{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T16:56:47Z","timestamp":1778000207059,"version":"3.51.4"},"reference-count":43,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T00:00:00Z","timestamp":1664323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"IFLP-CONICET Argentina","award":["PUE 22920170100066CO"],"award-info":[{"award-number":["PUE 22920170100066CO"]}]},{"name":"IFLP-CONICET Argentina","award":["Project 11\/X895"],"award-info":[{"award-number":["Project 11\/X895"]}]},{"name":"Universidad Nacional de La Plata","award":["PUE 22920170100066CO"],"award-info":[{"award-number":["PUE 22920170100066CO"]}]},{"name":"Universidad Nacional de La Plata","award":["Project 11\/X895"],"award-info":[{"award-number":["Project 11\/X895"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Synaptic plasticity is characterized by remodeling of existing synapses caused by strengthening and\/or weakening of connections. This is represented by long-term potentiation (LTP) and long-term depression (LTD). The occurrence of a presynaptic spike (or action potential) followed by a temporally nearby postsynaptic spike induces LTP; conversely, if the postsynaptic spike precedes the presynaptic spike, it induces LTD. This form of synaptic plasticity induction depends on the order and timing of the pre- and postsynaptic action potential, and has been termed spike time-dependent plasticity (STDP). After an epileptic seizure, LTD plays an important role as a depressor of synapses, which may lead to their complete disappearance together with that of their neighboring connections until days after the event. Added to the fact that after an epileptic seizure the network seeks to regulate the excess activity through two key mechanisms: depressed connections and neuronal death (eliminating excitatory neurons from the network), LTD becomes of great interest in our study. To investigate this phenomenon, we develop a biologically plausible model that privileges LTD at the triplet level while maintaining the pairwise structure in the STPD and study how network dynamics are affected as neuronal damage increases. We find that the statistical complexity is significantly higher for the network where LTD presented both types of interactions. While in the case where the STPD is defined with purely pairwise interactions an increase is observed as damage becomes higher for both Shannon Entropy and Fisher information.<\/jats:p>","DOI":"10.3390\/e24101384","type":"journal-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T20:58:47Z","timestamp":1664398727000},"page":"1384","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Spike Timing-Dependent Plasticity with Enhanced Long-Term Depression Leads to an Increase of Statistical Complexity"],"prefix":"10.3390","volume":"24","author":[{"given":"Monserrat","family":"Pallares Di Nunzio","sequence":"first","affiliation":[{"name":"Instituto de F\u00edsica de La Plata (IFLP), CONICET-UNLP, La Plata B1900, Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0129-5237","authenticated-orcid":false,"given":"Fernando","family":"Montani","sequence":"additional","affiliation":[{"name":"Instituto de F\u00edsica de La Plata (IFLP), CONICET-UNLP, La Plata B1900, Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Buzs\u00e1ki, G. (2006). Rhythms of the Brain, Oxford University Press.","DOI":"10.1093\/acprof:oso\/9780195301069.001.0001"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"345","DOI":"10.31887\/DCNS.2012.14.4\/gbuzsaki","article-title":"Brain rhythms and neural syntax: Implications for efficient coding of cognitive content and neuropsychiatric disease","volume":"14","author":"Watson","year":"2012","journal-title":"Dialogues Clin. Neurosci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1523\/JNEUROSCI.2834-05.2006","article-title":"Involvement of the CA3-CA1 synapse in the acquisition of associative learning in behaving mice","volume":"26","author":"Gruart","year":"2006","journal-title":"J. Neurosci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1126\/science.1128134","article-title":"Learning induces long-term potentiation in the hippocampus","volume":"313","author":"Whitlock","year":"2006","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1038\/sj.npp.1301559","article-title":"Synaptic Plasticity: Multiple Forms, Functions, and Mechanisms","volume":"33","author":"Citri","year":"2008","journal-title":"Neuropsychopharmacology"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.1007\/PL00000640","article-title":"The role of mammalian ionotropic receptors in synaptic plasticity: LTP, LTD and epilepsy","volume":"57","author":"Kullmann","year":"2000","journal-title":"Cell. Mol. Life Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1038\/nn0705-839","article-title":"Postsynaptic depolarization requirements for LTP and LTD: A critique of spike timing-dependent