The Effect of Slow Electrical Stimuli to Achieve Learning in Cultured Networks of Rat Cortical Neurons

Learning, or more generally, plasticity may be studied using cultured networks of rat cortical neurons on multi electrode arrays. Several protocols have been proposed to affect connectivity in such networks. One of these protocols, proposed by Shahaf and Marom, aimed to train the input-output relationship of a selected connection in a network using slow electrical stimuli. Although the results were quite promising, the experiments appeared difficult to repeat and the training protocol did not serve as a basis for wider investigation yet. Here, we repeated their protocol, and compared our ‘learning curves’ to the original results. Although in some experiments the protocol did not seem to work, we found that on average, the protocol showed a significantly improved stimulus response indeed. Furthermore, the protocol always induced functional connectivity changes that were much larger than changes that occurred after a comparable period of random or no stimulation. Finally, our data shows that stimulation at a fixed electrode induces functional connectivity changes of similar magnitude as stimulation through randomly varied sites; both larger than spontaneous connectivity fluctuations. We concluded that slow electrical stimulation always induced functional connectivity changes, although uncontrolled. The magnitude of change increased when we applied the adaptive (closed-loop) training protocol. We hypothesize that networks develop an equilibrium between connectivity and activity. Induced connectivity changes depend on the combination of applied stimulus and initial connectivity. Plain stimuli may drive networks to the nearest equilibrium that accommodates this input, whereas adaptive stimulation may direct the space for exploration and force networks to a new balance, at a larger distance from the initial state.     

Multiscale modeling of skeletal muscle properties and experimental validations in isometric conditions

In this article, we describe an approach to model the electromechanical behavior of the skeletal muscle based on the Huxley formulation. We propose a model that complies with a well established macroscopic behavior of striated muscles where force-length, force–velocity, and Mirsky–Parmley properties are taken into account. These properties are introduced at the microscopic scale and related to a tentative explanation of the phenomena. The method used integrates behavior ranging from the microscopic to the macroscopic scale, and allows the computation of the dynamics of the output force and stiffness controlled by EMG or stimulation parameters. The model can thus be used to simulate and carry out research to develop control strategies using electrical stimulation in the context of rehabilitation. Finally, through animal experiments, we estimated model parameters using a Sigma Point Kalman Filtering technique and dedicated experimental protocols in isometric conditions and demonstrated that the model can accurately simulate individual variations and thus take into account subject dependent behavior.     

Robust closed-loop control of hypnosis with propofol using WAVCNS index as the controlled variable

This paper presents a robust closed-loop strategy for control of depth of hypnosis. The proposed method regulates the electroencephalogram (EEG)-derived WAV_CNS index as measure of hypnosis by manipulating intravenous propofol administration. In contrast to many existing closed-loop control methods for hypnosis drug delivery, the control design presented in this paper produces stability and robustness against uncertainty by explicitly accounting for the pharmacokinetic (PK) and pharmacodynamic (PD) variability between individuals, as well as the unexpected surgical stimulation and anesthetic–analgesic interaction that the closed-loop control is required to tolerate. This robust closed-loop controller was evaluated in comparison with a heuristically tuned proportional-derivative-integral (PID) controller using a simulated surgical procedure on 44 patients whose PK and PD models were identified using real clinical data. The results demonstrate that the robust control strategy can deliver propofol to yield consistent and acceptable closed-loop induction and maintenance phase responses over wide-ranging PK and PD differences (mean rise and settling times of 4 min and 7 min and mean overshoot of less than 8%, which meets anesthesiologists’ response specifications), whereas its PID control counterpart exhibits limitations in performance.     

Closed-loop deep brain stimulation is superior in ameliorating parkinsonism

Continuous high-frequency deep brain stimulation (DBS) is a widely used therapy for advanced Parkinson's disease (PD) management. However, the mechanisms underlying DBS effects remain enigmatic and are the subject of an ongoing debate. Here, we present and test a closed-loop stimulation strategy for PD in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) primate model of PD. Application of pallidal closed-loop stimulation leads to dissociation between changes in basal ganglia (BG) discharge rates and patterns, providing insights into PD pathophysiology. Furthermore, cortico-pallidal closed-loop stimulation has a significantly greater effect on akinesia and on cortical and pallidal discharge patterns than standard open-loop DBS and matched control stimulation paradigms. Thus, closed-loop DBS paradigms, by modulating pathological oscillatory activity rather than the discharge rate of the BG-cortical networks, may afford more effective management of advanced PD. Such strategies have the potential to be effective in additional brain disorders in which a pathological neuronal discharge pattern can be recognized.     

