicability of brain-behavior associations identified by these approaches remains an open question. In this study, we...
Large-scale datasets present unique opportunities to perform scientific investigations with unprecedented breadth. However, they also pose considerable challenges for the findability, accessibility, interoperability, and reusability (FAIR) of research outcomes due to infrastructure limitations, data usage constraints, or software license restrictio...
Large-scale datasets present unique opportunities to perform scientific investigations with unprecedented breadth. However, they also pose considerable challenges for the findability, accessibility, interoperability, and reusability (FAIR) of research outcomes due to infrastructure limitations, data usage constraints, or software license restrictio...
DataLad is a Python-based tool for the joint management of code, data, and their relationship,built on top of a versatile system for data logistics (git-annex) and the most popular distributed version control system (Git). It adapts principles of open-source software development and distribution to address the technical challenges of data managemen...
Decentralized research data management (dRDM) systems handle digital research objects across participating nodes without critically relying on central services. We present four perspectives in defense of dRDM, illustrating that, in contrast to centralized or federated research data management solutions, a dRDM system based on heterogeneous but inte...
Taste processing is an essential ability in all animals signaling potential harm or benefit of ingestive behavior. However, current evidence for cortical taste representations remains contradictory. To address this issue, high-resolution functional MRI (fMRI) and multivariate pattern analysis were used to characterize taste-related informational co...
We investigated if the fusiform face area (FFA) and the parahippocampal place area (PPA) contain a representation of fixation sequences that are typically used when looking at faces or houses. Here, we instructed observers to follow a dot presented on a uniform background. The dot’s movements represented gaze paths acquired separately from observer...
Naturalistic stimuli show significant potential to inform behavioral, cognitive, and clinical neuroscience. To date, this impact is still limited by the relative inaccessibility of both generated neuroimaging data as well as the supporting naturalistic stimuli. In this perspective, we highlight currently available naturalistic datasets and technica...
The simultaneous acquisition of functional magnetic resonance imaging (fMRI) with in-scanner eye tracking promises to combine the advantages of full-brain coverage of brain activity measurements with a fast and unobtrusive capture of eye movement behavior and attentional deployment. Despite its applicability to a wide variety of research questions,...
Taste processing is an essential ability in all animals signaling potential harm or benefit of ingestive behavior. Although the peripheral taste coding is well understood, current evidence for central taste processing remains contradictory. To address this issue, human participants judged pleasantness and intensity of low and high-concentration tas...
We investigated if the fusiform face area (FFA) and the parahippocampal place area (PPA) contain a representation of fixation sequences that are typically used when looking at faces or houses. For this purpose, we instructed observers to follow a dot presented on a uniform background. The dot's movements represented gaze paths acquired separately w...
There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generali...
There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generali...
Previously published results indicate that the accuracy of decoding visual orientation from 7 Tesla fMRI data of V1 peaks at spatial acquisition resolutions that are routinely accessible with more conventional 3 Tesla scanners. This study directly compares the decoding performance between a 3 Tesla and a 7 Tesla dataset that were acquired using the...
Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation – primarily in the visual cortex. Previous research indicates that such signals are spatially broadband in n...
Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation – primarily in the visual cortex. Previous research indicates that such signals are spatially broadband in n...
Little is known about the cortical regions involved in representing task-related content in preparation for visual task performance. Here we used representational similarity analysis (RSA) to investigate the BOLD response pattern similarity between task relevant and task irrelevant feature dimensions during conjunction viewing and target template m...
The perception of an acoustic rhythm is invariant to the absolute temporal intervals constituting a sound sequence. It is unknown where in the brain temporal Gestalt, the percept emerging from the relative temporal proximity between acoustic events, is encoded. Two different relative temporal patterns, each induced by 3 experimental conditions with...
A central tenet in chemosensory research is the characterisation of gustatory cortex. Tastant-specific neural populations have been identified in the macaque (Scott et al., 1999) and rat homologues of human insula (Peng et al., 2015). To date, however, only one fMRI-study (Schoenfeld et al., 2004) reported similar tastant-related activated patterns...
This article is based on discussions from a workshop to encourage sharing in neuroscience, held in Cambridge, UK, December 2014. It was financially supported and organized by the International Neuroinformatics Coordinating Facility (http://www.incf.org), with additional support from the Software Sustainability institute (http://www.software.ac.uk)....
