Biology subjects

Ahamed, T.

Publications and source records attributed to Ahamed, T..

6 recordsLinked to original sources

bioRxiv2023

A Markovian dynamics for C. elegans behavior across scales

How do we capture the breadth of behavior in animal movement, from rapid body twitches to aging? Using high-resolution videos of the nematode worm C. elegans, we show that a single dynamics connects posture-scale fluctuations with trajectory diffusion, and longer-lived behavioral states. We take short posture sequences as an instantaneous behavioral measure, fixing the sequence length for maximal prediction. Within the space of posture sequences we construct a fine-scale, maximum entropy partition so that transitions among microstates define a high-fidelity Markov model, which we also use as a means of principled coarse-graining. We translate these dynamics into movement using resistive force theory, capturing the statistical properties of foraging trajectories. Predictive across scales, we leverage the longest-lived eigenvectors of the inferred Markov chain to perform a top-down subdivision of the worms foraging behavior, revealing both "runs-and-pirouettes" as well as previously uncharacterized finer-scale behaviors. We use our model to investigate the relevance of these fine-scale behaviors for foraging success, recovering a trade-off between local and global search strategies. SIGNIFICANCE STATEMENTComplex phenotypes, such as an animals behavior, generally depend on an overwhelming number of processes that span a vast range of scales. While there is no reason that behavioral dynamics permit simple models, by subsuming inherent nonlinearities and memory into maximally-predictive microstates, we find one for C. elegans foraging. The resulting "Markov worm" is effectively indistinguishable from real worm motion across a range of timescales, and we can decompose our model dynamics both to recover and discover behavioral states. Employing a simple form of substrate interactions, we connect postures to trajectories, illuminating how worms explore the environment. In more complex organisms, our approach can also link behaviors across time, from rapid muscular control to neuromodulation.

animal behavior and cognition↗

bioRxiv2022

A descending interneuron with depolarized resting membrane potential controls C. elegans motor states

Continuity of behaviors requires animals to make smooth transitions between successive and mutually exclusive behavioral states. Neural principles that govern these transitions are not well understood. C. elegans spontaneously switch between two opposite motor states, forward and backward movement, a phenomenon long thought to reflect the reciprocal inhibition between two interneurons that separately gate the forward and backward motor circuits, AVB and AVA. Combining experimental data and mathematical modeling, we report that spontaneous forward and backward locomotion and their corresponding motor circuits are not separately controlled. AVA and AVB are neither functionally equivalent nor strictly reciprocally inhibitory. Instead, while AVA phasically inhibits the forward promoting interneuron AVB at a fast timescale, it maintains a tonic, extrasynaptic excitation on AVB over the longer timescale. AVAs depolarized spontaneous membrane potential is necessary for this tonic excitation. We propose a new, master neuron model for locomotion. AVA, with tonic and phasic activity of opposite polarities on different time scales, acts as a master neuron to break the symmetry between the underlying forward and backward motor circuits. This offers a parsimonious solution for sustained locomotion consisted of mutually exclusive motor states. TeaserA tonically active C. elegans premotor interneuron functions as the master neuron that underlies continuous modulation of forward and backward movement to ensure smooth transitions between the two opposing motor states.

neuroscience↗

bioRxiv2022

Post-embryonic maturation of the C. elegans motor circuit

During development, animals can maintain behavioral output even as the underlying circuits structurally remodel. After hatching, C. elegans undergoes substantial motor neuron expansion and synapse re-wiring while the animal continuously moves with an undulatory pattern. To understand how the circuit transitions from its juvenile to mature configuration without disrupting functional output, we reconstructed the C. elegans motor circuit by electron microscopy across larval development. We observed: 1) Embryonic motor neurons transiently interact with the developing post-embryonic motor neurons prior to remodeling of their juvenile wiring; 2) Post-embryonic neurons initiate synapse development with their future partners as their neurites navigate through the juvenile nerve cords; 3) Embryonic and post-embryonic neurons sequentially build structural machinery needed for the adult circuit before the embryonic neurons relinquish their roles to post-embryonic neurons; 4) This transition is repeated region by region along the body in an anterior to posterior sequence, following the birth order of post-embryonic neurons. Through this orchestrated, programmed and gradual rewiring, the motor circuit transforms from asymmetric to symmetric wiring. These maturation strategies support the continuous maintenance of motor patterns as the juvenile circuit develops into the adult configuration. HighlightsO_LIPost-embryonic motor circuit maturation was reconstructed by synapse-resolution serial EM. C_LIO_LIMotor patterns are maintained as the circuit matures from asymmetric to symmetric configuration. C_LIO_LIProgrammed rewiring gradually and sequentially transforms the circuit structure. C_LIO_LIPreparatory and communicative wiring-rewiring allows maturation without functional disruption. C_LI

neuroscience↗

bioRxiv2021

Extrasynaptic signaling enables an asymmetric juvenile motor circuit to produce a symmetric mature gait.

