This document provides an overview of magnetoencephalography (MEG), a non-invasive brain imaging technique. MEG measures magnetic fields produced by neuronal activity in the brain with millisecond temporal resolution. It has advantages over other functional imaging methods in measuring fast network oscillations. The document describes how MEG works, the data acquisition and analysis process, and its potential applications in studying neurodegeneration and understanding brain function at the network level.
Magnetoencephalography (MEG) is a non-invasive technique that measures the magnetic fields generated by neuronal brain activity. MEG uses very sensitive magnetometers to record these natural magnetic fields produced by the brain's electrical currents. Though brain signals appear irregular, they may be generated by deterministic nonlinear systems. MEG provides both high temporal resolution and excellent spatial resolution of brain function without exposure to radiation or invasive procedures.
MEG measures the magnetic fields generated by electric currents in the brain. It has very high temporal resolution and good spatial resolution when combined with MRI. MEG is more sensitive than EEG to superficial cortical activity due to the way magnetic fields propagate. It is useful for localizing epileptic foci prior to epilepsy surgery and mapping eloquent cortex. Source analysis is performed to estimate the location of cortical generators. MEG provides better spatial resolution than EEG for localizing interictal epileptic discharges.
The document discusses various current applications of electroencephalography (EEG) technology both within and outside of clinical settings. It outlines EEG's predominant use in epilepsy and sleep disorder diagnosis clinically. It also explores recent developments that enable portable and cheaper EEG units, allowing novel consumer and research applications. Specifically, the document examines EEG's role in investigating sleep disorders, assessing brain death, monitoring anesthesia depth, cognitive engagement, brain development, and more. It explores EEG's growing use in cognitive science, neuroscience, and other research domains. Finally, it discusses emerging areas like brain-computer interfaces, closed-loop systems, and neuromarketing.
MEG measures magnetic fields produced by electrical activity in the brain. It provides high spatial resolution to localize brain regions activated during specific cognitive tasks and can help localize epileptic seizures. While MEG was first developed in the 1970s, advances over decades now allow it to map brain rhythms, language processing, connectivity between regions, and development from prenatal periods to learning. Key applications include epilepsy evaluation, mapping functional areas near brain tumors to guide surgery, and monitoring stroke recovery and chronic pain.
1. Impedance is opposition to alternating current flow and has two components: resistance and reactance. Resistance opposes direct current, while reactance depends on frequency and includes capacitance and inductance. (2) Because EEG contains strong AC signals, impedance rather than just resistance is measured. (3) Electrode impedance is measured by passing a small current between electrodes and is impacted by dead skin cells separating the electrode from living tissue.
MagnetoenCephaloGraphy (MEG) is a technique for mapping brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain, using very sensitive magnetometers.
Artifacts in EEG - Recognition and differentiationRahul Kumar
This Presentation discusses the variously commonly seen artifacts in EEG, and how to recognize them. In EEG interpretation, it is often more important to identify an artifact than to identify true pathology. Once all the artifacts are ruled out, one is sure that what one is dealing with represents disease/abnormality
The document summarizes the history and technical aspects of conventional EEG. It discusses how EEG works to detect and amplify the brain's electrical activity, which is measured using electrodes placed on the scalp. Different electrode placements and montages are used to view brain activity from various regions and perspectives. While imaging techniques now provide anatomical details, EEG remains clinically useful for evaluating brain function in various neurological disorders.
Magnetoencephalography (MEG) is a non-invasive technique that measures the magnetic fields generated by neuronal brain activity. MEG uses very sensitive magnetometers to record these natural magnetic fields produced by the brain's electrical currents. Though brain signals appear irregular, they may be generated by deterministic nonlinear systems. MEG provides both high temporal resolution and excellent spatial resolution of brain function without exposure to radiation or invasive procedures.
MEG measures the magnetic fields generated by electric currents in the brain. It has very high temporal resolution and good spatial resolution when combined with MRI. MEG is more sensitive than EEG to superficial cortical activity due to the way magnetic fields propagate. It is useful for localizing epileptic foci prior to epilepsy surgery and mapping eloquent cortex. Source analysis is performed to estimate the location of cortical generators. MEG provides better spatial resolution than EEG for localizing interictal epileptic discharges.
The document discusses various current applications of electroencephalography (EEG) technology both within and outside of clinical settings. It outlines EEG's predominant use in epilepsy and sleep disorder diagnosis clinically. It also explores recent developments that enable portable and cheaper EEG units, allowing novel consumer and research applications. Specifically, the document examines EEG's role in investigating sleep disorders, assessing brain death, monitoring anesthesia depth, cognitive engagement, brain development, and more. It explores EEG's growing use in cognitive science, neuroscience, and other research domains. Finally, it discusses emerging areas like brain-computer interfaces, closed-loop systems, and neuromarketing.
MEG measures magnetic fields produced by electrical activity in the brain. It provides high spatial resolution to localize brain regions activated during specific cognitive tasks and can help localize epileptic seizures. While MEG was first developed in the 1970s, advances over decades now allow it to map brain rhythms, language processing, connectivity between regions, and development from prenatal periods to learning. Key applications include epilepsy evaluation, mapping functional areas near brain tumors to guide surgery, and monitoring stroke recovery and chronic pain.
1. Impedance is opposition to alternating current flow and has two components: resistance and reactance. Resistance opposes direct current, while reactance depends on frequency and includes capacitance and inductance. (2) Because EEG contains strong AC signals, impedance rather than just resistance is measured. (3) Electrode impedance is measured by passing a small current between electrodes and is impacted by dead skin cells separating the electrode from living tissue.
MagnetoenCephaloGraphy (MEG) is a technique for mapping brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain, using very sensitive magnetometers.
Artifacts in EEG - Recognition and differentiationRahul Kumar
This Presentation discusses the variously commonly seen artifacts in EEG, and how to recognize them. In EEG interpretation, it is often more important to identify an artifact than to identify true pathology. Once all the artifacts are ruled out, one is sure that what one is dealing with represents disease/abnormality
The document summarizes the history and technical aspects of conventional EEG. It discusses how EEG works to detect and amplify the brain's electrical activity, which is measured using electrodes placed on the scalp. Different electrode placements and montages are used to view brain activity from various regions and perspectives. While imaging techniques now provide anatomical details, EEG remains clinically useful for evaluating brain function in various neurological disorders.
The document discusses electroencephalography (EEG), which measures the electrical activity of the brain using electrodes placed on the scalp. It describes brain anatomy, including the cerebrum, cerebellum, and brainstem. It also discusses the 10-20 international system for electrode placement on the scalp and the different types of brain waves that can be measured by EEG, including alpha, beta, theta, delta, and gamma waves. The document provides an overview of how EEG is used to record and analyze brain activity for applications such as epilepsy diagnosis, monitoring anesthesia and brain injury.
Transcranial magnetic stimulation (TMS) is a noninvasive procedure that uses magnetic fields to stimulate nerve cells in the brain and has shown positive results in treating depression. Repetitive transcranial magnetic stimulation (rTMS) involves placing an electromagnet against the patient's head to deliver magnetic bursts and stimulate the brain region involved in mood control. rTMS has evolved as a tool for improving various neurological and psychiatric disorders beyond just depression.
EEG is used to record the electrical activity of the brain. It uses electrodes placed on the scalp that are smaller than those used in ECGs. EEG can be used to diagnose neurological disorders like epilepsy. There are different types of brain waves like delta, theta, alpha, beta, and gamma waves that are defined by their frequency ranges and locations in the brain. Evoked potentials involve stimulating specific sensory pathways and measuring the electrical response in certain brain areas to help diagnose conditions.
The 10-20 system is an internationally recognized method for standardizing EEG electrode placement on the scalp. It is based on the relationship between electrode positions and the underlying areas of the cerebral cortex. Electrodes are placed at fixed locations based on percentages of the total front-to-back or right-to-left distance of the head. Letters and numbers identify the hemisphere and lobe locations of the electrodes. The system allows for reproducible positioning of scalp electrodes across patients and research studies.