Delay-Dependent Response in Weakly Electric Fish under Closed-Loop Pulse Stimulation

In this paper, we apply a real time activity-dependent protocol to study how freely swimming weakly electric fish produce and process the timing of their own electric signals. Specifically, we address this study in the elephant fish, Gnathonemus petersii, an animal that uses weak discharges to locate obstacles or food while navigating, as well as for electro-communication with conspecifics. To investigate how the inter pulse intervals vary in response to external stimuli, we compare the response to a simple closed-loop stimulation protocol and the signals generated without electrical stimulation. The activity-dependent stimulation protocol explores different stimulus delivery delays relative to the fish’s own electric discharges. We show that there is a critical time delay in this closed-loop interaction, as the largest changes in inter pulse intervals occur when the stimulation delay is below 100 ms. We also discuss the implications of these findings in the context of information processing in weakly electric fish.     

Grid Support for Collaborative Control Room in Fusion Science

The National Fusion Collaboratory project seeks to enable fusion scientists to exploit Grid capabilities in support of experimental science. To this end we are exploring the concept of a collaborative control room that harnesses Grid and collaborative technologies to provide an environment in which remote experimental devices, codes, and expertise can interact in real time during an experiment. This concept has the potential to make fusion experiments more efficient by enabling researchers to perform more analysis and by engaging more expertise from a geographically distributed team of scientists and resources. As the realities of software development, talent distribution, and budgets increasingly encourage pooling resources and specialization, we see such environments as a necessary tool for future science. In this paper, we describe an experimental mock-up of a remote interaction with the DIII-D control room. The collaborative control room was demonstrated at SC03 and later reviewed at an international ITER Grid Workshop. We describe how the combined effect of various technologies—collaborative, visualization, and Grid—can be used effectively in experimental science. Specifically, we describe the Access Grid, experimental data presentation tools, and agreement-based resource management and workflow systems enabling time-bounded end-to-end application execution. We also report on FusionGrid services whose use during the fusion experimental cycle became possible for the first time thanks to this technology, and we discuss its potential use in future fusion experiments.     

Optimal motor control may mask sensory dynamics

Properties of neural controllers for closed-loop sensorimotor behavior can be inferred with system identification. Under the standard paradigm, the closed-loop system is perturbed (input), measurements are taken (output), and the relationship between input and output reveals features of the system under study. Here we show that under common assumptions made about such systems (e.g. the system implements optimal control with a penalty on mechanical, but not sensory, states) important aspects of the neural controller (its zeros mask the modes of the sensors) remain hidden from standard system identification techniques. Only by perturbing or measuring the closed-loop system “between” the sensor and the control can these features be exposed with closed-loop system identification methods; while uncommon, there exist noninvasive techniques such as galvanic vestibular stimulation that perturb between sensor and controller in this way. This work was supported by the National Science Foundation under Grant No. 0543985, and by the National Institutes of Health under Grant No. 2RO1 NS35070.     

Effect of stimulus parameters in the treatment of seizures by electrical stimulation in the kainate animal model

Preliminary results from animal and clinical studies demonstrate that electrical stimulation of brain structures can reduce seizure frequency in patients with refractory epilepsy. Since most researchers derive stimulation parameters by trial and error, it is unclear what stimulation frequency, amplitude and duration constitutes a set of optimal stimulation parameters for aborting seizure activity in a given patient. In this investigation, we begin to quantify the independent effects of stimulation parameters on electrographic seizures, such that they could be used to develop an efficient closed-loop prosthesis that intervenes before the clinical onset of a seizure and seizure generalization. Biphasic stimulation is manually delivered to the hippocampus in response to a visually detected electrographic seizure. Such focal, responsive stimulation allows for anti-seizure treatment delivery with improved temporal and spatial specificity over conventional open-loop stimulation paradigms, with the possibility of avoiding tissue damage stemming from excessive exposure to electrical stimulation. We retrospectively examine the effects of stimulation frequency (low, medium and high), pulse-width (low and high) and amplitude (low and high) in seizures recorded from 23 kainic acid treated rats. We also consider the effects of total charge delivered and the rate of charge delivery, and identify stimulation parameter sets that induce after-discharges or more seizures. Among the stimulation parameters evaluated, we note 2 major findings. First, stimulation frequency is a key parameter for inhibiting seizure activity; the anti-seizure effect cannot be attributed to only the charge delivered per phase. Second, an after-discharge curve shows that as the frequency and pulse-width of stimulation increases, smaller pulse amplitudes are capable of eliciting an after-discharge. It is expected that stimulation parameter optimization will lead to devices with enhanced treatment efficacies and reduced side-effect profiles, especially when used in conjunction with seizure prediction or detection algorithms in a closed-loop control application.     

