Relatore: Prof. Hugues Duffau, Centre Hospitalier Universitaire de Montpellier, Francia
Quando: 18 febbraio 2025 alle ore 17:30
Dove: Aula Magna della Clinica Neurologica oppure online su piattaforma Zoom (https://unipd.zoom.us/j/88122453021)
Relatore: Dott.ssaMonica Ferlisi, AOUI Verona
Quando: 11 febbraio 2025 alle ore 17:30
Dove: Aula Magna della Clinica Neurologica oppure online su piattaforma Zoom (https://unipd.zoom.us/j/88575019107)
Relatore: Prof.ssa Miryam Carecchio, Università di Padova
Quando: 4 febbraio 2025 alle ore 17:30
Dove: Aula Magna della Clinica Neurologica oppure online su piattaforma Zoom (https://unipd.zoom.us/j/88575019107)
by Prof. Marco Mainardi, University of Padua
When: January 30, 2025, at 3:00 pm
Where: Sala Seminari VIMM (Fondazione per la Ricerca Biomedica Avanzata Onlus, Via Orus 2, Padova)
Abstract: Information storage in the brain, as well as adaptation of neural circuits to external stimuli, rely on restless rearrangement of synaptic connections. Moreover, synapses adjust their strength by varying their molecular composition. Despite the obvious importance of these phenomena, the use of specific tools to study them has been sporadic. Appropriate genetically encoded reporters and probes can help to fill this gap in terms of both imaging and determination of the molecular composition of synapses.
During my talk, I will discuss my most recent effort in this regard, which are based on the in vivo use of recombinant proteins for synapse visualization and for the isolation of the synaptome in specific activation states.
By using behavioral paradigms of hippocampus-dependent learning, my results contribute to elucidate whether specific hotspots for synaptic plasticity exist and to determine the changes in the molecular composition of synapses that support learning and memory.
Relatore: Dott. Andrea Cortese, University College of London (UCL)
Quando: 28 gennaio 2025 alle ore 17:30
Dove: Aula Magna della Clinica Neurologica oppure online su piattaforma Zoom (https://unipd.zoom.us/j/88575019107) 2025-01-28 – Andrea Cortese
Relatore: Prof. Alessandro Padovani, Università degli Studi di Brescia
Quando: 21 gennaio 2025 alle ore 17:30
Dove: Aula Magna della Clinica Neurologica
Speaker: Prof. Luca Mazzucato (Institute of Neuroscience, University of Oregon, USA)
When: 11 December 2024, h. 5:30 pm
Where: 1AD100, Torre Archimede
Abstract: Recent years have brought tremendous progress in the fields of artificial intelligence and neuroscience, however, a comprehensive framework to explain the computational principles of complex cognitive function and flexible behavior is still lacking. Addressing the complexity within large-scale, multi-area neuronal recordings with simultaneous monitoring of behavioral variables demands novel and deeper connections between the different axes of theoretical neuroscience. In this talk, I will review current approaches and highlight challenges in the upcoming NeuroAI field with particular focus on the following questions: i) What kind of dynamical systems can explain the complex spatiotemporal features of naturalistic animal behavior? ii) What new physical ingredients should recurrent neural networks incorporate to explain the richness observed in large-scale neural activity during behavior? iii) What is the geometry of neural representations in animal brains and how is it related to the geometry of deep learning? Finally, I will show some recent work in my lab showing how the optimal cognitive function known as the Yerkes-Dodson law of psychology relies on a phase transition occurring in sensory cortical circuits.
by Prof. Francesco Vespignani, University of Padova
When: November 28, 2024, at 3:00 pm
Where: Sala Seminari VIMM (Fondazione per la Ricerca Biomedica Avanzata Onlus, Via Orus 2, Padova)
Abstract: Cognitive science of language has been dominated for decades by innatism based on generative grammar theory. More recent years have seen a renaissance of models based on (statistical) learning only, leading to positions which I dub neo-behavioralist. These positions are recently even more popular, partially boosted by recent developments of AI large language models. Within this debate, prediction and sensitivity to rhythmicity and regularities of language play a significant role in models of language processing, tightly linked to theories of system neurosciences. I will present some of my current research on prediction, repetition, and entrainment in language processing at the sentence level. I will also try to persuade the audience that it is time to abandon strict ideological position on nature/nurture dualism.