Trans cranial magnetic stimulation - Diagnostic & Therapeutic applicationNeurologyKota
Transcranial magnetic stimulation (TMS) is a non-invasive technique that uses electromagnetic induction to stimulate neural tissue without causing pain. TMS can have acute effects like activating neural circuits or disrupting speech, as well as prolonged effects like changing synaptic strength and modulating cortical excitability. TMS has diagnostic applications like measuring motor thresholds and central motor conduction time to evaluate motor pathways, and therapeutic applications for treating depression, Parkinson's disease, neuropathic pain, and more. Common TMS protocols include single pulse, paired pulse, and repetitive TMS with low or high frequency stimulation. TMS is generally safe but can infrequently cause minor side effects like headaches.
This ppt describes the various features, signal processing methods that are commonly applied like wavelet, HHT, FT etc. Hope it helps someone understand better. EEG During mental arithmetic task dataset is used.
The document discusses electrophysiology techniques used to study the electrical activity of neurons and other excitable cells. It begins by explaining that electrophysiology allows measurement of ionic currents across cell membranes and helps understand how cells and tissues function. Different techniques are then described, including intracellular recordings, patch clamp recordings, and extracellular recordings. The document outlines the historical development of the field and covers topics like resting membrane potentials, action potentials, ion channels, and how neurons encode and transmit information.
- The EEG records electrical activity from the cerebral cortex which is amplified over 10 million times to be visible. It detects action potentials and post-synaptic potentials from neurons.
- Electrodes are placed on standardized locations on the scalp according to the 10-20 or 10-10 systems to allow comparison across studies. Recordings can be bipolar between adjacent electrodes or referential against a common electrode.
- Activity is recorded through amplifiers and can be displayed through different montages optimized for localization or overall brain activity. Calibration ensures consistent sensitivity and filtering removes unwanted interference.
Brainstem Auditory Evoked Potentials (BAEP) involves recording electrophysiological responses from the ear in response to auditory stimulation to assess the functioning of the auditory pathway. BAEP testing involves placing electrodes on the scalp to record waveforms representing activity in the auditory nerve and brainstem in response to click sounds. BAEP is useful for screening and monitoring conditions affecting the auditory pathway such as tumors near the cerebellopontine angle, multiple sclerosis, and coma. It can also be used for newborn hearing screening and evaluating stroke and tuberculous meningitis patients.
This document provides an overview of electromyography (EMG) including:
1. EMG measures the bioelectric potentials of muscle activity through either inserted fine-wire or needle electrodes, or skin surface electrodes.
2. Different types of electrodes have advantages and disadvantages related to sensitivity, ability to access deep muscles, risk of cross-talk, and ease of use.
3. Factors like signal-to-noise ratio and minimal signal distortion are important to maximize the quality of EMG signals.
Cardiac artifacts appear as periodic waves that are time-locked to the heartbeat as recorded by ECG. They include electrical artifacts seen as QRS complexes and mechanical artifacts seen as pulse waves. Electrode artifacts occur due to poor electrode contact or lead movement and appear as irregular waves of varying morphology and amplitude. External device artifacts are caused by electrical or mechanical devices and may appear as 50/60Hz noise, spike-like waves from IV drips, or irregular high amplitude waves from electrical motors. Artifacts must be distinguished from physiological activity and epileptiform discharges based on characteristics like distribution, morphology, and periodicity to avoid misinterpretation.
EEG measures the electrical activity of the brain through electrodes placed on the scalp. It can detect different wave patterns associated with different brain states. Evoked potentials involve stimulating a sensory pathway and measuring the electrical response along the pathway. This allows localization of lesions. Somatosensory evoked potentials involve stimulating a peripheral nerve like the median nerve and measuring the response along the pathway to detect spinal cord or brain injuries. Auditory evoked potentials involve measuring the brainstem response to a click stimulus to detect acoustic neuromas or other posterior fossa lesions. Both evoked potentials and EMG monitoring are used during surgery to detect injuries.
This document discusses EEG (electroencephalography) and provides an overview of several key topics:
- It outlines the agenda/topics to be covered including the history of EEG, neural activities, action potentials, EEG generation, brain rhythms, recording and measurement techniques, abnormal EEG patterns, aging effects, and mental disorders.
- It describes how EEG signals are generated by the electrical activity of neurons in the brain and measured via electrodes on the scalp. Different brain wave frequencies (rhythms) can be identified in the EEG based on amplitude and frequency.
- Recording, measuring, and processing EEG signals requires electrodes, amplifiers, filters, and techniques like sampling to convert the analog signals to digital
Nerve conduction studies and electromyography are used to diagnose disorders of the peripheral nervous system including motor and sensory neurons, nerve roots, plexuses, peripheral nerves, neuromuscular junctions, and muscles. The document provides details on the anatomy and physiology relevant to nerve conduction studies and electromyography. It then describes the fundamentals and technical aspects of performing nerve conduction studies to evaluate motor, sensory, and mixed nerves. Common conduction study patterns are presented to characterize axonal loss, demyelination, myopathies, and neuromuscular junction disorders. Late responses including F-waves, H-reflexes, and axon reflexes are also summarized.
This lecture is all about the recognition of an abnormal EEG, its characteristics, its appearance and all about how to differentiate the abnormal activity with normal EEG background.
The working of diffrent transducers and its priciples are discussed. The various types of sensors, transducers for the biopotential detections are also discussed with necessary diagrams.
EEG - Montages, Equipment and Basic PhysicsRahul Kumar
This presentation discusses the 10-20 system of electrode placement, with its modifications. Also discussed are the Equipment Specifications, basic Physics and sources of interference
Electroencephalography (eeg),electrical activity recorded via electrodes on the scalp,Neurophysiological Basis of EEG,Scalp EEG Recordings,Wearable EEG Devices,Recording EEG Signals,EEG Rhythms,
MNG Europe is an outsourced business development and consultancy firm based in Switzerland that specializes in helping innovative technology companies enter, establish, or expand their business in Europe. There are many challenges to doing business in Europe, such as cultural differences between markets and the importance of relationships. MNG Europe can provide clients with an instant European presence through their experienced professionals who can generate leads, manage partnerships, and help clients avoid the high costs and risks of setting up remote operations themselves.
Slides from an invited talk I gave at the MEG Basics series in the winter of 2012. Covers the theory behind signal processing techniques used in magnetoencephalography (MEG), including:
- Signal Space Projection (SSP)
- Signal Space Separation (SSS)
- Temporally-extended Signal Space Separation (tSSS)
- Principle Component Analysis (PCA)
- Independent Component Analysis (ICA)
The document discusses electroencephalography (EEG), which measures the electrical activity of the brain using electrodes placed on the scalp. It describes brain anatomy, including the cerebrum, cerebellum, and brainstem. It also discusses the 10-20 international system for electrode placement on the scalp and the different types of brain waves that can be measured by EEG, including alpha, beta, theta, delta, and gamma waves. The document provides an overview of how EEG is used to record and analyze brain activity for applications such as epilepsy diagnosis, monitoring anesthesia and brain injury.
Transcranial magnetic stimulation (TMS) is a noninvasive procedure that uses magnetic fields to stimulate nerve cells in the brain and has shown positive results in treating depression. Repetitive transcranial magnetic stimulation (rTMS) involves placing an electromagnet against the patient's head to deliver magnetic bursts and stimulate the brain region involved in mood control. rTMS has evolved as a tool for improving various neurological and psychiatric disorders beyond just depression.
EEG is used to record the electrical activity of the brain. It uses electrodes placed on the scalp that are smaller than those used in ECGs. EEG can be used to diagnose neurological disorders like epilepsy. There are different types of brain waves like delta, theta, alpha, beta, and gamma waves that are defined by their frequency ranges and locations in the brain. Evoked potentials involve stimulating specific sensory pathways and measuring the electrical response in certain brain areas to help diagnose conditions.
The 10-20 system is an internationally recognized method for standardizing EEG electrode placement on the scalp. It is based on the relationship between electrode positions and the underlying areas of the cerebral cortex. Electrodes are placed at fixed locations based on percentages of the total front-to-back or right-to-left distance of the head. Letters and numbers identify the hemisphere and lobe locations of the electrodes. The system allows for reproducible positioning of scalp electrodes across patients and research studies.
Trans cranial magnetic stimulation - Diagnostic & Therapeutic applicationNeurologyKota
Transcranial magnetic stimulation (TMS) is a non-invasive technique that uses electromagnetic induction to stimulate neural tissue without causing pain. TMS can have acute effects like activating neural circuits or disrupting speech, as well as prolonged effects like changing synaptic strength and modulating cortical excitability. TMS has diagnostic applications like measuring motor thresholds and central motor conduction time to evaluate motor pathways, and therapeutic applications for treating depression, Parkinson's disease, neuropathic pain, and more. Common TMS protocols include single pulse, paired pulse, and repetitive TMS with low or high frequency stimulation. TMS is generally safe but can infrequently cause minor side effects like headaches.
