Existence of a Long-Range Caudo-Rostral Sensory Influence in Terrestrial Locomotion.

In multisegmented locomotion, coordination of all appendages is crucial for the generation of a proper motor output. In running for example, leg coordination is mainly based on the central interaction of rhythm generating networks, called central pattern generators (CPGs). In slower forms of locomotion, however, sensory feedback, which originates from sensory organs that detect changes in position, velocity and load of the legs' segments, has been shown to play a more crucial role. How exactly sensory feedback influences the activity of the CPGs to establish functional neuronal connectivity is not yet fully understood. Using the female stick insect Carausius morosus, we show for the first time that a long-range caudo-rostral sensory connection exists and highlight that load as sensory signal is sufficient to entrain rhythmic motoneuron (MN) activity in the most rostral segment. So far, mainly rostro-caudal influencing pathways have been investigated where the strength of activation, expressed by the MN activity in the thoracic ganglia, decreases with the distance from the stepping leg to these ganglia. Here, we activated CPGs, producing rhythmic neuronal activity in the thoracic ganglia by using the muscarinic agonist pilocarpine and enforced the stepping of a single, remaining leg. This enabled us to study sensory influences on the CPGs' oscillatory activity. Using this approach, we show that, in contrast to the distance-dependent activation of the protractor-retractor CPGs in different thoracic ganglia, there is no such dependence for the entrainment of the rhythmic activity of active protractor-retractor CPG networks by individual stepping legs.SIGNIFICANCE STATEMENT We show for the first time that sensory information is transferred not only to the immediate adjacent segmental ganglia but also to those farther away, indicating the existence of a long-range caudo-rostral sensory influence. This influence is dependent on stepping direction but independent of whether the leg is actively or passively moved. We suggest that the sensory information comes from unspecific load signals sensed by cuticle mechanoreceptors (campaniform sensilla) of a leg. Our results provide a neuronal basis for the long-established behavioral rules of insect leg coordination. We thus provide a breakthrough in understanding the neuronal networks underlying multilegged locomotion and open new vistas into the neuronal functional connectivity of multisegmented locomotion systems across the animal kingdom.

A kinematic model of stick-insect walking.

Animal, and insect walking (locomotion) in particular, have attracted much attention from scientists over many years up to now. The investigations included behavioral, electrophysiological experiments, as well as modeling studies. Despite the large amount of material collected, there are left many unanswered questions as to how walking and related activities are generated, maintained, and controlled. It is obvious that for them to take place, precise coordination within muscle groups of one leg and between the legs is required: intra- and interleg coordination. The nature, the details, and the interactions of these coordination mechanisms are not entirely clear. To help uncover them, we made use of modeling techniques, and succeeded in developing a six-leg model of stick-insect walking. Our main goal was to prove that the same model can mimic a variety of walking-related behavioral modes, as well as the most common coordination patterns of walking just by changing the values of a few input or internal variables. As a result, the model can reproduce the basic coordination patterns of walking: tetrapod and tripod and the transition between them. It can also mimic stop and restart, change from forward-to-backward walking and back. Finally, it can exhibit so-called search movements of the front legs both while walking or standing still. The mechanisms of the model that enable it to produce the aforementioned behavioral modes can hint at and prove helpful in uncovering further details of the biological mechanisms underlying walking.

Age-related changes in oscillatory power affect motor action.

With increasing age cognitive performance slows down. This includes cognitive processes essential for motor performance. Additionally, performance of motor tasks becomes less accurate. The objective of the present study was to identify general neural correlates underlying age-related behavioral slowing and the reduction in motor task accuracy. To this end, we continuously recorded EEG activity from 18 younger and 24 older right-handed healthy participants while they were performing a simple finger tapping task. We analyzed the EEG records with respect to local changes in amplitude (power spectrum) as well as phase locking between the two age groups. We found differences between younger and older subjects in the amplitude of post-movement synchronization in the ß band of the sensory-motor and medial prefrontal cortex (mPFC). This post-movement ß amplitude was significantly reduced in older subjects. Moreover, it positively correlated with the accuracy with which subjects performed the motor task at the electrode FCz, which detects activity of the mPFC and the supplementary motor area. In contrast, we found no correlation between the accurate timing of local neural activity, i.e. phase locking in the δ-θ frequency band, with the reaction and movement time or the accuracy with which the motor task was performed. Our results show that only post-movement ß amplitude and not δ-θ phase locking is involved in the control of movement accuracy. The decreased post-movement ß amplitude in the mPFC of older subjects hints at an impaired deactivation of this area, which may affect the cognitive control of stimulus-induced motor tasks and thereby motor output.

