Lamb Temporal Bone as a Surgical Training Model of Round Window Cochlear Implant Electrode Insertion

OBJECTIVE The preservation of residual hearing in cochlear implantation opens the door for optimal functional results. This atraumatic surgical technique requires training; however, the traditional human cadaveric temporal bones have become less available or unattainable in some institutions. This study investigates the suitability of an alternative model, using cadaveric lamb temporal bone, for surgical training of atraumatic round window electrode insertion. INTERVENTION A total of 14 lamb temporal bones were dissected for cochlear implantation by four surgeons. After mastoidectomy, visualization, and drilling of the round window niche, an atraumatic round window insertion of a Medel Flex24 electrode was performed. Electrode insertion depth and position were verified by computed tomography scans. MAIN OUTCOME MEASURE All cochleas were successfully implanted using the atraumatic round window approach; however, surgical access through the mastoid was substantially different when compared human anatomy. The mean number of intracochlear electrode contacts was 6.5 (range, 4-11) and the mean insertion depth 10.4 mm (range, 4-20 mm), which corresponds to a mean angular perimodiolar insertion depth of 229 degrees (range 67-540°). Full insertion of the electrode was not possible because of the smaller size of the lamb cochlea in comparison to that of the human. CONCLUSION The lamb temporal bone model is well suited as a training model for atraumatic cochlear implantation at the level of the round window. The minimally pneumatized mastoid as well as the smaller cochlea can help prepare a surgeon for difficult cochlear implantations. Because of substantial differences to human anatomy, it is not an adequate training model for other surgical techniques such as mastoidectomy and posterior tympanotomy as well as full electrode insertion.

Comparison of the effects of the alpha-2 agonists detomidine, romifidine and xylazine on nociceptive withdrawal reflex and temporal summation in horses

OBJECTIVE: To evaluate and compare the antinociceptive effects of the three alpha-2 agonists, detomidine, romifidine and xylazine at doses considered equipotent for sedation, using the nociceptive withdrawal reflex (NWR) and temporal summation model in standing horses. STUDY DESIGN: Prospective, blinded, randomized cross-over study. ANIMALS: Ten healthy adult horses weighing 527-645 kg and aged 11-21 years old. METHODS: Electrical stimulation was applied to the digital nerves to evoke NWR and temporal summation in the left thoracic limb and pelvic limb of each horse. Electromyographic reflex activity was recorded from the common digital extensor and the cranial tibial muscles. After baseline measurements a single bolus dose of detomidine, 0.02 mg kg(-1), romifidine 0.08 mg kg(-1), or xylazine, 1 mg kg(-1), was administered intravenously (IV). Determinations of NWR and temporal summation thresholds were repeated at 10, 20, 30, 40, 60, 70, 90, 100, 120 and 130 minutes after test-drug administration alternating the thoracic limb and the pelvic limb. Depth of sedation was assessed before measurements at each time point. Behavioural reaction was observed and recorded following each stimulation. RESULTS: The administration of detomidine, romifidine and xylazine significantly increased the current intensities necessary to evoke NWR and temporal summation in thoracic limbs and pelvic limbs of all horses compared with baseline. Xylazine increased NWR thresholds over baseline values for 60 minutes, while detomidine and romifidine increased NWR thresholds over baseline for 100 and 120 minutes, respectively. Temporal summation thresholds were significantly increased for 40, 70 and 130 minutes after xylazine, detomidine and romifidine, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: Detomidine, romifidine and xylazine, administered IV at doses considered equipotent for sedation, significantly increased NWR and temporal summation thresholds, used as a measure of antinociceptive activity. The extent of maximal increase of NWR and temporal summation thresholds was comparable, while the duration of action was drug-specific.

Spastin in the human and mouse central nervous system with special reference to its expression in the hippocampus of mouse pilocarpine model of status epilepticus and temporal lobe epilepsy

In the present in situ hybridization and immunocytochemical studies in the mouse central nervous system (CNS), a strong expression of spastin mRNA and protein was found in Purkinje cells and dentate nucleus in the cerebellum, in hippocampal principal cells and hilar neurons, in amygdala, substantia nigra, striatum, in the motor nuclei of the cranial nerves and in different layers of the cerebral cortex except piriform and entorhinal cortices where only neurons in layer II were strongly stained. Spastin protein and mRNA were weakly expressed in most of the thalamic nuclei. In selected human brain regions such as the cerebral cortex, cerebellum, hippocampus, amygdala, substania nigra and striatum, similar results were obtained. Electron microscopy showed spastin immunopositive staining in the cytoplasma, dendrites, axon terminals and nucleus. In the mouse pilocarpine model of status epilepticus and subsequent temporal lobe epilepsy, spastin expression disappeared in hilar neurons as early as at 2h during pilocarpine induced status epilepticus, and never recovered. At 7 days and 2 months after pilocarpine induced status epilepticus, spastin expression was down-regulated in granule cells in the dentate gyrus, but induced expression was found in reactive astrocytes. The demonstration of widespread distribution of spastin in functionally different brain regions in the present study may provide neuroanatomical basis to explain why different neurological, psychological disorders and cognitive impairment occur in patients with spastin mutation. Down-regulation or loss of spastin expression in hilar neurons may be related to their degeneration and may therefore initiate epileptogenetic events, leading to temporal lobe epilepsy.

