A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia

Frontiers in Systems Neuroscience

Volumn 9, Issue MAR, 2015, Pages

  Faghihi, Faramarz ^a   Moustafa, Ahmed A ^b,c  

^a Krasnow Institute for Advanced Study   (United States)

^b VETERANS AFFAIRS MEDICAL CENTER   (United States)

^c WESTERN SYDNEY UNIVERSITY   (Australia)

Author keywords

Connectivity rate; Dentate gyrus; Entorhinal cortex; Feedback inhibition; Mutual information; Pattern separation; Sparse coding; Sparse spiking

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONNECTOME; DENTATE GYRUS; ENTORHINAL CORTEX; EPISODIC MEMORY; INFORMATION PROCESSING; MATHEMATICAL PARAMETERS; NEGATIVE FEEDBACK; SCHIZOPHRENIA; SEPARATION TECHNIQUE; SPIKE WAVE; STIMULUS RESPONSE;

EID: 84928114237     PISSN: 16625137     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnsys.2015.00042     Document Type: Article

References (55)

1. Amaral, D. G., Ishizuka, N., and Claiborne, B. (1990). Chapter neurons, numbers and the hippocampal network. Prog. Brain Res. 83, 1–11. doi: 10.1016/S00796123(08)61237-6
2. Bakker, A., Kirwan, C. B., Miller, M., and Stark, C. E. (2008). Pattern separation in the human hippocampal CA3 and dentate gyrus. Science 319, 1640–1642. doi: 10.1126/science.1152882
3. Barres, B. A., Silverstein, B. E., Corey, D. P., and Chun, L. L. (1988). Immunological, morphological, and electrophysiological variation among retinal ganglion cells purified by panning. Neuron 1, 791–803. doi: 10.1016/0896-6273(88)90127-4
4. Clayton, N. S., and Hen, R. (2005). Neural circuits and behaviour: developmental and evolutionary perspectives. Curr. Opin. Neurobiol.15, 683–685. doi: 10.1016/j.conb.2005.10.007
5. D’Amelio, M., and Rossini, P. M. (2012). Brain excitability and connectivity of neuronal assemblies in Alzheimer’s disease: from animal models to human firain e. Prog. Neurobiol. 99, 42–60. doi: 10.1016/j.pneurobio.2012.07.001
6. Das, T., Ivleva, E. I., Wagner, A. D., Stark, C. E., and Tamminga, C. A. (2014). Loss of pattern separation performance in schizophrenia suggests dentate gyrus dysfunction. Schizophr. Res. 159, 193–197. doi: 10.1016/j.schres.2014.05.006
7. Deco, G., and andSchürmann, B. (1998). Stochastic resonance in the mutual information between input and output spike trains of noisy central neurons. Physica D Nonlinear Phenomena 117, 276–282. doi: 10.1016/S0167-2789(97)00313-8
8. Derrick, B. E. (2007). Plastic processes in the dentate gyrus: a computational perspective. Prog. Brain Res. 163, 417–451. doi: 10.1016/S0079-6123(07)63024-6
9. Ebner, M., and Hameroff, S. (2011). Lateral information processing by spiking neurons: a theoretical model of the neural correlate of consciousness. Comput. Intell. Neurosci. 2011:11. doi: 10.1155/2011/247879
10. English, D. F., Peyrache, A., Stark, E., Roux, L., Vallentin, D., Long, M. A., et al. (2014). Excitation and inhibition compete to control spiking during hippocam- pal ripples: intracellular study in behaving mice. J. Neurosci. 34, 16509–16517. doi: 10.1523/JNEUROSCI.2600-14.2014
11. Faghihi, F., Kolodziejski, C., Fiala, A., Wörgötter, F., and Tetzlaff, C. (2013). An information theoretic model of information processing in the Drosophila olfactory system: the role of inhibitory neurons for system efficiency. Front. Comput. Neurosci. 7:183. doi: 10.3389/fncom.2013.00183
12. Faghihi, F., and Moustafa, A. A. (2015). Impaired homeostatic regulation of feedback inhibition associated with system deficiency to detect fluctuation in stimulus intensity: a simulation study. Neurocomputing 151, 1248–1254. doi: 10.1016/j.neucom.2014.11.008
13. Flores, C. E., and Méndez, P. (2014). Shaping inhibition: activity dependent structural plasticity of GABAergic synapses. Front. Cell. Neurosci. 8:327. doi: 10.3389/fncel.2014.00327
14. Gilbert, P. E., Kesner, R. P., and DeCoteau, W. E. (1998). Memory for spatial location: role of the hippocampus in mediating spatial pattern separation. J. Neurosci. 18, 804–810
