The cross-hemispheric nigrostriatal pathway prevents the expression of levodopa-induced dyskinesias.

Parkinson's disease (PD) is a neurodegenerative movement disorder that is routinely treated with levodopa. Unfortunately, long-term dopamine replacement therapy using levodopa leads to levodopa-induced dyskinesias (LID), a significant and disabling side-effect. Clinical findings indicate that LID typically only occurs following the progression of PD motor symptoms from the unilateral (Hoehn and Yahr (HY) Stage I) to the bilateral stage (HY Stage II). This suggests the presence of some compensatory interhemispheric mechanisms that delay the occurrence of LID. We therefore investigated the role of interhemispheric connections of the nigrostriatal pathway on LID expression in a rat model of PD. The striatum of one hemisphere of rats was first injected with a retrograde tracer to label the ipsi- and cross-hemispheric nigrostriatal pathways. Rats were then split into groups and unilaterally lesioned in the striatum or medial forebrain bundle of the tracer-injected hemisphere to induce varying levels of hemiparkinsonism. Finally, rats were treated with levodopa and tested for the expression of LID. Distinct subsets emerged from rats that underwent the same lesioning paradigm based on LID. Strikingly, non-dyskinetic rats had significant sparing of their cross-hemispheric nigrostriatal pathway projecting from the unlesioned hemisphere. In contrast, dyskinetic rats only had a small proportion of this cross-hemispheric nigrostriatal pathway survive lesioning. Crucially, both non-dyskinetic and dyskinetic rats had nearly identical levels of ipsi-hemispheric nigrostriatal pathway survival and parkinsonian motor deficits. Our data suggest that the survival of the cross-hemispheric nigrostriatal pathway plays a crucial role in preventing the expression of LID and represents a potentially novel target to halt the progression of this devastating side-effect of a common anti-PD therapeutic.

Polysomnographic Features of Sleep Disturbances and REM Sleep Behavior Disorder in the Unilateral 6-OHDA Lesioned Hemiparkinsonian Rat.

Sleep pattern disruption, specifically REM sleep behavior disorder (RBD), is a major nonmotor cause of disability in PD. Understanding the pathophysiology of these sleep pattern disturbances is critical to find effective treatments. 24-hour polysomnography (PSG), the gold standard for sleep studies, has never been used to test sleep dysfunction in the standard 6-OHDA lesioned hemiparkinsonian (HP) rat PD model. In this study, we recorded 24-hour PSG from normal and HP rats. Recordings were scored into wake, rapid eye movement (REM), and non-REM (NREM). We then examined EEG to identify REM periods and EMG to check muscle activity during REM. Normal rats showed higher wakefulness (70-80%) during the dark phase and lower wakefulness (20%) during the light phase. HP rats showed 30-50% sleep in both phases, less modulation and synchronization to the light schedule (P < 0.0001), and more long run lengths of wakefulness (P < 0.05). HP rats also had more REM epochs with muscle activity than control rats (P < 0.05). Our findings that the sleep architecture in the HP rat resembles that of PD patients demonstrate the value of this model in studying the pathophysiological basis of PD sleep disturbances and preclinical therapeutics for PD related sleep disorders including RBD.

The Antiparkinsonian and Antidyskinetic Mechanisms of Mucuna pruriens in the MPTP-Treated Nonhuman Primate.

Chronic treatment with levodopa (LD) in Parkinson's disease (PD) can cause drug induced dyskinesias. Mucuna pruriens endocarp powder (MPEP) contains several compounds including natural LD and has been reported to not cause drug-induced dyskinesias. We evaluated the effects of Mucuna pruriens to determine if its underlying mechanistic actions are exclusively due to LD. We first compared MPEP with and without carbidopa (CD), and LD+CD in hemiparkinsonian (HP) monkeys. Each treatment ameliorated parkinsonism. We then compared the neuronal firing properties of the substantia nigra reticulata (SNR) and subthalamic nucleus (STN) in HP monkeys with MPEP+CD and LD+CD to evaluate basal ganglia circuitry alterations. Both treatments decreased SNR firing rate compared to HP state. However, LD+CD treatments significantly increased SNR bursting firing patterns that were not seen with MPEP+CD treatments. No significant changes were seen in STN firing properties. We then evaluated the effects of a water extract of MPEP. Oral MPWE ameliorated parkinsonism without causing drug-induced dyskinesias. The distinctive neurophysiological findings in the basal ganglia and the ability to ameliorate parkinsonism without causing dyskinesias strongly suggest that Mucuna pruriens acts through a novel mechanism that is different from that of LD.

