ORCID Profile
0000-0001-9163-3150
Current Organisations
Memorial Sloan Kettering Cancer Center
,
University of South Australia
,
The University of Adelaide Adelaide Medical School
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Frontiers Media SA
Date: 18-05-2015
Publisher: Elsevier BV
Date: 04-2021
Publisher: Cold Spring Harbor Laboratory
Date: 17-07-2020
DOI: 10.1101/2020.07.16.207738
Abstract: 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.
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.22489428.V1
Abstract: Supplementary Data from Rb Tumor Suppressor in Small Cell Lung Cancer: Combined Genomic and IHC Analysis with a Description of a Distinct Rb-Proficient Subset
Publisher: SAGE Publications
Date: 12-02-2021
Abstract: In preclinical models, behavioral training early after stroke produces larger gains compared with delayed training. The effects are thought to be mediated by increased and widespread reorganization of synaptic connections in the brain. It is viewed as a period of spontaneous biological recovery during which synaptic plasticity is increased. To look for evidence of a similar change in synaptic plasticity in the human brain in the weeks and months after ischemic stroke. We used continuous theta burst stimulation (cTBS) to activate synapses repeatedly in the motor cortex. This initiates early stages of synaptic plasticity that temporarily reduces cortical excitability and motor-evoked potential litude. Thus, the greater the effect of cTBS on the motor-evoked potential, the greater the inferred level of synaptic plasticity. Data were collected from separate cohorts (Australia and UK). In each cohort, serial measurements were made in the weeks to months following stroke. Data were obtained for the ipsilesional motor cortex in 31 stroke survivors (Australia, 66.6 ± 17.8 years) over 12 months and the contralesional motor cortex in 29 stroke survivors (UK, 68.2 ± 9.8 years) over 6 months. Depression of cortical excitability by cTBS was most prominent shortly after stroke in the contralesional hemisphere and diminished over subsequent sessions ( P = .030). cTBS response did not differ across the 12-month follow-up period in the ipsilesional hemisphere ( P = .903). Our results provide the first neurophysiological evidence consistent with a period of enhanced synaptic plasticity in the human brain after stroke. Behavioral training given during this period may be especially effective in supporting poststroke recovery.
Publisher: Springer Science and Business Media LLC
Date: 27-05-2021
DOI: 10.1007/S00429-021-02299-4
Abstract: A patterned repetitive transcranial magnetic stimulation protocol, known as continuous theta burst stimulation (cTBS), can suppress corticospinal excitability via mechanisms that appear similar to long-term depression synaptic plasticity. Despite much potential, this technique is currently limited by substantial response variability. The purpose of this study was to investigate whether baseline resting state functional connectivity is a determinant of response to cTBS. Eighteen healthy young adults participated in up to three experimental sessions. Single-pulse transcranial magnetic stimulation was used to quantify change in corticospinal excitability following cTBS. Three minutes of resting electroencephalographic activity was recorded, and functional connectivity was estimated using the debiased weighted phase lag index across different frequency bands. Partial least squares regression identified models of connectivity between a seed region (C3) and the whole scalp that maximally accounted for variance in cTBS responses. There was no group-level effect of a single cTBS train or spaced cTBS trains on corticospinal excitability (p = 0.092). A low beta frequency band model of connectivity accounted for the largest proportion of variance in spaced cTBS response (R
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.22489425
Abstract: Supplementary Data from Rb Tumor Suppressor in Small Cell Lung Cancer: Combined Genomic and IHC Analysis with a Description of a Distinct Rb-Proficient Subset
Publisher: Elsevier BV
Date: 09-2020
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.22489419
Abstract: Supplementary Figure from Rb Tumor Suppressor in Small Cell Lung Cancer: Combined Genomic and IHC Analysis with a Description of a Distinct Rb-Proficient Subset
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.22489425.V1
Abstract: Supplementary Data from Rb Tumor Suppressor in Small Cell Lung Cancer: Combined Genomic and IHC Analysis with a Description of a Distinct Rb-Proficient Subset
Publisher: SAGE Publications
Date: 21-05-2020
Abstract: Background. Resting state functional connectivity (RSFC) is a developmental priority for stroke recovery. Objective. To determine whether (1) RSFC differs between stroke survivors based on integrity of descending motor pathways (2) RSFC is associated with upper-limb behavior in chronic stroke and (3) the relationship between interhemispheric RSFC and upper-limb behavior differs based on descending motor pathway integrity. Methods. A total of 36 people with stroke (aged 64.4 ± 11.1 years, time since stroke 4.0 ± 2.8 years) and 25 healthy adults (aged 67.3 ± 6.7 years) participated in this study. RSFC was estimated from electroencephalography (EEG) recordings. Integrity of descending motor pathways was ascertained using transcranial magnetic stimulation to determine motor-evoked potential (MEP) status and magnetic resonance imaging to determine lesion overlap and fractional anisotropy of the corticospinal tract (CST). For stroke participants, upper-limb motor behavior was assessed using the Fugl-Meyer test, Action Research Arm Test and grip strength. Results. β-Frequency interhemispheric sensorimotor RSFC was greater for MEP+ stroke participants compared with MEP− ( P = .020). There was a significant positive correlation between β RSFC and upper-limb behavior ( P = .004) that appeared to be primarily driven by the MEP+ group. A hierarchical regression identified that the addition of β RSFC to measures of CST integrity explained greater variance in upper-limb behavior ( R 2 change = 0.13 P = .01). Conclusions. This study provides insight to understand the role of EEG-based measures of interhemispheric network activity in chronic stroke. Resting state interhemispheric connectivity was positively associated with upper-limb behavior for stroke survivors where residual integrity of descending motor pathways was maintained.