Human temporal bones versus mechanical model to evaluate three middle ear transducers

A life-size mechanical middle ear model and human temporal bones were used to evaluate three different middle ear transducers for implantable hearing aids: the driving rod transducer (DRT), the floating mass transducer (FMT) or vibrant sound bridge, and the contactless transducer (CLT). Results of the experiments with the mechanical model were within the range of the results for human temporal bones. However, results with the mechanical model showed better reproducibility. The handling of the mechanical model was considerably simpler and less time-consuming. Systematic variations of mounting parameters showed that the angle of the rod has virtually no effect on the output of the DRT, the mass loading on the cable of the FMT has a larger impact on the output than does the tightness of crimping, and the output level of the CLT can be increased by 10 dB by optimizing the mounting parameters.

Analyzing spatio-temporal patterns of genuine cross-correlations

In multivariate time series analysis, the equal-time cross-correlation is a classic and computationally efficient measure for quantifying linear interrelations between data channels. When the cross-correlation coefficient is estimated using a finite amount of data points, its non-random part may be strongly contaminated by a sizable random contribution, such that no reliable conclusion can be drawn about genuine mutual interdependencies. The random correlations are determined by the signals' frequency content and the amount of data points used. Here, we introduce adjusted correlation matrices that can be employed to disentangle random from non-random contributions to each matrix element independently of the signal frequencies. Extending our previous work these matrices allow analyzing spatial patterns of genuine cross-correlation in multivariate data regardless of confounding influences. The performance is illustrated by example of model systems with known interdependence patterns. Finally, we apply the methods to electroencephalographic (EEG) data with epileptic seizure activity.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

Spatio-temporal credit assignment in population learning

We present a model for plasticity induction in reinforcement learning which is based on a cascade of synaptic memory traces. In the cascade of these so called eligibility traces presynaptic input is first corre lated with postsynaptic events, next with the behavioral decisions and finally with the external reinforcement. A population of leaky integrate and fire neurons endowed with this plasticity scheme is studied by simulation on different tasks. For operant co nditioning with delayed reinforcement, learning succeeds even when the delay is so large that the delivered reward reflects the appropriateness, not of the immediately preceeding response, but of a decision made earlier on in the stimulus - decision sequence . So the proposed model does not rely on the temporal contiguity between decision and pertinent reward and thus provides a viable means of addressing the temporal credit assignment problem. In the same task, learning speeds up with increasing population si ze, showing that the plasticity cascade simultaneously addresses the spatial problem of assigning credit to the different population neurons. Simulations on other task such as sequential decision making serve to highlight the robustness of the proposed sch eme and, further, contrast its performance to that of temporal difference based approaches to reinforcement learning.

An insulin infusion advisory system based on autotuning nonlinear model-predictive control

This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.

Spatio-Temporal Credit Assignment in Neuronal Population Learning

n learning from trial and error, animals need to relate behavioral decisions to environmental reinforcement even though it may be difficult to assign credit to a particular decision when outcomes are uncertain or subject to delays. When considering the biophysical basis of learning, the credit-assignment problem is compounded because the behavioral decisions themselves result from the spatio-temporal aggregation of many synaptic releases. We present a model of plasticity induction for reinforcement learning in a population of leaky integrate and fire neurons which is based on a cascade of synaptic memory traces. Each synaptic cascade correlates presynaptic input first with postsynaptic events, next with the behavioral decisions and finally with external reinforcement. For operant conditioning, learning succeeds even when reinforcement is delivered with a delay so large that temporal contiguity between decision and pertinent reward is lost due to intervening decisions which are themselves subject to delayed reinforcement. This shows that the model provides a viable mechanism for temporal credit assignment. Further, learning speeds up with increasing population size, so the plasticity cascade simultaneously addresses the spatial problem of assigning credit to synapses in different population neurons. Simulations on other tasks, such as sequential decision making, serve to contrast the performance of the proposed scheme to that of temporal difference-based learning. We argue that, due to their comparative robustness, synaptic plasticity cascades are attractive basic models of reinforcement learning in the brain.

