arXiv subjects

Marco Dal Maschio

Publications and source records attributed to Marco Dal Maschio.

3 recordsLinked to original sources

arXiv2026

Scaling and tuning to criticality in resting-state human magnetoencephalography

From 1/f noise to neuronal avalanches, evidence of scaling in brain activity has been increasingly linked to tuning to or near criticality. The concept of scaling is intimately related to the renormalization group (RG), in essence providing coarse-grained, simplified descriptions that generalize to classes of diverse physical systems. Following the RG idea, scaling laws have been reported in populations of spiking neurons at microscopic scales. Whether similar scaling principles govern large-scale neural activity in the human brain and how they relate to underlying neural physiology remains unresolved. Here, we analyze large-scale electrophysiological recordings (MEG) of human resting-state brain activity and apply a RG-inspired coarse-graining approach to track collective neural dynamics across spatial scales. We find that multiple observables exhibit robust scale-invariant behavior under coarse-graining: activity variance and correlations grow according to power laws, covariance eigenspectra follow a characteristic scaling relation, and neuronal avalanche statistics remain invariant. Using an analytically tractable neural network model, we show that the observed scaling signatures arise when the system operates slightly below criticality, and that the scaling exponents depend on the excitation-inhibition balance. These findings demonstrate that RG-inspired scaling analysis can uncover signatures of critical dynamics in non-invasive human electrophysiology and suggest a principled route toward estimating excitation-inhibition balance from large-scale brain recordings.

q-bio.NC↗

arXiv2025

Optimal information gain at the onset of habituation to repeated stimuli

Biological and living systems process information across spatiotemporal scales, exhibiting the hallmark ability to constantly modulate their behavior to ever-changing and complex environments. In the presence of repeated stimuli, a distinctive response is the progressive reduction of the activity at both sensory and molecular levels, known as habituation. In this work, we solve a minimal microscopic model devoid of biological details, where habituation to an external signal is driven by negative feedback provided by a slow storage mechanism. We show that our model recapitulates the main features of habituation, such as spontaneous recovery, potentiation, subliminal accumulation, and input sensitivity. Crucially, our approach enables a complete characterization of the stochastic dynamics, allowing us to compute how much information the system encodes on the input signal. We find that an intermediate level of habituation is associated with a steep increase in information. In particular, we are able to characterize this region of maximal information gain in terms of an optimal trade-off between information and energy consumption. We test our dynamical predictions against experimentally recorded neural responses in a zebrafish larva subjected to repeated looming stimulations, showing that our model captures the main components of the observed neural habituation. Our work makes a fundamental step towards uncovering the functional mechanisms that shape habituation in biological systems from an information-theoretic and thermodynamic perspective.

cond-mat.stat-mech↗

arXiv2012

A hybrid bio-organic interface for neuronal photo-activation

Interfacing artificial functional materials and living neuronal tissues is at the forefront of bio-nano-technology. Attempts have been so far based onto microscale processing of metals and inorganic semiconductors as electrodes or photoactive layers in biased devices. More recently, also nanomaterials properties have been investigated. In spite of extensive research however, the communication between biological tissues and artificial sensors is still a challenge. Constraints consist in the complexity of the fabrication processes (i.e. metal and semiconductor lithography), the mechanical properties (e.g. flexibility and mechanical invasiveness) and chemical influence (e.g. inflammatory reactions). In addition, electrodes have fixed geometries that limit the location in space of the stimulus and often electrical currents are detrimental for the overall system. To this respect organic soft matter offers a chance in terms of biological affinity and mechanical properties. In particular conjugated polymers have appealing optoelectronic features which could lead to a new generation of neuronal communication and photo-manipulation techniques. So far conjugated polymers have being only tested as coatings of electrodes for neuronal activity recording. Here we report an up-scale of their use: the successful interfacing of an organic semiconductor to a network of cultured primary neurons, through optical excitation. This allows to a new paradigm for the optical stimulation of neurons which could have important implications for the development of an artificial retina based on organic photodetectors.

cond-mat.soft↗