This paper aims to frame certain fundamental aspects of the human mind (content and meaning of mental states) and foundational elements of brain computation (spatial and temporal patterns of neural activity) so as to enable at least in principle their integration within one and the same quantitative representation. Through the history of science, similar approaches have been instrumental to bridge other seemingly mysterious scientific phenomena, such as thermodynamics and statistical mechanics, optics and electromagnetism, or chemistry and quantum physics, among several other examples. Identifying the relevant levels of analysis is important to define proper mathematical formalisms for describing the brain and the mind, such that they could be mapped onto each other in order to explain their equivalence. Based on these premises, we overview the potential of neural connectivity to provide highly informative constraints on brain computational process. Moreover, we outline approaches for representing cognitive and emotional states geometrically with semantic maps. Next, we summarize leading theoretical framework that might serve as an explanatory bridge between neural connectivity and mental space. Furthermore, we discuss the implications of this framework for human communication and our view of reality. We conclude by analyzing the practical requirements to manage the necessary data for solving the mind-brain problem from this perspective. 1. Introduction The relationship between mind and matter has been a fundamental topic of investigation in many if not all cultures and traditions since the most ancient records of human thought, from the Hindu orthodox school of Sankhya nearly 27 centuries ago [1] to the classic Greek philosophy of Plato (e.g., in the dialogue Phaedo) 300 years later [2]. With few exceptions (most noticeably that of panpsychism: [3]) most theories of the mind throughout history related it to the body and its various parts, including the heart in Aristotle’s view [4] and the endocrine pineal gland in the work of Descartes [5]. Early physicians Hippocrates [6] and Galen [7] were among the first influential proponents of the central role of the brain in the operation of the mind based on anatomical and physiological observations. The development of modern neuroscience led to the (still ongoing) accumulation of massive evidence that irreversibly linked the mind to the brain [8]. The goal of this spotlight paper is emphatically not to provide an extensive review or even a balanced perspective of the enormous body of work on the brain-mind
References
[1]
S. G. Weerasinghe, The Sankhya Philosophy; A Critical Evaluation of Its Origins and Development, South Asia Books, New Delhi, India, 1993.
[2]
B. Jowett, The Dialogues of Plato Translated into English with Analyses and Introductions in Five Volumes, Oxford University Press, 3rd edition, 1892, Chapter: PHAEDO, http://oll.libertyfund.org/title/766/93700.
[3]
W. Seager and S. Allen-Hermanson, “Panpsychism,” in The Stanford Encyclopedia of Philosophy, E. N. Zalta, Ed., 2012, http://plato.stanford.edu/archives/spr2012/entries/panpsychism.
[4]
M. Shuttleworth, “Aristotle’s Psychology,” Experiment Resources, 2012, http://www.experiment-resources.com/aristotles-psychology.html.
[5]
G. J. C. Lokhorst and T. T. Kaitaro, “The originality of Descartes' theory about the pineal gland,” Journal of the History of the Neurosciences, vol. 10, no. 1, pp. 6–18, 2001.
[6]
F. Adams, “Translation of Hippocrates’ “On the Sacred Disease” (University of Adelaide Library, retrieved from Internet Classics Archive,” 2006, http://web.archive.org/web/20070926213032/, http://etext.library.adelaide.edu.au/mirror/classics.mit.edu/Hippocrates/sacred.html.
[7]
V. Nutton, Galen of Pergamum (Encyclop？dia Britannica), 2012, http://www.britannica.com/EBchecked/topic/223895/Galen-of-Pergamum.
[8]
E. R. Kandel and L. R. Squire, “Neuroscience: breaking down scientific barriers to the study of brain and mind,” Science, vol. 290, no. 5494, pp. 1113–1120, 2000.
[9]
D. J. Chalmers and D. Bourget, “Consciousness and Neuroscience. In Online Papers on Consciousness,” 2009, http://consc.net/online/8.1.
[10]
A. Zeman, “Consciousness,” Brain, vol. 124, no. 7, pp. 1263–1289, 2001.
[11]
G. A. Ascoli and J. Grafman, Eds., Consciousness, Mind and Brain, Massom Publisher, Milan, Italy, 2005.
[12]
G. A. Ascoli, “Brain and mind at the crossroad of time,” Cortex, vol. 41, no. 5, pp. 619–620, 2005.
[13]
J. A. Hobson, “REM sleep and dreaming: towards a theory of protoconsciousness,” Nature Reviews Neuroscience, vol. 10, no. 11, pp. 803–814, 2009.