Brain infiltration of leukocytes contributes to the pathophysiology of temporal lobe epilepsy

Clinical and experimental evidence indicates that inflammatory processes contribute to the pathophysiology of epilepsy, but underlying mechanisms remain mostly unknown. Using immunohistochemistry for CD45 (common leukocyte antigen) and CD3 (T-lymphocytes), we show here microglial activation and infiltration of leukocytes in sclerotic tissue from patients with mesial temporal lobe epilepsy (TLE), as well as in a model of TLE (intrahippocampal kainic acid injection), characterized by spontaneous, nonconvulsive focal seizures. Using specific markers of lymphocytes, microglia, macrophages, and neutrophils in kainate-treated mice, we investigated with pharmacological and genetic approaches the contribution of innate and adaptive immunity to kainate-induced inflammation and neurodegeneration. Furthermore, we used EEG analysis in mutant mice lacking specific subsets of lymphocytes to explore the significance of inflammatory processes for epileptogenesis. Blood-brain barrier disruption and neurodegeneration in the kainate-lesioned hippocampus were accompanied by sustained ICAM-1 upregulation, microglial cell activation, and infiltration of CD3(+) T-cells. Moreover, macrophage infiltration was observed, selectively in the dentate gyrus where prominent granule cell dispersion was evident. Unexpectedly, depletion of peripheral macrophages by systemic clodronate liposome administration affected granule cell survival. Neurodegeneration was aggravated in kainate-lesioned mice lacking T- and B-cells (RAG1-knock-out), because of delayed invasion by Gr-1(+) neutrophils. Most strikingly, these mutant mice exhibited early onset of spontaneous recurrent seizures, suggesting a strong impact of immune-mediated responses on network excitability. Together, the concerted action of adaptive and innate immunity triggered locally by intrahippocampal kainate injection contributes seizure-suppressant and neuroprotective effects, shedding new light on neuroimmune interactions in temporal lobe epilepsy.

Self-organised transients in a neural mass model of epileptogenic tissue dynamics

Stimulation of human epileptic tissue can induce rhythmic, self-terminating responses on the EEG or ECoG. These responses play a potentially important role in localising tissue involved in the generation of seizure activity, yet the underlying mechanisms are unknown. However, in vitro evidence suggests that self-terminating oscillations in nervous tissue are underpinned by non-trivial spatio-temporal dynamics in an excitable medium. In this study, we investigate this hypothesis in spatial extensions to a neural mass model for epileptiform dynamics. We demonstrate that spatial extensions to this model in one and two dimensions display propagating travelling waves but also more complex transient dynamics in response to local perturbations. The neural mass formulation with local excitatory and inhibitory circuits, allows the direct incorporation of spatially distributed, functional heterogeneities into the model. We show that such heterogeneities can lead to prolonged reverberating responses to a single pulse perturbation, depending upon the location at which the stimulus is delivered. This leads to the hypothesis that prolonged rhythmic responses to local stimulation in epileptogenic tissue result from repeated self-excitation of regions of tissue with diminished inhibitory capabilities. Combined with previous models of the dynamics of focal seizures this macroscopic framework is a first step towards an explicit spatial formulation of the concept of the epileptogenic zone. Ultimately, an improved understanding of the pathophysiologic mechanisms of the epileptogenic zone will help to improve diagnostic and therapeutic measures for treating epilepsy.

Differences between RNA and DNA due to RNA editing in temporal lobe epilepsy

To investigate whether alterations in RNA editing (an enzymatic base-specific change to the RNA sequence during primary transcript formation from DNA) of neurotransmitter receptor genes and of transmembrane ion channel genes play a role in human temporal lobe epilepsy (TLE), this exploratory study analyzed 14 known cerebral editing sites in RNA extracted from the brain tissue of 41 patients who underwent surgery for mesial TLE, 23 with hippocampal sclerosis (MTLE+HS). Because intraoperatively sampled RNA cannot be obtained from healthy controls and the best feasible control is identically sampled RNA from patients with a clinically shorter history of epilepsy, the primary aim of the study was to assess the correlation between epilepsy duration and RNA editing in the homogenous group of MTLE+HS. At the functionally relevant I/V site of the voltage-gated potassium channel Kv1.1, an inverse correlation of RNA editing was found with epilepsy duration (r=-0.52, p=0.01) but not with patient age at surgery, suggesting a specific association with either the epileptic process itself or its antiepileptic medication history. No significant correlations were found between RNA editing and clinical parameters at other sites within glutamate receptor or serotonin 2C receptor gene transcripts. An "all-or-none" (≥95% or ≤5%) editing pattern at most or all sites was discovered in 2 patients. As a secondary part of the study, RNA editing was also analyzed as in the previous literature where up to now, few single editing sites were compared with differently obtained RNA from inhomogenous patient groups and autopsies, and by measuring editing changes in our mouse model. The present screening study is first to identify an editing site correlating with a clinical parameter, and to also provide an estimate of the possible effect size at other sites, which is a prerequisite for power analysis needed in planning future studies.