Biology subjects

Santana, G. M.

Publications and source records attributed to Santana, G. M..

6 recordsLinked to original sources

bioRxiv2026

A neural circuit for olfactory motion detection

Movement is a defining feature of dynamic environments and a key variable encoded by sensory systems. In vision, neural mechanisms that extract motion direction have been studied extensively across species, revealing circuits that compare signals across space and time. Odor plumes likewise carry motion information in their spatiotemporal structure, which walking fruit flies detect and exploit to improve navigation (Brudner et al., 2025; Kadakia et al., 2022), independent of wind sensing. However, how olfactory circuits compute odor motion remains unknown. Here we identify circuitry in the Drosophila antennal lobe that transforms bilateral odor inputs into direction-selective signals that are propagated to higher brain regions. These direction-selective signals were widespread across most measured olfactory channels, spanning pheromones, food odors, and aversive cues. Directional responses were elicited by odor traces with naturalistic temporal statistics and tuned to inter-antennal delays of {approx}40 ms. Connectomic, physiological, and behav-ioral analyses identified one GABAergic inhibitory neuron in the antennal lobe as a key mediator of direction selectivity. Measurements of dynamics in direction-selective neurons revealed ipsilateral excitation and delayed contralateral inhibition. In a minimal data-driven model, this mechanism was sufficient to generate the observed direction-selective responses. These results establish motion detection as a circuit-level olfactory computation and reveal how an early sensory circuit transforms spatiotemporal chemical signals into a neural representation of odor motion to guide navigation.

neuroscience↗

bioRxiv2025

Age-specific regulation of sociability by hypothalamic Agrp neurons

Social isolation enhances sociability, suggesting that social behavior is maintained through a homeostatic mechanism. Further, mammalian social needs shift dramatically from infancy through adolescence into adulthood, raising the question of whether the neural mechanisms governing this homeostatic regulation evolve across developmental stages. Here, we show that agouti-related peptide (Agrp) neurons, which regulate hunger in adults, are activated by social isolation from weaning through adolescence but not in adulthood. Importantly, the activity of these neurons is critical for social behavior during adolescence: inhibiting Agrp neurons reduced isolation-induced sociability in juveniles but not in adults, and Agrp neuron activation promoted sociability only in young mice. After isolation, reunion with siblings or other conspecifics, but not unfamiliar adult males, rapidly decreased neuronal activity in juveniles, an effect requiring intact olfaction. These findings identify Agrp neurons as a key component of the circuitry governing age-specific social homeostasis.

neuroscience↗

bioRxiv2025

Fly navigational responses to odor motion and gradient cues are tuned to plume statistics

Odor cues guide animals to food and mates. Different environmental conditions can create differently patterned odor plumes, making navigation more challenging. Prior work has shown that animals turn upwind when they detect odor and cast crosswind when they lose it. Animals with bilateral olfactory sensors can also detect directional odor cues, such as odor gradient and odor motion. It remains unknown how animals use these two directional odor cues to guide crosswind navigation in odor plumes with distinct statistics. Here, we investigate this problem theoretically and experimentally. We show that these directional odor cues provide complementary information for navigation in different plume environments. We numerically analyzed real plumes to show that odor gradient cues are more informative about crosswind directions in relatively smooth odor plumes, while odor motion cues are more informative in turbulent or complex plumes. Neural networks trained to optimize crosswind turning converge to distinctive network structures that are tuned to odor gradient cues in smooth plumes and to odor motion cues in complex plumes. These trained networks improve the performance of artificial agents navigating plume environments that match the training environment. By recording Drosophila fruit flies as they navigated different odor plume environments, we verified that flies show the same correspondence between informative cues and plume types. Fly turning in the crosswind direction is correlated with odor gradients in smooth plumes and with odor motion in complex plumes. Overall, these results demonstrate that these directional odor cues are complementary across environments, and that animals exploit this relationship. SignificanceMany animals use smell to find food and mates, often navigating complex odor plumes shaped by environmental conditions. While upwind movement upon odor detection is well established, less is known about how animals steer crosswind to stay in the plume. We show that directional odor cues--gradients and motion--guide crosswind navigation differently depending on plume structure. Gradients carry more information in smooth plumes, while motion dominates in turbulent ones. Neural network trained to optimize crosswind navigation reflect this distinction, developing gradient sensitivity in smooth environments and motion sensitivity in complex ones. Experimentally, fruit flies adjust their turning behavior to prioritize the most informative cue in each context. These findings likely generalize to other animals navigating similarly structured odor plumes.

