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Building an organic computing device with multiple interconnected brains : Scientific Reports : Nature Publishing Group

Building an organic computing device with multiple interconnected brains : Scientific Reports : Nature Publishing Group | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
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Human-level control through deep reinforcement learning

Human-level control through deep reinforcement learning | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
Nima Dehghani's insight:

full paper:
http://www.nature.com/articles/nature14236.epdf?shared_access_token=GIOrFXxA5wzljOYzWRImAtRgN0jAjWel9jnR3ZoTv0P5kedCCNjz3FJ2FhQCgXkAePdzyjambXhp5LvdzdyyCNg34zh4473TwBocbqMfDjtLMFljQyylqXySHKcB585VHZDGSzYyXk0oiP2Rt2vUAlNIuBitkPUO4IlY9pFoWlfmlzHtdTOkTTI8P5gqa7k56Yxz--Pb0DYy2QuvFpIgyLADMejyqoWJknb-dMcsXFE%3D

 

commentary (behind pay wall): 

http://www.nature.com/nature/journal/v518/n7540/full/518486a.html

 

news:

http://www.bbc.com/news/science-environment-31623427

 

http://www.nature.com/news/game-playing-software-holds-lessons-for-neuroscience-1.16979?WT.mc_id=FBK_NatureNews

 

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"What is life?" Second take, a post-Darwinian hypothesis...Statistical Physics of Adaptation.

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paper:

http://arxiv-web3.library.cornell.edu/abs/1412.1875v1

 

Few months ago, Quanta Magazine released an interesting piece on England's work:

http://www.quantamagazine.org/20140122-a-new-physics-theory-of-life/

 

His talk on the matter in Stockholm:

https://www.youtube.com/watch?v=e91D5UAz-f4

 

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Neural Turing Machines

Neural Turing Machines | Biobit: Computational Neuroscience & Biocomputation | Scoop.it

The capabilities of neural networks were extended by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples.

  
Nima Dehghani's insight:

arXivblog coverage:

http://bit.ly/1DwqIRD ;

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[An Information-Theoretic Formalism for Multiscale Structure in Complex Systems

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Coverage by science news:

https://www.sciencenews.org/blog/context/there’s-new-way-quantify-structure-and-complexity

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Graph analysis of functional brain networks: practical issues in translational neuroscience

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A million spiking-neuron integrated circuit with a scalable communication network and interface

A million spiking-neuron integrated circuit with a scalable communication network and interface | Biobit: Computational Neuroscience & Biocomputation | Scoop.it

IBM Neuromorphic architecture

Nima Dehghani's insight:

Commentary:

http://www.sciencemag.org/content/345/6197/614.short

 

if behind paywall, you can read pop-sci articles about it here:

http://www.wired.com/2014/08/ibm-unveils-a-brain-like-chip-with-4000-processor-cores/

 

http://www.technologyreview.com/news/529691/ibm-chip-processes-data-similar-to-the-way-your-brain-does/?utm_campaign=socialsync&utm_medium=social-post&utm_source=facebook

 

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Algorithms, games, and evolution

Algorithms, games, and evolution | Biobit: Computational Neuroscience & Biocomputation | Scoop.it

the mathematical description of evolution in the presence of sexual recombination and weak selection is equivalent to a repeated game between genes played according to the multiplicative weight updates algorithm

Nima Dehghani's insight:

If you are behind PNAS paywall, you can read Quanta Magazine's commentary:

http://www.simonsfoundation.org/quanta/20140618-the-game-theory-of-life/

 

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First Movie Of An Entire Brain’s Neuronal Activity — The Physics arXiv Blog

First Movie Of An Entire Brain’s Neuronal Activity — The Physics arXiv Blog | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
Neuroscientists have never been able to study the simultaneous activity of neurons in an entire brain. Until now…
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Algorithm Distinguishes Memes from Ordinary Information  — The Physics arXiv Blog

Algorithm Distinguishes Memes from Ordinary Information  — The Physics arXiv Blog | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
Memes are the cultural equivalent of genes: units that transfer ideas or practices from one human to another by means of imitation.
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Consciousness as a State of Matter?