Multiscale autoregressive identification of neuroelectrophysiological systems.

Electrical signals between connected neural nuclei are difficult to model because of the complexity and high number of paths within the brain. Simple parametric models are therefore often used. A multiscale version of the autoregressive with exogenous input (MS-ARX) model has recently been developed which allows selection of the optimal amount of filtering and decimation depending on the signal-to-noise ratio and degree of predictability. In this paper, we apply the MS-ARX model to cortical electroencephalograms and subthalamic local field potentials simultaneously recorded from anesthetized rodent brains. We demonstrate that the MS-ARX model produces better predictions than traditional ARX modeling. We also adapt the MS-ARX results to show differences in internuclei predictability between normal rats and rats with 6OHDA-induced parkinsonism, indicating that this method may have broad applicability to other neuroelectrophysiological studies.

The effect of striatal dopaminergic grafts on the neuronal activity in the substantia nigra pars reticulata and subthalamic nucleus in hemiparkinsonian rats.

The electrophysiological correlates of parkinsonism in the basal ganglia have been well studied in patients with Parkinson's disease and animal models. Separately, striatal dopaminergic cell transplantation has shown promise in ameliorating parkinsonian motor symptoms. However, the effect of dopaminergic grafts on basal ganglia electrophysiology has not thoroughly been investigated. In this study, we transplanted murine foetal ventral mesencephalic cells into rats rendered hemiparkinsonian by 6-hydroxydopamine injection. Three months after transplantation, extracellular and local field potential recordings were taken under urethane anaesthesia from the substantia nigra pars reticulata and subthalamic nucleus along with cortical electroencephalograms and were compared to recordings from normal and hemiparkinsonian controls. Recordings from cortical slow-wave activity and global activation states were analysed separately. Rats with histologically confirmed xenografts showed behavioural improvement measured by counting apomorphine-induced rotations and with the extended body axis test. Firing rates in both nuclei were not significantly different between control and grafted groups. However, burst firing patterns in both nuclei in the slow-wave activity state were significantly reduced (P < 0.05) in rats with large surviving grafts, compared to hemiparkinsonian controls. The neuronal firing entropies and oscillations in both nuclei were restored to normal levels in the large-graft group. Electroencephalogram spike-triggered averages also showed normalization in the slow-wave activity state (P < 0.05). These results suggest that local continuous dopaminergic stimulation exerts a normalizing effect on the downstream parkinsonian basal ganglia firing patterns. This novel finding is relevant to future preclinical and clinical investigations of cell transplantation and the development of next-generation therapies for Parkinson's disease that ameliorate pathophysiological neural activity and provide optimal recovery of function.

The effects of chronic levodopa treatments on the neuronal firing properties of the subthalamic nucleus and substantia nigra reticulata in hemiparkinsonian rhesus monkeys.

