{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T02:39:37Z","timestamp":1761964777481},"reference-count":36,"publisher":"MIT Press - Journals","issue":"10","license":[{"start":{"date-parts":[[2020,7,15]],"date-time":"2020-07-15T00:00:00Z","timestamp":1594771200000},"content-version":"vor","delay-in-days":1383,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2016,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>In this letter, we propose a definition of the operational mode of a neuron, that is, whether a neuron integrates over its input or detects coincidences. We complete the range of possible operational modes by a new mode we call gap detection, which means that a neuron responds to gaps in its stimulus. We propose a measure consisting of two scalar values, both ranging from \u22121 to +1: the neural drive, which indicates whether its stimulus excites the neuron, serves as background noise, or inhibits it; the neural mode, which indicates whether the neuron\u2019s response is the result of integration over its input, of coincidence detection, or of gap detection; with all three modes possible for all neural drive values. This is a pure spike-based measure and can be applied to measure the influence of either all or subset of a neuron\u2019s stimulus. We derive the measure by decomposing the reverse correlation, test it in several artificial and biological settings, and compare it to other measures, finding little or no correlation between them. We relate the results of the measure to neural parameters and investigate the effect of time delay during spike generation. Our results suggest that a neuron can use several different modes simultaneously on different subsets of its stimulus to enable it to respond to its stimulus in a complex manner.<\/jats:p>","DOI":"10.1162\/neco_a_00875","type":"journal-article","created":{"date-parts":[[2016,8,24]],"date-time":"2016-08-24T15:56:58Z","timestamp":1472054218000},"page":"2091-2128","update-policy":"http:\/\/dx.doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":3,"title":["Integrator or Coincidence Detector: A Novel Measure Based on the Discrete\n          Reverse Correlation to Determine a Neuron\u2019s Operational Mode"],"prefix":"10.1162","volume":"28","author":[{"given":"Jacob","family":"Kanev","sequence":"first","affiliation":[{"name":"Institute of Software Engineering and Theoretical Computer Science, Technische Universit\u00e4t Berlin, Berlin 10587, Germany jkanev@zoho.com"}]},{"given":"Achilleas","family":"Koutsou","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Cyprus, 1678 Nicosia, Cyprus achilleas.k@cs.ucy.ac.cy"}]},{"given":"Chris","family":"Christodoulou","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Cyprus, 1678 Nicosia, Cyprus cchrist@cs.ucy.a.cy"}]},{"given":"Klaus","family":"Obermayer","sequence":"additional","affiliation":[{"name":"Institute of Software Engineering and Theoretical Computer Science, Technische Universit\u00e4t Berlin, Berlin 10587, Germany klaus.obermayer@mailbox.tu-berlin.de"}]}],"member":"281","published-online":{"date-parts":[[2016,10,1]]},"reference":[{"key":"2022050215131214500_R1","unstructured":"Abeles, M.\n           (1982). Role of the cortical neuron:\n            Integrator or coincidence detector?Israel Journal of Medical\n            Sciences, 18,\n          83\u201392."},{"key":"2022050215131214500_R2","unstructured":"Bell, A. J.,\n                Mainen, Z.\n              F., Tsodyks,\n                M., &\n                Sejnowski, T.\n              J. (1995).\n            Balancing of conductances may explain irregular cortical\n            spiking. (Technical Report INC-9502).\n            San Diego: Institute for Neural\n            Computation, UCSD."},{"key":"2022050215131214500_R3","doi-asserted-by":"crossref","unstructured":"Bugmann, G.,\n                Christodoulou,\n              C., &\n                Taylor, J.\n              G. (1997). Role\n            of temporal integration and fluctuation detection in the highly irregular firing of a\n            leaky integrator neuron model with partial reset. Neural\n            Computation, 9(5),\n            985\u20131000.","DOI":"10.1162\/neco.1997.9.5.985"},{"key":"2022050215131214500_R4","doi-asserted-by":"crossref","unstructured":"Destexhe, A.,\n                Rudolph,\n            M., Fellous,\n                J. M., &\n                Sejnowski, T.\n              J. (2001).\n            Fluctuating synaptic conductances recreate in vivo\u2013like activity in\n            neocortical neurons. Neuroscience,\n            107(1),\n          13\u201324.","DOI":"10.1016\/S0306-4522(01)00344-X"},{"key":"2022050215131214500_R5","doi-asserted-by":"crossref","unstructured":"Hsu, A.,\n                Borst, A.,\n            & Theunissen, F.