17 research outputs found
Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study
No full textTemporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.Duma et al. used innovative methods like subject-wise structural covariance network and neuronal avalanches to study structural and functional brain organization in temporal lobe epilepsy. A coupling was observed between the propagation of aperiodic burst of activity and cortical thickness organization focused in brain regions related to seizure initiation and propagation.Graphical Abstrac
Local cohomology, master equation and renormalization of higher-derivative and nonlocal quantum gravity
No full textIn this thesis we have studied the properties of a higher-derivative toy model of quantum gravity and we have used the results to analyze the main features of nonlocal theories of quantum gravity. The renormalizability of higher-derivative quantum gravity have been revisited by using the Batalin-Vilkovisky formalism. The very hearth of this formalism is the master equation which plays a foundamental role in the analysis of a gauge system. In particular, it is very useful to prove the renormalizability of a gauge theory. We have considered two main approaches to prove the renormalizability of higher-derivative quantum gravity, both performed by induction in the number of loops.
The “cohomological” approach preserves the validity of the master equation at each inductive step. We assume that the theory is renormalized up to n-loops and then prove that we can cancel out all the divergences at (n + 1)-loops. It turns out that the (n+1)-loops counterterms must satisfy a certain cohomological condition. The cohomological method only works if we can write the solution of this condition
as a sum of a gauge invariant functional of the gauge fields plus a trivial term. This is also known as Kluberg-Stern-Zuber conjecture. In the
original work on the renormalizability of higher-derivative quantum gravity, Stelle assumes the validity of the conjecture. So far, it has been proved for Yang-Mills theory and Einstein gravity. We have extended the proof to higher-derivative quantum gravity. Our results naturally extend to nonlocal theories of quantum gravity, which turn out to be super-renormalizable.
In general, it is not obvious that the Kluberg-Stern-Zuber condition holds. In such a situation, the cohomological approach would fail. A more powerful method which avoid this constraint is a so-called “quadratic” approach. In this case, the inductive procedure absorbs the divergences automatically at each loop. On the other hand, it postpones the solution of the master equation to the end of the inductive procedure, after the theory is renormalized to all orders. We have worked out the exact solution of the master equation at the renormalized level. This result also proves that higher-derivative quantum gravity is renormalizable, and generates the same number of renormalization constants as the cohomological approach. In particular,the structure of the BRST transformations is preserved by renormalization.
This last property, extended also to nonlocal gravity, enabled us to conclude that general covariance is the most general gauge symmetry of a renormalizable higher-derivative and nonlocal quantum theory of gravity.
Besides the investigation of higher-derivative quantum gravity, we have also considered aspects of nonlocal theories. The interest in studying nonlocal theories is twofold. On the one hand, it brings to light a sector of quantum field theory that is still vastly unexplored and worth of investigation. On the other hand, it is a candidate for a unitary and super-renormalizable quantum theory of gravitation. It is worth to note that these theories are also predictive to a certain extent. Indeed, they have a rather constrained behaviour in the UV limit and provide predictive transition amplitudes at high energies
Spontaneous neuronal avalanches as a correlate of access consciousness
No full textInternational audienceDecades of research have advanced our understanding of the biophysical mechanisms underlying consciousness. However, an overarching framework bridging between models of consciousness and the large-scale organization of spontaneous brain activity is still missing. Based on the observation that spontaneous brain activity dynamically switches between epochs of segregation and large-scale integration of information, we hypothesize a brain-state dependence of conscious access, whereby the presence of either segregated or integrated states marks distinct modes of information processing. We first review influential works on the neuronal correlates of consciousness, spontaneous resting-state brain activity and dynamical system theory. Then, we propose a test experiment to validate our hypothesis that conscious access occurs in aperiodic cycles, alternating windows where new incoming information is collected but not experienced, to punctuated short-lived integration events, where conscious access to previously collected content occurs. In particular, we suggest that the integration events correspond to neuronal avalanches, which are collective bursts of neuronal activity ubiquitously observed in electrophysiological recordings. If confirmed, the proposed framework would link the physics of spontaneous cortical dynamics, to the concept of ignition within the global neuronal workspace theory, whereby conscious access manifest itself as a burst of neuronal activity
Die Renormierungsgruppe Flussanalyse für eine Kosmologischer Sektor von Spin-Schaum Modells
No full textSpin Foam Models (SFM) provide a non-perturbative and background independent path integral formulation of Quantum Gravity. The models are built on a lattice which represents spacetime and serves as a tool to control the d.o.f. of geometry. In fact, a given discretization can be thought as a scale at which we look at spacetime, while its refinement resembles a shift towards UV regimes. In the light of this interpretation, a SFM state sum is understood as an effective theory for the available degrees of freedom provided by the lattice. Then, the Wilsonian renormalization group approach stands out as an ideal tool to organize and describe the flow of the theory along a scale of complexity of the base lattice.