Dopamine replacement therapy with levodopa (LD) is currently the most effective pharmacological treatment for Parkinson's disease (PD), a neurodegenerative disorder characterized by dysfunction of basal ganglia electrophysiology. The effects of chronic LD treatments on the electrophysiological activity of the subthalamic nucleus (STN) and the substantia nigra reticulata (SNR) in parkinsonism are not clear. In the present study we examined the effects of chronic LD treatments on the firing rate and firing pattern of STN and SNR neurons in the stable hemiparkinsonian monkey model of PD. We also evaluated local field potentials of both nuclei before and after LD treatments. In a stable hemiparkinsonian state, STN and SNR had a mean firing rate of 42.6 ± 3.5H z (mean ± SEM) and 52.1 ± 5.7 Hz, respectively. Chronic intermittent LD exposure induced marked amelioration of parkinsonism with no apparent drug-induced motor complications. LD treatments did not significantly change the mean firing rate of STN neurons (41.3 ± 3.3 Hz) or bursting neuronal firing patterns. However, LD treatments induced a significant reduction of the mean firing rates of SNR neurons to 36.2 ± 3.3 Hz (p<0.05) and a trend toward increased burstiness. The entropy of the spike sequences from STN and SNR was unchanged by LD treatment, while there was a shift of spectral power into higher frequency bands in the LFPs. The inability of chronic LD treatments to reduce the bursty firing patterns in the STN and SNR should be further examined as a potential pathophysiological mechanism for PD symptoms that are refractory to LD treatments.

Three-dimensional reconstruction of transcranial ultrasound images obtained through the temporal bone window using a helmet-mounted mechanical beam-steering device.

Transcranial sonography has been an increasingly widespread diagnostic tool for the diagnosis of neural diseases like Parkinson's disease. However, the utilization of modern 3D ultrasound techniques has been hampered by the acoustical barrier of the skull bones. We report the development of and preliminary results from an ultrasound helmet which uses mechanical beam-steering to allow 3-D reconstruction of deep brain structures such as the substantia nigra.

Multiscale autoregressive identification of neuro-electrophysiological systems.

Electrical signals between connected neural nuclei are difficult to model because of the complexity and high number of paths within the brain. Simple parametric models are therefore often used. A multiscale version of the autoregressive with exogenous input (MS-ARX) model has recently been developed which allows selection of the optimal amount of filtering and decimation depending on the signal-to-noise ratio and degree of predictability. In this paper we apply the MS-ARX model to cortical electroencephalograms and subthalamic local field potentials simultaneously recorded from anesthetized rodent brains. We demonstrate that the MS-ARX model produces better predictions than traditional ARX modeling. We also adapt the MS-ARX results to show differences in inter-nuclei predictability between normal rats and rats with 6OHDA-induced parkinsonism, indicating that this method may have broad applicability to other neuro-electrophysiological studies.

Manual rat sleep classification in principal component space.

A simple method is described for using principal component analysis (PCA) to score rat sleep recordings as awake, rapid-eye-movement (REM) sleep, or non-REM (NREM) sleep. PCA was used to reduce the dimensionality of the features extracted from each epoch to three, and the projections were then graphed in a scatterplot where the clusters were visually apparent. The clusters were then directly manually selected, classifying the entire recording at once. The method was tested in a set of ten 24-h rat sleep electroencephalogram (EEG) and electromyogram (EMG) recordings. Classifications by two human raters performing traditional epoch-by-epoch scoring were blindly compared with classifications by another two human raters using the new PCA method. Overall inter-rater median percent agreements ranged between 93.7% and 94.9%. Median Cohen's kappa coefficient ranged from 0.890 to 0.909. The PCA method on average required about 5 min for classification of each 24-h recording. The combination of good accuracy and reduced time compared to traditional sleep scoring suggests that the method may be useful for sleep research.

A comparison of neural feature extraction methods for brain-machine interfaces.

Brain-machine interfaces (BMIs) have shown promise in augmenting people's control of their surroundings, especially for those suffering from paralysis due to neurological disorders. This paper describes an experiment using the rodent model to explore information available in neural signals recorded from chronically implanted intracortical microelectrode arrays. In offline experiments, a number of neural feature extraction methods were utilized to obtain neural activity vectors (NAVs) describing the activity of the underlying neural population while rats performed a discrimination task. The methods evaluated included standard techniques such as binned spike rates and local field potential spectra as well as more novel approaches including matched-filter energy, raw signal spectra, and an autocorrelation energy measure (AEM) approach. Support vector machines (SVMs) were trained offline to classify left from right going movements by utilizing features contained in the NAVs obtained by the different methods. Each method was evaluated for accuracy and robustness. Results show that most algorithms worked well for decoding neural signals both during and prior to movement, with spectral methods providing the best stability.