Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation.

The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. The present paper focuses on ischemic stroke. We first review accumulating observations of traveling waves occurring spontaneously or triggered by external stimuli in healthy subjects as well as in patients with brain disorders. We examine the putative functions of these waves and focus on post-stroke aphasia observed when brain language networks become fragmented and/or partly silent, thus perturbing the progression of traveling waves across perilesional areas. Secondly, we focus on a simplified model based on the current literature in the field and describe cortical traveling wave dynamics and their modulation. This model uses a biophysically realistic integro-differential equation describing spatially distributed and synaptically coupled neural networks producing traveling wave solutions. The model is used to calculate wave parameters (speed, amplitude and/or frequency) and to guide the reconstruction of the perturbed wave. A stimulation term is included in the model to restore wave propagation to a reasonably good level. Thirdly, we examine various issues related to the implementation model-guided neuromodulation in the treatment of post-stroke aphasia given that closed-loop invasive brain stimulation studies have recently produced encouraging results. Finally, we suggest that modulating traveling waves by acting selectively and dynamically across space and time to facilitate wave propagation is a promising therapeutic strategy especially at a time when a new generation of closed-loop cortical stimulation systems is about to arrive on the market.

The use of neurocomputational models as alternatives to animal models in the development of electrical brain stimulation treatments.

Recent publications call for more animal models to be used and more experiments to be performed, in order to better understand the mechanisms of neurodegenerative disorders, to improve human health, and to develop new brain stimulation treatments. In response to these calls, some limitations of the current animal models are examined by using Deep Brain Stimulation (DBS) in Parkinson's disease as an illustrative example. Without focusing on the arguments for or against animal experimentation, or on the history of DBS, the present paper argues that given recent technological and theoretical advances, the time has come to consider bioinspired computational modelling as a valid alternative to animal models, in order to design the next generation of human brain stimulation treatments. However, before computational neuroscience is fully integrated in the translational process and used as a substitute for animal models, several obstacles need to be overcome. These obstacles are examined in the context of institutional, financial, technological and behavioural lock-in. Recommendations include encouraging agreement to change long-term habitual practices, explaining what alternative models can achieve, considering economic stakes, simplifying administrative and regulatory constraints, and carefully examining possible conflicts of interest.

Closed-loop cortical neuromodulation in Parkinson's disease: An alternative to deep brain stimulation?

Deep brain stimulation (DBS) is usually performed to treat advanced Parkinson's disease (PD) patients with electrodes permanently implanted in basal ganglia while the stimulator delivers electrical impulses continuously and independently of any feedback (open-loop stimulation). Conversely, in closed-loop stimulation, electrical stimulation is delivered as a function of neuronal activities recorded and analyzed online. There is an emerging development of closed-loop DBS in the treatment of PD and a growing discussion about proposing cortical stimulation rather than DBS for this purpose. Why does it make sense to "close the loop" to treat parkinsonian symptoms? Could closed-loop stimulation applied to the cortex become a valuable therapeutic strategy for PD? Can mathematical modeling contribute to the development of this technique? We review the various evidences in favor of the use of closed-loop cortical stimulation for the treatment of advanced PD, as an emerging technique which might offer substantial clinical benefits for PD patients.

Using "smart stimulators" to treat Parkinson's disease: re-engineering neurostimulation devices.

Let's imagine the cruise control of your car locked at 120 km/h on any road in any condition (city, country, highway, sunny or rainy weather), or your car air conditioner set on maximum cold in any temperature condition (even during a snowy winter): would you find it efficient? That would probably not be the most optimal strategy for a proper and comfortable driving experience. As surprising as this may seem, this is a pretty accurate illustration of how deep brain stimulation is used today to treat Parkinson's disease motor symptoms and other neurological disorders such as essential tremor, obsessive-compulsive disorder, or epilepsy.

Model-driven therapeutic treatment of neurological disorders: reshaping brain rhythms with neuromodulation.