[14]
D. Kahn and T. Gover, “Consciousness in dreams,” International Review of Neurobiology, vol. 92, pp. 181–195, 2010.
[15]
R. E. Brown, R. Basheer, J. T. McKenna, R. E. Strecker, and R. W. McCarley, “Control of sleep and wakefulness,” Physiological Reviews, vol. 92, no. 3, pp. 1087–1187, 2012.
[16]
A. V. Samsonovich and G. A. Ascoli, “The conscious self: ontology, epistemology and the mirror quest,” Cortex, vol. 41, no. 5, pp. 621–636, 2005.
[17]
J. G. Taylor, “Mind and consciousness: towards a final answer?” Physics of Life Reviews, vol. 2, no. 1, pp. 1–45, 2005.
[18]
J. H. Reynolds and R. Desimone, “The role of neural mechanisms of attention in solving the binding problem,” Neuron, vol. 24, no. 1, pp. 19–29, 1999.
[19]
J. J. Van Boxtel, N. Tsuchiya, and C. Koch, “Consciousness and attention: on sufficiency and necessity,” Frontiers in Psychology, vol. 1, article 217, 2010.
[20]
T. Nagel, “What is it like to be a bat?” The Philosophical Review, vol. 83, no. 4, pp. 435–450, 1974.
[21]
A. Gierer, “Brain, mind and limitations of a scientific theory of human consciousness,” BioEssays, vol. 30, no. 5, pp. 499–505, 2008.
[22]
N. Block, “Consciousness, accessibility, and the mesh between psychology and neuroscience,” Behavioral and Brain Sciences, vol. 30, no. 5-6, pp. 481–548, 2007.
[23]
O. J. Hulme, K. F. Friston, and S. Zeki, “Neural correlates of stimulus reportability,” Journal of Cognitive Neuroscience, vol. 21, no. 8, pp. 1602–1610, 2009.
[24]
B. Peeters, “Language and the mind. On concepts and values,” Pragmatics and Cognition, vol. 4, pp. 139–152, 1996.
[25]
A. B. Butler, “Hallmarks of consciousness,” Advances in Experimental Medicine and Biology, vol. 739, pp. 291–309, 2012.
[26]
R. P. Behrendt, “Contribution of hippocampal region CA3 to consciousness and schizophrenic hallucinations,” Neuroscience and Biobehavioral Reviews, vol. 34, no. 8, pp. 1121–1136, 2010.
[27]
L. De Gennaro, C. Marzano, C. Cipolli, and M. Ferrara, “How we remember the stuff that dreams are made of: neurobiological approaches to the brain mechanisms of dream recall,” Behavioural Brain Research, vol. 226, no. 2, pp. 592–596, 2012.
[28]
G. Tononi and G. M. Edelman, “Consciousness and complexity,” Science, vol. 282, no. 5395, pp. 1846–1851, 1998.
[29]
A. Cleeremans, “Computational correlates of consciousness,” Progress in Brain Research, vol. 150, pp. 81–98, 2005.
[30]
V. G. Hardcastle, “Consciousness and the neurobiology of perceptual binding,” Seminars in Neurology, vol. 17, no. 2, pp. 163–170, 1997.
[31]
J. Aru, N. Axmacher, A. T. Do Lam et al., “Local category-specific gamma band responses in the visual cortex do not reflect conscious perception,” The Journal of Neuroscience, vol. 32, pp. 14909–14914, 2012.
[32]
R. Q. Quiroga, “Concept cells: the building blocks of declarative memory functions,” Nature Reviews Neuroscience, vol. 13, no. 8, pp. 587–597, 2012.
[33]
V. A. F. Lamme, “Towards a true neural stance on consciousness,” Trends in Cognitive Sciences, vol. 10, no. 11, pp. 494–501, 2006.
[34]
B. Libet, “Reflections on the interaction of the mind and brain,” Progress in Neurobiology, vol. 78, no. 3–5, pp. 322–326, 2006.