This ppt describes the various features, signal processing methods that are commonly applied like wavelet, HHT, FT etc. Hope it helps someone understand better. EEG During mental arithmetic task dataset is used.
The document discusses electrophysiology techniques used to study the electrical activity of neurons and other excitable cells. It begins by explaining that electrophysiology allows measurement of ionic currents across cell membranes and helps understand how cells and tissues function. Different techniques are then described, including intracellular recordings, patch clamp recordings, and extracellular recordings. The document outlines the historical development of the field and covers topics like resting membrane potentials, action potentials, ion channels, and how neurons encode and transmit information.
- The EEG records electrical activity from the cerebral cortex which is amplified over 10 million times to be visible. It detects action potentials and post-synaptic potentials from neurons.
- Electrodes are placed on standardized locations on the scalp according to the 10-20 or 10-10 systems to allow comparison across studies. Recordings can be bipolar between adjacent electrodes or referential against a common electrode.
- Activity is recorded through amplifiers and can be displayed through different montages optimized for localization or overall brain activity. Calibration ensures consistent sensitivity and filtering removes unwanted interference.
Brainstem Auditory Evoked Potentials (BAEP) involves recording electrophysiological responses from the ear in response to auditory stimulation to assess the functioning of the auditory pathway. BAEP testing involves placing electrodes on the scalp to record waveforms representing activity in the auditory nerve and brainstem in response to click sounds. BAEP is useful for screening and monitoring conditions affecting the auditory pathway such as tumors near the cerebellopontine angle, multiple sclerosis, and coma. It can also be used for newborn hearing screening and evaluating stroke and tuberculous meningitis patients.
This document provides an overview of electromyography (EMG) including:
1. EMG measures the bioelectric potentials of muscle activity through either inserted fine-wire or needle electrodes, or skin surface electrodes.
2. Different types of electrodes have advantages and disadvantages related to sensitivity, ability to access deep muscles, risk of cross-talk, and ease of use.
3. Factors like signal-to-noise ratio and minimal signal distortion are important to maximize the quality of EMG signals.
Cardiac artifacts appear as periodic waves that are time-locked to the heartbeat as recorded by ECG. They include electrical artifacts seen as QRS complexes and mechanical artifacts seen as pulse waves. Electrode artifacts occur due to poor electrode contact or lead movement and appear as irregular waves of varying morphology and amplitude. External device artifacts are caused by electrical or mechanical devices and may appear as 50/60Hz noise, spike-like waves from IV drips, or irregular high amplitude waves from electrical motors. Artifacts must be distinguished from physiological activity and epileptiform discharges based on characteristics like distribution, morphology, and periodicity to avoid misinterpretation.
EEG measures the electrical activity of the brain through electrodes placed on the scalp. It can detect different wave patterns associated with different brain states. Evoked potentials involve stimulating a sensory pathway and measuring the electrical response along the pathway. This allows localization of lesions. Somatosensory evoked potentials involve stimulating a peripheral nerve like the median nerve and measuring the response along the pathway to detect spinal cord or brain injuries. Auditory evoked potentials involve measuring the brainstem response to a click stimulus to detect acoustic neuromas or other posterior fossa lesions. Both evoked potentials and EMG monitoring are used during surgery to detect injuries.
This document discusses EEG (electroencephalography) and provides an overview of several key topics:
- It outlines the agenda/topics to be covered including the history of EEG, neural activities, action potentials, EEG generation, brain rhythms, recording and measurement techniques, abnormal EEG patterns, aging effects, and mental disorders.
- It describes how EEG signals are generated by the electrical activity of neurons in the brain and measured via electrodes on the scalp. Different brain wave frequencies (rhythms) can be identified in the EEG based on amplitude and frequency.
- Recording, measuring, and processing EEG signals requires electrodes, amplifiers, filters, and techniques like sampling to convert the analog signals to digital
Nerve conduction studies and electromyography are used to diagnose disorders of the peripheral nervous system including motor and sensory neurons, nerve roots, plexuses, peripheral nerves, neuromuscular junctions, and muscles. The document provides details on the anatomy and physiology relevant to nerve conduction studies and electromyography. It then describes the fundamentals and technical aspects of performing nerve conduction studies to evaluate motor, sensory, and mixed nerves. Common conduction study patterns are presented to characterize axonal loss, demyelination, myopathies, and neuromuscular junction disorders. Late responses including F-waves, H-reflexes, and axon reflexes are also summarized.
This lecture is all about the recognition of an abnormal EEG, its characteristics, its appearance and all about how to differentiate the abnormal activity with normal EEG background.
The working of diffrent transducers and its priciples are discussed. The various types of sensors, transducers for the biopotential detections are also discussed with necessary diagrams.
EEG - Montages, Equipment and Basic PhysicsRahul Kumar
This presentation discusses the 10-20 system of electrode placement, with its modifications. Also discussed are the Equipment Specifications, basic Physics and sources of interference
Electroencephalography (eeg),electrical activity recorded via electrodes on the scalp,Neurophysiological Basis of EEG,Scalp EEG Recordings,Wearable EEG Devices,Recording EEG Signals,EEG Rhythms,
MNG Europe is an outsourced business development and consultancy firm based in Switzerland that specializes in helping innovative technology companies enter, establish, or expand their business in Europe. There are many challenges to doing business in Europe, such as cultural differences between markets and the importance of relationships. MNG Europe can provide clients with an instant European presence through their experienced professionals who can generate leads, manage partnerships, and help clients avoid the high costs and risks of setting up remote operations themselves.
Slides from an invited talk I gave at the MEG Basics series in the winter of 2012. Covers the theory behind signal processing techniques used in magnetoencephalography (MEG), including:
- Signal Space Projection (SSP)
- Signal Space Separation (SSS)
- Temporally-extended Signal Space Separation (tSSS)
- Principle Component Analysis (PCA)
- Independent Component Analysis (ICA)
Magnetoencephalography (meg) and diffusion tensor imagingAdonis Sfera, MD
The document discusses using magnetoencephalography (MEG) and diffusion tensor imaging (DTI) to better diagnose mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD). Conventional imaging like CT and MRI often miss injuries from mTBI and find nothing abnormal for PTSD. MEG can detect abnormal low-frequency brain signals from injured areas in mTBI patients. DTI can find reduced anisotropy in white matter tracts, providing evidence of axonal injuries linked to areas generating MEG signals. Combining MEG and DTI findings provides stronger evidence of neuronal injury in mTBI than conventional imaging alone. MEG may also detect hyperactivated brain networks involved in PTSD
This document provides information about electroencephalography (EEG) and how it is used to diagnose and classify epilepsy. It discusses how EEG detects abnormal brain wave patterns associated with seizures. Specific EEG patterns can help distinguish between different types of partial and generalized seizures. Partial seizures are localized to one area of the brain, while generalized seizures involve both hemispheres. Common seizure types discussed include simple and complex partial, absence, myoclonic, clonic, tonic, and tonic-clonic seizures. The EEG patterns that correspond to each seizure type are described to aid in diagnosis and classification of epilepsy.
This document provides an overview of various epilepsy syndromes classified by onset in the brain and cause of seizures. It describes several generalized and focal epilepsy syndromes including childhood absence epilepsy, juvenile myoclonic epilepsy, benign epilepsy with centrotemporal spikes, Panayiotopoulos syndrome, autosomal dominant nocturnal frontal lobe epilepsy, Doose's syndrome, Dravet's syndrome, infantile spasms/West syndrome, Lennox-Gastaut syndrome, and Ohtahara syndrome. For each syndrome, it covers key characteristics, EEG findings, treatment approaches, and typical prognosis.
The document discusses various epileptic syndromes categorized by age of onset - neonatal, infancy, childhood, adolescence-adult. For each syndrome, it provides information on defining features, age of onset, seizure types, EEG patterns, treatment and prognosis. The syndromes discussed include benign familial neonatal epilepsy, Ohtahara syndrome, West syndrome, Panayiotopoulos syndrome, Lennox-Gastaut syndrome, juvenile myoclonic epilepsy and others.