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.22489419.V1
Abstract: Supplementary Figure from Rb Tumor Suppressor in Small Cell Lung Cancer: Combined Genomic and IHC Analysis with a Description of a Distinct Rb-Proficient Subset
Publisher: Wiley
Date: 18-01-2017
DOI: 10.1111/EJN.13508
Abstract: Responses to non-invasive brain stimulation are highly variable between subjects. Resting state functional connectivity was investigated as a marker of plasticity induced by anodal transcranial direct current stimulation (tDCS). Twenty-six healthy adults (15 male, 26.4 ± 6.5 years) were tested. Experiment 1 investigated whether functional connectivity could predict modulation of corticospinal excitability following anodal tDCS. Experiment 2 determined test-retest reliability of connectivity measures. Three minutes of electroencephalography was recorded and connectivity was quantified with the debiased weighted phase lag index. Anodal (1 mA, 20 min) or sham tDCS was applied to the left primary motor cortex (M1), with a change in motor evoked potential litude recorded from the right first dorsal interosseous used as a marker of tDCS response. Connectivity in the high beta frequency (20-30 Hz) between an electrode approximating the left M1 (C3) and electrodes overlying the left parietal cortex was a strong predictor of tDCS response (cross-validated R
Publisher: Wiley
Date: 03-11-2020
DOI: 10.1111/PSYP.13719
Publisher: Cold Spring Harbor Laboratory
Date: 30-06-2023
DOI: 10.1101/2023.06.28.546988
Abstract: As visual working memory (WM) is limited in capacity, it is important to direct neural resources towards task-relevant information and away from task-irrelevant information. Neural oscillations in the alpha frequency band (8-12 Hz) have been suggested to play a role in the inhibition of distracting information during WM retention in younger adults, but it is unclear if alpha power modulation also supports distractor inhibition in older adults. Here, we recorded electroencephalography (EEG) while 24 younger (aged 18-35) and 24 older (aged 60-86) adults completed a modified delay match-to-s le task in which distractors of varying strength appeared during the retention period. We found: (1) strong distractors impaired WM performance compared with weak and no distractors in both age groups, but there were no age-differences in WM performance (2) while younger adults demonstrated significant increases in alpha power prior to the onset of the distractor in all conditions, decreases in alpha power were seen in all distractor conditions in older adults (3) there was no difference in alpha power between the strong and no distractor conditions and (4) alpha power in anticipation of the distractor was only associated with task performance in younger adults. Our results suggest that younger adults, but not older adults, modulate alpha power in anticipation of distractors during the visual WM retention period.
