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Giulio Gabrieli

@giuliog.bsky.social
26 followers 28 following 12 posts

Researcher by Day, Nerd by Night. PostDoc at Digital Futures Research Hub, Technological University Dublin (TU Dublin) Turns coffee into Open Science & Open Source.

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Giulio Gabrieli @giuliog.bsky.social · 08/04/2026
On my way to beautiful Galway for #Dementia Research Network #Ireland (DRNI) Early Career Researcher Day. Presenting a poster on how to use biomarkers for the identification of cognitive impairment using a gamification approach. Come meet me :) #artificialIntelligence #Neuroscience #Dementia
This research poster from Technological University Dublin (TU Dublin) describes a mobile AI application designed for early cognitive monitoring.

## Title and Overview
The main heading at the top states: "Mobile AI uses the natural way you speak about your photos to identify the hidden acoustic markers of cognitive change."

## Content Sections
* **Background:** Explains the shift from episodic testing to continuous, unobtrusive monitoring in domestic settings to identify neurodegenerative trajectories.
* **Methods:** Details a pipeline that extracts language-agnostic acoustic and prosodic characteristics from audio recordings to serve as inputs for machine learning classification models.
* **Visuals:**
    * **Figure 1:** An illustration of the user workflow: taking a photo, receiving a prompt at a later time, and recording a verbal description.
    * **Figure 2:** Displays speech features including waveforms, Mel spectrograms, MFCCs, and fundamental frequency.
    * **Figure 3 & 4:** Bar charts showing model performance (Mean Balanced Accuracy) across different classification models like Logistic Regression and Random Forest, including cross-linguistic performance in English, Greek, and Mandarin.