Computational techniques are central in many areas of neuroscience and are relatively easy to share. This paper describes why computer programs underlying scientific publications should be shared and lists simple steps for sharing. Together with ongoing efforts in data sharing, this should aid reproducibility of research.
Multivariate pattern classification methods have been successfully applied to decode orientation of visual grating stimuli from BOLD fMRI activity recorded in human visual cortex ([12,10]). Though there has been extensive research investigating the true spatial scale of the orientation specific signals ([2,15,1,4,5]), it remained inconclusive what...
Goal-directed behavior in a complex world requires the maintenance of goal-relevant information despite multiple sources of distraction. However, the brain mechanisms underlying distractor-resistant working or short-term memory (STM) are not fully understood. Although early single-unit recordings in monkeys and fMRI studies in humans pointed to an...
Given concerns about the reproducibility of scientific findings, neuroimaging must define best practices for data analysis, results reporting, and algorithm and data sharing to promote transparency, reliability and collaboration. We describe insights from developing a set of recommendations on behalf of the Organization for Human Brain Mapping and...
A decade after it was shown that the orientation of visual grating stimuli can be decoded from human visual cortex activity by means of multivariate pattern classification of BOLD fMRI data, numerous studies have investigated which aspects of neuronal activity are reflected in BOLD response patterns and are accessible for decoding. However, it rema...
The studyforrest (http://studyforrest.org) dataset is likely the largest neuroimaging dataset on natural language and story processing publicly available today. In this article, along with a companion publication, we present an update of this dataset that extends its scope to vision and multi-sensory research. 15 participants of the original cohort...
Here we present an update of the studyforrest (http://studyforrest.org) dataset that complements the previously released functional magnetic resonance imaging (fMRI) data for natural language processing with a new two-hour 3 Tesla fMRI acquisition while 15 of the original participants were shown an audio-visual version of the stimulus motion pictur...
A decade after it was shown that the orientation of visual grating stimuli can be decoded from human visual cortex activity by means of multivariate pattern classification of BOLD fMRI data, numerous studies have investigated which aspects of neuronal activity are reflected in BOLD response patterns and are accessible for decoding. However, it rema...
Here we extend the information on the structure of the core stimulus of the studyforrest project (http://studyforrest.org) with a description of semantic conflict in the " Forrest Gump " movie. Three observers annotated the movie independently regarding episodes with portrayal of lies, irony or sarcasm. We present frequency statistics, and inter-ob...
The Python script to compute all descriptive statistics presented in the paper from the released annotations is provided.
Events of semantic conflict and occurrences of irony cues in the motion picture "Forrest Gump"
Raw data are presented in csv tables.
Here we present an annotation of locations and temporal progression depicted in the movie " Forrest Gump " , as an addition to a large public functional brain imaging dataset (). The annotation provides http://studyforrest.org information about the exact timing of each of the 870 shots, and the depicted location after every cut with a high, medium,...
Python script to compute all descriptive statistics presented in the Data Note manuscript from the released annotations
CSV table with of depicted locations, and temporal progression in the motion picture “Forrest Gump”
Each row corresponds to a shot in the the movie
Previous studies have found a network from prefrontal to posterior parietal and ventral visual regions involved in feature-based attention control and task-relevant content representation. There is much debate about the different functions of these regions and where stimulus information is represented in preparation for visual search. Here we inves...
Neuroimaging enables rich noninvasive measurements of human brain activity, but translating such data into neuroscientific insights and clinical applications requires complex analyses and collaboration among a diverse array of researchers. The open science movement is reshaping scientific culture and addressing the challenges of transparency and re...
The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience res...
Here we present an update of the studyforrest ( http://studyforrest.org ) dataset that complements the previously released functional magnetic resonance imaging (fMRI) data for natural language processing with a new two-hour 3Tesla fMRI acquisition while 15 of the original participants were shown an audio-visual version of the stimulus motion pictu...
The studyforrest ( http://studyforrest.org ) dataset is likely the largest neuroimag-ing dataset on natural language and story processing publicly available today. In this article, along with a companion publication, we present an update of this dataset that extends its scope to vision and multi-sensory research. 15 participants of the original coh...
The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience res...