Title of the Project
“Aggregazione e armonizzazione di dati retrospettivi e prospettici di neuroimmagini, clinici e comportamentali relativi a ictus, glioma e malattia di Parkinson” (in English: “Aggregate and harmonise retrospective and prospective neuroimaging, clinical and behavioural stroke, glioma and Parkinson’s data”), Research Supervisor Prof. Maurizio Corbetta
Purpose of the Research Grant
The purpose of this Research Grant, which is funded by the European Union in the framework of the Horizon Europe project “EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health”, Principal Investigator Prof. Maurizio Corbetta, is to grant research into:
The EBRAINS project (European Brain Research Infrastructures, https://www.ebrains.eu/) is an innovative collaborative research infrastructure created with the aim of advancing and accelerating scientific progress in the field of neuroscience and Brain Health. This innovative platform, derived from the Human Brain Project (HBP), is an ecosystem in which researchers, clinicians, and experts from various disciplines converge to explore and analyse the complexity of the brain at various scales, from the molecular and cellular level to whole organ functioning and the implications on human behaviour and disease. The ambition of EBRAINS is to create a new standard for brain atlases from the micro- to the macro-scale, integrating clinical, demographic and brain connectivity data (connectomes) from healthy and pathological brains; to create digital twin brains through mathematical models enabling simulations of the effects of pathologies or brain stimulation; to serve as a preferred and competitive infrastructure for the use of neuroscience data according to FAIR (Findable, Accessible, Interoperable, Re-usable) principles.
Activity: The research fellow will play a pivotal role in aggregating and harmonizing extensive retrospective and prospective collections of neuroimaging, clinical, and behavioural data related to brain pathologies such as stroke, glioma, epilepsy, and Parkinson’s disease. S/He will systematically collect and integrate data from multiple centers around Europe, ensuring consistency and compatibility across diverse datasets. Responsibilities include initiating and coordinating prospective data collection using standardized protocols, conducting data cleaning and normalization, and developing workflows for the extraction and public release of imaging features from clinical datasets. The research fellow will process clinical neuroimaging data (structural MRI, DWI, fMRI) ensuring data anonymity and compliance with ethical guidelines. S/He will integrate processed imaging features into the EBRAINS platform, contributing to a centralized repository that fosters collaboration and accelerates advancements in neuroscience and clinical research. Eventually, the research fellow will help in the development and validation of predictive frameworks for clinical and behavioural outcomes. Close collaboration with neurologists, neuroscientists, data scientists, and other collaborators within the consortium is essential, as well as active participation in project meetings and contributing to the development of standardized EU consensus protocols for imaging and clinical assessments.
Profile: The ideal candidate has a background in neuroscience, or a related field. S/He has experience in neuroimaging data analysis, particularly with clinical datasets involving structural MRI, fMRI, DWI and is proficient in data integration and harmonization techniques for large-scale, multi-center datasets. Strong programming and scripting skills (Python, MATLAB, Bash) are highly desirable, along with knowledge of advanced analytical techniques such as machine learning, multivariate analysis, and statistical modeling. The candidate should be familiar with processing and analyzing clinical, and behavioral data related to neurological conditions and have experience in developing workflows and pipelines for data processing and feature extraction. Excellent communication skills, both written and verbal, are required, as well as the ability to work collaboratively in a multidisciplinary research environment.
Deadline for submitting applications
3 December 2024 at 1:00 pm CET
by Dr. Filippo Pisano, University of Padova
When: November 14, 2024, at 3:00 pm
Where: Sala Seminari VIMM (Fondazione per la Ricerca Biomedica Avanzata Onlus, Via Orus 2, Padova)
Abstract: Over the past two decades, a versatile technological framework combining optical methods with genetically encoded molecular reporters has opened unprecedented opportunities for monitoring neural activity in the living mouse brain. These advancements have been accompanied by a growing awareness that a comprehensive investigation of brain function must account for the brain’s multifaceted complexity, including biomolecular changes associated with physiological and pathological dynamics. This seminar will explore the opportunities afforded by a broader perspective on light-brain interactions, presenting a methodology for low-invasive, label-free optical spectroscopy in deep brain regions. This approach can complement existing techniques towards a more complete understanding of neural mechanisms, with potential applications in both fundamental and translational research.
by Dr. Micaela Zonta, CNR Neuroscience Institute
When: October 31, 2024, at 3:00 pm
Where: Aula RI (Complesso Vallisneri, Viale Colombo 3, Padova)
Abstract: Alzheimer’s disease (AD) is a chronic, incurable neurodegenerative disorder, characterized by progressive memory loss. Despite the advances in the research on neurodegenerative diseases, the molecular and cellular mechanisms underlying AD pathogenesis and the early events that anticipate the cognitive decline remain poorly understood.
