An inversion method based on random sampling for real-time MEG neuroimaging

The MagnetoEncephaloGraphy (MEG) is a non-invasive neuroimaging technique with a high temporal resolution which can be successfully used in real-time applications, such as brain-computer interface training or neurofeedback rehabilitation. The localization of the active area of the brain from MEG data results in a highly ill-posed and ill-conditioned inverse problem that requires fast and efficient inversion methods to be solved. In this paper we use an inversion method based on random spatial sampling to solve the MEG inverse problem. The method is fast, efficient and has a low computational load. The numerical tests show that the method can produce accurate map of the electric activity inside the brain even in case of deep neural sources

Prospects for atomic magnetometers employing hollow core optical fibre

Presently, among the most demanding applications for highly sensitive magnetometers are Magnetocardiography (MCG) and Magnetoencephalography (MEG), where sensitivities of around 1pT.Hz<sup>-1/2</sup> and 1fT.Hz<sup>-1/2</sup> are required. Cryogenic Superconducting Quantum Interference Devices (SQUIDs) are currently used as the magnetometers. However, there has been some recent work on replacing these devices with magnetometers based on atomic spectroscopy and operating at room temperature. There are demonstrations of MCG and MEG signals measured using atomic spectroscopy These atomic magnetometers are based on chip-scale microfabricated components. In this paper we discuss the prospects of using photonic crystal optical fibres or hollow core fibres (HCFs) loaded with Rb vapour in atomic magnetometer systems. We also consider new components for magnetometers based on mode-locked semiconductor lasers for measuring magnetic field via coherent population trapping (CPT) in Rb loaded HCFs

Detection of temporal-lobe epilepsy with the physiological responses to fear and anxiety

Epilepsy is a neurological disease caused by an abnormal neuronal activity on a region of the brain, which provokes seizures and the loss of consciousness to its patients. Epilepsy can be very disabling, since patients do not know when crisis or seizures are going to occur. The epilepsy we will focus on is "temporal lobe epilepsy", which is caused because of an abnormal neuronal activity on the temporal lobe. Before the development of an onset, the brain's temporal lobe -and consequently, the amygdala- are activated. Once having assured the relationship between the amygdala and an onset, the project will analyse the relationship between high levels of fear and anxiety -related with amygdala functions- and the development of a seizure. After determining what the relationship between fear and anxiety and the start of the seizure is, the project aims to develop a device that can do that by itself. The device will detect the patients' heart rate -since it is the main reaction to fear- and, when the heart rate is high enough to develop into a seizure, it will warn the patient. Thanks to that, epilepsy patients will live less anxious, since they will know when a seizure is going to happen and they will be able prevent themselves from the damages which might occur

Examining Neural Synchrony in Autism During Resting State With Magnetoencephalography (MEG)

Autism Spectrum Disorder (ASD) comprises a group of neurodevelopmental disorders associated with the functioning of the central nervous system (American Psychiatric Association, 2013). The symptoms experienced by individuals with this disorder include social impairment, communication difficulties, and repetitive and stereotyped behaviors. The etiology of ASD has yet to be determined, and it is typically diagnosed based on behavioral criteria of the Diagnostic and Statistical Manual- 5th Edition (DSM-5; APA, 2013) and confirmed with “gold standard” assessment tools such as the Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview- Revised (ADI-R; Johnson Center for Child Health Development, 2014). Abnormalities in synchronous neural activity have been hypothesized to be a core pathophysiological mechanism (Cornew et al., 2012). Magnetoencephalography (MEG) can measure synchronous neural activity during resting state, when the brain is not consciously engaged in cognitive processing. Coherence is a measure of the synchronicity. We examined differences in coherence during resting state in ASD, compared to neurotypical developing individuals (NT), in an attempt to identify potential biomarkers and illuminate a core etiological mechanism

Non-Conscious Brain Processes Revealed by Magnetoencephalography (MEG)

Information processing in the human brain can happen fully conscious or in total absence of consciousness. Despite being far away from understanding consciousness in terms of being a subjective phenomenon based on neural activity we can at least imagine what it means to be consciously aware of a sensory perception or knowledge or ourselves. At the very moment we know that we know and what we know, the respective knowledge is consciously processed and can be verbally expressed, but what about information processing in the absence of consciousness? Can non-conscious information processing do the same just without consciousness? It is difficult to imagine what kind of information processing happens below the level of consciousness and what it actually means. What does non-conscious information look like? What does non-conscious information represent and what can it do? These are important questions to be answered in order to better understand consciousness itself. Among others a recent review reports about unconscious high-level processing in the human brain. In this review, the authors summarise scientific evidence to support the idea that decision making, an apparently conscious process, as well as other parts of highly sophisticated human behaviour can happen automatically without conscious control. This is exactly in line with the spirit of this book chapter that is written to support this notion with neuroimaging data collected via magnetoencephalography (MEG)