{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T07:40:10Z","timestamp":1748331610939,"version":"3.41.0"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000015","name":"U.S. Department of Energy","doi-asserted-by":"publisher","award":["DE-SC0023391"],"award-info":[{"award-number":["DE-SC0023391"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1751230"],"award-info":[{"award-number":["1751230"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Implementations of neurons, delays, and synapse circuits are presented with simulations. These neural elements are used to create two small spiking neural networks, the Rate-Window and Order-Biased clusters, which are capable of detecting simple two-spike spatiotemporal patterns. A simple pattern detecting network (SPDN) is created by combining the Rate-Window and Order-Biased clusters, where clusters are small spiking neural networks, and its simple pattern detection ability is demonstrated in simulation. The SPDN is used to implement a complex pattern detecting network (CPDN) and its complex pattern detection ability is demonstrated in simulation. Methods for generating arbitrary spatiotemporal patterns are presented. The CPDN and spatiotemporal pattern generation methods are then used to implement a novel spatiotemporal computing paradigm based on detecting and responding to spatiotemporal symbols. A simulation of a spatiotemporal half adder is presented to demonstrate the computing paradigm.<\/jats:p>","DOI":"10.1007\/s00521-025-11046-3","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T13:49:32Z","timestamp":1741268972000},"page":"9621-9637","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatiotemporal pattern detection, generation, and computation with circuits"],"prefix":"10.1007","volume":"37","author":[{"given":"Robert C.","family":"Ivans","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0254-4346","authenticated-orcid":false,"given":"Kurtis D.","family":"Cantley","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,3,6]]},"reference":[{"issue":"5014","key":"11046_CR1","doi-asserted-by":"publisher","first-page":"1854","DOI":"10.1126\/science.2063199","volume":"252","author":"W Bialek","year":"1991","unstructured":"Bialek W, Rieke F, Van Steveninck RDR, Warland D (1991) Reading a neural code. Science 252(5014):1854\u20131857","journal-title":"Science"},{"issue":"4","key":"11046_CR2","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/BF00197657","volume":"169","author":"MH Holmqvist","year":"1991","unstructured":"Holmqvist MH, Srinivasan MV (1991) A visually evoked escape response of the housefly. J Comp Physiol A 169(4):451\u2013459","journal-title":"J Comp Physiol A"},{"key":"11046_CR3","first-page":"18","volume":"4","author":"B Glackin","year":"2010","unstructured":"Glackin B, Wall JA, McGinnity TM, Maguire LP, McDaid LJ (2010) A spiking neural network model of the medial superior olive using spike timing dependent plasticity for sound localization. Front Comput Neurosci 4:18","journal-title":"Front Comput Neurosci"},{"issue":"6","key":"11046_CR4","doi-asserted-by":"publisher","first-page":"1235","DOI":"10.1016\/S0896-6273(00)80643-1","volume":"21","author":"PX Joris","year":"1998","unstructured":"Joris PX, Smith PH, Yin TC (1998) Coincidence detection in the auditory system: 50 years after jeffress. Neuron 21(6):1235\u20131238","journal-title":"Neuron"},{"issue":"10","key":"11046_CR5","doi-asserted-by":"publisher","first-page":"3227","DOI":"10.1523\/JNEUROSCI.10-10-03227.1990","volume":"10","author":"C Carr","year":"1990","unstructured":"Carr C, Konishi M (1990) A circuit for detection of interaural time differences in the brain stem of the barn owl. J Neurosci 10(10):3227\u20133246","journal-title":"J Neurosci"},{"issue":"4","key":"11046_CR6","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/BF02478259","volume":"5","author":"WS McCulloch","year":"1943","unstructured":"McCulloch WS, Pitts W (1943) A logical calculus of the ideas immanent in nervous activity. Bull Math Biophys 5(4):115\u2013133","journal-title":"Bull Math Biophys"},{"key":"11046_CR7","doi-asserted-by":"publisher","unstructured":"Turing AM (1950) I.