## Footer Information
The bottom of the poster lists the research team, led by Giulio Gabrieli, and provides a QR code for supplemental materials. The TU Dublin logo is prominently displayed in the bottom right corner.
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
📚 Where you can find it The full open-access article is published in PLOS Biology: journals.plos.org/plosbiology/... 🧵10/10
journals.plos.org
Electrical Spinal Imaging: A noninvasive, high-resolution approach that enables electrophysiological mapping of the human spinal cord
The role of the spinal cord in relaying brain-body signals has been hard to study due to challenges in non-invasive neural imaging. This study develops a new approach - Electrical Spinal Imaging (ESI)...
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
🌐 Why it matters: ESI opens the door to precise, real-time monitoring of the spinal cord🔍🧩, with the potential to advance both basic neuroscience 🧠 and clinical neurophysiology 🏥offering diagnostic tools for conditions like spinal dysfunction and spinal cord injury. 🧵9/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
And here’s the real wow moment 🤯⚡: attention actually changes spinal activity, revealing that our cognitive state can influence sensory processing all the way down in the spinal cord, not just in the brain. 🧵8/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
These signals correspond to different steps in the sensory processing chain: -on the side of the stimulation, sP9 reflects a traveling volley of incoming sensory input⚡➡️ - central and symmetrical in the spine, sN13 and sP22 capture local postsynaptic processing 🔄 🧵7/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
We detected 3 electrical responses in the spinal cord: sP9, sN13, and sP22 ⚡ (numbers reflect their timing in milliseconds after the stimulus). Each response represents a different stage of how sensory information is processed as it travels into the spinal cord. 🧵6/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
To activate the sensory system, we delivered gentle, controlled electrical pulses to the wrist 🔌✋. By recording signals from the peripheral nerves, spinal cord, and brain, we built high-resolution maps 🗺️⏱️ of how sensory information travels through the body. 🧵5/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
We then applied a rigorous, data-driven cleaning pipeline 🧼📊 to remove noise from muscles, movement, and other sources. This allowed us to isolate the true spinal responses ⚡ with much higher clarity and spatial detail than previous noninvasive methods. 🧵4/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
We developed a new technique called Electrical Spinal Imaging (ESI). It uses a dense array of surface electrodes placed on the back to record tiny electrical signals from the spinal cord, while also capturing EEG (brain)🧠 and ECG (heart) ❤️‍🩹. 🧵3/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
Historically, neuroscience has lacked a reliable noninvasive way to record electrical activity directly from the human spinal cord: neuroimaging methods (e.g. fMRI) are limited by poor temporal resolution and artifacts. 🧵2/10
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Giulio Gabrieli @giuliog.bsky.social · 18/12/2025
🚨Our latest paper, Electrical Spinal Imaging: A noninvasive, high‑resolution approach that enables electrophysiological mapping of the human spinal cord is out now in PLOS Biology doi.org/10.1371/jour... It's not only fancy figures, let me show you ⬇️ 🧵1/10
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Reposted by Giulio Gabrieli
BehavEcolPapers @behavecolpapers.bsky.social · 13/12/2025
Electrical Spinal Imaging: A noninvasive, high-resolution approach that enables electrophysiological mapping of the human spinal cord @PLOSBiology.org
dlvr.it
Electrical Spinal Imaging: A noninvasive, high-resolution approach that enables electrophysiological mapping of the human spinal cord
by Giulio Gabrieli, Richard Somervail, André Mouraux, Massimo Leandri, Patrick Haggard, Gian Domenico Iannetti The spinal cord is the key bridge between the brain and the body. However, scientific understanding of healthy spinal cord function has historically been limited because noninvasive measures of its neural activity have proven exceptionally challenging. In this work, we describe an enhanced recording and analysis approach, Electrical Spinal Imaging (ESI), to obtain noninvasive, high-resolution images of the spinal cord electrical activity in humans. ESI is analytically simple, easy to implement, and data-driven: it does not involve template-based strategies prone to produce spurious signals. Using this approach, we provide a detailed description and physiological characterization of the spatiotemporal dynamics of the peripheral, spinal, and cortical activity elicited by somatosensory stimulation. We also demonstrate that attention modulates postsynaptic activity at spinal cord level. Our method has enabled five important insights regarding spinal cord activity. (1) We identified three distinct responses in the time domain: sP9, sN13, and sP22. (2) The sP9 is a traveling wave reflecting the afferent volley entering the spinal cord through the dorsal root. (3) In contrast, the sN13 and sP22 reflect segmental postsynaptic activity. (4) While the sP9 response is first seen on the dorsal electrodes ipsilateral to the stimulated side, the sN13 and sP22 were not lateralized with respect to the side of stimulation. (5) Unimodal attention strongly modulates the amplitude of the sP22, but not that of the sP9 and sN13 components. The proposed method offers critical insights into the spatiotemporal dynamics of somatosensory processing within the spinal cord, paving the way for precise noninvasive functional monitoring of the spinal cord in basic and clinical neurophysiology.