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.C.6532947.V1
Abstract: AbstractPurpose: i RB1 /i mutations and loss of retinoblastoma (Rb) expression represent consistent but not entirely invariable hallmarks of small cell lung cancer (SCLC). The prevalence and characteristics of SCLC retaining wild-type Rb are not well-established. Furthermore, the performance of targeted next-generation sequencing (NGS) versus immunohistochemistry for Rb assessment is not well-defined. Experimental Design: A total of 208 clinical SCLC s les were analyzed by comprehensive targeted NGS, covering all exons of i RB1 /i , and Rb IHC. On the basis of established coordination of Rb 16/cyclinD1 expression, p16-high/cyclinD1-low profile was used as a marker of constitutive Rb deficiency. Results: Fourteen of 208 (6%) SCLC expressed wild-type Rb, accompanied by a unique p16-low/cyclinD1-high profile supporting Rb proficiency. Rb-proficient SCLC was associated with neuroendocrine-low phenotype, combined SCLC with non-SCLC (NSCLC) histology and aggressive behavior. These tumors exclusively harbored i CCND1 /i lification (29%), and were markedly enriched in i CDKN2A /i mutations (50%) and NSCLC-type alterations ( i KEAP1 /i , i STK11, FGFR1 /i ). The remaining 194 of 208 SCLC were Rb-deficient (p16-high/cyclinD1-low), including 184 cases with Rb loss (of which 29% lacked detectable i RB1 /i alterations by clinical NGS pipeline), and 10 cases with mutated but expressed Rb. Conclusions: This is the largest study to date to concurrently analyze Rb by NGS and IHC in SCLC, identifying a 6% rate of Rb proficiency. Pathologic-genomic data implicate NSCLC-related progenitors as a putative source of Rb-proficient SCLC. Consistent upstream Rb inactivation via i CDKN2A /i 16 sup ↓ /sup and i CCND1 /i /cyclinD1 sup ↑ /sup suggests the potential utility of CDK4/6 inhibitors in this aggressive SCLC subset. The study also clarifies technical aspects of Rb status determination in clinical practice, highlighting the limitations of exon-only sequencing for i RB1 /i interrogation. i a href="lincancerres/article/doi/10.1158/1078-0432.CCR-22-2187" target="_blank" See related commentary by Mahadevan and Sholl, p. 4603 /a /i /
Publisher: Cold Spring Harbor Laboratory
Date: 20-11-2019
DOI: 10.1101/848127
Abstract: Working memory (WM) is vulnerable to age-related decline, particularly under high loads. Visual alpha oscillations contribute to WM performance in younger adults, and although alpha decreases in power and frequency with age, it is unclear if alpha activity supports WM in older adults. We recorded electroencephalography (EEG) while 24 younger (aged 18-35 years) and 30 older (aged 50-86) adults performed a modified Sternberg task with varying load conditions. Older adults demonstrated slower reaction times at all loads, but there were no significant age differences in accuracy. Regardless of age, alpha power decreased, and alpha frequency increased with load during encoding, and the magnitude of alpha suppression during retention was larger at higher loads. While alpha power during retention was lower than fixation in older, but not younger adults, the relative change from fixation was not significantly different between age groups. In idual differences in alpha power did not predict performance for either age groups or at any WM loads. Future research should elaborate the functional significance of alpha power and frequency changes that accompany WM performance in cognitive ageing.
Publisher: Cold Spring Harbor Laboratory
Date: 09-2021
DOI: 10.1101/2021.08.31.458328
Abstract: Previous research using electroencephalography (EEG) and magnetoencephalography (MEG) has shown that neural oscillatory activity within the alpha band (8-12 Hz) becomes slower and lower in litude with advanced age. However, most studies have focused on quantifying age-related differences in periodic oscillatory activity with little consideration of the influence of aperiodic activity on these measures. The aim of this study was to investigate age differences in aperiodic activity inherent in the resting EEG signal. We assessed aperiodic activity in 85 healthy younger adults (mean age: 22.2 years, SD: 3.9, age range: 18–35, 37 male) and 92 healthy older adults (mean age: 66.1 years, SD: 8.2, age range 50–86, 53 male) by fitting the 1/f-like background activity evident in EEG power spectra using the fitting oscillations & one over f (FOOOF) toolbox. Across the scalp, the aperiodic exponent and offset were smaller in older compared to younger participants, reflecting a flatter 1/f-like slope and a downward broadband shift in the power spectra with age. Before correcting for aperiodic activity, older adults showed slower peak alpha frequency and reduced peak alpha power relative to younger adults. After correcting for aperiodic activity, peak alpha frequency remained slower in older adults however, peak alpha power no longer differed statistically between age groups. The large s le size utilized in this study, as well as the depth of analysis, provides further evidence that the aperiodic component of the resting EEG signal is altered with aging and should be considered when investigating neural oscillatory activity.