While many promising results have been achieved in SFM, the dynamics of these models is still hard to solve and most calculations are performed on extremely coarse discretizations. In order to get access to finer lattices we reduce the path integral state sum to certain symmetric configurations of geometry. This allows a numerical evaluation of some geometric observables on coarser and finer discretizations. Their comparison defines the renormalization group flow of the model in the parameter space. Notably, we find a fixed point with one attractive and two repulsive directions in the three-dimensional parameter space of the asymptotic Euclidean EPRL-FK Spin Foam Model. In such point, the expectation value of the observables do not depend on the lattice complexity. The existence of a fixed point opens the way to study another open problem of SFM, i.e. the continuum (infinite refinement) limit.Spin-Schaum Modells ermöglichen eine nicht-perturbative Pfadintegral Formulierung der Quantengravitation unabhängig von Hintergrund. Diese Modelle werden auf einem Gitter konstruiert, welches die Raumzeit repräsentiert und als Hilfsmittel dient um die Freiheitsgrade der Geometrie zu kontrollieren. Tatsächlich kann eine bestimmte Diskretisierung als Größenordnung auf welcher wir die Raumzeit betrachten, verstanden werden. Eine Verfeinerung bedeutet eine Verschiebung in den ultraviolett Bereich. In Anbetracht dieser Interpretation kann eine Spin-Schaum Zustandssumme als eine effektive Theorie für die durch das Gitter vorgegeben verfügbaren Freiheitsgrade verstanden werden. Daraus ergibt sich der Ansatz der Wilsonschen Renormierungsgruppe als ideales Hilfsmittel um den Fluss der Theorie in die Richtung einer Größenordnung an Komplexität des Grund-Gitters zu organisieren und zu beschreiben.
Während viele vielversprechende Ergebnisse mit Spin-Schaum Modellen erreicht wurden, ist die Dynamik dieser Modelle immer noch schwer zu lösen und die meisten Berechnungen werden auf extrem groben Diskretisierungen durchgeführt. Um eine feinere Gitterauflösung zu erreichen, reduzieren wir die Zustandssumme des Pfadintegrals auf gewisse symmetrische Konfigurationen der Geometrie. Dies erlaubt eine numerische Auswertung von einigen geometrischen Observablen auf gröberen und feineren Diskretisierungen. Der Vergleich von diesen definiert den Fluss der Renormierungsgruppe des Modells im Parameterraum. Bemerkenswerterweise finden wir einen Fixpunkt mit einer attraktiven und zwei repulsiven Richtungen im dreidimensionalen Parameterraum eines asymptotisch euklidischen EPRL-FK Spin-Schaum Modell. In einem solchen Punkt hängt der Erwartungswert der Observablen nicht von der Gitterkomplexität ab. Die Existenz eines solchen Fixpunktes öffnet einen neuen Weg um anderen offene Probleme des Spin-Schaum Modells wie das kontinuierliche Limit (unendliche Verfeinerung) zu studieren
Magnetoencephalography dimensionality reduction informed by dynamic brain states
No full textComplex spontaneous brain dynamics mirror the large number of interactions taking place among regions, supporting higher functions. Such complexity is manifested in the interregional dependencies among signals derived from different brain areas, as observed utilising neuroimaging techniques, like magnetoencephalography. The dynamics of this data produce numerous subsets of active regions at any moment as they evolve. Notably, converging evidence shows that these states can be understood in terms of transient coordinated events that spread across the brain over multiple spatial and temporal scales. Those can be used as a proxy of the ‘effectiveness’ of the dynamics, as they become stereotyped or disorganised in neurological diseases. However, given the high-dimensional nature of the data, representing them has been challenging thus far. Dimensionality reduction techniques are typically deployed to describe complex interdependencies and improve their interpretability. However, many dimensionality reduction techniques lose information about the sequence of configurations that took place. Here, we leverage a newly described algorithm, potential of heat-diffusion for affinity-based transition embedding (PHATE), specifically designed to preserve the dynamics of the system in the low-dimensional embedding space. We analysed source-reconstructed resting-state magnetoencephalography from 18 healthy subjects to represent the dynamics of the configuration in low-dimensional space. After reduction with PHATE, unsupervised clustering via K-means is applied to identify distinct clusters. The topography of the states is described, and the dynamics are represented as a transition matrix. All the results have been checked against null models, providing a parsimonious account of the large-scale, fast, aperiodic dynamics during resting-state.
