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A brief overview of Brain Oscillations, Synchrony and Plasticity by author Dr. Jos J. Eggermont
One may take two approaches to the study of neurological and psychiatric disorders. These are the molecular approach and the systems approach. The first approach is reductionist in kind, the second synthetic. In Brain Oscilliations, Synchrony and Plasticity, I emphasize the latter approach—based on electrophysiology and neuroimaging—partially because I am more familiar with it, but mostly because it is widely applicable to humans. Some of the imaging findings are fortunately highly correlated with molecular findings, especially in Schizophrenia and Alzheimer’s disease, so I included these molecular data. In this book, I discuss the role of brain oscillations, especially with respect to the auditory system and how those oscillations are measured, change over the lifespan, and falter leading to a variety of psychiatric and neurological disorders
Non-invasive methods, dominantly based on resting state electro- and magneto-encephalography (EEG/MEG) allowing the registration of brain rhythms, and structural and functional MRI (fMRI) are especially suited to detect changes in connectivity between brain networks. They have great potential for diagnosis and assessing the potency of drug treatments, effects of neuromodulation and behavioral cognitive therapy. Connections between parts of the brain can be shown as existing nerve tracts using diffusion tensor MRI with tractography. These are called structural connections and serve the basic action potential-based transmission between neurons and networks. Connections can also be estimated from correlated changes in the various networks, such as the very slow BOLD fluctuations. These correlations reflect functional connectivity, which is non-directional and may be more far ranging as structural connectivity by way of common inputs. A structural MRI technique, voxel-based morphology, allows the measurement of gray matter density and volume, and has been applied in relation to disorders such as tinnitus and hearing loss, and may diagnose atrophy of specific brain regions.
At the scalp-level, correlations in voltage or current time series between scalp electrodes or magnetic sensors can be used to infer functional networks at the sensor level. A better way is to first estimate intracranial sources (sometimes called equivalent dipoles) from the scalp activity and then estimate correlations between the local source voltage- or current-time series. Given the large number of frequency bands detectable in the EEG or MEG, correlations at the sensor or source level are often conducted after filtering the time series into applicable frequency bands, from delta to gamma. This may result in different connections between identified networks, the latter often based on fMRI. Especially, but not exclusively, the gamma band activity correlates strongly with the networks identified on basis of correlations between the very slow BOLD fluctuations.
Oscillations in the brain are organized hierarchically, with frequencies from less than 1 Hz, to more than 100 Hz. These are named according to common frequency bands 1-4 Hz (delta waves), 4-8 Hz (theta waves), 8-12 Hz (alpha waves), 13-30 Hz (beta waves) and >40 Hz (gamma waves). The ~0.1 Hz very slow waves features in the EEG but also as the dominant fluctuation in the blood oxygen level dependent (BOLD) response of the functional MRI (fMRI). The higher frequency rhythms can only be seen in the EEG and MEG. The alpha rhythm, which is the dominant oscillatory activity in awake adults, probably originates from an interaction between local negative feedback circuits in the thalamus and the cortex. Faster EEG rhythms such as beta and gamma are produced by feedback circuits between cortical pyramidal neurons and local inhibitory inter neurons. Some types of theta may originate in medial temporal circuits and are projected to other parts of the cortex via the hippocampus. Physiological EEG rhythms thus arise in different neural circuits, and probably have different functions. The alpha rhythm may play a role in attention and semantic memory, but may also have a modulatory effect on other rhythms. Beta rhythms are often related to motor processes, and gamma rhythms to perception and consciousness. The theta rhythm has been associated with working memory.
A basic question is how the low frequency—including the very slow—waves become synchronized or transmitted over large distances? There are two possibilities: via the nerve tracts as trains of rhythmic action potentials and/or as volume conducted activity. Notably, the very slow fluctuations in the fMRI, basically reflecting BOLD, fluctuations are correlated or anti-correlated across large brain areas. Their electrophysiological equivalents are very slow changes in membrane potentials, caused by synchronous synaptic potentials, and measurable as local field potentials (LFPs) and very slow waves in the EEG. These synchronized local rhythms are either localized in the brain and in that case with frequencies in the beta and gamma range, whereas they are more long ranging for the lower frequencies, particular the delta and theta frequency range and to a lesser extend the alpha range. The low frequencies are capable of organizing higher frequency oscillations whose amplitude or phase is locked to the phase of the lower frequency ones. In this way higher frequency ones (e.g., gamma) may be synchronized between far away regions in the brain.
