Biology subjects

Shaevitz, J. W.

Publications and source records attributed to Shaevitz, J. W..

5 recordsLinked to original sources

bioRxiv2018

Predicting natural behavior from whole-brain neural dynamics

The activity of an animals brain contains information about that animals actions and movements. We investigated the neural representation of locomotion in the nematode C. elegans by recording population calcium activity during unrestrained movement. We report that a neural population more accurately decodes locomotion than any single neuron. Relevant signals are distributed across neurons with diverse tunings to locomotion. Two distinct subpopulations are informative for decoding velocity and body curvature, and different neurons activities contribute features relevant for different instances of behavioral motifs. We labeled neurons AVAL and AVAR and found their activity was highly correlated with one another. They exhibited expected transients during backward locomotion, although they were not always the most informative neurons for decoding velocity. Finally, we compared population neural activity during movement and immobilization. Immobilization alters the correlation structure of neural activity and its dynamics. Some neurons previously correlated with AVA become anti-correlated and vice versa. The activity of an animals brain contains information about that animals actions and movements. We investigated the neural representation of locomotion in the nematode C. elegans by recording brain-wide neural dynamics in freely moving animals. We report that a population of neurons more accurately decodes the animals locomotion than any single neuron. Neural signals are distributed across neurons in the population with a diversity of tuning to locomotion. Two distinct subpopulations are most informative for decoding velocity and body curvature, and different neurons activities contribute features relevant for different instances of behavioral motifs within these subpopulations. We additionally labeled the AVA neurons within our population recordings. AVAL and AVAR exhibit activity that is highly correlated with one another, and they exhibit the expected responses to locomotion, although we find that AVA is not always the most informative neuron for decoding velocity. Finally, we compared brain-wide neural activity during movement and immobilization and observe that immobilization alters the correlation structure of neural activity and its dynamics. Some neurons that were previously correlated with AVA become anti-correlated and vice versa during immobilization. We conclude that neural population codes are important for understanding neural dynamics of behavior in moving animals.

neuroscience↗

bioRxiv2018

Fast animal pose estimation using deep neural networks

Recent work quantifying postural dynamics has attempted to define the repertoire of behaviors performed by an animal. However, a major drawback to these techniques has been their reliance on dimensionality reduction of images which destroys information about which parts of the body are used in each behavior. To address this issue, we introduce a deep learning-based method for pose estimation, LEAP (LEAP Estimates Animal Pose). LEAP automatically predicts the positions of animal body parts using a deep convolutional neural network with as little as 10 frames of labeled data for training. This framework consists of a graphical interface for interactive labeling of body parts and software for training the network and fast prediction on new data (1 hr to train, 185 Hz predictions). We validate LEAP using videos of freely behaving fruit flies (Drosophila melanogaster) and track 32 distinct points on the body to fully describe the pose of the head, body, wings, and legs with an error rate of <3% of the animals body length. We recapitulate a number of reported findings on insect gait dynamics and show LEAPs applicability as the first step in unsupervised behavioral classification. Finally, we extend the method to more challenging imaging situations (pairs of flies moving on a mesh-like background) and movies from freely moving mice (Mus musculus) where we track the full conformation of the head, body, and limbs.

animal behavior and cognition↗

bioRxiv2017

Optogenetic dissection of descending behavioral control in Drosophila

In most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how these neurons control an insects movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrial D. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies and associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a population of descending neurons, we found, that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically-activated behaviors were often dependent on the behavioral state prior to activation.

neuroscience↗

bioRxiv2017

RodZ promotes MreB polymer formation and curvature localization to determine the cylindrical uniformity of E. coli shape

Cell shape in bacteria is determined by the cell wall, which is synthesized by a variety of proteins whose actions are coordinated by the actin-like MreB protein. MreB uses local geometric cues of envelope curvature to avoid the cell poles and localize to specific regions of the cell body. However, it remains unclear whether MreBs curvature preference is regulated by additional factors, and which features of MreB are essential for specific aspects of rod shape growth, such as cylindrical uniformity. Here we show that in addition to its previously-described role in mediating MreB motion, RodZ also modulates MreB polymer number and curvature preference. MreB polymer number and curvature localization can be regulated independently. Quantitative 3D measurements and a series of mutant strains show that among various properties of MreB, polymer number, total length of MreB polymers, and MreB curvature preference are the key determinants of cylindrical uniformity, a measure of the variability in radius within a single cell. Changes in the values of these parameters are highly predictive of the resulting changes in cell shape (r2=0.93). Our data suggest a model for rod shape in which RodZ promotes the assembly of multiple long MreB polymers that ensure the growth of a uniform cylinder.

microbiology↗

bioRxiv2017

A Tunable Protein Oscillator Controls Directional Movements In Myxococcus xanthus

Dynamic control of cell polarity is of critical importance for many aspects of cellular development and motility. In Myxococcus xanthus, a G-protein and its cognate GTPase-activating protein establish a polarity axis that defines the direction of movement of the cell and which can be rapidly inverted by the Frz chemosensory system. Although vital for collective cell behaviours, how Frz triggers this switch has remained unknown. Here, we use genetics, imaging and mathematical modelling to show that Frz controls polarity reversals via a gated relaxation oscillator. FrzX, which we newly identify as the primary Frz output, provides the gating and thus acts as the trigger for reversals. Slow relocalisation of the polarity protein RomR then creates a refractory period during which another switch cannot be triggered. A secondary Frz output, FrzZ, decreases this delay allowing rapid reversals when required. This architecture thus results in a highly tunable switch that allows a wide range of motility responses.

microbiology↗