The study applies the PHATE algorithm to source-reconstructed magnetoencephalography (MEG) data, reducing dimensionality while preserving large-scale neural dynamics. Results reveal distinct configurations, or ‘states’, of brain activity, identified via unsupervised clustering. Their transitions are characterised by a transition matrix. This method offers a simplified yet rich view of complex brain interactions, opening new perspectives on large-scale brain dynamics in health and disease
Deformation of the Engle-Livine-Pereira-Rovelli spin foam model by a cosmological constant
No full textComplexity in speech and music listening via neural manifold flows
No full textInternational audienceUnderstanding the complex neural mechanisms underlying speech and music perception remains a multifaceted challenge. In this study, we investigated neural dynamics using human intracranial recordings. Employing a novel approach based on low-dimensional reduction techniques, the Manifold Density Flow (MDF), we quantified the complexity of brain dynamics during naturalistic speech and music listening and during resting state. Our results reveal higher complexity in patterns of interdependence between different brain regions during speech and music listening compared with rest, suggesting that the cognitive demands of speech and music listening drive the brain dynamics toward states not observed during rest. Moreover, speech listening has more complexity than music, highlighting the nuanced differences in cognitive demands between these two auditory domains. Additionally, we validated the efficacy of the MDF method through experimentation on a toy model and compared its effectiveness in capturing the complexity of brain dynamics induced by cognitive tasks with another established technique in the literature. Overall, our findings provide a new method to quantify the complexity of brain activity by studying its temporal evolution on a low-dimensional manifold, suggesting insights that are invisible to traditional methodologies in the contexts of speech and music perception
Metodologie didattiche per l'insegnamento-apprendimento della Fisica: studi di caso nella Scuola Secondaria di II grado
No full text2015 - 2016The present work focuses on case studies conducted from 2014 to 2016 in Secondary Schools in
Campania where new teaching methodologies for teaching - Physical Learning have been
experimented. Of these methodologies, merits and limits are highlighted and each case, as an example
of good practice, shows the possible replication in other contexts. Work is to be a didactic
epistemological attempt to address learning-learning issues also in relation to teacher training needs.
Case studies cover some salient themes of physics, from mechanics to modern physics but also
replicable in other contexts and in relation to other topics.
The following methodologies have experimented: situated learning, flipped learning, Inquiry-Based
Science Education (IBSE), Digital Storytelling, Educational Robotics, Action Research, Scrum
methodology. The experiments were presented at national and international conferences (AIF Perugia
2014, AIF Trento 2015, AIF Assergi 2016, SIF Roma 2015, SIF Padova 2016, GIREP Wroclaw 2015,
DIFIMA Torino 2015, HPM Montpellier 2016, WCPE San Paolo 2016) Have been published in
international journals or conference proceedings, others are being published.
In addition, some experimental activities have been welcomed at the City of Science as an example
of good teaching practice at the "Three Days for School" (2015) and the Picnics of Science (2016).
An activity was presented at the International Forum SkySEF 2015 in Shimizu, Japan, receiving
appreciation from the jury of experienced teachers at Shizuoka University.
Finally, training courses were held in the Campania area for teachers on skills education, in the three
areas of knowledge, Pedagogical Knowledge, Subject Matter Content Knowledge and Knowledge
Curricular Knowledge, which includes programs, materials, and teaching tools, software (Shulman).
The didactic activities carried out during these three years have been shown to teach teachers how to
implement effective classroom action in the classroom, how to make an intervention product, how to
form an authentic test. Of these training actions, the reports have been collected and included in this
work.
The research methodology implemented falls within the framework of Educational Reconstruction
(Kattmann et al, 1995), which allows studying the teaching phenomena by designing and realizing
learning environments, artifacts, teaching/learning sequences that the researcher experiences,
evaluates, re-elaborates and develops in authentic educational contexts. The study is contextualized
in the theoretical/epistemological framework of Enactivism and, in particular, the cognitive theory
that is being considered is the development of knowledge through model building. [edited by Author]Il presente lavoro è incentrato su studi di caso condotti, dal 2014 al 2016, in Istituti Secondari di II
grado del territorio campano in cui si sono state sperimentate nuove metodologie didattiche per
l’insegnamento – apprendimento della Fisica. Di tali metodologie si evidenziano meriti e limiti e di
ciascun caso, come esempio di buona pratica, viene mostrata la possibile replicabilità in altri contesti.
