Features for detection of Parkinson's disease tremor from local field potentials of the subthalamic nucleus

Deep Brain Stimulation (DBS) is a treatment routinely used to alleviate the symptoms of Parkinson's disease (PD). In this type of treatment, electrical pulses are applied through electrodes implanted into the basal ganglia of the patient. As the symptoms are not permanent in most patients, it is desirable to develop an on-demand stimulator, applying pulses only when onset of the symptoms is detected. This study evaluates a feature set created for the detection of tremor - a cardinal symptom of PD. The designed feature set was based on standard signal features and researched properties of the electrical signals recorded from subthalamic nucleus (STN) within the basal ganglia, which together included temporal, spectral, statistical, autocorrelation and fractal properties. The most characterized tremor related features were selected using statistical testing and backward algorithms then used for classification on unseen patient signals. The spectral features were among the most efficient at detecting tremor, notably spectral bands 3.5-5.5 Hz and 0-1 Hz proved to be highly significant. The classification results for determination of tremor achieved 94% sensitivity with specificity equaling one.

Parkinson’s Disease tremor classification – a comparison between Support Vector Machines and neural networks

Deep Brain Stimulation has been used in the study of and for treating Parkinson’s Disease (PD) tremor symptoms since the 1980s. In the research reported here we have carried out a comparative analysis to classify tremor onset based on intraoperative microelectrode recordings of a PD patient’s brain Local Field Potential (LFP) signals. In particular, we compared the performance of a Support Vector Machine (SVM) with two well known artificial neural network classifiers, namely a Multiple Layer Perceptron (MLP) and a Radial Basis Function Network (RBN). The results show that in this study, using specifically PD data, the SVM provided an overall better classification rate achieving an accuracy of 81% recognition.

Parkinsonian tremor identification with multiple local field potential feature classification

This paper explores the development of multi-feature classification techniques used to identify tremor-related characteristics in the Parkinsonian patient. Local field potentials were recorded from the subthalamic nucleus and the globus pallidus internus of eight Parkinsonian patients through the implanted electrodes of a Deep brain stimulation (DBS) device prior to device internalization. A range of signal processing techniques were evaluated with respect to their tremor detection capability and used as inputs in a multi-feature neural network classifier to identify the activity of Parkinsonian tremor. The results of this study show that a trained multi-feature neural network is able, under certain conditions, to achieve excellent detection accuracy on patients unseen during training. Overall the tremor detection accuracy was mixed, although an accuracy of over 86% was achieved in four out of the eight patients.

Attacking human implants: a new generation of cybercrime

Human ICT implants, such as RFID implants, cochlear implants, cardiac pacemakers, Deep Brain Stimulation, bionic limbs connected to the nervous system, and networked cognitive prostheses, are becoming increasingly complex. With ever-growing data processing functionalities in these implants, privacy and security become vital concerns. Electronic attacks on human ICT implants can cause significant harm, both to implant subjects and to their environment. This paper explores the vulnerabilities which human implants pose to crime victimisation in light of recent technological developments, and analyses how the law can deal with emerging challenges of what may well become the next generation of cybercrime: attacks targeted at technology implanted in the human body. After a state-of-the-art description of relevant types of human implants and a discussion how these implants challenge existing perceptions of the human body, we describe how various modes of attacks, such as sniffing, hacking, data interference, and denial of service, can be committed against implants. Subsequently, we analyse how these attacks can be assessed under current substantive and procedural criminal law, drawing on examples from UK and Dutch law. The possibilities and limitations of cybercrime provisions (eg, unlawful access, system interference) and bodily integrity provisions (eg, battery, assault, causing bodily harm) to deal with human-implant attacks are analysed. Based on this assessment, the paper concludes that attacks on human implants are not only a new generation in the evolution of cybercrime, but also raise fundamental questions on how criminal law conceives of attacks. Traditional distinctions between physical and non-physical modes of attack, between human bodies and things, between exterior and interior of the body need to be re-interpreted in light of developments in human implants. As the human body and technology become increasingly intertwined, cybercrime legislation and body-integrity crime legislation will also become intertwined, posing a new puzzle that legislators and practitioners will sooner or later have to solve.

