Tommaso Menara

Tommaso Menara
University of California, San Diego | UCSD · Department of Mechanical and Aerospace Engineering (MAE)

Doctor of Philosophy

About

30
Publications
4,560
Reads
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266
Citations
Introduction
Tommaso Menara currently works at the Department of Mechanical and Aerospace Engineering, University of California, San Diego. Tommaso does research in Control Systems Engineering and Network Neuroscience.
Education
September 2013 - April 2016
Università di Pisa
Field of study
  • Robotics and Automation Engineering
September 2010 - September 2013
University of Padova
Field of study
  • Mechanics and Mechatronics Engineering

Publications

Publications (30)
Article
The theory of structural controllability allows us to assess controllability of a network as a function of its interconnection graph and independently of the edge weights. Yet, existing structural controllability results require the weights to be selected arbitrarily and independently from one another, and provide no guarantees when these condition...
Conference Paper
In this paper, we propose a framework to control brain-wide functional connectivity by selectively acting on the brain's structure and parameters. Functional connectivity, which measures the degree of correlation between neural activities in different brain regions, can be used to distinguish between healthy and certain diseased brain dynamics and,...
Preprint
Full-text available
Oscillatory activity is ubiquitous in natural and engineered network systems. The interaction scheme underlying interdependent oscillatory components governs the emergence of network-wide patterns of synchrony that regulate and enable complex functions. Yet, understanding, and ultimately harnessing, the structure-function relationship in oscillator...
Article
Full-text available
Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory performance entails brain-wide switching between activity states using a combination of functional magnetic resonance imaging in healthy controls and individuals with schizophrenia, pha...
Preprint
Full-text available
Humans are capable of adjusting to changing environments flexibly and quickly. Empirical evidence has revealed that representation learning plays a crucial role in endowing humans with such a capability. Inspired by this observation, we study representation learning in the sequential decision-making scenario with contextual changes. We propose an o...
Preprint
Full-text available
In this paper, we study representation learning for multi-task decision-making in non-stationary environments. We consider the framework of sequential linear bandits, where the agent performs a series of tasks drawn from distinct sets associated with different environments. The embeddings of tasks in each set share a low-dimensional feature extract...
Preprint
Full-text available
The human brain consumes a disproportionate amount of energy to generate neural dynamics. Yet precisely how energetic processes are altered in neurological disorders remains far from understood. Here, we use network control theory to profile the brain's energy landscape, describing the rich dynamical repertoire supported by the structural connectom...
Article
Full-text available
Cross-frequency phase-amplitude coupling (PAC) describes the phenomenon where the power of a high-frequency oscillation evolves with the phase of a low-frequency one. It has been widely observed in the brain and linked to various brain functions. In this paper, we show that Stuart-Landau oscillators coupled in a nonlinear fashion can give rise to P...
Article
Remote synchronization describes a fascinating phenomenon where oscillators that are not directly connected via physical links evolve synchronously. This phenomenon is thought to be critical for distributed information processing in the mammalian brain, where long-range synchronization is empirically observed between neural populations belonging to...
Article
Full-text available
Context: Large multi-site neuroimaging datasets have significantly advanced our quest to understand brain-behavior relationships and to develop biomarkers of psychiatric and neurodegenerative disorders. Yet, such data collections come at a cost, as the inevitable differences across samples may lead to biased or erroneous conclusions. Objective:...
Preprint
Full-text available
Phase-amplitude coupling (PAC) describes the phenomenon where the power of a high-frequency oscillation evolves with the phase of a low-frequency one. We propose a model that explains the emergence of PAC in two commonly-accepted architectures in the brain, namely, a high-frequency neural oscillation driven by an external low-frequency input and tw...
Preprint
Full-text available
Phase-amplitude coupling (PAC) describes the phenomenon where the power of a high-frequency oscillation evolves with the phase of a low-frequency one. We propose a model that explains the emergence of PAC in two commonly-accepted architectures in the brain, namely, a high-frequency neural oscillation driven by an external low-frequency input and tw...
Article
Feedback linearization allows for the local transformation of a nonlinear system to an equivalent linear one by means of a coordinate transformation and a feedback law. Feedback linearization of large-scale nonlinear network systems is typically difficult, as existing conditions become harder to check as the network size becomes larger. In this let...
Preprint
Full-text available
Large multi-site neuroimaging datasets have significantly advanced our quest to understand brain-behaviour relationships and to develop biomarkers of psychiatric and neurodegenerative disorders. Yet, such data collections come at a cost, as the inevitable differences across samples may lead to biased or erroneous conclusions. Previous work has inve...
Article
Full-text available
Optimizing direct electrical stimulation for the treatment of neurological disease remains difficult due to an incomplete understanding of its physical propagation through brain tissue. Here, we use network control theory to predict how stimulation spreads through white matter to influence spatially distributed dynamics. We test the theory's predic...
Conference Paper
In this paper we derive exact and approximate conditions for the (local) stability of the cluster synchronization manifold for sparsely interconnected oscillators with heteroge- neous and weighted Kuramoto dynamics. Cluster synchroniza- tion, which emerges when the oscillators can be partitioned in a way that their phases remain identical over time...
Preprint
Full-text available
Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory entails brain-wide switching between activity states. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expre...
Preprint
Full-text available
Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory entails brainwide switching between activity states. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expres...
Preprint
In this paper, we propose a framework to controlbrain-wide functional connectivity by selectively acting onthe brain’s structure and parameters. Functional connectivity,which measures the degree of correlation between neuralactivities in different brain regions, can be used to distinguishbetween healthy and certain diseased brain dynamics and,possi...
Conference Paper
In this paper we propose and analyze a novel notion of controllability of network systems with linear dynamics and symmetric weights. Namely, we quantify the controllability degree of a network with its distance from the set of uncontrollable networks with the same structure, that is, with the minimum Frobenius norm of a structured perturbation ren...
Preprint
In this paper we study cluster synchronization in networks of oscillators with heterogenous Kuramoto dynamics, where multiple groups of oscillators with identical phases coexist in a connected network. Cluster synchronization is at the basis of several biological and technological processes; yet the underlying mechanisms to enable cluster synchroni...
Preprint
Full-text available
Electrical brain stimulation is currently being investigated as a therapy for neurological disease. However, opportunities to optimize such therapies are challenged by the fact that the beneficial impact of focal stimulation on both neighboring and distant regions is not well understood. Here, we use network control theory to build a model of brain...
Preprint
Full-text available
Electrical brain stimulation is currently being investigated as a potential therapy for neurological disease. However, opportunities to optimize and personalize such therapies are challenged by the fact that the beneficial impact (and potential side effects) of focal stimulation on both neighboring and distant regions is not well understood. Here,...
Preprint
Full-text available
This is only a note. The full work is available here: https://ieeexplore.ieee.org/document/8533416 __________________________________________________________________________
Conference Paper
Network controllability is a structural property, that is, mild and well-understood conditions on the network interconnection pattern ensure controllability from a given set of control nodes for most choices of the edge weights. To ensure network controllability for all choices of edge weights, namely strong structural controllability, more stringe...
Conference Paper
Full-text available
This paper describes the comparison between two drug control strategies to hemophilia A. To emulate blood clotting and the pathological condition of hemophilia, a mathematical model composed by 14 ordinary differential equations is considered. We adopt a variable structure non-linear PID approach and a Model Predictive Control in order to control t...

Projects

Projects (2)
Project
Develop a rigorous framework to approach control of functional connectivity in the human brain by means of cluster synchronization of nonlinear oscillators.
Project
Investigate controllability properties of brain networks.