Graded boosting of synaptic signals by low-threshold voltage-activated calcium conductance

A tale of two leeches: Toward the understanding of the evolution and development of behavioral neural circuits

In the animal kingdom, behavioral traits encompass a broad spectrum of biological phenotypes that have critical roles in adaptive evolution, but an EvoDevo approach has not been broadly used to study behavior evolution. Here, we propose that, by integrating two leech model systems, each of which has already attained some success in its respective field, it is possible to take on behavioral traits with an EvoDevo approach. We first identify the developmental changes that may theoretically lead to behavioral evolution and explain why an EvoDevo study of behavior is challenging. Next, we discuss the pros and cons of the two leech model species, Hirudo, a classic model for invertebrate neurobiology, and Helobdella, an emerging model for clitellate developmental biology, as models for behavioral EvoDevo research. Given the limitations of each leech system, neither is particularly strong for behavioral EvoDevo. However, the two leech systems are complementary in their technical accessibilities, and they do exhibit some behavioral similarities and differences. By studying them in parallel and together with additional leech species such as Haementeria, it is possible to explore the different levels of behavioral development and evolution.

A modeling study of spinal motoneuron recruitment regulated by ionic channels during fictive locomotion

During fictive locomotion cat lumbar motoneurons exhibit changes in membrane proprieties including a decrease in voltage threshold (V_th), afterhyperpolarization (AHP) and input resistance (R_in) and an increase in non-linear membrane property. The impact of these changes on the motoneuron recruitment remains unknown. Using modeling approach we investigated the channel mechanism regulating the motoneuron recruitment. Three types of motoneuron pools including slow (S), fatigue-resistant (FR) and fast-fatigable (FF) motoneurons were constructed based on the membrane proprieties of cat lumbar motoneurons. The transient sodium (NaT), persistent sodium (NaP), delayed-rectifier potassium [K(DR)], Ca²⁺-dependent K⁺ [K(AHP)] and L-type calcium (Ca_L) channels were included in the models. Simulation results showed that (1) Strengthening synaptic inputs increased the number of recruitments in all three types of motoneurons following the size principle. (2) Increasing NaT or NaP or decreasing K(DR) or K(AHP) lowered rheobase of spike generation thus increased recruitment of motoneuron pools. (3) Decreasing R_in reduced recruitment in all three types of motoneurons. (4) The FF-type motoneuron pool, followed by FR- and S-type, were the most sensitive to increase of synaptic inputs, reduction of R_in, upregulation of NaT and NaP, and downregulation of K(DR) and K(AHP). (5) Increasing Ca_L enhanced overall discharge rate of motoneuron pools with little effect on the recruitment. Simulation results suggested that modulation of ionic channels altered the output of motoneuron pools with either modulating the number of recruited motoneurons or regulating the overall discharge rate of motoneuron pools. Multiple channels contributed to the recruitment of motoneurons with interaction of excitatory and inhibitory synaptic inputs during walking.

Functional contributions of electrical synapses in sensory and motor networks

Intercellular interactions in the nervous system are mediated by two types of dedicated structural arrangements: electrical and chemical synapses. Several characteristics distinguish these two mechanisms of communication, such as speed, reliability and the fact that electrical synapses are, potentially, bidirectional. Given these properties, electrical synapses can subserve, in addition to synchrony, three main interrelated network functions: signal amplification, noise reduction and/or coincidence detection. Specific network motifs in sensory and motor systems of invertebrates and vertebrates illustrate how signal transmission through electrical junctions contributes to a complex processing of information.