-computing machinery and intelligence. Mind LIX (236), 433\u2013460 https:\/\/doi.org\/10.1093\/mind\/LIX.236.433","DOI":"10.1093\/mind\/LIX.236.433"},{"key":"11046_CR8","doi-asserted-by":"crossref","unstructured":"Rosenblatt F (1961) Principles of neurodynamics. perceptrons and the theory of brain mechanisms. Technical report, Cornell Aeronautical Lab Inc Buffalo NY","DOI":"10.21236\/AD0256582"},{"key":"11046_CR9","unstructured":"Mead C (1989) Analog VLSI and neural systems. Addison-Wesley Longman Publishing Co., Inc, United States of America"},{"issue":"5","key":"11046_CR10","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1109\/JPROC.2014.2313565","volume":"102","author":"BV Benjamin","year":"2014","unstructured":"Benjamin BV, Gao P, McQuinn E, Choudhary S, Chandrasekaran AR, Bussat J-M, Alvarez-Icaza R, Arthur JV, Merolla PA, Boahen K (2014) Neurogrid: a mixed-analog-digital multichip system for large-scale neural simulations. Proc IEEE 102(5):699\u2013716","journal-title":"Proc IEEE"},{"issue":"5","key":"11046_CR11","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1109\/JPROC.2014.2304638","volume":"102","author":"SB Furber","year":"2014","unstructured":"Furber SB, Galluppi F, Temple S, Plana LA (2014) The spinnaker project. Proc IEEE 102(5):652\u2013665","journal-title":"Proc IEEE"},{"key":"11046_CR12","doi-asserted-by":"crossref","unstructured":"Schemmel J, Fieres J, Meier K (2008) Wafer-scale integration of analog neural networks. In: 2008 IEEE international joint conference on neural networks (IEEE world congress on computational intelligence). IEEE, pp 431\u2013438","DOI":"10.1109\/IJCNN.2008.4633828"},{"issue":"6197","key":"11046_CR13","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1126\/science.1254642","volume":"345","author":"PA Merolla","year":"2014","unstructured":"Merolla PA, Arthur JV, Alvarez-Icaza R, Cassidy AS, Sawada J, Akopyan F, Jackson BL, Imam N, Guo C, Nakamura Y et al (2014) A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 345(6197):668\u2013673","journal-title":"Science"},{"issue":"1","key":"11046_CR14","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/MM.2018.112130359","volume":"38","author":"M Davies","year":"2018","unstructured":"Davies M, Srinivasa N, Lin T-H, Chinya G, Cao Y, Choday SH, Dimou G, Joshi P, Imam N, Jain S et al (2018) Loihi: a neuromorphic manycore processor with on-chip learning. IEEE Micro 38(1):82\u201399","journal-title":"IEEE Micro"},{"issue":"05","key":"11046_CR15","doi-asserted-by":"publisher","first-page":"1733","DOI":"10.1142\/S0218127409023809","volume":"19","author":"EM Izhikevich","year":"2009","unstructured":"Izhikevich EM, Hoppensteadt FC (2009) Polychronous wavefront computations. Int J Bifurc Chaos 19(05):1733\u20131739","journal-title":"Int J Bifurc Chaos"},{"issue":"11","key":"11046_CR16","doi-asserted-by":"publisher","first-page":"2261","DOI":"10.1162\/NECO_a_00783","volume":"27","author":"X Lagorce","year":"2015","unstructured":"Lagorce X, Benosman R (2015) Stick: Spike time interval computational kernel, a framework for general purpose computation using neurons, precise timing, delays, and synchrony. Neural Comput 27(11):2261\u20132317","journal-title":"Neural Comput"},{"key":"11046_CR17","doi-asserted-by":"publisher","unstructured":"Cantley KD, Ivans RC, Subramaniam A, Vogel EM (2017) Spatio-temporal pattern recognition in neural circuits with memory-transistor-driven memristive synapses. In: 2017 International joint conference on neural networks (IJCNN), pp 4633\u20134640. https:\/\/doi.org\/10.1109\/IJCNN.2017.7966444","DOI":"10.1109\/IJCNN.2017.7966444"},{"issue":"1","key":"11046_CR18","doi-asserted-by":"publisher","first-page":"1377","DOI":"10.1371\/journal.pone.0001377","volume":"3","author":"T Masquelier","year":"2008","unstructured":"Masquelier T, Guyonneau R, Thorpe SJ (2008) Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains. PLoS ONE 3(1):1377","journal-title":"PLoS ONE"},{"issue":"10","key":"11046_CR19","doi-asserted-by":"publisher","first-page":"4206","DOI":"10.1109\/TNNLS.2019.2952768","volume":"31","author":"RC Ivans","year":"2019","unstructured":"Ivans RC, Dahl SG, Cantley KD (2019) A model for $$ r (t) $$ elements and $$ r (t) $$-based spike-timing-dependent plasticity with basic circuit examples. IEEE Trans Neural Netw Learn Syst 31(10):4206\u20134216","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"2","key":"11046_CR20","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1109\/JETCAS.2015.2433552","volume":"5","author":"X Wu","year":"2015","unstructured":"Wu X, Saxena V, Zhu K (2015) Homogeneous spiking neuromorphic system for real-world pattern recognition. IEEE J Emerg Sel Top Circuits Syst 5(2):254\u2013266","journal-title":"IEEE J Emerg Sel Top Circuits Syst"},{"issue":"1","key":"11046_CR21","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/TBCAS.2008.2005781","volume":"3","author":"S Mitra","year":"2008","unstructured":"Mitra S, Fusi S, Indiveri G (2008) Real-time classification of complex patterns using spike-based learning in neuromorphic VLSI. IEEE