An integrated neuromechanical model of the mouse to study neural control of locomotion

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P7

Comparative investigation of control mechanisms for turning during quadrupedal robot locomotion

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P

The Functional Role of Striatal Cholinergic Interneurons in Reinforcement Learning From Computational Perspective

In this study, we explore the functional role of striatal cholinergic interneurons, hereinafter referred to as tonically active neurons (TANs), via computational modeling; specifically, we investigate the mechanistic relationship between TAN activity and dopamine variations and how changes in this relationship affect reinforcement learning in the striatum. TANs pause their tonic firing activity after excitatory stimuli from thalamic and cortical neurons in response to a sensory event or reward information. During the pause striatal dopamine concentration excursions are observed. However, functional interactions between the TAN pause and striatal dopamine release are poorly understood. Here we propose a TAN activity-dopamine relationship model and demonstrate that the TAN pause is likely a time window to gate phasic dopamine release and dopamine variations reciprocally modulate the TAN pause duration. Furthermore, this model is integrated into our previously published model of reward-based motor adaptation to demonstrate how phasic dopamine release is gated by the TAN pause to deliver reward information for reinforcement learning in a timely manner. We also show how TAN-dopamine interactions are affected by striatal dopamine deficiency to produce poor performance of motor adaptation

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Zero Kinetic Energy Spectroscopy: Mass-Analyzed Threshold Ionization Spectra of Chromium Sandwich Complexes with Alkylbenzenes, (η6-RPh)2Cr (R = Me, Et, i-Pr, t-Bu)

For over 25 years zero kinetic energy (ZEKE) spectroscopy has yielded a rich foundation of high-resolution results of molecular ions. This was based on the discovery in the late 60's of long-lived ion states throughout the ionization continuum of molecular ions. Here, an example is chosen from another fundamental system pioneered at this university. The mass-analyzed threshold ionization (MATI) spectra of jet-cooled chromium bisarene complexes (eta(6)-RPh)(2)Cr (R = Me (1), Et (2), i-Pr (3), and t-Bu (4)) have been measured and interpreted on the basis of DFT calculations. The MATI spectra of complexes 1 and 2 appear to reveal features arising from ionizations of the isomers formed by the rotation of one arene ring relative to the other. The 1 and 2 MATI spectra show two intense peaks corresponding to the 0(0)(0) ionizations with inverse intensity ratios. As indicated by the DFT calculations, the intensity ratio change on going from 1 to 2 results from different isomers contributing to each MATI peak. The ionization energies corresponding to the 0(0)(0) peaks are 42746 +/- 5 and 42809 +/- 5 cm(-1) for compound 1 and 42379 +/- 5 and 42463 5 cm-1 for complex 2. The 1 and 2 spectra show also the weaker features representing transitions to the vibrationally excited cationic levels, the signals of individual rotamers being detected and assigned on the basis of calculated vibrational frequencies. The MATI spectra of compounds 3 and 4 reveal only one strong peak because of close ionization potentials of the isomers contributing to the MATI signal. The 3 and 4 ionization energies are 42104 +/- 5 and 41917 +/- 5 cm(-1), respectively. The precise values of ionization energies obtained from the MATI spectra reveal a nonlinear dependence of the IE on the number of Me groups in the alkyl substituents of (eta(6)-RPh)(2)Cr. This can be explained by an increase in the molecular zero point energies on methylation of the substituents

The interplay between cerebellum and basal ganglia in motor adaptation: A modeling study

Motor adaptation to perturbations is provided by learning mechanisms operating in the cerebellum and basal ganglia. The cerebellum normally performs motor adaptation through supervised learning using information about movement error provided by visual feedback. However, if visual feedback is critically distorted, the system may disengage cerebellar error-based learning and switch to reinforcement learning mechanisms mediated by basal ganglia. Yet, the exact conditions and mechanisms of cerebellum and basal ganglia involvement in motor adaptation remain unknown. We use mathematical modeling to simulate control of planar reaching movements that relies on both error-based and non-error-based learning mechanisms. We show that for learning to be efficient only one of these mechanisms should be active at a time. We suggest that switching between the mechanisms is provided by a special circuit that effectively suppresses the learning process in one structure and enables it in the other. To do so, this circuit modulates learning rate in the cerebellum and dopamine release in basal ganglia depending on error-based learning efficiency. We use the model to explain and interpret experimental data on error- and non-error-based motor adaptation under different conditions