The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation
|
|---|---|
| Published in |
Frontiers in Aging Neuroscience, June 2017
|
| DOI | 10.3389/fnagi.2017.00189 |
| Pubmed ID | |
| Authors |
Assenza Giovanni, Fioravante Capone, Lazzaro di Biase, Florinda Ferreri, Lucia Florio, Andrea Guerra, Massimo Marano, Matteo Paolucci, Federico Ranieri, Gaetano Salomone, Mario Tombini, Gregor Thut, Vincenzo Di Lazzaro |
| Abstract |
Non-invasive brain stimulation (NIBS) has been under investigation as adjunct treatment of various neurological disorders with variable success. One challenge is the limited knowledge on what would be effective neuronal targets for an intervention, combined with limited knowledge on the neuronal mechanisms of NIBS. Motivated on the one hand by recent evidence that oscillatory activities in neural systems play a role in orchestrating brain functions and dysfunctions, in particular those of neurological disorders specific of elderly patients, and on the other hand that NIBS techniques may be used to interact with these brain oscillations in a controlled way, we here explore the potential of modulating brain oscillations as an effective strategy for clinical NIBS interventions. We first review the evidence for abnormal oscillatory profiles to be associated with a range of neurological disorders of elderly (e.g., Parkinson's disease (PD), Alzheimer's disease (AD), stroke, epilepsy), and for these signals of abnormal network activity to normalize with treatment, and/or to be predictive of disease progression or recovery. We then ask the question to what extent existing NIBS protocols have been tailored to interact with these oscillations and possibly associated dysfunctions. Our review shows that, despite evidence for both reliable neurophysiological markers of specific oscillatory dis-functionalities in neurological disorders and NIBS protocols potentially able to interact with them, there are few applications of NIBS aiming to explore clinical outcomes of this interaction. Our review article aims to point out oscillatory markers of neurological, which are also suitable targets for modification by NIBS, in order to facilitate in future studies the matching of technical application to clinical targets. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Chile | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 251 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 251 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 40 | 16% |
| Researcher | 40 | 16% |
| Student > Master | 29 | 12% |
| Student > Bachelor | 24 | 10% |
| Student > Doctoral Student | 13 | 5% |
| Other | 37 | 15% |
| Unknown | 68 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 50 | 20% |
| Medicine and Dentistry | 41 | 16% |
| Psychology | 21 | 8% |
| Engineering | 13 | 5% |
| Agricultural and Biological Sciences | 7 | 3% |
| Other | 31 | 12% |
| Unknown | 88 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 June 2017.
All research outputs
#14,069,530
of 22,982,639 outputs
Outputs from Frontiers in Aging Neuroscience
#3,107
of 4,833 outputs
Outputs of similar age
#170,746
of 317,532 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#96
of 126 outputs
Altmetric has tracked 22,982,639 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,833 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,532 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 126 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.