Closed-loop estimation of the open-loop carotid sinus baroreflex transfer function for the use of animal experiments in space

In order to develop effective counter measures to cardiovascular maladaptation associated with space flight, it is essential to know how dynamic characteristics of blood pressure regulation are altered in space. The open-loop transfer characteristics of the carotid sinus baroreflex can be divided into the neural arc and peripheral arc transfer functions (Ikeda et al. 1996). The neural arc transfer function represents the dynamic input-output characteristics from arterial pressure (AP) to efferent sympathetic nerve activity (SNA), while the peripheral arc transfer function represents those from SNA to AP. Although AP perturbation according to a white noise sequence can be used to estimate the transfer functions under baroreflex closed-loop conditions (Kwanda et al. 1997), arterial catheter implantation necessary to perturb AP limits the applicability of this method to freely moving animal experiments. To overcome this problem, we explored the closed-loop system identification method using electrical stimulation. We used aortic depressor nerve (ADN) stimulation and rapid pacing (RP) of the heart to perturb the arterial baroreflex system.     

Teaching fluid shifts during orthostasis using a classic paper by Foux et al

Hypovolemic and orthostatic challenge can be simulated in humans by the application of lower body negative pressure (LBNP), because this perturbation leads to peripheral blood pooling and, consequently, central hypovolemia. The classic paper by Foux and colleagues clearly shows the effects of orthostasis simulated by LBNP on fluid shifts and homeostatic mechanisms. The carefully carried out experiments reported in this paper show the interplay between different physiological control systems to ensure blood pressure regulation, failure of which could lead to critical decreases in cerebral blood flow and syncope. Here, a teaching seminar for graduate students is described that is designed in the context of this paper and aimed at allowing students to learn how Foux and colleagues have advanced this field by addressing important aspects of blood regulation. This seminar is also designed to put their research into perspective by including important components of LBNP testing and protocols developed in subsequent research in the field. Learning about comprehensive protocols and carefully controlled studies can reduce confounding variables and allow for an optimal analysis and elucidation of the physiological responses that are being investigated. Finally, in collaboration with researchers in mathematical modeling, in the future, we will incorporate the concepts of applicable mathematical models into our curriculum.     

State Based Model of Long-Term Potentiation and Synaptic Tagging and Capture

Recent data indicate that plasticity protocols have not only synapse-specific but also more widespread effects. In particular, in synaptic tagging and capture (STC), tagged synapses can capture plasticity-related proteins, synthesized in response to strong stimulation of other synapses. This leads to long-lasting modification of only weakly stimulated synapses. Here we present a biophysical model of synaptic plasticity in the hippocampus that incorporates several key results from experiments on STC. The model specifies a set of physical states in which a synapse can exist, together with transition rates that are affected by high- and low-frequency stimulation protocols. In contrast to most standard plasticity models, the model exhibits both early- and late-phase LTP/D, de-potentiation, and STC. As such, it provides a useful starting point for further theoretical work on the role of STC in learning and memory.     

Computer simulation studies and the scientific method

The scientific method is the formal procedure for all acceptable scientific endeavors. With this methodology, there is a continual interaction between theory, in the form of an hypothesis, and objective, experimental analysis. There is a new step in the scientific method that involves the use of computer models and simulation studies. When computer models are incorporated into hypothesis formulation, they can be used in simulation studies to test ideas before they are tried experimentally. An iterative feedback between these tests and current ideas allows for a preliminary refinement of hypotheses and development of more intelligent research protocols. In this way, computer simulation studies can serve as an intermediate step in the scientific method, reducing the number of animals used in biomedical experimentation. In this article we also explore other ways that computer simulation studies could limit the use of animals in biomedical research and education.     

