Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex

Abstract

Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these two types of neural activity remains unknown. Here we map electromagnetic networks (measured using magnetoencephalography; MEG) to haemodynamic networks (measured using functional magnetic resonance imaging; fMRI). We find that the relationship between the two modalities is regionally heterogeneous and systematically follows the cortical hierarchy, with close correspondence in unimodal cortex and poor correspondence in transmodal cortex, potentially reflecting patterns of laminar differentiation, recurrent subcortical input and neurovascular coupling. Correspondence between the two is largely driven by slower rhythms, particularly the delta (2-4 Hz) and beta (15-29 Hz) frequency band. Moreover, haemodynamic connectivity cannot be explained by electromagnetic activity in a single frequency band, but rather arises from the mixing of multiple neurophysiological rhythms. Collectively, these findings demonstrate highly organized but only partly overlapping patterns of connectivity in MEG and fMRI functional networks, opening fundamentally new avenues for studying the relationship between cortical micro-architecture and multi-modal connectivity patterns.

Adult lifespan trajectories of neuromagnetic signals and interrelations with cortical thickness

“…In general, the correspondence was of moderate effect size ( r s ~0.2-0.5), similar to previous attempts directly linking structural and functional connectivity using MRI (39). This seems plausible given that a mixture of brain rhythms can explain fMRI networks, but with a particular role for the beta band (40, 41). Notably, variation in cortical thickness is arranged along a poster-anterior axis that is thought to have unfolded during neurogenesis and to be related to myelination (13) and genetic components (81).…”

Conserved whole-brain spatiomolecular gradients shape adult brain functional organization

“…In contrast, the fMRI-based functional hierarchy map (Margulies et al, 2016) far better explained the topography of meta-analytic task-related coactivation patterns from the Neurosynth database. This is notable given that electrophysiological and fMRI measure brain activity at different time-scales, overlapping mostly at the high frequency band (Baria et al, 2011; Hermes et al, 2017; Kucyi et al, 2018; Leong et al, 2016; Shafiei et al, 2021). Together, these results suggest that our spatiomolecular gradients and previously described functional gradients probably represent two distinct elements of cortical organization.…”

“…These maps approximate local field potentials from cell populations by detecting electromagnetic cortical activity occurring at multiple wavelengths. This data was measured from 100 individuals as part of the Human Connectome Project (Van Essen et al, 2013), and was processed using the Brainstorm software (Baillet et al, 2011) as previously described (Shafiei et al, 2021). Maps were available for the following canonical frequency bands: alpha (8–12 Hz), beta (15-29 Hz), delta (2-4 Hz), theta (5–7 Hz), low gamma (30-59), high gamma (60-90), as well as intrinsic timescale (Gao et al, 2020; Markello et al, 2022).…”

Task matters: individual MEG signatures from naturalistic and neurophysiological brain states

“…Notably, we find some spatial divergence in the fingerprint patterns relative to fMRI literature. This is not surprising since the nature of brain signals measured by both modalities is quite different, and the relationship between hemodynamic and electrophysiological connectivity in response to task-demands is largely unknown 52 . Note that our work does not directly address the cross-modality difference of connectome fingerprints.…”