Abstract
The recall performance of a well-established canonical microcircuit model of the hippocampus, a region of the mammalian brain that acts as a short-term memory, was systematically evaluated. All model cells were simplified compartmental models with complex ion channel dynamics. In addition to excitatory cells (pyramidal cells), four types of inhibitory cells were present: axo-axonic (axonic inhibition), basket (somatic inhibition), bistratified cells (proximal dendritic inhibition) and oriens lacunosum-moleculare (distal dendritic inhibition) cells. All cells’ firing was timed to an external theta rhythm paced into the model by external reciprocally oscillating inhibitory inputs originating from the medial septum. Excitatory input to the model originated from the region CA3 of the hippocampus and provided context and timing information for retrieval of previously stored memory patterns. Model mean recall quality was tested as the number of stored memory patterns was increased against selectively modulated feedforward and feedback excitatory and inhibitory pathways. From all modulated pathways, simulations showed recall performance was best when feedforward inhibition from bistratified cells to pyramidal cell dendrites is dynamically increased as stored memory patterns is increased with or without increased pyramidal cell feedback excitation to bistratified cells. The study furthers our understanding of how memories are retrieved by a brain microcircuit. The findings provide fundamental insights into the inner workings of learning and memory in the brain, which may lead to potential strategies for treatments in memory-related disorders.
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References
Amaral D, Lavenex P. Hippocampal neuroanatomy. In: Andersen P, Morris R, Amaral D, Bliss T, O’Keefe J, editors. The hippocampus book. Oxford: University Press; 2007. p. 37–114.
Amit DJ. Modeling brain function: the world of attractor neural networks. New York: Cambridge University Press; 1989.
Andersen P, Morris R, Amaral D, Bliss T, O’Keefe J. The hippocampus book. Oxford: University Press; 2007.
Borhegyi Z, Varga V, Szilagyi N, Fabo D, Freund TF. Phase segregation of medial septal GABAergic neurons during hippocampal theta activity. J Neurosci. 2004;24:8470–9.
Buckingham J, Willshaw D. On setting unit thresholds in an incompletely connected associative net. Network. 1993;4:441–59.
Chamberland S, Topolnik L. Inhibitory control of hippocampal inhibitory neurons. Front Neurosci. 2012;6:165.
Cutsuridis V, Hasselmo M. GABAergic modulation of gating, timing and theta phase precession of hippocampal neuronal activity during theta oscillations. Hippocampus. 2012;22:1597–621.
Cutsuridis V, Poirazi P. A computational study on how theta modulated inhibition can account for the long temporal delays in the entorhinal-hippocampal loop. Neurobiol Learn Mem. 2015;120:69–83.
Cutsuridis V, Wenneckers T. Hippocampus, microcircuits and associative memory. Neural Netw. 2009;22(8):1120–8.
Cutsuridis V, Cobb S, Graham BP. Encoding and retrieval in the hippocampal CA1 microcircuit model. Hippocampus. 2010;20:423–46.
de Luca E, Ravasenga T, Petrini EM, Polenghi A, Nieus T, Guazzi S, et al. Inter-synaptic lateral diffusion of GABAA receptors shapes inhibitory synaptic currents. Neuron. 2017;95(1):63–69.e5.
Freund TF, Buzsaki G. Interneurons of the hippocampus. Hippocampus. 1996;6:347–470.
Ganter P, Szucs P, Paulsen O, Somogyi P. Properties of horizontal axo-axonic cells in stratum oriens of the hippocampal CA1 area of rats in vitro. Hippocampus. 2004;14:232–43.
Graham B, Willshaw D. Improving recall from an associative memory. Biol Cybern. 1995;72:337–46.
Graham B, Willshaw D. Capacity and information efficiency of the associative net. Network. 1997;8:35–54.
Hasselmo M, Bodelon C, Wyble B. A proposed function of the hippocampal theta rhythm: separate phases of encoding and retrieval of prior learning. Neural Comput. 2002;14:793–817.
Hines ML, Carnevale T. The NEURON simulation environment. Neural Comput. 1997;9:1179–209.