Article Review on Simultanoeus Optical Stimulation and Electrical Recording f...Md Kafiul Islam
This summarizes a document reviewing an integrated device for combined optical neuromodulation and electrical recording for chronic in-vivo applications. The device consists of an optical fiber integrated with a microelectrode array (MEA), called an optrode-MEA, that allows for simultaneous optical stimulation and electrophysiological recording. The summary is:
[1] The optrode-MEA was developed to allow for optical stimulation at one cortical site while recording neural activity from surrounding neurons to study local circuit dynamics. [2] Experiments in freely moving rats demonstrated the device could successfully record neural signals over months, mapping spatially and temporally resolved neuronal responses. [3] Analysis of recorded signals under different stimulation conditions proved the
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
International Journal of Computational Engineering Research(IJCER)ijceronline
This document summarizes a research paper that aims to estimate human consciousness levels using electroencephalography (EEG) and wavelet analysis. The paper describes collecting EEG signals from electrodes placed on a subject's forehead and earlobe. The signals are filtered to extract beta waves associated with consciousness. Wavelet decomposition is then applied using Daubechies wavelets to further analyze consciousness levels. Results found good agreement between estimated consciousness from EEG signals and a subject's actual cognitive state under different drug conditions.
Magnetoencephalography an emerging biological marker for neurodegenerative an...Adonis Sfera, MD
Magnetoencephalography (MEG) is a technique that measures magnetic fields produced by electrical currents in the brain to map functional areas with great temporal resolution. MEG detects alterations in brain structure correlated with changes in function as seen with MRI. A new combined MEG-MRI device can simultaneously record ultra-low-field MRI and MEG to unprecedentedly locate brain activity. MEG has accurately diagnosed PTSD at 90% by identifying patterns unique to sufferers, and combining with diffusion tensor imaging may further improve diagnostic accuracy.
This document provides an overview of repetitive transcranial magnetic stimulation (rTMS) technique and its current status. It discusses how rTMS works by using changing magnetic fields to induce electric currents in the brain without the need for surgery. It summarizes the different types of rTMS protocols and their effects on neuronal activity. The document also reviews the diagnostic and therapeutic applications of rTMS, particularly for major depressive disorder. Clinical trials show rTMS can significantly reduce depressive symptoms compared to sham treatment with a mild side effect profile.
The document provides information on electroencephalography (EEG) and magnetoencephalography (MEG). It discusses the history of EEG, how the signals are recorded, various montages used, neural basis of the signals, analysis methods for EEG including evoked potentials and artifacts. MEG is described as detecting the magnetic fields generated by electrical activity in the brain using SQUIDs, and its increased sensitivity to activity in sulcal walls compared to EEG. Key differences between the two methods are the orientation of measured fields relative to current flow in neurons.
The document discusses compressive wideband power spectrum analysis for EEG signals using FastICA and neural networks. It first provides background on EEG signals and how they are measured. It then describes using FastICA to extract independent components from EEG signals related to detecting epileptic seizures. The independent components are then used to train a backpropagation neural network for effective detection of epileptic seizures. The proposed method involves preprocessing EEG signals, performing spectral estimation using FastICA, and classifying brain activity patterns using the neural network.
EEG and MEG are non-invasive neuroimaging techniques that measure electrical and magnetic fields produced by neural activity in the brain. EEG detects electrical currents using scalp electrodes, while MEG directly measures magnetic fields using SQUID magnetometers. Both have excellent temporal resolution of 1ms or less but MEG has better spatial resolution of under 1cm. Together, EEG and MEG provide insights into neural correlates of cognitive processes and are useful for clinical applications like epilepsy diagnosis.
Basis_MEEG_signal_LiS2 EEG is a signal pattern that is obtained by amplifying and recording the spontaneous biological potential of the brain on the scalp. This potential has been shown to reflect the macroscopic activity of the brain surface and is typically acquired using noninvasive electrodes applied onto the scalp.
The document discusses various electrophysiological procedures used in neuroscience research and clinical practice. It provides details on electroencephalography (EEG) including its history, physiology, procedures, applications, advantages and disadvantages. It also discusses related techniques like stereoelectroencephalography (SEEG), event-related potentials (ERPs), electrocorticography (ECoG), magnetoencephalography (MEG) and intraoperative neurophysiological monitoring (IONM).
This document presents a new approach to implementing an intelligent single neuron model in VLSI. It describes a neuron model with dendrites as inputs from surrounding neurons, and an axon to broadcast signals to other neurons. The proposed model includes a logic processing unit that determines which incoming signals to process based on an equality comparison, and which to ignore. Simulation results showed the new neuron model can make decisions about which signals to process or stop in the neural network. The approach aims to contribute to designing intelligent nodes in neural networks.
Neuroimaging and its implications in psychiatryRupinder Oberoi
This document discusses various neuroimaging techniques used to study the structure and function of the living human brain, including their applications and limitations. It describes computed tomography (CT), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), functional MRI (fMRI), and single photon emission computed tomography (SPECT). CT and MRI are used to examine brain structure, while fMRI, MRS and SPECT provide insights into brain function by detecting changes in blood flow, metabolism or radiotracer distribution associated with neuronal activity. These techniques have advanced understanding of neurological and psychiatric disorders but each has specific strengths and weaknesses for clinical or research applications.
Modelling and Analysis of EEG Signals Based on Real Time Control for Wheel ChairIJTET Journal
Free versatility is center to having the capacity to perform exercises of day by day living without anyone else's input. In this proposed framework introduce an imparted control construction modeling that couples the knowledge and cravings of the client with the exactness of a controlled wheelchair. Outspread Basis Function system was utilized to characterize the predefined developments, for example, rest, forward, regressive, left and right of the wheelchair. This EEG-based cerebrum controlled wheelchair has been produced for utilization by totally incapacitated patients. The proposed outline incorporates a novel methodology for selecting ideal terminal positions, a progression of sign transforming and an interface to a controlled wheelchair.The Brain Controlled Wheelchair (BCW) is a basic automated framework intended for individuals, for example, bolted in individuals, who are not ready to utilize physical interfaces like joysticks or catches. The objective is to add to a framework usable in healing centers and homes with insignificant base alterations, which can help these individuals recover some portability. Also, it is explored whether execution in the STOP interface would be influenced amid movement, and discovered no modification with respect to the static performance.Finally, the general procedure was assessed and contrasted with other cerebrum controlled wheelchair ventures. Notwithstanding the overhead needed to choose the destination on the interface, the wheelchair is quicker than others .It permits to explore in a commonplace indoor environment inside a sensible time. Accentuation was put on client's security and comfort,the movement direction procedure guarantees smooth, protected and unsurprising route, while mental exertion and exhaustion are minimized by lessening control to destination determination.
Neuroprosthetics involves using brain signals acquired from neurons for various purposes like restoring movement in paralyzed patients. Nanotechnology like nano multi-electrode arrays can be used to receive and transmit brain signals more effectively by increasing electrode conduction and reducing incorrect connections with neurons. Neuroprosthetics has applications in both in vivo and in vitro contexts and can help improve functions like movement, speech, and understanding of drug effects on animal behavior and emotions.
An extensive review over current technology, possibilities and ethical implications in the area of neuronal implants.
Topics include:
- different forms of neuronal implants
- problems with current technology
- future possibilities
This is habilitation dissertation thesis on the importance of EEE and LPF phase for understanding of brain state dynamics of possible quantum coherent macroscopic phase
INVITEDP A P E RSilicon-Integrated High-DensityElectro.docxvrickens
INVITED
P A P E R
Silicon-Integrated High-Density
Electrocortical Interfaces
This paper examines the state of the art of chronically implantable
electrocorticography (ECoG) interface systems and introduces a novel modular
ECoG system using an encapsulated neural interfacing acquisition chip (ENIAC)
that allows for improved, broad coverage in an area of high spatiotemporal
resolution.