Current models of the functional architecture of human cortex emphasize areas that capture coarse-scale features of cortical
topography but provide no account for population responses that encode information in fine-scale patterns of activity. Here,
we present a linear model of shared representational spaces in human cortex that captures fine-scale...
Many areas of neuroscience are now critically dependent on computational tools to help understand the large volumes of data being created. Furthermore, computer models are increasingly being used to help predict and understand the function of the nervous system. Many of these computations are complex and often cannot be concisely reported in the me...
We developed task-optimized deep neural networks (DNNs) that achieved state-of-the-art performance in different evaluation scenarios for automatic music tagging. These DNNs were subsequently used to probe the neural representations of music. Representational similarity analysis revealed the existence of a representational gradient across the superi...
Unrestricted dissemination of methodological developments in neuroimaging became the propelling force in advancing our understanding of brain function. However, despite such a rich legacy, it remains not uncommon to encounter software and datasets that are distributed under unnecessarily restricted terms, or that violate terms of third-party produc...
Here we present an extension to the studyforrest dataset – a versatile resource for studying the behavior of the human brain in situations of real-life complexity (http://studyforrest.org). This release adds more high-resolution, ultra high-field (7 Tesla) functional magnetic resonance imaging (fMRI) data from the same individuals. The twenty parti...
Here we present a dataset with a description of portrayed emotions in the movie "Forrest Gump". A total of 12 observers independently annotated emotional episodes regarding their temporal location and duration. The nature of an emotion was characterized with basic attributes, such as arousal and valence, as well as explicit emotion category labels....
Studying the brain's behavior in situations of real-life complexity is crucial for an understanding of brain function as a whole. However, methodological difficulties and a general lack of public resources are hindering scientific progress in this domain. This channel will serve as a communication hub to collect relevant resources and curate knowle...
Introduction: Typically the output of a human neuroimaging experiment is a complex, heterogeneous and multidimensional dataset that can be arranged and described in many different ways. So far there is no consensus on how to organize and share raw data obtained in such experiments. For example, two researchers working in the same lab can choose to...
We investigated the neural basis of conjoined processing of color and spatial frequency with functional magnetic resonance imaging (fMRI). A multivariate classification algorithm was trained to differentiate between either isolated color or spatial frequency differences, or between conjoint differences in both feature dimensions. All displays were...
Here we present a high-resolution functional magnetic resonance (fMRI) dataset - 20 participants recorded at high field strength (7 Tesla) during prolonged stimulation with an auditory feature film ("Forrest Gump"). In addition, a comprehensive set of auxiliary data (T1w, T2w, DTI, susceptibility-weighted image, angiography) as well as measurements...
Over the last decades the majority of studies that investigated the neuronal basis of visual attention and the tightly coupled oculomotor system employed paradigms in which the attention shifts and associated eye movements were highly controlled by a given task and a distinct set of artificial stimuli. Few studies examined how attention and eye-mov...
Localizing neuronal activity in the brain, both in time and in space, is a
central challenge to advance the understanding of brain function. Because of
the inability of any single neuroimaging techniques to cover all aspects at
once, there is a growing interest to combine signals from multiple modalities
in order to benefit from the advantages of e...
The neural substrates of feature binding are an old, yet still not completely resolved problem. While patient studies suggest that posterior parietal cortex is necessary for feature binding, imaging evidence has been inconclusive in the past. These studies compared visual feature and conjunction search to investigate the neural substrate of feature...
Nipype is data processing framework written in Python. Its main goal is to provide a uniform access to many already existing neuroimaging tools. These currently include but are not limited to: FSL, SPM, FreeSurfer, and AFNI. At its core Nipype is a library of wrappers that take care of parsing and validating inputs, executing the software (whether...
). However, collecting these resources into a centralized clearing-house addresses only one necessary aspect on the way to a sustainable software ecosystem for neuroscience – availability. Unfortunately it does not ensure ease of deployment, nor does it offer a sustainable model for long-term maintenance.At the same time, the development model of m...
Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increas...
Evidence of category specificity from neuroimaging in the human visual system is generally limited to a few relatively coarse categorical distinctions-e.g., faces versus bodies, or animals versus artifacts-leaving unknown the neural underpinnings of fine-grained category structure within these large domains. Here we use fMRI to explore brain activi...
We present a high-dimensional model of the represent