Neuron model RF-PSTH
ASO Keyword Dashboard
Tracking 51 keywords for Neuron model RF-PSTH in Google Play
Neuron model RF-PSTH tracks 51 keywords (no keywords rank yet; 51 need traction). Key metrics: opportunity 71.0, difficulty 44.4.
Simulates Receptive Field (RF) structure and PSTH output signal of the neuron.
Tracked keywords
51
0 ranked • 51 not ranking yet
Top 10 coverage
—
Best rank — • Latest leader —
Avg opportunity
71.0
Top keyword: difference
Avg difficulty
44.4
Lower scores indicate easier wins
Opportunity leaders
- 63.6
difference
Opportunity: 75.0 • Difficulty: 41.2 • Rank —
Competitors: 478
- 59.9
output
Opportunity: 74.0 • Difficulty: 37.7 • Rank —
Competitors: 283
- 62.9
structure
Opportunity: 74.0 • Difficulty: 39.1 • Rank —
Competitors: 256
- 64.5
models
Opportunity: 74.0 • Difficulty: 50.0 • Rank —
Competitors: 854
- 60.4
dog
Opportunity: 74.0 • Difficulty: 42.7 • Rank —
Competitors: 534
Unranked opportunities
difference
Opportunity: 75.0 • Difficulty: 41.2 • Competitors: 478
output
Opportunity: 74.0 • Difficulty: 37.7 • Competitors: 283
structure
Opportunity: 74.0 • Difficulty: 39.1 • Competitors: 256
models
Opportunity: 74.0 • Difficulty: 50.0 • Competitors: 854
dog
Opportunity: 74.0 • Difficulty: 42.7 • Competitors: 534
High competition keywords
time
Total apps: 382,753 • Major competitors: 17,684
Latest rank: — • Difficulty: 57.6
features
Total apps: 256,014 • Major competitors: 15,263
Latest rank: — • Difficulty: 58.0
available
Total apps: 201,519 • Major competitors: 10,529
Latest rank: — • Difficulty: 58.5
real
Total apps: 184,515 • Major competitors: 13,323
Latest rank: — • Difficulty: 56.7
even
Total apps: 156,616 • Major competitors: 11,437
Latest rank: — • Difficulty: 56.8
All tracked keywords
Includes opportunity, difficulty, rankings and competitor benchmarks
| Major Competitors | |||||||
|---|---|---|---|---|---|---|---|
| try | 69 | 100 | 56 | 78 80,356 competing apps Median installs: 7,009 Avg rating: 4.0 | — | — | 7,920 major competitor apps |
| scientists | 71 | 100 | 32 | 49 1,170 competing apps Median installs: 2,487 Avg rating: 4.0 | — | — | 48 major competitor apps |
| needs | 70 | 100 | 48 | 76 57,220 competing apps Median installs: 1,291 Avg rating: 4.0 | — | — | 2,528 major competitor apps |
| time | 64 | 100 | 58 | 89 382,753 competing apps Median installs: 1,505 Avg rating: 4.0 | — | — | 17,684 major competitor apps |
| available | 66 | 100 | 58 | 84 201,519 competing apps Median installs: 2,612 Avg rating: 4.0 | — | — | 10,529 major competitor apps |
| program | 70 | 100 | 46 | 74 43,465 competing apps Median installs: 1,840 Avg rating: 4.1 | — | — | 1,329 major competitor apps |
| tool | 68 | 100 | 50 | 80 102,387 competing apps Median installs: 1,350 Avg rating: 4.0 | — | — | 4,128 major competitor apps |
| real | 66 | 100 | 57 | 84 184,515 competing apps Median installs: 2,406 Avg rating: 4.0 | — | — | 13,323 major competitor apps |
| ever | 71 | 100 | 53 | 72 33,419 competing apps Median installs: 4,351 Avg rating: 4.0 | — | — | 2,828 major competitor apps |
| please | 67 | 100 | 53 | 81 127,760 competing apps Median installs: 5,026 Avg rating: 4.1 | — | — | 6,895 major competitor apps |
| output | 74 | 100 | 38 | 60 5,805 competing apps Median installs: 3,529 Avg rating: 3.9 | — | — | 283 major competitor apps |
| teachers | 72 | 100 | 42 | 70 23,418 competing apps Median installs: 808 Avg rating: 4.0 | — | — | 300 major competitor apps |
| tablet | 72 | 100 | 56 | 70 23,978 competing apps Median installs: 5,280 Avg rating: 4.0 | — | — | 1,525 major competitor apps |
| structure | 74 | 100 | 39 | 63 8,920 competing apps Median installs: 1,248 Avg rating: 4.0 | — | — | 256 major competitor apps |
| features | 66 | 100 | 58 | 86 256,014 competing apps Median installs: 2,725 Avg rating: 4.0 | — | — | 15,263 major competitor apps |
| important | 68 | 100 | 52 | 81 118,554 competing apps Median installs: 1,454 Avg rating: 4.1 | — | — | 4,308 major competitor apps |
| field | 72 | 100 | 44 | 71 28,375 competing apps Median installs: 1,182 Avg rating: 3.9 | — | — | 698 major competitor apps |
| description | 73 | 100 | 42 | 66 14,630 competing apps Median installs: 1,400 Avg rating: 4.1 | — | — | 495 major competitor apps |
| based | 67 | 100 | 55 | 82 151,311 competing apps Median installs: 1,480 Avg rating: 4.0 | — | — | 5,822 major competitor apps |
| even | 67 | 100 | 57 | 83 156,616 competing apps Median installs: 4,222 Avg rating: 4.0 | — | — | 11,437 major competitor apps |
| big | 71 | 100 | 51 | 73 36,256 competing apps Median installs: 8,328 Avg rating: 4.0 | — | — | 4,037 major competitor apps |
| model | 73 | 100 | 45 | 66 14,644 competing apps Median installs: 3,809 Avg rating: 3.9 | — | — | 845 major competitor apps |
| able | 69 | 100 | 50 | 78 77,117 competing apps Median installs: 2,134 Avg rating: 4.0 | — | — | 3,593 major competitor apps |
| first | 68 | 100 | 51 | 80 105,380 competing apps Median installs: 3,142 Avg rating: 4.0 | — | — | 5,370 major competitor apps |
| difference | 75 | 100 | 41 | 64 9,887 competing apps Median installs: 1,694 Avg rating: 4.1 | — | — | 478 major competitor apps |
App Description
Simulates Receptive Field (RF) structure and PSTH output signal of the neuron.
Currently available artificial neuron models are unable to simulate fundamentally important features of real biological neurons: 1) antagonistic receptive fields and 2) PSTH output signal of neuron to any stimulus.
Even if some neuron models try to simulate antagonistic receptive fields then they are unable to simulate PSTH output signal, and vice versa – some other models try to simulate PSTH output signal of neuron, however these models fail to explain antagonistic receptive fields of neurons. As for example, a very popular DOG (Difference Of Gaussians) model simulates antagonistic structure of the receptive field, however DOG model fails to simulate PSTH output signal of neuron. And the vast majority of artificial neural models even fail to simulate both: antagonistic receptive fields and PSTH output signal.
For the first time ever neuron model RF-PSTH is able to simulate both antagonistic receptive fields and PSTH output signal.
Neuron model RF-PSTH is based on physics of real biological neurons.
Note: "Neuron model RF-PSTH" program needs big screen. Please use the tablet instead of phone.
Full description is available at the address:
http://neuroclusterbrain.com/neuron_model.html