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Reposted by Giulio Gabrieli
PLOS Biology @plosbiology.org · 28/11/2025
The role of the #SpinalCord in relaying brain-body signals has been hard to study noninvasively. @giuliog.bsky.social &co develop Electrical Spinal Imaging (ESI), enabling high-resolution, noninvasive recordings, revealing how #attention modulates spinal activity @plosbiology.org 🧪 plos.io/3MswZOf
Recording setup and data analysis. Top left panel: Schematic of the position of the electrodes to record EEG (white), ESI (black), ECG (red), somatosensory activity at Erb’s points (green), and the positions of Common Mode Sense (CMS) (blue) and DRL (orange) electrodes. Note that Erb and ECG electrodes were placed on the chest, while ESI electrodes were placed on the back. Top right and bottom panels: Flowchart describing the analysis procedure. (1 and 2) Raw ESI signals are first re-referenced to the most caudal dorsal electrode (S64). (3) The artifact caused by the electrical stimulation of the median nerve is removed by linear interpolation. (4) The ECG is used to identify ESI time windows contaminated by the QRS complex (orange). This allows subsequent selection of ESI time windows to retain. (5) These time windows are epoched around the somatosensory stimulus. (6) An amplitude-based threshold is used to identify and remove artifactual epochs (red). (7) Resulting artifact-free epochs are averaged across stimuli of each block. Subject-level average waveforms are subsequently averaged across participants. (8) Images of the spatial distribution of spinal cord activity are calculated by spline interpolation across ESI electrodes. The figurine depicts spinal cord activity at the latency of the N13 wave.
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Reposted by Giulio Gabrieli
PLOS Biology @plosbiology.org · 28/11/2025
The role of the #SpinalCord in relaying brain-body signals has been hard to study noninvasively. @giuliog.bsky.social &co develop Electrical Spinal Imaging (ESI), enabling high-resolution, noninvasive recordings, revealing how #attention modulates spinal activity @plosbiology.org 🧪 plos.io/3MswZOf
Recording setup and data analysis. Top left panel: Schematic of the position of the electrodes to record EEG (white), ESI (black), ECG (red), somatosensory activity at Erb’s points (green), and the positions of Common Mode Sense (CMS) (blue) and DRL (orange) electrodes. Note that Erb and ECG electrodes were placed on the chest, while ESI electrodes were placed on the back. Top right and bottom panels: Flowchart describing the analysis procedure. (1 and 2) Raw ESI signals are first re-referenced to the most caudal dorsal electrode (S64). (3) The artifact caused by the electrical stimulation of the median nerve is removed by linear interpolation. (4) The ECG is used to identify ESI time windows contaminated by the QRS complex (orange). This allows subsequent selection of ESI time windows to retain. (5) These time windows are epoched around the somatosensory stimulus. (6) An amplitude-based threshold is used to identify and remove artifactual epochs (red). (7) Resulting artifact-free epochs are averaged across stimuli of each block. Subject-level average waveforms are subsequently averaged across participants. (8) Images of the spatial distribution of spinal cord activity are calculated by spline interpolation across ESI electrodes. The figurine depicts spinal cord activity at the latency of the N13 wave.
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Reposted by Giulio Gabrieli
PLOS Biology @plosbiology.org · 01/12/2025
The role of the #SpinalCord in relaying brain-body signals has been hard to study noninvasively. @giuliog.bsky.social &co develop Electrical Spinal Imaging (ESI), enabling high-resolution, noninvasive recordings, revealing how #attention modulates spinal activity @plosbiology.org 🧪 plos.io/3MswZOf
Recording setup and data analysis. Top left panel: Schematic of the position of the electrodes to record EEG (white), ESI (black), ECG (red), somatosensory activity at Erb’s points (green), and the positions of Common Mode Sense (CMS) (blue) and DRL (orange) electrodes. Note that Erb and ECG electrodes were placed on the chest, while ESI electrodes were placed on the back. Top right and bottom panels: Flowchart describing the analysis procedure. (1 and 2) Raw ESI signals are first re-referenced to the most caudal dorsal electrode (S64). (3) The artifact caused by the electrical stimulation of the median nerve is removed by linear interpolation. (4) The ECG is used to identify ESI time windows contaminated by the QRS complex (orange). This allows subsequent selection of ESI time windows to retain. (5) These time windows are epoched around the somatosensory stimulus. (6) An amplitude-based threshold is used to identify and remove artifactual epochs (red). (7) Resulting artifact-free epochs are averaged across stimuli of each block. Subject-level average waveforms are subsequently averaged across participants. (8) Images of the spatial distribution of spinal cord activity are calculated by spline interpolation across ESI electrodes. The figurine depicts spinal cord activity at the latency of the N13 wave.
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Giulio Gabrieli @giuliog.bsky.social · 27/03/2025
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Reposted by Giulio Gabrieli
Ted Price @tedpricethepainguy.bsky.social · 18/03/2025
BOOM! This looks like quite the advance: www.biorxiv.org/content/10.1...
biorxiv.org
Electrical Spinal Imaging (ESI): Analysing spinal cord activity with non-invasive, high-resolution mapping
The spinal cord is the key bridge between the brain and the body. However, scientific understanding of healthy spinal cord function has historically been limited because noninvasive measures of its ne...
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