Modeling search movements of an insect's front leg.

Beside locomotion, search movements are another important type of motor activity of insects. They are very often performed by the front legs of the animals. They consist of cyclic stereotypical leg movements that can be modified by sensory signals. The details of the local organization of these movements have however not yet been studied. In this paper, we, using an appropriate variant of our existing one-leg model, present a scheme of how these searching movements might be organized and performed on the level of local neuromuscular control networks. In the simulations with the model, we attempted to mimic the experimental results by Berg et al. (J. Exp. Biol. 216:1064-1074, 2013) in which an obstacle was put in the way of the search movements of the front leg for a very short while, and then the recovery to the usual search movements was observed and analyzed. Our simulation results suggest that the recruitment of the fast levator and depressor muscles play a crucial part in resuming the search movements after removal of the obstacle. The interplay between the levator and depressor, and the extensor and flexor local control networks can, according to the model, bring about a large variety of search movements upon removal of the obstacle. A number of these movements are comparable with those seen in the experiments.

Effects of functional decoupling of a leg in a model of stick insect walking incorporating three ipsilateral legs.

Legged locomotion is a fundamental form of activity of insects during which the legs perform coordinated movements. Sensory signals conveying position, velocity and load of a leg are sent between the thoracic ganglia where the local control networks of the leg muscles are situated. They affect the actual state of the local control networks, hence the stepping of the legs. Sensory coordination in stepping has been intensively studied but important details of its neuronal mechanisms are still unclear. One possibility to tackle this problem is to study what happens to the coordination if a leg is, reversibly or irreversibly, deprived of its normal function. There are numerous behavioral studies on this topic but they could not fully uncover the underlying neuronal mechanisms. Another promising approach to make further progress here can be the use of appropriate models that help elucidate those coordinating mechanisms. We constructed a model of three ipsilateral legs of a stick insect that can mimic coordinated stepping of these legs. We used this model to investigate the possible effects of decoupling a leg. We found that decoupling of the front or the hind leg did not disrupt the coordinated walking of the two remaining legs. However, decoupling of the middle leg yielded mixed results. Both disruption and continuation of coordinated stepping of the front and hind leg occurred. These results agree with the majority of corresponding experimental findings. The model suggests a number of possible mechanisms of decoupling that might bring about the changes.

Investigating inter-segmental connections between thoracic ganglia in the stick insect by means of experimental and simulated phase response curves.

The neuronal networks that control the motion of the individual legs in insects, in particular in the stick insect, are located in the pro-, meso- and meta-thoracic ganglia. They ensure high flexibility of movement control. Thus, the legs can move in an apparently independent way, e.g., during search movements, but also in tight coordination during locomotion. The latter is evidently a very important behavioural mode. It has, therefore, inspired a large number of studies, all aiming at uncovering the nature of the inter-leg coordination. One of the basic questions has been as to how the individual control networks in the three thoracic ganglia are connected to each other. One way to study this problem is to use phase response curves. They can reveal properties of the coupling between oscillatory systems, such as the central pattern generators in the control networks in the thoracic ganglia. In this paper, we report results that we have achieved by means of a combined experimental and modelling approach. We have calculated phase response curves from data obtained in as yet unpublished experiments as well as from those in previously published ones. By using models of the connected pro- and meso-thoracic control networks of the protractor and retractor neuromuscular systems, we have also produced simulated phase response curves and compared them with the experimental ones. In this way, we could gain important information of the nature of the connections between the aforementioned control networks. Specifically, we have found that connections from both the protractor and the retractor "sides" of the pro-thoracic network to the meso-thoracic one are necessary for producing phase response curves that show close similarity to the experimental ones. Furthermore, the strength of the excitatory connections has been proven to be crucial, while the inhibitory connections have essentially been irrelevant. We, thus, suggest that this type of connection might also be present in the stick insect, and possibly in other insect species.