By Sohmyung Ha, Member IEEE, Abraham Akinin, Student Member IEEE,
Jiwoong Park, Student Member IEEE, Chul Kim, Student Member IEEE,
Hui Wang, Student Member IEEE, Christoph Maier, Member IEEE,
Patrick P. Mercier, Member IEEE, and Gert Cauwenberghs, Fellow IEEE
ABSTRACT | Recent demand and initiatives in brain research
have driven significant interest toward developing chronically
implantable neural interface systems with high spatiotempo-
ral resolution and spatial coverage extending to the whole
brain. Electroencephalography-based systems are noninva-
sive and cost efficient in monitoring neural activity across the
brain, but suffer from fundamental limitations in spatiotem-
poral resolution. On the other hand, neural spike and local
field potential (LFP) monitoring with penetrating electrodes
offer higher resolution, but are highly invasive and inade-
quate for long-term use in humans due to unreliability in
long-term data recording and risk for infection and inflamma-
tion. Alternatively, electrocorticography (ECoG) promises a
minimally invasive, chronically implantable neural interface
with resolution and spatial coverage capabilities that, with
future technology scaling, may meet the needs of recently
proposed brain initiatives. In this paper, we discuss the chal-
lenges and state-of-the-art technologies that are enabling
next-generation fully implantable high-density ECoG inter-
faces, including details on electrodes, data acquisition front-
ends, stimulation drivers, and circuits and antennas for
wireless communications and power delivery. Along with
state-of-the-art implantable ECoG interface systems, we
introduce a modular ECoG system concept based on a fully
encapsulated neural interfacing acquisition chip (ENIAC).
Multiple ENIACs can be placed across the cortical surface,
enabling dense coverage over wide area with high spatio-
temporal resolution. The circuit and system level details of
ENIAC are presented, along with measurement results.
KEYWORDS | BRAIN Initiative; electrocorticography; neural
recording; neural stimulation; neural technology
I. INTRODUCTION
The Brain Research through Advancing Innovative Neuro-
technologies (BRAIN) Initiative envisions expanding our
understanding of the human brain. It targets development
and application of innovative neural technologies to ad-
vance the resolution of neural recording, and stimulation
toward dynamic mapping of the brain circuits and process-
ing [1], [2]. These advanced neurotechnologies will enable
new studies and experiments to augment our current unde ...
The document proposes integrating EEG, fMRI, and transcranial magnetic stimulation technologies to create an audiovisual art piece solely based on an individual's brain activity and thoughts. This fusion of neuroscience and art could also have medical applications such as diagnosing motor and sensory disorders and enhancing or inhibiting specific brain activity. However, manipulating brain structures could alter memory and consciousness, so use of these technologies needs to be carefully monitored.
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1. Magnetoencephalography
Malcolm Proudfoot,1,2
Mark W Woolrich,2
Anna C Nobre,2
Martin R Turner1
1
Nuffield Department of Clinical
Neurosciences, University of
Oxford, UK
2
Oxford Centre for Human Brain
Activity, University of Oxford, UK
Correspondence to
Dr Martin Turner, Nuffield
Department of Clinical
Neurosciences, West Wing
Level 3, John Radcliffe Hospital,
Oxford OX3 9DU, UK;
martin.turner@ndcn.ox.ac.uk
To cite: Proudfoot M,
Woolrich MW, Nobre AC,
et al. Pract Neurol Published
Online First: [please include
Day Month Year]
doi:10.1136/practneurol-
2013-000768
INTRODUCTION
The understanding of brain function is
moving rapidly towards a systems-level,
network-based approach. It is now as naive
to talk simplistically about what a particu-
lar area of the brain ‘does’, as it was for
Franz Joseph Gall (1758–1828) to link
its performance to the thickness of the
overlying skull. Magnetoencephalography
(MEG) is a rapidly developing and unique
tool for the study of brain function, in
particular the underlying oscillations in
neuronal activity that appear to be funda-
mental (box 1), with real-time resolution
and potential for application across a range
of brain disorders. We provide a brief
overview of the technology, broad
approaches to data analysis, and aspirations
for its application to the study of
neurodegeneration.
FUNCTIONAL BRAIN IMAGING SO FAR
Structural MR imaging of the brain and
spinal cord has revolutionised the accur-
acy of diagnosis in common conditions,
such as stroke, and greatly expanded the
taxonomy of neurological disorders.
Advanced applications of MRI now allow
the assessment of white matter tract
integrity (diffusion-tensor imaging),
regional grey matter volume (voxel-based
morphometry), and cortical thickness
(surface-based morphometry). These
techniques enable the non-invasive and
rapid quantification of structure at a
given time point, but it is clear that the
brain cannot be understood in terms of
structure alone. Functional MRI (fMRI),
based on blood oxygen-level-dependent
(BOLD) image contrast, can achieve
almost submillimetre accuracy in the
spatial localisation of neuronal activity.
However, this relatively high spatial reso-
lution is not matched in temporal accur-
acy, in essence because the relatively slow
speed of haemodynamic changes in
response to neuronal activity fundamen-
tally limits the temporal detail that can be
extracted to a timescale of seconds.
When one considers the multiple synaptic
transmissions and physical distance
covered by brain activity within this time
frame, it is quickly appreciated that this
technology is limited in its ability to
deliver a systems-level understanding of
brain function if used in isolation.
THE UNIQUE ADVANTAGES OF MEG
Ever since the pioneering EEG recordings
made by German neurologist Hans
Berger (1873–1941), it has been possible
to identify the self-generated oscillatory
activity of neuronal ensembles and cat-
egorise frequency bands with increasing
accuracy. Electrical potential changes
related to brain activity measured at the
scalp by EEG are fundamentally limited
Box 1 An introduction to neuronal
oscillations
▸ Neuronal oscillatory activity is continu-
ous, but fluctuations in power and
timing allow rapid alteration in com-
munication strength within existing
structural network architecture, far
faster than synaptic modification.1
▸ Two distinct cerebral regions can facili-
tate preferential information exchange
by synchronising their rhythmic behav-
iour; the γ band (40–80 Hz), in particu-
lar, facilitates this process, but is also
modulated ‘top-down’ by lower fre-
quencies such as θ (4–7 Hz), reflecting
factors, such as arousal states.
▸ α Rhythms (8–13 Hz), so prominent in
the occipital cortex upon eye closure,
reflect more than just an ‘idling’ rhythm
but also contribute to active allocation
of attentional resources and suppress
irrelevant sensory information.2
▸ The influential theory ‘Communication
through Coherence’ developed by
Fries,3
builds on existing models of
‘binding by synchronisation’ that may
underpin selective attention, a key func-
tion in prioritising neural events to
guide awareness and action.4
HOW TO UNDERSTAND IT
Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768 1
2. by the distortive effects of the intervening structures,
which severely hamper efforts to localise the signal
source precisely. MEG, instead, measures the magnetic
field changes induced by intracellular current flow, the
generation of which obeys the ‘right-hand rule’ in the
application of Ampère’s law. Unlike EEG measures,
these pass through dura, skull and scalp relatively
unaltered. The technique, therefore, offers a safe,
non-invasive method to ‘listen’ in to brain activity at
rest and during simple tasks, which from the subject’s
perspective, despite measuring at several hundred
channels, is painless and quick to set up.
Mathematical modelling of these data then enables
localisation of sources while uniquely maintaining
sampling frequencies up to several thousand times per
second. Compared to fMRI’s temporal resolution of,
at best, several hundred milliseconds, MEG can
resolve events with millisecond precision.
HOW IT WORKS
The neuronal activity captured by MEG is not, as
perhaps expected, generated by the (too brief) axonal
action potentials of pyramidal cells, but rather by the
net contributions of excitatory and inhibitory den-
dritic postsynaptic potentials. This current flow
through the apical dendrites (represented as a
‘dipole’) generates a magnetic field that projects radi-
ally; thus, MEG excels at detecting dipoles arranged
in a tangential orientation to the skull. Fortunately,
the extensively folded sulci of the human cortex
promote that orientation for the majority of cortical
microcolumns (figure 1). However, MEG is less sensi-
tive to deeper (including subcortical) sources, as mag-
netic field change decreases rapidly with distance.
Compared with a standard clinical MR scanner
magnet strength of 1.5 Tesla, the strength of the
signals detected by MEG are 1014
orders smaller
(figure 2). It has been compared with hearing a pin
drop at a rock concert. The smallest measurable mag-
netic field changes are thought to be produced by sim-
ultaneously active arrays of approximately 50 000
pyramidal cells, which in theory covers a cortical
surface area of 0.9 mm diameter. It is increasingly
recognised that modulation of self-generated oscilla-
tory activity is a principal mechanism by which geo-
graphically distant network regions interact,6
thus, a
brain-wide imaging technique with high temporal sen-
sitivity is a prerequisite for interrogation.
