Temporally delayed linear modelling (TDLM) measures replay in both animals and humans
- University College London, United Kingdom
- University of Oxford, United Kingdom
- Massachusetts Institute of Technology, United States
- Donders Institute for Brain Cognition and Behaviour, Radboud University, Netherlands
- DeepMind, United Kingdom
Abstract
There are rich structures in off-task neural activity which are hypothesised to reflect fundamental computations across a broad spectrum of cognitive functions. Here, we develop an analysis toolkit – Temporal Delayed Linear Modelling (TDLM) for analysing such activity. TDLM is a domain-general method for finding neural sequences that respect a pre-specified transition graph. It combines nonlinear classification and linear temporal modelling to test for statistical regularities in sequences of task-related reactivations. TDLM is developed on the non-invasive neuroimaging data and is designed to take care of confounds and maximize sequence detection ability. Notably, as a linear framework, TDLM can be easily extended, without loss of generality, to capture rodent replay in electrophysiology, including in continuous spaces, as well as addressing second-order inference questions, e.g., its temporal and spatial varying pattern. We hope TDLM will advance a deeper understanding of neural computation and promote a richer convergence between animal and human neuroscience.
Data availability
No new data is used or generated in the current paper.Data relevant for current paper is available at https://github.com/YunzheLiu/TDLM. This dataset is from "Ólafsdóttir, H. F., Carpenter, F., & Barry, C. (2016). Coordinated grid and place cell replay during rest. Nature neuroscience, 19(6), 792-794."
Article and author information
Author details
Funding
Wellcome (098362/Z/12/Z)
- Raymond J Dolan
Wellcome (104765/Z/14/Z)
- Timothy E Behrens
Wellcome (219525/Z/19/Z)
- Timothy E Behrens
James S. McDonnell Foundation (JSMF220020372)
- Timothy E Behrens
Wellcome (212281/Z/18/Z)
- Caswell Barry
max planck
- Yunzhe Liu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The human dataset used in this study was reported in Liu et al 2019. All participants were recruited from the UCL Institute of Cognitive Neuroscience subject pool, had a normal or corrected-to-normal vision, no history of psychiatric or neurological disorders, and had provided written informed consent prior to the start of the experiment, which was approved by the Research Ethics Committee at University College London (UK), under ethics number 9929/002.
Copyright
© 2021, Liu et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,222
- views
-
- 936
- downloads
-
- 33
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Temporally delayed linear modelling (TDLM) measures replay in both animals and humans
eLife 10:e66917.
https://doi.org/10.7554/eLife.66917
Further reading
-
- Neuroscience
People selectively help others based on perceptions of their merit or need. Here, we develop a neurocomputational account of how these social perceptions translate into social choice. Using a novel fMRI social perception task, we show that both merit and need perceptions recruited the brain’s social inference network. A behavioral computational model identified two non-exclusive mechanisms underlying variance in social perceptions: a consistent tendency to perceive others as meritorious/needy (bias) and a propensity to sample and integrate normative evidence distinguishing high from low merit/need in other people (sensitivity). Variance in people’s merit (but not need) bias and sensitivity independently predicted distinct aspects of altruism in a social choice task completed months later. An individual’s merit bias predicted context-independent variance in people’s overall other-regard during altruistic choice, biasing people toward prosocial actions. An individual’s merit sensitivity predicted context-sensitive discrimination in generosity toward high and low merit recipients by influencing other- and self-regard during altruistic decision-making. This context-sensitive perception–action link was associated with activation in the right temporoparietal junction. Together, these findings point toward stable, biologically based individual differences in perceptual processes related to abstract social concepts like merit, and suggest that these differences may have important behavioral implications for an individual’s tendency toward favoritism or discrimination in social settings.
-
- Neuroscience
Mice lacking two neuropeptides thought to be essential for processing pain show no change in how they respond to a wide range of harmful stimuli.