[35]
G. Hesslow, “Will neuroscience explain consciousness?” Journal of Theoretical Biology, vol. 171, no. 1, pp. 29–39, 1994.
[36]
C. Mcginn, “Can we solve the mind-body problem?” Mind, vol. 98, no. 391, pp. 349–366, 1989.
[37]
J. R. Searle, “How to study consciousness scientifically,” Philosophical Transactions of the Royal Society B, vol. 353, no. 1377, pp. 1935–1942, 1998.
[38]
G. A. Ascoli, “Is it already time to give up on a science of consciousness? A commentary on mysterianism,” Complexity, vol. 5, no. 1, pp. 25–34, 1999.
[39]
I. Newton, “Philosophi？ Naturalis Principia Mathematica,” 1687, English translation by A. Motte 1729, http://en.wikisource.org/wiki/The_Mathematical_Principles_of_Natural_Philosophy.
[40]
M. Clavelin, The Natural Philosophy of Galileo, MIT Press, Cambridge, Mass, USA, 1974.
[41]
S. Carnot, Réflexions Sur la Puissance Motrice du Feu et Sur les Machines Propres à Développer cette Puissance, Bachelier, Paris, France, 1824, English translation of R. Thurston, 1890, http://books.google.com/books?id=tgdJAAAAIAAJ.
[42]
D. Cardwell, From Watt to Clausius: The Rise of Thermodynamics in the Early Industrial Age, Cornell University Press, Ithaca, NY, USA, 1971.
[43]
R. Brown, “A brief account of microscopical observations made in the months of June, July and August, 1827, on the particles contained in the pollen of plants; and on the general existence of active molecules in organic and inorganic bodies,” Philosophical Magazine, vol. 4, pp. 161–173, 1828.
[44]
D. Bernoulli, “Hydrodynamica, sive De viribus et motibus fluidorum commentarii,” 1738, http://echo.mpiwg-berlin.mpg.de/ECHOdocuViewfull?mode=imagepath&url=/mpiwg/online/permanent/library/AZ870BWE/pageimg&viewMode=images.
[45]
A. Einstein, Investigations on the Theory of Brownian Movement, Dover, New York, NY, USA, 1956.
[46]
G. A. Ascoli, “From data to knowledge,” Neuroinformatics, vol. 1, no. 2, pp. 145–147, 2003.
[47]
J. T. Vogelstein, R. J. Vogelstein, and C. E. Priebe, “Are mental properties supervenient on brain properties?” Scientific Reports, vol. 1, article 100, 2011.
[48]
M. Allen and G. Williams, “Consciousness, plasticity, and connectomics: the role of intersubjectivity in human cognition,” Frontiers in Psychology, vol. 2, article 20, 2011.
[49]
G. A. Silva, “The need for the emergence of mathematical neuroscience: beyond computation and simulation,” Frontiers in Computational Neuroscience, vol. 5, article 51, 2011.
[50]
W. Gerstner, H. Sprekeler, and G. Deco, “Theory and simulation in neuroscience,” Science, vol. 338, no. 6103, pp. 60–65, 2012.
[51]
G. O’Brien and J. Opie, “A connectionist theory of phenomenal experience,” Behavioral and Brain Sciences, vol. 22, no. 1, pp. 127–148, 1999.
[52]
G. Leisman and P. Koch, “Networks of conscious experience: computational neuroscience in understanding life, death, and consciousness,” Reviews in the Neurosciences, vol. 20, no. 3-4, pp. 151–176, 2009.
[53]
G. Buzsáki, “The structure of consciousness,” Nature, vol. 446, no. 7133, article 267, 2007.
[54]
O. Sporns, G. Tononi, and G. M. Edelman, “Connectivity and complexity: the relationship between neuroanatomy and brain dynamics,” Neural Networks, vol. 13, no. 8-9, pp. 909–922, 2000.
[55]
G. A. Ascoli, “The complex link between neuroanatomy and consciousness,” Complexity, vol. 6, pp. 20–26, 2000.
[56]
S. Herculano-Houzel, “The human brain in numbers: a linearly scaled-up primate brain,” Frontiers in Human Neuroscience, vol. 3, article 31, 2009.
[57]
R. J. Douglas and K. A. Martin, “Mapping the matrix: the ways of neocortex,” Neuron, vol. 56, no. 2, pp. 226–238, 2007.
[58]
C. C. King, “Fractal and chaotic dynamics in nervous systems,” Progress in Neurobiology, vol. 36, no. 4, pp. 279–308, 1991.