In many animals, there is a direct correspondence between the motor patterns that drive locomotion and the motor neuron innervation onto the muscle groups. For example, the adult C. elegans moves with symmetric and alternating dorsal-ventral bending waves arising from symmetric motor neuron input onto the dorsal and ventral muscles. In contrast to the adult, the C. elegans motor circuit at the juvenile larval stage has asymmetric wiring between motor neurons and muscles, but still generates adult-like bending waves with dorsal-ventral symmetry. We show that in the juvenile circuit, wiring between excitatory and inhibitory motor neurons coordinates the contraction of dorsal muscles with relaxation of ventral muscles, producing dorsal bends. However, ventral bending is not driven by analogous wiring. Instead, ventral muscles are excited uniformly by premotor interneurons through extrasynaptic signaling. Ventral bends occur in anti-phasic entrainment to activity of the same motor neurons that drive dorsal bends. During maturation, the juvenile motor circuit is replaced by two motor subcircuits that separately drive dorsal and ventral bending. Modeling reveals that the juveniles immature motor circuit is an adequate solution to generate adult-like dorsal-ventral bending before the animal matures. Developmental rewiring between functionally degenerate circuit solutions, that both generate symmetric bending patterns, minimizes behavioral disruption across maturation. HighlightsO_LIC. elegans larvae generate symmetric motor pattern with an asymmetrically wired motor circuit. C_LIO_LISynaptic wiring between excitatory and inhibitory motor neurons drives dorsal bending. C_LIO_LIExtrasynaptic excitation by premotor interneurons entrains ventral muscles for anti-phasic ventral bending. C_LIO_LIA developmental strategy to enable mature motor pattern before the circuit structurally matures. C_LI

neuroscience↗

bioRxiv2021

Maximally predictive ensemble dynamics from data

We leverage the interplay between microscopic variability and macroscopic order to connect physical descriptions across scales directly from data, without underlying equations. We reconstruct a state space by concatenating measurements in time, building a maximum entropy partition of the resulting sequences, and choosing the sequence length to maximize predictive information. Trading non-linear trajectories for linear, ensemble evolution, we analyze reconstructed dynamics through transfer operators. The evolution is parameterized by a transition time{tau} : capturing the source entropy rate at small{tau} and revealing timescale separation with collective, coherent states through the operator spectrum at larger{tau} . Applicable to both deterministic and stochastic systems, we illustrate our approach through the Langevin dynamics of a particle in a double-well potential and the Lorenz system. Applied to the behavior of the nematode worm C. elegans, we derive a "run-and-pirouette" navigation strategy directly from posture dynamics. We demonstrate how sequences simulated from the ensemble evolution capture both fine scale posture dynamics and large scale effective diffusion in the worms centroid trajectories and introduce a top-down, operator-based clustering which reveals subtle subdivisions of the "run" behavior. POPULAR SUMMARYComplex structure is often composed from a limited set of relatively simple building blocks; such as novels from letters or proteins from amino acids. In musical composition, e.g., sounds and silences combine to form longer time scale structures; motifs form passages which in turn form movements. The challenge we address is how to identify collective variables which distinguish structures across such disparate time scales. We introduce a principled framework for learning effective descriptions directly from observations. Just as a musical piece transitions from one movement to the next, the collective dynamics we infer consists of transitions between macroscopic states, like jumps between metastable states in an effective potential landscape. The statistics of these transitions are captured compactly by transfer operators. These operators play a central role, guiding the construction of maximally-predictive short-time states from incomplete measurements and identifying collective modes via eigenvalue decomposition. We demonstrate our analysis in both stochastic and deterministic systems, and with an application to the movement dynamics of an entire organism, unravelling new insight in long time scale behavioral states directly from measurements of posture dynamics. We can, in principle, also make connections to both longer or shorter timescales. Microscopically, postural dynamics result from the fine scale interactions of actin and myosin in the muscles, and from electrical impulses in the brain and nervous system. Macroscopically, behavioral dynamics may be extended to longer time scales, to moods or dispositions, including changes during aging, or over generations due to ecological or evolutionary adaptation. The generality of our approach provides opportunity for insights on long term dynamics within a wide variety of complex systems.

biophysics↗

bioRxiv2019

Capturing the Continuous Complexity of Behavior in C. elegans

Animal behavior is often quantified through subjective, incomplete variables that may mask essential dynamics. Here, we develop a behavioral state space in which the full instantaneous state is smoothly unfolded as a combination of short-time posture dynamics. Our technique is tailored to multivariate observations and extends previous reconstructions through the use of maximal prediction. Applied to high-resolution video recordings of the roundworm C. elegans, we discover a low-dimensional state space dominated by three sets of cyclic trajectories corresponding to the worms basic stereotyped motifs: forward, backward, and turning locomotion. In contrast to this broad stereotypy, we find variability in the presence of locally-unstable dynamics, and this unpredictability shows signatures of deterministic chaos: a collection of unstable periodic orbits together with a positive maximal Lyapunov exponent. The full Lyapunov spectrum is symmetric with positive, chaotic exponents driving variability balanced by negative, dissipative exponents driving stereotypy. The symmetry is indicative of damped, driven Hamiltonian dynamics underlying the worms movement control.

animal behavior and cognition↗