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Figure – Brain wave patterns (gamma-waves above 40 Hz). Gamma waves – 40 hz above – these are use for higher mental activity such as for problem solving, consciousness, fear. Beta waves – 13-39 Hz – these are for active thinking and active concentration, paranoia, cognition and arousal. Alpha waves – 7-13 Hz – these are for pre-sleep and pre-wake drowsiness and for relaxation. Theta waves – 4-7 Hz – these are for deep meditation, relaxation, dreams and rapid eye movement (REM) sleep. Delta waves – 4 Hz and below are for loss of body awareness and deep dreamless sleep (source: Medical School, link).

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Video – The Divided Brain (Oct. 2011) – In this new RSAnimate, renowned psychiatrist and writer Iain McGilchrist explains how our ‘divided brain’ has profoundly altered human behaviour, culture and society. Taken from a lecture given by Iain McGilchrist as part of the RSA’s free public events programme. To view the full lecture “The Divided Brain and the Making of the Western World“, do jump yourself into another YouTube video.

Figure – Understanding the Brain as a Computational Network: significant neuronal motifs of size 3.  Most over-represented colored motifs of size 3 in the C. elegans complex neuronal network. Green: sensory neuron; blue: motor neuron; red: interneuron. Arrows represent direction that the signal travels between the two cells. (from Adami et al. 2011 [Ref. below])

Abstract: […] Complex networks can often be decomposed into less complex sub-networks whose structures can give hints about the functional organization of the network as a whole. However, these structural motifs can only tell one part of the functional story because in this analysis each node and edge is treated on an equal footing. In real networks, two motifs that are topologically identical but whose nodes perform very different functions will play very different roles in the network. Here, we combine structural information derived from the topology of the neuronal network of the nematode C. elegans with information about the biological function of these nodes, thus coloring nodes by function. We discover that particular colorations of motifs are significantly more abundant in the worm brain than expected by chance, and have particular computational functions that emphasize the feed-forward structure of information processing in the network, while evading feedback loops. Interneurons are strongly over-represented among the common motifs, supporting the notion that these motifs process and transduce the information from the sensor neurons towards the muscles. Some of the most common motifs identified in the search for significant colored motifs play a crucial role in the system of neurons controlling the worm’s locomotion. The analysis of complex networks in terms of colored motifs combines two independent data sets to generate insight about these networks that cannot be obtained with either data set alone. The method is general and should allow a decomposition of any complex networks into its functional (rather than topological) motifs as long as both wiring and functional information is available. […] from Qian J, Hintze A, Adami C (2011) Colored Motifs Reveal Computational Building Blocks in the C. elegans Brain, PLoS ONE 6(3): e17013. doi:10.1371/journal.pone.0017013

[…] The role of evolution in producing these patterns is clear, said Adami. “Selection favors those motifs that impart high fitness to the organism, and suppresses those that work against the task at hand.” In this way, the efficient and highly functional motifs (such as the sensory neuron-interneuron-motor neuron motif) are very common in the nervous system, while those that would waste energy and give no benefit to, or even harm, the animal are not found in the network. “Adami and his team have used evolutionary computation to develop hypotheses about the evolution of neural circuits and find, for these nematode worms, that simplicity is the rule,” says George Gilchrist, program director in NSF’s Division of Environmental Biology (in the Directorate for Biological Sciences), which funds BEACON. “By including functional information about each node in the circuit, they have begun decoding the role of natural selection in shaping the architecture of neural circuits.” […] from Danielle J. Whittaker “Understanding the Brain as a Computational Network“, NSF, April 2011.

Working in various media including printmaking and film, Susan Aldworth has developed an extensive body of work that explores the nature of human consciousness and identity. Through blending personal and scientific narratives, Aldworth aims to challenge conventional definitions of portraiture through an examination of the internal structure of our brains. From the intricate details of the micro-circuits formed by billions of brain cells, to the output signals that the brain generates and which are recorded through the scanning process and reflect our conscious experience. By its very nature, neuroscience offers a unique bridge between the disciplines of art and science, in its pursuit of understanding human consciousness. Likewise, Aldworth advocates the internal person as a proper subject of portraiture in the light of contemporary neuroscience and the consequent understanding of what it is to be human, and how we articulate these findings via our own creative and expressive means. [text from The Portrait Anatomised, LSE Arts, 2010]

Time-lapse imaging in live zebrafish embryos reveals that cerebellar granule cells migrate in chain-like structures as discovered by a recent article [1] [Köster et al., PLoS, Nov. 2009]. Figure above – Granule cells taken from the cerebellum of a pigeon (above, B) are shown in this 1899 drawing by legendary neuroscientist Santiago Ramón y Cajal.