plasticity","volume":"8","author":"Lisman","year":"2005","journal-title":"Nat. Neurosci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"612073","DOI":"10.3389\/fnmol.2021.612073","article-title":"Neuropathophysiological Mechanisms and Treatment Strategies for Post-traumatic Epilepsy","volume":"14","author":"Sharma","year":"2021","journal-title":"Front. Mol. Neurosci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/bs.ctm.2019.07.007","article-title":"Chapter Seven\u2014Damage and repair of the axolemmal membrane: From neural development to axonal trauma and restoration","volume":"84","author":"Barrantes","year":"2019","journal-title":"Curr. Top. Membr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"S15","DOI":"10.1212\/WNL.59.9_suppl_5.S15","article-title":"Seizure-induced neuronal injury: Human data","volume":"59","author":"Duncan","year":"2002","journal-title":"Neurology"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1579","DOI":"10.1523\/JNEUROSCI.09-05-01579.1989","article-title":"Calpain I Activation Is Specifically Related to Excitatory Amino Acid Induction of Hippocampal Damage","volume":"9","author":"Siman","year":"1989","journal-title":"J. Neurosci. Off. J. Soc. Neurosci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1317","DOI":"10.1016\/j.neuron.2014.05.015","article-title":"Reduced Cognition in Syngap1 Mutants Is Caused by Isolated Damage within Developing Forebrain Excitatory Neurons","volume":"82","author":"Ozkan","year":"2014","journal-title":"Neuron"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Einarsdottir, H., Montani, F., and Schultz, S.R. (2007, January 11\u201313). A mathematical model of receptive field reorganization following stroke. Proceedings of the IEEE 6th International Conference on Development and Learning, ICDL\u201907, London, UK.","DOI":"10.1109\/DEVLRN.2007.4354027"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s12028-021-01431-w","article-title":"The Critical Role of Spreading Depolarizations in Early Brain Injury: Consensus and Contention","volume":"37","author":"Andrew","year":"2022","journal-title":"Neurocrit. Care"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"18","DOI":"10.3389\/fncom.2020.00018","article-title":"Neuronal Degeneration Impairs Rhythms Between Connected Microcircuits","volume":"14","author":"Schumm","year":"2020","journal-title":"Front. Comput. Neurosci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1162\/089976606775093882","article-title":"Polychronization: Computation with spikes","volume":"18","author":"Izhikevich","year":"2006","journal-title":"Neural Comput."},{"key":"ref_17","unstructured":"Koch, C., and Segev, I. (1998). Methods in Neuronal Modeling, Massachusetts Institute of Technology."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Izhikevich, E.M. (2006). Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting, MIT Press.","DOI":"10.7551\/mitpress\/2526.001.0001"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3637","DOI":"10.1152\/jn.00686.2005","article-title":"Adaptive exponential integrate-and-fire model as an effective description of neuronal activity","volume":"94","author":"Brette","year":"2005","journal-title":"J. Neurophysiol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"9673","DOI":"10.1523\/JNEUROSCI.1425-06.2006","article-title":"Triplets of spikes in a model of spike timing-dependent plasticity","volume":"26","author":"Pfister","year":"2006","journal-title":"J. Neurosci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"040106","DOI":"10.1103\/PhysRevE.79.040106","article-title":"Detecting and quantifying stochastic and coherence resonances via information-theory complexity measurements","volume":"79","author":"Rosso","year":"2009","journal-title":"Phys. Rev. E"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1140\/epjb\/e2009-00146-y","article-title":"Detecting and quantifying temporal correlations in stochastic resonance via information theory measures","volume":"69","author":"Rosso","year":"2009","journal-title":"Eur. Phys. J. B"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"075513","DOI":"10.1063\/1.5025187","article-title":"Rhythmic activities of the brain: Quantifying the high complexity of beta and gamma oscillations during visuomotor tasks","volume":"28","author":"Baravalle","year":"2018","journal-title":"Chaos"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Baravalle, R., Rosso, O.A., and Montani, F. (2018). Causal Shannon\u2013Fisher Characterization of Motor\/Imagery Movements in EEG. Entropy, 20.","DOI":"10.3390\/e20090660"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Gerstner, W., Kistler, W., Naud, R., and Paninski, L. (2014). Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition, Cambridge University Press.","DOI":"10.1017\/CBO9781107447615"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Song, S., Sj\u00f6str\u00f6m, P.J., Reigl, M., Nelson, S., and Chklovskii, D.B. (2005). Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits. PLoS Biol., 3.","DOI":"10.1371\/journal.pbio.0030350"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"13758","DOI":"10.1073\/pnas.0707492105","article-title":"Development of input connections in neural cultures","volume":"105","author":"Soriano","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1140\/epjb\/s10051-021-00046-6","article-title":"Network configurations of pain: An efficiency characterization of information transmission","volume":"94","author":"Baravalle","year":"2021","journal-title":"Eur. Phys. J. B"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"174102","DOI":"10.1103\/PhysRevLett.88.174102","article-title":"Permutation Entropy: A Natural Complexity Measure for Time Series","volume":"88","author":"Bandt","year":"2002","journal-title":"Phys. Rev. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2518","DOI":"10.1016\/j.physa.2011.12.033","article-title":"Ambiguities in the Bandt-Pompe\u2019s methodology for local entropic quantifiers","volume":"391","author":"Olivares","year":"2012","journal-title":"Physica A"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1577","DOI":"10.1016\/j.physleta.2012.03.039","article-title":"Contrasting chaos with noise via local versus global information quantifiers","volume":"376","author":"Olivares","year":"2012","journal-title":"Phys. Lett. A"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"046212","DOI":"10.1103\/PhysRevE.82.046212","article-title":"Permutation-information-theory approach to unveil delay dynamics from time-series analysis","volume":"82","author":"Zunino","year":"2010","journal-title":"Phys. Rev. E"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"052311","DOI":"10.1103\/PhysRevA.77.052311","article-title":"Metric character of the quantum Jensen-Shannon divergence","volume":"77","author":"Lamberti","year":"2008","journal-title":"Phys. Rev. A"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"083118","DOI":"10.1063\/1.4999613","article-title":"Detecting dynamical changes in time series by using the Jensen Shannon divergence","volume":"27","author":"Mateos","year":"2017","journal-title":"Chaos"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1130","DOI":"10.1093\/brain\/awy035","article-title":"Atlas of the normal intracranial electroencephalogram: Neurophysiological awake activity in different cortical areas","volume":"141","author":"Frauscher","year":"2018","journal-title":"Brain"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1002\/ana.25304","article-title":"High-Frequency Oscillations in the Normal Human Brain","volume":"84","author":"Frauscher","year":"2018","journal-title":"Ann. Neurol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1002\/ana.25651","article-title":"How the Human Brain Sleeps: Direct Cortical Recordings of Normal Brain Activity","volume":"87","author":"Ellenrieder","year":"2020","journal-title":"Ann. Neurol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"6851","DOI":"10.1523\/JNEUROSCI.5983-08.2009","article-title":"Stability of thalamocortical synaptic transmission across awake brain states","volume":"29","author":"Stoelzel","year":"2009","journal-title":"J. Neurosci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"7086","DOI":"10.1523\/JNEUROSCI.2849-20.2021","article-title":"G-Protein-Gated Inwardly Rectifying Potassium (Kir3\/GIRK) Channels Govern Synaptic Plasticity That Supports Hippocampal-Dependent Cognitive Functions in Male Mice","volume":"41","author":"Djebari","year":"2021","journal-title":"J. Neurosci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"E4510","DOI":"10.1073\/pnas.1315926110","article-title":"Long-term depression triggers the selective elimination of weakly integrated synapses","volume":"110","author":"Wiegert","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"19383","DOI":"10.1073\/pnas.1105933108","article-title":"A triplet spike-timing-dependent plasticity model generalizes the Bienenstock-Cooper-Munro rule to higher-order spatiotemporal correlations","volume":"108","author":"Gjorgjieva","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1038\/s42005-021-00696-z","article-title":"Ordinal patterns-based methodologies for distinguishing chaos from noise in discrete time series","volume":"4","author":"Zanin","year":"2021","journal-title":"Commun. Phys."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"435","DOI":"10.3389\/fnins.2018.00435","article-title":"Training Deep Spiking Convolutional Neural Networks with STDP-Based Unsupervised Pre-training Followed by Supervised Fine-Tuning","volume":"12","author":"Lee","year":"2018","journal-title":"Front. Neurosci."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/10\/1384\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:41:21Z","timestamp":1760143281000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/10\/1384"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,28]]},"references-count":43,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["e24101384"],"URL":"https:\/\/doi.org\/10.3390\/e24101384","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,28]]}}}