A graph-computational framework to quantify stimulus-evoked propagation and revealed a control-validated phenomenon, that repeated stimulation reshapes organoid networks is established, but longitudinal designs in which every preparation is stimulated cannot separate this from developmental maturation.
Abstract
Human cortical organoids provide an experimentally accessible model of early neural circuit formation, yet whether their activity reflects structured information processing rather than spontaneous synchronization is unclear. We developed a graph-computational framework to quantify stimulus-evoked propagation. This includes stimulus-conditioned functional graphs, a graph-constrained dynamical (graph-neural-network) model used as a system-identification tool, a biological message-passing principle bounding integration depth by observable propagation depth, and a suite of graph-level metrics. We carried this program out in full on longitudinal HD-MEA recordings from three organoids. Once the true acquisition sampling rate and stimulus timing were recovered, the evoked response proved to be a fast, near-synchronous network burst with no measurable outward propagation (peak-latency vs. distance slope = 0). The propagation/integration-depth metrics (Deff ,reachability index, dmax) therefore do not apply, and per-day connectivity graphs were not reliably estimable at the available trial count, a negative result with methodological consequences for applying such metrics to organoid data. Reframing around synchrony, response-population size and shared variability revealed a control-validated phenomenon, i.e., repeated daily stimulation progressively depressed and spatially contracted the evoked response. That repeated stimulation reshapes organoid networks is established, but longitudinal designs in which every preparation is stimulated cannot separate this from developmental maturation. We break that confound with a developmentally-matched, stimulation-naive control, where at day 7, an organoid receiving its first-ever stimulation engaged 93% of the array, whereas organoids with five prior sessions engaged 10%.
This work presents an analytical pipeline for inferring network-level properties of in vitro cortical cultures from multichannel electrophysiological recordings and proves the validity of the RC-based connectivity inference and establishes a scalable, data-driven framework for functional network characterization in neuronal culture systems.
I. Auslender, G. Letti, Yasaman Heydari et al.· 0 citations
Topological richness grows with network size, and second homology emerges significantly above the null only in the larger networks, and results show that persistent homology resolves structured topology in neural recordings at the scale experiments actually deliver.
Eve Bodnia, M. Basart, S. Hai et al.· bioRxiv· 0 citations
BACKGROUND
High-frequency deep-brain stimulation can reduce seizure burden but imposes a large stimulation load on the tissue, and its effects depend on both frequency and temporal patterning. We tested whether a compact reservoir model could generate a hippocampal-inspired event schedule and whether that schedule could modulate neuronal activity in vitro with fewer nominal pulses than 50-Hz stimulation.
METHODS
A 10-unit leaky reservoir with a one-dimensional affine ridge readout transformed cortical input recordings into CA3-inspired outputs. Retrospective computational validation used paired cortical-CA3 recordings, training-only scaling, removal of at least the first 10 s of every generated trace, date-grouped held-out evaluation, multiple spectral and temporal metrics, objective-function ablation and surrogate signals. One offline biomimetic schedule was then delivered open loop to primary rat cortical cultures on multielectrode arrays and compared with periodic 0.16-Hz and 50-Hz stimulation.
RESULTS
17 of 19 paired recordings passed the pre-specified transient diagnostic. In 11 scorable date-grouped held-out recordings, the reservoir had modestly lower median log-PSD RMSE and autocorrelation error than linear and lagged-ridge baselines. When applied to primary cortical cultures, the primary pooled analysis of all 11 biomimetic-stimulated MEAs yielded a mean firing-rate slope of 0.7655 relative to the null value of 1 (95% CI for the mean slope, 0.491-1.040; p = 0.0865). In separate MEA-level fold-change analyses of all 11 biomimetic-stimulated MEAs, normalized firing rate was 0.8458 and normalized burst rate was 0.7792, both significantly reduced relative to baseline. A post hoc exploratory classification identified reduced firing-rate slopes in 4 of 11 MEAs.