Resting tremor classification and detection in Parkinson's disease patients

Parkinson is a neurodegenerative disease, in which tremor is the main symptom. This paper investigates the use of different classification methods to identify tremors experienced by Parkinsonian patients.Some previous research has focussed tremor analysis on external body signals (e.g., electromyography, accelerometer signals, etc.). Our advantage is that we have access to sub-cortical data, which facilitates the applicability of the obtained results into real medical devices since we are dealing with brain signals directly. Local field potentials (LFP) were recorded in the subthalamic nucleus of 7 Parkinsonian patients through the implanted electrodes of a deep brain stimulation (DBS) device prior to its internalization. Measured LFP signals were preprocessed by means of splinting, down sampling, filtering, normalization and rec-tification. Then, feature extraction was conducted through a multi-level decomposition via a wavelettrans form. Finally, artificial intelligence techniques were applied to feature selection, clustering of tremor types, and tremor detection.The key contribution of this paper is to present initial results which indicate, to a high degree of certainty, that there appear to be two distinct subgroups of patients within the group-1 of patients according to the Consensus Statement of the Movement Disorder Society on Tremor. Such results may well lead to different resultant treatments for the patients involved, depending on how their tremor has been classified. Moreover, we propose a new approach for demand driven stimulation, in which tremor detection is also based on the subtype of tremor the patient has. Applying this knowledge to the tremor detection problem, it can be concluded that the results improve when patient clustering is applied prior to detection.

Age-dependent changes in adenosine A(1) receptor distribution and density within the nucleus tractus solitarii of normotensive and hypertensive rats

This study shows the distribution and density of adenosine A1 receptor (A(1)R) within the nucleus tractus solitarii (NTS) of Wistar Kyoto (WKY) and spontaneously hypertensive rats (SHR) from birth to adulthood (1, 15, 30 and 90 days old). The NTS shows heterogeneous distribution of A(1)R in dorsomedial/dorsolateral, subpostremal and medial/intermediate subnuclei. A(1)R decrease from rostral to caudal within dorsomedial/dorsolateral subnucleus in 15-, 30- and 90-day-old WKY and SHR. A(1)R increase from rostral to caudal subpostremal subnucleus in 30- and 90-day-old WKY, and in 15-, 30- and 90-day-old SHR. Furthermore, A(1)Rs are increased in SHR as compared with WKY within dorsomedial/dorsolateral in 30- and 90-day-old and within subpostremal of 15-, 30- and 90-day-old rats. Finally, A(1)Rs increase from 1- to 30-day-old rats. Medial/intermediate did not show any changes in A(1)R from rostral to caudal levels, age or strain. In summary, our result highlights the importance of A1 adenosine system regarding the neural control of blood pressure and the development of hypertension.

Limiting glutamate transmission in a Vglut2-expressing subpopulation of the subthalamic nucleus is sufficient to cause hyperlocomotion

The subthalamic nucleus (STN) is a key area of the basal ganglia circuitry regulating movement. We identified a subpopulation of neurons within this structure that coexpresses Vglut2 and Pitx2, and by conditional targeting of this subpopulation we reduced Vglut2 expression levels in the STN by 40%, leaving Pitx2 expression intact. This reduction diminished, yet did not eliminate, glutamatergic transmission in the substantia nigra pars reticulata and entopeduncular nucleus, two major targets of the STN. The knock-out mice displayed hyperlocomotion and decreased latency in the initiation of movement while preserving normal gait and balance. Spatial cognition, social function, and level of impulsive choice also remained undisturbed. Furthermore, these mice showed reduced dopamine transporter binding and slower dopamine clearance in vivo, suggesting that Vglut2-expressing cells in the STN regulate dopaminergic transmission. Our results demonstrate that altering the contribution of a limited population within the STN is sufficient to achieve results similar to STN lesions and high-frequency stimulation, but with fewer side effects.

Interferindo com oscilações de alta frequência no hipocampo epiléptico: consequências para as crises espontâneas

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Can the `yin and yang` BDNF hypothesis be used to predict the effects of rTMS treatment in neuropsychiatry?

