Research Line #: 1

Supervisor: Antonino Vallesi

Potential Co-Supervisor/s: Simone Messerotti Benvenuti, Ettore Ambrosini, Arianna Menardi, Giorgia Cona, Mario Bonato, Maurizio Corbetta, Enrico Collantoni, Fabio Sambataro

Other potential Collaborators: TBA

Short abstract: This research lines aims to examine how life experience, training and specialized expertise shape and enhance cognitive processes, and whether these effects can be amplified through targeted laboratory interventions. Adopting an integrative approach, the project will compare individuals with structured, long-term experience to identify cognitive and neural patterns linked to enhanced cognition, with a special focus on executive abilities. Key components of such expertise will then be translated into controlled training programs for the general population, and combined with laboratory techniques (e.g., neurofeedback or cognitive training) to test potential synergistic effects. By bridging real-world experience with experimental cognitive neuroscience, this work seeks to develop scalable, personalized interventions to strengthen executive functioning in both healthy (young and older) adults and clinical populations, using behavioral, electrophysiological, and/or neuroimaging methods.

Research Line #: 2

Supervisor: Antonino Vallesi

Potential Co-Supervisor/s: Arianna Menardi, Annachiara Cagnin, Ettore Ambrosini, Diego Cecchin, Marco Zorzi, Samir Suweis, Maurizio Corbetta, Alessandra Bertoldo, Michele Allegra, Fabio Sambataro, Enrico Collantoni

Other potential Collaborators: TBA

Short abstract: The relationship between brain connectivity and cognitive performance is essential for understanding how brain regions coordinate to support functions like executive functions, attention, decision-making and memory. In healthy individuals, optimal connectivity patterns enable efficient cognitive functioning. However, in pathological conditions, such as neurodegenerative diseases or psychiatric disorders, disrupted connectivity may impair cognitive abilities. Studying these changes provides insights into brain function and dysfunction, helping to better understand diagnosis and prognosis, and to develop targeted interventions aimed at improving cognitive performance, or at least at minimizing loss of function in case of neurodegeneration.

Research Line #: 3

Supervisor: Alessandra Bertoldo

Potential Co-Supervisor/s: Maurizio Corbetta, Samir Suweis, Michele Allegra, Marco Zorzi, Antonino Vallesi, Stefano De Marchi, Mattia Veronese

Other potential Collaborators: TBA

Short abstract: This research project aims to generate an integrated framework to understand the brain as a multi-layer, energy-constrained system in which cognitive processes emerge from the dynamic interplay between structure, function, electrophysiology, and metabolism. Moving beyond pairwise connectivity, this research project combines EEG dynamics, fMRI functional organization, structural connectomics, and FDG-PET metabolic measures within a unified neuroenergetic model. It is hypothesized that cognitive brain state transitions are governed by hierarchical energetic constraints: structural architecture defines baseline energy limits, electrophysiological dynamics modulate demand, and functional connectivity adapts to optimize network efficiency under metabolic cost. By incorporating effective connectivity, causal interactions, metastability, and controllability across scales are captured. This approach aims to reveal how energy shapes cognitive brain organization, drives state switching, and evolves across the lifespan.

Research Line #: 4

Supervisor: Alessandra Bertoldo

Potential Co-Supervisor/s: Alessandro Salvalaggio, Maurizio Corbetta, Diego Cecchin, Renzo Manara, other co-supervisors with expertise relevant to the defined project.

Other potential Collaborators: TBA

Short abstract: Gliomas, particularly glioblastoma (GBM), induce widespread alterations in brain networks extending beyond the visible lesion, limiting current imaging-based clinical decision-making. The research project aims to develop a connectome-based framework integrating structural MRI, diffusion MRI, and resting-state fMRI to quantify, at the individual level, the impact of glioma on brain organization. By combining structural, functional, and effective connectivity, network-level disruptions associated with tumor progression and infiltration will be identified. These multimodal features will be linked to histo-molecular markers (e.g., MGMT, IDH) and survival outcomes to derive novel prognostic biomarkers. The project will further enable prediction of disease impact and support clinical translation through tools for personalized surgical planning, radiotherapy optimization, and neurorehabilitation. An automated platform will facilitate integration into routine clinical workflows, including settings with limited imaging data. This approach aims to advance precision neuro-oncology by bridging brain connectivity and clinical practice.

Research Line #: 5

Supervisor: Cristina Scarpazza

Potential Co-Supervisor/s: Gentili Claudio

Other potential Collaborators: TBA

Short abstract: This research line seeks to test whether adding non‑invasive brain stimulation (NIBS) techniques to standard treatments can improve their effectiveness in reducing violent behavior in a defined group of offenders. The main goal is to examine whether increasing excitability and activity of the prefrontal cortex (PFC) via transcranial direct current stimulation (tDCS) can modulate aggression in male violent offendersThe project also aims to assess whether combining tDCS with standard treatment—especially psychoeducational interventions for IPV offenders—produces stronger and more long‑lasting improvements than standard treatment alone.

Research Line #: 6

Supervisor: Cristina Scarpazza

Potential Co-Supervisor/s: Gentili Claudio

Other potential Collaborators: TBA

Short abstract: This research line aims to investigate how neuroscientific evidence and cognitive biases influence human decision‑making in forensic contexts. The project seeks to identify systematic biases, improve the integration of neuroscience in court, and develop guidelines to support more accurate, transparent, and fair forensic decision‑making.