[59]
P. So, J. T. Francis, T. I. Netoff, B. J. Gluckman, and S. J. Schiff, “Periodic orbits: a new language for neuronal dynamics,” Biophysical Journal, vol. 74, no. 6, pp. 2776–2785, 1998.
[60]
A. A. Fingelkurts and A. A. Fingelkurts, “Making complexity simpler: multivariability and metastability in the brain,” International Journal of Neuroscience, vol. 114, no. 7, pp. 843–862, 2004.
[61]
S. Roy and R. Llinás, “Dynamic geometry, brain function modeling, and consciousness,” Progress in Brain Research, vol. 168, pp. 133–144, 2008.
[62]
G. Buzsáki, Rhythms of the Brain, Oxford University Press, Oxford, UK, 2006.
[63]
T. Klausberger and P. Somogyi, “Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations,” Science, vol. 321, no. 5885, pp. 53–57, 2008.
[64]
O. Sporns, Networks of the Brain, The MIT Press, Cambridge, Mass, USA, 2011.
[65]
O. Sporns, G. Tononi, and R. K？tter, “The human connectome: a structural description of the human brain,” PLoS Computational Biology, vol. 1, no. 4, article e42, 2005.
[66]
J. W. Lichtman, J. Livet, and J. R. Sanes, “A technicolour approach to the connectome,” Nature Reviews. Neuroscience, vol. 9, no. 6, pp. 417–422, 2008.
[67]
J. Kim, T. Zhao, R. S. Petralia, et al., “mGRASP enables mapping mammalian synaptic connectivity with light microscopy,” Nature Methods, vol. 9, no. 1, pp. 96–102, 2011.
[68]
J. DeFelipe, “From the connectome to the synaptome: an epic love story,” Science, vol. 330, no. 6008, pp. 1198–1201, 2010.
[69]
J. Lu, “Neuronal tracing for connectomic studies,” Neuroinformatics, vol. 9, no. 2-3, pp. 159–166, 2011.
[70]
N. Kasthuri and J. W. Lichtman, “The rise of the “projectome”,” Nature Methods, vol. 4, no. 4, pp. 307–308, 2007.
[71]
G. A. Ascoli, “Potential connectomics complements the endeavour of “no synapse left behind” in the cortex,” Journal of Physiology, vol. 590, no. 4, pp. 651–652, 2012.
[72]
S. L. Hill, Y. Wang, I. Riachi, F. Schürmann, and H. Markram, “Statistical connectivity provides a sufficient foundation for specific functional connectivity in neocortical neural microcircuits,” Proceedings of the National Academy of Sciences of the United States of America, vol. 109, no. 42, pp. E2885–E2894, 2012.
[73]
A. M. Packer, D. J. McConnell, E. Fino, and R. Yuste, “Axo-dendritic overlap and laminar projection can explain interneuron connectivity to pyramidal cells,” Cereb Cortex, 2012.
[74]
D. Kleinfeld, A. Bharioke, P. Blinder, et al., “Large-scale automated histology in the pursuit of connectomes,” Journal of Neuroscience, vol. 31, no. 45, pp. 16125–16138, 2011.
[75]
M. Helmstaedter and P. P. Mitra, “Computational methods and challenges for large-scale circuit mapping,” Current Opinion in Neurobiology, vol. 22, no. 1, pp. 162–169, 2012.
[76]
O. Sporns, “The human connectome: a complex network,” Annals of the New York Academy of Sciences, vol. 1224, pp. 109–125, 2011.
[77]
J. Sepulcre, M. R. Sabuncu, and K. A. Johnson, “Network assemblies in the functional brain,” Current Opinion in Neurology, vol. 25, no. 4, pp. 384–391, 2012.
[78]
A. W. Toga, K. A. Clark, P. M. Thompson, D. W. Shattuck, and J. D. Van Horn, “Mapping the human connectome,” Neurosurgery, vol. 71, no. 1, pp. 1–5, 2012.
[79]
D. C. Van Essen, K. Ugurbil, E. Auerbach, et al., “The human connectome project: a data acquisition perspective,” Neuroimage, vol. 62, no. 4, pp. 2222–2231, 2012.