The ability to detect endogenously generated mag-
netic fields was realised in the 1960s by physicist
David Cohen at Massachusetts Institute of
Technology, who furthered the then recent discovery
of ‘magnetocardiography’ by applying a magnetically
shielded room to remove the overwhelming noise of
the Earth’s magnetic field (figure 3). He could then
measure the even smaller magnetoencephalographic
signal by making use of superconducting loops super-
conducting quantum interference device (SQUIDs),
developed by his collaborator James Zimmerman. At
very low temperatures, SQUIDs are extremely sensi-
tive to magnetic field change, which can be recorded
and converted into digital signal (‘quantisation’).
Sensor arrays have evolved to provide whole-head
coverage via a helmet containing more than 300
Figure 2 Magnetic field strength density measured in
femtotesla (fT), highlighting the exquisite sensitivity of the
SQUIDs used in magnetoencephalography.
Figure 1 The organisation of cortical microcolumns within the
sulcal bank, tangentially orientated to the skull, allows their
detection with magnetoencephalography since their induced
magnetic fields will project beyond the skull surface. Conversely,
apical dendrites orientated perpendicularly to the skull, as
found at the gyral crown, are better detected by EEG. (From
Hansen et al5
).
HOW TO UNDERSTAND IT
2 Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768
3. sensor sites, enveloped in a ‘dewar’ of cooling liquid
helium. The subject’s head is positioned underneath
the helmet (figure 4) and it is possible to acquire EEG
recordings simultaneously if desired. In the future,
MEG may include atomic sensors, which still exploit
the principle of quantum tunnelling of pairs of elec-
trons, but obviate the need for cryogenic
temperatures.7
THE ACQUISITION
The sensor design itself has evolved to meet some of
the localisation challenges by using more than one
pick-up coil in series. A single ‘magnetometer’ coil
measures any orthogonal magnetic field. Pairs of coils
place closed together and wound in opposite direc-
tions are also used to measure gradients in the mag-
netic field over space. These ‘gradiometers’ are
particularly sensitive to a gradient in magnetism from
nearby (ie, neuronal) sources, but subtract out signal
from distant external (and thus artefactual) sources, as
these appear similar to both coils.
Electromagnetic signals are also generated by move-
ment of the head or eyes (including blinking), skeletal
and cardiac muscle electromagnetic activity. The
sensors, therefore, also pick up this physiological
noise, unrelated to brain activity. Interference from
dental amalgam, metal zippers, jewellery, and bra fas-
teners is also significant and avoided by pre-scan
screens if possible. Head location must be calculated
relative to the SQUID sensors, since the helmet is not
a tight fit. This is achieved by using small magnetic
coils attached to anatomical landmarks to localise the
subject’s head position in the MEG scanner, and these
can also be used to enable continuous motion correc-
tion. However, it is also important to maximise
subject comfort to discourage excess head movement.
Considerable care must also be taken in ensuring
that all stimulus presentation and response devices
within the magnetically shielded room are themselves
electromagnetically silent. Experimental tasks are typ-
ically designed to avoid eye movements during rele-
vant measurement periods in order to minimise
artefact, but remaining eye movements and blinks can
still be identified with a combination of surface
electro-oculography and infrared eye tracking. An
ECG is typically also recorded to enable identification
and subsequent exclusion of cardiac electrical activity,
which can otherwise create large contaminating arte-
facts in the MEG signal. There are comprehensive
expert consensus guidelines aiming to harmonise
MEG experimental strategies across sites8
in an effort
to improve reproducibility.
THE ANALYSIS
MEG analysis involves enormous datasets that require
vast computer processing power to manipulate them.
Having overcome the initial difficulties in artefact
identification, MEG data analysis still involves consid-
erable complexity. The fundamental issue is that of
the ‘inverse problem’. This concept, in relation to
MEG, summarises the challenge of precisely localising
in three dimensional (3D) space the underlying neural
sources of a magnetic recording. In reality, there may
be many equally plausible combinations of neural
sources, and thus, without additional constraints the
solution is not unique. Yet, this is a challenge our own
brains overcome daily by using constraints that reflect
Figure 3 After 4 s of raw magnetoencephalography data (two
channels contain obvious artefacts), the door to the
magnetically shielded room is opened during recording. The
interference caused by external magnetic fields highlights why
effective room shielding is essential.
Figure 4 A MEG recording session at OHBA, eyetracker device
shown in foreground.
HOW TO UNDERSTAND IT
Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768 3
4. sensible prior assumptions, for example in deciding if
a visual object is small and close, or large and far
away. We have existing expectations about object size
to guide us.
Methods to solve the inverse problem, therefore,
need to make additional assumptions, such as the
brain activity being spatially sparse or smooth. The
appropriate assumptions to make are often directed
by the particular experimental protocol and expected
findings. A given paradigm may seek to identify differ-
ential brain activity during a rudimentary sensory
stimulation task, in which case the localisation model
might assume that a small number of dipole sources
could account for the difference in signal production
(ie, the brain activity is sparse). Alternatively, for
example during cognitive tasks, there is a wide net of
possible sources in the brain to consider, and we need
more advanced modelling techniques. This includes
approaches that assume the brain activity is smooth
and sparse,9
and also constrained to a 3D map of the
patient’s own cortical mantle (obtained during a sub-
sequent structural MRI). A common approach for
representing these various assumptions is to use priors
in powerful Bayesian algorithms. A popular alternative
to overcome the inverse problem is to use beamform-
ing. This method, originally developed for use in
radar arrays, corresponds to an adaptive spatial filter
designed to extract the origins of a signal from some
prespecified spatial location.10
MEG data in either ‘sensor space’ (presented as
data recorded across the distribution of the sensors)
or ‘source space’ (reconstructed to a 3D model of
brain sources) offer a wealth of analysis possibilities
and selected features that can relate to a particular
clinical question (figure 5).
For example, it is possible to analyse the data time-
locked to experimental events in terms of event-related
fields (ERF, the MEG analogue of event-related poten-
tials), such as the mismatch negativity abnormalities
described in dyslexia.11
Additionally, MEG is
particularly powerful at investigating oscillatory brain
activity by using ‘Fourier transformations’, or related
transforms, such as Wavelet or Hilbert, to describe the
signal in terms of how it oscillates in different fre-
quency bands over time. These frequency bands show
meaningful changes in power or synchronisation of
ongoing oscillatory activity at behaviourally relevant
time points, and can also form the basis of functional
connectivity measurements (correlated changes over
time) between different brain regions captured in
MEG data12
(figure 6).
THE APPLICATIONS AND POTENTIAL OF MEG
MEG has found early clinical application in epileptic
source localisation, in particular for the planning of
subsequent surgery, and shows close correlation to
invasive studies of cortical activity.13
In a new era,
MEG applications are no longer limited to description
of relatively fundamental neurophysiology, but have
instead begun to describe whole-brain activity at the
network-level during the so-called resting state14
(figure 7) as well as task performance.15
This approach has been pioneered by fMRI,16
but
MEG now validates these findings in eliminating arte-
factual explanations based solely on correlated patterns
of vascular activity. MEG also offers the possibility of
decomposing the time-course of communication
between ‘nodes’ in such networks, assessing their func-
tionality during task activity, and indeed describing
their dysfunction during neurodegenerative disease,17
with the ultimate hope of developing sensitive pharma-
codynamic markers of therapeutic response. MEG
also offers information complementary to fMRI; the
uncertain impact of disease on the time course of the
BOLD haemodynamic response function encourages
multimodal data acquisition during brain activation (by
Figure 5 Sensor space MEG data (A) presented as a two
dimensional (2D) topographic map of contrasted α (8–12 Hz)
activity in a visual attention task (data concatenated from 38
subjects). α power is lower in the contralateral (attending)
hemisphere. MEG data reconstructed into source space (B) with
a beamformer approach and presented on a 3D cortical map.
Figure 6 Time–frequency plot from posterior sensors
following presentation of a visual stimulus (multiple subjects
combined). Increased power is noted in θ followed shortly by γ.
Desynchronisation instead occurs in α and β bands. Vertical lines
denote stimulus onset/offset.
