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.

Eastern partnership migrants in Germany: outcomes, potentials and challenges

Despite the ongoing dialogue on facilitating mobility between the European Union and the Eastern Partnership (EaP) countries, very little is known about the magnitude and characteristics of migration from these countries. We find that EaP migrants experience worse labor market outcomes than other migrant groups, but current and potential migrants hold qualifications in those areas were skill shortages are expected. Therefore, the monitoring and supervision of EaP integration will be consequential in order to understand how much of the current brain waste is driven by poor assessment of foreign qualifications, and to unleash the potential of migration for the German economy.

An optimized ERP Brain-computer interface based on facial expression changes

OBJECTIVE: Interferences from spatially adjacent non-target stimuli are known to evoke event-related potentials (ERPs) during non-target flashes and, therefore, lead to false positives. This phenomenon was commonly seen in visual attention-based brain-computer interfaces (BCIs) using conspicuous stimuli and is known to adversely affect the performance of BCI systems. Although users try to focus on the target stimulus, they cannot help but be affected by conspicuous changes of the stimuli (such as flashes or presenting images) which were adjacent to the target stimulus. Furthermore, subjects have reported that conspicuous stimuli made them tired and annoyed. In view of this, the aim of this study was to reduce adjacent interference, annoyance and fatigue using a new stimulus presentation pattern based upon facial expression changes. Our goal was not to design a new pattern which could evoke larger ERPs than the face pattern, but to design a new pattern which could reduce adjacent interference, annoyance and fatigue, and evoke ERPs as good as those observed during the face pattern. APPROACH: Positive facial expressions could be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast is big enough to evoke strong ERPs. In this paper, a facial expression change pattern between positive and negative facial expressions was used to attempt to minimize interference effects. This was compared against two different conditions, a shuffled pattern containing the same shapes and colours as the facial expression change pattern, but without the semantic content associated with a change in expression, and a face versus no face pattern. Comparisons were made in terms of classification accuracy and information transfer rate as well as user supplied subjective measures. MAIN RESULTS: The results showed that interferences from adjacent stimuli, annoyance and the fatigue experienced by the subjects could be reduced significantly (p < 0.05) by using the facial expression change patterns in comparison with the face pattern. The offline results show that the classification accuracy of the facial expression change pattern was significantly better than that of the shuffled pattern (p < 0.05) and the face pattern (p < 0.05). SIGNIFICANCE: The facial expression change pattern presented in this paper reduced interference from adjacent stimuli and decreased the fatigue and annoyance experienced by BCI users significantly (p < 0.05) compared to the face pattern.

Local Field Potentials in the Gustatory Cortex Carry Taste Information

It has been recently shownthat localfield potentials (LFPs)fromthe auditory and visual cortices carry information about sensory stimuli, but whether this is a universal property of sensory cortices remains to be determined. Moreover, little is known about the temporal dynamics of sensory information contained in LFPs following stimulus onset. Here we investigated the time course of the amount of stimulus information in LFPs and spikes from the gustatory cortex of awake rats subjected to tastants and water delivery on the tongue. We found that the phase and amplitude of multiple LFP frequencies carry information about stimuli, which have specific time courses after stimulus delivery. The information carried by LFP phase and amplitude was independent within frequency bands, since the joint information exhibited neither synergy nor redundancy. Tastant information in LFPs was also independent and had a different time course from the information carried by spikes. These findings support the hypothesis that the brain uses different frequency channels to dynamically code for multiple features of a stimulus.

Multimodal evoked potentials and the ovarian cycle in young ovulating women

There is controversy over how hormonal conditions influence cerebral physiology. We studied pattern-shift visual evoked potentials (PS-VEP), brain stem auditory evoked potentials (BAEP) and short-latency somatosensory evoked potentials (SSEV) in 20 female volunteers at different phases of the menstrual cycle (estrogen phase, ovulatory day and progesterone phase). Statistical analysis showed decreased latencies for P 100 (PS-VEP), N 19and P 22 (SSEV) waves in the progesterone phase compared with the estrogen phase. There was no significant difference between the estrogen and the ovulation day values. Comparing the three above stages, there were no significant differences in the brainstem auditory evoked potentials. The reduction of the latencies of the potentials generated in multisynaptic circuits provides the first consistent neurophysiological basis for a tentative comprehension of human pre-menstrual syndrome.