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.22489428
Abstract: Supplementary Data from Rb Tumor Suppressor in Small Cell Lung Cancer: Combined Genomic and IHC Analysis with a Description of a Distinct Rb-Proficient Subset
Publisher: Elsevier BV
Date: 12-2019
DOI: 10.1016/J.NEUROSCIENCE.2019.08.038
Abstract: 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 in idual 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 delta, 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 93% accurate in classifying the brains by age group. We report decreased functional connectivity with older age in delta, theta, alpha and gamma bands, and increased connectivity with older age in beta band. Most connections involving frontal, temporal, and parietal electrodes, and more than half of connections involving occipital electrodes, showed decreased connectivity with older age. Slightly less than half of the connections involving central electrodes showed increased connectivity with older age. Functional connections showing decreased strength with older age were not significantly different in 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 aging during a resting state.
Publisher: American Association for Cancer Research (AACR)
Date: 06-07-2022
DOI: 10.1158/1078-0432.CCR-22-1115
Abstract: RB1 mutations and loss of retinoblastoma (Rb) expression represent consistent but not entirely invariable hallmarks of small cell lung cancer (SCLC). The prevalence and characteristics of SCLC retaining wild-type Rb are not well-established. Furthermore, the performance of targeted next-generation sequencing (NGS) versus immunohistochemistry for Rb assessment is not well-defined. A total of 208 clinical SCLC s les were analyzed by comprehensive targeted NGS, covering all exons of RB1, and Rb IHC. On the basis of established coordination of Rb 16/cyclinD1 expression, p16-high/cyclinD1-low profile was used as a marker of constitutive Rb deficiency. Fourteen of 208 (6%) SCLC expressed wild-type Rb, accompanied by a unique p16-low/cyclinD1-high profile supporting Rb proficiency. Rb-proficient SCLC was associated with neuroendocrine-low phenotype, combined SCLC with non-SCLC (NSCLC) histology and aggressive behavior. These tumors exclusively harbored CCND1 lification (29%), and were markedly enriched in CDKN2A mutations (50%) and NSCLC-type alterations (KEAP1, STK11, FGFR1). The remaining 194 of 208 SCLC were Rb-deficient (p16-high/cyclinD1-low), including 184 cases with Rb loss (of which 29% lacked detectable RB1 alterations by clinical NGS pipeline), and 10 cases with mutated but expressed Rb. This is the largest study to date to concurrently analyze Rb by NGS and IHC in SCLC, identifying a 6% rate of Rb proficiency. Pathologic-genomic data implicate NSCLC-related progenitors as a putative source of Rb-proficient SCLC. Consistent upstream Rb inactivation via CDKN2A 16↓ and CCND1/cyclinD1↑ suggests the potential utility of CDK4/6 inhibitors in this aggressive SCLC subset. The study also clarifies technical aspects of Rb status determination in clinical practice, highlighting the limitations of exon-only sequencing for RB1 interrogation. See related commentary by Mahadevan and Sholl, p. 4603
Publisher: Cold Spring Harbor Laboratory
Date: 13-12-2018
DOI: 10.1101/495564
Abstract: 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 in idual 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.
Publisher: Informa UK Limited
Date: 13-12-2018
Publisher: Springer Science and Business Media LLC
Date: 20-11-2020
Publisher: American Association for Cancer Research (AACR)
Date: 04-2023
DOI: 10.1158/1078-0432.C.6532947
Abstract: AbstractPurpose: i RB1 /i mutations and loss of retinoblastoma (Rb) expression represent consistent but not entirely invariable hallmarks of small cell lung cancer (SCLC). The prevalence and characteristics of SCLC retaining wild-type Rb are not well-established. Furthermore, the performance of targeted next-generation sequencing (NGS) versus immunohistochemistry for Rb assessment is not well-defined. Experimental Design: A total of 208 clinical SCLC s les were analyzed by comprehensive targeted NGS, covering all exons of i RB1 /i , and Rb IHC. On the basis of established coordination of Rb 16/cyclinD1 expression, p16-high/cyclinD1-low profile was used as a marker of constitutive Rb deficiency. Results: Fourteen of 208 (6%) SCLC expressed wild-type Rb, accompanied by a unique p16-low/cyclinD1-high profile supporting Rb proficiency. Rb-proficient SCLC was associated with neuroendocrine-low phenotype, combined SCLC with non-SCLC (NSCLC) histology and aggressive behavior. These tumors exclusively harbored i CCND1 /i lification (29%), and were markedly enriched in i CDKN2A /i mutations (50%) and NSCLC-type alterations ( i KEAP1 /i , i STK11, FGFR1 /i ). The remaining 194 of 208 SCLC were Rb-deficient (p16-high/cyclinD1-low), including 184 cases with Rb loss (of which 29% lacked detectable i RB1 /i alterations by clinical NGS pipeline), and 10 cases with mutated but expressed Rb. Conclusions: This is the largest study to date to concurrently analyze Rb by NGS and IHC in SCLC, identifying a 6% rate of Rb proficiency. Pathologic-genomic data implicate NSCLC-related progenitors as a putative source of Rb-proficient SCLC. Consistent upstream Rb inactivation via i CDKN2A /i 16 sup ↓ /sup and i CCND1 /i /cyclinD1 sup ↑ /sup suggests the potential utility of CDK4/6 inhibitors in this aggressive SCLC subset. The study also clarifies technical aspects of Rb status determination in clinical practice, highlighting the limitations of exon-only sequencing for i RB1 /i interrogation. i a href="lincancerres/article/doi/10.1158/1078-0432.CCR-22-2187" target="_blank" See related commentary by Mahadevan and Sholl, p. 4603 /a /i /
Publisher: JMIR Publications Inc.