[80]
B. B. Biswal, M. Mennes, X. N. Zuo et al., “Toward discovery science of human brain function,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 10, pp. 4734–4739, 2010.
[81]
D. N. Kennedy, “Making connections in the connectome era,” Neuroinformatics, vol. 8, no. 2, pp. 61–62, 2010.
[82]
J. W. Bohland, C. Wu, H. Barbas et al., “A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale,” PLoS Computational Biology, vol. 5, no. 3, Article ID e1000334, 2009.
[83]
A. S. Chiang, C. Y. Lin, C. C. Chuang et al., “Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution,” Current Biology, vol. 21, no. 1, pp. 1–11, 2011.
[84]
A. M. Zador, J. Dubnau, H. K. Oyibo, H. Zhan, G. Cao, and I. D. Peikon, “Sequencing the connectome,” PLoS Biology, vol. 10, no. 10, Article ID e1001411, 2012.
[85]
E. T. Bullmore and D. S. Bassett, “Brain graphs: graphical models of the human brain connectome,” Annual Review of Clinical Psychology, vol. 7, pp. 113–140, 2011.
[86]
M. Kaiser, “A tutorial in connectome analysis: topological and spatial features of brain networks,” NeuroImage, vol. 57, no. 3, pp. 892–907, 2011.
[87]
P. Erd？s and A. Rényi, “On random graphs,” Publicationes Mathematica, vol. 6, pp. 290–297, 1959.
[88]
D. J. Watts and S. H. Strogatz, “Collective dynamics of “small-world” networks,” Nature, vol. 393, pp. 440–442, 1998.
[89]
A. L. Barabási and R. Albert, “Emergence of scaling in random networks,” Science, vol. 286, pp. 509–512, 1999.
[90]
R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, and U. Alon, “Network motifs: simple building blocks of complex networks,” Science, vol. 298, no. 5594, pp. 824–827, 2002.
[91]
O. Sporns and J. D. Zwi, “The small world of the cerebral cortex,” Neuroinformatics, vol. 2, no. 2, pp. 145–162, 2004.
[92]
S. Song, P. J. Sj？str？m, M. Reigl, S. Nelson, and D. B. Chklovskii, “Highly nonrandom features of synaptic connectivity in local cortical circuits,” PLoS Biology, vol. 3, no. 10, article e350, 2005.
[93]
W. J. Freeman and M. Breakspear, “Scale-free neocortical dynamics,” Scholarpedia, vol. 2, article 1357, 2007.
[94]
B. J. Prettejohn, M. J. Berryman, and M. D. McDonnell, “Methods for generating complex networks with selected structural properties for simulations: a review and tutorial for neuroscientists,” Frontiers in Computational Neuroscience, vol. 5, article 11, 2011.
[95]
M. A. Porter, J. P. Onnela, and P. J. Mucha, “Communities in networks,” Notices of the American Mathematical Society, vol. 56, no. 9, pp. 1082–1097, 2009.
[96]
M. P. van den Heuvel and O. Sporns, “Rich-club organization of the human connectome,” Journal of Neuroscience, vol. 31, no. 44, pp. 15775–15786, 2011.
[97]
M. Rivera-Alba, S. N. Vitaladevuni, Y. Mishchenko, et al., “Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain,” Current Biology, vol. 21, no. 23, pp. 2000–2005, 2011, Erratum in: Current Biology, vol. 22, no. 2, article 172, 2012.
[98]
E. Bullmore and O. Sporns, “The economy of brain network organization,” Nature Reviews Neuroscience, vol. 13, no. 5, pp. 336–349, 2012.
[99]
C. Assisi, M. Stopfer, and M. Bazhenov, “Using the structure of inhibitory networks to unravel mechanisms of spatiotemporal patterning,” Neuron, vol. 69, no. 2, pp. 373–386, 2011.
[100]
L. da Fontoura Costa, J. L. Batista, and G. A. Ascoli, “Communication structure of cortical networks,” Frontiers in Computational Neuroscience, vol. 5, article 6, 2011.
[101]
G. A. Ascoli, L. Alonso-Nanclares, S. A. Anderson et al., “Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex,” Nature Reviews Neuroscience, vol. 9, no. 7, pp. 557–568, 2008.
