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Dynamic searching in the brain

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Abstract

Cognitive functions rely on the extensive use of information stored in the brain, and the searching for the relevant information for solving some problem is a very complex task. Human cognition largely uses biological search engines, and we assume that to study cognitive function we need to understand the way these brain search engines work. The approach we favor is to study multi-modular network models, able to solve particular problems that involve searching for information. The building blocks of these multimodular networks are the context dependent memory models we have been using for almost 20 years. These models work by associating an output to the Kronecker product of an input and a context. Input, context and output are vectors that represent cognitive variables. Our models constitute a natural extension of the traditional linear associator. We show that coding the information in vectors that are processed through association matrices, allows for a direct contact between these memory models and some procedures that are now classical in the Information Retrieval field. One essential feature of context-dependent models is that they are based on the thematic packing of information, whereby each context points to a particular set of related concepts. The thematic packing can be extended to multimodular networks involving input-output contexts, in order to accomplish more complex tasks. Contexts act as passwords that elicit the appropriate memory to deal with a query. We also show toy versions of several ‘neuromimetic’ devices that solve cognitive tasks as diverse as decision making or word sense disambiguation. The functioning of these multimodular networks can be described as dynamical systems at the level of cognitive variables.

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References

  • Anderson JA (1972) A simple neural network generating an interactive memory. Math Biosci 14:197–220. doi:10.1016/0025-5564(72)90075-2

    Article  Google Scholar 

  • Ando RK, Lee L (2001) Iterative residual rescaling: an analysis and generalization of LSI. Proceedings of the 24th SIGIR, pp 154-162

  • beim Graben P, Pinotsis D, Saddy D, Potthast R (2008a) Language processing with dynamic fields. Cogn Neurodyn 2:79–88

    Article  PubMed  Google Scholar 

  • beim Graben P, Gerth S, Vasishth S (2008b) Towards dynamical system models of language-related brain potentials. Cogn Neurodyn 2:229–255

    Article  PubMed  Google Scholar 

  • Berry MW, Browne M (2005) Understanding search engines: mathematical modelling and text retrieval, 2nd edn. SIAM, Philadelphia

    Google Scholar 

  • Berry M, Dumais S, O’Brien G (1995) Using linear algebra for intelligent information retrieval. SIAM Rev 37:573–595. doi:10.1137/1037127

    Article  Google Scholar 

  • Blei DM, Ng AY, Jordan MI (2003) Latent Dirichlet allocation. J Mach Learn Res 3:993–1022

    Article  Google Scholar 

  • Christiansen M, Chater N (1999) Toward a connectionist model of recursion in human linguistic performance. Cogn Sci 23:157–205

    Article  Google Scholar 

  • Cooper LN (1973) A possible organization of animal memory and learning. In: Proceedings of the nobel symposium on collective properties of physical systems, Aspensagarden, Sweden

  • Cooper LN (2000) Memories and memory: a physicist’s approach to the brain. Int J Mod Phys A 15(26):4069–4082. doi:10.1142/S0217751X0000272X

    Article  CAS  Google Scholar 

  • Deerwester S, Dumais S, Furnas G, Landauer T, Harshman R (1990) Indexing by latent semantic analysis. J Am Soc Inf Sci 41:391–407. doi:10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9

    Article  Google Scholar 

  • Delmas J, Delmas A (1958) Voies et Centres Nerveux—Introduction à la Neurologie Masson, Paris

  • Elman J (1990) Finding structure in time. Cogn Sci 14:179–211

    Article  Google Scholar 

  • Elman J (1993) Learning and development in neural networks: the importance of starting small: the importance of starting small. Cognition 48:71–99. doi:10.1016/0010-0277(93)90058-4

    Article  CAS  PubMed  Google Scholar 

  • Fodor J, Pylyshyn Z (1988) Connectionism and cognitive architecture: a critical analysis. In: Pinker S, Mehler J (eds) Connections and symbols. MIT Press, Cambridge, pp 3–71

