Back

Rapid encoding of temporal sequences discovered in brain dynamics

Bonetti, L.; Brattico, E.; Carlomagno, F.; Donati, G.; Cabral, J.; Haumann, N. T.; Deco, G.; Vuust, P.; Kringelbach, M. L.

2020-12-11 neuroscience
10.1101/2020.12.11.421669 bioRxiv
Show abstract

Information encoding has received a wide neuroscientific attention, but the underlying rapid spatiotemporal brain dynamics remain largely unknown. Here, we investigated the rapid brain mechanisms for encoding and prediction of sounds forming a complex temporal sequence. Specifically, we used magnetoencephalography (MEG) to record the brain activity of 68 participants while they listened to a highly structured musical prelude. Advanced analysis of the phase synchronisation and graph theoretical measures showed the rapid transition of brain activity from primary auditory cortex to higher order association areas including insula and superior temporal pole within a whole-brain network, occurring during the first 220 ms of the encoding process. We discovered individual differences, revealing the rapid unfolding of brain network dynamics responsible for the processing of the current sounds and the prediction of the forthcoming events of the sequence. This provides a first glimpse of the general mechanisms underlying pattern encoding in the human brain.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Scientific Reports
○ 3612 papers in training set
Top 0.7%
18.7%
Similar papers in this journal
2
NeuroImage
○ 903 papers in training set
Top 0.6%
18.7%
Similar papers in this journal
3
Human Brain Mapping
○ 329 papers in training set
Top 0.4%
11.1%
Similar papers in this journal
4
Communications Biology
○ 993 papers in training set
Top 0.4%
7.9%
Similar papers in this journal
50% of probability mass above
5
Cerebral Cortex
◐ 396 papers in training set
Top 1.0%
5.6%
Similar papers in this journal
6
iScience
○ 1154 papers in training set
Top 4%
4.1%
7
Nature Communications
○ 5641 papers in training set
Top 35%
3.2%
8
eLife
● 5828 papers in training set
Top 36%
3.2%
9
Frontiers in Neuroscience
○ 256 papers in training set
Top 2%
2.7%
10
Imaging Neuroscience
● 282 papers in training set
Top 2%
2.1%
11
Brain Topography
○ 29 papers in training set
Top 0.2%
1.9%
12
PLOS Biology
● 486 papers in training set
Top 5%
1.7%
13
The Journal of Neuroscience
● 1025 papers in training set
Top 8%
1.3%
14
Progress in Neurobiology
○ 47 papers in training set
Top 0.4%
1.1%
15
Network Neuroscience
● 126 papers in training set
Top 1%
1.1%
16
Advanced Science
○ 286 papers in training set
Top 6%
1.1%
17
PLOS ONE
● 5266 papers in training set
Top 56%
1.0%
18
Cell Reports
○ 1498 papers in training set
Top 26%
0.9%
19
Scientific Data
○ 209 papers in training set
Top 3%
0.8%
20
Science Advances
● 1243 papers in training set
Top 33%
0.6%
21
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 44%
0.6%
22
eneuro
● 439 papers in training set
Top 8%
0.6%
23
Frontiers in Systems Neuroscience
○ 22 papers in training set
Top 0.3%
0.6%
24
European Journal of Neuroscience
○ 189 papers in training set
Top 4%
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.