15. Gilbert, P. E., Kesner, R. P., and Lee, I. (2001). Dissociating hippocampal subregions: a double dissociation between dentate gyrus and CA1. Hippocampus 11, 626–636. doi: 10.1002/hipo.1077
16. Gold, A. E., and Kesner, R. P. (2005). The role of the CA3 subregion of the dorsal hippocampus in spatial pattern completion in the rat. Hippocampus 15, 808–814. doi: 10.1002/hipo.20103
17. Gould, E., Tanapat, P., Hastings, N. B., and Shors, T. J. (1999). Neurogenesis in adulthood: a possible role in learning. Trends Cogn. Sci. 3, 186–192. doi: 10.1016/S1364-6613(99)01310-8
18. Griffen, T. C., and Maffei, A. (2014). GABAergic synapses: their plasticity and role in sensory cortex. Front. Cell. Neurosci. 8:91. doi: 10.3389/fncel.2014.00091
19. Gruart, A., Sánchez-Campusano, R., Fernández-Guizán, A., and Delgado-García, J. M. (2014). A differential and timed contribution of identified hippocampal synapses to associative learning in mice. Cereb. Cortex doi: 10.1093/cercor/bhu054 [Epub ahead of print]
20. Gupta, A., Vig, L., and Noelle, D. C. (2012). A neurocomputational approach to automaticity in motor skill learning. Biol. Inspired Cogn. Archit. 2, 1–12. doi: 10.1016/j.bica.2012.07.009
21. He, Y., Chen, Z., Gong, G., and Evans, A. (2009). Neuronal networks in Alzheimer’s disease. Neuroscientist 15, 333–350. doi: 10.1177/1073858409334423
22. Heisenberg, M. (2003). Mushroom body memoir: from maps to models. Nat. Rev. Neurosci. 4, 266–275. doi: 10.1038/nrn1074
23. Jiao, X., Zhu, D., and Wang, R. (2015). “Synchronization in neuronal population with phase response,” in Advances in Cognitive Neurodynamics (IV), ed. H. Liljenström (Dordrecht: Springer), 259–263
24. Konradi, C., Yang, C. K., Zimmerman, E. I., Lohmann, K. M., Gresch, P., Pantazopoulos, H., et al. (2011). Hippocampal interneurons are abnormal in schizophrenia. Schizophr. Res. 131, 165–173. doi: 10.1016/j.schres.2011.06.007
25. Lamprecht, R., and LeDoux, J. (2004). Structural plasticity and memory. Nat. Rev. Neurosci. 5, 45–54. doi: 10.1038/nrn1301
26. Leutgeb, J. K., Leutgeb, S., Moser, M. B., and Moser, E. I. (2007). Pattern separation in the dentate gyrus and CA3 of the hippocampus. Science 315, 961–966. doi: 10.1126/science.1135801
27. Lübke, J., Frotscher, M., and Spruston, N. (1998). Specialized electrophysiological properties of anatomically identified neurons in the hilar region of the rat fascia dentata. J. Neurophysiol. 79, 1518–1534
28. Marjovi, A., and Marques, L. (2011). Multi-robot olfactory search in structured environments. Rob. Auton. Syst. 59, 867–881. doi: 10.1016/j.robot.2011.07.010
29. Marr, D. (1970). A theory for cerebral neocortex. Proc. R. Soc. Lond. B Biol. Sci. 176, 161–234. doi: 10.1098/rspb.1970.0040
30. Mitaim, S., and Kosko, B. (2004). Adaptive stochastic resonance in noisy neurons based on mutual information. IEEE Trans. Neural Netw. 15, 1526–1540. doi: 10.1109/TNN.2004.826218
31. Myers, C. E., and Scharfman, H. E. (2009). A role for hilar cells in pattern separation in the dentate gyrus: a computational approach. Hippocampus 19, 321–337. doi: 10.1002/hipo.20516
32. Newman, E. L., and Hasselmo, M. E. (2014). CA3 Sees the big picture while dentate gyrus splits hairs. Neuron 81, 226–228. doi: 10.1016/j.neuron.2014.01.004
33. Nitz, D., and McNaughton, B. (2004). Differential modulation of CA1 and dentate gyrus interneurons during exploration of novel environments. J. Neurophysiol. 91, 863–872. doi: 10.1152/jn.00614.2003
34. Petrantonakis, P. C., and Poirazi, P. (2014). A compressed sensing per- spective of hippocampal function. Front. Syst. Neurosci. 8:141. doi: 10.3389/fnsys.2014.00141
35. Piatti, V. C., Ewell, L. A., and Leutgeb, J. K. (2013). Neurogenesis in the dentate gyrus: carrying the message or dictating the tone. Front. Neurosci. 7:50. doi: 10.3389/fnins.2013.00050
