By Katrin Amunts, Lucio Grandinetti, Thomas Lippert, Nicolai Petkov
This ebook constitutes revised chosen papers from the second one foreign Workshop on Brain-Inspired Computing, BrainComp 2015, held in Cetraro, Italy, in July 2015.
The 14 papers awarded during this quantity have been rigorously reviewed and chosen for inclusion during this e-book. They care for mind constitution and serve as; computational types and brain-inspired computing equipment with useful purposes; excessive functionality computing; and visualization for mind simulations.
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Additional resources for Brain-Inspired Computing: Second International Workshop, BrainComp 2015, Cetraro, Italy, July 6-10, 2015, Revised Selected Papers
We computed at a (so far maximum) resolution of 40 m a section-to-section nonlinear alignment. This step required up to 8 h of computation time per image, and was the computationally most expensive part. In order to improve the quality of the 3D-reconstruction, we computed for every image i the nonlinear alignment to the median image of its i ± 3 neighbors thus reducing minor local misalignments. Processing level (iv): Intensity corrections and BigTIFF image generation. Finally, a further section-to-section optical imbalance correction was computed.
Therefore, the brain sections were scanned in tiles with overlapping ﬁelds of view using a motorized scanning stage (M¨ arzh¨ auser, Germany). Image analysis was based on the implemented workﬂow [ABA14]. The segmentation procedure Automation and Parallelization of a Seeded Region Growing Segmentation 31 described here was optimized for the 3D-PLI modality referred to as transmittance map. A transmittance value reﬂects the average of the sinusoidal light intensity curve and is a direct measure of the local light extinction.
Full spatial resolution of 20 µm will be achieved at JURECA where the work is continued. 5 Results The second BigBrain has been 3D-resonstructed (Fig. 6). The quality of the reconstruction is high, as veriﬁed in the two virtual sectioning planes below. Minor structural imbalances are primarily due to the computation of the sectionto-section alignment at a reduced resolution of 40 µm. They are currently corrected by re-computing the alignments at full resolution on JURECA. Fig. 6. Images of virtual section planes of the second BigBrain data.
Brain-Inspired Computing: Second International Workshop, BrainComp 2015, Cetraro, Italy, July 6-10, 2015, Revised Selected Papers by Katrin Amunts, Lucio Grandinetti, Thomas Lippert, Nicolai Petkov