Research Line #: 7

Supervisor: Manfredo Atzori

Potential Co-Supervisor/s: Gianmaria Silvello, Maurizio Corbetta. Additional co-supervisors related to the considered use cases.

Other potential Collaborators: TBA

Short abstract: Exascale volumes of multimodal data are continuously produced in neurosciences and the biomedical domain, including for instance patient information, clinical data, biological laboratory data, bio-images, bio-signals, instrumental examinations and genetic data.
Fully exploiting them in order to extract knowledge and patterns is still an open challenge, due to the heterogeneity of data and state of the art limitations in machine learning.
This research line aims at developing machine learning methods to extract knowledge from multimodal biomedical data, in order to characterize patients with variable spatial and temporal resolution, leading to multimodal knowledge exploration and, eventually, precision medicine applications.

Research Line #: 8

Supervisor: Manfredo Atzori

Potential Co-Supervisor/s: Maurizio Corbetta, Alessandra Del Felice.

Other potential Collaborators: TBA

Short abstract: The recent advancements of machine learning and, particularly, of deep learning paved the way to unprecedented opportunities in many domains, including neuroscience and rehabilitation.
This research line targets the proposal of innovative ideas leveraging the capabilities of modern deep learning approaches for research applications in neurosciences and assistive robotics targeting real time rehabilitation of stroke patients using EEG and EMG data.

Research Line #: 9

Supervisor: Samir Suweis

Potential Co-Supervisor/s: Michele Allegra, Marco Dal Maschio, Stefano Vassanelli, Aram Megighian.

Other potential Collaborators: TBA

Short abstract: The brain is a dynamical system whose activity continuously evolves through a high-dimensional space of possible trajectories. Understanding whether, and how, these trajectories can be steered in a controlled manner is a fundamental challenge at the interface of neuroscience, physics, and machine learning. Animal models now provide an unprecedented opportunity to address this question, thanks to large-scale recordings and precise electrical or optogenetic perturbations. This project aims to develop a closed-loop control framework to steer pathological brain activity toward healthier target dynamics. We will combine functional connectivity, stochastic control, and recurrent neural networks to infer neural dynamics and design adaptive stimulation strategies based on the current brain state. The goal is to identify interventions that optimally move activity closer to a desired target pattern. The approach will be tested on large-scale neuronal recordings from zebrafish, Drosophila, and neuronal cultures interfaced with electrical or optogenetic control. By integrating cpmputational neuroscience, machine learning, and control theory, the project seeks to establish a principled framework for rational brain stimulation in disease recovery.

Research Line #: 10

Supervisor: Samir Suweis

Potential Co-Supervisor/s: Michele Allegra, Marco Zorzi, Antonino Vallesi, Stefano De Marchi, Alessandra Bertoldo, Maurizio Corbetta

Other potential Collaborators: TBA

Short abstract: Brain activity appears to be organized into dynamical modes that alternate over time, including global modes and states dominated by specific resting state networks such as the default mode network. These modes may be altered in neurological and psychiatric disorders. Experimental evidence shows that brain stimulation, delivered electrically or through transcranial magnetic stimulation, can support recovery of such disorders. Yet, how to identify optimal stimulation targets remains largely unknown. This project aims to understand the generative principles of brain eigenmodes and to develop methods to control them in order to restore healthy dynamics. We will build a generative model of mode emergence, interaction, and switching, and use it to design interventions that steer pathological dynamics toward healthy configurations. The framework will combine latent dynamical systems, network models, and control theory. Applications will focus on fMRI, TMS, EEG, and MEG data, linking brain dynamics across temporal and spatial scales. The project will provide a quantitative basis for understanding large-scale brain organization and for designing control strategies to recover healthy brain states.

Research Line #: 11

Supervisor: Camillo Porcaro

Potential Co-Supervisor/s: Alessandra Bertoldo, Maurizio Corbetta, other co-supervisors with expertise relevant to the defined project

Other potential Collaborators: TBA

Short abstract: The human brain operates at the ‘edge of chaos’, dynamically balancing an aperiodic energetic baseline (1/f noise), transient periodic oscillations, and critical network branching to optimize cognition. Current neuroscientist largely treats these computational features in isolation, failing to capture how neurological pathologies, such as epilepsy or dementia, collapse this delicate interdependency into rigid, inescapable states. This PhD project pioneers a unified ‘Triadic Phase Space’ framework. By synthesizing multiscale electrophysiology with statistical physics, we will mathematically map the geometry of healthy and pathological brain dynamics. By formalising the causal mechanics between baseline excitation/inhibition and network criticality, this research will develop personalized, Physics-Informed Digital Twins. Ultimately, this framework provides the algorithmic blueprint for next-generation, closed-loop Brain-Computer Interfaces capable of moving beyond symptom suppression to actively steer a patient’s neural manifold back to optimal cognitive fluidity.