[102]
D. E. Fishkind, D. L. Sussman, M. Tang, J. T. Vogelstein, and C. E. Priebe, “Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown,” SIAM Journal on Matrix Analysis and Applications, 2012.
[103]
C. E. Priebe, J. T. Vogelstein, and D. Bock, “Optimizing the quantity/quality trade-off in connectome inference,” Communications in Statistics, 2011.
[104]
J. Lu, J. C. Tapia, O. L. White, and J. W. Lichtman, “The interscutularis muscle connectome,” PLoS Biology, vol. 7, no. 2, article e32, 2009.
[105]
C. Kelly, B. B. Biswal, R. C. Craddock, F. X. Castellanos, and M. P. Milham, “Characterizing variation in the functional connectome: promise and pitfalls,” Trends in Cognitive Sciences, vol. 16, no. 3, pp. 181–188, 2012.
[106]
V. De Paola, A. Holtmaat, G. Knott et al., “Cell type-specific structural plasticity of axonal branches and boutons in the adult neocortex,” Neuron, vol. 49, no. 6, pp. 861–875, 2006.
[107]
M. Park, J. M. Salgado, L. Ostroff et al., “Plasticity-induced growth of dendritic spines by exocytic trafficking from recycling endosomes,” Neuron, vol. 52, no. 5, pp. 817–830, 2006.
[108]
K. M. Harris, “Structure, development, and plasticity of dendritic spines,” Current Opinion in Neurobiology, vol. 9, no. 3, pp. 343–348, 1999.
[109]
N. Gogolla, I. Galimberti, and P. Caroni, “Structural plasticity of axon terminals in the adult,” Current Opinion in Neurobiology, vol. 17, no. 5, pp. 516–524, 2007.
[110]
A. Holtmaat and K. Svoboda, “Experience-dependent structural synaptic plasticity in the mammalian brain,” Nature Reviews Neuroscience, vol. 10, no. 9, pp. 647–658, 2009, Erratum in: Nature Reviews Neuroscience, vo. 10, no. 10, article 759, 2009.
[111]
M. Fu and Y. Zuo, “Experience-dependent structural plasticity in the cortex,” Trends in Neurosciences, vol. 34, no. 4, pp. 177–187, 2011.
[112]
E. Bruel-Jungerman, S. Davis, and S. Laroche, “Brain plasticity mechanisms and memory: a party of four,” Neuroscientist, vol. 13, no. 5, pp. 492–505, 2007.
[113]
D. B. Chklovskii, B. W. Mel, and K. Svoboda, “Cortical rewiring and information storage,” Nature, vol. 431, no. 7010, pp. 782–788, 2004.
[114]
S. Fusi, P. J. Drew, and L. F. Abbott, “Cascade models of synaptically stored memories,” Neuron, vol. 45, no. 4, pp. 599–611, 2005.
[115]
C. Kahn, The Art and Thought of Heraclitus: Fragments with Translation and Commentary, Cambridge University Press, London, UK, 1979.
[116]
G. A. Ascoli and A. V. Samsonovich, “Science of the conscious mind,” Biological Bulletin, vol. 215, no. 3, pp. 204–215, 2008.
[117]
T. K. Landauer and S. T. Dumais, “A solution to Plato's problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge,” Psychological Review, vol. 104, no. 2, pp. 211–240, 1997.
[118]
C. H. Papadimitriou, P. Raghavan, H. Tamaki, and S. Vempala, “Latent semantic indexing: a probabilistic analysis,” Journal of Computer and System Sciences, vol. 61, no. 2, pp. 217–235, 2000.
[119]
D. M. Blei, A. Y. Ng, and M. I. Jordan, “Latent Dirichlet allocation,” Journal of Machine Learning Research, vol. 3, no. 4-5, pp. 993–1022, 2003.
[120]
C. Burgess and K. Lund, “Modelling parsing constraints with high-dimensional context space,” Language and Cognitive Processes, vol. 12, no. 2-3, pp. 177–210, 1997.
[121]
T. K. Landauer, D. S. McNamara, S. Dennis, and W. Kintsch, Eds., Handbook of Latent Semantic Analysis, Lawrence Erlbaum Associates, Mahwah, NJ, USA, 2007.
[122]
C. E. Osgood, G. Suci, and P. Tannenbaum, The Measurement of Meaning, University of Illinois Press, Urbana, Ill, USA, 1957.
