{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T06:21:16Z","timestamp":1783405276182,"version":"3.54.6"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Comput. Neurosci."],"abstract":"<jats:p>Perceptual distortions are widely observed in various psychiatric diseases, including Autism Spectrum Disorder (ASD). Recent Bayesian models of psychiatric disorders and learning disabilities propose a general theory grounded on the concept of \u201caberrant precision.\u201d However, these models have yet to be used as phenomenological models for visual distortions because previous models usually only deal with a low-dimensional input with Laplace approximation. Such assumptions are necessary for precision to be well-defined; otherwise, the explanation based on aberrant precision was hardly applicable. This study addresses these limitations using the predictive coding-based deep neural network PredNet and a new analysis method inspired by the precision account using the Hilbert-Schmidt Independence Criterion (HSIC). We found that the visual distortion happened when trained with more extended temporal contexts, which was mitigated when we increased the weight of the prediction error of the top layer. From HSIC analysis, we showed that this weight increase enhanced the top-down information flow in prediction, which led to an enhanced ability to capture global features of the visual input, such as rotation and average brightness and hue.<\/jats:p>","DOI":"10.3389\/fncom.2026.1869519","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T05:47:58Z","timestamp":1783403278000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Perceptual distortions in PredNet and quantification of top-down\/bottom-up flow"],"prefix":"10.3389","volume":"20","author":[{"given":"Hiroki","family":"Kojima","sequence":"first","affiliation":[{"name":"Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry","place":["Tokyo, Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keisuke","family":"Suzuki","sequence":"additional","affiliation":[{"name":"Center for Human Nature, Artificial Intelligence, and Neuroscience (CHAIN), Hokkaido University, Sapporo","place":["Hokkaido, Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuichi","family":"Yamashita","sequence":"additional","affiliation":[{"name":"Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry","place":["Tokyo, Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,7]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"47","DOI":"10.3389\/fpsyt.2013.00047","article-title":"The computational anatomy of psychosis","volume":"4","author":"Adams","year":"2013","journal-title":"Front. Psychiatry"},{"key":"B2","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/ICCE-ASIA.2018.8552151","article-title":"\u201cCortexNet: convolutional neural network with visual cortex in human brain,\u201d","author":"Ahmad","year":"2018","journal-title":"2018 IEEE international conference on consumer electronics-Asia (ICCE-Asia)"},{"key":"B3","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.biopsych.2008.03.023","article-title":"Visual perception and its impairment in schizophrenia","volume":"64","author":"Butler","year":"2008","journal-title":"Biol. Psychiatry"},{"key":"B4","doi-asserted-by":"publisher","first-page":"105022","DOI":"10.1016\/j.neubiorev.2022.105022","article-title":"10 years of bayesian theories of autism: a comprehensive review","volume":"145","author":"Chrysaitis","year":"2023","journal-title":"Neurosci. Biobehav. Rev"},{"key":"B5","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1017\/S0140525X12000477","article-title":"Whatever next? Predictive brains, situated agents, and the future of cognitive science","volume":"36","author":"Clark","year":"2013","journal-title":"Behav. Brain Sci"},{"key":"B6","doi-asserted-by":"publisher","first-page":"1226","DOI":"10.1109\/CVPR.2012.6247805","article-title":"\u201cSocial interactions: a first-person perspective,\u201d","author":"Fathi","year":"2012","journal-title":"2012 IEEE conference on computer vision and pattern recognition"},{"key":"B7","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.schres.2018.09.002","article-title":"Color vision impairments in schizophrenia and the role of antipsychotic medication type","volume":"204","author":"Fernandes","year":"2019","journal-title":"Schizophr. Res"},{"key":"B8","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1098\/rstb.2005.1622","article-title":"A theory of cortical responses","volume":"360","author":"Friston","year":"2005","journal-title":"Philos. Trans. R. Soc. B Biol. Sci"},{"key":"B9","doi-asserted-by":"publisher","first-page":"640","DOI":"10.1016\/j.bpsc.2017.08.007","article-title":"Precision psychiatry","volume":"2","author":"Friston","year":"2017","journal-title":"Biol. Psychiatry Cogn. Neurosci. Neuroimaging"},{"key":"B10","doi-asserted-by":"publisher","first-page":"762","DOI":"10.3389\/fpsyt.2020.00762","article-title":"Homogeneous intrinsic neuronal excitability induces overfitting to sensory noise: a robot model of neurodevelopmental disorder","volume":"11","author":"Idei","year":"2020","journal-title":"Front. Psychiatry"},{"key":"B11","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.neunet.2021.01.033","article-title":"Paradoxical sensory reactivity induced by functional disconnection in a robot model of neurodevelopmental disorder","volume":"138","author":"Idei","year":"2021","journal-title":"Neural Netw"},{"key":"B12","doi-asserted-by":"publisher","first-page":"14542","DOI":"10.1038\/s41598-022-18207-7","article-title":"Emergence of sensory attenuation based upon the free-energy