arXiv subjects

Yago Emanoel Ramos

Publications and source records attributed to Yago Emanoel Ramos.

3 recordsLinked to original sources

arXiv2026

Cortical information transfer reveals conserved hemispherical network dynamics across human handedness

Whether human motor and brain lateralization arises from fundamentally distinct neural architectures or emerges from conserved network dynamics remains a central question at the intersection of network science and neurobiology. Conventional measures of cortical activation often fail to resolve how directed information exchange adapts to manual preference during complex motor tasks. This ambiguity leaves it unclear whether left-handed individuals possess atypical neural organization or follow shared dynamical principles. Here, we combine Permutation Transfer Entropy (PTE) with network-based indices to map directed cortical signal flow using electroencephalography (EEG) during high-precision motor execution (handwriting) in both right- and left-handed individuals. We demonstrate that cortical communication is strictly scale-dependent regardless of handedness: ipsilateral dominance occurs primarily in general, network-wide interactions, whereas inter-hemispheric interactions maintain a contralateral profile. Crucially, left-handed individuals exhibit inter-hemispheric information dynamics that are functionally equivalent to right-handers when executing tasks with the same anatomical hand, refuting assumptions of mirrored or atypical lateralization. By demonstrating that human cortical lateralization relies on dynamical principles conserved across manual preferences, these findings suggest that functional asymmetries reflect adaptive optimizations governed by epigenetic or social flexibility, rather than fixed structural divergences.

q-bio.NC↗

arXiv2026

Multifractal human signals at the edge of life reveal a heart-brain anti-correlation

This study investigates the terminal breakdown of human neurophysiological function through the lens of non-linear dynamics by analyzing the multifractal spectrum. Using Multifractal Detrended Fluctuation Analysis (MF-DFA), we quantify the temporal evolution of complexity in synchronized electroencephalogram (EEG) and electrocardiogram (ECG) time series from patients in the terminal stage. Our results reveal a marked divergence in multifractal spectrum width: while neural activity exhibits a collapse of multifractality toward a more constrained state, cardiac signals undergo anomalous spectral broadening, indicating increased non-linear fluctuations and dynamical instability. A negative correlation between these spectral widths suggests effective functional decoupling and the emergence of anti-correlated dynamics between neural and cardiac systems. Rather than reflecting a uniform physiological decline, this divergence is consistent with a body-to-brain breakdown in which peripheral dysfunction progressively overwhelms central regulatory processes. In a broader context, the observed opposing trends resemble patterns reported in other body-driven adaptive processes, suggesting that inverse dynamics across coupled systems may emerge when constraints originate from peripheral rather than central mechanisms. Ultimately, the dying process appears to represent an extreme form of cross-system disintegration, marked by the collapse of the hierarchical coordination that normally sustains integrated physiological function.

q-bio.NC↗

arXiv2026

Emergent togetherness in collaborative dance improvisation: neural and motor synchronization reveal a coupling-decoupling paradox

Collective improvisation in dance provides a rich natural laboratory for studying emergent coordination in coupled neuro-motor systems. Here, we investigate how training shapes spontaneous synchronization patterns in both movement and brain signals during collaborative performance. Using a dual-recording protocol integrating 3D motion capture and hyperscanning EEG, participants engaged in free, interaction-driven, and rule-based improvisation before and after a program of generative dance, grounded in cellular-automata. Motor behavior was modeled through a time-resolved α-exponent derived from Movement Element Decomposition scaling between mean velocity and displacement, revealing fluctuations in energetic strategies and degrees of freedom. Synchronization events were quantified using Motif Synchronization (biomechanical data) and multilayer Time-Varying Graphs (neural data), enabling the detection of nontrivial lead-lag dependencies beyond zero-lag entrainment. Results indicate that training produced an intriguing dissociation: inter-brain synchronization increased, particularly within the frontal lobe, while interpersonal motor synchrony decreased. This opposite trend suggests that enhanced participatory sense-making fosters neural alignment while simultaneously expanding individual motor explorations, thereby reducing coupling in movement. Our findings position collaborative improvisation as a complex dynamical regime in which togetherness emerges not from identical motor outputs but from shared neural intentionality distributed across multilayer interaction networks, exemplifying the coupling-decoupling paradox, whereby increasing inter-brain synchrony supports the exploration of broader and mutually divergent motor trajectories. These results highlight the nonlinear nature of social coordination, offering new avenues for modeling creative joint action in human systems.

q-bio.NC↗