[123]
D. C. Rubin, “51 properties of 125 words: a unit analysis of verbal behavior,” Journal of Verbal Learning and Verbal Behavior, vol. 19, no. 6, pp. 736–755, 1980.
[124]
P. Roget, “Roget’s Thesaurus of English words and phrases,” 1852, http://www.roget.org.
[125]
C. Fellbaum, WordNet: An Electronic Lexical Database, MIT Press, Cambridge, Mass, USA, 1998.
[126]
T. Gruber, “Ontology,” in Encyclopedia of Database Systems, L. Liu and M. Tamer ？zsu, Eds., Springer, 2009, http://tomgruber.org/writing/ontology-definition-2007.htm.
[127]
A. V. Samsonovic and G. A. Ascoli, “Principal semantic components of language and the measurement of meaning,” PloS ONE, vol. 5, no. 6, Article ID e10921, 2010.
[128]
A. V. Samsonovich, R. F. Goldin, and G. A. Ascoli, “Toward a semantic general theory of everything,” Complexity, vol. 15, no. 4, pp. 12–18, 2010.
[129]
H. L？vheim, “A new three-dimensional model for emotions and monoamine neurotransmitters,” Medical Hypotheses, vol. 78, no. 2, pp. 341–348, 2012.
[130]
G. Kemerling, “Aristotle: logical methods,” in The Philosophy Pages, 2011, http://www.philosophypages.com/hy/2n.htm.
[131]
A. V. Samsonovich and G. A. Ascoli, “Augmenting weak semantic cognitive maps with an “abstractness” dimension,” Computational Intelligence and Neuroscience, 2013.
[132]
G. Recchia and M. N. Jones, “The semantic richness of abstract concepts,” Frontiers in Human Neuroscience, vol. 6, article 315, 2012.
[133]
J. A. Wheeler, “Information, physics, quantum: the search for links. Ch. 19,” in Complexity, Entropy, and the Physics of Information, W. Zurek, Ed., Addison-Wesley, Redwood City, Calif, USA, 1990.
[134]
G. A. Ascoli, “Association, abstraction, and the emergence of the self,” Noetic Journal, vol. 2, pp. 9–20, 1999.
[135]
G. A. Ascoli and M. Mainetti, Gated Learning: Much ADO About Background Information. Towards A Science of Consciousness, Stockholm, Sweden, 2011.
[136]
M. Mainetti and G. A. Ascoli, Much ADO about BIG Learning, APS Mtg, Washington, DC, USA, 2011.
[137]
G. Tononi, “Consciousness as integrated information: a provisional manifesto,” Biological Bulletin, vol. 215, no. 3, pp. 216–242, 2008.
[138]
G. Tononi and O. Sporns, “Measuring information integration,” BMC Neuroscience, vol. 4, article 31, 2003.
[139]
D. Balduzzi and G. Tononi, “Integrated information in discrete dynamical systems: motivation and theoretical framework,” PLoS Computational Biology, vol. 4, no. 6, Article ID e1000091, 2008.
[140]
B. J. Baars, “Global workspace theory of consciousness: toward a cognitive neuroscience of human experience,” Progress in Brain Research, vol. 150, pp. 45–53, 2005.
[141]
S. Dehaene and J. P. Changeux, “Experimental and theoretical approaches to conscious processing,” Neuron, vol. 70, no. 2, pp. 200–227, 2011.
[142]
D. Balduzzi and G. Tononi, “Qualia: the geometry of integrated information,” PLoS Computational Biology, vol. 5, no. 8, Article ID e1000462, 2009.
[143]
C. E. Shannon, “A mathematical theory of communication,” The Bell System Technical Journal, vol. 27, pp. 623–656, 1948.
[144]
D. B. Chklovskii, S. Vitaladevuni, and L. K. Scheffer, “Semi-automated reconstruction of neural circuits using electron microscopy,” Current Opinion in Neurobiology, vol. 20, no. 5, pp. 667–675, 2010.
[145]
E. G. Jones, J. M. Stone, and H. J. Karten, “High-resolution digital brain atlases: a Hubble telescope for the brain,” Annals of the New York Academy of Sciences, vol. 1225, no. 1, pp. E147–E159, 2011.