HOW TO UNDERSTAND IT
4 Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768
5. necessity non-concurrent, as MEG and fMRI cannot
be acquired simultaneously).18
MEG correlates of neurodegeneration
Focal slowing in temporoparietal regions was an
expected finding in early MEG studies of Alzheimer’s
disease, and was furthermore correlated with cogni-
tive measures.19
Attempts to model the source of
spontaneous α band activity also noted an anterior
shift from parieto-occipital regions to predominantly
temporal-lobe generators in Alzheimer’s disease versus
controls; this was interpreted to reflect somehow a
loss of cholinergic transmission.20
Another study pro-
vided more convincing evidence that described left
temporal MEG activity deficits, which correlated with
ipsilateral hippocampal atrophy and behavioural
measures.21
Surface EEG had already described abnormalities in
preattentive auditory processing of deviant tones in
neurodegenerative disease. These excessive evoked
response potential (ERP) abnormalities, perhaps
reflecting a failure to inhibit or adapt to irrelevant
stimuli, were convincingly replicated and localised in
MEG studies of Parkinson’s disease,22
Alzheimer’s
disease23
and amyotrophic lateral sclerosis.24
Subjects with Parkinson’s disease, even without
dementia, also show widespread oscillatory slowing.25
Furthermore, in combination with invasive local
recordings, MEG identified a dopamine-responsive
long-distance network operating in the β band that
showed coherence between prefrontal cortex and sub-
thalamic nuclei, in contrast to a spatially and spec-
trally distinct network in the α band connecting
brainstem with temporoparietal cortex.26
Global resting-state networks in neurodegeneration
A growing number of MEG studies have described
neurodegenerative alteration to functional connectiv-
ity during resting-state recordings, complementing
findings from fMRI. Resting-state networks describe
Figure 7 Comparison of resting-state networks identified from magnetoencephalography and fMRI data independently. (A) Default
mode network, (B) left lateral frontoparietal network, (C) right lateral frontoparietal network, (D) sensorimotor network. (Adapted
from Brookes et al14
).
HOW TO UNDERSTAND IT
Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768 5
6. the temporally coordinated, but often anatomically
disparate, spontaneous fluctuations in brain activity
that are present even at rest within distinct functional
brain networks.27
Although such networks are obvi-
ously engaged during relevant task activity, study of
resting-state networks is particularly appealing within
patient populations as impaired task performance is
no longer a possible confounding factor.
Alzheimer’s disease has been most frequently scruti-
nised using resting-state measures. A study of 18
patients (mean Mini-Mental State Examination Score
19.2) noted a loss of long-distance interhemispheric
connectivity (measured as synchronisation likelihood)
within the α and β bands. This correlated with cogni-
tive impairment and was not consequent to anticholi-
nesterase treatment.28
A repeat study focused on the
modular organisation of resting-state networks
(decomposed into functional subnetworks), and noted
Alzheimer’s disease to cause decrement of intermodu-
lar connectivity but also intramodular damage
restricted to certain cortical regions.29
Such graph-theory concepts could, in principle, be
employed to transfer descriptions of a ‘connectome’
(our unique neural fingerprint that defines us as indivi-
duals) across different modalities, including fMRI and
diffusion tensor imaging (DTI) studies.30
However,
results from these connectivity studies often conflict,
perhaps reflecting differing population samples, but also
implying a mismatch between functional and structural
connection strength,31
which may hint at underlying
pathological mechanisms, such as interneuronal dys-
function in amyotrophic lateral sclerosis.32
Oscillatory signatures in neurodegeneration
The suitability of MEG to capture neuronal activity
during relevant motor or cognitive tasks has encour-
aged parallel investigation of induced changes in oscil-
latory activity—perturbations of spontaneous brain
activity patterns are fundamental to all our experi-
ences, decisions and actions.1
A block-design study of
patients with Alzheimer’s disease or dementia with
Lewy bodies contrasted their cortical spectral power
during periods of either rest or repeated auditory
attention tasks. In both conditions, there were large
group differences from anterior sensors in a 3–7 Hz θ
band.33
An event-related experimental design was
used to study visual working memory tasks attempted
by Alzheimer’s disease and vascular dementia
patients.34
Those dementia subjects still able to com-
plete the task successfully demonstrated (against con-
trols) significantly delayed and stronger amplitude α
desynchronisation during the task epochs (albeit with
limited topographical localisation), in keeping with
the comparatively higher burden of cognitive process.
Task-based MEG recordings of 12 subjects with fron-
totemporal dementia were compared with controls,
while making categorical semantic judgements about
visually presented objects. There was an early
difference in temporoparietal cortex activity followed
by a later reduction in frontoparietal activity in each
task epoch, interpreted as corresponding to semantic
information processing and subsequent action selec-
tion.35
This result highlights the high temporal reso-
lution achievable in MEG recordings such that
component parts of a rapid cognitive task can be distin-
guished with confidence in time and anatomical space.
Even swallowing has proved to be an informative
motor task in the study of neurodegenerative disease
with MEG. An investigation of Parkinson’s disease sub-
jects with and without dysphagia found evidence for
compensatory adaptive cerebral changes to involve
wider cortical regions.36
The same researchers have
noted right hemispheric lateralisation of swallow-related
activity in amyotrophic lateral sclerosis37
and Kennedy’s
syndrome,38
perhaps reflecting plasticity in the face of
progressive neurodegeneration.
Biomarker potential
MEG has been used to predict whether subjects were
more likely to progress to clinically defined
Alzheimer’s disease on the basis of more widespread
power changes during a memory task, in a study of a
small number of subjects with minimal cognitive
impairment.39
A larger (117 Alzheimer’s disease sub-
jects) multicentre MEG study was subsequently per-
formed; 1 min of resting-state data was sufficient to
detect increased functional connectivity.40
Ten-month
interval assessment of 31 subjects detailed progressive
abnormalities, correlating with worsening neuropsy-
chometry. A longitudinal study of Parkinson’s disease
showed progressive slowing of oscillatory activity over
a 4-year follow-up period in 59 initially non-
demented Parkinson’s disease subjects.41
These
changes were particularly associated with mild cogni-
tive decline and, furthermore, MEG signals, above
and beyond neuropsychometry, predicted subsequent
conversion to Parkinson’s disease dementia, as borne
out at the 7-year follow-up time point.42
CONCLUSION
In combination with the increasingly high structural
resolution offered by MRI, MEG has unique potential
as part of a multimodal approach to brain disorders
that is sensitive to time as well as space. It seems clear
from presymptomatic studies across a range of neuro-
degenerative disorders, that the earliest events occur
many years, possibly decades, before the onset of
symptoms. Primary prevention of neurodegeneration
will require sensitivity to very subtle changes in brain
activity that seem likely to operate at the network
level.43
As well as studying the patterns of brain activ-
ity in the resting state, cognitive or motor MEG-based
tasks could reveal key pathological or compensatory
patterns of activity that might form the basis for early
intervention, including pharmacodynamic biomarkers
of therapeutic intervention.
HOW TO UNDERSTAND IT
6 Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768
7. Key points
▸ Magnetoencephalography (MEG) is non-invasive, safe
and comfortable.
▸ MEG offers unsurpassed temporal resolution; it can
probe neuronal oscillation activity that is fundamen-
tal to brain function in health and disease.
▸ Modern MEG systems include several hundred
distortion-free sensors surrounding the head to
provide high spatial precision over superficial cortical
areas.
▸ MEG analysis describes in vivo function of whole
brain networks in real time, and has the potential to
detect the very earliest changes in neurodegenerative
disorders and assess preventative therapies of the
future.
Acknowledgements We thank George Wallis, OHBA, for
providing figures 5 and 6.
Contributors MP drafted the manuscript. MWWedited the
manuscript. KN edited the manuscript. MRT conceived and
edited the manuscript, and is guarantor of the content.
Funding This work was support by the Wellcome Trust
(092753), the National Institute for Health Research (NIHR)
Oxford Biomedical Research Centre (BRC) based at Oxford
University Hospitals and by an MRC UK MEG Partnership
Grant, MR/K005464/1. MP receives funding from The
Guarantors of Brain and the Oxford BRC. MRT receives
funding from the Medical Research Council and Motor
Neurone Disease Association UK Lady Edith Wolfson
Fellowship (MR/K01014X/1).
Competing interests None.
Provenance and peer review Not commissioned; externally
peer reviewed. This paper was reviewed by Khalid Hamandi,
Cardiff, UK.
Open Access This is an Open Access article distributed in
accordance with the terms of the Creative Commons
Attribution (CC BY 3.0) license, which permits others to
distribute, remix, adapt and build upon this work, for
commercial use, provided the original work is properly cited.
