bioRxiv
November 26, 2020
Andrea I. Luppi, Pedro A.M. Mediano, Fernando E. Rosas et al.
49 citations
preprint
The brain coordinates information from many sources to create a unified conscious experience. Combining network science and information theory, the authors identify a “synergistic global workspace” where gateway regions gather synergistic information from specialized brain modules, integrate it, and then broadcast it widely via broadcaster regions. Functional MRI shows that gateway regions correspond to the default mode network and broadcasters to the executive control network. Loss of consciousness from general anesthesia or disorders of consciousness reduces the workspace’s ability to integrate information, which is restored upon recovery. This work reconciles aspects of the Global Neuronal Workspace and Integrated Information Theory.
Pedro A.M. Mediano, Fernando E. Rosas, Andrea I. Luppi et al.
10 citations
A new method called Complexity via State-space Entropy Rate (CSER) estimates neural signal complexity with better temporal resolution and spectral decomposition than the standard Lempel-Ziv complexity (LZ) approach. CSER matches LZ in distinguishing conscious states but offers two key advantages: it can break complexity down by frequency bands, and it provides temporal resolution about 100 times finer. Using MEG, EEG, and ECoG data from humans and monkeys, CSER revealed that gamma-band activity primarily drives complexity changes across states of consciousness. In an auditory mismatch negativity experiment, CSER detected early entropy increases roughly 20 milliseconds before the standard event-related potential. This method enables finer-grained study of how signal complexity relates to cognitive processes and conscious states.
bioRxiv Preprint Server
June 25, 2021
Claudia Pascovich, Santiago Castro-Zaballa, Pedro A.M. Mediano et al.
7 citations
preprint
Neural complexity, measured by the Lempel-Ziv compression algorithm, is lowest during NREM sleep and similar during REM sleep and wakefulness in cats with intracranial electrodes. Under subanesthetic doses of ketamine (5, 10, and 15 mg/kg), complexity follows an inverted U-shaped curve in some electrodes, especially in prefrontal cortex, rising at low doses and falling as doses approach anesthetic levels. Variability in the ketamine dose-response across cats and cortices is larger than sleep-stage differences, revealing distinct local dynamics. These results replicate findings in humans and other species, showing neural complexity is sensitive to conscious state changes and dose-dependent ketamine effects.
bioRxiv
February 1, 2022
Hardik Rajpal, Pedro A.M. Mediano, Fernando E. Rosas et al.
5 citations
preprint
Schizophrenia and drug-induced states from LSD and ketamine both increase neural signal diversity, but they differ in how information flows in the brain. In schizophrenia, transfer entropy from the front to the back of the brain is increased, whereas under both drugs it is reduced overall. These differences can be modeled by altering Bayesian inference within a predictive processing framework: drug effects correspond to reduced precision of prior beliefs, while schizophrenia corresponds to increased precision of sensory information. The findings clarify similarities and differences between these altered states, with potential implications for understanding consciousness and developing mental health treatments.
NeuroImage
February 11, 2023
Andrea I. Luppi, Pedro A.M. Mediano, Fernando E. Rosas et al.
High-level brain functions are thought to arise from coordinated activity across neural systems, but this has been hard to test empirically. Using a framework called Integrated Information Decomposition, which quantifies emergence in dynamical systems, the authors analyzed functional MRI data and found that emergent and hierarchical neural dynamics are significantly reduced in chronically unresponsive patients with severe brain injury. Emergence capacity was positively correlated with hierarchical organization in brain activity. Combining network control theory and whole-brain modeling, the authors show that reduced emergent and hierarchical dynamics in these patients can be explained by disruptions in the structural connectome. The results suggest that chronic unresponsiveness after severe brain injury may stem from structural damage to neural infrastructure needed for emergent brain dynamics.