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We generalize the Kuramoto model for coupled phase oscillators by allowing the frequencies to drift in time according to Ornstein-Uhlenbeck dynamics. Such drifting frequencies were recently measured in cellular populations of circadian oscillator and inspi ...
Voltage-sensitive dye imaging resolves the spatiotemporal dynamics of supragranular subthreshold cortical activity with millisecond temporal resolution and subcolumnar spatial resolution. We used a flexible fiber optic image bundle to visualize voltage-sen ...
Successful behavior depends on effective communication between distant brain regions. Moreover, disturbance of effective communication can cause neurological symptoms like apraxia, dyslexia or object agnosia. Interregional communication can be assessed by ...
We propose a novel detection method for non-coherent synchronization (signal acquisition) in multi-access UWB impulse radio (IR) networks. It is designed to solve the IUI (Inter-User Interference) that occurs in some ad-hoc networks where concurrent transm ...
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 r ...
In this paper, we investigate the use of brain activity for person authentication. It has been shown in previous studies that the brain-wave pattern of every individual is unique and that the electroencephalogram (EEG) can be used for biometric identificat ...
Gradient boosting is a machine learning method, that builds one strong classifier from many weak classifiers. In this work, an algorithm based on gradient boosting is presented, that detects event-related potentials in single electroencephalogram (EEG) tri ...
To understand the interface between global brain function and molecular neuroscience--that is, the microcircuit level--a major challenge. Such understanding is prerequisite if we are to account for neural function in cellular terms. Very few vertebrate mic ...
Brain-computer interfaces, as any other interaction modality based on physiological signals and body channels (e.g., muscular activity, speech and gestures), are prone to errors in the recognition of subject's intent. In this paper we exploit a unique feat ...
We compare the use of two Markovian models, HMMs and IOHMMs, to discriminate between three mental tasks for brain computer interface systems using an asynchronous protocol. We show that IOHMMs outperform HMMs but that, probably due to the lack of any prior ...