Research Line #: 12

Supervisor: Camillo Porcaro

Potential Co-Supervisor/s: Alessandro Salvalaggio, Maurizio Corbetta, other co-supervisors with expertise relevant to the defined project

Other potential Collaborators: TBA

Short abstract: Brain tumors exhibit profound structural and microenvironmental chaos, creating a “complexity gap” where standard Euclidean imaging measurements consistently fail to capture true tumor infiltration and biological aggressiveness. This PhD project investigates the “Fractal Paradox” in neuro-oncology by applying advanced non-linear mathematical modeling to multimodal magnetic resonance imaging (MRI). By extracting high-order complexity metrics, specifically fractal dimension, lacunarity, and thermodynamic entropy, the project aims to decode the chaotic architecture of gliomas. The research will systematically evaluate these biophysical markers to perform non-invasive “virtual biopsies” (e.g., predicting IDH1 status), resolve critical diagnostic dilemmas such as distinguishing true tumor progression from treatment-induced pseudoprogression, and accurately predict patient overall survival. Ultimately, this work seeks to translate fractal geometry and non-linear dynamics from theoretical biophysics into robust, standardized clinical biomarkers, fundamentally redefining how tumor heterogeneity is quantified in precision neuro-oncology.

Research Line #: 13

Supervisor: Giorgia Cona

Potential Co-Supervisor/s: Jeff Kiesner, Camillo Porcaro, Giorgio Arcara, other co-supervisors with expertise relevant to the defined project

Other potential Collaborators: TBA

Short abstract: The menstrual cycle is a natural part of life for many women, yet its effects on mental well-being remain poorly understood and often stigmatized. While all women experience hormonal fluctuations, only a minority show meaningful changes in mood, cognition, or behavior. Evidence suggests these differences reflect increased brain sensitivity to typical hormonal changes rather than abnormal hormone levels. This project investigates the psychological, cognitive and neural features of two symptom profiles. One profile is characterized by irritability and anxiety, which emerges after ovulation during the mid-luteal phase. The other profile involves depressed mood and reduced interest or pleasure, which are more common in the days immediately preceding menstruation. The probject will involve cognitive assessment and recordings of brain electrical activity, allowing researchers to observe how brain and cognitive functioning change in relation to the mentrual-related symtoms.

Research Line #: 14

Supervisor: Giorgia Cona

Potential Co-Supervisor/s: Camillo Porcaro, Giorgio Arcara, Enrico Collantoni, Angelo Antonini

Other potential Collaborators: TBA

Short abstract: The aim of this project is exploring brain dynamics associated with time-related processes, such as delay discounting and mental time travel, by using EEG and brain stimulation techniques.Furthermore, the project will explore how such processes change in clinical population, such as in patiens with anorexia or bulimia and patients with Parkinson’s disease.

Research Line #: 15

Supervisor: Filippo Pisano

Potential Co-Supervisor/s: Judit Gervain, Marco Dal Maschio, Manuela Allegra

Other potential Collaborators: TBA

Short abstract: In the past few decades, optical approaches to control and monitor neural activity have revolutionized neuroscience research. Recently, photonic strategies have opened promising directions towards next-generation pre-clinical and clinical tools. This research line aims to explore innovative approaches exploiting light-brain interactions to extract information on the functional and biomolecular state of neural tissues, with high sensitivity and high spatio-temporal resolution, in situ. The activities will entail interdisciplinary approaches bridging the disciplines of optics and photonics (in particular, the development of advanced optical systems), data analysis and neuro-biology.

Research Line #: 16

Supervisor: Emanuela Formaggio

Potential Co-Supervisor/s: Maria Rubega, Michela Agostini

Other potential Collaborators: TBA

Short abstract: There is very limited research into the effectiveness of conventional and bimanual robot-based upper limb (UL) rehabilitation for people with neurological disorders. In recent years, conventional UL rehabilitation has been enhanced by the development of robots, which can provide high-intensity, repetitive, interactive and task-specific exercises. This project aims to explore the underlying neuronal mechanisms of UL recovery using neurophysiological investigations and the innovative robotic equipment available at the Department of Neuroscience and Padova University Hospital. The project involves a multidisciplinary team of physiatrists, physiotherapists, neuropsychologists, and bioengineers specialising in advanced biological signal processing and biomechanics.

Research Line #: 17

Supervisor: Emanuela Formaggio

Potential Co-Supervisor/s: Edoardo Passarotto, Maria Rubega

Other potential Collaborators: TBA

Short abstract: Healthy aging is one of the greatest challenges of our time, and it is important to identify cost-effective activities to counteract cognitive decline. Meta-analyses suggest that listening to music can improve health, well-being, and cognitive function in older adults. However, results are inconsistent and the process by which music affects cognitive function is largely unexplained. This project aims to identify aspects of music that improve cognitive performance in older adults and to develop personalized music listening interventions to counteract cognitive decline based on electroencephalography (EEG) activity. Effectiveness will be evaluated on behavioral and EEG parameters.

Research Line #: 18

Supervisor: Stefano Masiero

Potential Co-Supervisor/s: Gianluca Regazzo

Other potential Collaborators: TBA

Short abstract: This project brings together experts in rehabilitation medicine, neurology, psychology and data analytics to investigate the neurophysiological factors that influence how patients respond to treatment for nociplastic pain conditions, such as fibromyalgia. The central objective is to identify mechanistic and clinical predictors that can inform the personalisation of rehabilitation pathways. This project aims to stratify patients according to their neurophysiological, functional and psychosocial profiles to optimise therapeutic matching and improve clinical outcomes. Key pathophysiological domains include central sensitisation, altered descending pain modulation, autonomic dysregulation and maladaptive sensorimotor integration. These mechanisms will be analysed in relation to differential responses to rehabilitation interventions such as graded exercise therapy, therapeutic exercise, cognitive behavioural strategies, education-based interventions and integrative approaches (e.g. spa-based or environmental rehabilitation models). The PhD student will be involved in acquiring, analysing and interpreting multimodal datasets, including neurophysiological measures, quantitative sensory testing, biomechanical and kinematic assessments, and patient-reported outcomes.

