{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T22:32:48Z","timestamp":1761863568768},"reference-count":55,"publisher":"MIT Press - Journals","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2016,9]]},"abstract":"<jats:p> The free-energy principle is a candidate unified theory for learning and memory in the brain that predicts that neurons, synapses, and neuromodulators work in a manner that minimizes free energy. However, electrophysiological data elucidating the neural and synaptic bases for this theory are lacking. Here, we propose a novel theory bridging the information-theoretical principle with the biological phenomenon of spike-timing dependent plasticity (STDP) regulated by neuromodulators, which we term mSTDP. We propose that by integrating an mSTDP equation, we can obtain a form of Friston\u2019s free energy (an information-theoretical function). Then we analytically and numerically show that dopamine (DA) and noradrenaline (NA) influence the accuracy of a principal component analysis (PCA) performed using the mSTDP algorithm. From the perspective of free-energy minimization, these neuromodulatory changes alter the relative weighting or precision of accuracy and prior terms, which induces a switch from pattern completion to separation. These results are consistent with electrophysiological findings and validate the free-energy principle and mSTDP. Moreover, our scheme can potentially be applied in computational psychiatry to build models of the faulty neural networks that underlie the positive symptoms of schizophrenia, which involve abnormal DA levels, as well as models of the NA contribution to memory triage and posttraumatic stress disorder. <\/jats:p>","DOI":"10.1162\/neco_a_00862","type":"journal-article","created":{"date-parts":[[2016,7,8]],"date-time":"2016-07-08T22:21:25Z","timestamp":1468016485000},"page":"1859-1888","source":"Crossref","is-referenced-by-count":8,"title":["Linking Neuromodulated Spike-Timing Dependent Plasticity with the Free-Energy Principle"],"prefix":"10.1162","volume":"28","author":[{"given":"Takuya","family":"Isomura","sequence":"first","affiliation":[{"name":"Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, University of Tokyo, Tokyo 113-8656, Japan, and Japan Society for the Promotion of Science, Tokyo 102-0083, Japan"}]},{"given":"Koji","family":"Sakai","sequence":"additional","affiliation":[{"name":"Department of Precision Engineering, School of Engineering, University of Tokyo, 113-8656, Japan"}]},{"given":"Kiyoshi","family":"Kotani","sequence":"additional","affiliation":[{"name":"Research Center for Advanced Science and Technology, University of Tokyo, Tokyo 153-8904, Japan, and PRESTO, Japan Science and Technology Agency, Saitama 332-0012, Japan"}]},{"given":"Yasuhiko","family":"Jimbo","sequence":"additional","affiliation":[{"name":"Department of Precision Engineering, School of Engineering, University of Tokyo, Tokyo 113-8656, Japan"}]}],"member":"281","reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00365229"},{"key":"B2","first-page":"757","volume-title":"Advances in neural information processing systems","volume":"8","author":"Amari S. 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