peerherholz/alpaca repository overview

Glasser at al. summarized it quite well in their 2016 "A Multi-modal Parcellation of Human Cerebral Cortex" paper (https://doi.org/10.1038/nature18933⁠) when they were stating "In contrast to early visual and somatomotor cortex, parcellation of the early auditory cortex has proven much more challenging..." (Suppl. 3, page 35, line 7-8). The robust and reliable localization and parcellation of the human auditory cortex, along with it's functional principles has been the subject of a long-standing debatte with the vast amount of possible analyses that to can be applied to the variety of possible measurements adding yet another layer of complexity. Well, worry no more and check out ALPACA (https://github.com/PeerHerholz/ALPACA⁠) (OSF page: https://osf.io/w8h36/⁠), an open-source python toolbox for the "Automated Localization and Parcellation of Auditory Cortex Areas" (full disclosure: I had the abbreviation first and then tried to come up with a fitting name, luckily that worked out pretty well) which will include experiment and analyses scripts for different paradigms (natural sounds & classic tone bursts) and approaches (structural parcellation, mapping of auditory ROIs from atlases, fMRI, EEG, searchlights, encoding, etc.). The respective parts can be combined as preferred and run as functions or fully automated via this docker image and/or as a BIDS app (in the near future), hopefully helping folks with creating ROIs for their study and/or further advancing the investigation of the human auditory cortex.