Biology subjects

Yakovenko, S.

Publications and source records attributed to Yakovenko, S..

3 recordsLinked to original sources

bioRxiv2018

Study of the DiI method accuracy on the example of the afferent connections of the Habenula in P6 F1-C57Bl6 / CBA mice

ABSTACTDiI (1,1-dioctadecyl-3,3,33-tetramethylindocarbocyanine perchlorate) is a lipophilic carbocyanine stain diffusing in the plasma membrane and coloring the cell as a whole.\n\nThe DiI injection method is an alternative to stereotaxis in the study of the neural connections of higher vertebrates. However, despite a number of studies performed to identify the neural connections of embryos and fetuses of different animals, the question of the accuracy of the DiI method remains open. The main goal of this study is to investigate the accuracy of the DiI method by examining the afferent Habenula (Hb) connections in P6 F1-C57Bl6/CBA mice. Hb is a paired structure of the intermediate brain, consisting of two nuclei - the medial (MHb) and lateral (LHb). At P6, the main Hb tracts are already formed but not yet myelinated. To estimate the accuracy of the method, two groups of cases with different types of application on different Hb nuclei were compared: bilateral applications of several DiI crystals - group 1 (26 applications); Unilateral applications of a single crystal DiI - control group 2 (7 applications). It is known that MHb is strictly innervated by Triangular septal nuclei (TS) and Septofimbrial septal nuclei (SFi); LHb is strictly innervated by the Lateral preopteic area (LPA). Any deviation from this scheme is a false positive result. When applying the marker to different Hb nuclei in group 1, the number of successful cases without deviations was -0%; in group 2 (control) - 28.57%. Unilateral applications of a single DiI crystal are more accurate. However, there are still a number of unavoidable problems, such as the fragmentation or loss of a single DiI crystal during application and the super-strong diffusion of the marker at the application site. Given this, the overall accuracy of the DiI injection method, even in the form of a single crystal, remains low.

neuroscience↗

bioRxiv2017

Analytical solution of a bilateral Brown-type central pattern generator for symmetric and asymmetric locomotion

The coordinated activity of muscles is produced in part by spinal rhythmogenic neural circuits, termed central pattern generators (CPGs). A classical CPG model, proposed conceptually by T.G. Brown in 1911, is a system of coupled oscillators that transform locomotor drive into coordinated and gait-specific patterns of muscle recruitment. A system of ordinary differential equations with a physiologically-inspired coupling locus of interactions captures the timing relationship for bilateral coordination of limbs in locomotion and is typically solved numerically. Consequently, it is intriguing to have a full analytical description of this plausible CPG architecture to illuminate the functionality within this structure. Here, we provided a closed-form analytical solution contrasted against the previous numerical method. The computational load of the analytical solution was decreased by an order of magnitude when compared to the numerical approach (relative errors, <0.01%). The analytical solution tested and supported the previous finding that the input to the model can be expressed in units of the desired limb locomotor speed. Furthermore, we performed parametric sensitivity analysis in the context of controlling asymmetric locomotion and documented two possible mechanisms associated with either an external drive or intrinsic CPG parameters. The results support the idea that many different combinations of network states, even within the same anatomical CPG structure, may generate the same behavioral outcomes.\n\nAuthor SummaryUsing a simple process of leaky integration, we developed an analytical solution to a robust model of spinal pattern generation. We analyzed the ability of this neural element to exert locomotor control of the signal associated with limb speeds, which represent high-level modality within the motor system. Furthermore, we tested the ability of this simple structure to embed steering control using the velocity signal in the models inputs or within the internal connectivity of its elements. Both mechanisms can produce the same behavioral outcome, pointing to the methodological challenges of modeling central pattern generators and demonstrating the possibility of spinal circuit adaptations to asymmetric short- or long-term conditions in health and disease.

neuroscience↗

bioRxiv2017

The Nonlinear Relationship Between Sensory And Motor Primitives During Reaching Movements

The stabilizing role of sensory feedback in relation to realistic 3-dimensional movement dynamics remains poorly understood. The objective of this study was to quantify how primary afferent activity contributes to shaping muscle activity patterns during reaching movements. To achieve this objective, we designed a virtual reality task that guided healthy human subjects through a set of planar reaching movements with controlled kinematic and dynamic conditions that minimized inter-subject variability. Next, we integrated human upper-limb models of musculoskeletal dynamics and proprioception to analyze motion and major muscle activation patterns during these tasks. We recorded electromyographic and motion-capture data and used the integrated model to simulate joint kinematics, joint torques due to muscle contractions, muscle length changes, and simulated primary afferent feedback. The parameters of the primary afferent model were altered systematically to evaluate the effect of fusimotor drive. The experimental and simulated data were analyzed with hierarchical clustering. We found that the muscle activity patterns contained flexible task-dependent groups that consisted of co-activating agonistic and antagonistic muscles that changed with the dynamics of the task. The activity of muscles spanning only the shoulder generally grouped into a proximal cluster, while the muscles spanning the wrist grouped into a distal cluster. The bifunctional muscle spanning the shoulder and elbow were flexibly grouped with either proximal or distal cluster based on the dynamical requirements of the task. The composition and activation of these groups reflected the relative contribution of active and passive forces to each motion. In contrast, the simulated primary afferent feedback was most related to joint kinematics rather than dynamics, even though the primary afferent models had nonlinear dynamical components and variable fusimotor drive. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce the dynamical features in muscle activity pattern. Altogether, these results suggest that sensory feedback signals are in a different domain from that of muscle activation signals. This indicates that to solve the neuromechanical problem, the central nervous system controls limb dynamics through task-dependent co-activation of muscles and non-linear modulation of monosynaptic primary afferent feedback. New & NoteworthyHere we answered the fundamental question in sensorimotor transformation of how primary afferent signals can contribute to the compensation for limb dynamics evident in muscle activity. We combined computational and experimental approaches to create a new experimental paradigm that challenges the nervous system with passive limb dynamics that either assists or resists the desired movement. We found that the active dynamical features present in muscle activity are unlikely to arise from direct feedback from primary afferents.

neuroscience↗