One of the most promising avenues for compiling connectivity data originates from the notion that individual brain regions maintain individual connectivity profiles; the functional repertoire of a cortical area (“the functional fingerprint”) is closely related to its anatomical connections (“the connectional fingerprint”) and, hence, a segregated cortical area may be characterized by a highly coherent connectivity pattern. Diffusion tractography can be used to identify borders between such cortical areas. Each cortical area is defined based upon a unique probabilistic tractogram and such a tractogram is representative of a group of tractograms, thereby forming the cortical area. The underlying methodology is called connectivity-based cortex parcellation and requires clustering or grouping of similar diffusion tractograms. Despite the relative success of this technique in producing anatomically sensible results, existing clustering techniques in the context of connectivity-based parcellation typically depend on several non-trivial assumptions. In this paper, we embody an unsupervised hierarchical information-based framework to clustering probabilistic tractograms that avoids many drawbacks offered by previous methods. Cortex parcellation of the inferior frontal gyrus together with the precentral gyrus demonstrates a proof of concept of the proposed method: The automatic parcellation reveals cortical subunits consistent with cytoarchitectonic maps and previous studies including connectivity-based parcellation. Further insight into the hierarchically modular architecture of cortical subunits is given by revealing coarser cortical structures that differentiate between primary as well as premotoric areas and those associated with pre-frontal areas.
Toe‐tapping is a widespread anuran behaviour commonly associated with feeding where the anurans move the middle toes of their hind legs up and down. Previous studies have interpreted it as a pedal lure, a prey localization method and a stimulus used to transfix prey. A database of online videos was constructed in order to study this behaviour across species, with a particular focus on arrow poison frogs (Dendrobatidae); tapping occurrence, prey characteristics and environmental factors were recorded. The data collected include 19 species that have, as of yet, not been recorded to tap, 16 of which exhibit feeding‐related tapping, while in the three other species, tapping seemed to be related to courtship. Across dendrobatid species, a significant correlation was found between prey activity and the occurrence of tapping, which supports a prey localization hypothesis. The database proved to be a valid method of research as it provided a sample size large enough for detailed data analysis across the Dendrobatidae. The utility of the data was partially limited by the available number of observations per species and the inconsistency in video quality, however.
The processing capabilities of current smartphones have increased significantly. We propose a distributed and collaborative context prediction approach that exclusively uses current smartphones to automatically collect, process and predict contexts of users. To predict a user's next context, not only her context history is utilised but also context histories of other users are used. The communication between the smartphones of the users is realised using peer-2-peer. Therefore, no centralised server unit is needed to process the context information of the users externally. We provide a proof-of-concept implementation and present experimental results that demonstrate the practicality of the proposed architecture.
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