Social Foraging
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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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The #Neuroscience of Social #Influence | Beautiful Minds

The #Neuroscience of Social #Influence | Beautiful Minds | Social Foraging | Scoop.it
Before I wrote this article, I went through two stages. In the first stage, I cruised the academic journals for interesting papers. Once I found a ...

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luiy's curator insight, December 18, 2014 9:32 AM

Can the pattern of neurons firing in my brain predict how much this article will be retweeted on twitter?

 

A recent study conducted by Emily Falk, Matthew Lieberman, and colleagues gets us closer to answering these important questions. The researchers recruited undergraduate participants and randomly assigned them to two groups: the “interns” and the “producers.” The 20 interns were asked to view ideas for television pilots and provide recommendations to the 79 producers about which shows should be considered for further development and production. All of the interns had their brains scanned by fMRI while they viewed the videos, and they were then videotaped while they discussed the merits of each pilot show idea. The producers rated which ideas they would like to further recommend. How was neural activity related to the spread of ideas?

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Frontiers in Neuroscience: Physical principles for scalable neural recording of the brain

Frontiers in Neuroscience: Physical principles for scalable neural recording of the brain | Social Foraging | Scoop.it

Neuroscience depends on monitoring the electrical activities of neurons within functioning brains (Alivisatos et al., 2012; Bansal et al., 2012; Gerhard et al., 2013) and has advanced through steady improvements in the underlying observational tools. The number of neurons simultaneously recorded using wired electrodes, for example, has doubled every 7 years since the 1950s, currently allowing electrical observation of hundreds of neurons at sub-millisecond timescales (Stevenson and Kording, 2011). Recording techniques have also diversified: activity-dependent optical signals from neurons endowed with fluorescent indicators can be measured by photodetectors, and radio-frequency emissions from excited nuclear spins allow the construction of magnetic resonance images modulated by activity-dependent contrast mechanisms. Ideas for alternative methods have been proposed, including the direct recording of neural activities into information-bearing biopolymers (Kording, 2011; Zamft et al., 2012; Glaser et al., 2013).


Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices.


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Consciousness more complex thought: after anesthesia, brain passes through multiple metastable activity states

Consciousness more complex thought: after anesthesia, brain passes through multiple metastable activity states | Social Foraging | Scoop.it
Research shows that recovery from deep anesthesia is not a smooth, linear process but is instead a dynamic journey with specific states of activity the brain must temporarily occupy on the way to full recovery.

 

"I always found it remarkable that someone can recover from anesthesia, not only that you blink your eyes and can walk around, but you return to being yourself. So if you learned how to do something on Sunday and on Monday, you have surgery, and you wake up and you still know how to do it," says Alexander Proekt, a visiting fellow in Don Pfaff's Laboratory of Neurobiology and Behavior at Rockefeller University and an anesthesiologist at Weill Cornell Medical College. "It seemed like there ought to be some kind of guide or path for the system to follow."

 

The obvious explanation is that as the anesthetic washes out of the body, electrical activity in the brain gradually returns to its conscious patterns. However, new research by Proekt and colleagues suggests the trip back is not so simple.

 

In the awake brain, of both humans and rats, neurons generate electrical voltage that oscillates. Many of these oscillations together form a signal that appears as a squiggly line on a recording of brain activity, such as an LFP. When someone is asleep, under anesthesia, or in a coma, these oscillations occur more slowly, or at a low frequency. When he or she is awake, they speed up. The researchers examined the recordings from the rats' brains to figure out how the electrical activity in these regions changed as they moved from anesthetized to awake.

 

"Recordings from each animal wound up having particular features that spontaneously appeared, suggesting their brain activity was abruptly transitioning through particular states," Hudson says. "We analyzed the probability of a brain jumping from one state to another, and we found that certain states act as hubs through which the brain must pass to continue on its way to consciousness." While the electrical activity in all the rats' brains passed through these hubs, the precise path back to consciousness was not the same each time, the team reports today in the Proceedings of the National Academy of Sciences.

 

Reference:

Andrew E. Hudson, Diany Paol Calderon, Donald W. Pfaff and Alex Proekt.Recovery of consciousness is mediated by a network of discrete metastable activity states. Proceedings of the National Academy of Sciences, June 9, 2014 DOI: 10.1073/pnas.1408296111


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