Research Line #: 19

Supervisor: Stefano Masiero

Potential Co-Supervisor/s: Maria Rubega, Emanuela Formaggio, Paola Contessa

Other potential Collaborators: TBA

Short abstract: The pathophysiology of Adolescent Idiopathic Scoliosis (AIS) is not yet completely understood, but multi-factorial hypotheses have been proposed including defective central nervous system control of posture, biomechanics alterations and alterations of body schema. AIS could be the expression of a sub-clinical nervous system disorder. The aim of our study was to compare the electroencephalography activity in adolescents with AIS and controls, to examine the brain oscillatory changes related to balance control and inquire possibly related body schema representational alterations. Results may represent a valuable biomarker of AIS disease progression and offers novel therapeutic targets according to the identified pathophysiological patterns.

Research Line #: 20

Supervisor: Marco Zorzi

Potential Co-Supervisor/s: Andea Zangrossi; additional co-supervisors: Maurizio Corbetta, Giovanni Pezzulo (CNR-ISTC)

Other potential Collaborators: TBA

Short abstract: This project investigates eye movements during free-viewing tasks to uncover individual differences and identify novel biomarkers for neurological disorders. Building upon foundational work establishing idiosyncratic “viewing styles”, this research line aims to decode the complex dynamics of visual exploration. The primary objective is the unsupervised discovery of oculomotor endophenotypes that map onto specific neuro-cognitive profiles. The project will leverage advanced computational approaches, such as generative modeling and active inference frameworks, to model the underlying computational mechanisms of active vision and gaze allocation, moving beyond standard descriptive metrics. Ultimately, this research seeks to translate spontaneous viewing behavior into powerful, non-invasive computational phenotypes, offering critical insights into healthy cognitive diversity and the mechanistic disruptions characterizing neurological disease.

Research Line #: 21

Supervisor: Marco Zorzi

Potential Co-Supervisor/s: Michele Allegra, Maurizio Corbetta, Luca Pasa, Samir Suweis

Other potential Collaborators: TBA

Short abstract: This project focuses on developing explainable machine and/or deep learning models for the long-term prediction of clinical outcomes across diverse neurological disorders. A core objective is to rigorously assess the predictive contribution of multimodal data using a hierarchical framework that mirrors real-world clinical availability. Models will progressively integrate baseline demographics, neurological/neuropsychological information, routine structural neuroimaging, and ultimately, advanced neuroimaging (i.e., connectomics). Crucially, the project emphasizes Explainable AI (XAI) techniques to ensure the driving factors behind long-term predictions remain transparent, clinically interpretable, and biologically plausible. By mapping the specific added value of each clinical and neuroimaging tier, this research aims to deliver robust, trustworthy computational tools that optimize personalized patient care and resource allocation.

Research Line #: 22

Supervisor: Miryam Carecchio

Potential Co-Supervisor/s: Alessandra Bertoldo, Renzo Manara

Other potential Collaborators: TBA

Short abstract: Primary Brain Calcification (PBC) is a genetic neurodegenerative disorder characterized by bilateral basal ganglia calcification, with possible additional calcium deposition in cerebellar dentate nuclei, subcortical white matter, cerebral cortex, brainstam and thalami. MRI has been scarcely used in PBC diagnosis, given that CT is the gold standard to visualize brain calcification. This research line aims to investigate PBC disease using a multimodal MRI neuroimaging approach to better characterize its underlying pathophysiology. By integrating complementary imaging techniques, including structural MRI, diffusion imaging, functional MRI, and metabolic imaging, we seek to capture alterations across different levels of brain organization. The study will focus on identifying patterns of brain calcification and their relationship with microstructural integrity, functional connectivity, and metabolic changes, correlating these features with genetic mutations, clinical and neuropsychological scales.
Particular attention will be given to the interplay between structural damage and functional reorganization, with the goal of understanding how these changes contribute to clinical symptoms. Advanced data integration methods will be applied to combine information across modalities and improve sensitivity to subtle disease-related alterations.
Overall, this approach aims to provide a more comprehensive characterization of PBC, potentially contributing to the identification of imaging biomarkers and improving our understanding of disease mechanisms and disease trajectories across its heterogeneous clinical and genetic spectrum.

Research Line #: 23

Supervisor: Onelia Gagliano

Potential Co-Supervisor/s: TBA

Other potential Collaborators: TBA

Short abstract: Engineering organoid models represents a powerful strategy to investigate the cellular and molecular basis of human neurodevelopment. In this project, human pluripotent stem cell–derived organoids will be developed and refined to faithfully recapitulate early stages of neural tube formation. By integrating bioengineering approaches and controlled microenvironmental cues, these models will enable precise manipulation of developmental processes.
The platform will be used to dissect key signaling pathways, morphogenetic events, and gene regulatory networks involved in neural tube development. Particular emphasis will be placed on modeling the pathogenesis of neural tube defects, including spina bifida. Advanced imaging and transcriptomic analyses will provide high-resolution insights into developmental dynamics. Ultimately, this work aims to uncover fundamental mechanisms and identify novel targets for early diagnosis and therapeutic intervention.