[146]
H. Hama, H. Kurokawa, H. Kawano, et al., “Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain,” Nature Neuroscience, vol. 14, no. 11, pp. 1481–1488, 2011.
[147]
Y. Mishchenko and L. Paninski, “A Bayesian compressed-sensing approach for reconstructing neural connectivity from subsampled anatomical data,” Journal of Computational Neuroscience, vol. 33, no. 2, pp. 371–388, 2012.
[148]
A. Irimia, M. C. Chambers, C. M. Torgerson, and J. D. Horn, “Circular representation of human cortical networks for subject and population-level connectomic visualization,” Neuroimage, vol. 60, no. 2, pp. 1340–1351, 2012.
[149]
R. A. Koene, “Experimental research in whole brain emulation: the need for innovative in vivo measurement techniques,” International Journal of Machine Consciousness, vol. 4, no. 1, pp. 35–65, 2012.
[150]
R. Kurzweil and T. Grossman, “Fantastic voyage: live long enough to live forever. The science behind radical life extension questions and answers,” Studies in Health Technology and Informatics, vol. 149, pp. 187–194, 2009.
[151]
M. J. Hawrylycz, E. S. Lein, A. L. Guillozet-Bongaarts, et al., “An anatomically comprehensive atlas of the adult human brain transcriptome,” Nature, vol. 489, no. 7416, pp. 391–399, 2012.
[152]
G. D. Evrony, X. Cai, E. Lee, et al., “Single-neuron sequencing analysis of l1 retrotransposition and somatic mutation in the human brain,” Cell, vol. 151, no. 3, pp. 483–496, 2012.
[153]
O. Schmitt and P. Eipert, “neuroVIISAS: approaching multiscale simulation of the rat connectome,” Neuroinformatics, vol. 10, no. 3, pp. 243–267, 2012.
[154]
G. A. Ascoli, “The coming of age of the hippocampome,” Neuroinformatics, vol. 8, no. 1, pp. 1–3, 2010.
[155]
K. H. Ambert and A. M. Cohen, “Text-mining and neuroscience,” International Review of Neurobiologys, vol. 103, pp. 109–132, 2012.
[156]
L. French, S. Lane, L. Xu, et al., “Application and evaluation of automated methods to extract neuroanatomical connectivity statements from free text,” Bioinformatics, vol. 28, no. 22, pp. 2963–2970, 2012.
[157]
G. A. Ascoli, “Global neuroscience: distributing the management of brain knowledge worldwide,” Neuroinformatics, vol. 11, no. 1, pp. 1–3, 2013.
[158]
H. Akil, M. E. Martone, and D. C. Van Essen, “Challenges and opportunities in mining neuroscience data,” Science, vol. 331, no. 6018, pp. 708–712, 2011.
[159]
G. A. Ascoli, Ed., Computational Neuroanatomy: Principles and Methods, Springer, Totowa, NJ, USA, 2002.
[160]
M. Djurfeldt, “The connection-set algebra—a novel formalism for the representation of connectivity structure in neuronal network models,” Neuroinformatics, vol. 10, no. 3, pp. 287–304, 2012.
[161]
J. A. Brown, J. D. Rudie, A. Bandrowski, J. D. Van Horn, and S. Y. Bookheimer, “The UCLA multimodal connectivity database: a web-based platform for brain connectivity matrix sharing and analysis,” Frontiers in Neuroinformatics, vol. 6, article 28, 2012.
[162]
G. V. Gkoutos, P. N. Schofield, and R. Hoehndorf, “The neurobehavior ontology: an ontology for annotation and integration of behavior and behavioral phenotypes,” International Review of Neurobiology, vol. 3, pp. 69–87, 2012.
[163]
J. A. Turner and A. R. Laird, “The cognitive paradigm ontology: design and application,” Neuroinformatics, vol. 10, no. 1, pp. 57–66, 2012.
[164]
M. A. Arbib, J. J. Bonaiuto, I. Bornkessel-Schlesewsky et al., “Action and language mechanisms in the brain: data, models and neuroinformatics,” Neuroinformatics, 2013.
[165]
T. E. Feinberg, “Neuroontology, neurobiological naturalism, and consciousness: a challenge to scientific reduction and a solution,” Physics of Life Reviews, vol. 9, no. 1, pp. 13–34, 2012.
