Giuseppe de Alteriis (@GAlteriis) header
Giuseppe de Alteriis (@GAlteriis) profile picture

Computational Neuroscience PhD student at King's College London. From Naples, Italy.

London, England
Joined December 2022
Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)Photo by Giuseppe de Alteriis (@GAlteriis)
Here is DySCo, a general framework for dynamic Functional Connectivity! tinyurl.com/mu2v952x We unify multiple dFC approaches, their associated measures, and introduce an ultrafast algorithm to compute them! Thanks @Olitob123 @leechbrain @Joana_Cabral__ @ExpertPol
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Looking for a one stop high-dimensional time-series analysis platform for neuroimaging data? Dysco might be just what you are looking for! Well done to @GAlteriis and @Olitob123 for seeing this one out!
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"Duality" is a deep concept in mathematics, but an intuitive way to think about it is in terms of tables. When we lay out data in a table, we are familiar with the idea that each row represents a different "entity", and each column represents a different "property". (1/10)
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Excited to share our work on between-scanner test-retest reliability of ultra-low-field brain MRI morphometry and correspondence to high-field MRI: biorxiv.org/content/10.1101/… | We scanned 23 healthy adults (20-69 y) on two identical 64 mT @Hyperfine Swoop systems and 3 T MRI (1/n)
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are you at #OHBM2024 ? Are you interested in Dynamic Functional Connectivity or tenuous links to 70s popular culture...? If yes: Please come and chat to either me or @Olitob123 and check out our poster (# 1545) tomorrow and on Thursday!
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MATLAB repo is out now! Python coming soon...
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4/N The RMEVD algorithm can be orders of magnitude faster than naive approaches. Practically speaking, this means that DySCo allows to work with huge, non-parcellated dFC matrices, potentially real-time!
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N/N For example, we applied DySCo to compute dynamic correlation matrices with 1 billion elements on unparcellated fMRI ! See our results on the preprint or discuss with me and Oli at OHBM in Seoul!
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1/N dFC is a tool to understand how spatiotemporal interaction patterns change with time. In this toy example (3 signals), the brain switches from the blue to the green pattern. A single correlation/covariance matrix cannot capture this switch.
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2/N There are multiple ways to compute time-varying interaction patterns (i.e. matrices): from simple correlation/covariance to approaches based on phase alignment. DySCo puts all of them together, with a unique set of tools and algorithms, given their common structure.
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Just finished one more figure to illustrate the Leading Eigenvector Dynamics Algorithm (LEiDA), for our upcomming toolbox paper. There's a lot of persistence behind each plot. – at Lisbon, Portugal
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New paper in Imaging Neuroscience by Giuseppe de Alteriis, Federico E. Turkheimer, et al: EiDA: A lossless approach for dynamic functional connectivity; application to fMRI data of a model of ageing doi.org/10.1162/imag_a_00113
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Please check out our study on VIP interneurons & attention, now published in @NeuroCellPress. Particularly proud that this first paper from the lab is essentially a negative result! cell.com/neuron/fulltext/S08… Led by the amazing @DMyersJoseph with @k47h4 @marianf_otero & @ClopathLab
Attention can enhance responses in sensory areas, and this is a pretty fundamental cognitive process, but how does this happen? Check out the latest preprint from our lab which tackles this question, led by the amazing Dylan Myers-Joseph! @DMyersJoseph biorxiv.org/content/10.1101/…
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New paper out investigating the effect of anesthesia-induced loss of consciousness on the integration/segregation balance (tinyurl.com/5bsy28vd) lead by the fantastic @LDLord13, with @teo121270, @henrique_frnnds and Federico Turkheimer, supported by @imera_amu
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