Trans Biomed Circuits Syst 3(1):32\u201342","journal-title":"IEEE Trans Biomed Circuits Syst"},{"issue":"11","key":"11046_CR22","doi-asserted-by":"publisher","first-page":"78318","DOI":"10.1371\/journal.pone.0078318","volume":"8","author":"Q Yu","year":"2013","unstructured":"Yu Q, Tang H, Tan KC, Li H (2013) Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns. PLoS ONE 8(11):78318","journal-title":"PLoS ONE"},{"key":"11046_CR23","doi-asserted-by":"crossref","unstructured":"Diehl PU, Neil D, Binas J, Cook M, Liu S-C, Pfeiffer M (2015) Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. In: 2015 international joint conference on neural networks (IJCNN). IEEE, pp 1\u20138","DOI":"10.1109\/IJCNN.2015.7280696"},{"issue":"3","key":"11046_CR24","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1109\/TNNLS.2015.2416771","volume":"27","author":"Q Yu","year":"2015","unstructured":"Yu Q, Yan R, Tang H, Tan KC, Li H (2015) A spiking neural network system for robust sequence recognition. IEEE Trans Neural Netw Learn Syst 27(3):621\u2013635","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"11046_CR25","doi-asserted-by":"publisher","unstructured":"Gautam A, Kohno T (2023) Adaptive stdp-based on-chip spike pattern detection. Front Neurosci 17. https:\/\/doi.org\/10.3389\/fnins.2023.1203956","DOI":"10.3389\/fnins.2023.1203956"},{"key":"11046_CR26","doi-asserted-by":"publisher","unstructured":"Ivans R, Cantley KD (2019) A spatiotemporal pattern detector. In: 2019 IEEE 62nd international midwest symposium on circuits and systems (MWSCAS), pp 444\u2013447. https:\/\/doi.org\/10.1109\/MWSCAS.2019.8884799","DOI":"10.1109\/MWSCAS.2019.8884799"},{"key":"11046_CR27","doi-asserted-by":"crossref","unstructured":"Gavrilov AV, Maliavko AA, Yakimenko AA (2017) Key-threshold based spiking neural network. In: 2017 second Russia and pacific conference on computer technology and applications (RPC). IEEE, pp 64\u201367","DOI":"10.1109\/RPC.2017.8168069"},{"key":"11046_CR28","unstructured":"Vogt H, Hendrix M, Nenzi P (2019) Ngspice Users Manual Version 30 (Describes ngspice release version) . http:\/\/ngspice.sourceforge.net\/docs\/ngspice-30-manual.pdf"},{"key":"11046_CR29","unstructured":"BSIM4\u2014BSIM Group (2016). http:\/\/bsim.berkeley.edu\/models\/bsim4\/"},{"key":"11046_CR30","doi-asserted-by":"publisher","unstructured":"Rahmatinezhad M, Ahmadi A, Ahmadi M (2024) A neural assembly-based state machine design. In: 2024 IEEE 67th international midwest symposium on circuits and systems (MWSCAS), pp 656\u2013659. https:\/\/doi.org\/10.1109\/MWSCAS60917.2024.10658665","DOI":"10.1109\/MWSCAS60917.2024.10658665"},{"issue":"4","key":"11046_CR31","doi-asserted-by":"publisher","first-page":"859","DOI":"10.1162\/0899766053429390","volume":"17","author":"R Guyonneau","year":"2005","unstructured":"Guyonneau R, VanRullen R, Thorpe SJ (2005) Neurons tune to the earliest spikes through stdp. Neural Comput 17(4):859\u2013879","journal-title":"Neural Comput"},{"key":"11046_CR32","doi-asserted-by":"publisher","unstructured":"Kumar P, Bhandari NS, Bhargav L, Rathi R, Yadav SC (2017) Design of low power and area efficient half adder using pass transistor and comparison of various performance parameters. In: 2017 international conference on computing, communication and automation (ICCCA), pp 1477\u20131482. https:\/\/doi.org\/10.1109\/CCAA.2017.8230033","DOI":"10.1109\/CCAA.2017.8230033"},{"key":"11046_CR33","doi-asserted-by":"publisher","first-page":"2057","DOI":"10.5829\/idosi.wasj.2014.31.12.651","volume":"31","author":"M Sadeghi","year":"2014","unstructured":"Sadeghi M, Golmakani A (2014) Two new topologies for low-power half-adder in 180nm cmos technology. World Appl Sci J 31:2057\u20132061. https:\/\/doi.org\/10.5829\/idosi.wasj.2014.31.12.651","journal-title":"World Appl Sci J"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-025-11046-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-025-11046-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-025-11046-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T07:07:45Z","timestamp":1748329665000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-025-11046-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,6]]},"references-count":33,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["11046"],"URL":"https:\/\/doi.org\/10.1007\/s00521-025-11046-3","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2025,3,6]]},"assertion":[{"value":"2 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 January 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 March 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}