A putative neuronal network controlling the activity of the leg motoneurons of the stick insect.

It is widely accepted that the electrical activity of motoneurons that drive locomotion in the stick insect are controlled by two separate mechanisms: (i) the frequency of the activity through the central pattern generator, which provides the rhythm of movement during locomotion and (ii) the 'magnitude' through circuits distinct from the earlier one. In this study, we show a possible way of how this control mechanism might be implemented in the nervous system of the stick insect by means of a network model. To do this, we had to define the 'magnitude' of the neuronal activity more precisely as the average number of spikes per unit time. The model was constructed on the basis of relevant electrophysiological and morphological data. However, only their integration in the model led to the novel properties that enable the network quickly to adapt the motoneuronal activity to central commands or sensory signals by changing both the firing pattern and intensity of the motoneuron discharges. The network would thus act as the controlling network for each of the muscle pairs that move the individual joints in each of the legs. Our model may contribute to a better understanding of the mechanisms that underlie the fast adaptive control of locomotion in this, and possibly in other types of locomotor systems.

The thalamic low-threshold Ca²âº potential: a key determinant of the local and global dynamics of the slow (<1 Hz) sleep oscillation in thalamocortical networks.

During non-rapid eye movement sleep and certain types of anaesthesia, neurons in the neocortex and thalamus exhibit a distinctive slow (<1 Hz) oscillation that consists of alternating UP and DOWN membrane potential states and which correlates with a pronounced slow (<1 Hz) rhythm in the electroencephalogram. While several studies have claimed that the slow oscillation is generated exclusively in neocortical networks and then transmitted to other brain areas, substantial evidence exists to suggest that the full expression of the slow oscillation in an intact thalamocortical (TC) network requires the balanced interaction of oscillator systems in both the neocortex and thalamus. Within such a scenario, we have previously argued that the powerful low-threshold Ca(2+) potential (LTCP)-mediated burst of action potentials that initiates the UP states in individual TC neurons may be a vital signal for instigating UP states in related cortical areas. To investigate these issues we constructed a computational model of the TC network which encompasses the important known aspects of the slow oscillation that have been garnered from earlier in vivo and in vitro experiments. Using this model we confirm that the overall expression of the slow oscillation is intricately reliant on intact connections between the thalamus and the cortex. In particular, we demonstrate that UP state-related LTCP-mediated bursts in TC neurons are proficient in triggering synchronous UP states in cortical networks, thereby bringing about a synchronous slow oscillation in the whole network. The importance of LTCP-mediated action potential bursts in the slow oscillation is also underlined by the observation that their associated dendritic Ca(2+) signals are the only ones that inform corticothalamic synapses of the TC neuron output, since they, but not those elicited by tonic action potential firing, reach the distal dendritic sites where these synapses are located.

Dominance of local sensory signals over inter-segmental effects in a motor system: experiments.

Legged locomotion requires that information local to one leg, and inter-segmental signals coming from the other legs are processed appropriately to establish a coordinated walking pattern.However, very little is known about the relative importance of local and inter-segmental signals when they converge upon the central pattern generators (CPGs) of different leg joints.We investigated this question on the CPG of the middle leg coxa­trochanter (CTr)-joint of the stick insect which is responsible for lifting and lowering the leg.We used a semi-intact preparation with an intact front leg stepping on a treadmill, and simultaneously stimulated load sensors of the middle leg.We found that middle leg load signals induce bursts in the middle leg depressor motoneurons(MNs). The same local load signals could also elicit rhythmic activity in the CPG of the middle leg CTr-joint when the stimulation of middle leg load sensors coincided with front leg stepping. However, the influence of front leg stepping was generally weak such that front leg stepping alone was only rarely accompanied by switching between middle leg levator and depressor MN activity. We therefore conclude that the impact of the local sensory signals on the levator­depressor motor system is stronger than the inter-segmental influence through front leg stepping.