Research Line #: 24

Supervisor: Ettore Ambrosini

Potential Co-Supervisor/s: Giada Viviani (UGR, Granada, ES), Maria Montefinese, Manfredo Atzori, Giovanni Pezzulo (CNR-ISTC)

Other potential Collaborators: TBA

Short abstract: This research line aims to characterize the neural and computational foundations of task sets and how they are dynamically modulated by cognitive control during conflict processing. Task sets are conceptualized as structured configurations linking stimuli, rules, and responses, whose activation and interference critically shape behavior in paradigms such as Stroop and task-switching. The project combines behavioral modeling, computational approaches, and neurophysiological measures (e.g., EEG) to quantify how task-set representations are instantiated, maintained, and selectively adjusted under conflict. A central goal is to identify how task-set similarity, automaticity, and contextual interference influence performance and neural signatures. By integrating theory-driven models with empirical data, this research seeks to advance a mechanistic account of cognitive control, bridging abstract computational principles with their neural implementation.

Research Line #: 25

Supervisor: Ettore Ambrosini

Potential Co-Supervisor/s: Giada Viviani (UGR, Granada, ES), Maria Montefinese, Antonino Visalli (UniMoRe), Manfredo Atzori, Giovanni Pezzulo (CNR-ISTC)

Other potential Collaborators: TBA

Short abstract: This research line investigates how predictive processes shape cognitive control and the resolution of conflict in goal-directed behavior. Within a predictive processing framework, control is conceptualized as the dynamic use of expectations about upcoming contextual demands. By manipulating environmental regularities and conflict probability, the project aims to quantify how prior expectations influence cognitive control and performance, particularly in terms of interference and facilitation effects. The approach combines behavioral paradigms with multivariate pattern analysis (MVPA) of electrophysiological data (e.g., EEG) and computational modeling to track how representational formats evolve over time and in response to expectation violations. A central objective is to determine whether predictive mechanisms operate across multiple representational levels and how these are reorganized under varying control demands. This research seeks to link predictive dynamics to the structure of neural representations, providing a mechanistic account of adaptive behavior.

Research Line #: 34

Supervisor: Annachiara Cagnin

Potential Co-Supervisor/s: Diego Cecchin

Other potential Collaborators: TBD

Short abstract: To study new and combined surrogate markers of in vivo neuropathology in neurodegenerative diseases by using PET/MRI imaging and fluid biomarkers

Research Line #: 35

Supervisor: Diego Cecchin

Potential Co-Supervisor/s: Alessandra Bertoldo, Francesco Marchetti

Other potential Collaborators: TBD

Short abstract: New 3D-4D CZT SPET/CT systems allows sensitive 360 acquisition but the reconstruction is still far from being perfect. We need to explore the entire process of reconstruction from raw images to reconstruction and filtering.

Research Line #: 36

Supervisor: Paolo Meneguzzo

Potential Co-Supervisor/s: Elena Tenconi

Other potential Collaborators: TBD

Short abstract: This PhD project investigates neuropsychological changes associated with gender-affirming hormone therapy (GAHT) in transgender and gender-diverse (TGD) individuals. Employing a longitudinal design, the study evaluates executive functioning, impulsivity, emotional processing, and decision-making at baseline, 6, and 12 months after initiating GAHT. Correlations between neuropsychological outcomes and hormonal profiles will be examined. Results aim to advance personalized care by clarifying hormonal influences on cognition and emotional health, promoting tailored interventions to support TGD well-being.

Research Line #: 37

Supervisor: Paolo Meneguzzo

Potential Co-Supervisor/s: Elena Tenconi

Other potential Collaborators: Angela Favaro

Short abstract: This PhD project investigates autistic traits in individuals with eating disorders (EDs), focusing on clinical severity, neuropsychological functioning, and social cognition. Through a cross-sectional design, the study evaluates autistic symptomatology, ED psychopathology severity, executive functions, emotional processing, and theory of mind abilities. Correlations between autistic features, cognitive profiles, social cognition impairments, and clinical presentations are analyzed, considering potential gender biases in assessment tools. Findings aim to enhance diagnostic precision and inform targeted, personalized interventions for ED patients with autism spectrum characteristics.

Research Line #: 38

Supervisor: Simone Messerotti Benvenuti

Potential Co-Supervisor/s: Fabio Sambataro, Carola Dell’Acqua

Other potential Collaborators: TBD

Short abstract: Major depressive disorder (MDD) is among the world’s most widespread and burdensome conditions, with chronic and recurrent courses. For prevention efforts to succeed, it is necessary to identify people early, and ideally, before they become ill. To advance our understanding of MDD’s pathophysiological mechanisms, this research line investigates deficits in motivation for rewards – particularly social rewards – as a potential early risk marker. To achieve this aim, this project will leverage subjective, physiological (e.g., ERPs), and behavioral methods to disentangle social reward processing in populations at-risk for the development of MDD.