animal behavior and cognition↗

bioRxiv2024

SqueakOut: Autoencoder-based segmentation of mouse ultrasonic vocalizations

Mice emit ultrasonic vocalizations (USVs) that are important for social communication. Despite great advancements in tools to detect USVs from audio files in the recent years, highly accurate segmentation of USVs from spectrograms (i.e., removing noise) remains a significant challenge. Here, we present a new dataset of 12,954 annotated spectrograms explicitly labeled for mouse USV segmentation. Leveraging this dataset, we developed SqueakOut, a lightweight (4.6M parameters) fully convolutional autoencoder that achieves high accuracy in supervised segmentation of USVs from spectrograms, with a Dice score of 90.22. SqueakOut combines a MobileNetV2 backbone with skip connections and transposed convolutions to precisely segment USVs. Using stochastic data augmentation techniques and a hybrid loss function, SqueakOut learns robust segmentation across varying recording conditions. We evaluate SqueakOuts performance, demonstrating substantial improvements over existing methods like VocalMat (63.82 Dice score). The accurate USV segmentations enabled by SqueakOut will facilitate novel methods for vocalization classification and more accurate analysis of mouse communication. To promote further research, we release the annotated 12,954 spectrogram USV segmentation dataset and the SqueakOut implementation publicly.

neuroscience↗

bioRxiv2021

Deficiency of the paternally inherited gene Magel2 alters the development of separation induced vocalization in mice

The behavior of offspring results from the combined expression of maternal and paternal genes. Genomic imprinting silences some genes in a parent-of-origin specific manner, a process that, among all animals, occurs only in mammals. How genomic imprinting affects the behavior of mammalian offspring, however, remains poorly understood. Here, we studied how the loss of the paternally inherited gene Magel2 in mouse pups affects the emission of separation-induced ultrasonic vocalizations (USV). Using quantitative analysis of more than one hundred thousand USVs, we characterized the rate of vocalizations as well as their spectral features from postnatal days 6 to 12 (P6-P12), a critical phase of mouse development during which pups fully depend on the mother for survival. Our analyses show that Magel2 deficient offspring emit separation-induced vocalizations at lower rates and with altered spectral features. We also show that dams display altered behavior towards their own Magel2 deficient offspring. In a test to compare the retrieval of two pups, dams retrieve wildtype control pups first and faster than Magel2 deficient offspring. These results suggest that the loss of Magel2 impairs the expression of separation-induced vocalization in pups as well as maternal behavior, both of which support the pups growth and development.

neuroscience↗

bioRxiv2020

ANALYSIS OF ULTRASONIC VOCALIZATIONS FROM MICE USING COMPUTER VISION AND MACHINE LEARNING

AO_SCPLOWBSTRACTC_SCPLOWMice emit ultrasonic vocalizations (USV) to transmit socially-relevant information. To detect and classify these USVs, here we describe the development of VocalMat. VocalMat is a software that uses image-processing and differential geometry approaches to detect USVs in audio files, eliminating the need for user-defined parameter tuning. VocalMat also uses computational vision and machine learning methods to classify USVs into distinct categories. In a dataset of >4,000 USVs emitted by mice, VocalMat detected more than >98% of the USVs and accurately classified {approx}86% of USVs when considering the most likely label out of 11 different USV types. We then used Diffusion Maps and Manifold Alignment to analyze the probability distribution of USV classification among different experimental groups, providing a robust method to quantify and qualify the vocal repertoire of mice. Thus, VocalMat allows accurate and highly quantitative analysis of USVs, opening the opportunity for detailed and high-throughput analysis of this behavior.

animal behavior and cognition↗