    Google Scholar 

  • Friston KJ (1998) Imaging neuroscience: principles or maps? Proc Natl Acad Sci USA 95:796–802. doi:10.1073/pnas.95.3.796

    Article  CAS  PubMed  Google Scholar 

  • Graham A (1981) Kronecker products and matrix calculus with applications. Ellis Horwood, Chichester

    Google Scholar 

  • Hersh W, Buckley C, Leone T, Hickam D (1994) Ohsumed: an interactive retrieval evaluation and new large test collection for research. Proceedings of the 17th annual ACM SIGIR Conference, pp 192–201

  • Hoffman RE, Rapaport J, Ameli R, McGlashan TH, Harcherik D, Servan-Schreiber D (1995) A neural network simulation of hallucinated “voices” and associated speech perception impairments in schizophrenia patients. J Cogn Neurosci 7:479–497

    Article  Google Scholar 

  • Ide N, Véronis J (1998) Word sense disambiguation: the state of the art. Comput linguist 24:1–41

    Google Scholar 

  • Kandel ER, Schwartz JH (1985) Principles of neural science. Elsevier, New York

    Google Scholar 

  • Kohonen T (1972) Correlation matrix memories. IEEE Trans Comput C 21:353–359

    Article  Google Scholar 

  • Kohonen T (1977) Associative memory: a system-theoretical approach. Springer, New York

    Google Scholar 

  • Landauer T, Dumais S (1997) A solution to Plato’s problem: the latent semantic analysis theory of acquisition, induction and representation of knowledge. Psychol Rev 104:211–240

    Article  Google Scholar 

  • Marcus G (2001) The algebraic mind. The MIT Press, Cambridge

    Google Scholar 

  • Martin A, Wiggs CL, Ungerleider LG, Haxby JV (1996) Neural correlates of category-specific knowledge. Nature (London) 379:649–652

    Article  CAS  Google Scholar 

  • McGlashan TH, Hoffman RE (2000) Schizophrenia as a disorder of developmentally reduced synaptic connectivity. Arch Gen Psychiatry 57:637–648

    Article  CAS  PubMed  Google Scholar 

  • Mizraji E (1989) Context-dependent associations in linear distributed memories. Bull Math Biol 51:195–205

    CAS  PubMed  Google Scholar 

  • Mizraji E (2008) Neural memories and search engines. Int J Gen Syst 37:715–732

    Article  Google Scholar 

  • Mizraji E, Lin J (1997) A dynamical approach to logical decisions. Complexity 2:56–63

    Article  Google Scholar 

  • Mizraji E, Lin J (2001) Fuzzy decisions in modular neural networks. Int J Bifurc Chaos 11:155–167

    Article  Google Scholar 

  • Mizraji E, Lin J (2002) The dynamics of logical decisions: a neural network approach. Physica D: Nonlinear Phenomena 168–169C:386–396

    Article  Google Scholar 

  • Mizraji E, Pomi A, Alvarez F (1994) Multiplicative contexts in associative memories. Biosystems 32:145–161

    Article  CAS  PubMed  Google Scholar 

  • Montemurro MA, Pury PA (2002) Long-range fractal correlations in literary corpora. Fractals 10:451–461

    Article  Google Scholar 

  • Nass MM, Cooper LN (1975) A theory for the development of feature detecting cells in visual cortex. Biol Cybern 19:1–18

    Article  CAS  PubMed  Google Scholar 

  • Newell A, Simon HA (1976) Computer science as empirical inquiry: symbols and search. Commun ACM 19:113–126

    Article  Google Scholar 

  • Papadimitriou CH, Raghavan P, Tamaki H, Vempala S (2000) Latent semantic indexing: a probabilistic analysis. J Comput Syst Sci 61:217–235

    Article  Google Scholar 

  • Pike R (1984) Comparison of convolution and matrix distributed memory systems for associative recall and recognition. Psychol Rev 91:281–294