Date: 11-12-2020
DOI: 10.2196/23369
Abstract: Behavior change apps can develop iteratively, where the app evolves into a complex, dynamic, or personalized intervention through cycles of research, development, and implementation. Understanding how existing users engage with an app (eg, frequency, amount, depth, and duration of use) can help guide further incremental improvements. We aim to explore how simple visualizations can provide a good understanding of temporal patterns of engagement, as usage data are often longitudinal and rich. This study aims to visualize behavioral engagement with Drink Less, a behavior change app to help reduce hazardous and harmful alcohol consumption in the general adult population of the United Kingdom. We explored behavioral engagement among 19,233 existing users of Drink Less. Users were included in the s le if they were from the United Kingdom were 18 years or older were interested in reducing their alcohol consumption had a baseline Alcohol Use Disorders Identification Test score of 8 or above, indicative of excessive drinking and had downloaded the app between May 17, 2017, and January 22, 2019 (615 days). Measures of when sessions begin, length of sessions, time to disengagement, and patterns of use were visualized with heat maps, timeline plots, k-modes clustering analyses, and Kaplan-Meier plots. The daily 11 AM notification is strongly associated with a change in engagement in the following hour reduction in behavioral engagement over time, with 50.00% (9617/19,233) of users disengaging (defined as no use for 7 or more consecutive days) 22 days after download identification of 3 distinct trajectories of use, namely engagers (4651/19,233, 24.18% of users), slow disengagers (3679/19,233, 19.13% of users), and fast disengagers (10,903/19,233, 56.68% of users) and limited depth of engagement with 85.076% (7,095,348/8,340,005) of screen views occurring within the Self-monitoring and Feedback module. In addition, a peak of both frequency and amount of time spent per session was observed in the evenings. Visualizations play an important role in understanding engagement with behavior change apps. Here, we discuss how simple visualizations helped identify important patterns of engagement with Drink Less. Our visualizations of behavioral engagement suggest that the daily notification substantially impacts engagement. Furthermore, the visualizations suggest that a fixed notification policy can be effective for maintaining engagement for some users but ineffective for others. We conclude that optimizing the notification policy to target both effectiveness and engagement is a worthwhile investment. Our future goal is to both understand the causal effect of the notification on engagement and further optimize the notification policy within Drink Less by tailoring to contextual circumstances of in iduals over time. Such tailoring will be informed from the findings of our micro-randomized trial (MRT), and these visualizations were useful in both gaining a better understanding of engagement and designing the MRT.
Publisher: Elsevier BV
Date: 2023
DOI: 10.1016/J.NEUROBIOLAGING.2022.09.003
Abstract: Alpha-band oscillatory activity in human electroencephalography (EEG) becomes slower and lower in litude with advanced age. However, the influence of aperiodic activity on these measures has received little consideration. We investigated whether age-related differences in aperiodic activity explains differences in resting EEG peak alpha frequency and power. We assessed aperiodic activity in 85 younger and 92 older adults by fitting the 1/f-like background activity evident in EEG power spectra using the spectral parameterization ("specparam") algorithm. Across the scalp, the aperiodic exponent and offset were smaller in older compared to younger participants, reflecting a flatter 1/f-like slope and a downward broadband shift in power spectra with age. After correcting for aperiodic activity, peak alpha frequency remained slower in older adults however, peak alpha power no longer differed statistically between age groups. The large s le size utilized in this study, as well as the depth of analysis, provides further evidence that the aperiodic component of the resting EEG signal is altered with aging and should be considered when investigating neural oscillatory activity.
Location: United States of America
Location: Australia
No related grants have been discovered for Lynton Graetz.