Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture

  1. Richard Gao  Is a corresponding author
  2. Ruud L van den Brink
  3. Thomas Pfeffer
  4. Bradley Voytek
  1. Department of Cognitive Science, University of California, San Diego, United States
  2. Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Germany
  3. Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Spain
  4. Halıcıoğlu Data Science Institute, University of California, San Diego, United States
  5. Neurosciences Graduate Program, University of California, San Diego, United States
  6. Kavli Institute for Brain and Mind, University of California, San Diego, United States
7 figures, 2 tables and 4 additional files

Figures

Schematic of study and timescale inference technique.

(A) In this study, we infer neuronal timescales from intracranial field potential recordings, which reflect integrated synaptic and transmembrane current fluctuations over large neural populations (B…

Figure 2 with 4 supplements
Timescale increases along the anatomical hierarchy in humans and macaques.

(A) Example time series from five electrodes along the human cortical hierarchy (M1: primary motor cortex; SMC: supplementary motor cortex; OFC: orbitofrontal cortex; ACC: anterior cingulate cortex; …

Figure 2—figure supplement 1
MNI-iEEG dataset electrode coverage.

(A) Per-parcel Gaussian-weighted mask values showing how close the nearest electrode was to a given HCP-MMP1.0 parcel for each participant. Brighter means closer, 0.5 corresponds to the nearest …

Figure 2—figure supplement 2
Comparison of spatial autocorrelation-preserving null map generation methods.

(A) Distributions of Spearman correlation values between empirical T1w/T2w map and 1000 spatial-autocorrelation preserving null timescale maps generated using Moran Spectral Randomization (MSR), …

Figure 2—figure supplement 3
Cortical thickness.

Cortical thickness from the HCP dataset is positively correlated with neuronal timescale (left) and negatively correlated with T1w/T2w, i.e., thicker brain regions have longer (slower) timescales …

Figure 2—figure supplement 4
Macaque ECoG and single-unit coverage.

(A) Locations of 180-electrode ECoG grid from two animals in the Neurotycho dataset; colors correspond to locations used for comparison with single-unit timescales. (B) Electrode indices of the …

Figure 3 with 2 supplements
Timescale gradient is linked to expression of genes related to synaptic receptors and transmembrane ion channels across the human cortex.

(A) Timescale gradient follows the dominant axis of gene expression variation across the cortex (z-scored PC1 of 2429 brain-specific genes, arbitrary direction). (B) Timescale gradient is …

Figure 3—figure supplement 1
Transcriptomic principal component analysis results.

(A) Proportion of variance explained by the top 10 principal components (PCs) of brain-specific genes (top) and all AHBA genes (bottom). (B) Absolute Spearman correlation between timescale map and …

Figure 3—figure supplement 2
Individual timescale-gene correlations magnitudes.

Correlation between timescale and expression of genes from Figure 3C, with gene symbols labeled and grouped into functional families for ease of interpretation.

Figure 4 with 2 supplements
Timescales expand during working memory maintenance while tracking performance, and task-free average timescales compress in older adults.

(A) Fourteen participants with overlapping intracranial coverage performed a visuospatial working memory task, with 900 ms of baseline (pre-stimulus) and delay period data analyzed (PC: parietal, …

Figure 4—figure supplement 1
Spectral correlates of working memory performance.

(A) Difference between delay and baseline periods for 1/f-exponent, timescale (same as main Figure 4C but absolute units on y-axis, instead of percentage), theta power, and high-frequency power. (B) …

Figure 4—figure supplement 2
Parameter sensitivity for timescale-aging analysis.

(A) Cortex-averaged timescale is independent of parcel coverage across participants. (B) Sensitivity analysis for the number of valid parcels a participant must have in order to be included in …

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Tables

Table 1
Summary of open-access datasets used.
DataRef.Specific source/format usedParticipant infoRelevant figures
MNI Open iEEG AtlasFrauscher et al., 2018a; Frauscher et al., 2018bN = 105 (48 females)
Ages: 13–65, 33.4 ± 10.6
Figure 2A–D,
Figure 3,
Figure 4E and F
T1w/T2w and cortical thickness maps from
Human Connectome Project
Glasser et al., 2016; Glasser and Van Essen, 2011Release S1200, March 1, 2017N = 1096 (596 females)
Age: 22–36+ (details restricted due to identifiability)
Figure 2C and D,
Figure 3D–F
Neurotycho macaque ECoGNagasaka et al., 2011; Yanagawa et al., 2013Eyes-open state from anesthesia datasets (propofol and ketamine)Two animals (Chibi and George)
four sessions each
Figure 2E–G
Macaque single-unit timescalesMurray et al., 2014Figure 1 of referenceFigure 2E–G
Whole-cortex interpolated Allen Brain Atlas human gene expressionGryglewski et al., 2018; Hawrylycz et al., 2012Interpolated maps downloadable from http://www.meduniwien.ac.at/neuroimaging/mRNA.htmlN = 6 (one female)
Age: 24, 31, 39, 49, 55, 57 (42.5 ± 12.2)
Figure 3
Single-cell timescale-related genesBomkamp et al., 2019; Tripathy et al., 2017Table S3 from Tripathy et al., 2017, Online Table 1 from Bomkamp et al., 2019N = 170 (Tripathy et al., 2017) and 4168 (Bomkamp et al., 2019) genesFigure 3C and D
Human working memory ECoGJohnson, 2019; Johnson, 2018c; Johnson et al., 2018a, Johnson et al., 2018bCRCNS fcx-2 and fcx-3N = 14 (five females)
Age: 22–50, 30.9 ± 7.8
Figure 4A–D
Table 2
Reproducing figures from code repository.
All IPython notebooks (Gao, 2020): https://github.com/rdgao/field-echos/tree/master/notebooks
NotebookResults
1_sim_method_schematic.ipynbSimulations: Figure 1B–E
2_viz_NeuroTycho-SU.ipynbMacaque timescales: Figure 2E–G, Figure 2—figure supplement 4
3_viz_human_structural.ipynbHuman timescales vs. T1w/T2w and gene expression:

Figure 2A–D, Figure 2—figure supplements 1 and 3, Figure 3, Figure 3—figure supplements 1 and 2, Supplementary file 1–Supplementary file 2Supplementary file 3.
4b_viz_human_wm.ipynbHuman working memory: Figure 4A–D, Figure 4—figure supplement 1
4a_viz_human_aging.ipynbHuman aging: Figure 4E and F, Figure 4—figure supplement 2
 supp_spatialautocorr.ipynbSpatial autocorrelation-preserving nulls:
supp_spatialautocorr.ipynb

Spatial autocorrelation-preserving nulls: Figure 2—figure supplement 2

Additional files

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