Repetitive transcranial magnetic stimulation (rTMS) is a novel technique of non-invasive brain stimulation which has been used to treat several neuropsychiatric disorders such as major depressive disorder, chronic pain and epilepsy. Recent studies have shown that the therapeutic effects of rTMS are associated with plastic changes in local and distant neural networks. In fact, it has been suggested that rTMS induces long-term potentiation (LTP) and long-term depression (LTD) - like effects. Besides the initial positive clinical results; the effects of rTMS are stilt mixed. Therefore new toots to assess the effects of plasticity non-invasively might be useful to predict its therapeutic effects and design novel therapeutic approaches using rTMS. In this paper we propose that brain-derived neurotrophic factor (BDNF) might be such a tool. Brain-derived neurotrophic factor is a neurotrophin that plays a key role in neuronal survival and synaptic strength, which has also been studied in several neuropsychiatric disorders. There is robust evidence associating BDNF with the LTP/LTD processes, and indeed it has been proposed that BNDF might index an increase or decrease of brain activity - the `yin and yang` BDNF hypothesis. In this article, we review the initial studies combining measurements of BDNF in rTMS clinical trials and discuss the results and potential usefulness of this instrument in the field of rTMS. (C) 2008 Elsevier Ltd. All rights reserved.

Neurogenic neuroprotection: Future perspectives

Neurogenic neuroprotection elicited by deep brain stimulation is emerging as a promising approach for treating patients with ischemic brain lesions. In rats, stimulation of the fastigial nucleus, but not dentate nucleus, has been shown to reduce the volume of focal infarction. Protection of neural tissue is a rapid intervention that has a relatively long-lasting effect, rendering fastigial nucleus stimulation (FNS) a potentially valuable method for clinical application. We review some of the main findings of animal experimental research from a clinical perspective. Results: Although the complete mechanisms of neuroprotection induced by FNS remain unclear, important data has been presented in the last two decades. The acute effect of electrical stimulation of the fastigial nucleus is likely mediated by a prolonged opening of potassium channels, and the sustained effect appears to be linked to inhibition of the apoptotic cascade. A better understanding of the cellular and molecular mechanisms underlying neurogenic neuroprotection by stimulation of deep brain nuclei, with special attention to the fastigial nucleus, can contribute toward improving neurological outcomes in ischemic brain insults.

Motor control system in Parkinson’s disease: a modeling approach

Parkinson’s disease is a neurodegenerative disorder due to the death of the dopaminergic neurons of the substantia nigra of the basal ganglia. The process that leads to these neural alterations is still unknown. Parkinson’s disease affects most of all the motor sphere, with a wide array of impairment such as bradykinesia, akinesia, tremor, postural instability and singular phenomena such as freezing of gait. Moreover, in the last few years the fact that the degeneration in the basal ganglia circuitry induces not only motor but also cognitive alterations, not necessarily implicating dementia, and that dopamine loss induces also further implications due to dopamine-driven synaptic plasticity got more attention. At the present moment, no neuroprotective treatment is available, and even if dopamine-replacement therapies as well as electrical deep brain stimulation are able to improve the life conditions of the patients, they often present side effects on the long term, and cannot recover the neural loss, which instead continues to advance. In the present thesis both motor and cognitive aspects of Parkinson’s disease and basal ganglia circuitry were investigated, at first focusing on Parkinson’s disease sensory and balance issues by means of a new instrumented method based on inertial sensor to provide further information about postural control and postural strategies used to attain balance, then applying this newly developed approach to assess balance control in mild and severe patients, both ON and OFF levodopa replacement. Given the inability of levodopa to recover balance issues and the new physiological findings than underline the importance in Parkinson’s disease of non-dopaminergic neurotransmitters, it was therefore developed an original computational model focusing on acetylcholine, the most promising neurotransmitter according to physiology, and its role in synaptic plasticity. The rationale of this thesis is that a multidisciplinary approach could gain insight into Parkinson’s disease features still unresolved.

Ottimizzazione di metodi numerici e realizzazione di un setup per l'imaging di colture cellulari 3D con tomografia ad impedenza elettrica