36. Roudi, Y., Nirenberg, S., and Latham, P. E. (2009). Pairwise maximum entropy models for studying large biological systems: when they can work and when they can’t. PLoS Comput. Biol. 5:e1000380. doi: 10.1371/journal.pcbi.1000380
37. Roux, L., and Buzsáki, G. (2014). Tasks for inhibitory interneurons in intact brain circuits. Neuropharmacology 30:e14. doi: 10.1016/j.neuropharm.2014.09.011
38. Rowan, M. (2012). Information-selectivity of beta-amyloid pathology in an associative memory model. Front. Comput. Neurosci. 6:2. doi: 10.3389/fncom.2012.00002
39. Rozo, L., Jiménez, P., and Torras, C. (2013). A robot learning from demonstration framework to perform force-based manipulation tasks. Intel. Serv. Robotics 6, 33–51. doi: 10.1007/s11370-012-0128-9
40. Schmidt, B., Marrone, D. F., and Markus, E. J. (2012). Disambiguating the similar: the dentate gyrus and pattern separation. Brain Res. 226, 56–65. doi: 10.1016/j.bbr.2011.08.039
41. Sengupta, B., Laughlin, S. B., and Niven, J. E. (2013). Balanced excitatory and inhibitory synaptic currents promote efficient coding and metabolic efficiency. PLoS Comput. Biol. 9:e1003263. doi: 10.1371/journal.pcbi.1003263
42. Seung, H. S., and Sümbül, U. (2014). Neuronal cell types and connectivity: lessons from the retina. Neuron 83, 1262–1272. doi: 10.1016/j.neuron.2014.08.054
43. Song, K., Liu, Q., and Wang, Q. (2011). Olfaction and hearing based mobile robot navigation for odor/sound source search. Sensors 11, 2129–2154. doi: 10.3390/s110202129
44. Spalding, K. L., Bergmann, O., Alkass, K., Bernard, S., Salehpour, M., Huttner, H. B., et al. (2013). Dynamics of hippocampal neurogenesis in adult humans. Cell 153, 1219–1227. doi: 10.1016/j.cell.2013.05.002
45. Stramandinoli, F., Marocco, D., and Cangelosi, A. (2012). The grounding of higher order concepts in action and language: a cognitive robotics model. Neural Netw. 32, 165–173. doi: 10.1016/j.neunet.2012.02.012
46. Tamminga, C. A., Stan, A. D., and Wagner, A. D. (2010). The hippocampal formation in schizophrenia. Am. J. Psychiatry 167, 1178–1193. doi: 10.1176/appi.ajp.2010.09081187
47. vanSteveninck, R. R. D. R., Lewen, G. D., Strong, S. P., Koberle, R., and Bialek, W. (1997). Reproducibility and variability in neural spike trains. Science 275, 1805–1808. doi: 10.1126/science.275.5307.1805
48. Van Strien, N. M., Cappaert, N. L. M., and Witter, M. P. (2009). The anatomy of memory: an interactive overview of the parahippocampal–hippocampal network. Nat. Rev. Neurosci. 10, 272–282. doi: 10.1038/nrn2614
49. Vega-Flores, G., Gruart, A., and Delgado-García, J. M. (2014). Involvement of the GABAergicsepto-hippocampal pathway in brain stimulation reward. PLoS ONE 9:e113787. doi: 10.1371/journal.pone.0113787
50. Wang, L., and Maffei, A. (2014). Inhibitory plasticity dictates the sign of plasticity at excitatory synapses. J. Neurosci. 34, 1083–1093. doi: 10.1523/JNEUROSCI.4711-13.2014
51. Wilbrecht, L., and Shohamy, D. (2009). Neural circuits can bridge systems and cognitive neuroscience. Front. Hum. Neurosci. 3:81. doi: 10.3389/neuro.09.081.2009
52. Yassa, M. A., and Stark, C. E. (2011). Pattern separation in the hippocampus. Trends Neurosci. 34, 515–525. doi: 10.1016/j.tins.2011.06.006
53. Yeckel, M. F., and Berger, T. W. (1990). Feedforward excitation of the hippocampus by afferents from the entorhinal cortex: redefinition of the role of the trisynaptic pathway. Proc. Natl. Acad. Sci. U.S.A. 87, 5832–5836. doi: 10.1073/pnas.87.15.5832
54. Yue, S., Rind, F. C., Keil, M. S., Cuadri, J., and Stafford, R. (2006). A bio-inspired visual collision detection mechanism for cars: optimization of a model of a locust neuron to a novel environment. Neurocomputing 69, 1591–1598. doi: 10.1016/j.neucom.2005.06.017
55. Zawadzki, K., Feenders, C., Viana, M. P., Kaiser, M., and Costa, L. D. F. (2012). Morphological homogeneity of neurons: searching for outlier neuronal cells. Neuroinformatics 10, 379–389. doi: 10.1007/s12021-012-9150-5