CONCLUSION
These results provide an open-loop in vitro proof of concept that a low-event, irregular stimulation schedule can be associated with heterogeneous modulation of cortical-network activity. Periodic stimulation at the same nominal mean event rate did not produce a statistically significant modulation under the conditions tested. The irregular schedule may contain timing-related properties that contribute to the observed response, but the specific contribution of ESN-derived temporal ordering remains unresolved. Future work should test appropriate temporal controls and evaluate the approach in closed-loop and epilepsy-model experiments.
Ángel Canal-Alonso, Adam Armada-Moreira, Alessio Di Clemente et al.· Brain Stimulation· 0 citations
It is found that the method alone can change the apparent structure of the network as much as real biological differences do, and practical recommendations for parameter selection, reporting, and cross-method validation in MEA-based network neuroscience are provided.
J. Ort, V. Witzig, Aniella Bak et al.· bioRxiv· 0 citations
Directed communication across brain regions is fundamental to human brain function, yet how local spontaneous activity links to directed whole-brain propagation patterns remains elusive. Prior studies have characterized local propagation events and global wave-like dynamics, but a framework linking local events, interregional propagation pathways, and canonical large-scale propagation patterns remains lacking. Using resting-state functional MRI data from the Human Connectome Project 7T cohort and an intrinsic ignition framework, we quantified cascades of suprathreshold activity events and constructed directed propagation probability networks. We found spatially heterogeneous regional propagation preferences, with high outgoing propagation preferences predominantly localized in somatomotor, visual, and default-mode regions. At the functional system level, propagation modules broadly separated visual, somatomotor, dorsal attention, and ventral attention networks from association systems. Regional stepwise propagation pathways were aligned with the principal functional gradient, and greater hierarchical separation between regions was associated with longer propagation distance. These pathways formed two canonical propagation patterns linking primary and association systems, with somatomotor regions preferentially initiated in bottom-up propagation, default-mode regions in top-down propagation, and attention networks occupying intermediate positions. Notably, the two patterns were not simple mirror images, with top-down propagation showing substantial deviations within somatomotor and visual systems. These findings were replicated in an independent cohort. Moreover, individual propagation architecture predicted cognitive performance and tobacco-use behavior. Collectively, our findings provide cross-scale insights into spontaneous activity propagation in the human brain by bridging local ignition events with hierarchical whole-brain propagation pathways and behaviorally relevant individual differences. Significance Spontaneous brain activity is often quantified by the temporal synchronization between regions, but this approach does not show how local activity propagates across the brain. We used an interpretable ignition framework to link local spontaneous events and their cascades to directed whole-brain propagation patterns. This approach revealed outgoing propagation preferences of primary and default-mode regions, a modular architecture separating primary and attentional systems from association systems, and two canonical propagation patterns aligned with the brain’s functional hierarchy. These two patterns were not simple mirror images, indicating partially distinct bottom-up and top-down routes. Individual propagation architecture also predicted cognitive performance and tobacco-use behavior. These findings provide a path-based view of spontaneous brain dynamics.
Jiangling Liu, Xi Chen, Xuhong Liao· bioRxiv· 0 citations
Human cortical activity reflects interactions between local recurrent circuits and distributed brain-wide inputs, but how these contributions shape cortical dynamics remains unclear. We compared oscillatory and single unit activity in laminar recordings from the same human cortical regions in eight patients across wakefulness, NREM sleep, and acute slices after surgical isolation. Gamma-band spike-field synchronization increased from wakefulness to sleep and isolated cortex, whereas population coupling, putative connectivity, network integration, and dynamical dimensionality declined. Laminar gamma sink-source organization persisted in isolation, indicating the presence of local gamma-generating mechanisms. Integration with histological data showed preserved tissue architecture, while neuronal density predicted population integration in vivo but not after isolation. Removing long-range inputs thus did not suppress cortical activity but shifted its organization toward stronger rhythmic coordination and reduced integration. Our findings suggest that neocortical microcircuits intrinsically generate coherent gamma activity, whereas network embedding supports the diverse, high-dimensional dynamics of the intact cortex.
Unknown authors· bioRxiv· 0 citations
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