Research Line #: 39

Supervisor: Simone Messerotti Benvenuti

Potential Co-Supervisor/s: Antonino Vallesi, Carola Dell’Acqua

Other potential Collaborators: TBD

Short abstract: Reduced approach motivation, namely emotional disengagement from appetitive cues, plays a key role in the development of major depressive disorder (MDD). EEG-based neurofeedback targeting left frontal activity (FAA-NF), a region linked to approach motivation, may help enhance this process. However, FAA-NF has yet to be applied during exposure to appetitive stimuli, and its potential to modulate their processing remains unexplored. This research examines whether FAA-NF can enhance appetitive cue processing in individuals with depressive symptoms, as measured by event-related potentials (ERPs).

Research Line #: 40

Supervisor: Mario Bonato

Potential Co-Supervisor/s: Giorgia Cona

Other potential Collaborators: TBD

Short abstract: To what extent cognitive performance as measured in the lab is relevant for everyday life ? We will tackle this issue from a lifespan perspective, asking participants to systematically report the more challenging situations they encounter on daily basis.

Research Line #: 41

Supervisor: Mario Bonato

Potential Co-Supervisor/s: TBD

Other potential Collaborators: TBD

Short abstract: We will use digital testing in stroke and Parkinson’s patients in order to better understand how they process time, space and quantities, namely fundamental characteristics of our environment. Particular attention will be devoted to the link between digital testing and everyday life contexts and to the performance of age-matched controls.

Research Line #: 42

Supervisor: Elisa Di Rosa

Potential Co-Supervisor/s: Annachiara Cagnin

Other potential Collaborators: TBD

Short abstract: Adverse life events, depression and anxiety experienced during the lifetime represent significant risk factors not only for the development of psychopathological conditions such as late-life depression but also for cognitive decline and dementia. However, the exact mechanisms underlying this link is still not clear. Furthermore, coping, emotion regulation strategies and social support have been recently suggested as possible proxy of Affective Reserve (Di Rosa, 2024), which might represent a protective factor for the development of both depression and cognitive decline in older adults. The project will be aimed at gaining new knowledge in this field studying the relationship between affective and cognitive processes.

Research Line #: 43

Supervisor: Elisa Di Rosa

Potential Co-Supervisor/s: Antonino Vallesi

Other potential Collaborators: TBD

Short abstract: Tobacco use, alcohol consumption, and unhealthy diet are key contributors of preventable morbidity and early mortality worldwide (Global Burden of Disease Collaborative Network, 2021). Despite these behaviours have been linked to impaired executive functions, evidence is still scarce for what concerns key mechanisms of this link, such as the delay of gratification capacity. The project is aimed at gaining new knowledge in this field, defining the neural, cognitive and behavioural mechanisms underlying health behaviour, with a special focus on delay of gratification capacity.

Research Line #: 44

Supervisor: Elisabetta Patron

Potential Co-Supervisor/s: Antonino Vallesi

Other potential Collaborators: TBD

Short abstract: A novel integrated approach is crucial for exploring the intricate interplay between the brain and body. This research line focuses on investigating the complex interactions among neural processes, physiological responses (e.g., cardiac, gastric), exploiting novel indexes such as the brain-heart interplay index. By incorporating advanced bio- and neurofeedback techniques, we can obtain real-time insights into brain-body communication patterns. Through this innovative methodology, which includes analyzing metrics such as heart rate variability in relation to neural oscillations, the ultimate goal of this project is to unravel the mechanisms that contribute to the development of psychopathological disorders and chronic diseases.

Research Line #: 45

Supervisor: Fabio Sambataro

Potential Co-Supervisor/s: Giuseppe Blasi

Other potential Collaborators: TBD

Short abstract: Bipolar disorder (BD) is highly heritable, with genetic factors accounting for approximately 70-85% of the risk. Neuroimaging studies suggest that this genetic predisposition influences brain structure and function, particularly in regions involved in mood regulation. Twin and family studies show that first-degree relatives of BD patients exhibit similar neuroimaging abnormalities, even without clinical symptoms, highlighting their potential as endophenotypes. Genetic variations, including polygenic risk scores, have been linked to alterations in white matter integrity and functional connectivity, providing insights into BD’s neurobiological underpinnings.

Research Line #: 46

Supervisor: Aram Megighian

Potential Co-Supervisor/s: Marco Dal Maschio, Maria Elena Miletto Petrazzini

Other potential Collaborators: David Baracchi

Short abstract: Adaptive behavior is the set of coordinated actions generated by the nervous system (NS) in response to environmental or internal stimuli, chosen among the most rewarding responses through the actual and former experience through decision-making. Visuomotor-responses (VMR) are critical for any organism fitness and are already present in animals evolutionarily distant from humans.
We analyse different processes regulating adaptive behavior by investigating VMR in D. melanogaster using quantitative behavior analyses, neurophysiology and calcium imaging, combined with genetic and molecular techniques.
Our aim is to investigate the neurobiological basis of said processes, linking the circuit to the behavior in a multiscale approach.

Research Line #: 47

Supervisor: Maurizio Corbetta

Potential Co-Supervisor/s: Manuela Allegra

Other potential Collaborators: Alessandro Salvalaggio

Short abstract: This research line focuses on the effect of focal lesions (stroke, tumors) on the brain connectome studied with multi-modal imaging. We will develop individual and group level fingerprints of connectomics dysfunction that predict behavior and long-term outcome. In addition, we will study the correlative and causal neurophysiological mechanisms using high density EEG and TMS-EEG. A final goal of the project is to develop novel treatments based on the connecomics insight offered by the above studies.

