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PubblicazioneFermi-liquid corrections to the intrinsic anomalous Hall conductivity of topological metals( 2025)We show that topological metals lacking time-reversal symmetry have an intrinsic non-quantised component of the anomalous Hall conductivity which is contributed not only by the Berry phase of quasiparticles on the Fermi surface, but also by Fermi-liquid corrections due to the residual interactions among quasiparticles, the Landau f-parameters. These corrections pair up with those that modify the optical mass with respect to the quasiparticle effective one, or the charge compressibility with respect to the quasiparticle density of states. Our result supports recent claims that the correct expressions for topological observables include vertex corrections besides the topological invariants built just upon the Green’s functions. Furthermore, it demonstrates that such corrections are naturally accounted for by Landau’s Fermi liquid theory, here extended to the case in which coherence effects between bands crossing the chemical potential and those that are instead away from it may play a crucial role, as in the anomalous Hall conductivity, and have important implications when those metals are on the verge of a doping-driven Mott transition, as we discuss.
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PubblicazioneDeciphering Rapid Cell Signaling and Control of Cell Motility by Reverse Opto-Chemical Engineering( 2026)Cells transform complex environmental stimuli into physiological responses. In dynamic environments, or when a motile cell moves in a static setting, stimuli change over time. Here we introduce a concept, “reverse opto-chemical engineering,” which uses temporal light patterns and photo-triggers to create virtual sensory landscapes for cells. This allows us to record their physiological responses and motor behavior in real time. Using this approach, we studied cyclic-nucleotide signaling in sperm cells and mapped their stimulus-response transfer function. The technique can be employed for remote control of motility by light. Exploiting the chemotactic signaling backbone, we enable sperm to navigate in light gradients, making them attracted to light. This method offers possibilities for uncovering the mechanisms and signaling molecules behind rapid cellular computations, helping to understand the wiring diagram of cellular networks.
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PubblicazioneVisual motion processing recruits regions selective for auditory motion in early deaf individuals( 2021)In early deaf individuals, the auditory deprived temporal brain regions become engaged in visual processing. In our study we tested further the hypothesis that intrinsic functional specialization guides the expression of cross-modal responses in the deprived auditory cortex. We used functional MRI to characterize the brain response to horizontal, radial and stochastic visual motion in early deaf and hearing individuals matched for the use of oral or sign language. Visual motion showed enhanced response in the ‘deaf’ mid-lateral planum temporale, a region selective to auditory motion as demonstrated by a separate auditory motion localizer in hearing people. Moreover, multivariate pattern analysis revealed that this reorganized temporal region showed enhanced decoding of motion categories in the deaf group, while visual motion-selective region hMT+/V5 showed reduced decoding when compared to hearing people. Dynamic Causal Modelling revealed that the ‘deaf’ motion-selective temporal region shows a specific increase of its functional interactions with hMT+/V5 and is now part of a large-scale visual motion selective network. In addition, we observed preferential responses to radial, compared to horizontal, visual motion in the ‘deaf’ right superior temporal cortex region that also show preferential response to approaching/receding sounds in the hearing brain. Overall, our results suggest that the early experience of auditory deprivation interacts with intrinsic constraints and triggers a large-scale reallocation of computational load between auditory and visual brain regions that typically support the multisensory processing of motion information.
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PubblicazioneMultimodal processing in face-to-face interactions: A bridging link between psycholinguistics and sensory neuroscience( 2023)In face-to-face communication, humans are faced with multiple layers of discontinuous multimodal signals, such as head, face, hand gestures, speech and non-speech sounds, which need to be interpreted as coherent and unified communicative actions. This implies a fundamental computational challenge: optimally binding only signals belonging to the same communicative action while segregating signals that are not connected by the communicative content. How do we achieve such an extraordinary feat, reliably, and efficiently? To address this question, we need to further move the study of human communication beyond speech-centred perspectives and promote a multimodal approach combined with interdisciplinary cooperation. Accordingly, we seek to reconcile two explanatory frameworks recently proposed in psycholinguistics and sensory neuroscience into a neurocognitive model of multimodal face-to-face communication. First, we introduce a psycholinguistic framework that characterises face-to-face communication at three parallel processing levels: multiplex signals, multimodal gestalts and multilevel predictions. Second, we consider the recent proposal of a lateral neural visual pathway specifically dedicated to the dynamic aspects of social perception and reconceive it from a multimodal perspective (“lateral processing pathway”). Third, we reconcile the two frameworks into a neurocognitive model that proposes how multiplex signals, multimodal gestalts, and multilevel predictions may be implemented along the lateral processing pathway. Finally, we advocate a multimodal and multidisciplinary research approach, combining state-of-the-art imaging techniques, computational modelling and artificial intelligence for future empirical testing of our model.
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PubblicazioneHow much can the eigenvalues of a random hermitian matrix fluctuate?( 2021)The goal of this article is to study how much the eigenvalues of large Hermitian random matrices deviate from certain deterministic locations-or in other words, to investigate optimal rigidity estimates for the eigenvalues. We do this in the setting of one-cut regular unitary invariant ensembles of random Hermitian matrices, the Gaussian unitary ensemble (GUE) being the prime example of such an ensemble. Our approach to this question combines extreme value theory of log-correlated stochastic processes, and in particular the theory of multiplicative chaos, with asymptotic analysis of large Hankel determinants with Fisher-Hartwig symbols of various types, such as merging jump singularities, size-dependent impurities, and jump singularities approaching the edge of the spectrum. In addition to optimal rigidity estimates, our approach sheds light on the fractal geometry of the eigenvalue counting function.