Biomolecular information, brain activity and cognitive functions

Molecular neurobiology has provided an explanation of mechanisms supporting mental functions as learning, memory, emotion and consciousness. However, an explanatory gap remains between two levels of description: molecular mechanisms determining cellular and tissue functions, and cognitive functions. In this paper we review molecular and cellular mechanisms that determine brain activity, and then hypothetize about their relation with cognition and consciousness. The brain is conceived of as a dynamic system that exchanges information with the whole body and the environment. Three explanatory hypotheses are presented, stating that: a) brain tissue function is coordinated by macromolecules controlling ion movements, b) structured (amplitude, frequency and phase-modulated) local field potentials generated by organized ionic movement embody cognitive information patterns, and c) conscious episodes are constructed by a large-scale mechanism that uses oscillatory synchrony to integrate local field patterns. © by São Paulo State University.

Triple-aspect monism: Physiological, mental unconscious and conscious aspects of brain activity

Brain activity contains three fundamental aspects: (a) The physiological aspect, covering all kinds of processes that involve matter and/or energy; (b) the mental unconscious aspect, consisting of dynamical patterns (i.e., frequency, amplitude and phase-modulated waves) embodied in neural activity. These patterns are variously operated (transmitted, stored, combined, matched, amplified, erased, etc), forming cognitive and emotional unconscious processes and (c) the mental conscious aspect, consisting of feelings experienced in the first-person perspective and cognitive functions grounded in feelings, as memory formation, selection of the focus of attention, voluntary behavior, aesthetical appraisal and ethical judgment. Triple-aspect monism (TAM) is a philosophical theory that provides a model of the relation of the three aspects. Spatially distributed neuronal dendritic potentials generate amplitude-modulated waveforms transmitted to the extracellular medium and adjacent astrocytes, prompting the formation of large waves in the astrocyte network, which are claimed to both integrate distributed information and instantiate feelings. According to the valence of the feeling, the large wave feeds back on neuronal synapses, modulating (reinforcing or depressing) cognitive and behavioral functions.

Non-invasive brain stimulation for the management of arterial hypertension

The neural control of the cardiovascular system is a complex process that involves many structures at different levels of nervous system. Several cortical areas are involved in the control of systemic blood pressure, such as the sensorimotor cortex, the medial prefrontal cortex and the insular cortex. Non-invasive brain stimulation techniques - repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) - induce sustained and prolonged functional changes of the human cerebral cortex. rTMS and tDCS has led to positive results in the treatment of some neurological and psychiatric disorders. Because experiments in animals show that cortical modulation can be an effective method to regulate the cardiovascular system, non-invasive brain stimulation might be a novel tool in the therapeutics of human arterial hypertension. We here review the experimental evidence that non-invasive brain stimulation can influence the autonomic nervous system and discuss the hypothesis that focal modulation of cortical excitability by rTMS or tDCS can influence sympathetic outflow and, eventually, blood pressure, thus providing a novel therapeutic tool for human arterial hypertension. (C) 2009 Published by Elsevier Ltd.

From otoacoustic emission to late auditory potentials P300: the inhibitory effect

This study verifies the effects of contralateral noise on otoacoustic emissions and auditory evoked potentials. Short, middle and late auditory evoked potentials as well as otoacoustic emissions with and without white noise were assessed. Twenty-five subjects, normal-hearing, both genders, aged 18 to 30 years, were tested. In general, latencies of the various auditory potentials were increased at noise conditions, whereas amplitudes were diminished at noise conditions for short, middle and late latency responses combined in the same subject. The amplitude of otoacoustic emission decreased significantly in the condition with contralateral noise in comparison to the condition without noise. Our results indicate that most subjects presented different responses between conditions (with and without noise) in all tests, thereby suggesting that the efferent system was acting at both caudal and rostral portions of the auditory system.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

Mental states monitoring through passive Brain-Computer Interface systems

The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.

Human Preferences for Symmetry: Subjective Experience, Cognitive Conflict and Cortical Brain Activity

This study examines the links between human perceptions, cognitive biases and neural processing of symmetrical stimuli. While preferences for symmetry have largely been examined in the context of disorders such as obsessive-compulsive disorder and autism spectrum disorders, we examine various these phenomena in non-clinical subjects and suggest that such preferences are distributed throughout the typical population as part of our cognitive and neural architecture. In Experiment 1, 82 young adults reported on the frequency of their obsessive-compulsive spectrum behaviors. Subjects also performed an emotional Stroop or variant of an Implicit Association Task (the OC-CIT) developed to assess cognitive biases for symmetry. Data not only reveal that subjects evidence a cognitive conflict when asked to match images of positive affect with asymmetrical stimuli, and disgust with symmetry, but also that their slowed reaction times when asked to do so were predicted by reports of OC behavior, particularly checking behavior. In Experiment 2, 26 participants were administered an oddball Event-Related Potential task specifically designed to assess sensitivity to symmetry as well as the OC-CIT. These data revealed that reaction times on the OC-CIT were strongly predicted by frontal electrode sites indicating faster processing of an asymmetrical stimulus (unparallel lines) relative to a symmetrical stimulus (parallel lines). The results point to an overall cognitive bias linking disgust with asymmetry and suggest that such cognitive biases are reflected in neural responses to symmetrical/asymmetrical stimuli.

