Evolutionary shaping of human brain dynamics
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Australia
- QIMR Berghofer Medical Research Institute, Australia
- Department of Anthropology, Emory University, United States
- Department of Psychiatry and Behavioral Sciences, Emory University, United States
- Yerkes National Primate Research Center, Emory University, United States
- Department of Complex Traits Genetics, Center for Neurogenetics and Cognitive Research, Vrije Universiteit Amsterdam, Netherlands
- Department of Clinical Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands
Figures
Figure 1
Human and chimpanzee connectome properties.
(A, B) Parcellation and connectome. The surface plots show the 114-region atlas (Supplementary file 1) on inflated cortical surfaces. The matrices represent the group-averaged structural …
Figure 2 with 1 supplement
Brain network modeling.
(A) Group-averaged human and chimpanzee networks visualized on the same brain template. Top 20% of connections by strength are shown. (B) Schematic diagram of the model. Each brain region is …
Figure 2—figure supplement 1
Validation of simulated dynamics on empirical functional neuroimaging data.
(A) From the connectome, neural activity is simulated using the model presented in Figure 2B. This activity is fed into a hemodynamic model to obtain a simulated fMRI signal for each brain region. …
Figure 3 with 10 supplements
Human and chimpanzee neural dynamics.
(A) Regional neural dynamics as a function of global recurrent strength (). (B) Violin plot of the distribution of dynamic ranges across brain regions. Each violin shows the first to third …
Figure 3—figure supplement 1
Confirmatory analysis on individual-specific connectomes and accounting for total brain volume.
(A) Regional neural dynamics as a function of global recurrent strength () for exemplar human and chimpanzee participants. (B) Violin plot of the standard deviation () of the distribution of …
Figure 3—figure supplement 2
Confirmatory analysis on human and chimpanzee connectomes of equal connection density.
(A) Regional neural dynamics as a function of global recurrent strength () for the original human connectome, original chimpanzee connectome, and human connectome pruned to have an equal density …
Figure 3—figure supplement 3
Confirmatory analysis accounting for inter-individual variability of connectomic data.
(A) Regional neural dynamics as a function of global recurrent strength () for the original human connectome, original chimpanzee connectome, and human connectome rescaled to match the …
Figure 3—figure supplement 4
Confirmatory analysis on matched sample size.
(A) Regional neural dynamics as a function of global recurrent strength () for the original human connectome, original chimpanzee connectome, and an exemplar human connectome averaged from a …
Figure 3—figure supplement 5
Confirmatory analysis accounting for activity propagation delays between brain regions.
(A) Violin plot of the distribution of propagation time delays () across all connections for a representative human and chimpanzee. Each violin shows the first to third quartile range (black …
Figure 3—figure supplement 6
Confirmatory analysis accounting for heterogeneous excitatory input across brain regions.
(A) The excitatory input in each brain region is inversely proportional to the rank of its total connection strength (). The inset shows the actual relationship between and . (B) Regional …
Figure 3—figure supplement 7
Replication of human neural dynamics on an independent dataset.
(A) Regional neural dynamics as a function of global recurrent strength () for the original human connectome and human connectome obtained from the Human Connectome Project (HCP). (B) Violin plot …
Figure 3—figure supplement 8
Replication of human and chimpanzee neural dynamics using a different biophysical model (the Wilson-Cowan model).
(A) Exemplar connectome and schematic diagram of the Wilson-Cowan model. In this biophysical model, each brain region comprises interacting populations of excitatory () and inhibitory () …
Figure 3—figure supplement 9
Gradient of dynamic ranges and regional chimpanzee-to-human cortical expansion along the anterior-posterior axis.
(A) Relationship between a brain region’s dynamic range and its anterior-posterior location. The dynamic range values are transformed to z scores. The solid line represents a linear fit with …
Figure 3—figure supplement 10
Anatomical locations of regions clustered according to seven canonical brain networks.
VIS = Visual; SM = Somatomotor; DA = Dorsal Attention; VA = Ventral Attention; LIM = Limbic; FP = Frontoparietal; DM = Default Mode. These functional networks are mapped onto the 114-region atlas in …
Figure 4
Association of the human and chimpanzee connectomes’ path length and dynamic range.
Average regional path length as a function of z-score-transformed dynamic ranges. is the Spearman rank correlation and p is the p value.
Figure 5 with 1 supplement
Neural dynamics of human and non-human primates.
(A) Regional neural dynamics as a function of global recurrent strength () for human, chimpanzee, macaque, and marmoset. (B) Violin plot of the distribution of dynamic ranges across brain regions. …
Figure 5—figure supplement 1
Replication of macaque neural dynamics on an independent dataset (CoCoMac).
(A) Regional neural dynamics as a function of global recurrent strength (). (B) Violin plot of the distribution of dynamic ranges across brain regions. The violin shows the first to third quartile …
Figure 6 with 4 supplements
Human and chimpanzee neural timescales and connectome decision-making capacity.
(A) Ranked neural timescales as a function of ranked dynamic ranges. The solid line represents a linear fit with Pearson’s correlation coefficient (r) and p value (p). (B) Exemplar connectome and …
Figure 6—figure supplement 1
Method for calculating neural timescales.
(Left) Sample regional neural activity. (Right) Autocorrelation of the data (neural activity) as a function of time lag (solid line) and corresponding exponential fit (dashed line) from which the …
Figure 6—figure supplement 2
Macaque and marmoset neural timescales and their connectome’s decision-making capacity.
(A) Ranked neural timescales as a function of ranked dynamic ranges (similar to Figure 6A). The solid line represents a linear fit with Pearson’s correlation coefficient (r) and p value (p). (B) …
Figure 6—figure supplement 3
Effects of excitation and inhibition on decision-making capacity of the human and chimpanzee connectomes.
(A) Extended drift-diffusion model, which includes a parameter that scales the self-coupling term. corresponds to our original drift-diffusion model, corresponds to increased excitation, …
Figure 6—figure supplement 4
Difference in Default-Mode Network (DMN) accuracy across time between humans and chimpanzees.
The DMN regions are visualized on inflated human cortical surfaces.
Figure 7
Testing of model predictions on T1w:T2w data.
(A) T1w:T2w maps visualized on inflated cortical surfaces. Light color represents high T1w:T2w value (high myelination) and dark color represents low T1w:T2w value (low myelination). (B) Regional …
Figure 8
Testing of model predictions on functional neuroimaging data.
(A) Functional connectivity () within large-scale networks and across the whole brain of humans and macaques. The human large-scale networks are similar to those defined in Figure 3D. The macaque …
Additional files
-
MDAR checklist
- https://cdn.elifesciences.org/articles/80627/elife-80627-mdarchecklist1-v2.docx
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Supplementary file 1
Table listing the names of 57 cortical regions in each hemisphere.
- https://cdn.elifesciences.org/articles/80627/elife-80627-supp1-v2.docx
