Back

Neural Stimulation in vitro and in vivo by Photoacoustic Nanotransducers

Huang, Y.; Jiang, Y.; Luo, X.; Wu, J.; Zong, H.; Shi, L.; Cheng, R.; Jiang, S.; Jia, X.; Mei, J.; Man, H.; Cheng, J.-X.; Yang, C.

2020-05-23 neuroscience
10.1101/2020.05.20.106898 bioRxiv
Show abstract

Neuromodulation is an invaluable approach for study of neural circuits and clinical treatment of neurological diseases. Here, we report semiconducting polymer nanoparticles based photoacoustic nanotransducers (PANs) for neural stimulation. Our PANs strongly absorb light in the near-infrared second window and generate localized acoustic waves. PANs can also be surface-modified to selectively bind onto neurons. PAN-mediated activation of primary neurons in vitro is achieved with ten 3-nanosecond laser pulses at 1030 nm over a 3 millisecond duration. In vivo neural modulation of mouse brain activities and motor activities is demonstrated by PANs directly injected into brain cortex. With millisecond-scale temporal resolution, sub-millimeter spatial resolution and negligible heat deposition, PAN stimulation is a new non-genetic method for precise control of neuronal activities, opening potentials in non-invasive brain modulation.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Advanced Science
○ 286 papers in training set
Top 0.2%
13.3%
Similar papers in this journal
2
Science Advances
● 1243 papers in training set
Top 0.7%
12.0%
Similar papers in this journal
3
Nature Communications
○ 5641 papers in training set
Top 18%
9.9%
Similar papers in this journal
4
ACS Nano
● 113 papers in training set
Top 0.4%
5.5%
Similar papers in this journal
5
iScience
○ 1154 papers in training set
Top 3%
4.9%
Similar papers in this journal
6
Scientific Reports
○ 3612 papers in training set
Top 21%
4.4%
50% of probability mass above
7
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 12%
4.1%
8
Neurophotonics
● 42 papers in training set
Top 0.2%
3.5%
9
Communications Biology
○ 993 papers in training set
Top 5%
3.3%
10
Advanced Functional Materials
○ 46 papers in training set
Top 0.4%
3.3%
11
Analytical Chemistry
● 218 papers in training set
Top 1%
3.2%
12
Small
○ 78 papers in training set
Top 0.6%
2.5%
13
eLife
● 5828 papers in training set
Top 45%
2.1%
14
Small Methods
○ 29 papers in training set
Top 0.2%
1.7%
15
Advanced Healthcare Materials
○ 85 papers in training set
Top 1.0%
1.5%
16
Cell Reports Methods
○ 165 papers in training set
Top 2%
1.1%
17
Bioactive Materials
○ 20 papers in training set
Top 0.4%
1.1%
18
Nanoscale
● 42 papers in training set
Top 0.6%
1.1%
19
Chemical Communications
● 25 papers in training set
Top 0.4%
1.1%
20
RSC Advances
● 22 papers in training set
Top 0.6%
1.0%
21
Advanced Materials
○ 56 papers in training set
Top 1.0%
0.9%
22
Lab on a Chip
● 96 papers in training set
Top 1.0%
0.9%
23
ACS Chemical Neuroscience
● 67 papers in training set
Top 1%
0.9%
24
Optica
● 27 papers in training set
Top 0.3%
0.9%
25
Theranostics
● 37 papers in training set
Top 1%
0.6%
26
ACS Biomaterials Science & Engineering
● 37 papers in training set
Top 1%
0.6%
27
Biosensors and Bioelectronics
○ 57 papers in training set
Top 0.8%
0.6%
28
Light: Science & Applications
○ 16 papers in training set
Top 0.3%
0.6%
29
Nature Chemistry
○ 42 papers in training set
Top 1%
0.6%
30
Journal of Neural Engineering
○ 221 papers in training set
Top 2%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.