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260 lines
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<title>Research</title>
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<meta name="save_as" content="research.html" />
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<meta name="url" content="research.html" />
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<body>
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<p>Our research covers a broad range from advancing research methodology, to
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the actual engineering of readily usable tools, to the application of such
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developments to concrete research questions in medicine, psychology, or
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cognitive neuroscience — because there is nothing worse than a solution
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without a problem.</p>
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<h2>Ongoing Projects</h2>
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<p>A main research focus lies on studying the representation of information
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about, and for interacting with, the environment. We believe that
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ecologically valid conclusions about these representations can only be drawn
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when they are also studied under conditions of real-life complexity. Hence
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our aim is to combine controlled experiments with complex natural stimulation
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in order to validate our findings. The second major focus is the development
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of tools and workflow capable of managing and processing the large and
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versatile dataset that are required to pursue these research aims.</p>
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<section id="studyforrest" class="alternate">
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<div class='sponsor-logos'>
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<img src="/img/logo/lsa.svg" alt="German State of Sachsen-Anhalt Logo" />
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<img src="/img/logo/erdf.svg" alt="European Reginal Development Fund Logo" />
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</div>
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<h3>The studyforrest Project</h3>
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<p>This is a long-running project that aims to built a unique resource for
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studying the brain's natural behavior. It combines brain imaging with other
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data acquisition techniques to capture a versatile recording of the human
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response to a prolonged complex natural stimulus, the motion picture
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"Forrest Gump".</p>
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<p>We invite anyone and everyone to participate in this decentralized effort
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to explore the opportunities of open science in neuroimaging. One of our
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goals is to document how much (scientific) value can be generated — from the
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publication of scientific findings derived from this dataset, algorithms and
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methods evaluated on this dataset, and/or extensions of this dataset by the
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acquisition and incorporation of new data.</p>
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<div class="figure">
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<img alt="studyforrest data overview" src="/img/studyforrest_figure.png" />
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<p>Overview of functional (top), and structural (middle)
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brain imaging data, as well as annotations of the complex real-life
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stimulus (bottom) that are available through the studyforrest.org
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project.</p>
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</div>
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<p>Since 2014, a number of datasets have been publicly released for
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unrestricted use, covering functional and structural brain imaging, eye
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tracking, physiological recordings, and numerous annotations of the
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structure of the movie stimulus. For up-to-date information on available
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data, funding, and our many collaborators, please see the project
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homepage.</p>
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<ul class='social-links'>
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<li><a class='icon-home' aria-label='Website' href="http://studyforrest.org"></a></li>
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<li><a class='icon-twitter' aria-label='Twitter' href="https://twitter.com/studyforrest"></a></li>
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<li><a class='icon-github' aria-label='GitHub' href="https://github.com/psychoinformatics-de?q=studyforrest"></a></li>
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</ul>
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</section>
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<section id="datalad" class="alternate">
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<div class='sponsor-logos'>
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<a href='http://www.gesundheitsforschung-bmbf.de/de/2550.php'>
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<img src="/img/logo/bmbf.svg" alt="German Federal Ministry of Education and Research (BMBF) Logo" class="squarish" />
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</a>
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</div>
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<h3>DataLad</h3>
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<p>Data are key ingredients of science, but interesting data are often
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scattered across many different locations, with heterogeneous access methods,
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and are packaged in a multitude of structures and formats. This makes it
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hard to discover, obtain, and re-use existing data.</p>
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<p>DataLad is a software engineering project that aims to deliver a data
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management tool that aids data discovery, to simplify and homogenize access
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to data across many providers, and to re-share data with a community. One
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could think of DataLad as "Git for collections of datasets".</p>
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<p>As such, this software is ideally suited for projects like our
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<em>studyforrest</em> effort. It applies the successful model of
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collaborative, decentralized open source software development to the
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domain of managing and sharing (scientific) data.</p>
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<div class="figure">
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<img alt="DataLad data flow overview" src="/img/datalad_figure.png" />
