Understanding the semantic structure of human fMRI brain recordings with formal concept analysis

We investigate whether semantic information related to object categories can be obtained from human fMRI BOLD responses with Formal Concept Analysis (FCA). While the BOLD response provides only an indirect measure of neural activity on a relatively coarse spatio-temporal scale, it has the advantage that it can be recorded from humans, who can be questioned about their perceptions during the experiment, thereby obviating the need of interpreting animal behavioral responses. Furthermore, the BOLD signal can be recorded from the whole brain simultaneously. In our experiment, a single human subject was scanned while viewing 72 gray-scale pictures of animate and inanimate objects in a target detection task. These pictures comprise the formal objects for FCA. We computed formal attributes by learning a hierarchical Bayesian classifier, which maps BOLD responses onto binary features, and these features onto object labels. The connectivity matrix between the binary features and the object labels can then serve as the formal context. In line with previous reports, FCA revealed a clear dissociation between animate and inanimate objects with the inanimate category also including plants. Furthermore, we found that the inanimate category was subdivided between plants and non-plants when we increased the number of attributes extracted from the BOLD response. FCA also allows for the display of organizational differences between high-level and low-level visual processing areas. We show that subjective familiarity and similarity ratings are strongly correlated with the attribute structure computed from the BOLD signal

Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe´s terrestrial ecosystems: a review

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributedobservation programmes designed to monitor climatechange, better understand its impacts on global ecosystems,and evaluate possible mitigation and adaptation strategies. Thepan-European Integrated Carbon Observation System combinescarbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observationswithin the atmosphere, terrestrial ecosystems and oceans.High-precision measurements are obtained using standardisedmethodologies, are centrally processed and openly available ina traceable and verifiable fashion in combination with detailedmetadata. The Integrated Carbon Observation System ecosystemstation network aims to sample climate and land-cover variabilityacross Europe. In addition to GHG flux measurements,a large set of complementary data (including management practices,vegetation and soil characteristics) is collected to supportthe interpretation, spatial upscaling and modelling of observedecosystem carbon and GHG dynamics. The applied samplingdesign was developed and formulated in protocols by the scientificcommunity, representing a trade-off between an ideal datasetand practical feasibility. The use of open-access, high-quality andmulti-level data products by different user communities is crucialfor the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.<br