Il presente lavoro di tesi presenta la progettazione, realizzazione e applicazione di un setup sperimentale miniaturizzato per la ricostruzione di immagine, con tecnica di Tomografia ad Impedenza Elettrica (EIT). Il lavoro descritto nel presente elaborato costituisce uno studio di fattibilità preliminare per ricostruire la posizione di piccole porzioni di tessuto (ordine di qualche millimetro) o aggregati cellulari dentro uno scaffold in colture tissutali o cellulari 3D. Il setup disegnato incorpora 8 elettrodi verticali disposti alla periferia di una camera di misura circolare del diametro di 10 mm. Il metodo di analisi EIT è stato svolto utilizzando i) elettrodi conduttivi per tutta l’altezza della camera (usati nel modello EIT bidimensionale e quasi-bidimensionale) e ii) elettrodi per deep brain stimulation (conduttivi esclusivamente su un ridotto volume in punta e posti a tre diverse altezze: alto, centro e basso) usati nel modello EIT tridimensionale. Il metodo ad elementi finiti (FEM) è stato utilizzato per la soluzione sia del problema diretto che del problema inverso, con la ricostruzione della mappa di distribuzione della conduttività entro la camera di misura. Gli esperimenti svolti hanno permesso di ricostruire la mappa di distribuzione di conduttività relativa a campioni dell’ordine del millimetro di diametro. Tali dimensioni sono compatibili con quelle dei campioni oggetto di studio in ingegneria tissutale e, anche, con quelle tipiche dei sistemi organ-on-a-chip. Il metodo EIT sviluppato, il prototipo del setup realizzato e la trattazione statistica dei dati sono attualmente in fase di implementazione in collaborazione con il gruppo del Professor David Holder, Dept. Medical Physics and Bioengineering, University College London (UCL), United Kingdom.

Factors predicting protracted improvement after pallidal DBS for primary dystonia: the role of age and disease duration

In many patients, optimal results after pallidal deep brain stimulation (DBS) for primary dystonia may appear over several months, possibly beyond 1 year after implant. In order to elucidate the factors predicting such protracted clinical effect, we retrospectively reviewed the clinical records of 44 patients with primary dystonia and bilateral pallidal DBS implants. Patients with fixed skeletal deformities, as well as those with a history of prior ablative procedures, were excluded. The Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS) scores at baseline, 1 and 3 years after DBS were used to evaluate clinical outcome. All subjects showed a significant improvement after DBS implants (mean BFMDRS improvement of 74.9% at 1 year and 82.6% at 3 years). Disease duration (DD, median 15 years, range 2-42) and age at surgery (AS, median 31 years, range 10-59) showed a significant negative correlation with DBS outcome at 1 and 3 years. A partition analysis, using DD and AS, clustered subjects into three groups: (1) younger subjects with shorter DD (n = 19, AS < 27, DD ? 17); (2) older subjects with shorter DD (n = 8, DD ? 17, AS ? 27); (3) older subjects with longer DD (n = 17, DD > 17, AS ? 27). Younger patients with short DD benefitted more and faster than older patients, who however continued to improve 10% on average 1 year after DBS implants. Our data suggest that subjects with short DD may expect to achieve a better general outcome than those with longer DD and that AS may influence the time necessary to achieve maximal clinical response.

Structural and resting state functional connectivity of the subthalamic nucleus: identification of motor STN parts and the hyperdirect pathway

Deep brain stimulation (DBS) for Parkinson's disease often alleviates the motor symptoms, but causes cognitive and emotional side effects in a substantial number of cases. Identification of the motor part of the subthalamic nucleus (STN) as part of the presurgical workup could minimize these adverse effects. In this study, we assessed the STN's connectivity to motor, associative, and limbic brain areas, based on structural and functional connectivity analysis of volunteer data. For the structural connectivity, we used streamline counts derived from HARDI fiber tracking. The resulting tracks supported the existence of the so-called "hyperdirect" pathway in humans. Furthermore, we determined the connectivity of each STN voxel with the motor cortical areas. Functional connectivity was calculated based on functional MRI, as the correlation of the signal within a given brain voxel with the signal in the STN. Also, the signal per STN voxel was explained in terms of the correlation with motor or limbic brain seed ROI areas. Both right and left STN ROIs appeared to be structurally and functionally connected to brain areas that are part of the motor, associative, and limbic circuit. Furthermore, this study enabled us to assess the level of segregation of the STN motor part, which is relevant for the planning of STN DBS procedures.

Auditory verbal hallucinations: imaging, analysis, and intervention

In this article, we will link neuroimaging, data analysis, and intervention methods in an important psychiatric condition: auditory verbal hallucinations (AVH). The clinical and phenomenological background as well as neurophysiological findings will be covered and discussed with respect to noninvasive brain stimulation. Additionally, methods of noninvasive brain stimulation will be presented as ways to intervene with AVH. Finally, preliminary conclusions and possible future perspectives will be proposed.