\n              E. (2004).\n            Quantifying variability in neural responses and its application for the\n            validation of model predictions. Network: Computation in Neural\n            Systems, 15(2),\n            91\u2013109.","DOI":"10.1088\/0954-898X_15_2_002"},{"key":"2022050215131214500_R6","doi-asserted-by":"crossref","unstructured":"Kempter, R.,\n                Gerstner,\n              W., & van\n                Hemmen, J. L.\n            (1998). How the threshold of a neuron determines its\n            capacity for coincidence detection. BioSystems,\n            48(1\u20133),\n          105\u2013112.","DOI":"10.1016\/S0303-2647(98)00055-0"},{"key":"2022050215131214500_R7","doi-asserted-by":"crossref","unstructured":"Kempter, R.,\n                Gerstner,\n              W., van\n                Hemmen, J. L., &\n                Wagner,\n            H. (1998).\n            Extracting oscillations. Neuronal coincidence detection with noisy\n            periodic spike input. Neural Computation,\n            10(8),\n          1987\u20132017.","DOI":"10.1162\/089976698300016945"},{"key":"2022050215131214500_R8","doi-asserted-by":"crossref","unstructured":"K\u00f6nig, P.,\n                Engel, A.\n              K., & Singer,\n                W. (1996).\n            Integrator or coincidence detector? The role of the cortical neuron\n            revisited. Trends in Neurosciences,\n            19(4),\n          130\u2013137.","DOI":"10.1016\/S0166-2236(96)80019-1"},{"key":"2022050215131214500_R9","doi-asserted-by":"crossref","unstructured":"Koutsou, A.,\n                Christodoulou,\n              C., Bugmann,\n                G., &\n                Kanev,\n            J. (2012).\n            Distinguishing the causes of firing with the membrane potential\n            slope. Neural Computation,\n            29(9),\n          2318\u20132345.","DOI":"10.1162\/NECO_a_00323"},{"key":"2022050215131214500_R10","doi-asserted-by":"crossref","unstructured":"Koutsou, A.,\n                Kanev, J.,\n            & Christodoulou,\n              C. (2013).\n            Measuring input synchrony in the Ornstein\u2014Uhlenbeck neuronal model\n            through input parameter estimation. Brain Research,\n            1536, 97\u2013106.","DOI":"10.1016\/j.brainres.2013.05.012"},{"key":"2022050215131214500_R11","doi-asserted-by":"crossref","unstructured":"Koutsou, A.,\n                Kanev, J.,\n                Economidou,\n              M., &\n                Christodoulou,\n              C. (2016).\n            Integrator or coincidence detector: What shapes the relation of stimulus\n            synchrony and the operational mode of a neuron?Mathematical\n            Biosciences and Engineering, 13(3),\n            521\u2013535.","DOI":"10.3934\/mbe.2016005"},{"key":"2022050215131214500_R12","doi-asserted-by":"crossref","unstructured":"Kreuz, T.,\n                Chicharro,\n              D.,\n              Andrzejak, R.\n              G., Haas, J.\n                S., & Abarbanel,\n                H. D. I.\n          (2009). Measuring multiple spike train\n            synchrony. Journal of Neuroscience Methods,\n            184(2),\n          287\u2013299.","DOI":"10.1016\/j.jneumeth.2009.06.039"},{"key":"2022050215131214500_R13","doi-asserted-by":"crossref","unstructured":"Kreuz, T.,\n                Chicharro,\n              D.,\n              Greschner,\n            M., &\n                Andrzejak, R.\n              G. (2011).\n            Time-resolved and time-scale adaptive measures of spike train\n            synchrony. Journal of Neuroscience Methods,\n            195(1),\n          92\u2013106.","DOI":"10.1016\/j.jneumeth.2010.11.020"},{"key":"2022050215131214500_R14","doi-asserted-by":"crossref","unstructured":"Kreuz, T.,\n                Chicharro,\n              D., Houghton,\n                C.,\n                Andrzejak, R.\n              G., & Mormann,\n                F. (2013).\n            Monitoring spike train synchrony. Journal of\n            Neurophysiology, 109(5),\n            1457\u20131472.","DOI":"10.1152\/jn.00873.2012"},{"key":"2022050215131214500_R15","doi-asserted-by":"crossref","unstructured":"Kreuz, T.,\n                Haas, J.\n            S., Morelli,\n                A.,\n                Abarbanel, H. D.\n              I., & Politi,\n                A. (2007).\n            Measuring spike train synchrony. Journal of\n            Neuroscience Methods, 165(1),\n            151\u2013161.","DOI":"10.1016\/j.jneumeth.2007.05.031"},{"key":"2022050215131214500_R16","doi-asserted-by":"crossref","unstructured":"Kreuz, T.,\n                Mulansky,\n              M., &\n                Bozanic,\n            N. (2015).