Quote from Mastodon, Twitter and publics 2017-04-24

Mastodon, Twitter and publics 2017-04-24 by Kevin Marks (kevinmarks.com)
The furore over Fake News is really about the seizures caused by overactivity in these synapses - confabulation and hallucination in the global brain of mutual media. With popularity always following a power law, runaway memetic outbreaks can become endemic, especially when the platform is doing what it can to accelerate them without any sense of their context or meaning.

One might think that Facebook (and others) could easily analyze the things within their network that are getting above average reach and filter out or tamp down the network effects of the most damaging things which in the long run I suspect are going to damage their network overall.

Our synapses have the ability to minimize feedback loops and incoming signals which have deleterious effects–certainly our social networks could (and should) have these features as well.

Syndicated copies to:

Ben Carson Just Got a Whole Lot Wrong About the Brain | Wired

Ben Carson Just Got a Whole Lot Wrong About the Brain by Emily Dreyfuss and Anna Vlasits (Wired)
TODAY, IN HIS first speech to his staff at the Department of Housing and Urban Development, newly minted Secretary Ben Carson delivered an extemporaneous disquisition on the unparalleled marvel that is the human brain and memory. “There is nothing in this universe that even begins to compare with the human brain and what it is capable of,” he began. “Billions and billions of neurons, hundreds of billions of interconnections.” It was a tangent in a speech about how in America, anything is possible.

Continue reading “Ben Carson Just Got a Whole Lot Wrong About the Brain | Wired”

Syndicated copies to:

🔖 The Epidemic Spreading Model and the Direction of Information Flow in Brain Networks

The Epidemic Spreading Model and the Direction of Information Flow in Brain Networks by J. Meier, X. Zhou, A. Hillebrand, P. Tewarie, C.J. Stam, P. Van Mieghem (NeuroImage, February 5, 2017)
The interplay between structural connections and emerging information flow in the human brain remains an open research problem. A recent study observed global patterns of directional information flow in empirical data using the measure of transfer entropy. For higher frequency bands, the overall direction of information flow was from posterior to anterior regions whereas an anterior-to-posterior pattern was observed in lower frequency bands. In this study, we applied a simple Susceptible-Infected-Susceptible (SIS) epidemic spreading model on the human connectome with the aim to reveal the topological properties of the structural network that give rise to these global patterns. We found that direct structural connections induced higher transfer entropy between two brain regions and that transfer entropy decreased with increasing distance between nodes (in terms of hops in the structural network). Applying the SIS model, we were able to confirm the empirically observed opposite information flow patterns and posterior hubs in the structural network seem to play a dominant role in the network dynamics. For small time scales, when these hubs acted as strong receivers of information, the global pattern of information flow was in the posterior-to-anterior direction and in the opposite direction when they were strong senders. Our analysis suggests that these global patterns of directional information flow are the result of an unequal spatial distribution of the structural degree between posterior and anterior regions and their directions seem to be linked to different time scales of the spreading process.
Syndicated copies to: