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Electroencephalography (EEG) of the mouse brain offers the advantage to monitor brain states in freely moving conditions under genetic or molecular manipulation. We present a novel, flexible, and biocompatible microfabricated electrode based on polyimide to record a multi-channel EEG from a mouse. Our microelectrode has 32 recording electrodes, including two ground electrodes. The connectors for the...
BIS monitoring is a processed electroencephalogram (EEG) technology that is designed to follow the effects that anesthetics and sedatives have on cerebral function. Much is know about the technology, it's utility and limitations. The economic case for widespread utilization of this technology is weak. There appears to be little opportunity to decrease health care cost by either reduction of drug costs...
Invasive BCI studies have classically relied on actual or imagined movements to train their neural decoding algorithms. In this study, non-human primates were required to perform a 2D BCI task using epidural microECoG recordings. The decoding weights and cortical locations of the electrodes used for control were randomly chosen and fixed for a series of daily recording sessions for five days. Over...
This paper presents the design and development of BioLogger, a wireless physiological signal sensing and logging system. BioLogger can simultaneously monitor and record various types of physiological signals. Energy saving design is incorporated to both hardware and software design phases in order to prolong the life time of sensor nodes. Moreover, a simple scheduler is implemented to make sure the...
The anti-social behaviors of the people who are characteristic of abnormal action have seriously affected our society. Recent years, with the development of brain science, the features of human's abnormal action have been identified by means of the low frontal lobe activities. However, in many countries, the corresponding systems for identification and treatment are in an insufficient situation. Thus,...
Electrical cortical stimulation (CS) of the auditory cortices has been shown to reduce the severity of debilitating tinnitus in some patients. In this study, we performed MEG source imaging of spontaneous brain activity during concurrent CS of the left secondary auditory cortex of a volunteer suffering from right unilateral tinnitus. CS produced MEG artifacts which were successfully sorted and removed...
One of the most challenging questions open in neuroscience today is the characterization of the brain responses during social interaction. A major limitation of the approaches used in most of the studies performed so far is that only one of the participating brains is measured each time. The ldquointeractionrdquo between cooperating, competing or communicating brains is thus not measured directly,...
Vagus nerve stimulation (VNS) is an approved therapy for the treatment of adult patients and adolescents aged 12 years and older who have partial onset seizures refractory to antiepileptic medications. More than 50,000 patients worldwide have been implanted with the VNS system. Work continues to understand the mechanism of action of VNS with the goal of improving the treatment, particularly to identify...
The learning of a novel task currently rely heavily on conventional classroom instruction with qualitative assessment and observation. Introduction of individualized tutorials with integrated neuroscience-based evaluation techniques could significantly accelerate skill acquisition and provide quantitative evidence of successful training. We have created a suite of adaptive and interactive neuro-educational...
Brain-computer interfaces (BCI) offer potential for individuals with a variety of motor and sensory disabilities to control their environment, communicate, and control mobility aids. However, the key to BCI usability rests in being able to extract relevant time varying signals that can be classified into usable commands in real time. This paper reports the first success of the Strathclyde BCI controlling...
Epilepsy is a neurological disorder that affects around 50 million people worldwide. The seizure detection is an important component in the diagnosis of epilepsy. In this study, the Empirical Mode Decomposition (EMD) method was proposed on the development of an automatic epileptic seizure detection algorithm. The algorithm first computes the Intrinsic Mode Functions (IMFs) of EEG records, then calculates...
Perinatal hypoxia remains a significant cause of brain damage. Currently there are no biomarkers to detect the at risk brain. Recent research, however, suggests that the appearance of epileptiform transients in the first 6-8 hours after hypoxia (the latent phase of injury) are predictive of neural outcome. To quantify this further a key need is to automate EEG signal analysis to aid clinical staff...
This paper examines whether an appropriate algorithm, developed for use with neonatal data, could also be used, without alteration, for the detection of seizures in adults with epilepsy. The performance of a feature extraction and SVM classifier system is evaluated on databases of 17 neonatal patients and 15 adult patients. Mean ROC curve areas of 0.96 and 0.94 for neonatal and adult databases respectively...
In the present study, we propose a theoretical graph procedure to investigate the communication redundancy in brain networks. By taking into account all the possible paths between pairs of cortical regions, this method captures the network redundancy i.e. a critical resource of the brain enhancing the resilience to neural damages and dysfunctions. As an example for its potential, we apply this procedure...
We have investigated the suitable spatial filters for inverse estimation of cortical dipole imaging from the scalp electroencephalogram. The effects of incorporating statistical information of noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) was applied to an inhomogeneous three-sphere volume conductor head model....
It is said that the result of the game of sports is controlled by player's mental state. Especially, player's concentration greatly controls the result of the game. Therefore, we think that if player's mental state under exercising can be evaluated, it becomes possible to guide the player appropriately. Our mental state can be understood from analyzing EEG (Electroencephalogram). Especially, it is...
Electroencephalogram (EEG) signals give important information about the vigilance states of a subject. Therefore, this study constructs a real-time EEG-based system for detecting a drowsy driver. The proposed system uses a novel six channels active dry electrode system to acquire EEG non-invasively. In addition, it uses a TMS320VC5510 DSP chip as the algorithm processor, and a MSP430F149 chip as a...
BrainNetVis is an application, written in Java, that displays and analyzes synchronization networks from brain signals. The program implements a number of network indices and visualization techniques. We demonstrate its use through a case study of left hand and foot motor imagery. The data sets were provided by the Berlin BCI group. Using this program we managed to find differences between the average...
For the past few years, the potential of transcranial direct current stimulation (tDCS) for the treatment of several pathologies has been investigated. Knowledge of the current density distribution is an important factor in optimizing such applications of tDCS. We use the finite element method to compare three different models in tDCS, where the stimulation electrodes (EEG electrodes) are placed in...
An active paradigm was employed to produce reliable and prominent target response in an auditory brain computer interface (BCI), in which subject's voluntary recognition of the property of a target human voice enhances the discriminability between target and non-target EEG response. Furthermore, to adaptively decide the optimal number of trials being averaged for SVM classification, a statistical...
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