Complexity Thoughts: Issue #6
Unraveling complexity: building knowledge, one paper at a time
Networks and Complex Systems Foundations
Embodiment in distributed information processing: “Solid” plants versus “liquid” ant colonies
How does system wide information arise from local communication?
How does long-distance communication contribute to information integration?
How do environmental feedbacks enhance information integration?
If you look for an answer to any of this questions, you must read this paper. For context, I also recommend a whole special issue about liquid brains edited by Ricard Solé, Melanie Moses and Stephanie Forrest: follow this link!
Network Geometry is used to differentiate phenotypical states in macroscale structural-MRI brain connectomes, suggesting connectomes might have a latent neurobiological geometry accounting for more information than the visible tridimensional Euclidean.
Network Medicine
Genomics and phenomics of body mass index reveals a complex disease network
Obesity (as measured by BMI) is linked to many health problems that can be fatal. Using a genetic risk score including 2,446 variants, obesity was found to increase the risk of 316 different diseases, being connected to a variety of health problems in the circulatory, genitourinary, respiratory, musculoskeletal, and dermatologic systems.
Bio-inspired computing
The authors propose a simple model where the dendrite is implemented as a sequence of thresholded linear units. They manipulate the underlying architecture and investigate the impacts of binary branching constraints and repetition of synaptic inputs on neural computation, finding that models with such manipulations can perform (surprisingly) well on machine learning tasks.
Noise-induced artificial intelligence
The authors conclude that intrinsic stochasticity is probably positively utilized by brains, not only to optimize the signal response but also to induce intelligence itself, and one of the key roles, played by astrocytes in information processing, could be dealing with noises.
Predictive coding is a consequence of energy efficiency in recurrent neural networks
Predictive coding is a promising framework for understanding brain function. It postulates that the brain continuously inhibits predictable sensory input, ensuring preferential processing of surprising elements. A central aspect of this view is its hierarchical connectivity, involving recurrent message passing between excitatory bottom-up signals and inhibitory top-down feedback.
But here the authors show that such architectural hardwiring is not necessary.
Global Systems
The direct drivers of recent global anthropogenic biodiversity loss
What's driving biodiversity loss? At variance w/ what one'd expect, land/sea use change has been the dominant direct driver worldwide. Follow direct exploitation of natural resources, pollution, climate change and invasive alien species.