Adaptive Local and Global Synchronization and Phase Control of Inferior Olive Neurons (Ions)

Clusters of inferior olive neurons (IONs) in the olive-cerebellar system play an important role in providing synchronized motor control signals for the activation of large number of muscles. However, the dynamics of IONs are highly nonlinear and the system parameters are assumed to be unknowm. The IONs evolving from arbitrary initial conditions are not synchronized. However the application of IONs for control of BAUV\u27s requires that IONs oscillate in unison. The objective is to design control laws such that the controlled ION tracks the trajectories of the reference ION. The two control laws are derived based on tuning functions adaptive method for local and global synchronization. Furthermore, based on L1 adaptive control theory for local and global synchronization is designed. They are completed in two steps of a back stepping design process. Using Lyapunov analysis, it is shown that in the closed-loop system, the controlled ION asymptotically tracks the trajectories of the reference ION. Phase control for the synchronization of IONs based on tuning functions and L1 adaptive control method has been studied. Simulation results are presented to evaluate the performance of each control system designed

Spike-Timing-Based Computation in Sound Localization

Spike timing is precise in the auditory system and it has been argued that it conveys information about auditory stimuli, in particular about the location of a sound source. However, beyond simple time differences, the way in which neurons might extract this information is unclear and the potential computational advantages are unknown. The computational difficulty of this task for an animal is to locate the source of an unexpected sound from two monaural signals that are highly dependent on the unknown source signal. In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. The model was able to accurately estimate the location of previously unknown sounds in both azimuth and elevation (including front/back discrimination) in a known acoustic environment. We found that multiple representations of different acoustic environments could coexist as sets of overlapping neural assemblies which could be associated with spatial locations by Hebbian learning. The model demonstrates the computational relevance of relative spike timing to extract spatial information about sources independently of the source signal

Sensory Prediction or Motor Control? Application of Marr–Albus Type Models of Cerebellar Function to Classical Conditioning

Marr–Albus adaptive filter models of the cerebellum have been applied successfully to a range of sensory and motor control problems. Here we analyze their properties when applied to classical conditioning of the nictitating membrane response in rabbits. We consider a system-level model of eyeblink conditioning based on the anatomy of the eyeblink circuitry, comprising an adaptive filter model of the cerebellum, a comparator model of the inferior olive and a linear dynamic model of the nictitating membrane plant. To our knowledge, this is the first model that explicitly includes all these principal components, in particular the motor plant that is vital for shaping and timing the behavioral response. Model assumptions and parameters were systematically investigated to disambiguate basic computational capacities of the model from features requiring tuning of properties and parameter values. Without such tuning, the model robustly reproduced a range of behaviors related to sensory prediction, by displaying appropriate trial-level associative learning effects for both single and multiple stimuli, including blocking and conditioned inhibition. In contrast, successful reproduction of the real-time motor behavior depended on appropriate specification of the plant, cerebellum and comparator models. Although some of these properties appear consistent with the system biology, fundamental questions remain about how the biological parameters are chosen if the cerebellar microcircuit applies a common computation to many distinct behavioral tasks. It is possible that the response profiles in classical conditioning of the eyeblink depend upon operant contingencies that have previously prevailed, for example in naturally occurring avoidance movements

Adjustment of interaural-time-difference analysis to sound level

To localize low-frequency sound sources in azimuth, the binaural system compares the timing of sound waves at the two ears with microsecond precision. A similarly high precision is also seen in the binaural processing of the envelopes of high-frequency complex sounds. Both for low- and high-frequency sounds, interaural time difference (ITD) acuity is to a large extent independent of sound level. The mechanisms underlying this level-invariant extraction of ITDs by the binaural system are, however, only poorly understood. We use high-frequency pip trains with asymmetric and dichotic pip envelopes in a combined psychophysical, electrophysiological, and modeling approach. Although the dichotic envelopes cannot be physically matched in terms of ITD, the match produced perceptually by humans is very reliable, and it depends systematically on the overall sound level. These data are reflected in neural responses from the gerbil lateral superior olive and lateral lemniscus. The results are predicted in an existing temporal-integration model extended with a level-dependent threshold criterion. These data provide a very sensitive quantification of how the peripheral temporal code is conditioned for binaural analysis

Human interaural time difference thresholds for sine tones: The high-frequency limit

[EN] The smallest detectable interaural time difference (ITD) for sine tones was measured for four human listeners to determine the dependence on tone frequency. At low frequencies, 250 700 Hz, threshold ITDs were approximately inversely proportional to tone frequency. At mid-frequencies, 700 1000 Hz, threshold ITDs were smallest. At high frequencies, above 1000 Hz, thresholds increased faster than exponentially with increasing frequency becoming unmeasurably high justabove 1400 Hz. A model for ITD detection began with a biophysically based computational model for a medial superior olive (MSO) neuron that produced robust ITD responses up to 1000 Hz, and demonstrated a dramatic reduction in ITD-dependence from 1000 to 1500 Hz. Rate-ITD functions from the MSO model became inputs to binaural display models both place based and rate-differ-ence based. A place-based, centroid model with a rigid internal threshold reproduced almost all fea- tures of the human data. A signal-detection version of this model reproduced the high-frequence divergence but badly underestimated low-frequency thresholds. A rate-difference model incorporat- ing fast contralateral inhibition reproduced the major features of the human threshold data except for the divergence. A combined, hybrid model could reproduce all the threshold data.We are grateful to Dr. Les Bernstein for a useful discussion about the centroid display and to Dr. Steve Colburn for discussions about modeling. Zane Crawford provided valuable statistical help. This research was supported by The Vicerectorado de Profesorado y Ordenacion Academica of the Universitat Politecnica de Valencia (Spain), which brought L. D. to Michigan State, by the NIDCD Grant No. DC-00181 and the AFOSR Grant No. 11NL002. A. B. was supported by NIDCD Grant Nos. DC-00100 (H. S. Colburn) and P30-DC04663 (Core Center).Brughera, A.; Dunai ., L.; Hartmann, WM. (2013). Human interaural time difference thresholds for sine tones: The high-frequency limit. The Journal of the Acoustical Society of America. 133(5):2839-2855. https://doi.org/10.1121/1.4795778S28392855133

Predicting lateralization performance at high frequencies from auditory-nerve spike timing

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (leaves 77-82).Psychophysical sensitivity to interaural time differences (ITD) in the envelope of high- frequency sinusoidally amplitude-modulated (SAM) tones is generally poorer than that to low- frequency pure tones (PT). ITD sensitivity at high frequencies might be improved using "transposed stimuli" (TS), which seek to produce the same temporal discharge patters in high- frequency neurons as in low-frequency neurons for PT. Here, we study ITD sensitivity for PT, SAM tones and TS using neurophysiology, psychoacoustics and computational models. Phase locking of auditory-nerve fibers in anesthetized cats was characterized using both the synchronization index and autocorrelograms. With both measures, phase locking is stronger for PT than TS, and for TS than for SAM tones. Phase locking to SAM tones and TS degrades with increasing stimulus level, while remaining more stable for PT. ITD discrimination was measured in humans for stimuli presented either in quiet or with band-reject noise intended to restrict listening to a narrow frequency band. Performance improves slightly with increasing stimulus level for all three stimuli both with and without noise. ITD sensitivity to TS is comparable to PT performance only in the absence of noise. To relate psychophysical performance to auditory-nerve activity, we developed a physiologically-based optimal binaural processor model with delay lines and coincidence detectors. In the no-noise condition, model performance is stable with stimulus level, consistent with psychophysics. However, in the band- reject noise condition, model performance for SAM tones and TS degrades with increasing level. .(cont.) These results have implications for the relative roles of peripheral patterns of activity and the binaural processor in accounting for ITD sensitivity at low versus high frequenciesby Anna Alexandra Dreyer.M.Eng

Harnessing the power of theta: natural manipulations of cognitive performance during hippocampal theta-contingent eyeblink conditioning

Neurobiological oscillations are regarded as essential to normal information processing, including coordination and timing of cells and assemblies within structures as well as in long feedback loops of distributed neural systems. The hippocampal theta rhythm is a 3-12 Hz oscillatory potential observed during cognitive processes ranging from spatial navigation to associative learning. The lower range, 3-7 Hz, can occur during immobility and depends upon the integrity of cholinergic forebrain systems. Several studies have shown that the amount of pre-training theta in the rabbit strongly predicts the acquisition rate of classical eyeblink conditioning and that impairment of this system substantially slows the rate of learning. Our lab has used a brain-computer interface that delivers eyeblink conditioning trials contingent upon the explicit presence or absence of hippocampal theta. A behavioral benefit of theta-contingent training has been demonstrated in both delay and trace forms of the paradigm with a two- to four-fold increase in learning speed. This behavioral effect is accompanied by enhanced amplitude and synchrony of hippocampal local field potentials, multiple-unit excitation, and single-unit response patterns that depend on theta state. Additionally, training in the presence of hippocampal theta has led to increases in the salience of tone-induced unit firing patterns in the medial prefrontal cortex, followed by persistent multi-unit activity during the trace interval. In cerebellum, rhythmicity and precise synchrony of stimulus time-locked local field potentials with those of hippocampus occur preferentially under the theta condition. Here we review these findings, integrate them into current models of hippocampal-dependent learning and suggest how improvement in our understanding of neurobiological oscillations is critical for theories of medial temporal lobe processes underlying intact and pathological learning

Cerebellar Modules and Their Role as Operational Cerebellar Processing Units

The compartmentalization of the cerebellum into modules is often used to discuss its function. What, exactly, can be considered a module, how do they operate, can they be subdivided and do they act individually or in concert are only some of the key questions discussed in this consensus paper. Experts studying cerebellar compartmentalization give their insights on the structure and function of cerebellar modules, with the aim of providing an up-to-date review of the extensive literature on this subject. Starting with an historical perspective indicating that the basis of the modular organization is formed by matching olivocorticonuclear connectivity, this is followed by consideration of anatomical and chemical modular boundaries, revealing a relation between anatomical, chemical, and physiological borders. In addition, the question is asked what the smallest operational unit of the cerebellum might be. Furthermore, it has become clear that chemical diversity of Purkinje cells also results in diversity of information processing between cerebellar modules. An additional important consideration is the relation between modular compartmentalization and the organization of the mossy fiber system, resulting in the concept of modular plasticity. Finally, examination of cerebellar output patterns suggesting cooperation between modules and recent work on modular aspects of emotional behavior are discussed. Despite the general consensus that the cerebellum has a modular organization, many questions remain. The authors hope that this joint review will inspire future cerebellar research so that we are better able to understand how this brain structure makes its vital contribution to behavior in its most general form