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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Spatial information in large-scale neural recordings
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, January 2015
|
| DOI | 10.3389/fncom.2014.00172 |
| Pubmed ID | |
| Authors |
Thaddeus R. Cybulski, Joshua I. Glaser, Adam H. Marblestone, Bradley M. Zamft, Edward S. Boyden, George M. Church, Konrad P. Kording |
| Abstract |
To record from a given neuron, a recording technology must be able to separate the activity of that neuron from the activity of its neighbors. Here, we develop a Fisher information based framework to determine the conditions under which this is feasible for a given technology. This framework combines measurable point spread functions with measurable noise distributions to produce theoretical bounds on the precision with which a recording technology can localize neural activities. If there is sufficient information to uniquely localize neural activities, then a technology will, from an information theoretic perspective, be able to record from these neurons. We (1) describe this framework, and (2) demonstrate its application in model experiments. This method generalizes to many recording devices that resolve objects in space and should be useful in the design of next-generation scalable neural recording systems. |
X Demographics
The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 27% |
| Canada | 2 | 9% |
| Norway | 1 | 5% |
| France | 1 | 5% |
| Finland | 1 | 5% |
| Portugal | 1 | 5% |
| Belgium | 1 | 5% |
| Unknown | 9 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 64% |
| Scientists | 7 | 32% |
| Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 4% |
| France | 3 | 2% |
| Germany | 2 | 1% |
| United Kingdom | 2 | 1% |
| Chile | 1 | <1% |
| Canada | 1 | <1% |
| Portugal | 1 | <1% |
| Japan | 1 | <1% |
| Luxembourg | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 145 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 43 | 26% |
| Researcher | 30 | 18% |
| Student > Master | 14 | 9% |
| Professor > Associate Professor | 13 | 8% |
| Student > Bachelor | 13 | 8% |
| Other | 39 | 24% |
| Unknown | 11 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 39 | 24% |
| Agricultural and Biological Sciences | 37 | 23% |
| Engineering | 32 | 20% |
| Physics and Astronomy | 7 | 4% |
| Computer Science | 6 | 4% |
| Other | 20 | 12% |
| Unknown | 22 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 02 March 2015.
All research outputs
#2,780,278
of 25,389,532 outputs
Outputs from Frontiers in Computational Neuroscience
#108
of 1,471 outputs
Outputs of similar age
#38,042
of 359,626 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#4
of 33 outputs
Altmetric has tracked 25,389,532 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,471 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done particularly well, scoring higher than 91% 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 359,626 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.