\n            SPIKY: A graphical user interface for monitoring spike train\n            synchrony. Journal of Neurophysiology,\n            113(9),\n          3432\u20133445.","DOI":"10.1152\/jn.00848.2014"},{"key":"2022050215131214500_R17","doi-asserted-by":"crossref","unstructured":"Kumar, P., &\n                Ohana,\n            O. (2008).\n            Inter- and intralaminar subcircuits of excitatory and inhibitory neurons\n            in layer 6a of the rat barrel cortex. Journal of\n            Neurophysiology, 100(4),\n            1909\u20131922.","DOI":"10.1152\/jn.90684.2008"},{"key":"2022050215131214500_R18","doi-asserted-by":"crossref","unstructured":"Magee, J. C.\n           (2000). Dendritic integration of excitatory\n            synaptic input. Nature Reviews Neuroscience,\n            1(3),\n          181\u2013190.","DOI":"10.1038\/35044552"},{"key":"2022050215131214500_R19","doi-asserted-by":"crossref","unstructured":"Mainen, Z. F., &\n                Sejnowski, T.\n              J. (1995).\n            Reliability of spike timing in neocortical neurons.\n            Science, 268(5216),\n            1503\u20131506.","DOI":"10.1126\/science.7770778"},{"key":"2022050215131214500_R20","doi-asserted-by":"crossref","unstructured":"Mulansky, M.,\n                Bozanic,\n            N., Sburlea,\n                A., &\n                Kreuz,\n            T. (2015).\n            A guide to time-resolved and parameter-free measures of spike train\n            synchrony. In IEEE Proceedings of the 1st Int. Conf. on\n            Event-Based Control, Communication, and Signal Processing Poland (pp.\n            1\u20138). Piscataway, NJ:\n            IEEE.","DOI":"10.1109\/EBCCSP.2015.7300693"},{"key":"2022050215131214500_R21","doi-asserted-by":"crossref","unstructured":"Ostojic, S.,\n                Brunel, N.,\n            & Hakim,\n            V. (2009).\n            How connectivity, background activity, and synaptic properties shape the\n            cross-correlation between spike trains. Journal of\n            Neuroscience, 29(33),\n            10234\u201310253.","DOI":"10.1523\/JNEUROSCI.1275-09.2009"},{"key":"2022050215131214500_R22","doi-asserted-by":"crossref","unstructured":"Plesser, H. E., &\n                Tanaka,\n            S. (1997).\n            Stochastic resonance in a model neuron with reset.\n            Physics Letters A, 225,\n            228\u2013234.","DOI":"10.1016\/S0375-9601(96)00878-X"},{"key":"2022050215131214500_R23","doi-asserted-by":"crossref","unstructured":"Ratt\u00e9, S.,\n                Lankarany,\n              M., Rho,\n                Y.-A.,\n                Patterson,\n              A., &\n                Prescott, S.\n              A. (2015).\n            Subthreshold membrane currents confer distinct tuning properties that\n            enable neurons to encode the integral or derivative of their input.\n            Frontiers in Cellular Neuroscience, 8,\n            452.","DOI":"10.3389\/fncel.2014.00452"},{"key":"2022050215131214500_R24","doi-asserted-by":"crossref","unstructured":"Roy, S. A., &\n                Alloway, K.\n              D. (2001).\n            Coincidence detection or temporal integration? What the neurons in\n            somatosensory cortex are doing. Journal of\n          Neuroscience, 21(7),\n            2462\u20132473.","DOI":"10.1523\/JNEUROSCI.21-07-02462.2001"},{"key":"2022050215131214500_R25","doi-asserted-by":"crossref","unstructured":"Rudolph, M., &\n                Destexhe,\n              A. (2001).\n            Correlation detection and resonance in neural systems with distributed\n            noise sources. Physical Review Letters,\n            86(16), 3662\u20133665.","DOI":"10.1103\/PhysRevLett.86.3662"},{"key":"2022050215131214500_R26","doi-asserted-by":"crossref","unstructured":"Rudolph, M., &\n                Destexhe,\n              A. (2003).\n            Tuning neocortical pyramidal neurons between integrators and coincidence\n            detectors. Journal of Computational Neuroscience,\n            14(3),\n          239\u2013251.","DOI":"10.1023\/A:1023245625896"},{"key":"2022050215131214500_R27","doi-asserted-by":"crossref","unstructured":"Sanabria, E. R. G.,\n                Wozniak, K.\n              M., Slusher,\n                B. S., &\n                Keller,\n            A. (2004).\n            GCP II (NAALADase) inhibition suppresses mossy fiber-CA3 synaptic\n            neurotransmission by a presynaptic mechanism. Journal of\n            Neurophysiology, 91(1),\n            182\u2013193.","DOI":"10.1152\/jn.00465.2003"},{"key":"2022050215131214500_R28","doi-asserted-by":"crossref","unstructured":"Scorza, C. A.,\n                Araujo, B. H.