Üç hücreli motif genelleme ile oluşturulan küçük ölçekli biyolojik sinir ağlarının bellek davranışı

Yıl 2019, , 565 - 577, 28.06.2019

Ahmet Turan , Temel Kayıkçıoğlu

https://doi.org/10.25092/baunfbed.624503

Öz

Biyolojik bellek yapısını ve fonksiyonlarını anlamak için teorik ve deneysel pek çok çalışma yapılmaktadır. Bu çalışmalarda biyolojik ağların, özel hücreler arası bağlantılardan (motifler) oluştuğu görülmüştür. Deneysel çalışmalar ışığında oluşturulan modeller üzerinde, biyolojik ağlardan oluşan bellek yapıları ve bu yapıların temel yapı taşı olan motifler incelenmektedir.  Çalışmamızda sinir hücresi, sadece soma bölümünden oluşan ve tek bölmeli hücre şeklinde modellendi.  Hücreler arası iletişim kimyasal sinaps şeklinde tercih edildi ve modelde hücreler arası iletişim incelendi.  Hücre rolleri giriş, ara ve çıkış olarak düşünülen üç hücreli motiflerde, uzun -ve kısa dönem bellek davranışı çalışıldı.  Üç hücreli motiflerin giriş, ara ve çıkış hücrelerinin çoklanması yöntemiyle oluşturulan (motif genelleme) küçük ölçekli biyolojik ağların, uzun -ve kısa dönem bellek davranışları tespit edildi.  Motiflerde ve motiflerden oluşan ağlarda yaptığımız çalışmalardan elde edilen bulgular karşılaştırıldı.  Biyolojik ağın, kendisini oluşturan motiflerle aynı bellek davranışını sergilediği gösterildi.  Böylece biyolojik ağların bellek davranışlarını anlayabilmek için öncelikle ağda bulunan motifler üzerinde daha detaylı çalışılması gerektiği ortaya konuldu.

Anahtar Kelimeler

Biyolojik ağ, kısa-dönem bellek, sinaptik iletişim, uzun-dönem bellek, uyarıcı ve engelleyici uyaran, üç hücreli motif

Memory behavior of small-scale biological neural networks generated by generalization of a three-cell motif

Öz

Many theoretical and experimental studies are performed to understand the structure and functions of biological memory.  In these studies, it was seen that biological networks consisted of special intercellular connection (motifs).  On the models created in the light of experimental studies, the memory structures composed of biological networks and the basic building blocks of these structures are examined.  In our study, the nerve cell was modeled as a single compartment cell consisting only of soma section.  Intercellular communication was preferred in the form of chemical synapses and the intercellular communication was examined in the model.  Long-and short-term memory behavior was studied in three-cell motifs which were thought to be input, intermediate and output of cell roles.  Long-term and short-term memory behaviors of small-scale biological networks which were formed by multiplexing of input, intermediate and output cells (motif generalization) of three-cell motifs were determined.  The results of our studies in the networks consisting of motifs and motifs were compared.  It was shown that the biological network exhibited the same memory behavior as its motifs.  Thus, in order to understand the memory behaviors of the biological networks, it was revealed that the motifs in the network should be studied in more detail.

Anahtar Kelimeler

Biological network, short-term memory, synaptic communication, long-term memory, excitatory and inhibitory stimuli, three-cell motif

Kaynakça

• Humphries, M. D., Dynamical networks: Finding, measuring, and tracking neural population activity, Massachusetts Institute of Technology, 1,4, 324-338, (2017).
• Cornelia, I.B. ve Eve, M., From the connectome to brain function, Nature America, (2013).
• Li, C., Functions of neuronal network motifs, Physical reviewe E, 037101, (2008).
• Prill, R.J, Iglesias, P.A. ve Levchenko, A., Dynamic properties of network motifs contribute to biological network organization, PLOS Biology, (2005).
• Sporns, O. ve Kotter, R., Motifs in Brain Networks, PLOS Biology, (2004).
• Gorochowski T.E., Grierson, C.S., Bernardo, M., Organisation of feed-forward loop motifs reveals architectural principles in natural and engineered networks, Biorxiv The preprint server for biology, (2017).
• Dong, C.Y., Lim, J., Nam, Y. ve Cho, K.H., Systematic analysis of synchronized oscillatory neuronal networks reveals an enrichment for coupled direct and indirect feedback motifs, Bioinformatics, 25, 13, 1680–1685, (2009).
• Heinz, K. ve Stefan, H., Motifs, algebraic connectivity and computational performance of two data-based cortical circuit templates, International Workshop on Computational Systems Biology, (2009).
• Kim, J.R., Yoon, Y. ve Cho, K.H., Coupled feedback loops form dynamic motifs of cellular networks, Biophysical Journal 94, 359–365, (2008).
• Song, S., Sjöström, P.J., Reigl, M., Nelson, S. ve Chklovskii, D.B., Highly nonrandom features of synaptic connectivity in local cortical circuits, PLOS Biology, (2005).
• Feldmeyer, D., Qi, G., Emmenegger, E. ve Staiger, J.F., Inhibitory Interneurons and their Circuit Motifs in the Many Layers of the Barrel Cortex, Neuroscience, Published by Elsevier Ltd, (2018).
• Chenkov, N., Sprekeler, H. ve Kempter, R., Memory replay in balanced recurrent networks, PLoS Computational Biology,13(1): e1005359, (2017).
• Dong, C.Y., Lim, J., Nam, Y. ve Cho, K.H., Systematic analysis of synchronized oscillatory neuronal networks reveals an enrichment for coupled direct and indirect feedback motifs, Bioinformatics, 25, 13, 1680–1685, (2009).
• Elodie, B.J., Sabrina, D. ve Serge, L., Brain plasticity mechanisms and memory, A Party of Four Neuroscientist, 13, 492, (2007).
• Kaiser, T.F. ve Peters, F.J., Synaptic Plasticity, Nova science publishers, New York, (2009).
• Mark, M., Steven, A.S. ve Eric, R.K., Synapses and memory storage, Cold Spring Harb Perspect Biology, (2012).
• Arbib, M.A., The handbook of brain theory and neural network, (Second edition), (2003).
• Bassett, D.S. ve Bullmore E., Small-World Brain Networks Revisited, The Neuroscientist, 23(5), 499–516, (2017).
• Khambhati, A.N, Sizemore, A.E., Betzel, R.F. ve Bassett, D.S, Modelling and Interpreting Network Dynamics, Biorxiv The preprint server for biology, ( 2017).
• Tang, E., Bassett, D.S, Control of Dynamics in Brain Networks, Reviews of modern physics, (2017).
• Keleş, E. ve Çepni, S., Beyin ve Öğrenme, Journal of Turkish Science, (2006).
• Mirisis, A.A., Alexandrescu, A., Carew, T.J. ve Kopec A.M., The Contribution of Spatial and Temporal Molecular Networks in the Induction of Long-term Memory and Its Underlying Synaptic Plasticity, Neuroscience, (2016).
• Spiegler, A., Hansen E., Bernard, C., McIntosh, A.R. ve Jirsa, V.K., Selective Activation of Resting-State Networks following Focal Stimulation in a Connectome-Based Network Model of the Human Brain, Eneuro, (2016).
• Junker, B.H. ve Schreiber, F., Analysis of biological networks, (2008).
• Thurley, K., Wu, L.F. ve Altschuler, S.J., Response-time behaviors of intercellular communication network motifs, Biorxiv The preprint server for biology, (2017).
• Wang, J., Jianming, G.J. ve Fei, X., Two-parameters hopf bifurcation in the Hodgkin–Huxley model, Chaos, Solitons & Fractals: X, 23, 973–980, (2005).
• Schachinger, D., Simulation of extracellularly recorded activities from small nerve formations in the brain, Thesis, Wien, Mai, (2003).
• Bower, J.M. ve Beeman, D., The Book of GENESIS (Second edition), Springer-Verlag, (1998).
• Gerstner, W. ve Kistler, W.M., Spiking neuron models, Cambridge University Press, (2002).
• Keener, J. ve Sneyd, J., Mathematical physiology (Second Edition), ( 2009).
• Jackman S.L., Regehr W.G.,The Mechanisms and Functions of Synaptic Facilitation, Neuron, 94,3,447-464, (2017).
• Dayan, P. ve Abbott, L.F., Theoretical neuroscience, (2002).
• Izhikevich, E.M., Dynamical systems in neuroscience, The MIT Press Cambridge, 16-17, (2007).
• Milo, R., Shen, O.S., Itzkovitz, S., Kashtan, N., Chklovskii, D. ve Alon, U., Network motifs simple building blocks of complex networks, Science, 298, 824-827, (2002).
• Bassett, D.S. ve Bullmore, E., Small-world brain networks, The Neuroscientist, 512-523, (2006).
• Han, Z., Vondriska, T.M., Yang, L., Maclellan, W.R., Weissa, J.N. ve Qu, Z., Signal transduction network motifs and biological memory, Journal of Theoretical Biology, 246, 755–761, (2007).
• Navlakha, S., Joseph, Z.B. ve Barth, A.L., Network Design and the Brain, Trends in cognitive sciences, 64-78, 22, 1, 67-78, (2018).