Electric stimulation has been investigated for several decades to treat, with various degrees of success, a broad spectrum of neurological disorders. Historically, the development of these methods has been largely empirical but has led to a remarkably efficient, yet invasive treatment: deep brain stimulation (DBS). However, the efficiency of DBS is limited by our lack of understanding of the underlying physiological mechanisms and by the complex relationship existing between brain processing and behaviour. Biophysical modelling of brain activity, describing multi-scale spatio-temporal patterns of neuronal activity using a mathematical model and taking into account the physical properties of brain tissue, represents one way to fill this gap. In this review, we illustrate how biophysical modelling is beginning to emerge as a driving force orienting the development of innovative brain stimulation methods that may move DBS forward. We present examples of modelling works that have provided fruitful insights in regards to DBS underlying mechanisms, and others that also suggest potential improvements for this neurosurgical procedure. The reviewed literature emphasizes that biophysical modelling is a valuable tool to assist a rational development of electrical and/or magnetic brain stimulation methods tailored to both the disease and the patient's characteristics.

Using a virtual cortical module implementing a neural field model to modulate brain rhythms in Parkinson's disease.

We propose a new method for selective modulation of cortical rhythms based on neural field theory, in which the activity of a cortical area is extensively monitored using a two-dimensional microelectrode array. The example of Parkinson's disease illustrates the proposed method, in which a neural field model is assumed to accurately describe experimentally recorded activity. In addition, we propose a new closed-loop stimulation signal that is both space- and time- dependent. This method is especially designed to specifically modulate a targeted brain rhythm, without interfering with other rhythms. A new class of neuroprosthetic devices is also proposed, in which the multielectrode array is seen as an artificial neural network interacting with biological tissue. Such a bio-inspired approach may provide a solution to optimize interactions between the stimulation device and the cortex aiming to attenuate or augment specific cortical rhythms. The next step will be to validate this new approach experimentally in patients with Parkinson's disease.

Delayed and lasting effects of deep brain stimulation on locomotion in Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by a variety of motor signs affecting gait, postural stability, and tremor. These symptoms can be improved when electrodes are implanted in deep brain structures and electrical stimulation is delivered chronically at high frequency (>100 Hz). Deep brain stimulation (DBS) onset or cessation affects PD signs with different latencies, and the long-term improvements of symptoms affecting the body axis and those affecting the limbs vary in duration. Interestingly, these effects have not been systematically analyzed and modeled. We compare these timing phenomena in relation to one axial (i.e., locomotion) and one distal (i.e., tremor) signs. We suggest that during DBS, these symptoms are improved by different network mechanisms operating at multiple time scales. Locomotion improvement may involve a delayed plastic reorganization, which takes hours to develop, whereas rest tremor is probably alleviated by an almost instantaneous desynchronization of neural activity in subcortical structures. Even if all PD patients develop both distal and axial symptoms sooner or later, current computational models of locomotion and rest tremor are separate. Furthermore, a few computational models of locomotion focus on PD and none exploring the effect of DBS was found in the literature. We, therefore, discuss a model of a neuronal network during DBS, general enough to explore the subcircuits controlling locomotion and rest tremor simultaneously. This model accounts for synchronization and plasticity, two mechanisms that are believed to underlie the two types of symptoms analyzed. We suggest that a hysteretic effect caused by DBS-induced plasticity and synchronization modulation contributes to the different therapeutic latencies observed. Such a comprehensive, generic computational model of DBS effects, incorporating these timing phenomena, should assist in developing a more efficient, faster, durable treatment of distal and axial signs in PD.

Linking brain dynamics, neural mechanisms, and deep brain stimulation in Parkinson's disease: an integrated perspective.

