Biology subjects

Pedraja, F.

Publications and source records attributed to Pedraja, F..

5 recordsLinked to original sources

bioRxiv2023

Collective Sensing in Electric Fish

A number of organisms, including dolphins, bats, and electric fish, possess sophisticated active sensory systems that use self-generated signals (e.g. acoustic or electrical emissions) to probe the environment1,2. Studies of active sensing in social groups have typically focused on strategies for minimizing interference from conspecific emissions2-4. However, it is well-known from engineering that multiple spatially distributed emitters and receivers can greatly enhance environmental sensing (e.g. multistatic radar and sonar)5-8. Here we provide evidence from modeling, neural recordings, and behavioral experiments that the African weakly electric fish Gnathonemus petersii utilizes the electrical pulses of conspecifics to extend electrolocation range, discriminate objects, and increase information transmission. These results suggest a novel, collective mode of active sensing in which individual perception is enhanced by the energy emissions of nearby group members.

neuroscience↗

bioRxiv2023

Ultra-high density electrodes improve detection, yield, and cell type specificity of brain recordings

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device samples neuronal activity at ultra-high spatial density ([~]10 times higher than previous probes) with low noise levels, while trading off recording span. NP Ultra is effectively an implantable voltage-sensing camera that captures a planar image of a neurons electrical field. We use a spike sorting algorithm optimized for these probes to demonstrate that the yield of visually-responsive neurons in recordings from mouse visual cortex improves up to [~]3-fold. We show that NP Ultra can record from small neuronal structures including axons and dendrites. Recordings across multiple brain regions and four species revealed a subset of extracellular action potentials with unexpectedly small spatial spread and axon-like features. We share a large-scale dataset of these brain-wide recordings in mice as a resource for studies of neuronal biophysics. Finally, using ground-truth identification of three major inhibitory cortical cell types, we found that these cell types were discriminable with approximately 75% success, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, detection of subcellular compartments, and cell type classification to enable more powerful dissection of neural circuit activity during behavior.

neuroscience↗

bioRxiv2023

Detection and localization of conspecifics in ghost knifefish are influenced by the relationship between the spatial organization of receptors and signals.

The detection and localization of signals rely on arrays of receptors, and their spatial organization plays a key role in determining the accuracy of the system. Weakly electric ghost knifefish rely on a distributed array of electroreceptors to detect spatially diffuse electric signals from conspecifics. While we know that spatial resolution for small objects, such as prey, is enhanced near the head due to a high receptor density, it is not clear how receptor organization influences the processing of global and diffuse signals from conspecifics. Using spatially realistic modeling, we quantified how receptor density influences detection and localization accuracy for conspecific signals across varying distances. Our main result demonstrates that receptor density markedly enhances detection accuracy in frontal regions at intermediate distances (35-50 cm) yet surprisingly contributes minimally to improving localization accuracy. This highlights a fundamental principle: receptor convergence primarily benefits signal detection when dealing with spatially diffuse stimuli, even though higher receptor density can enhance localization accuracy for spatially delineated signals. Our findings extend beyond the electrosensory modality, drawing parallels with other sensory systems, and offer broader insights into spatial processing principles.

neuroscience↗

bioRxiv2023

Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools

Contemporary pose estimation methods enable precise measurements of behavior via supervised deep learning with hand-labeled video frames. Although effective in many cases, the supervised approach requires extensive labeling and often produces outputs that are unreliable for downstream analyses. Here, we introduce "Lightning Pose," an efficient pose estimation package with three algorithmic contributions. First, in addition to training on a few labeled video frames, we use many unlabeled videos and penalize the network whenever its predictions violate motion continuity, multiple-view geometry, and posture plausibility (semi-supervised learning). Second, we introduce a network architecture that resolves occlusions by predicting pose on any given frame using surrounding unlabeled frames. Third, we refine the pose predictions post-hoc by combining ensembling and Kalman smoothing. Together, these components render pose trajectories more accurate and scientifically usable. We release a cloud application that allows users to label data, train networks, and predict new videos directly from the browser.

neuroscience↗

bioRxiv2022

Why the brown ghost chirps at night

Since the pioneering work by Moeller, Szabo, and Bullock, weakly electric fish have served as a valuable model for investigating spatial and social cognitive abilities in a vertebrate taxon usually less accessible than mammals or other terrestrial vertebrates. These fish, through their electric organ, generate low-intensity electric fields to navigate and interact with conspecifics, even in complete darkness. The brown ghost knifefish is appealing as a study subject due to a rich electric "vocabulary", made by individually variable and sex-specific electric signals. These are mainly characterized by brief frequency modulations of the oscillating dipole moment continuously generated by their electric organ, and are known as chirps. Different types of chirps are believed to convey specific and behaviorally salient information, serving as behavioral readouts for different internal states during behavioral observations. Despite the success of this model in neuroethology over the past seven decades, the code to decipher their electric communication remains unknown. To this aim, in this study we re-evaluate the correlations between signals and behavior offering an alternative, and possibly complementary, explanation for why these freshwater bottom dwellers emit electric chirps. By uncovering correlations among chirping, electric field geometry, and detectability in enriched environments, we present evidence for a previously unexplored role of chirps as specialized self-directed signals, enhancing conspecific electrolocation during social encounters.

animal behavior and cognition↗