The time window for generation of dendritic spikes by coincidence of action potentials and EPSPs is layer specific in somatosensory cortex

The precise timing of events in the brain has consequences for intracellular processes, synaptic plasticity, integration and network behaviour. Pyramidal neurons, the most widespread excitatory neuron of the neocortex have multiple spike initiation zones, which interact via dendritic and somatic spikes actively propagating in all directions within the dendritic tree. For these neurons, therefore, both the location and timing of synaptic inputs are critical. The time window for which the backpropagating action potential can influence dendritic spike generation has been extensively studied in layer 5 neocortical pyramidal neurons of rat somatosensory cortex. Here, we re-examine this coincidence detection window for pyramidal cell types across the rat somatosensory cortex in layers 2/3, 5 and 6. We find that the time-window for optimal interaction is widest and shifted in layer 5 pyramidal neurons relative to cells in layers 6 and 2/3. Inputs arriving at the same time and locations will therefore differentially affect spike-timing dependent processes in the different classes of pyramidal neurons.

Social Cognition And Functional Brain Imaging: Extending The Broader Autism Phenotype

Evidence suggests that the social cognition deficits prevalent in autism spectrum disorders (ASDs) are widely distributed in first degree and extended relatives. This ¿broader autism phenotype¿ (BAP) can be extended into non-clinical populations and show wide distributions of social behaviors such as empathy and social responsiveness ¿ with ASDs exhibiting these behaviors on the lower ends of the distributions. Little evidence has previously shown relationships between self-report measures of social cognition and more objective tasks such as face perception in functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). In this study, three specific hypotheses were addressed: a) increased social ability, as measured by an increased Empathy Quotient, decreased Social Responsiveness Scale (SRS-A) score, and increased Social Attribution Task score, will predict increased activation of the fusiform gyrus in response to faces as compared to houses; b) these same measures will predict N170 amplitude and latency showing decreased latency and increased amplitude for faces as compared to houses with increased social ability; c) increased amygdala volume will predict increased fusiform gyrus activation when viewing faces as compared to houses. Findings supported all of the hypotheses. Empathy scores significantly predicted both right FFG activation [F(1,20) = 4.811, p = .041, ß = .450, R2 = 0.20] and left FFG activation [F(1,20) = 7.70, p = .012, ß = .537, R2 = 0.29]. Based on ERP results increased right lateralization face-related N170 was significantly predicted by the EQ [F(1,54) = 6.94, p = .011, ß = .338, R2 = 0.11]. Finally, total amygdala volume significantly predicted right [F(1,20) = 7.217, p = .014, ß = .515, R2 = 0.27] and left [F(1,20) = 36.77, p < .001, ß = .805, R2 = 0.65] FFG activation. Consistent with the a priori hypotheses, traits attributed to the BAP can significantly predict neural responses to faces in a non-clinical population. This is consistent with the face processing deficits seen in ASDs. The findings presented here contribute to the extension of the BAP from unaffected relatives of individuals with ASDs to the general population. These findings also give continued evidence in support of a continuous distribution of traits found in psychiatric illnesses in place of a traditional, dichotomous ¿all-or-nothing¿ diagnostic framework of neurodevelopmental and neuropsychiatric disorders.

Tracking the implicit self using event-related potentials

Negative biases in implicit self-evaluation are thought to be detrimental to subjective well-being and have been linked to various psychological disorders, including depression. An understanding of the neural processes underlying implicit self-evaluation in healthy subjects could provide a basis for the investigation of negative biases in depressed patients, the development of differential psychotherapeutic interventions, and the estimation of relapse risk in remitted patients. We thus studied the brain processes linked to implicit self-evaluation in 25 healthy subjects using event-related potential (ERP) recording during a self-relevant Implicit Association Test (sIAT). Consistent with a positive implicit self-evaluation in healthy subjects, they responded significantly faster to the congruent (self-positive mapping) than to the incongruent sIAT condition (self-negative mapping). Our main finding was a topographical ERP difference in a time window between 600 and 700 ms, whereas no significant differences between congruent and incongruent conditions were observed in earlier time windows. This suggests that biases in implicit self-evaluation are reflected only indirectly, in the additional recruitment of control processes needed to override the positive implicit self-evaluation of healthy subjects in the incongruent sIAT condition. Brain activations linked to these control processes can thus serve as an indirect measure for estimating biases in implicit self-evaluation. The sIAT paradigm, combined with ERP, could therefore permit the tracking of the neural processes underlying implicit self-evaluation in depressed patients during psychotherapy.