Biology subjects

Mohler, W.

Publications and source records attributed to Mohler, W..

4 recordsLinked to original sources

bioRxiv2026

Transient morphogenetic constraints organize self-assembling axon neighborhoods for robust yet flexible wiring

Nervous systems form wiring patterns that are reproducible across individuals. This reproducibility is thought to emerge from molecular encoding and developmental events, but their relative contributions remain unclear. We address this question in the C. elegans neuropil, where embryonic developmental dynamics and adult anatomy are resolved at single-cell resolution. We find that transient morphogenetic structures -- rosettes, corridor cells, pioneer axon scaffold -- restrict which axons make contact, shaping the neuropil into overlapping neighborhoods. This demonstrates how early events constrain wiring choices, but not whether they explain the resulting reproducibility. To explain, we use an agent-based model of stochastic innervation that recapitulates macro- and micro-level reproducibility, revealing a trade-off between physical constraint and molecular specificity that limits neighborhood size. Counterintuitively, less selective axons produce more reproducible wiring when constrained within neighborhoods. This trade-off lets nervous systems maximize reproducibility without having to molecularly encode every axon-contact, a strategy for robust yet flexible wiring.

neuroscience↗

bioRxiv2026

Experience-Dependent Gain Modulation Drives Thermosensory Responses in Behavior

Sensory neurons must extract behaviorally relevant features from dynamic environments while maintaining sensitivity across wide stimulus ranges. To understand how sensory encoding adapts to experience during behavior, we combine long-duration calcium imaging in freely moving C. elegans with a temperature-trajectory playback paradigm to determine how the thermosensory neuron AFD extracts behaviorally relevant sensory features during navigation. We observe that AFD functions as a leaky integrator of recently experienced temperature changes, accumulating thermal inputs over a rolling window of tens of seconds, resulting in calcium levels that represent recent temperature dynamics during runs. Importantly, we determine that AFD selectively amplifies responses to temperature changes near its learned preferred temperature. This experience-dependent gain control aligns encoding with the navigational goal, providing a mechanism for representing temperature preference within a derivative-based sensory system. A minimal mathematical model incorporating derivative detection, leaky integration, and temperature-dependent gain captures the calcium dynamics over a range of stimuli, and a simulation based on the mathematical model predicts goal-oriented locomotor strategies across stimulus regimes. Together, these findings show how gain control allows a derivative-based sensory code to represent an absolute goal and guide locomotory strategies during navigation. HighlightsO_LIAFD encodes recent temperature changes over behaviorally relevant timescales. C_LIO_LIAFD amplifies temperature-change responses within a learned temperature-centered gain window. C_LIO_LIGain control provides a mechanism for representing distance to temperature preference within the derivative-based sensory system. C_LIO_LIA mathematical model and simulation of derivative sensing, leaky integration, and gain control predicts AFD calcium responses and goal-oriented locomotory strategies across stimulus regimes. C_LI

neuroscience↗

bioRxiv2024

NeuroSCAN: Exploring Neurodevelopment via Spatiotemporal Collation of Anatomical Networks

Volume electron microscopy (vEM) datasets such as those generated for connectome studies allow nanoscale quantifications and comparisons of the cell biological features underpinning circuit architectures. Quantifying cell biological relationships in the connectome yields rich, multidimensional datasets that benefit from data science approaches, including dimensionality reduction and integrated graphical representations of neuronal relationships. We developed NeuroSC (also known as NeuroSCAN) an open source online platform that bridges sophisticated graph analytics from data science approaches with the underlying cell biological features in the connectome. We analyze a series of published C. elegans brain neuropils and demonstrate how these integrated representations of neuronal relationships facilitate comparisons across connectomes, catalyzing new insights into the structure-function relationships of the circuits and their changes during development. NeuroSC is designed for intuitive examination and comparisons across connectomes, enabling synthesis of knowledge from high-level abstractions of neuronal relationships derived from data science techniques to the detailed identification of the cell biological features underpinning these abstractions.

neuroscience↗

bioRxiv2020

Structural and developmental principles of neuropil assembly in C. elegans

Neuropil is a fundamental form of tissue organization within brains1. In neuropils, densely packed neurons synaptically interconnect into precise circuit architecture2,3, yet the structural and developmental principles governing nanoscale precision in bundled neuropil assembly remain largely unknown4-6. Here we use diffusion condensation, a coarse-graining clustering algorithm7, to identify nested circuit structures within the C. elegans cerebral neuropil (called the nerve ring). We determine that the nerve ring neuropil is organized into four tightly bundled strata composed of related behavioral circuits. We demonstrate that the stratified architecture of the neuropil is a geometrical representation of the functional segregation of sensory information and motor outputs, with specific sensory organs and muscle quadrants mapping onto particular neuropil strata. We identify groups of neurons with unique morphologies that integrate information across strata and that create a sophisticated honeycomb-shaped scaffold that encases the strata within the nerve ring. We resolve the developmental sequence leading to stratified neuropil organization through the integration of lineaging and cell tracking algorithms with high resolution light-sheet microscopy, and reveal principles of cell position, migration and hierarchical outgrowth that guide neuropil organization. Our results uncover conserved design principles underlying nerve ring neuropil architecture and function, and a pioneer neuron-based, temporal progression of outgrowth that guides the hierarchical development of the layered neuropil. Our findings provide a blueprint for using structural and developmental approaches to systematically understand neuropil organization within brains.

neuroscience↗