Parkinson's disease (PD) is a neurodegenerative disease as well as a dynamical disease. Its symptoms can be alleviated by high-frequency deep brain stimulation (DBS), which has become standard therapeutic strategy for about two decades. Today, the subthalamic nucleus (STN) is the preferred target for DBS in PD. The physiological mechanisms underlying the effects of this procedure are still far from clear, and several hypotheses have been proposed to explain the effect of DBS. However, no consensus has yet been reached. In this review paper, existing interpretations of DBS effects during STN stimulation in PD are examined. Based on results of a population-based computational model, we argue that the alleviation of PD symptoms originates in the functional decoupling of neurons in the stimulated area. This mechanism, which we call stimulation-induced functional decoupling (SIFD), is then tested against various observations, paradoxes, and modeling results. Finally, we suggest that current hypotheses indeed reflect various facets of SIFD and the resonant properties of STN neurons. This review is the first to propose an explanation of the effects of DBS by integrating and building bridges across several levels of description, including synapses, neuron population, and population network.

Quantitative assessment of neuromotor function in workers with current low exposure to mercury vapor.

Evaluation of neuromotor function has been used in several epidemiological studies of workers with long-term exposure to mercury vapor (Hg 0). Some recent studies indicate adverse effects at relatively low exposure levels. In the present study, we used sensitive quantitative methods, developed specifically to detect subtle effects of exposure to toxins on motor function. After exclusion of individuals with neurological diseases or other conditions that may affect performance, 43 chloralkali workers with current low exposure to Hg 0, and 22 age-matched referents remained for further analysis. The median urinary mercury concentration in exposed workers was 5.9 microg/g (range 1.3-25) creatinine (microg/gC), while that in referents was 0.7 microg/gC (range 0.2-4.1). The mean exposure time was 15 years, and the median cumulative mercury index was 161 years x microg/gC in exposed workers. A eurythmokinesimeter (EKM) was used to quantify eye-hand coordination, and a diadochokinesimeter, to measure rapid alternating rotation of the forearms. In general, the differences in performance between the exposed workers and the referents were small. Age was associated with a decrease in speed, more tremor, and longer contact duration between the stylus and the metal targets in performance of rapid pointing movements. Smokers had significantly more tremor, and more contacts per event in the EKM test, than nonsmokers. Taking age, shift work, and smoking habits into account, no significant associations with current or cumulative mercury exposure were found for the majority of the outcome variables from the quantitative tests. In general, this study indicates no significant adverse effects of Hg 0 on neuromotor function at the exposure levels studied.

Postural sway and effect of levodopa in early Parkinson's disease.

OBJECTIVE: To characterize postural stability control and levodopa responsiveness in early Parkinson's disease (PD). METHODS: Postural sway was studied during quiet stance in ten patients within six years of PD onset, both before (OFF) and after (ON) regular oral levodopa dosing. Postural sway was recorded using a force platform during 30 sec with eyes open, and six dependent variables were examined. RESULTS: Mild baseline subclinical changes in postural sway were recorded in our patients. Clear benefit was observed in five out of six characteristics (mean sway, transversal sway, sagittal sway, sway intensity, and sway area) in the ON condition. CONCLUSION: Postural control mechanisms are affected early in PD and modulated by dopamine.

Statistical determination of the optimal subthalamic nucleus stimulation site in patients with Parkinson disease.