See: http://creativecommons.org/licenses/by/3.0/
REFERENCES
1 Buzsaki G. Rhythms of the Brain. USA: OUP, 2011.
2 Klimesch W. Α-band oscillations, attention, and controlled
access to stored information. Trends Cogn Sci 2012;16:606–17.
3 Fries P. A mechanism for cognitive dynamics: neuronal
communication through neuronal coherence. Trends Cogn Sci
2005;9:474–80.
4 Engel AK, Singer W. Temporal binding and the neural
correlates of sensory awareness. Trends Cogn Sci 2001;5:16–25.
5 Fernando H, Lopes da Silva. MEG: an introduction to
methods. eds: Hansen, Kringelback & Salmelin. USA: OUP,
2010:1–23, figure 1.3 from p6.
6 Buzsáki G, Draguhn A. Neuronal oscillations in cortical
networks. Science 2004;304:1926–9.
7 Kominis IK, Kornack TW, Allred JC, et al. A subfemtotesla
multichannel atomic magnetometer. Nature 2003;422:596–9.
8 Gross J, Baillet S, Barnes GR, et al. Good practice for conducting
and reporting MEG research. Neuroimage 2013;65:349–63.
9 Friston K, Harrison L, Daunizeau J, et al. Multiple sparse
priors for the M/EEG inverse problem. Neuroimage
2008;39:1104–20.
10 Woolrich M, Hunt L, Groves A, et al. MEG beamforming
using Bayesian PCA for adaptive data covariance matrix
regularization. Neuroimage 2011;57:1466–79.
11 Salmelin R, Service E, Kiesilä P, et al. Impaired visual word
processing in dyslexia revealed with magnetoencephalography.
Ann Neurol 1996;40:157–62.
12 Hipp JF, Hawellek DJ, Corbetta M, et al. Large-scale cortical
correlation structure of spontaneous oscillatory activity. Nat
Neurosci 2012;15:884–90.
13 Stufflebeam SM. Clinical magnetoencephalography for
neurosurgery. Neurosurg Clin N Am 2011;22:153–67, vii–viii.
14 Brookes MJ, Woolrich M, Luckhoo H, et al. Investigating the
electrophysiological basis of resting state networks using
magnetoencephalography. Proc Natl Acad Sci USA
2011;108:16783–8.
15 Luckhoo H, Hale JRJRR, Stokes MGMG, et al. Inferring
task-related networks using independent component analysis in
magnetoencephalography. Neuroimage 2012;62:530–41.
16 Smith SM, Fox PT, Miller KL, et al. Correspondence of the
brain’s functional architecture during activation and rest. Proc
Natl Acad Sci USA 2009;106:13040–5.
17 Stam CJ. Use of magnetoencephalography (MEG) to study
functional brain networks in neurodegenerative disorders.
J Neurol Sci 2010;289:128–34.
18 Singh KD. Which ‘neural activity’ do you mean? fMRI, MEG,
oscillations and neurotransmitters. Neuroimage 2012;62:
1121–30.
19 Fernández A, Maestú F, Amo C, et al. Focal temporoparietal
slow activity in Alzheimer’s disease revealed by
magnetoencephalography. Biol Psychiatry 2002;52:764–70.
20 Osipova D, Ahveninen J, Jensen O, et al. Altered generation of
spontaneous oscillations in Alzheimer’s disease. Neuroimage
2005;27:835–41.
21 Maestu F, Arrazola J, Fernandez A, et al. Do cognitive patterns
of brain magnetic activity correlate with hippocampal atrophy
in Alzheimer’s disease? J Neurol Neurosurg Psychiatry
2003;74:208–12.
22 Pekkonen E, Ahveninen J, Virtanen J, et al. Parkinson’s disease
selectively impairs preattentive auditory processing: an MEG
study. Neuroreport 1998;9:2949–52.
23 Osipova D, Pekkonen E, Ahveninen J. Enhanced magnetic
auditory steady-state response in early Alzheimer’s disease. Clin
Neurophysiol 2006;117:1990–5.
24 Pekkonen E, Osipova D, Laaksovirta H. Magnetoencephalographic
evidence of abnormal auditory processing in amyotrophic lateral
sclerosis with bulbar signs. Clin Neurophysiol Off J Int Fed Clin
Neurophysiol 2004;115:309–15.
25 Stoffers D, Bosboom JLW, Deijen JB, et al. Slowing of
oscillatory brain activity is a stable characteristic of Parkinson’s
disease without dementia. Brain 2007;130:1847–60.
26 Litvak V, Jha A, Eusebio A, et al. Resting oscillatory
cortico-subthalamic connectivity in patients with Parkinson’s
disease. Brain 2011;134:359–74.
27 Beckmann CF, DeLuca M, Devlin JT, et al. Investigations into
resting-state connectivity using independent component analysis.
Philos Trans R Soc Lond B Biol Sci 2005;360:1001–13.
28 Stam CJ, Jones BF, Manshanden I, et al.
Magnetoencephalographic evaluation of resting-state functional
connectivity in Alzheimer’s disease. Neuroimage
2006;32:1335–44.
HOW TO UNDERSTAND IT
Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768 7
8. 29 De Haan W, van der Flier WM, Koene T, et al. Disrupted
modular brain dynamics reflect cognitive dysfunction in
Alzheimer’s disease. Neuroimage 2012;59:3085–93.
30 Tijms BM, Wink AM, de Haan W, et al. Alzheimer’s disease:
connecting findings from graph theoretical studies of brain
networks. Neurobiol Aging 2013;34:2023–36.
31 Honey CJ, Sporns O, Cammoun L, et al. Predicting human
resting-state functional connectivity from structural
connectivity. Proc Natl Acad Sci USA 2009;
106:2035–40.
32 Douaud G, Filippini N, Knight S, et al. Integration of
structural and functional magnetic resonance imaging in
amyotrophic lateral sclerosis. Brain 2011;134:3470–9.
33 Franciotti R, Iacono D, Della Penna S, et al. Cortical rhythms
reactivity in AD, LBD and normal subjects: a quantitative MEG
study. Neurobiol Aging 2006;27:1100–9.
34 Babiloni C, Cassetta E, Chiovenda P, et al. Alpha rhythms in
mild dements during visual delayed choice reaction time tasks:
a MEG study. Brain Res Bull 2005;65:457–70.
35 Hughes LE, Nestor PJ, Hodges JR, et al. Magnetoencephalography
of frontotemporal dementia: spatiotemporally localized changes
during semantic decisions. Brain 2011;134:2513–22.
36 Suntrup S, Teismann I, Bejer J, et al. Evidence for adaptive
cortical changes in swallowing in Parkinson’s disease. Brain
2013;136:726–38.
37 Teismann IK, Warnecke T, Suntrup S, et al. Cortical processing
of swallowing in ALS patients with progressive dysphagia—a
magnetoencephalographic study. PLoS ONE 2011;6:e19987.
38 Dziewas R, Teismann IK, Suntrup S, et al. Cortical compensation
associated with dysphagia caused by selective degeneration of
bulbar motor neurons. Hum Brain Mapp 2009;30:1352–60.
39 Maestú F, Yubero R, Moratti S, et al. Brain activity patterns in
stable and progressive mild cognitive impairment during
working memory as evidenced by magnetoencephalography.
J Clin Neurophysiol 2011;28:202–9.
40 Verdoorn TA, McCarten JR, Arciniegas DB, et al. Evaluation
and tracking of Alzheimer’s disease severity using resting-state
magnetoencephalography. J Alzheimers Dis 2011;26(Suppl 3):
239–55.
41 Olde Dubbelink KTE, Hillebrand A, Stoffers D, et al.
Disrupted brain network topology in Parkinson’s disease:
a longitudinal magnetoencephalography study. Brain 2014;
137(Pt 1):197–207.
42 Olde Dubbelink KTE, Hillebrand A, Twisk JWR, et al. Predicting
dementia in Parkinson disease by combining neurophysiologic
and cognitive markers. Neurology 2013;82:263–70.
43 Eisen A, Turner MR. Does variation in neurodegenerative
disease susceptibility and phenotype reflect cerebral differences
at the network level? Amyotroph Lateral Scler Frontotemporal
Degener 2013;14:1–7.
HOW TO UNDERSTAND IT
8 Proudfoot M, et al. Pract Neurol 2014;0:1–8. doi:10.1136/practneurol-2013-000768