    Article  Google Scholar 

  • Pomi A (2007) Associative memory models shed light on some mechanisms underlying cognitive errors in medical diagnosis, 6th International Conference of Biological Physics, Radisson Victoria Plaza, Montevideo

  • Pomi A, Mizraji E (1999) Memories in context. BioSystems 50:173–188

    Article  Google Scholar 

  • Pomi A, Mizraji E (2001) A cognitive architecture that solves a problem stated by Minsky. IEEE Trans Syst, Man, Cybernet-Part B: Cybernet 31:729–734

    Article  CAS  Google Scholar 

  • Pomi A, Mizraji E (2004) Semantic graphs and associative memories. Phys Rev E, 70, 0666136, pp 1–6

    Google Scholar 

  • Pomi A, Olivera F (2006) Context-sensitive autoassociative memories as expert systems in medical diagnosis. BMC Med Inform Decis Mak 6:39

    Article  PubMed  Google Scholar 

  • Raichle ME (2003) Functional brain imaging and human brain function. J Neurosci 23:3959–3962

    CAS  PubMed  Google Scholar 

  • Reali F (2002) Interacciones multiplicativas en modelos de redes neuronales: algunas aplicaciones en redes de procesamiento del lenguaje. Tesis de Maestria. PEDECIBA—Facultad de Ciencias, Uruguay

  • Spitzer M (1999) The mind within the net. MIT Press, Massachusetts, Chap 10

    Google Scholar 

  • Steyvers M, Griffiths T (2007) Probabilistic topic models. In: Landauer T, McNamara DS, Dennis S, Kintsch W (eds) Handbook of latent semantic analysis. Erlbaum, Hillsdale

    Google Scholar 

  • Tsuda I (2001) Toward an interpretation of dynamic neural activity in terms of chaotic dynamical systems. Behav Brain Sci 24(5):793–847

    Article  CAS  PubMed  Google Scholar 

  • Valle-Lisboa JC, Mizraji E (2005) Un modelo neuronal de procesamiento de lenguaje basado en herramientas de búsqueda de información. In Abstracts of the XI Jornadas de la Sociedad Uruguaya de Biociencias, Minas, Uruguay, 2–4 September 2005

  • Valle Lisboa JC, Reali F, Anastasía H, Mizraji E (2005) Elman topology with sigma-pi units: an application to the modeling of verbal hallucinations in schizophrenia. Neural Netw 18:863–877

    Article  PubMed  Google Scholar 

  • Valle-Lisboa JC, Mizraji E (2007) The uncovering of hidden structures by latent semantic analysis. Inf Sci 177:4122–4147

    Article  Google Scholar 

  • van Gelder TJ (1999) Dynamic approaches to cognition. In: Wilson R, Keil F (eds) The MIT encyclopedia of cognitive sciences. MIT Press, Cambridge, pp 244–246

    Google Scholar 

  • Wright JJ, Rennie CJ, Lees GJ, Robinson PA, Bourke PD, Chapman CL, Gordon E, Rowe DL (2004) Simulated electrocortical activity at microscopic, mesoscopic and global scales. Int J Bifurc Chaos 14:853–872

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was partially supported by PEDECIBA-Uruguay. JCVL received partial support from “Fondo Clemente Estable”, FCE—S/C/IF/54/002.

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Authors and Affiliations

  1. Group of Cognitive Systems Modeling, Biophysical Section, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo, 11400, Uruguay

    Eduardo Mizraji, Andrés Pomi & Juan C. Valle-Lisboa

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  1. Eduardo Mizraji
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  2. Andrés Pomi
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  3. Juan C. Valle-Lisboa
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Correspondence to Eduardo Mizraji.

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Mizraji, E., Pomi, A. & Valle-Lisboa, J.C. Dynamic searching in the brain. Cogn Neurodyn 3, 401–414 (2009). https://doi.org/10.1007/s11571-009-9084-2

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