Dominance of local sensory signals over inter-segmental effects in a motor system: modeling studies.

Recent experiments, reported in the accompanying paper, have supplied key data on the impact afferent excitation has on the activity of the levator­depressor motor system of an extremity in the stick insect. The main finding was that, stimulation of the campaniform sensillae of the partially amputated middle leg in an animal where all other but one front leg had been removed, had a dominating effect over that of the stepping ipsilateral front leg. In fact,the latter effect was minute compared to the former. In this article, we propose a local network that involves the neuronal part of the levator­depressor motor system and use it to elucidate the mechanisms that underlie the generation of neuronal activity in the experiments. In particular, we show that by appropriately modulating the activity in the neurons of the central pattern generator of the levator­depressor motor system, we obtain activity patterns of the motoneurons in the model that closely resemble those found in extracellular recordings in the stick insect. In addition, our model predicts specific properties of these records which depend on the stimuli applied to the stick insect leg. We also discuss our results on the segmental mechanisms in the context of inter-segmental coordination.

Nucleus-specific abnormalities of GABAergic synaptic transmission in a genetic model of absence seizures.

Human and experimental studies indicate that molecular genetic changes in GABA(A) receptors may underlie the expression of spike-and-waves discharges (SWDs) occurring during absence seizures. However, the full spectrum of the genetic defects underlying these seizures has only been partially elucidated, the expression and functional profiles of putative abnormal protein(s) within the thalamocortical network are undefined, and the pathophysiological mechanism(s) by which these proteins would lead to absence paroxysms are poorly understood. Here we investigated GABA(A) inhibitory postsynaptic currents (IPSCs) in key thalamocortical areas, i.e., the somatosensory cortex, ventrobasal thalamus (VB) and nucleus reticularis thalami (NRT), in preseizure genetic absence epilepsy rats from Strasbourg (GAERS), a well-established genetic model of typical absence seizures that shows no additional neurological abnormalities, and compared their properties to age-matched non-epileptic controls (NECs). Miniature GABA(A) IPSCs of VB and cortical layers II/III neurons were similar in GAERS and NEC, whereas in GAERS NRT neurons they had 25% larger amplitude, 40% faster decay. In addition, baclofen was significantly less effective in decreasing the frequency of NRT mIPSCs in GAERS than in NEC, whereas no difference was observed for cortical and VB mIPSCS between the two strains. Paired-pulse depression was 45% smaller in GAERS NRT, but not in VB, and was insensitive to GABA(B) antagonists. These results point to subtle, nucleus-specific, GABA(A) receptor abnormalities underlying SWDs of typical absence seizures rather than a full block of these receptors across the whole thalamocortical network, and their occurrence prior to seizure onset suggests that they might be of epileptogenic significance.

Neuronal basis of the slow (<1 Hz) oscillation in neurons of the nucleus reticularis thalami in vitro.

During deep sleep and anesthesia, the EEG of humans and animals exhibits a distinctive slow (<1 Hz) rhythm. In inhibitory neurons of the nucleus reticularis thalami (NRT), this rhythm is reflected as a slow (<1 Hz) oscillation of the membrane potential comprising stereotypical, recurring "up" and "down" states. Here we show that reducing the leak current through the activation of group I metabotropic glutamate receptors (mGluRs) with either trans-ACPD [(+/-)-1-aminocyclopentane-trans-1,3-dicarboxylic acid] (50-100 microM) or DHPG [(S)-3,5-dihydroxyphenylglycine] (100 microM) instates an intrinsic slow oscillation in NRT neurons in vitro that is qualitatively equivalent to that observed in vivo. A slow oscillation could also be evoked by synaptically activating mGluRs on NRT neurons via the tetanic stimulation of corticothalamic fibers. Through a combination of experiments and computational modeling we show that the up state of the slow oscillation is predominantly generated by the "window" component of the T-type Ca2+ current, with an additional supportive role for a Ca2+-activated nonselective cation current. The slow oscillation is also fundamentally reliant on an Ih current and is extensively shaped by both Ca2+- and Na+-activated K+ currents. In combination with previous work in thalamocortical neurons, this study suggests that the thalamus plays an important and active role in shaping the slow (<1 Hz) rhythm during deep sleep.