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<p>DataLad facilitates and homogenizes data exchange between peers, and
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tracking of resources from data portals. It is data format agnostic and
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exposes meta data to ease data discovery. Access to sensitive data is
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supported via configurable authentication schemes.</p>
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</div>
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<p>This project is executed in collaboration with
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<a href="http://haxbylab.dartmouth.edu/ppl/yarik.html">Yaroslav Halchenko (Dartmouth College)</a>,
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and is co-funded by the US National Science Foundation (NSF 1429999,
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1912266) and the German Federal Ministry of Education and Research (BMBF;
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01GQ1411, 01GQ1905) as part of a US-German collaboration in computational
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neuroscience (CRCNS). Development was supported by the German federal
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state of Saxony-Anhalt and the European Regional Development Fund (Project:
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Center for Behavioral Brain Sciences, Imaging Platform), the European
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Union’s Horizon 2020 research and innovation programme under grant
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agreements <a href="https://cordis.europa.eu/project/id/945539">Human Brain
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Project (SGA3, H2020-EU.3.1.5.3, grant no. 945539)</a>, and <a
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href="https://cordis.europa.eu/project/id/826421">Virtual Brain Cloud
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(H2020-EU.3.1.5.3, grant no. 826421)</a>.</p>
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<ul class='social-links'>
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<li><a class='icon-home' aria-label='Website' href="http://datalad.org"></a></li>
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<li><a class='icon-twitter' aria-label='Twitter' href="https://twitter.com/datalad"></a></li>
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<li><a class='icon-github' aria-label='GitHub' href="https://github.com/datalad"></a></li>
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</ul>
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</section>
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<section id="sfb1451-inf" class="alternate">
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<div class='sponsor-logos'>
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<img src="/img/logo/dfg.svg" alt="Deutsche Forschungsgemeinschaft Logo" />
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</div>
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<h3>Information management for research on key mechanism of motor control in health and disease (SFB1451)</h3>
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<p>In this project we provide expertise for access, description, and
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modeling of data collected in the individual projects of the collaborative
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research center, as well as the two core data acquisition projects.
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This includes assessing general workflows, resource
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requirements, and data analysis processes to capture between-project
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differences that may impact data comparability and re-usability across
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projects. We provide tools, services and training to help projects
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align their research output to facilitate data analysis for extracting
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common activity patterns and mechanisms underlying motor behaviours across
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species, and promote data-driven computational modeling.</p>
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<p>This project is performed in collaboration with
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<a href="https://zoologie.uni-koeln.de/arbeitsgruppen/ag-daun/inhalt/mitarbeiterinnen/prof-dr-silvia-daun">
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Sylvia Daun (FZJ/U Cologne)</a>, and
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<a href="https://neuroscience.uni-koeln.de/neuroforum/ag-nawrot">Martin Nawrot
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(U Cologne)</a>. It is funded by the German Research Council
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(DFG) as a part of the Collaborative Research Center <a
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href="http://sfb1451.de">SFB 1451</a> in Cologne.</p>
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<ul class='social-links'>
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<li><a class='icon-home' aria-label='Website' href="http://sfb1451.de"></a></li>
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</ul>
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</section>
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<h2>Completed Projects</h2>
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<section id="primary-rewards" class="alternate">
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<div class='sponsor-logos'>
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<img src="/img/logo/dfg.svg" alt="Deutsche Forschungsgemeinschaft Logo" />
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</div>
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<h3>Anticipation, Processing, and Control of Primary Rewards</h3>
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<p>An investigation into the perception and neural representation of primary
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rewards (i.e. tastes) of their visual correspondences (secondary rewards)
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and of their (mis)matched combination in the human brain. The aims of this
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project are: 1) to identify the motivational, hedonic, and category-specific
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representations (sweet, sour etc.) of primary rewards; 2) to identify the
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influence of secondary reinforcers on these representations; and 3) identify
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the effects of over-learned and novel visuo-gustatory correspondences on
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these and their functional interplay by means of univariate fMRI-approaches
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(plus functional connectivity), classification analysis, and functional
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hyperalignment.</p>
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<p>This project is a collaboration with
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<a href="http://www.ipsy.ovgu.de/Abteilungen/Biologische+Psychologie.html">Toemme Noesselt (Magdeburg University)</a>,
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and is funded by the German Research Council (DFG) as a part of the
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Collaborative Research Center <a href="http://www.sfb779.de/en/">SFB 779</a>
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in Magdeburg.</p>
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<ul class='social-links'>
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<li><a class='icon-home' aria-label='Website' href="http://www.sfb779.de/en/a15n.html"></a></li>