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Consciousness as a State of Matter? but why Tegmark based his calculations on an unproved hypothesis?

 

here is the arXiv blog piece on the story..https://medium.com/the-physics-arxiv-blog/5e7ed624986d

 

and some pop-sci simplification: http://www.extremetech.com/extreme/181284-human-consciousness-is-simply-a-state-of-matter-like-a-solid-or-liquid-but-quantum

 

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Testing Turing’s theory of morphogenesis in chemical cells validated

Testing Turing’s theory of morphogenesis in chemical cells validated | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
Alan Turing, in “The Chemical Basis of Morphogenesis”, described how, incircular arrays of identical biological cells, diffusion can interact with chemical reactions to generate up to six periodic spatiotemporal chemical structures. Turing proposed that one of these structures, a stationary pattern with a chemically determined wavelength, is responsible for differentiation.  Quantitative experimental results obtained using this artificial cellular system establish the strengths and weaknesses of the Turing model, applicable to biology and materials science alike, and pinpoint which directions are required for improvement.
Nima Dehghani's insight:

For those who do not have access to the full paper, they can check a summary here:

http://www.brandeis.edu/now/2014/march/turingpnas.html

http://machineslikeus.com/news/alan-turings-theory-morphogenesis-finally-validated?utm_source=feedburner&utm_medium=twitter&utm_campaign=Feed%3A+MachinesLikeUs+%28Machines+Like+Us+-+Top+Stories%29

 

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Power laws and self-organized criticality in theory and nature

Power laws and self-organized criticality in theory and nature | Biobit: Computational Neuroscience & Biocomputation | Scoop.it

a comparative overview of distinct modeling
approaches together with a discussion of their potential relevance as
generative models for real-world phenomena...A
special section is devoted to an assessment of power-law scaling in the
neural activity.

Nima Dehghani's insight:

 Dimitrije Marković and Claudius Gros argue that:

"Finally, in spite of the evidence that quite different physical systems exhibit dynamical properties akin to the one observed in various sandpile models, there is no convincing proof that the generative mechanism for power-law scaling, as proposed by SOC, constitutes the true causal explanation. A substantial controversy regarding the interpretation of empirical data still persists, and the resolve of this controversy will, together with novel approaches for experimental setups and data analysis, require measurements with higher resolution.

On a final note, what one actually considers a self-organized process is to a certain extent a question of semantics. It is possible, in many circumstances, to tune a system toward a critical point. There is general agreement that the underlying process can be considered self-organized whenever this tuning process occurs through internal drives on time scales shorter than (or comparable to) the experimental time scale. The tuning of internal parameters may however also result from processes acting on much longer time scales, like, for example, Kauffman’s notion of “life at the edge of criticality”, as a consequence of Darwinian selection. In both cases the dynamical state will never be, for real-world systems, exactly at the critical point, but fluctuating around it, albeit on very long time scales."

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Adaptation to sensory input tunes visual cortex to criticality

Adaptation to sensory input tunes visual cortex to criticality | Biobit: Computational Neuroscience & Biocomputation | Scoop.it

 In visual cortex and in a computational model, strong sensory input initially elicits cortical network dynamics that are not critical, but adaptive changes in the network rapidly tune the system to criticality.

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Neuromimetic Circuits with Synaptic Devices Based on Strongly Correlated Electron Systems

Neuromimetic Circuits with Synaptic Devices Based on Strongly Correlated Electron Systems | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
A crucial feature of biological neural architectures is their ability to learn, and unlearn, in response to external stimulation. In this work the authors reproduce this feature in an electronic network composed of strongly correlated electron materials implemented as synaptic devices. This network responds to both excitatory and inhibitory excitations, exhibits associative as well as nonassociative learning, and even displays habituation-like behavior and other aspects of authentic neuronal systems. This opens avenues for both investigating biological behaviors and designing computers with the capacity to learn and remember based on hardware alone.
Nima Dehghani's insight:

http://physics.aps.org/synopsis-for/10.1103/PhysRevApplied.2.064003

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Computational capacity of human neurons: High Bandwidth Synaptic Communication and Frequency Tracking

Computational capacity of human neurons: High Bandwidth Synaptic Communication and Frequency Tracking | Biobit: Computational Neuroscience & Biocomputation | Scoop.it

Data show that, in contrast to the widely held views of limited information transfer in rodent depressing synapses, fast recovering synapses of human neurons can actually transfer substantial amounts of information during spike trains. In addition, human pyramidal neurons are equipped to encode high synaptic information content. Thus, adult human cortical microcircuits relay information at a wider bandwidth than rodent microcircuits..