Calcium control of triphasic hippocampal STDP

Synaptic plasticity is believed to represent the neural correlate of mammalian learning and memory function. It has been demonstrated that changes in synaptic conductance can be induced by approximately synchronous pairings of pre- and post- synaptic action potentials delivered at low frequencies. It has also been established that NMDAr-dependent calcium influx into dendritic spines represents a critical signal for plasticity induction, and can account for this spike-timing dependent plasticity (STDP) as well as experimental data obtained using other stimulation protocols. However, subsequent empirical studies have delineated a more complex relationship between spike-timing, firing rate, stimulus duration and post-synaptic bursting in dictating changes in the conductance of hippocampal excitatory synapses. Here, we present a detailed biophysical model of single dendritic spines on a CA1 pyramidal neuron, describe the NMDAr-dependent calcium influx generated by different stimulation protocols, and construct a parsimonious model of calcium driven kinase and phosphatase dynamics that dictate the probability of stochastic transitions between binary synaptic weight states in a Markov model. We subsequently demonstrate that this approach can account for a range of empirical observations regarding the dynamics of synaptic plasticity induced by different stimulation protocols, under regimes of pharmacological blockade and metaplasticity. Finally, we highlight the strengths and weaknesses of this parsimonious, unified computational synaptic plasticity model, discuss differences between the properties of cortical and hippocampal plasticity highlighted by the experimental literature, and the manner in which further empirical and theoretical research might elucidate the cellular basis of mammalian learning and memory function.     

时域相干刺激研究进展

脑深部电刺激已成为许多神经和精神疾病的有效治疗方法。然而,侵入性的电极植入会带来手术并发症的风险,并且刺激靶区在植入后很难改变。经颅磁刺激和经颅电刺激等非侵入性刺激方法为调节大脑功能提供了新的途径。但是,尚未证明这些非侵入性脑刺激方法可以直接调节脑深部神经元活动而不影响皮层神经元。因此,这些方法主要用于调节大脑表层脑区的神经活动。时域相干（temporal interference,TI）刺激是通过两个高频电场相互作用,产生低频包络调节神经活动的一种非侵入式脑深部电刺激的新方法,该方法有望解决无创脑深部刺激的需求。本文首先介绍TI刺激的概念以及安全性,然后阐述TI刺激现有研究中的电场分析方法,并讨论电场分析相关的生理模型建模方法和仿真平台以及TI刺激诱发场分布的研究进展与在动物和人体中的应用进展。最后,本文展望了TI刺激技术未来发展方向,以期为无创脑深部刺激研究提供新的研究思路。     

A Biological Micro Actuator: Graded and Closed-Loop Control of Insect Leg Motion by Electrical Stimulation of Muscles

In this study, a biological microactuator was demonstrated by closed-loop motion control of the front leg of an insect (Mecynorrhina torquata, beetle) via electrical stimulation of the leg muscles. The three antagonistic pairs of muscle groups in the front leg enabled the actuator to have three degrees of freedom: protraction/retraction, levation/depression, and extension/flexion. We observed that the threshold amplitude (voltage) required to elicit leg motions was approximately 1.0 V; thus, we fixed the stimulation amplitude at 1.5 V to ensure a muscle response. The leg motions were finely graded by alternation of the stimulation frequencies: higher stimulation frequencies elicited larger leg angular displacement. A closed-loop control system was then developed, where the stimulation frequency was the manipulated variable for leg-muscle stimulation (output from the final control element to the leg muscle) and the angular displacement of the leg motion was the system response. This closed-loop control system, with an optimized proportional gain and update time, regulated the leg to set at predetermined angular positions. The average electrical stimulation power consumption per muscle group was 148 µW. These findings related to and demonstrations of the leg motion control offer promise for the future development of a reliable, low-power, biological legged machine (i.e., an insect–machine hybrid legged robot).     

Recovery of Dynamics and Function in Spiking Neural Networks with Closed-Loop Control

There is a growing interest in developing novel brain stimulation methods to control disease-related aberrant neural activity and to address basic neuroscience questions. Conventional methods for manipulating brain activity rely on open-loop approaches that usually lead to excessive stimulation and, crucially, do not restore the original computations performed by the network. Thus, they are often accompanied by undesired side-effects. Here, we introduce delayed feedback control (DFC), a conceptually simple but effective method, to control pathological oscillations in spiking neural networks (SNNs). Using mathematical analysis and numerical simulations we show that DFC can restore a wide range of aberrant network dynamics either by suppressing or enhancing synchronous irregular activity. Importantly, DFC, besides steering the system back to a healthy state, also recovers the computations performed by the underlying network. Finally, using our theory we identify the role of single neuron and synapse properties in determining the stability of the closed-loop system.     

