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Current and Emerging Clinical Applications of the auditory Steady-State Response
Published in Stavros Hatzopoulos, Andrea Ciorba, Mark Krumm, Advances in Audiology and Hearing Science, 2020
Another practical application of ASSR is assessment of age-related deficits in speech perception in noise. This common patient complaint involves difficulty in following conversations, especially in the presence of background noise or while multiple speakers are talking (Goossens et al., 2016). Speech perception in noise problems may be due to peripheral and/or central auditory dysfunction, as well as cognitive impairments. ASSR may permit objective measurement of neural oscillations in the CNS and synchronization of phase patterns related to temporal features of sound speech. Specifically, the size of the ASSR reveals the degree of synchronization of neural oscillation that coincides with characteristic frequency of acoustic stimulation. Difficulties in speech perception with aging can be associated with disruption of synchronized neural activity. Age-related reduction in neural synchrony occurs at the level of brainstem and may be associated reduced levels of the inhibitory neurotransmitter GABA (Mamo et al., 2016; Anderson et al., 2012; Bidelman et al., 2014; Caspary et al., 2008).
Electrical Brain Stimulation to Treat Neurological Disorders
Published in Bahman Zohuri, Patrick J. McDaniel, Electrical Brain Stimulation for the Treatment of Neurological Disorders, 2019
Bahman Zohuri, Patrick J. McDaniel
Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity of the brain. It is typically noninvasive, with the electrodes placed along the scalp, although invasive electrodes are sometimes used such as in electrocorticography. EEG measures voltage fluctuations resulting from ionic current within the neurons of the brain. In clinical contexts, EEG refers to the recording of the brain’s spontaneous electrical activity over a period of time, as recorded from multiple electrodes placed on the scalp. Diagnostic applications generally focus either on event-related potentials or on the spectral content of EEG. The former investigates potential fluctuations time locked to an event like stimulus onset or button press. The latter analyses the type of neural oscillations (popularly called “brain waves”) that can be observed in EEG signals in the frequency domain.
Tics and Tourette’s syndrome
Published in Quentin Spender, Judith Barnsley, Alison Davies, Jenny Murphy, Primary Child and Adolescent Mental Health, 2019
Quentin Spender, Judith Barnsley, Alison Davies, Jenny Murphy
Tics used to be thought of as a manifestation of anxiety. It is true that anxiety or tension may worsen tics, as may excitement or illness, but sometimes the need to maintain focus can instead serve to suppress them. There is often a family history of tics, and there seems to be a strong biological basis. A recent theory is that the symptoms of the Tourette’s disorder are a consequence of aberrant neural oscillations.3 By definition, tics are not due to some other neurological disorder such as encephalitis.
Alpha synchronisation of acoustic responses in active listening is indicative of native language listening experience
Published in International Journal of Audiology, 2022
Alyssa Dyball, Nan Xu Rattanasone, Ronny Ibrahim, Mridula Sharma
One way to analyse induced activities is by using Time-frequency analyses (TFA). TFA works by analysing the electrophysiological data into its component frequencies such as alpha, theta, beta and gamma components across time, to isolate time points at which the neuronal oscillatory activity is strongest (Klimesch et al. 2000). Current understanding of neural oscillations suggests that neural activity within specific wavelengths is reflective of different cognitive processes. Alpha for example is most closely linked to directed attention (Klimesch et al. 1990). The induced activity can also be described as being either relatively increased (event-related synchronised) or decreased (event-related desynchronised) (Oostenveld et al. 2011). For example, increased synchronisation in the alpha-band is thought to reflect increased inhibition while desynchronisation in the alpha-band is reportedly reflective of focussed attention (Klimesch et al., 2012). Thus, TFA can assist in providing information on how the brain orchestrates the processing of linguistically relevant acoustic information.
Impact of β-range-induced oscillatory activity on human input–output relationship of the corticospinal pathway
Published in Neurological Research, 2021
Alessandro Rossi, Matteo Feurra, Simone Rossi, Emiliano Santarnecchi, Federica Ginanneschi
Spontaneously occurring oscillatory electrical activity in the central nervous system reflects rhythmic changes in membrane potential, likely affecting the neuronal firing probability [1]. Transcranial alternating current stimulation (tACS) has been shown to interact and entrain spontaneous oscillations in a frequency-specific manner by subthreshold modulation of membrane potentials, possibly affecting the likelihood of neuronal firing [2,3]. Beta-band oscillations are the dominant oscillatory activity in the primary motor cortex (M1) at rest [4,5]. It has been suggested that the β-rhythm is not simply a background process that is suppressed during movement [6], but rather that it plays an active and important role in motor processing [7]. Neural oscillation-dependent modulation of excitability can be studied convincingly when tACS is combined with neurostimulation techniques such as transcranial magnetic stimulation (TMS), as this makes it possible to prove causality [8].
Current perspectives on galvanic vestibular stimulation in the treatment of Parkinson’s disease
Published in Expert Review of Neurotherapeutics, 2021
Soojin Lee, Aiping Liu, Martin J. McKeown
Concurrent GVS and neuroimaging in PD could further advance the understanding of potential neural mechanisms, as well as assisting in developing advanced stimulation protocols, such as those for personalized stimulation. A technical challenge of concurrent EEG and MEG is the stimulation-induced artifacts in the recordings, which can be several orders of magnitude larger in amplitude than the actual brain signals. Although this can be easily resolved by applying digital filters if the stimulation frequency is out of the range of the neural oscillations of interest, it is common that the stimulation frequencies lie within the range of human brain oscillations (<50 Hz). While several signal processing methods such as adaptive filtering and joint blind source separation approaches have been proposed to tackle the challenge [121], this is still an area of active exploration which can aid in a better understanding of the stimulation effects.