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Multiscale Balance of Excitation and Inhibition in Single-Unit ensemble Recordings in Human and Monkey Neocortex

Multiscale Balance of Excitation and Inhibition in Single-Unit ensemble Recordings in Human and Monkey Neocortex | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
Nima Dehghani's insight:

new paper out...arXiv link will be added shortly get the pdf here: http://scholar.harvard.edu/nima/publications/multiscale-balance-excitation-and-inhibition-single-unit-ensemble-recordings-human

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Nerve pulse or electromechanical wave? Penetration of Action Potentials During Collision

Nerve pulse or electromechanical wave? Penetration of Action Potentials During Collision | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
Experiments on neuron fibers from earthworms and lobsters reveal that two nerve pulses that collide do not annihilate, contrary to common beliefs of nerve electrophysiology.
Nima Dehghani's insight:

See commentary:

http://physics.aps.org/synopsis-for/10.1103/PhysRevX.4.031047

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Characterizing Autopoiesis in the Game of Lif - Artificial Life

Characterizing Autopoiesis in the Game of Lif  - Artificial Life | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
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Neurosci data deluge: Mapping brain activity at scale with cluster computing

Neurosci data deluge: Mapping brain activity at scale with cluster computing | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
An open-source library of analytical tools for mapping large-scale patterns of brain activity using cluster computing finds structure in two-photon imaging data from mouse and whole-brain light-sheet functional imaging data from behaving larval zebrafish. Vladimirov et al., also online, describes the light-sheet functional imaging system used here.
Nima Dehghani's insight:

With such surge of data, the lack of theory is the Achilles' heel of neuroscience.

 

Can computing keep up with the neuroscience data deluge?

http://spectrum.ieee.org/tech-talk/biomedical/imaging/can-computing-keep-up-with-the-neuroscience-data-deluge

 

Media coverage:

http://www.theguardian.com/science/neurophilosophy/2013/mar/18/an-activity-map-of-the-whole-zebrafish-brain

 

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Self-referencing cellular automata: A model of the evolution of information control in biological systems

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commentary:

https://www.sciencenews.org/blog/context/if-world-computer-life-algorithm

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NSF Distinguished Lecture in Mathematical and Physical Sciences: "Theoretical Physics and the Phenomena of Life: How Much Can We Calculate?

NSF Distinguished Lecture in Mathematical and Physical Sciences: "Theoretical Physics and the Phenomena of Life: How Much Can We Calculate? | Biobit: Computational Neuroscience & Biocomputation | Scoop.it

NSF's mission is to advance the progress of science, a mission accomplished by funding proposals for research and education made by scientists, engineers, and educators from across the country.

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David Deutsch – On Artificial Intelligence

David Deutsch – On Artificial Intelligence | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
The very laws of physics imply that artificial intelligence must be possible. What's holding us up?
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Universal computing by DNA origami robots in a living animal : Nature Nanotechnology : Nature Publishing Group

Universal computing by DNA origami robots in a living animal : Nature Nanotechnology : Nature Publishing Group | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
Nanoscale robots made from DNA origami can dynamically interact with each other and perform logic computations in a living animal.
Nima Dehghani's insight:

if you are behind paywall, see the coverage here:

http://www.newscientist.com/article/dn25376-dna-nanobots-deliver-drugs-in-living-cockroaches.html?utm_source=NSNS&utm_medium=SOC&utm_campaign=twitter&cmpid=SOC%7CNSNS%7C2012-GLOBAL-twitter#.U0bOo9x7Ecv

 

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"Can Neuroscience Help Us Build Better Computer Vision and Machine Learning Systems?"

"Can Neuroscience Help Us Build Better Computer Vision and Machine Learning Systems?" | Biobit: Computational Neuroscience & Biocomputation | Scoop.it
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