Towards a connectome of descending commands controlling locomotion

Inhibitory medial zona incerta pathway drives exploratory behavior by inhibiting glutamatergic cuneiform neurons

The cuneiform nucleus (CnF) regulates locomotor activity, which is canonically viewed as being primarily involved in initiating locomotion and regulating speed. Recent research shows greater context dependency in the locomotor functions of this nucleus. Glutamatergic neurons, which contain vesicular glutamate transporter 2 (vGLUT2), regulate context-dependent locomotor speed in the CnF and play a role in defensive behavior. Here, we identify projections from the medial zona incerta (mZI) to CnF vGLUT2 neurons that promote exploratory behavior. Using fiber photometry recordings in male mice, we find that mZI gamma-aminobutyric acid (GABA) neurons increase activity during periods of exploration. Activation of mZI GABAergic neurons is associated with reduced spiking of CnF neurons. Additionally, activating both retrogradely labeled mZI-CnF GABAergic projection neurons and their terminals in the CnF increase exploratory behavior. Inhibiting CnF vGLUT2 neuronal activity also increases exploratory behavior. These findings provide evidence for the context-dependent dynamic regulation of CnF vGLUT2 neurons, with the mZI-CnF circuit shaping exploratory behavior.

Switching neuron contributions to second network activity

Network flexibility is important for adaptable behaviors. This includes neuronal switching, where neurons alter their network participation, including changing from single- to dual-network activity. Understanding the implications of neuronal switching requires determining how a switching neuron interacts with each of its networks. Here, we tested 1) whether "home" and second networks, operating via divergent rhythm generation mechanisms, regulate a switching neuron and 2) if a switching neuron, recruited via modulation of intrinsic properties, contributes to rhythm or pattern generation in a new network. Small, well-characterized feeding-related networks (pyloric, ∼1 Hz; gastric mill, ∼0.1 Hz) and identified modulatory inputs make the isolated crab (Cancer borealis) stomatogastric nervous system (STNS) a useful model to study neuronal switching. In particular, the neuropeptide Gly1-SIFamide switches the lateral posterior gastric (LPG) neuron (2 copies) from pyloric-only to dual-frequency pyloric/gastric mill (fast/slow) activity via modulation of LPG-intrinsic properties. Using current injections to manipulate neuronal activity, we found that gastric mill, but not pyloric, network neurons regulated the intrinsically generated LPG slow bursting. Conversely, selective elimination of LPG from both networks using photoinactivation revealed that LPG regulated gastric mill neuron-firing frequencies but was not necessary for gastric mill rhythm generation or coordination. However, LPG alone was sufficient to produce a distinct pattern of network coordination. Thus, modulated intrinsic properties underlying dual-network participation may constrain which networks can regulate switching neuron activity. Furthermore, recruitment via intrinsic properties may occur in modulatory states where it is important for the switching neuron to actively contribute to network output.NEW & NOTEWORTHY We used small, well-characterized networks to investigate interactions between rhythmic networks and neurons that switch their network participation. For a neuron switching into dual-network activity, only the second network regulated its activity in that network. In addition, the switching neuron was sufficient but not necessary to coordinate second network neurons and regulated their activity levels. Thus, regulation of switching neurons may be selective, and a switching neuron is not necessarily simply a follower in additional networks.

Hypothalamic A11 Nuclei Regulate the Circadian Rhythm of Spinal Mechanonociception through Dopamine Receptors and Clock Gene Expression

Several types of sensory perception have circadian rhythms. The spinal cord can be considered a center for controlling circadian rhythms by changing clock gene expression. However, to date, it is not known if mechanonociception itself has a circadian rhythm. The hypothalamic A11 area represents the primary source of dopamine (DA) in the spinal cord and has been found to be involved in clock gene expression and circadian rhythmicity. Here, we investigate if the paw withdrawal threshold (PWT) has a circadian rhythm, as well as the role of the dopaminergic A11 nucleus, DA, and DA receptors (DR) in the PWT circadian rhythm and if they modify clock gene expression in the lumbar spinal cord. Naïve rats showed a circadian rhythm of the PWT of almost 24 h, beginning during the night–day interphase and peaking at 14.63 h. Similarly, DA and DOPAC’s spinal contents increased at dusk and reached their maximum contents at noon. The injection of 6-hydroxydopamine (6-OHDA) into the A11 nucleus completely abolished the circadian rhythm of the PWT, reduced DA tissue content in the lumbar spinal cord, and induced tactile allodynia. Likewise, the repeated intrathecal administration of D1-like and D2-like DA receptor antagonists blunted the circadian rhythm of PWT. 6-OHDA reduced the expression of Clock and Per1 and increased Per2 gene expression during the day. In contrast, 6-OHDA diminished Clock, Bmal, Per1, Per2, Per3, Cry1, and Cry2 at night. The repeated intrathecal administration of the D1-like antagonist (SCH-23390) reduced clock genes throughout the day (Clock and Per2) and throughout the night (Clock, Per2 and Cry1), whereas it increased Bmal and Per1 throughout the day. In contrast, the intrathecal injection of the D2 receptor antagonists (L-741,626) increased the clock genes Bmal, Per2, and Per3 and decreased Per1 throughout the day. This study provides evidence that the circadian rhythm of the PWT results from the descending dopaminergic modulation of spinal clock genes induced by the differential activation of spinal DR.

A review of motor neural system robotic modeling approaches and instruments

In this review, we are considering an actively developing tool in neuroscience-robotic modeling. The new perspective and existing application fields, tools, and methods are discussed. We try to determine starting positions and approaches that are useful at the beginning of new research in this field. Among multiple directions of the research is robotic modeling on the level of muscles fibers and their afferents, skin surface sensors, muscles, and joints proprioceptors. Some examples of technical implementation for physical modeling are reviewed. They are software and hardware tools like event-related modeling algorithms, reduced neuron models, robotic drives constructions. We observe existing drives technologies and prospective electric motor types: switched reluctance and transverse flux motors. Next, we look at the existing examples and approaches for robotic modeling of the cerebellum and spinal cord neural networks. These examples show practical methods for the model neural network architecture and adaptation. Those methods allow the use of cortical and spinal cord reflexes for the network training and apply additional artificial blocks for data processing in other brain structures that transmit and receive data from biologically realistic models.

The Mesencephalic Locomotor Region: Beyond Locomotor Control

The mesencephalic locomotor region (MLR) was discovered several decades ago in the cat. It was functionally defined based on the ability of low threshold electrical stimuli within a region comprising the cuneiform and pedunculopontine nucleus to evoke locomotion. Since then, similar regions have been found in diverse vertebrate species, including the lamprey, skate, rodent, pig, monkey, and human. The MLR, while often viewed under the lens of locomotion, is involved in diverse processes involving the autonomic nervous system, respiratory system, and the state-dependent activation of motor systems. This review will discuss the pedunculopontine nucleus and cuneiform nucleus that comprises the MLR and examine their respective connectomes from both an anatomical and functional angle. From a functional perspective, the MLR primes the cardiovascular and respiratory systems before the locomotor activity occurs. Inputs from a variety of higher structures, and direct outputs to the monoaminergic nuclei, allow the MLR to be able to respond appropriately to state-dependent locomotion. These state-dependent effects are roughly divided into escape and exploratory behavior, and the MLR also can reinforce the selection of these locomotor behaviors through projections to adjacent structures such as the periaqueductal gray or to limbic and cortical regions. Findings from the rat, mouse, pig, and cat will be discussed to highlight similarities and differences among diverse species.