OBJECT: The subthalamic nucleus (STN) is currently recognized as the preferred target for deep brain stimulation (DBS) in patients with Parkinson disease (PD). If there is agreement in the literature that DBS improves motor symptoms significantly, the situation is less clear with respect to the side effects of this procedure. The goal of this study was to correlate the coordinate values of active electrode contacts with the amplitude of residual clinical symptoms and side effects using a mathematical approach. METHODS: In this study the investigators examined a cohort of 41 patients with PD who received clinical benefits from DBS after stimulating electrodes had been implanted bilaterally into the STN. The combined scores of residual clinical symptoms plus side effects, including speech disturbance, postural instability, and weight gain, were fitted by using either inverted ellipsoidal exponefitials or smooth splines. These analyses showed evidence of lower combined scores for stimulating contacts at an x coordinate approximately 12.0 to 12.3 mm lateral to the anterior commissure-posterior commissure (AC-PC) line and at a z coordinate approximately 3.1 to 3.3 mm under the AC-PC line. There was insufficient evidence for a preferred y coordinate location. CONCLUSIONS: The authors propose a "best" therapeutic ellipse area that is centered at an x, z location of 12.5 mm, -3.3 mm and characterized by an extension of 1.85 mm in the x direction and 2.22 mm in the z direction. Therapeutic electrode contacts located within this area are well correlated with the lowest occurrence of residual symptoms and the lowest occurrence of side effects independent of STN anatomical considerations. The lack of a significant result in the y direction remains to be explored further.

Development and validation of a neural population model based on the dynamics of a discontinuous membrane potential neuron model.

The major goal of this study was to develop a population density based model derived from statistical mechanics based on the dynamics of a discontinuous membrane potential neuron model. A secondary goal was to validate this model by comparing results from a direct simulation approach on the one hand and our population based approach on the other hand. Comparisons between the two approaches in the case of a synaptically uncoupled and a synaptically coupled neural population produced satisfactory qualitative agreement in terms of firing rate and mean membrane potential. Reasonable quantitative agreement was also obtained for these variables in performed simulations. The results of this work based on the dynamics of a discontinuous membrane potential neuron model provide a basis to simulate phenomenologically large-scale neuronal networks with a reasonably short computing time.

Quantitative tremor assessment in workers with current low exposure to mercury vapor.

Measurement of tremor has been used in several occupational studies of workers with long-term exposure to mercury vapor (Hg(0)). Recent studies indicate an adverse effect even at relatively low exposure levels. In the present study, we used sensitive quantitative methods to assess tremor in chloralkali workers with current low exposure to Hg(0). Neurological examinations and recordings of tremor using both an accelerometer and a laser-based system were conducted in 43 mercury-exposed workers and 22 age-matched referents. The median urinary mercury concentration in exposed workers was 5.9 (1.3-25) microg/g creatinine (microg/gC), while it was 0.7 (0.2-4.1) microg/gC in referents. The mean exposure time was 15 years, and the median cumulative mercury index was 161 years x microg/gC in exposed workers. There were no differences between the exposed workers and the referents in the clinical evaluation of tremor. In the quantitative tremor tests, no associations were found with current or cumulative mercury exposure for the majority of tremor measures. There were indications that exposure to Hg(0) was associated with a lowering of tremor frequency in the non-dominant hand, and a possible interaction with smoking. The differences were small, however, and overall, this study indicates no significant adverse effects on tremor at these exposure levels.

Individual subject sensitivity to extremely low frequency magnetic field.

It is becoming important to specify the smallest effects of extremely low frequency (ELF) magnetic fields (MF) on human physiology. One difficulty is that some people seem more sensitive and more responsive than others to MF exposure. Consequently, within- and between-subject differences have to be taken into account when evaluating these effects. As shown in previous work, human postural tremor is sensitive to MF exposure. But data about individual responses have not been examined in detail. Thus, postural tremor of 24 subjects was evaluated under ELF MF "on" and "off" conditions in a double-blind real/sham exposure protocol. The direction of the tremor changes was analyzed individually for three tremor characteristics. Results showed that subjects with high amplitude tremor seem to be more responsive to MF exposure. MF had an instantaneous effect (between "on" and "off" conditions) and also a more delayed and persistent one (between real and sham conditions), but differences were small. Moreover, due to the within- and between-subject variability, no statistical analysis could be done. However, these results do not show any potentially harmful effect of domestic or industrial 50 Hz MF on humans. They provide a starting point to orient future studies and should be taken into account in the establishment of new exposure limits.

Transient effect of low-intensity magnetic field on human motor control.