Our research evaluates the involvement of astrocytes in AD pathogenesis, focusing on astrocyte Ca2+ signaling and its dysregulation during AD progression. Indeed, the widely recognized evidence that brain function requires dynamic interactions between neurons and astrocytes implies that both cell types can contribute to brain dysfunction.
We employ two-photon microscopy to perform Ca2+ imaging experiments in brain slices and in vivo preparations of somatosensory cortex (SSCx) astrocytes expressing GCaMP6f, and electrophysiological monitoring to assess the efficiency of long-term memory processes. We describe significant alterations in astrocyte activity in the familial AD model PS2APP, as well as in astrocyte-dependent long-term plasticity and reveal the molecular mechanisms underlying Ca2+ dysregulation. Most importantly, we describe a genetic strategy to rescue astrocyte signals and synaptic plasticity.
Our data identify the dysregulation of astrocyte Ca2+ activity as a functional hallmark of early AD stages, revealing a new target to recover AD symptoms.
When: October 24 (Thursday), 2024, at 8:45 pm and October 27 (Sunday), 2024, at 5:00 pm
Where: Sala dei Giganti (Thursday) and Chiesa di San Francesco, Padova (Sunday)
Abstract: Within the project “Soprano: lo spettacolo del cervello”, on Thursday, 24 October, at 8:45 pm at the Sala dei Giganti the Orchestra Asclepio will perform the concert Quando la musica diventa cura, while the second concert La musica del cervello will take place on Sunday, 27 October, at 5 pm, at the Chiesa di San Francesco, Padova.
Both the events are free of charge, but registration is required:
Link: https://ilbolive.unipd.it/it/event/mondo-salute/musica-cervello?amp a
by Dr. Francesco Papaleo, Istituto Italiano di Tecnologia, Genoa, Italy
When: October 17, 2024, at 3:00 pm
Where: Sala Seminari VIMM (Fondazione per la Ricerca Biomedica Avanzata Onlus, Via Orus 2, Padova)
Abstract: The way we perceive, process, and react to others’ emotional states (Emotion Recognition) is at the core of all animal interactions, playing a central role not only in our daily lives and well-being, but also in shaping societies. Determining the mechanisms underpinning emotion recognition will significantly advance our understanding of how individuals engage with others and the role of the social brain in health and disease. We recently developed and validated a series of innovative paradigms for mice that allow disentangling previously unexplored cell- and circuit-specific mechanisms of emotion recognition. Deploy these innovative translational socio-cognitive assessments in mice complemented by state-of-the-art genetics, single-cell imaging, and optogenetics tools we are starting to uncover evolutionary conserved substrates of emotion recognition. A special focus of our investigations is on the prefrontal cortex (PFC)-centered circuits.
When: September 28-29, 2024, from 10:00 am to 7:00 pm (Saturday) and from 10:00 am to 2:00 pm (Sunday)
Where: Palazzo del Bo, Via VIII Febbraio 2, Padova PD
Abstract: The University of Padua presents the 2024 edition of the Science4All Festival, which aims at communicating science in a simple but engaging way. The public will meet researchers from the University of Padua and participate in scientific experiments through workshops, games and other activities. All activities are free.
