2018
DOI: 10.1523/eneuro.0379-17.2018
|View full text |Cite
|
Sign up to set email alerts
|

Uncovering Neuronal Networks Defined by Consistent Between-Neuron Spike Timing from Neuronal Spike Recordings

Abstract: It is widely assumed that distributed neuronal networks are fundamental to the functioning of the brain. Consistent spike timing between neurons is thought to be one of the key principles for the formation of these networks. This can involve synchronous spiking or spiking with time delays, forming spike sequences when the order of spiking is consistent. Finding networks defined by their sequence of time-shifted spikes, denoted here as spike timing networks, is a tremendous challenge. As neurons can participate… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
12
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
4
3
1

Relationship

0
8

Authors

Journals

citations
Cited by 11 publications
(12 citation statements)
references
References 67 publications
0
12
0
Order By: Relevance
“…we may be unable to ground such relations to anything meaningful). Nonetheless, promising new methods that decompose population time series [62], cluster neural patterns [73,74] or estimate neural states [31,75] have begun to be used for the unsupervised detection and quantification of neural sequences. Finally, the recent development of deep learning techniques that can capture the statistics of neuronal patterns, even in single trials [76] is an interesting direction that will probably attract a lot of attention in the coming years.…”
Section: (B) Template-free Approachesmentioning
confidence: 99%
“…we may be unable to ground such relations to anything meaningful). Nonetheless, promising new methods that decompose population time series [62], cluster neural patterns [73,74] or estimate neural states [31,75] have begun to be used for the unsupervised detection and quantification of neural sequences. Finally, the recent development of deep learning techniques that can capture the statistics of neuronal patterns, even in single trials [76] is an interesting direction that will probably attract a lot of attention in the coming years.…”
Section: (B) Template-free Approachesmentioning
confidence: 99%
“…A code that relies on neural sequences implies temporally precise activation of single neurons (see Fig. 2a for schematic) (Buzsáki, 2010; van der Meij & Voytek, 2018). We examined the firing properties of 3543 neurons in 17 recording sessions (mean of 208, median of 229 simultaneously recorded neurons per session).…”
Section: Resultsmentioning
confidence: 99%
“…Nevertheless, the results of Nádasdy et al (1999) are ambiguous. More than two decades after this study, it remains very difficult to trace signals as they traverse multiple nodes of known connectivity in a brain network (see van der Meij and Voytek, 2018;Hodassman et al, 2022). Models that rely on inferring causality linking separate measurements of structure and activation (e.g., Javadzadeh and Hofer, 2021) can be misleading (see, e.g., Mehler and Kording, 2018;Brette, 2019;Bruineberg et al, 2021).…”
Section: Box Evidence For Flexible Routing In Hippocampal Circuits?mentioning
confidence: 99%