Electroencephalography (EEG)(Schomer & Lopez de Silva, 2011) is a noninvasive neuroimaging procedure which records electrical activity of the brain (Duffy et al., 1994). EEG (along with MEG) is a direct measure of neural activity (i.e., collections of neurons)  and operates in the millisecond time domain, which is the same time domain of the brain and central nervous system. Due to these properties, EEG is the most sensitive measure of neural dynamics (activities of neural networks).
Use[edit | edit source]
The last 70 years of neuroscience has established that most of brain's metabolism is used to create brain cell activity (summated synaptic potentials) operating on on the least-effort principle. This activity is mostly excitatory, some is inhibitory (slows things down) but it achieves a balance that optimizes the excitation and inhibition and produced electrical potentials, which we see at the scalp, in the form of the EEG. The EEG is a function of the electrical potentials in our brain, at the scalp. LORETA looks at the electrical potentials deeper into the brain. Only pyramidal neurons generate these potentials, and over 85% of our brains are made up of pyramidal neurons. All neurons generate all EEG frequencies, so the most important thing to remember is whether there is deregulation in a given region or network, with the frequency being secondary.
2 Billion dollars during 1990s (decade of the brain) resulted in huge proliferation of knowledge and understanding in a much for fundamental way how the brain is wired, how the neurons are synchronized and how they “talk” to each other. We are very privileged to be able to take advantage of it. It has matured to the point that we can now apply it. The ultimate goal of bringing together all imaging modalities is good clinical outcome. In order to achieve that, it requires putting together all the imaging modalities and understanding where we are and understanding where the EEG is with respect to the other imaging modalities (structural MRI, functional MRI, PET scans, SPECT scans, EEG, MEG) and at all levels of phylogeny (animals to humans). There is a common coordinate system so we can relate the EEG to networks inside the brain and nodes and connections between nodes within the brain that are related to symptoms.
The brain is organized in networks which operate on a millisecond time-scale. These networks are physical systems containing interdependent brain regions connected by nerves (bundles of nerve cells). Electrical neuroimaging of modules and hubs within the brain using structural MRI, DTI—this forms the infrastructure for the foundation for our understanding of the EEG. However, DTI, MRI structural imaging is the same whether you are alive or dead. Only the EEG, fMRI capture neuronal dynamics; however, the difference is that the fMRI has 10-20 second latency in order to measure anything whereas the EEG is in milliseconds. This near-instantaneous measurement aspect of EEG is crucial for examining brain dynamics, which, given the articles presented here appear to be very relevant for the study of ME. The time it takes for the brain to recruit a billion neurons across different network nodes varies from about 20ms to 80ms. Therefore, this means that network phase measures are completely INVISIBLE to the fMRI.Furthermore, the EEG spatial resolution, although not as high as fMRI, is quite accurate and sufficient for us to evaluate the dynamics of communication between large groups of neurons. What this means is that, if one is interested in brain dynamics and function, the EEG is the only modality that will capture it.
The brain is not like a computer, as we once thought. It depends on information that flows in regulated loops which continually change, not in fixed circuits like computers. The brain primary task is prediction, by matching what is previously learned with new information 'on the fly.' Our awareness is one step behind these predictions in that the brain has already represented our actions milliseconds before we perform them. Information flow is therefore a continual re-mapping that takes information from sensory systems and sends it to higher-order systems, which results in regulatory control which bring about adaption in homeostasis of feelings, actions, perceptions and consciousness. The EEG is therefore the only non-invasive and inexpensive measure of this continual temporal evolution of brain information in real time that is crucial for the understanding of cognitive and emotional functioning for healthy individuals as well as people with neurocognitive dysfunction.
Cortico-thalamic Integration[edit | edit source]
EEG patterns (rhythms) are primarily a fundamental property of brainstem-thalamo-cortical and corticothalamic dynamics regulated by many sub-thalamic brainstem systems including the ascending reticular activating system (ARAS), the locus coeruleus (LC) and the globus pallidus. It is these and other subcortical structures which regulate brain rhythms that produce the states of consciousness and cognition, producing cognitive abilities. More specifically, the networks which modulate arousal (vigilance) rhythms are some of the most important networks in the brain due to their function in the shift between arousal states ranging from the completely disconnected state to the fully alert, vigilant state [23-25]. The thalamus, part of the ascending reticular activating system (RAS) provides two important functions within this circuit; first, to mediate sleep or low arousal (triggering sleep and wakefulness) and to perform memory consolidation during sleep. Therefore, any failure of the ability of the ARAS to regulate the thalamus efficiently results in generalized reduction in information flow in extensive cortical regions causing reduced overall efficiency, slowed information processing speed, memory failures, attention problems and overall cognitive deficits.
Network, Central Executive Network, Default Mode Network, Intrinsic Connectivity Network, Salience Network, Small-world Network, Structural Connectivity, Functional Connectivity.
Notable Studies[edit | edit source]
- 2016, Electroencephalogram characteristics in patients with chronic fatigue syndrome (January 28) "The spontaneous brain electrical activities in CFS patients were significantly reduced. The abnormal changes in the cerebral functions were localized at the right frontal and left occipital regions in CFS patients"
- 2016, -Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study](February 11). "We found support for all three core networks of the Menon triple network model-the central executive network (CEN), salience network (SN), and the default mode network (DMN)- indicating hypo-connectivity in the Delta, Alpha, and Alpha-2 frequency bands in patients with ME compared to controls. In addition to the current source density resting state dysfunction in the occipital, parietal, posterior temporal and posterior cingulate, the disrupted connectivity of the CEN, SN, and DMN appears to be involved in cognitive impairment for patients with ME. This research suggests that disruptions in these regions and networks could be a core neurobiological feature of the disorder, representing underlying neural dysfunction."
- 2017, Small-world network analysis of cortical connectivity in Chronic Fatigue Syndrome using quantitative EEG.(Full Text)
- 2018 - Cortical hypoactivation during resting EEG suggests central nervous system pathology in patients with chronic fatigue syndrome(Abstract)
See Also[edit | edit source]
References[edit | edit source]
- Lopes da Silva, Fernando (Dec 4, 2013). "EEG and MEG: Relevance to Neuroscience". Neuron. 80 (5): 1112–1128. doi:10.1016/j.neuron.2013.10.017.
- Zinn, Mark Alan; Zinn, Marcie L.; Jason, Leonard A. (Dec 7, 2017). "Small-World Network Analysis of Cortical Connectivity in Chronic Fatigue Syndrome Using Quantitative EEG". NeuroRegulation. 4 (3-4): 125. doi:10.15540/nr.4.3-4.125. ISSN 2373-0587.
- Zinn, M.A.; Zinn, M.L.; Valencia, I.; Jason, L.A.; Montoya, J.G. (Jul 2018). "Cortical hypoactivation during resting EEG suggests central nervous system pathology in patients with chronic fatigue syndrome". Biological Psychology. 136: 87–99. doi:10.1016/j.biopsycho.2018.05.016. PMID 29802861.