Role of synchronous activation of cerebellar purkinje cell ensembles in multi-joint movement control

It is a longstanding question in neuroscience how elaborate multi-joint movements are coordinated coherently. Microzones of cerebellar Purkinje cells (PCs) are thought to mediate this coordination by controlling the timing of particular motor domains. However, it remains to be elucidated to what extent motor coordination deficits can be correlated with abnormalities in coherent activity within these microzones and to what extent artificially evoked synchronous activity within PC ensembles can elicit multi-joint motor behavior. To study PC ensemble correlates of limb, trunk, and tail movements, we developed a transparent disk treadmill that allows quantitative readout of locomotion and posture parameters in head-fixed mice and simultaneous cellular-resolution imaging and/or optogenetic manipulation. We show that PC ensembles in the ataxic and dystonic mouse mutant tottering have a reduced level of complex spike co-activation, which is delayed relative to movement onset and co-occurs with prolonged swing duration and reduced phase coupling of limb movements as well as with enlarged deflections of body-axis and tail movements. Using optogenetics to increase simple spike rate in PC ensembles, we find that preferred locomotion and posture patterns can be elicited or perturbed depending on the behavioral state. At rest, preferred sequences of limb movements can be elicited, whereas during locomotion, preferred gait-inhibition patterns are evoked. Our findings indicate that synchronous activation of PC ensembles can facilitate initiation and coordination of limb and trunk movements, presumably by tuning downstream systems involved in the execution of behavioral patterns

Whole brain 7T-fMRI during pelvic floor muscle contraction in male subjects

Aim: The primary aim of this study is to demonstrate that 7-tesla functional magnetic resonance imaging (7T-fMRI) can visualize the neural representations of the male pelvic floor in the whole brain of a single subject. Methods: In total, 17 healthy male volunteers (age 20-47) were scanned in a 7T-MRI scanner (Philips Achieva). The scanning protocol consisted of two functional runs using a multiband echo planar imaging sequence and a T1-weighted scan. The subjects executed two motor tasks, one involving consecutive pelvic floor muscle contractions (PFMC) and a control task with tongue movements. Results: In single subjects, results of both tasks were visualized in the cortex, putamen, thalamus, and the cerebellum. Activation was seen during PFMC in the superomedial and inferolateral primary motor cortex (M1), supplementary motor area (SMA), insula, midcingulate gyrus (MCG), putamen, thalamus, and in the anterior and posterior lobes of the cerebellum. During tongue movement, activation was seen in the inferolateral M1, SMA, MCG, putamen, thalamus, and anterior and posterior lobes of the cerebellum. Tongue activation was found in the proximity of, but not overlapping with, the PFMC activation. Connectivity analysis demonstrated differences in neural networks involved in PFMC and tongue movement. Conclusion: This study demonstrated that 7T-fMRI can be used to visualize brain areas involved in pelvic floor control in the whole brain of single subjects and defined the specific brain areas involved in PFMC. Distinct differences between brain mechanisms controlling the pelvic floor and tongue movements were demonstrated using connectivity analysis

Anticipatory grip force control using a cerebellar model.

Grip force modulation has a rich history of research, but the results remain to be integrated as a neurocomputational model and applied in a robotic system. Adaptive grip force control as exhibited by humans would enable robots to handle objects with sufficient yet minimal force, thus minimizing the risk of crushing objects or inadvertently dropping them. We investigated the feasibility of grip force control by means of a biological neural approach to ascertain the possibilities for future application in robotics. As the cerebellum appears crucial for adequate grip force control, we tested a computational model of the olivo-cerebellar system. This model takes into account that the processing of sensory signals introduces a 100 ms delay, and because of this delay, the system needs to learn anticipatory rather than feedback control. For training, we considered three scenarios for feedback information: (1) grip force error estimation, (2) sensory input on deformation of the fingertips, and (3) as a control, noise. The system was trained on a data set consisting of force and acceleration recordings from human test subjects. Our results show that the cerebellar model is capable of learning and performing anticipatory grip force control closely resembling that of human test subjects despite the delay. The system performs best if the delayed feedback signal carries an error estimation, but it can also perform well when sensory data are used instead. Thus, these tests indicate that a cerebellar neural network can indeed serve well in anticipatory grip force control not only in a biological but also in an artificial system

Climbing fiber burst size and olivary sub-threshold oscillations in a network setting.

textabstractThe inferior olivary nucleus provides one of the two main inputs to the cerebellum: the so-called climbing fibers. Activation of climbing fibers is generally believed to be related to timing of motor commands and/or motor learning. Climbing fiber spikes lead to large all-or-none action potentials in cerebellar Purkinje cells, overriding any other ongoing activity and silencing these cells for a brief period of time afterwards. Empirical evidence shows that the climbing fiber can transmit a short burst of spikes as a result of an olivary cell somatic spike, potentially increasing the information being transferred to the cerebellum per climbing fiber activation. Previously reported results from in vitro studies suggested that the information encoded in the climbing fiber burst is related to the occurrence of the spike relative to the ongoing sub-threshold membrane potential oscillation of the olivary cell, i.e. that the phase of the oscillation is reflected in the size of the climbing fiber burst. We used a detailed three-compartmental model of an inferior olivary cell to further investigate the possible factors determining the size of the climbing fiber burst. Our findings suggest that the phase-dependency of the burst size is present but limited and that charge flow between soma and dendrite is a major determinant of the climbing fiber burst. From our findings it follows that phenomena such as cell ensemble synchrony can have a big effect on the climbing fiber burst size through dendrodendritic gap-junctional coupling between olivary cells