Biology subjects

Ferrari, P. F.

Publications and source records attributed to Ferrari, P. F..

4 recordsLinked to original sources

bioRxiv2026

Number-Space Association in Macaques

Humans order numbers in space from left to right, with smaller quantities represented preferentially in the left hemispace and larger ones in the right hemispace. The direction of this mental number line (MNL), or more generally of number-space associations (NSA), is influenced by cultural habits such as reading and writing direction. However, a growing body of evidence from pre-verbal infants and non-human animals suggests that number-space mappings may also have biological foundations. In non-human primates, evidence for a directional MNL remains mixed, partly due to small sample sizes and methodological heterogeneity. Here, we tested samples of rhesus (Macaca mulatta) and crab-eating macaques (Macaca fascicularis) across two experiments using spontaneous food-related tasks. In Experiment 1, monkeys chose between identical food quantities (1x1 to 24x24) presented on the left and right. No systematic spatial choice bias emerged as a function of numerical magnitude, and hand use did not differ across exact numerical pairs, although exploratory analyses revealed magnitude-related modulations of manual responses. In Experiment 2, monkeys were habituated to small (4x4) or large (16x16) quantities and subsequently tested with the alternative quantity. Result showed significantly more leftward choices following numerical decreases (16[->]4) and more rightward choices following numerical increases (4[->]16), indicating that relative numerical context, rather than absolute magnitude, elicited directional spatial biases. These findings suggest that in macaques, number-space associations emerge most robustly in comparative contexts involving expectancy violations of magnitude.

animal behavior and cognition↗

bioRxiv2025

Frontal cortex encodes action goals and social context in freely moving and socially interacting macaques

Classic studies of goal-directed behavior in primates have investigated frontal cortical circuits under restraint conditions, leaving their role in natural social contexts largely unknown. We wirelessly recorded neural activity from freely moving macaques to study how frontal areas encode actions during naturalistic interactions. Neurons in ventral premotor and ventrolateral prefrontal cortex distinguished identical motor acts, such as grasping, depending on whether they occurred during foraging or grooming, indicating sensitivity to social meaning. Some units were selectively tuned to socially directed goals, while population analyses showed both regions flexibly integrated motor plans with social context. These results provide direct evidence that these regions, long considered key motor hubs, also encode the social dimension of action, redefining current models of frontal lobe function. One-Sentence SummaryFreely-moving, social-interacting macaques reveal new properties of frontal circuits in encoding motor goals and social context.

neuroscience↗

bioRxiv2023

Bursting with potential: How sensorimotor beta bursts develop from infancy to adulthood

Beta activity is thought to play a critical role in sensorimotor processes. However, little is known about how activity in this frequency band develops. Here, we investigated the developmental trajectory of sensorimotor beta activity from infancy to adulthood. We recorded electroencephalography (EEG) from adults, 12-month-olds, and 9-month-olds while they observed and executed grasping movements. We analysed beta burst activity using a novel method that combines time-frequency decomposition and principal component analysis (PCA). We then examined the changes in burst rate and waveform motifs along the selected principal components. Our results reveal systematic changes in beta activity during action execution across development. We found a decrease in beta burst rate during movement execution in all age groups, with the greatest decrease observed in adults. Additionally, we identified four principal components that defined waveform motifs that systematically changed throughout the trial. We found that bursts with waveform shapes closer to the median waveform were not rate-modulated, whereas those with waveform shapes further from the median were differentially rate-modulated. Interestingly, the decrease in the rate of certain burst motifs occurred earlier during movement and was more lateralized in adults than in infants, suggesting that the rate modulation of specific types of beta bursts becomes increasingly refined with age.

neuroscience↗

bioRxiv2022

Bayesian multilevel hidden Markov models identify stable state dynamics in longitudinal recordings from macaque primary motor cortex

Neural populations, rather than single neurons, may be the fundamental unit of cortical computation. Analyzing chronically recorded neural population activity is challenging not only because of the high dimensionality of activity in many neurons, but also because of changes in the recorded signal that may or may not be due to neural plasticity. Hidden Markov models (HMMs) are a promising technique for analyzing such data in terms of discrete, latent states, but previous approaches have either not considered the statistical properties of neural spiking data, have not been adaptable to longitudinal data, or have not modeled condition specific differences. We present a multilevel Bayesian HMM which addresses these shortcomings by incorporating multivariate Poisson log-normal emission probability distributions, multilevel parameter estimation, and trial-specific condition covariates. We applied this framework to multi-unit neural spiking data recorded using chronically implanted multi-electrode arrays from macaque primary motor cortex during a cued reaching, grasping, and placing task. We show that the model identifies latent neural population states which are tightly linked to behavioral events, despite the model being trained without any information about event timing. We show that these events represent specific spatiotemporal patterns of neural population activity and that their relationship to behavior is consistent over days of recording. The utility and stability of this approach is demonstrated using a previously learned task, but this multilevel Bayesian HMM framework would be especially suited for future studies of long-term plasticity in neural populations.

neuroscience↗