Biology subjects

Ridding, M. C.

Publications and source records attributed to Ridding, M. C..

4 recordsLinked to original sources

bioRxiv2020

The role of alpha power in the suppression of anticipated distractors during verbal working memory

As working memory (WM) is limited in capacity, it is important to direct neural resources towards processing task-relevant information while ignoring distractors. Neural oscillations in the alpha frequency band (8-12 Hz) have been suggested to play a role in the inhibition of task-irrelevant information during WM, although results are mixed, possibly due to differences in the type of WM task employed. Here, we examined the role of alpha power in inhibition of anticipated distractors of varying strength using a modified Sternberg task where the encoding and retention periods were temporally separated. We recorded EEG while 20 young adults completed the task and found: 1) slower reaction times in strong distractor trials compared to weak distractor trials; 2) increased alpha power in posterior regions from baseline prior to presentation of a distractor regardless of condition; and 3) no differences in alpha power between strong and weak distractor conditions. Our results suggest that parieto-occipital alpha power is increased prior to a distractor. However we could not find evidence that alpha power is further modulated by distractor strength.

neuroscience↗

bioRxiv2018

Characterization of young and old adult brains: An EEG functional connectivity analysis

Brain connectivity studies have reported that functional networks change with older age. We aim to (1) investigate whether electroencephalography (EEG) data can be used to distinguish between individual functional networks of young and old adults; and (2) identify the functional connections that contribute to this classification. Two eyes-open resting-state EEG recording sessions with 64 electrodes for each of 22 younger adults (19-37 years) and 22 older adults (63-85 years) were conducted. For each session, imaginary coherence matrices in theta, alpha, beta and gamma bands were computed. A range of machine learning classification methods were utilized to distinguish younger and older adult brains. A support vector machine (SVM) classifier was 94% accurate in classifying the brains by age group. We report decreased functional connectivity with older age in theta, alpha and gamma bands, and increased connectivity with older age in beta band. Most connections involving frontal, temporal, and parietal electrodes, and approximately two-thirds of connections involving occipital electrodes, showed decreased connectivity with older age. Just over half of the connections involving central electrodes showed increased connectivity with older age. Functional connections showing decreased strength with older age had significantly longer electrode-to-electrode distance than those that increased with older age. Most of the connections used by the classifier to distinguish participants by age group belonged to the alpha band. Findings suggest a decrease in connectivity in key networks and frequency bands associated with attention and awareness, and an increase in connectivity of the sensorimotor functional networks with ageing during a resting state.

neuroscience↗

bioRxiv2018

Test-retest reliability of functional brain network characteristics using resting-state EEG and graph theory

Metrics of brain network organization can be derived from neuroimaging data using graph theory. We explored the test-retest reliability of graph metrics of functional networks derived from resting-state electroencephalogram (EEG) recordings. Data were collected within two designs: (1) within sessions (WS) design where EEG data were collected from 18 healthy participants in four trials within a few hours and (2) between sessions (BS) design where EEG data were collected from 19 healthy participants in three trials on three different days at least one week apart. Electrophysiological source activity was reconstructed and functional connectivity between pairs of sensors or brain regions was determined in different frequency bands. We generated undirected binary graphs and used intra-class correlation coefficient (ICC) to estimate reliability. We showed that reliabilities ranged from poor to good. Reliability at the sensor-level was significantly higher than source-level. The most reliable graph metric at the sensor-level was cost efficiency and at the source-level was global efficiency. At the sensor-level: WS reliability was significantly higher than BS reliability; high beta band in WS design had the highest reliability; in WS design reliability in gamma band was significantly lower than reliability in low and high beta bands. At the source-level: low beta band in BS design had the highest reliability; there was no significant main effect of frequency band on reliability; reliabilities of WS and BS designs were not significantly different. These results suggest that these graph metrics can provide reliable outcomes, depending on how the data were collected and analysed.

neuroscience↗

bioRxiv2017

The effect of stimulation interval on plasticity following repeated blocks of intermittent theta burst stimulation

IntroductionTheta burst stimulation (TBS) is a non-invasive brain stimulation paradigm capable of influencing cortical circuits in humans by inducing neural plasticity. Applying spaced blocks of TBS can affect both the direction and magnitude of plasticity, but the impact of interval duration on these interactions following intermittent TBS (iTBS) is unclear.\n\nObjectivesTo assess the effect of interval duration on plasticity magnitude/direction following spaced iTBS.\n\nMethods15 healthy participants received three different iTBS conditions on separate days: single iTBS; spaced iTBS with a 5 minute interval (iTBS-5); and spaced iTBS with a 15 minute interval (iTBS-15). Changes in cortical excitability and short-interval cortical inhibition (SICI) resulting from iTBS were assessed via motor-evoked potentials (MEPs) measured from the first dorsal interosseus muscle before and up to 60 mins following stimulation.\n\nResultsiTBS-15 increased MEP amplitude up to 60 mins post stimulation, whereas iTBS-5 decreased MEP amplitude. In contrast, MEP amplitude was not altered by single iTBS. Despite the significant effect of iTBS-15 on MEP amplitude at the group level, there was still considerable inter-individual variability, with only 53% of individuals meeting response criteria. Modulation of SICI did not differ between conditions.\n\nConclusionsThe interval duration between spaced iTBS plays an important role in determining the direction of plasticity on excitatory, but not inhibitory circuits in human motor cortex. While iTBS-15 can increase the magnitude of facilitation in some individuals compared to single iTBS, this approach still suffers from high inter-individual variability.

neuroscience↗