\n              S., Leite, L.\n                A., Torres,\n                L. B.,\n                Otalora, L. F.\n              P., Oliveira,\n                M. S., \u2026\n                Cavalheiro, E.\n              A. (2011).\n            Morphological and electrophysiological properties of pyramidal-like\n            neurons in the stratum oriens of Cornu ammonis 1 and Cornu ammonis 2 area of\n            Proechimys. Neuroscience, 177,\n            252\u2013268.","DOI":"10.1016\/j.neuroscience.2010.12.054"},{"key":"2022050215131214500_R29","doi-asserted-by":"crossref","unstructured":"Shadlen, M. N., &\n                Newsome, W.\n              T. (1994).\n            Noise, neural codes and cortical organization.\n            Current Opinion in Neurobiology, 4(4),\n            569\u2013579.","DOI":"10.1016\/0959-4388(94)90059-0"},{"key":"2022050215131214500_R30","doi-asserted-by":"crossref","unstructured":"Shadlen, M. N., &\n                Newsome, W.\n              T. (1998). The\n            variable discharge of cortical neurons: Implications for connectivity, computation, and\n            information coding. Journal of Neuroscience,\n            18(10),\n          3870\u20133896.","DOI":"10.1523\/JNEUROSCI.18-10-03870.1998"},{"key":"2022050215131214500_R31","doi-asserted-by":"crossref","unstructured":"Softky, W. R., &\n                Koch,\n            C. (1993).\n            The highly irregular firing of cortical cells is inconsistent with\n            temporal integration of random EPSPs. Journal of\n            Neuroscience, 13(1),\n            334\u2013350.","DOI":"10.1523\/JNEUROSCI.13-01-00334.1993"},{"key":"2022050215131214500_R32","doi-asserted-by":"crossref","unstructured":"Stevens, C. F., &\n                Zador, A.\n              M. (1998).\n            Input synchrony and the irregular firing of cortical\n            neurons. Nature Neuroscience,\n            1(3),\n          210\u2013217.","DOI":"10.1038\/659"},{"key":"2022050215131214500_R33","doi-asserted-by":"crossref","unstructured":"Tchumatchenko, T.,\n                Malyshev,\n              A., Geisel,\n                T.,\n                Volgushev,\n              M., &\n                Wolf,\n            F. (2010).\n            Correlations and synchrony in threshold neuron models.\n            Physical Review Letters, 104(5),\n            5\u20138.","DOI":"10.1103\/PhysRevLett.104.058102"},{"key":"2022050215131214500_R34","doi-asserted-by":"crossref","unstructured":"Waterhouse, B. D.,\n                Mouradian,\n              R., Sessler,\n                F. M., &\n                Lin, R.\n            C. (2000).\n            Differential modulatory effects of norepinephrine on synaptically driven\n            responses of layer V barrel field cortical neurons. Brain\n            Research, 868(1),\n            39\u201347.","DOI":"10.1016\/S0006-8993(00)02261-7"},{"key":"2022050215131214500_R35","doi-asserted-by":"crossref","unstructured":"Wenning, G., &\n                Obermayer,\n              K. (2003).\n            Activity driven adaptive stochastic resonance.\n            Physical Review Letters, 90(12),\n            120602.","DOI":"10.1103\/PhysRevLett.90.120602"},{"key":"2022050215131214500_R36","doi-asserted-by":"crossref","unstructured":"Williams, S. R., &\n                Stuart, G.\n              J. (2000). Site\n            independence of EPSP time course is mediated by dendritic I(h) in neocortical pyramidal\n            neurons. Journal of Neurophysiology,\n            83(5),\n          3177\u20133182.","DOI":"10.1152\/jn.2000.83.5.3177"}],"container-title":["Neural Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/direct.mit.edu\/neco\/article-pdf\/28\/10\/2091\/2015921\/neco_a_00875.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/direct.mit.edu\/neco\/article-pdf\/28\/10\/2091\/2015921\/neco_a_00875.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T15:13:40Z","timestamp":1651504420000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/neco\/article\/28\/10\/2091\/8198\/Integrator-or-Coincidence-Detector-A-Novel-Measure"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,10,1]]},"references-count":36,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2016,10,1]]},"published-print":{"date-parts":[[2016,10,1]]}},"URL":"https:\/\/doi.org\/10.1162\/neco_a_00875","relation":{},"ISSN":["0899-7667","1530-888X"],"issn-type":[{"value":"0899-7667","type":"print"},{"value":"1530-888X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2016,10]]},"published":{"date-parts":[[2016,10,1]]}}}