John M. Beggs
Neuroscience · Indiana University
Publications
110
Citations
8,248
Est. group size
—
Recurring co-author estimate
Active years
42
Publishing since 1984
John M. Beggs studies how networks of neurons process and transmit information, with a particular focus on the idea that the brain operates near a 'critical point'—a delicately balanced state that may optimize how activity spreads. Much of the work uses living neural cultures grown in the lab (in vitro) to record and analyze the collective firing of neurons, including phenomena called 'neuronal avalanches.' The research combines experimental neuroscience with computational and mathematical modeling of network structure and dynamics.
Publication activity peaked around 2020–2022 and has been somewhat lower and variable in the most recent years, averaging about three publications per year over the last five years.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Living Neurosheets: Engineering readily deployable neural architectures
bioRxiv (Cold Spring Harbor Laboratory) · 2025
- Simple model for the prediction of seizure durations
Physical review. E · 2024
- Recurrent activity in neuronal avalanches
Scientific Reports · 2023
- Mind In Vitro Platforms: Versatile, Scalable, Robust, and Open Solutions to Interfacing with Living Neurons
Advanced Science · 2023
- A Literature Review of Similarities Between and Among Patients With Autism Spectrum Disorder and Epilepsy
Cureus · 2023
- ‘Mind <i>in Vitro</i> ’ platforms: Versatile, scalable, robust and open solutions to interfacing with living neurons
bioRxiv (Cold Spring Harbor Laboratory) · 2023
- The Cortex and the Critical Point
The MIT Press eBooks · 2022
- Addressing skepticism of the critical brain hypothesis
Frontiers in Computational Neuroscience · 2022
- Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures
PLoS Computational Biology · 2021
- Model-based detection of putative synaptic connections from spike recordings with latency and type constraints
Journal of Neurophysiology · 2020
- Network structure of cascading neural systems predicts stimulus propagation and recovery
Journal of Neural Engineering · 2020
- Model-based detection of putative synaptic connections from spike recordings with latency and type constraints
bioRxiv (Cold Spring Harbor Laboratory) · 2020
- Correlated activity favors synergistic processing in local cortical networks in vitro at synaptically relevant timescales
Network Neuroscience · 2020
- Synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures
bioRxiv (Cold Spring Harbor Laboratory) · 2020
- Computation is concentrated in rich clubs of local cortical networks
PMC · 2019
- bioRxiv (Cold Spring Harbor Laboratory)×12
- PLoS Computational Biology×3
- Network Neuroscience×3
- arXiv (Cornell University)×3
- Frontiers in Physiology×2
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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