Non-Invasive Estimation of Local Field Potentials for Neuroprosthesis Control

Recent experiments have shown the possibility to use the brain electrical activity to directly control the movement of robots or prosthetic devices in real time. Such neuroprostheses can be invasive or non-invasive, depending on how the brain signals are recorded. In principle, invasive approaches will provide a more natural and flexible control of neuroprostheses, but their use in humans is debatable given the inherent medical risks. Non-invasive approaches mainly use scalp electroencephalogram (EEG) signals and their main disadvantage is that these signals represent the noisy spatiotemporal overlapping of activity arising from very diverse brain regions; i.e., a single scalp electrode picks up and mixes the temporal activity of myriads of neurons at very different brain areas. In order to combine the benefits of both approaches, we propose to rely on the non-invasive estimation of local field potentials (LFP) in the whole human brain from the scalp measured EEG data using a recently developed inverse solution (ELECTRA) to the EEG inverse problem. The goal of a linear inverse procedure is to de-convolve or un-mix the scalp signals attributing to each brain area its own temporal activity. To illustrate the advantage of this approach we compare, using identical set of spectral features, classification of rapid voluntary finger self-tapping with left and right hands based on scalp EEG and non-invasively estimated LFP on two subjects using different number of electrodes

Very High Frequency Oscillations (VHFO) as a Predictor of Movement Intentions

Gamma band (30-80 Hz) oscillations arising in neuronal ensembles are thought to be a crucial component of the neural code. Recent studies in animals suggest a similar functional role for very high frequency oscillations (VHFO) in the range 80-200Hz. Since some intracerebral studies in humans link VHFO to epileptogenesis, it remains unclear if VHFO appear in the healthy human brain and if so which is their role. This study uses EEG recordings from twelve healthy volunteers, engaged in a visuo-motor reaction time task, to show that VHFO are not necessarily pathological but rather code information about upcoming movements. Oscillations within the range (30-200Hz) occurring in the period between stimuli presentation and the fastest hand responses allow highly accurate (>96%) prediction of the laterality of the responding hand in single trials. Our results suggest that VHFO belong in functional terms to the gamma band that must be considerably enlarged to better understand the role of oscillatory activity in brain functioning. This study has therefore important implications for the recording and analysis of electrophysiological data in normal subjects and patients

Non-stationary distributed source approximation: an alternative to improve localization procedures

Localization of the generators of the scalp measured electrical activity is particularly difficult when a large number of brain regions are simultaneously active. In this study, we describe an approach to automatically isolate scalp potential maps, which are simple enough to expect reasonable results after applying a distributed source localization procedure. The isolation technique is based on the time-frequency decomposition of the scalp-measured data by means of a time-frequency representation. The basic rationale behind the approach is that neural generators synchronize during short time periods over given frequency bands for the codification of information and its transmission. Consequently potential patterns specific for certain time-frequency pairs should be simpler than those appearing at single times but for all frequencies. The method generalizes the FFT approximation to the case of distributed source models with non-stationary time behavior. In summary, the non-stationary distributed source approximation aims to facilitate the localization of distributed source patterns acting at specific time and frequencies for non-stationary data such as epileptic seizures and single trial event related potentials. The merits of this approach are illustrated here in the analysis of synthetic data as well as in the localization of the epileptogenic area at seizure onset in patients. It is shown that time and frequency at seizure onset can be precisely detected in the time-frequency domain and those localization results are stable over seizures. The results suggest that the method could also be applied to localize generators in single trial evoked responses or spontaneous activity

Temporal and spatial determination of EEG-seizure onset in the frequency domain

OBJECTIVE: A quantitative analysis of scalp electric fields in patients suffering from pharmacoresistant temporal lobe epilepsy was performed in order to study the development of rhythmic ictal activities over time. METHODS: A method that calculates phase-corrected voltage maps in the frequency domain (FFT-approximation) was applied to ictal multichannel recordings in 10 epileptic patients. The onset of the ictally dominant frequency was determined and its temporal evolution over a time period of 46 s around the ictal EEG onset was studied. The analysis was completed by a linear inverse solution that estimated the sources of the dominant frequency. RESULTS: This method permitted the identification of an ictally dominant frequency which started on the average prior to the onset of initial EEG signs as determined by visual inspection. The frequency incremented during the evolution of the seizure in all patients. The linear inverse solution algorithm localized the source of this frequency to the brain region which was clinically determined as the site of seizure onset and whose resection rendered all patients seizure-free. CONCLUSIONS: Our data suggest that the constant increase of the ictally dominant frequency is related to the amount of temporal lobe tissue generating the ictal discharges. Frequential analysis of ictal electric fields can be reliably used to detect focal pathological activity early during seizure onset arising in deep structures such as the mesial temporal lobe

