Biology subjects

Johnson, R. E.

Publications and source records attributed to Johnson, R. E..

6 recordsLinked to original sources

bioRxiv2026

Whole-body 3D kinematics of freely behaving Drosophila

Understanding how nervous systems generate coordinated movement requires precise measurement of body kinematics during natural behavior. The fruit fly, Drosophila, is a model organism with sophisticated behavior and well-studied neural circuits, but tracking fly movements in 3D remains challenging because of their teeny bodies, rapid movements, and frequent self-occlusions. Here we present a pipeline for markerless, full-body 3D pose estimation of fly terrestrial behavior, combining seven synchronized high-speed cameras to capture whole-body kinematics at 800 frames per second. We trained a hybrid 2D/3D deep learning model to track 50 keypoints, then refined them to produce anatomically feasible kinematic trajectories through a retargeting process that solved an inverse kinematics problem constrained by a biomechanical body model. Analysis of 3D kinematics revealed that flies perform grounded running across their full speed range, without transitioning between discrete gaits. Using multi-animal tracking, we found that courting males coordinate both wings during song and modulate body pitch to track the female's vertical position. Our open-source pipeline and large 3D kinematic dataset of fly behavior provide a foundation for neuromechanical modeling and mechanistic studies of motor control in a genetically tractable model organism.

neuroscience↗

bioRxiv2025

The human Flower isoform hFWE4 facilitates cornification in cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the second most common human tumor and arises from keratinocytes that comprise the epidermis and its associated hair follicles. Remarkably, transformed keratinocytes within a cSCC retain some ability to execute the terminal differentiation program that typically generates a stratified epidermis. Instead of the polarized stratification towards the body surface seen in normal epidermis, cSCC keratinocytes differentiate concentrically inward to produce keratin pearls. It is well appreciated that cSCC differentiation status is correlated with degree of local invasion and potential for distant metastasis, with well differentiated tumors having a better prognosis. While molecular mechanisms that govern the differentiation process are incompletely understood, identifying candidate molecules associated with cSCC differentiation can provide new histologic markers for prognostic stratification. Here we demonstrate that Flower (FWE), a newly described regulator of lamellar body (LB) trafficking in normal epidermis, is specifically expressed within highly differentiated layers of cSCC. Genetic knockout of the hFWE gene dysregulates cornification and LB-related gene expression leading to abnormal keratinization patterns, while ectopic hFWE4 expression drives G1-arrest and exit from the proliferative basal keratinocyte population. Additionally, we find that poorly differentiated keratinocyte regions of human cSCC exhibit minimal FWE-positivity, while this population is readily detectable in well-differentiated regions. We propose that FWE represents a novel differentiation marker in cSCC that could be utilized for classifying differentiation status and prognostic stratifying these tumors.

cancer biology↗

bioRxiv2020

Artificial Joint Speed Feedback for Myoelectric Prosthesis Control

I.Accurate control of human limbs involves both feedforward and feedback signals. For prosthetic arms, feedforward control is commonly accomplished by recording myoelectric signals from the residual limb to predict the users intent, but augmented feedback signals are not explicitly provided in commercial devices. Previous studies have demonstrated inconsistent results when artificial feedback was provided in the presence of vision. We hypothesized that negligible benefits in past studies may have been due to artificial feedback with low precision compared to vision, which results in heavy reliance on vision during reaching tasks. Furthermore, we anticipated more reliable benefits from artificial feedback when providing information that vision estimates with high uncertainty - joint speed. In this study, we test an artificial sensory feedback system providing joint speed information and how it impacts performance and adaptation during a hybrid positional-and-myoelectric ballistic reaching task. We found modest improvement in overall reaching errors after perturbed control, and that high prosthesis control noise was compensated for by strategic overreaching with the positional control and underreaching with the myoelectric control. These results provide insights into the relevant factors influencing the improvements conferred by artificial sensory feedback.

neuroscience↗

bioRxiv2019

Probabilistic Models of Larval Zebrafish Behavior: Structure on Many Scales

Nervous systems have evolved to combine environmental information with internal state to select and generate adaptive behavioral sequences. To better understand these computations and their implementation in neural circuits, natural behavior must be carefully measured and quantified. Here, we collect high spatial resolution video of single zebrafish larvae swimming in a naturalistic environment and develop models of their action selection across exploration and hunting. Zebrafish larvae swim in punctuated bouts separated by longer periods of rest called interbout intervals. We take advantage of this structure by categorizing bouts into discrete types and representing their behavior as labeled sequences of bout-types emitted over time. We then construct probabilistic models - specifically, marked renewal processes - to evaluate how bout-types and interbout intervals are selected by the fish as a function of its internal hunger state, behavioral history, and the locations and properties of nearby prey. Finally, we evaluate the models by their predictive likelihood and their ability to generate realistic trajectories of virtual fish swimming through simulated environments. Our simulations capture multiple timescales of structure in larval zebrafish behavior and expose many ways in which hunger state influences their action selection to promote food seeking during hunger and safety during satiety.

animal behavior and cognition↗

bioRxiv2019

A bidirectional network for appetite control in zebrafish

Medial and lateral hypothalamic loci are known to suppress and enhance appetite, respectively, but the dynamics and functional significance of their interaction have yet to be explored. Here we report that, in larval zebrafish, primarily serotonergic neurons of the ventromedial caudal hypothalamus (cH) become increasingly active during food deprivation, whereas activity in the lateral hypothalamus (LH) is reduced. Exposure to food sensory and consummatory cues reverses the activity patterns of these two nuclei, consistent with their representation of opposing internal hunger states. Baseline activity is restored as food-deprived animals return to satiety via voracious feeding. The antagonistic relationship and functional importance of cH and LH activity patterns were confirmed by targeted stimulation and ablation of cH neurons. Collectively, the data allow us to propose a model in which these hypothalamic nuclei regulate different phases of hunger and satiety and coordinate energy balance via antagonistic control of distinct behavioral outputs.

neuroscience↗

bioRxiv2018

Joint Speed Discrimination and Augmentation For Prosthesis Feedback

Sensory feedback is critical in fine motor control, learning, and adaptation. However, robotic prosthetic limbs currently lack the feedback segment of the communication loop between user and device. Artificial sensory feedback can close this gap, but sometimes this improvement only persists when users cannot see their prosthesis. suggesting the provided feedback is redundant with vision. Thus, given the choice, users rely on vision over artificial feedback. To effectively augment vision, sensory feedback must provide information that vision cannot provide or provides poorly. Although vision is known to be less precise at estimating speed than position, no work has compared speed precision of biomimetic arm movements. In this study, we investigated the uncertainty of visual speed estimates as defined by different virtual arm movements. We found that uncertainty was greatest for visual estimates of joint speeds, compared to absolute or linear endpoint speeds. Furthermore, this uncertainty increased when the joint reference frame speed varied over time, potentially caused by an overestimation of joint speed. Finally, we demonstrate a joint-based sensory feedback paradigm capable of significantly reducing joint speed uncertainty when paired with vision. Ultimately, this work may lead to improved prosthesis control and capacity for motor learning.

neuroscience↗