The Padova Neuroscience Center and our PhD Program in Neuroscience will be present at Palazzo Bo (booth No 21) and they will present “Un viaggio interattivo nel mondo delle neuroscienze“, a series of activities showing how research methods and new discoveries have improved our knowledge of the brain.
by Dr. Peter Zeidman, University College London, UK
When: September 27, 2024, at 3:00 pm
Where: Sala Seminari VIMM (Fondazione per la Ricerca Biomedica Avanzata Onlus, Via Orus 2, Padova)
Abstract: In this talk, I will introduce methods for identifying the neural and vascular physiology that gives rise to non-invasive human neuroimaging data (e.g. MRI, fMRI, fNIRS, M/EEG). These methods enable us to go beyond simply describing our data, and test hypotheses about underlying neural and vascular mechanisms that cause the data. The key ingredients are Bayesian statistical methods, which enable us to quantify the evidence for competing explanations for how our data were generated. In particular, using worked examples from clinical and cognitive neuroscience, I will highlight 1) a Bayesian approach for statistical parametric mapping of fMRI data and Voxel Based Morphometry (VBM), and 2) state-space models of neural connectivity and vascular dynamics. All the methods I will describe are freely available in the SPM software package, among others.
Title of the Project
“Analisi multimodale della connettività cerebrale e modelli predittivi del comportamento basati su machine learning” (in English: “Multimodal analysis of brain connectivity and predictive modelling of behavior based on machine learning”), Research Supervisor Prof. Marco Zorzi
Purpose of the Research Grant
The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:
The aim of the research fellowship is to develop analytical methods that integrate multimodal neuroimaging data at the connectome level and then derive predictions on behavior and cognition.
Activity: The research fellow will work with and contribute to the acquisition of new multimodal data (MRI, fMRI, EEG) pre-processed from healthy subjects and neurological patients. The research fellow will (i) develop an automated procedure to pre-process and analyze data from different sources in a common reference space; (ii) compare brain connectivity derived by different modalities or methods (e.g. functional vs. effective connectivity) and assess its predictivity on behavior and cognition using also machine learning methods; (iii) evaluate methods and possible benefits of integrating multimodal data.
Profile: The ideal candidate should have: (a) experience in analyzing functional magnetic resonance imaging data; (b) experience in using machine learning on neuroimaging data; (c) advanced data analysis and programming skills in Python/Matlab.
Deadline for submitting applications
1 October 2024 at 1:00 pm CEST
by Dr. Manuela Allegra, National Research Council and University of Padua
When: September 19, 2024, at 3:00 pm
Where: Sala Seminari VIMM (Fondazione per la Ricerca Biomedica Avanzata Onlus, Via Orus 2, Padova)
Abstract: The ability of the brain to reorganize its structure and function in response to intrinsic or extrinsic stimuli is defined neuroplasticity. Plasticity of the nervous system is crucial throughout the lifespan, refining sensory systems during development, mediating learning and memory in adulthood and being the key mechanism for neuro-rehabilitation in case of injury and for the prevention of neurodegenerative disorders later in life. Using in vivo recording techniques (extracellular LFP recordings and calcium imaging), we will explore neuroplasticity in physiological and pathological conditions and we will describe how neuronal circuits of the hippocampus and neocortex can rewire their activity during learning and memory, and in response to brain injury.
Title of the Project
“Modellizzazione multimodale dell’attività cerebrale con reti neurali ricorrenti” (in English: Multimodal modeling of brain activity with recurrent neural networks”), Research Supervisor Prof. Samir Simon Suweis
Purpose of the Research Grant
The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:
The general aim of the research fellowship is using recurrent neural networks to jointly model brain activity observed with several imaging modalities.
Activity: The research fellow will use machine learning techniques, based on recurrent neural networks, to model brain activity observed with different imaging modalities. The research fellow will (i) use numerical simulations to develop recurrent networks that can be trained with data at different spatio-temporal resolutions; (ii) use recurrent networks to model brain activity observed with different imaging modalities.
Profile: The ideal candidate should have: (a) experience in machine learning and possibly its use to model dynamic phenomena; (b) advanced data analysis and programming skills in Python/Matlab.
Deadline for submitting applications
13 September 2024 at 1:00 pm CEST
Title of the Project
“Analisi e modellizzazione multimodale dell’attività cerebrale” (in English: “Multimodal analysis and modeling of brain activity”), Research Supervisor Prof. Samir Simon Suweis
Purpose of the Research Grant
The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:
The global aim of the research fellowship is developing data analysis and modeling strategies to integrate multimodal neuroimaging data within a common framework.