Research Line #: 48

Supervisor: Maurizio Corbetta

Potential Co-Supervisor/s: Michele Allegra

Other potential Collaborators: Manuela Allegra, Andrea Zangrossi, Ilaria Mazzonetto

Short abstract: This line of research focuses on the fundamental question of “what is spontaneous activity (SA) for?”. We are testing predictions of a theory of SA developed by our group (Pezzulo et al. TICS 2021). Accordingly SA is a generative model of the body, environment, and cognitive function representing dynamically the most common and behavioral relevant variables in each domain. We are carrying out numerous studies using both fMRI and HD-EEG testing this idea in the visual and motor domain, as well as in patients with focal lesions. In parallel we are carrying our animal studies using calcium imaging and optogenetics to test some of the same ideas. Parallel computational studies are trying to provide formal insight on these relationships.

Research Line #: 49

Supervisor: Marco Dal Maschio

Potential Co-Supervisor/s: Aram Megighian, Maria Elena Miletto Petrazzini

Other potential Collaborators: Nicola Facchinello

Short abstract: Coping with a continously changing environment calls for learning or updating the organism action-percpetion schemes. These type of primitives are considered the basis for the optimal processing of the sensoty inputs and at the same time the support for informing the motor program selection and execution. We will use visuo-motor processessing in Zebrafish larvae to investigate these mechanisms combining functional imaging, behavior tracking and targeted neuronal modulation. The ojective is to characterize the neuronal circuits involved and their role with the visuomotor adaptation mechanism as well as their alterations in genetic models of neurodevelopmental disorders.

Research Line #: 50

Supervisor: Mario Liotti

Potential Co-Supervisor/s: Simone Cutini

Other potential Collaborators: Antonino Vallesi

Short abstract: People with severe anxiety present difficulties in executive functions that affect quality of life. The present project will compare EEG and fNIRS measures of regional activity and functional connectivity at rest and in a cognitive control task with emotional distractors in groups of participants with high or low trait anxiety, to confirm correlates of high trait anxiety involving the frontoparietal and cingulo-opercular networks. Second aim is to perform a randomized controlled trial and a follow-up study to test the short-term efficacy of Beta tACS in alleviating anxiety symptoms and influencing the frontoparietal and cingulo-opercular networks. The third objective is to evaluate the long-term efficacy of neurostimulation treatment.

Research Line #: 51

Supervisor: Roberta Biundo

Potential Co-Supervisor/s: Erika Borella

Other potential Collaborators: TBD

Short abstract: Parkinson’s disease (PD) is a progressive neurodegenerative disorder affecting motor and non-motor functions. As the global population ages, the prevalence of PD is expected to rise, necessitating innovative rehabilitation approaches. While novel technologies are being developed to manage PD cognitive impairment (CI), their success rates vary. Variables affecting intervention effectiveness are unknown. The focus of the project is to understand the role of biomarkers profile (blood/CSF/neuroimaging), the cognitive and clinical phenotypes, into the differential effect of cognitive treatment efficacy, contributing to the development of personalized rehabilitation strategies. The role of cognitive reserve will be also investigated.

Research Line #: 52

Supervisor: Alessandra Del Felice

Potential Co-Supervisor/s: Manfredo Atzori

Other potential Collaborators: TBD

Short abstract: Motor recovery after stroke is still unsatisfactory. In fact, it relies mainly on qualitative measures (i.e., clinical scales), which provide only a partial prospective of the complex reorganization trajectories of motor performance during recovery. Quantitative assessment is mandatory and may inform rehabilitative pathways. The project aims to develop an innovative method to classify motor impairments by decomposing complex movements into functional modules (motor primitives). This will be possible by combining machine learning techniques with advanced Inertial Measurement Units (IMUs) and electromyographic (EMG) analysis. Eventually, this approach will be employed to phenotype post-stroke impairment, with critical clinical perspectives.

Research Line #: 53

Supervisor: Alessandra Del Felice

Potential Co-Supervisor/s: Emanuele Menegatti

Other potential Collaborators: TBD

Short abstract: TBD

Research Line #: 54

Supervisor: Angelo Antonini

Potential Co-Supervisor/s: Roberta Biundo, Marta Campagnolo

Other potential Collaborators: Aron Emmi

Short abstract: Establishing a clear correlation between clinical phenotypes and underlying neuropathology in neurodegenerative diseases remains a significant challenge. A single neuropathological entity can present with diverse clinical syndromes, making accurate diagnosis based solely on clinical features difficult. This challenge is further compounded by symptom overlap among different neurodegenerative diseases, such as tauopathies, Alzheimer’s disease, and Parkinson disease. This PhD will address the need for improved cognitive, imaging and neuropshsilogical biomarkers to enhance the accuracy of in vivo classification of neurodegenerative diseases.

