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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Forward Prediction in the Posterior Parietal Cortex and Dynamic Brain-Machine Interface
|
|---|---|
| Published in |
Frontiers in Integrative Neuroscience, October 2016
|
| DOI | 10.3389/fnint.2016.00035 |
| Pubmed ID | |
| Authors |
He Cui |
| Abstract |
While remarkable progress has been made in brain-machine interfaces (BMIs) over the past two decades, it is still difficult to utilize neural signals to drive artificial actuators to produce predictive movements in response to dynamic stimuli. In contrast to naturalistic limb movements largely based on forward planning, brain-controlled neuroprosthetics mainly rely on feedback without prior trajectory formation. As an important sensorimotor interface integrating multisensory inputs and efference copy, the posterior parietal cortex (PPC) might play a proactive role in predictive motor control. Here it is proposed that predictive neural activity in PPC could be decoded to provide prosthetic control signals for guiding BMI systems in dynamic environments. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 17% |
| Netherlands | 1 | 17% |
| United States | 1 | 17% |
| Italy | 1 | 17% |
| Switzerland | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 63 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 22% |
| Researcher | 13 | 21% |
| Student > Master | 8 | 13% |
| Student > Bachelor | 4 | 6% |
| Student > Postgraduate | 4 | 6% |
| Other | 7 | 11% |
| Unknown | 13 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 20 | 32% |
| Agricultural and Biological Sciences | 7 | 11% |
| Engineering | 4 | 6% |
| Linguistics | 3 | 5% |
| Psychology | 3 | 5% |
| Other | 9 | 14% |
| Unknown | 17 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 22 November 2016.
All research outputs
#12,971,559
of 22,896,955 outputs
Outputs from Frontiers in Integrative Neuroscience
#396
of 856 outputs
Outputs of similar age
#155,809
of 314,045 outputs
Outputs of similar age from Frontiers in Integrative Neuroscience
#7
of 11 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 856 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has gotten more attention than average, scoring higher than 52% of its peers.
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 314,045 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.