Activity: The research fellow will work with pre-processed multimodal data (MRI,fMRI,(i)EEG) from healthy subjects and neurological patients, and will contribute to the acquisition of new multimodal data. The research fellow will (i) develop an automatic procedure to pre-process and analyse data from different sources in a common reference space; (ii) develop a procedure to estimate and compare functional connectivity (FC) obtained with different functional data; (iii) train whole-brain models, in particular to consistently reproduce essential features of multimodal data (e.g. FC).
Profile: The ideal candidate should have: (a) experience in analysing brain activity data; (b) experience in modelling brain activity; (c) advanced data analysis and programming skills in Python/Matlab.
Deadline for submitting applications
13 September 2024 at 1:00 pm CEST
y Prof. Russell Poldrack, Stanford University, USA
When: September 6, 2024, at 3:00 pm
Where: Sala Seminari VIMM (Fondazione per la Ricerca Biomedica Avanzata Onlus, Via Orus 2, Padova)
Abstract: It is now widely accepted that openness and transparency are keys to improving the reproducibility of scientific research, but many challenges remain to adoption of these practices. I will discuss the growth of an ecosystem for open science within the field of cognitive neuroscience, focusing on platforms for open data sharing and open source tools for reproducible data analysis. I will also discuss the role of the Brain Imaging Data Structure (BIDS), a community standard for data organization, in enabling this open science ecosystem, and will outline the scientific impacts of these resources.
Title of the Project
“Modellizzazione multimodale dell’attività cerebrale e studio della risposta a stimolazioni” (in English: “Multimodal modeling of brain activity and study of the response to stimulation”), Research Supervisor Dr. Michele Allegra
Purpose of the Research Grant
The purpose of this Research Grant, which is funded by the European Union – NextGenerationEU – through MUR PNRR fundings in the framework of the project MNESYS “A multiscale integrated approach to the study of the nervous system in health and disease” – PE00000006, Missione 4 “Istruzione e ricerca”, Componente 2 “Dalla ricerca all’impresa”, Investimento 1.3 “Creazione di Partenariati Estesi alle università, centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base”, M4C2 Spoke 2, CUP: B83C22004960002, is to grant research into:
The global aim of the research fellowship is pairing whole-brain models of neural activity, trained on multimodal data, with control and perturbation theory techniques, to determine the effect of electromagnetic stimuli on brain activity, and identify the optimal stimulation loci to obtain desired effects.
Activity: The research fellow will investigate the possibility of using whole-brain models, trained on multimodal data acquired at rest, to predict the effect of electromagnetic stimulations on neuronal activity: (i) starting from the model and exploiting numerical simulations and/or perturbation theory techniques, the research fellow will develop quantitative predictions about the local and remote effect of stimulations; (ii) the predictions will be compared with the results actually measured in subjects subjected to stimulation; (iii) using control theory techniques, the research fellow will determine the optimal stimulation points to excite/inhibit the activity of specific cortical/subcortical areas and networks.
Profile: The ideal candidate should have: (a) experience in modeling brain activity; (b) experience in using models to predict the effect of perturbations; (c) advanced programming skills in Python/Matlab.
Deadline for submitting applications
13 September 2024 at 1:00 pm CEST
Title of the Project
“Generazione di Atlanti Normativi da Dati Multicentrici e Multimodali Acquisiti in Soggetti Sani” (in English: “Generation of Normative Atlases from Multicentric and Multimodal Data Acquired in Healthy Subjects”), Research Supervisor Prof. Alessandra Bertoldo
Purpose of the Research Grant
The purpose of this Research Grant, which is funded by the European Union in the framework of the Horizon Europe project “EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health”, Principal Investigator Prof. Maurizio Corbetta, is to grant research into:
The project involves the generation of foundational normative atlas by acquiring advanced imaging data from a large, diverse multicentric healthy cohort. The dataset will include structural MRI, resting state fMRI, multi-shell DWI, high-density EEG, and dynamic 18F-FDG PET, providing comprehensive insights into brain anatomy, functional connectivity, white matter fiber orientations, neural electrical activity, and glucose metabolism. The acquired data will be employed to extract relevant imaging features, covering structural, functional, connectivity, activity, and metabolic aspects of the brain. Three main extraction approaches will be used: voxel-based, region-based, and connectivity-based features. Rigorous validation and quality assurance procedures will ensure the accuracy and reliability of the features. Once validated, the curated imaging features will be made available on an open-access platform to promote collaboration and advance understanding of brain function and neurological disorders.