Il lavoro vuole essere un tentativo didattico-epistemologico di affrontare problematiche di
insegnamento-apprendimento anche in relazione ai bisogni formativi dei docenti. Gli studi di caso
riguardano alcuni temi salienti della fisica, dalla meccanica alla fisica moderna ma replicabili anche
in altri contesti e in relazione ad altri argomenti.
Sono state sperimentate le seguenti metodologie: l’apprendimento situato (situated learning), il
metodo della classe capovolta (flipped teaching), l’Inquiry Based Science Education (IBSE), il
Digital Storytelling, la Robotica educativa, la Ricerca – Azione (Action Research), la metodologia
Scrum.
Le sperimentazioni sono state presentate in convegni nazionali e internazionali (AIF Perugia 2014,
AIF Trento 2015, AIF Assergi 2016, SIF Roma 2015, SIF Padova 2016, GIREP Wroclaw 2015,
DIFIMA Torino 2015, HPM Montpellier 2016, WCPE San Paolo 2016): alcune sono state oggetto di
pubblicazione su riviste internazionali o su atti di convegno, altre sono in fase di pubblicazione.
Inoltre, alcune attività sperimentali sono state accolte a Città della Scienza come esempio di buone
pratiche didattiche, in occasione dei “Tre giorni per la scuola” (2015), e del “Pic nic della scienza”
(2016). Una attività è stata presentata al Forum Internazionale SkySEF 2015 a Shimizu in Giappone
ricevendo apprezzamenti dalla giuria di docenti esperti dell’Università di Shizuoka.
Infine, sono stati condotti, sempre sul territorio campano, corsi di formazione rivolti ai docenti sulla
didattica per competenze, nei tre ambiti di conoscenza, la Conoscenza Pedagogica (Pedagogical
Knowledge), la Conoscenza di Contenuti disciplinari (Subject Matter Content Knewledge) e la
Conoscenza Curricolare (Curricular Knowledge), che comprende programmi, materiali e strumenti
didattici, software (Shulman). Sono state mostrate le attività didattiche svolte in questi tre anni per
dare spunto ai docenti su come implementare in classe una efficace azione didattica per competenza,
come realizzare un prodotto di intervento, come strutturare una prova autentica. Di queste azioni di
formazione sono stati raccolti i report e inseriti in questo lavoro.
La metodologia di ricerca attuata rientra nel quadro della Educational Reconstruction (Kattmann et
al, 1995), che permette di studiare i fenomeni didattici progettando e realizzando ambienti di
apprendimento, artefatti, sequenze di insegnamento/apprendimento che il ricercatore sperimenta,
valuta, rielabora e sviluppa in contesti educativi autentici.
Lo studio si contestualizza nel quadro teorico/epistemologico dell’Enattivismo e, in particolare, la
teoria cognitiva che viene presa in esame è quella dello sviluppo della conoscenza attraverso la
costruzione di modelli. [a cura dell'Autore]XXIX n.s
Neuronal Cascades Shape Whole-Brain Functional Dynamics at Rest
No full textInternational audienceAt rest, mammalian brains display remarkable spatiotemporal complexity, evolving through recurrent functional connectivity (FC) states on a slow timescale of the order of tens of seconds. While the phenomenology of the resting state dynamics is valuable in distinguishing healthy and pathologic brains, little is known about its underlying mechanisms. Here, we identify neuronal cascades as a potential mechanism. Using full-brain network modeling, we show that neuronal populations, coupled via a detailed structural connectome, give rise to large-scale cascades of firing rate fluctuations evolving at the same time scale of resting-state networks (RSNs). The ignition and subsequent propagation of cascades depend on the brain state and connectivity of each region. The largest cascades produce bursts of blood oxygen level-dependent (BOLD) co-fluctuations at pairs of regions across the brain, which shape the simulated RSN dynamics. We experimentally confirm these theoretical predictions. We demonstrate the existence and stability of intermittent epochs of FC comprising BOLD co-activation (CA) bursts in mice and human functional magnetic resonance imaging (fMRI). We then provide evidence for the existence and leading role of the neuronal cascades in humans with simultaneous EEG/fMRI recordings. These results show that neuronal cascades are a major determinant of spontaneous fluctuations in brain dynamics at rest