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</ul>
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</section>
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<section id="perceptual-relevance" class="alternate">
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<div class='sponsor-logos'>
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<img src="/img/logo/dfg.svg" alt="Deutsche Forschungsgemeinschaft Logo" />
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</div>
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<h3>Tracing the Template: Investigating the Representation of Perceptual Relevance</h3>
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<p>In this effort we seek to identify the nature of attentional preferences
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of cognitive behavior, in terms of function (how it affects our behavior),
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physiology (how it is implemented in the brain), and time (how it is
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affected by learning/selection history). Specifically, what preferences can
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it hold, how do these change as a function of experience, and what are the
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neural codes underlying these representations?</p>
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<p>This project is a collaboration with
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<a href="http://www.ipsy.ovgu.de/allgpsych.html">S. Pollmann (Magdeburg University)</a>,
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M. Eimer (Birkbeck College, University of London), and C.N.L. Olivers
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(Vrije Universiteit Amsterdam). It is co-funded by the German Research
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Foundation (DFG; PO 548/16-1).</p>
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</section>
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<section id="neural-spaces" class="alternate">
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<div class='sponsor-logos'>
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<img src="/img/logo/bmbf.svg" alt="German Federal Ministry of Education and Research (BMBF) Logo" class="squarish" />
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</div>
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<h3>Building Common High-dimensional Models of Neural Representational Spaces</h3>
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<p>It is possible to decode information from brain activation patterns with
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multivariate analysis procedures. Despite this fact, little is known how
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neural codes vary across individuals. The main disadvantage of current
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decoding approaches is that they have to be built for each brain
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individually, because it is difficult to bring two brains into alignment at
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a fine scale. This project developed methods that allow for the detection
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and description of common neural representations. Individual brain activity
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patterns are projected into a common high-dimensional space, to build models
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of representational spaces of cortical areas that are valid for a range of
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stimuli and across individuals. This includes complex cortical networks that
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do not respond consistently on direct stimulation (e.g. social
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cognition).</p>
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<p>A collaboration with the groups of James V. Haxby (Dartmouth College,
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USA) and Peter J. Ramadge (Princeton University, USA), this project was
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funded by the German Federal Ministry of Education and Research (01GQ1112)
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as well as the US National Science Foundation (1129764).</p>
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</section>
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<section id="advanced-analysis" class="alternate">
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<div class='sponsor-logos'>
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<img src="/img/logo/cbbs.svg" alt="Center for Behavioral Brain Sciences Logo" class="squarish" />
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</div>
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<h3>Advanced fMRI-based Analysis of Human Sensory Cortex</h3>
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<p>This project focused on the development and validation of new
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experimental and neuro-computational approaches for the investigation of the
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neuronal processing of sensory input to the human visual cortex. Novel
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approaches to decode cortical processing with functional magnetic resonance
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tomography (fMRI) are developed and applied to the analysis of the visual
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cortex. On the one hand spatial high-resolution fMRI approaches are
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established, validated, and optimized. On the other hand, multivariate
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data-analysis approaches are adapted, optimized and applied to the analysis
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of fMRI data sets. These methodological developments open up a wide range of
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applications, not only to deepen our understanding of the healthy visual
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system, but also to investigate pathophysiology and plasticity of the visual
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system for the optimization of future therapeutic strategies.</p>
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<p>A collaboration with Prof. Michael Hoffmann (Visual Processing Lab,
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Eye-Clinic, Magdeburg), this project was funded by the federal state of
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Saxony-Anhalt as part of the project "Center for Behavioral Brain
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Sciences".</p>
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</section>
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<section id="mvpa-7T" class="alternate">
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<div class='sponsor-logos'>
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<img src="/img/logo/dfg.svg" alt="Deutsche Forschungsgemeinschaft Logo" />
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</div>
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<h3>The Role of the Posterior Parietal Cortex for Trans- and Intra Dimensional Feature Binding — Multivariate Pattern Analyses of High-field(7T) fMRI Data</h3>
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<p>A collaboration with Prof. Stefan Pollmann (Experimental Psychology,
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Institute of Psychology II, Magdeburg), this project was funded by the
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German Research Foundation (DFG; PO 548/10-1).</p>
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</section>
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</body>
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</html>
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