A biomechanical model to estimate corrective changes in muscle activation patterns for stroke patients

We have created a model to estimate the corrective changes in muscle activation patterns needed for a person who has had a stroke to walk with an improved gait-nearing that of an unimpaired person. Using this model, we examined how different functional electrical stimulation (FES) protocols would alter gait patterns. The approach is based on an electromyographically (EMG)-driven model to estimate joint moments. Different stimulation protocols were examined, which generated different corrective muscle activation patterns. These approaches grouped the muscles together into flexor and extensor groups (to simulate FES using surface electrodes) or left each muscle to vary independently (to simulate FES using intramuscular electrodes). In addition, we limited the maximal change in muscle activation (to reduce fatigue). We observed that with the two protocols (grouped and ungrouped muscles), the calculated corrective changes in muscle activation yielded improved joint moments nearly matching those of unimpaired subjects. The protocols yielded different muscle activation patterns, which could be selected based on practical condition. These calculated corrective muscle activation changes can be used in studying FES protocols, to determine the feasibility of gait retraining with FES for a given subject and to determine which protocols are most reasonable.     

Optimization of respiratory chain enzymatic assays in muscle for the diagnosis of mitochondrial disorders

The diagnosis of mitochondrial disorders is difficult due to clinical and genetic heterogeneity. Measurements of mitochondrial respiratory chain (RC) enzyme activities are essential for both clinical diagnoses and many basic research questions. Current protocols for RC analysis are not standardized, and so are prone to inter-laboratory variability, and also to biochemical interferences that lead to analytical discrepancies. Moreover, knowledge of the analytical performances of these assays, which is essential to draw meaningful conclusions from the results, is lacking. To understand this variability and to propose possible solutions, we systematically investigated the effect of different homogenization protocols and chemical conditions on RC assays using muscle homogenates. We developed optimized protocols and a novel complex III method with improved sensitivity, precision, and linearity. These methods can be reliably performed on minute muscle samples with a single-wavelength spectrophotometer. Moreover, we measured the variability of the proposed homogenization protocol and we provide a systematic evaluation of each assay's specificity, precision, and linearity. These data will be useful for quality control in both clinical and research laboratories.     

Effect of gonadotrophin dose on oocyte retrieval in superovulated BALB/c mice

Mice are commonly used animal models in reproductive and developmental research. In order to get satisfying results from such experiments, large numbers of ova must be available and this can be achieved by using various ovulation induction protocols. To obtain an optimal response from these stimulation protocols, parameters such as breeding-housing conditions of the animal strains, the best age for superovulation, and type and dose of gonadotrophins must be optimized. The aim of this study was to investigate the impact of exogenous stimulation with increasing amounts of gonadotrophins on the number and quality of oocytes/pre-embryos recovered from outbred BALB/c mice. A dose-response analysis was performed by stimulating prepubescent (21- to 25-day-old) and sexually mature (6 to 8 weeks old) female mice with hMG, which contains equal amounts of follicle-stimulating hormone (FSH) and luteinizing hormone (LH). The stimulation dose contained 5, 10, 15, 20, 25 or 30 IU of FSH/LH. The effect of increasing stimulation was assessed by monitoring the number and maturity of ova recovered from the tubes. The data were analyzed by using a one-way Anova test and student t-test. Increasing stimulation doses in the prepubescent females resulted in an increased number of ova. A maximum of 55 ova per mouse was reached when stimulating with 20 IU of FSH/LH; higher stimulation doses showed no further increase in oocyte recovery. In the prepubescent group, a maximal number of recovered mature ova was reached with 15 IU of FSH/LH. In the sexually mature female group, 20 IU of FSH/LH gave the best quantitative and qualitative results. Positive effects of copulation on the number and maturity of oocytes in all induction doses were more evident in the prepubescent females and these parameters were significantly more improved (P < 0.05) in this group when compared to the pubertal females. Our findings led to the conclusion that ovulation induction of prepubescent outbred BALB/c mice with 15 IU FSH/LH and sexually mature ones with 20 IU FSH/LH give the best results in terms of oocyte number and maturity.     

Amplification protocols introduce systematic but reproducible errors into gene expression studies

The desire to perform microarray experiments with small starting amounts of RNA has led to the development of a variety of protocols for preparing and amplifying mRNA. This has consequences not only for the standardization of experimental design, but also for reproducibility and comparability between experiments. Here we investigate the differences between the Affymetrix standard and small sample protocols and address the data analysis issues that arise when comparing samples and experiments that have been processed in different ways. We show that data generated on the same platform using different protocols are not directly comparable. Further, protocols introduce systematic biases that can be largely accounted for by using the correct data analysis techniques.