Research Line #: 55

Supervisor: Angelo Antonini

Potential Co-Supervisor/s: Roberta Biundo, Andrea Landi

Other potential Collaborators: Andrea Guerra

Short abstract: Understanding the neural mechanisms of motivation and its dysfunction remains challenging, particularly in identifying specific biomarkers for symptoms, neuropsychiatric features, and cognitive sub-processes. Evidence suggests distinct spatio-spectral networks underlie dissociable functions, but single-site local field potential (LFP) recordings may capture overlapping neuronal activity. This project will use multi-site (cortical and subcortical) LFP recordings to investigate network dynamics in Parkinson’s disease. By integrating neurophysiological and computational approaches, this research aims to improve biomarker specificity and advance our understanding of motivation-related neural circuits.

Research Line #: 56

Supervisor: Enrico Collantoni

Potential Co-Supervisor/s: Antonino Vallesi, Arianna Menardi

Other potential Collaborators: TBD

Short abstract: Anorexia Nervosa is a severe and often treatment-resistant psychiatric disorder. This project investigates the effects of non-invasive brain stimulation targeting parietal circuits involved in body representation and cognitive control. Through a randomized trial and multimodal assessment, the project will explore clinical efficacy, underlying neurocognitive mechanisms, and predictors of treatment response. Ultimately, it aims to identify neurobiological and behavioral markers to inform personalized interventions and deepen our understanding of AN pathophysiology.

Research Line #: 57

Supervisor: Enrico Collantoni

Potential Co-Supervisor/s: Angela Favaro, Valentina Cardi

Other potential Collaborators: Andrea Serino (University of Lausanne, Switzerland)

Short abstract: Disturbances in body perception are core features of eating and weight disorders. This project aims to investigate the neural and computational mechanisms underlying these alterations through the lens of predictive coding and multisensory integration. By employing experimental paradigms based on virtual reality and inducing visuotactile and visuo-interoceptive conflicts, the project will examine how sensory inputs are weighted and integrated to generate a coherent sense of the body. Behavioral, neuroimaging, and molecular data will be combined with computational modeling to characterize altered predictive processes and their clinical relevance across the spectrum of these conditions.

Research Line #: 58

Supervisor: Marco Mainardi

Potential Co-Supervisor/s: Manuela Allegra

Other potential Collaborators: TBD

Short abstract: Synaptic plasticity is a cornerstone of nervous system development during development and adulthood, supporting the fine-tuning of neural circuits in response to experience. Isolating the key molecular orchestrators of synaptic plasticity is a fundamental goal in both basic and translational research.
Here, custom-made genetically encoded proteomics probes will be expressed in healthy mice and in transgenic models of neurodevelopmental diseases via adeno associated viral (AAV) vectors to characterize the synaptic proteome. Then, the impact of manipulating the expression of selected candidate proteins will be analyzed using behavioral testing and electrophysiology to identify potential druggable targets.

Research Line #: 59

Supervisor: Mario Bortolozzi

Potential Co-Supervisor/s: Marco Dal Maschio, Angelo Antonini

Other potential Collaborators: Jens Schwamborn (Luxembourg University)

Short abstract: Perfluoroalkyl substances (PFAS) are a large group of synthetic chemicals widely used in everyday products. Once ingested or inhaled, they accumulate in different organs, increasing the risk of cancer as well as neurological and reproductive disorders. In 2018, the Council of Ministers declared a state of emergency due to PFAS contamination in Vicenza, Verona, and Padua. Our 2022 study (Di Nisio et al., Env Int) was the first to demonstrate that PFAS alter human dopaminergic neuron development. This PhD project, conducted at the Veneto Institute of Molecular Medicine (VIMM, Padova), will further investigate PFAS effects using a 3D brain organoid model, applying advanced imaging and electrophysiological techniques.

Research Line #: 60

Supervisor: Mario Bortolozzi

Potential Co-Supervisor/s: Marco dal Maschio, Filippo Pisano

Other potential Collaborators: Vladimir Khorkov (ETH Zurich, Switzerland)

Short abstract: Discovered in 1993, the X-linked form of Charcot–Marie–Tooth disease (CMT1X) is the second most common genetic peripheral neuropathy. Caused by mutations in the GJB1 gene encoding connexin 32 (Cx32), its molecular mechanisms remain unclear, hindering personalized treatments based on genetic diagnosis. This PhD project aims to (i) show that ATP release dysfunction in Cx32 hemichannels drives CMT1X pathogenesis and (ii) develop in vitro assays to test potential therapies for various CMT1X mutations. The selected candidate will work at the Veneto Institute of Molecular Medicine (VIMM, Padua), benefiting from state-of-the-art biological and biophysical facilities.

Research Line #: 61

Supervisor: Judit Gervain

Potential Co-Supervisor/s: Silvia Benavides Varela

Other potential Collaborators: TBD

Short abstract: Infants learn language with surprising ease. How they perceive the speech input they receive plays an important role in scaffolding language development. The current line of research investigates the neural mechanisms underlying newborns and young infants’ speech perception abilities and how they contribute to learning language.

Research Line #: 62

Supervisor: Judit Gervain

Potential Co-Supervisor/s: Samir Simon Suweis, Ramon Guevara

Other potential Collaborators: TBD

Short abstract: Language acquisition is a par excellence critical period phenomenon: young infants learning language with ease, while adults need to make efforts, and typically do not achieve native-like competence. The underlying neural mechanisms of the reduction of neuroplasticity for speech perception and language acquisition are only now beginning to be understood. This line of research explore these mechanisms in young infants using state-of-the-art neuroimaging and models them using dynamical systems theory.