arXiv subjects

Daniel M. Castro

Publications and source records attributed to Daniel M. Castro.

5 recordsLinked to original sources

arXiv2026

Hierarchical organization of critical brain dynamics

The hierarchical organization of the brain is a fundamental structural principle, while brain criticality is a leading hypothesis for its collective dynamics. However, the connection between structure and signatures of criticality remains an open question. Here, we address this issue by applying phenomenological renormalization group approaches to large-scale neuronal spiking activity from the mouse visual cortex and hippocampus. We find that signatures of criticality are not uniform, but instead vary systematically along the known anatomical hierarchy in both brain systems. Strikingly, the direction along this gradient is inconsistent across different criticality exponents, revealing a nontrivial, measure-dependent organization: exponents based on static properties point to a gradient in one direction, while the exponent based on dynamic properties points in the opposite direction. Moreover, the signatures across the visual system are strongly modulated by the engagement in a visual task. We show that the correlations among criticality markers of different brain regions during active engagement are sufficient to reconstruct the anatomical hierarchy from the dynamics. Scaling exponents closely follow a theoretically predicted scaling relation among them, and covary with the hierarchical position. Our findings provide a direct link between the collective dynamics of neurons and the macroscopic architecture of the brain.

q-bio.NC↗

arXiv2025

Phenomenological renormalization group in neuronal models near criticality

The phenomenological renormalization group (PRG) has been applied to the study of scaleinvariant phenomena in neuronal data, providing evidence for critical phenomena in the brain. However, it remains unclear how reliably these observed signatures indicate genuine critical behavior, as it is not well established how close to criticality a system must be for them to emerge. Here, we rely on neuronal models with known critical points to investigate under which conditions the PRG procedure yields consistent results. We show that the PRG method detects scaling behavior in neuronal models only within a narrow vicinity of the critical point, reinforcing the interpretations drawn from PRG results in experimental data. We also demonstrate that time-binning choices can substantially affect the results and introduce a data-driven adaptive binning procedure to circumvent this issue.

cond-mat.dis-nn↗

arXiv2024

Interdependent scaling exponents in the human brain

We apply the phenomenological renormalization group to resting-state fMRI time series of brain activity in a large population. By recursively coarse-graining the data, we compute scaling exponents for the series variance, log probability of silence, and largest covariance eigenvalue. The exponents clearly exhibit linear interdependencies, which we derive analytically in a mean-field approach. We find a significant correlation of exponent values with the gray matter volume and cognitive performance. Akin to scaling relations near critical points in thermodynamics, our findings suggest scaling interdependencies are intrinsic to brain organization and may also exist in other complex systems.

cond-mat.dis-nn↗

arXiv2024

Criticality at work: scaling in the mouse cortex enhances performance

The critical brain hypothesis posits that neural systems operate near a phase transition, optimizing the processing of information. While scale invariance and non-Gaussian dynamics--hallmarks of criticality--have been observed in brain activity, a direct link between criticality and behavioral performance remains unexplored. Here, we use a phenomenological renormalization group approach to examine neuronal activity in the primary visual cortex of mice performing a visual recognition task. We show that nontrivial scaling in neuronal activity is associated with enhanced task performance, with pronounced scaling observed during successful task completion. When rewards were removed or non-natural stimuli presented, scaling signatures diminished. These results suggest that critical dynamics in the brain is crucial for optimizing behavioral outcomes, offering new insights into the functional role of criticality in cortical processing.

q-bio.NC↗

arXiv2021

Feedforward and feedback influences through distinct frequency bands between two spiking-neuron networks

Several studies with brain signals suggested that bottom-up and top-down influences are exerted through distinct frequency bands among visual cortical areas. It has been recently shown that theta and gamma rhythms subserve feedforward, whereas the feedback influence is dominated by the alpha-beta rhythm in primates. A few theoretical models for reproducing these effects have been proposed so far. Here we show that a simple but biophysically plausible two-network motif composed of spiking-neuron models and chemical synapses can exhibit feedforward and feedback influences through distinct frequency bands. Differently from previous studies, this kind of model allows us to study directed influences not only at the population level, by using a proxy for the local field potential, but also at the cellular level, by using the neuronal spiking series.

q-bio.NC↗