Hunter R, Cobb S, Graham BP. Improving associative memory in a network of spiking neurons. In: Kurkova V, et al., editors. Lecture notes in computer science (LNCS 5164). Berlin Heidelberg: Springer-Verlag; 2008. p. 636–45.
Klausberger T, Magill PJ, Marton LF, David J, Roberts B, Cobden PM, et al. Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature. 2003;421:844–8.
Klausberger T, Marton LF, Baude A, Roberts JD, Magill PJ, Somogyi P. Spike timing of dendrite-targeting bistratified cells during hippocampal network oscillations in vivo. Nat Neurosci. 2004;7:41–7.
Levy W. A sequence predicting CA3 is a flexible associator that learns and uses context to solve hippocampal-like tasks. Hippocampus. 1996;6:579–90.
Marr D. A simple theory of archicortex. Philos Trans R Soc Lond Ser B Biol Sci. 1971;262(841):23–81.
Mendoza E, Galarraga E, Tapia D, Laville A, Hernandez-Echeagaray E, Bargas J. Differential induction of long term synaptic plasticity in inhibitory synapses of the hippocampus. Synapse. 2006;60(7):533–42.
Palm G. On associative memories. Biol Cybern. 1980;36:9–31.
Pelletier JG, Lacaille JC. Long-term synaptic plasticity in hippocampal feedback inhibitory networks. Prog Brain Res. 2008;169:241–50.
Petersen CCH, Malenka RC, Nicoll RA, Hopfield JJ. All-or none potentiation at CA3-CA1 synapses. Proc Natl Acad Sci U S A. 1998;95:4732–7.
Poirazzi P, Brannon T, Mel BW. Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell. Neuron. 2003a;37:977–87.
Poirazzi P, Brannon T, Mel BW. Pyramidal neuron as a 2-layer neural network. Neuron. 2003b;37:989–99.
Santhakumar V, Aradi I, Soltetz I. Role of mossy fiber sprouting and mossy cell loss in hyperexcitability: a network model of the dentate gyrus incorporating cells types and axonal topography. J Neurophysiol. 2005;93:437–53.
Saraga F, Wu CP, Zhang L, Skinner FK. Active dendrites and spike propagation in multicompartment models of oriens-lacunosum/moleculare hippocampal interneurons. J Physiol. 2003;552:673–89.
Saraga F, Balena T, Wolansky T, Dickson CT, Woodin MA. Inhibitory synaptic plasticity regulates pyramidal neuron spiking in the rodent hippocampus. Neuroscience. 2008;155(1):64–75.
Sommer FT, Wennekers T. Modelling studies on the computational function of fast temporal structure in cortical circuit activity. J Physiol Paris. 2000;94:473–88.
Sommer FT, Wennekers T. Associative memory in networks of spiking neurons. Neural Netw. 2001;14:825–34.
Somogyi P, Katona L, Klausberger T, Lasztóczi B, Viney TJ. Temporal redistribution of inhibition over neuronal subcellular domains underlies state-dependent rhythmic change of excitability in the hippocampus. Philos Trans R Soc Lond Ser B Biol Sci. 2013;369(1635):20120518.
Steinbuch K. Non-digital learning matrices as preceptors. Kybernetik. 1961;1:117–24.
Treves A, Rolls E. Computational constraints suggest the need for two distinct input systems to the hippocampal CA3 network. Hippocampus. 1992;2:189–200.
Willshaw D, Buneman O, Longuet-Higgins H. Non-holographic associative memory. Nature. 1969;222:960–2.
Zarnadze S, Bäuerle P, Santos-Torres J, Böhm C, Schmitz D, Geiger JR, et al. Cell-specific synaptic plasticity induced by network oscillations. Elife. 2016;5:e14912.
Zhang S, Huang K, Hussain A. Learning from few samples with memory network. Cogn Comput. 2018;10(1):15–22.
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Cutsuridis, V. Improving the Recall Performance of a Brain Mimetic Microcircuit Model. Cogn Comput 11, 644–655 (2019). https://doi.org/10.1007/s12559-019-09658-8
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DOI: https://doi.org/10.1007/s12559-019-09658-8