The 'window' T-type calcium current in brain dynamics of different behavioural states.

All three forms of recombinant low voltage-activated T-type Ca(2)(+) channels (Ca(v)3.1, Ca(v)3.2 and Ca(v)3.3) exhibit a small, though clearly evident, window T-type Ca(2)(+) current (I(Twindow)) which is also present in native channels from different neuronal types. In thalamocortical (TC) and nucleus reticularis thalami (NRT) neurones, and possibly in neocortical cells, an I(Twindow)-mediated bistability is the key cellular mechanism underlying the expression of the slow (< 1 Hz) sleep oscillation, one of the fundamental EEG rhythms of non-REM sleep. As the I(Twindow)-mediated bistability may also represent one of the cellular mechanisms underlying the expression of high frequency burst firing in awake conditions, I(Twindow) is of critical importance in neuronal population dynamics associated with different behavioural states.

Key mechanisms for setting the input-output gain across the motoneuron pool.

This chapter summarizes a number of factors that control the "input-output" function across the motoneurons (MNs) comprising a single spinal motor nucleus. The main focus is on intrinsic properties of individual MNs that can be controlled by neuromodulators. These include: (1) amplification of the synaptic input at the cell's dendritic level by voltage-gated, persistent inward currents (plateau potentials); and (2) transduction of the net synaptic excitation into a frequency code (the MN's stimulus current-spike frequency relation) at the cell's soma/initial segment. Two other aspects of the synaptic control of MNs, which may affect their input-output gain, are also discussed. They include the hypotheses that: (1) a non-uniform distribution of synaptic effects to low- and high-threshold motor units causes a change in recruitment gain; and (2) recurrent inhibition, via motor axon collaterals and Renshaw cells, functions as a variable gain regulator of MN discharge.

Modelling large scale neuronal networks using 'average neurones'.

Large scale neuronal network models have become important tools in studying the information transmission within the CNS. In most cases, these models use simplifying assumptions because of unavailable data (e.g. unknown exact network connectivity), and for technical reasons (to preserve numerical stability of the model). Here, we present a novel approach, based on a probabilistic connectivity principle, to this modelling problem for which no knowledge of the exact network connectivity is required. This principle makes it sufficient to compute only the typical neuronal behaviour, represented by 'average neurones', in the network. As a consequence, detailed neurone models can be employed without seriously compromising computational efficiency. Our model thus provides a viable alternative to deterministic models.

Novel neuronal and astrocytic mechanisms in thalamocortical loop dynamics.

In this review, we summarize three sets of findings that have recently been observed in thalamic astrocytes and neurons, and discuss their significance for thalamocortical loop dynamics. (i) A physiologically relevant 'window' component of the low-voltage-activated, T-type Ca(2+) current (I(Twindow)) plays an essential part in the slow (less than 1 Hz) sleep oscillation in adult thalamocortical (TC) neurons, indicating that the expression of this fundamental sleep rhythm in these neurons is not a simple reflection of cortical network activity. It is also likely that I(Twindow) underlies one of the cellular mechanisms enabling TC neurons to produce burst firing in response to novel sensory stimuli. (ii) Both electrophysiological and dye-injection experiments support the existence of gap junction-mediated coupling among young and adult TC neurons. This finding indicates that electrical coupling-mediated synchronization might be implicated in the high and low frequency oscillatory activities expressed by this type of thalamic neuron. (iii) Spontaneous intracellular Ca(2+) ([Ca(2+)](i)) waves propagating among thalamic astrocytes are able to elicit large and long-lasting N-methyl-D-aspartate-mediated currents in TC neurons. The peculiar developmental profile within the first two postnatal weeks of these astrocytic [Ca(2+)](i) transients and the selective activation of these glutamate receptors point to a role for this astrocyte-to-neuron signalling mechanism in the topographic wiring of the thalamocortical loop. As some of these novel cellular and intracellular properties are not restricted to thalamic astrocytes and neurons, their significance may well apply to (patho)physiological functions of glial and neuronal elements in other brain areas.