Marco Celotto

Decomposing the modulation of interactions between neuronal populations

The paper introduces MICs to analyze how modulators reshape interactions between neural populations using a bilinear perturbation framework, showing its effectiveness in simulations and real neural data.

nELAVL phosphorylation by CDKL5 regulates RNA metabolism and condensates communication to promote experience-dependent maturation of the visual cortex

This study identifies CDKL5-mediated phosphorylation of nELAVL as critical for regulating RNA metabolism and condensate communication, essential for visual cortex maturation.

Confirmation Bias through Selective Readout of Information Encoded in Human Parietal Cortex

The paper shows that brain activity in the parietal cortex encodes evidence consistently with prior choices, leading to confirmation bias in decision-making.

MINT: a toolbox for the analysis of multivariate neural information coding and transmission

MINT is a toolbox for analyzing multivariate neural information coding and transmission using information theory and dimensionality reduction, applied to simulated and real neural data.

Cortical astrocytes extend phasic norepinephrine signals and critically mediate learned behavior

The paper shows that cortical astrocytes mediate learned behavior by extending norepinephrine signals through calcium dynamics and ATP release, influencing neuronal encoding of task variables.

Sampling bias corrections for accurate neural measures of redundant, unique, and synergistic information

The paper develops bias correction methods for Partial Information Decomposition (PID) in neural data, improving estimates of synergy and redundancy in mouse brain regions.

Stimulus information guides the emergence of behavior related signals in primary somatosensory cortex during learning

This study shows that sensory information increases in primary somatosensory cortex during learning, while choice information emerges later and relies on population coding.

Measuring stimulus-related redundant and synergistic functional connectivity with single cell resolution in auditory cortex

The paper measures redundant and synergistic functional connectivity in mouse auditory cortex during a perceptual task, finding that connected neuron pairs show more redundancy and less synergy than unconnected pairs.

An information-theoretic quantification of the content of communication between brain regions

This paper introduces a new information-theoretic measure, FIT, to quantify feature-specific information transfer between brain regions using simulated and empirical neural data.

NIT: an open-source tool for information theoretic analysis of neural population data

NIT is an open-source toolbox for information-theoretic analysis of neural data, including calcium imaging, offering tools for encoding quantification, information transmission, and partial information decompositions.