There is no consensus with respect to how extremely low frequency (ELF) magnetic fields (MF) affect biological systems. However, this information is crucial to establishing new guidelines for: (i) the new design of electronic devices, (ii) working conditions of exposed workers (e.g. electric linepersons), and in a general manner (iii) policies for human risk management. This study evaluates the effect of a sinusoidal 50 Hz, 1000 microT MF centered at the level of the head on human postural tremor of the index finger, using the wavelet analysis method. In addition to the detection of transient events in tremor time series linked with MF, this method was used to evaluate the differences between MF "on" and "off" conditions and between real and sham exposure in a counterbalanced protocol. Results indicate that neither transient events nor "off-on" or "on-off" MF transition effects were present in the postural tremor time series. Surprisingly, an unexpected significant time dependent decrease in tremor average power was noted along the 20s recordings. Interestingly, this effect was significantly more pronounced in the presence of MF. These results suggest a relaxing effect of ELF MF on motor control resulting in an attenuation of postural tremor intensity.

Is a computational model useful to understand the effect of deep brain stimulation in Parkinson's disease?

A growing number of computational models have been proposed over the last few years to help explain the therapeutic effect of deep brain stimulation (DBS) on motor disorders in Parkinson's disease (PD). However, none of these has been able to explain in a convincing manner the physiological mechanisms underlying DBS. Can these models really contribute to improving our understanding? The model by Rubin and Terman [31] represents one of the most comprehensive and biologically plausible models of DBS published recently. We examined the validity of the model, replicated its simulations and tested its robustness. While our simulations partially reproduced the results presented by Rubin and Terman [31], several issues were raised including the high complexity of the model in its non simplified form, the lack of robustness of the model with respect to small perturbations, the nonrealistic representation of the thalamus and the absence of time delays. Computational models are indeed necessary, but they may not be sufficient in their current forms to explain the effect of chronic electrical stimulation on the activity of the basal ganglia (BG) network in PD.

Effect of a low intensity magnetic field on human motor behavior.

Extremely low frequency (ELF) magnetic fields (MF) are omnipresent in our modern daily environment, but their effects on humans are still not clearly established. The aim of this study was to determine the effect of a 50 Hz, 1,000 microT MF centered at the level of the head on human index finger micro-displacements. Twenty-four men recruited among the personnel of the French company, Electricité de France (EDF), completed the experiment. Their postural and kinetic tremors were recorded under four "field-on" and four "field-off" conditions, each tested during a real and a sham sequence. Eight postural and four kinetic tremor characteristics were calculated on recorded time series and were used for statistical analysis. No effect of the MF was found for kinetic tremor. Concerning postural tremor, the proportion of oscillations at low frequencies (between 2 and 4 Hz) was higher during the real than during the sham exposure sequence (P<.05). It suggests that MF could have a subtle delayed effect on human behavior, which is clearly not pathological. These results should be taken into account for the establishment of new exposure limits.

Automatic detection of movement disorders using recordings of rapid alternating movements.

The present work assesses the potential of rapid alternating movement analysis for detecting movement disorders like Parkinson's disease. Rapid alternating wrist movements were recorded by a diadochokinesimeter for patients with Parkinson's disease (n=10) and healthy controls (n=20). An index of irregularity was computed for each individual as the density of jerk singularities (i.e. zero-crossings) during the movements. Several scales of analysis (i.e. "coarseness") were used for detecting the jerk events and two methods were compared for all of these scales: (1) automatic classification by means of a threshold that optimally separates the indexes of irregularity of the patients from those of the controls, and (2) statistical decision (normal or abnormal) based upon a distribution of indexes of irregularity obtained from a large population of normal subjects. The results showed that (1) two scales of analysis were sufficient and that (2) both methods presented similar performances (e.g. sensitivity=1.00, specificity=0.85, efficiency=0.90). However, statistical decision should be preferred because of its simplicity. The possibility of automatic detection of movement disorders from alternating movements is discussed.