Activity: The research fellow will share responsibilities with other researchers hired in Padua for the same EU project, including the acquisition, anonymization, pre-processing, processing, and integration of neuroimaging and simultaneously acquired HD-EEG signals on the Biograph mMR Siemens hybrid system. They will also take care of cognitive tests and clinical characteristics as part of their shared activities. The research fellow will collaborate on the voxel-level quantification of parameters from dynamic PET images obtained with [18F]FDG and on the parameters of diffusion models at both the single-subject and group levels. Additionally, they will actively collaborate closely with external collaborators, including neurologists, neuroscientists, and physicists.
Profile: The ideal candidate should have a basic experience in neuroimaging analysis and, preferably, training in bioengineering and/or applied mathematics/physics and related fields. They must have knowledge of basic and advanced analysis techniques used in neuroscience (e.g., multivariate approaches, machine learning, graph theory, etc.). Analytical/mathematical skills are required. Programming and scripting skills (Python, Matlab, Bash) are not mandatory but are a clear advantage. Furthermore, the candidate must be highly motivated and creative, with the ability to work in a dynamic and multidisciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists.
Deadline for submitting applications
2 August 2024 at 1:00 pm CEST
Guidelines for Submitting Applications
Decree of Acts Approval and Ranking
Title of the Project
“Acquisizione e analisi dei segnali EEG ad alta densità per quantificare la connettività funzionale intrinseca del cervello e la sua integrazione in uno studio multimodale multicentrico” (in English: “Acquisition and analysis of high-density EEG signals to quantify intrinsic brain functional connectivity and its integration in a multicenter multimodal study”), Research Supervisor Prof. Alessandra Bertoldo
Purpose of the Research Grant
The purpose of this Research Grant, which is funded by the European Union in the framework of the Horizon Europe project “EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health”, Principal Investigator Prof. Maurizio Corbetta, is to grant research into:
The project involves the generation of foundational normative atlas by acquiring advanced imaging data from a large, diverse multicentric healthy cohort. The dataset will include structural MRI, resting state fMRI, multi-shell DWI, high-density EEG, and dynamic 18F-FDG PET, providing comprehensive insights into brain anatomy, functional connectivity, white matter fiber orientations, neural electrical activity, and glucose metabolism. The acquired data will be employed to extract relevant imaging features, covering structural, functional, connectivity, activity, and metabolic aspects of the brain. Three main extraction approaches will be used: voxel-based, region-based, and connectivity-based features. Rigorous validation and quality assurance procedures will ensure the accuracy and reliability of the features. Once validated, the curated imaging features will be made available on an open-access platform to promote collaboration and advance understanding of brain function and neurological disorders.
Activity: The research fellow will share responsibilities with other researchers hired in Padua for the same EU project, including the acquisition, anonymization, pre-processing, processing, and integration of neuroimaging and simultaneously acquired HD-EEG signals on the Biograph mMR Siemens hybrid system. They will also take care of cognitive tests and clinical characteristics as part of their shared activities. Specifically, the research fellow will analyze EEG signals both at the scalp level and after reconstruction using source analysis. The analysis methods will be both in the time domain and in the frequency domain. Brain functional connectivity (FC) will be investigated in terms of coupling (non-directed FC) and causality (directed FC). Both approaches will be used, considering (but not limited to) spectral coherence, phase locking value, synergy, transfer entropy, and Granger causality. The research fellow will work actively in close interaction with external collaborators, including neurologists, neuroscientists, and physicists.
Profile: The ideal candidate should have a basic experience in EEG signal analysis and neuroimaging, and preferably a background in bioengineering and/or applied mathematics/physics and related fields. They must have experience in advanced analytical techniques (e.g., multivariate approaches, machine learning, graph theory, etc.). Analytical/mathematical skills are required. Programming and scripting skills (Python, Matlab, Bash) are not mandatory but represent a clear advantage. Additionally, the candidate should be highly motivated and creative, with the ability to work in a dynamic and multidisciplinary research environment and willing to interact with both experimental and theoretical neuroscientists.
Deadline for submitting applications
2 August 2024 at 1:00 pm CEST
Guidelines for Submitting Applications
Decree of Acts Approval and Ranking