The brain is a complex system, built up from modules (e.g., auditory cortex) into local networks (i.e., the auditory system network) that connect with among others salience-, attention- and default mode- networks. Less than two decades ago, this network approach to the human brain was pioneered using fMRI and based on long-distance correlation of the very low frequency fluctuations in the BOLD response. Networks are made from structural connections, and from synchrony of brain oscillations, both local and global. The so formed functional and structural connections within and between brain regions are commonly studied by graph-theoretical methods leading to concepts as small-world, hubs and neural modules.
Do the various neurological disorders have substrates in the neural networks and their connectivity? As we have seen, distributed neural systems may communicate through synchronization of their oscillatory activity. Synchronization here refers to the existence of a consistent relationship between activity patterns of two or more spatially separated neuronal groups. It often implies that there is a consistent relation between the phases of the oscillatory activity of two brain regions. Synchronization in different frequency bands has been associated with various cognitive functions and the integration of information in the healthy brain. In neurological disorders this process of functional integration can become disrupted and give rise to various symptoms of cognitive dysfunction. The fact that structural hubs, particularly in the default mode network, play such a striking role in brain network controllability may further help to explain the growing body of evidence indicating that diseases preferentially target hub areas.
In Brain Oscillations, Synchrony and Plasticity, I present an overview of some neuromodulation methods and results; namely the effects induced by transcranial magnetic stimulation (TMS), transcranial alternating and direct current stimulation (tACS and tDCS). In addition, I discuss recently developed neuromodulation procedures based on focused low intensity ultrasound. TMS may induce dynamic relationships between regions of intrinsic brain networks. Theta-TMS induces activity in the dorsal auditory stream, causally related to memory manipulation. Paired associative TMS can induce both Hebbian and anti-Hebbian STDP in human long-range connections. tDCS does modulate synaptic strength within motor cortex, as visualized in the MEP but absent in the BOLD. tDCS effects in auditory cortex were small. However, oscillating tDCS modulated auditory detection thresholds in sinusoidal manner. tRNS works by inducing stochastic resonance and enhances threshold detection in phase-dependent fashion. tACS at 4 and 10 Hz also resulted in periodic modulation of auditory detection thresholds, as well as enhancement in auditory temporal processing. Transcranial focal ultrasound stimulation (tFUS) produces a significant attenuation in the power of short-latency evoked gamma-band (30–55 Hz) activity occurring within 70 ms of median nerve stimulation. tFUS alters the phase distribution of intrinsic brain activity for beta frequencies, but not gamma.
The way brain networks are formed and changed across the lifespan is reflected in a rich-club organization that is evident across the lifespan, whereas hub integration decreased linearly with age, especially accompanied by the loss of frontal hubs and their connections. The very preterm brain exhibited stronger rich-club architecture than the adult brain, despite possessing a relative paucity of white-matter resources. Both resting-state and task-related gamma oscillations emerge during early childhood, and precise temporal coordination through neural synchrony continues to mature until early adulthood. The default-mode network (DMN) structure in children deviates significantly from that in the adult. Over age, however, the default network becomes significantly more integrated. Connection strength within functional modules do not change with age, and the modules resemble hub networks previously described for MRI. Late adolescence is characterized by selective, yet significant remodeling of hub–hub connectivity, with the topological organization of hubs shifting emphasis from subcortical hubs in favor of an increasingly prominent role for frontal hub regions.