Temporal and spatial determination of EEG-seizure onset in the frequency domain

OBJECTIVE: A quantitative analysis of scalp electric fields in patients suffering from pharmacoresistant temporal lobe epilepsy was performed in order to study the development of rhythmic ictal activities over time. METHODS: A method that calculates phase-corrected voltage maps in the frequency domain (FFT-approximation) was applied to ictal multichannel recordings in 10 epileptic patients. The onset of the ictally dominant frequency was determined and its temporal evolution over a time period of 46 s around the ictal EEG onset was studied. The analysis was completed by a linear inverse solution that estimated the sources of the dominant frequency. RESULTS: This method permitted the identification of an ictally dominant frequency which started on the average prior to the onset of initial EEG signs as determined by visual inspection. The frequency incremented during the evolution of the seizure in all patients. The linear inverse solution algorithm localized the source of this frequency to the brain region which was clinically determined as the site of seizure onset and whose resection rendered all patients seizure-free. CONCLUSIONS: Our data suggest that the constant increase of the ictally dominant frequency is related to the amount of temporal lobe tissue generating the ictal discharges. Frequential analysis of ictal electric fields can be reliably used to detect focal pathological activity early during seizure onset arising in deep structures such as the mesial temporal lobe

Measuring the complexity of time series: an application to neurophysiological signals

Measures of signal complexity can be used to distinguish neurophysiological activation from noise in those neuroimaging techniques where we record variations of brain activity with time, e.g., fMRI, EEG, ERP. In this paper we explore a recently developed approach to calculate a quantitative measure of deterministic signal complexity and information content: The Renyi number. The Renyi number is by definition an entropy, i.e., a classically used measure of disorder in physical systems, and is calculated in this paper over the basis of the time frequency representation (TFRs) of the measured signals. When calculated in this form, the Renyi entropy (RE) indirectly characterizes the complexity of a signal by providing an approximate counting of the number of separated elementary atoms that compose the time series in the time frequency plane. In this sense, this measure conforms closely to our visual notion of complexity since low complexity values are obtained for signals formed by a small number of "components". The most remarkable properties of this measure are twofold: 1) It does not rely on assumptions about the time series such as stationarity or gaussianity and 2) No model of the neural process under study is required, e.g., no hemodynamic response model for fMRI. The method is illustrated in this paper using fMRI, intracranial ERPs and intracranial potentials estimated from scalp recorded ERPs through an inverse solution (ELECTRA). The main theoretical and practical drawbacks of this measure, especially its dependence of the selected TFR, are discussed. Also the capability of this approach to produce, with less restrictive hypothesis, results comparable to those obtained with more standard methods but is emphasized

Prospects of brain–machine interfaces for space system control

The dream of controlling and guiding computer-based systems using human brain signals has slowly but steadily become a reality. The available technology allows real-time implementation of systems that measure neuronal activity, convert their signals, and translate their output for the purpose of controlling mechanical and electronic systems. This paper describes the state of the art of non-invasive brain-machine interfaces (BMIs) and critically investigates both the current technological limits and the future potential that BMIs have for space applications. We present an assessment of the advantages that BMIs can provide and justify the preferred candidate concepts for space applications together with a vision of future directions for their implementation. © 2008 Elsevier Ltd. All rights reserved

Visually induced activity in human frontal motor areas during simple visuomotor performance

Visuomotor tasks elicit neuronal activity in primate motor areas at relatively short latencies. Although this early activity embodies features of visual responses (short latency, stimulus-dependency), its sensory nature has been questioned. We investigated neural correlates of visuomotor performance in human motor areas using scalp and intracranial event-related potential measures. A simple visuomanual reaction-time task evoked early potentials at 133-145 ms post-stimulus which occurred much earlier than the motor potentials of the same region. The amplitude of the early potentials covaried with stimulus location and was independent of parameters of the motor response. Because of their timing, stimulus-dependency and characteristics of our behavioral task, the early potentials are suggested to reflect neuronal responses of sensory nature rather than processing related to pure motor aspects of the task

Individualschutz durch Wirtschaftsgrundrechte im Gesellschaftsrecht

Los procesos de diseño, fabricación y explotación de la maquinaria agrícola están estrechamente relacionados con el aumento de los niveles de productividad, consumo de combustible y mejoramiento de las cosechas de caña. La presente investigación tiene como objetivo realizar un análisis comparativo de los indicadores técnicos explotativos en las cosechadoras de caña KTP-2M y KTP-3000S. En el análisis se demostró que el desempeño de la cosechadora KTP-3000S es superior a la KTP-2M, alcanzando valores significativos en cuanto a tiempo, eficiencia en el campo, coeficiente de seguridad técnica, materias extrañas durante el corte y valores de producción total, no teniendo este mismo comportamiento con los indicadores de consumo de combustible y valores de las pérdidas en cosecha de todo el período.Por lo que se puede afirmar que la cosechadora cañera KTP-3000S presentó un mejor desempeño durante el cumplimiento de su destino de servicio. // The processes of design, manufacture and operation of agricultural machinery are closely related to increased levels of productivity, fuel consumption and improving cane crops. This research aims to make a comparative analysis of the exploitative technical indicators cane harvesters KTP-2M and KTP-3000S. In the analysis it was demonstrated that the performance of the KTP-3000S harvester exceeds the KTP 2M, achieving significant values in terms of time, field efficiency, coefficient of technical safety, foreign matter field during cutting and values of total production not having this same behavior with fuel consumption indicators and values of crop losses throughout the period.So we can say that the KTP-3000S sugar cane harvester, presented a better performance during the fulfillment of its service destiny