Did talk about sticky objects and self-organization in the past,  how positive and negative feedback’s  stigmergic-like agents integrated could promote changes and learning over a complex system.  Same happens to bacteria as also ants. On the other hand, we do know memes are also sticky (e.g. Chip Heath, Dan Heath, “Made to Stick: Why Some Ideas Survive and Others Die“, Random House, ISBN 978-1-4000-6428-1, January 2007). What’s new however, is that there are increasing proofs that our own brains my follow similar mechanisms (as Douglas Hofstadter in the past did made some analogies with how brains could work and how ant colonies raid different environments). In this recent new study, Köster and colleagues [1] [PLoS, Nov. 2009] reveal crucial pieces of this puzzle, showing how (neuronal) cells orient themselves to migrate together (like bacteria, above). The team studied zebrafish, one of the workhorses of developmental neurobiology, because its transparent body allows researchers to track movements of cells inside of it. As explained by Mason Inman [2]:

[…] Neurons in the developing brain complete their own self-organized waltz, coordinating with their neighbors to migrate to the right spots to form the cerebellum, visual cortex, or other parts of the brain. In this issue of PLoS Biology, Reinhard Köster and colleagues show that some of these brain cells behave much like slime molds, coordinating with other cells of the same type to migrate in a herd. They found that one particular protein called Cadherin-2 is crucial in allowing the cells to adhere to their neighbors so they can coordinate their movements and all wind up in the right spot. […] Slime molds provide a textbook example of self-organization. They live as single cells until food becomes scarce. Then, they broadcast chemical signals that trigger their mass assembly into a fruiting body, with some cells forming a stalk and others turning into spores that cast about in the winds to spread far and wide. […] Neurons in the developing brain complete their own self-organized waltz, coordinating with their neighbors to migrate to the right spots to form the cerebellum, visual cortex, or other parts of the brain. In this issue of PLoS Biology, Reinhard Köster and colleagues show that some of these brain cells behave much like slime molds, coordinating with other cells of the same type to migrate in a herd. They found that one particular protein called Cadherin-2 is crucial in allowing the cells to adhere to their neighbors so they can coordinate their movements and all wind up in the right spot.[…]

[…] But the mechanisms behind this coordinated movement – in particular, how each cell adjusts its inner workings to move to the right place at the right time – are only now starting to be revealed, using imaging that tracks these cells in live animals as they develop. […] To figure out what triggers the cells to line up and move together, the authors looked at what other kinds of cells were in the neighborhood. Many studies have shown that support cells, known as glial cells, often help guide neurons during these kinds of migrations. But during the first few days of the zebrafish embryo’s development, Köster and colleagues found, there were no glial cells along the granular cells’ migration route. That means these cells must go it alone, the team reasoned, with their own mechanism for signaling between each other to line up into chains and make their move. […] Although the study focused on just one type of brain cell, the findings could explain how many types of neurons find their way to their proper spots as the brain develops. There are still some pieces of the puzzle missing, however. While the findings explain how the granule cells are able to coordinate and follow their neighbors, it’s still not clear how the first few cells to head out on the journey – those at the front of the “conga line” – get oriented in the right direction. This suggests there must be some kind of signal from surrounding cells to get them headed in the right direction, the authors argue – yet another level of organization. […] , in Mason Inman (Nov., 2009) Migrating Brain Cells Stick Together, PloS. [2]

[1] Rieger S, Senghaas N, Walch A, Köster RW (Nov., 2009) Cadherin-2 Controls Directional Chain Migration of Cerebellar Granule Neurons. PLoS Biology.
[2] Mason Inman (Nov., 2009) Migrating Brain Cells Stick Together, PloS Biology.

[...] People should learn how to play Lego with their minds. Concepts are building bricks [...] V. Ramos, 2002.

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