Disorders with auditory components
An important aspect for understanding pathology is that network hubs appear to be energy demanding, are the most vulnerable part of the networks, and may become damaged in hearing loss, neurological and psychiatric disorders. With respect to sensorineural hearing loss (SNHL), animal research has shown that delta-theta activity in auditory cortex is dramatically different from activity in an adjacent non-auditory responsive region. Unilateral hearing loss, sudden as well as long-term, shows changes in the limbic and paralimbic systems, and in the auditory network brain areas but these are critically dependent on the side of hearing loss. Right, but not left, unilateral hearing loss (UHL) can lead to a downward cross-modal plasticity. Compared with normal hearing controls, patients with long-term bilateral hearing loss, as in UHL, presented weaker brain region activations in primary auditory cortex (A1) and the language network, accompanied by enhanced neural activity in the DMN. Inefficient modulation of the salience network in SNHL might contribute to central effects and associated cognition and emotion deficits. No significant changes in gray matter density in A1 for pre- and post-lingual deafness are found. However, unlike post-lingual, pre-lingual deafness shows increased bilateral temporal connectivity of the A1 compared to the hearing adults. Finishing, I describe the communalities in the vulnerability of hubs connecting networks in tinnitus, dyslexia, autism, Schizophrenia and Alzheimer’s disease, all of which show in addition disorders in auditory perception.
Tinnitus often co-occurs with hearing loss. Structural brain changes, including those outside the auditory areas, have also been attributed to hearing loss. No strong relationship exists between whole scalp EEG band power and psychoacoustic or psychosocial variables related to tinnitus. Dominant factors in changing cortical networks in tinnitus patients are foremost the degree and type of hearing loss, and comorbidities such as distress and mood. So far, no definite changes have been attributed to tinnitus proper, albeit changes in connectivity between the dorsal attention network and the parahippocampal area appear to be a potential candidate.
I discuss two developmental disorders, dyslexia and autism. In dyslexia, some white matter tracts are affected leading to deficient phonemic processing and atypical rapid-rate acoustic processing. Children with dyslexia showed significantly less lateralization of auditory cortical functioning, and a different pattern of development of auditory lateralization with age compared to children with normal reading ability. Phonological representations also develop differently in dyslexia; for example, impaired speech rhythm detection might be compensated for by extra sensitivity to phonetic cues. This atypical trajectory would preserve spoken language processing while impairing written language processing.
In Autism Spectrum Disorder, enhanced connection strengths are found between prefrontal cortex and default mode network, and between cerebellum and auditory and visual areas. Decreased connectivity is more prevalent and found between medial temporal gyrus and prefrontal sulcus, precuneus and posterior cingulate cortex; between default mode and executive control network; between posterior cingulate cortex and default mode network, and between executive control network and posterior cingulate cortex.
The last chapter compares two neurological disorders with auditory involvement. Schizophrenia patients (SZ) display deficits in both basic non-verbal auditory processing pitch, loudness, amplitude modulation, and duration, Abnormal rich-club organization plays a central role in the etiology of schizophrenia. Some of the hub regions, especially the thalamus and precuneus, show impaired connections, and are thus vulnerable to damage in SZ. Robust reductions are found in structural integrity of the fronto-parietal control and salience networks, but not default mode, dorsal attention, motor and sensory networks. In SZ with audio verbal hallucinations, auditory cortex becomes hyperactive during silence. This is consistent with aberrant gamma rhythms in schizophrenia.
Alzheimer’s disease (AD) selectively targeted highly connected hub regions of brain networks, involving the medial and lateral prefrontal and parietal cortices, insula, and thalamus. The sites of amyloid-beta (Aβ) deposition in patients with AD correlate with the location of major hubs. This impairment is most severe in the long-range connections. Moreover, AD also disrupts functional connections within the default mode, salience and executive control networks, and connections between the salience and executive control networks.
Summarizing, brain rhythms with oscillation frequencies from ~0.1 Hz to > 100 Hz may be recorded from the scalp, the lowest are also found in fluctuations of the BOLD signal of the fMRI. Low frequency (1-15 Hz) rhythms underlie long distance functional connections, whereas higher frequency oscillations reflect local connectivity. Because the higher frequency rhythms are nested with the lower rhythms, they may also be synchronized between distant brain regions. Many neurological disorders are characterized by dys-synchrony within and between hubs and brain modules.
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About the author:
Dr. Jos J. Eggermont is an Emeritus Professor in the Departments of Physiology and Pharmacology, and Psychology at the University of Calgary in Alberta, Canada. Dr. Eggermont is one of the most renowned scientists in the field of the auditory system and his work has contributed substantially to the current knowledge about hearing loss. His research comprises most aspects of audition with an emphasis on the electrophysiology of the auditory system in experimental animals. He has published over 200 scientific articles, authored/edited 8 books, and contributed to over 90 book chapters all focusing on the auditory system.
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