principle","volume":"12","author":"Idei","year":"2022","journal-title":"Sci. Rep"},{"key":"B13","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1016\/j.survophthal.2016.02.001","article-title":"Diagnosis, pathophysiology, and treatment of photophobia","volume":"61","author":"Katz","year":"2016","journal-title":"Surv. Ophthalmol"},{"key":"B14","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1016\/j.neuron.2018.10.003","article-title":"Predictive processing: a canonical cortical computation","volume":"100","author":"Keller","year":"2018","journal-title":"Neuron"},{"key":"B15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-022-07438-3","article-title":"Motion illusion-like patterns extracted from photo and art images using predictive deep neural networks","volume":"12","author":"Kobayashi","year":"2022","journal-title":"Sci. Rep"},{"key":"B16","first-page":"3519","article-title":"\u201cSimilarity of neural network representations revisited,\u201d","volume-title":"International conference on machine learning","author":"Kornblith","year":"2019"},{"key":"B17","doi-asserted-by":"publisher","first-page":"302","DOI":"10.3389\/fnhum.2014.00302","article-title":"An aberrant precision account of autism","volume":"8","author":"Lawson","year":"2014","journal-title":"Front. Hum. Neurosci"},{"key":"B18","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1038\/s41593-018-0308-9","article-title":"Perceptual bias reveals slow-updating in autism and fast-forgetting in dyslexia","volume":"22","author":"Lieder","year":"2019","journal-title":"Nat. Neurosci"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1605.08104","article-title":"Deep predictive coding networks for video prediction and unsupervised learning","author":"Lotter","year":"2016","journal-title":"arXiv"},{"key":"B20","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1038\/s42256-020-0170-9","article-title":"A neural network trained for prediction mimics diverse features of biological neurons and perception","volume":"2","author":"Lotter","year":"2020","journal-title":"Nat. Mach. Intell"},{"key":"B21","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3389\/fnhum.2011.00039","article-title":"A Bayesian foundation for individual learning under uncertainty","volume":"5","author":"Mathys","year":"2011","journal-title":"Front. Hum. Neurosci"},{"key":"B22","doi-asserted-by":"publisher","first-page":"825","DOI":"10.3389\/fnhum.2014.00825","article-title":"Uncertainty in perception and the hierarchical gaussian filter","volume":"8","author":"Mathys","year":"2014","journal-title":"Front. Hum. Neurosci"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2107.12979","article-title":"Predictive coding: a theoretical and experimental review","author":"Millidge","year":"2021","journal-title":"arXiv"},{"key":"B24","first-page":"32","article-title":"\u201cComputational analysis of atypical visual perception in autism spectrum disorder: application to perception simulator,\u201d","volume-title":"Proceedings of the 32nd annual meeting of the Japanese cognitive science society","author":"Nagai","year":"2015"},{"key":"B25","doi-asserted-by":"publisher","first-page":"1623","DOI":"10.1177\/0333102418784750","article-title":"Current understanding of photophobia, visual networks and headaches","volume":"39","author":"Noseda","year":"2019","journal-title":"Cephalalgia"},{"key":"B26","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1037\/bul0000097","article-title":"Bayesian approaches to autism: towards volatility, action, and behavior","volume":"143","author":"Palmer","year":"2017","journal-title":"Psychol. Bull"},{"key":"B27","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.neunet.2019.01.012","article-title":"Continual lifelong learning with neural networks: a review","volume":"113","author":"Parisi","year":"2019","journal-title":"Neural Netw"},{"key":"B28","doi-asserted-by":"publisher","first-page":"633037","DOI":"10.3389\/fpsyg.2021.633037","article-title":"Visual sensory experiences from the viewpoint of autistic adults","volume":"12","author":"Parmar","year":"2021","journal-title":"Front. Psychol"},{"key":"B29","doi-asserted-by":"publisher","first-page":"829","DOI":"10.1007\/s13164-021-00604-y","article-title":"From generative models to generative passages: a computational approach to (neuro) phenomenology","volume":"13","author":"Ramstead","year":"2022","journal-title":"Rev. Philos. Psychol"},{"key":"B30","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1145\/3372278.3390694","article-title":"\u201cPredNet and predictive coding: a critical review,\u201d","author":"Rane","year":"2020","journal-title":"Proceedings of the 2020 international conference on multimedia retrieval"},{"key":"B31","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1038\/4580","article-title":"Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects","volume":"2","author":"Rao","year":"1999","journal-title":"Nat. Neurosci"},{"key":"B32","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1038\/nrn.2017.112","article-title":"Sensory perception in autism","volume":"18","author":"Robertson","year":"2017","journal-title":"Nat. Rev. Neurosci"},{"key":"B33","doi-asserted-by":"publisher","first-page":"niaa024","DOI":"10.1093\/nc\/niaa024","article-title":"Neural network models for DMT-induced visual hallucinations","volume":"2020","author":"Schartner","year":"2020","journal-title":"Neurosci. Conscious"},{"key":"B34","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1007\/s11055-015-0103-y","article-title":"Contrast sensitivity in patients with schizophrenia of different durations of illness","volume":"45","author":"Shoshina","year":"2015","journal-title":"Neurosci. Behav. Physiol"},{"key":"B35","doi-asserted-by":"publisher","first-page":"2705","DOI":"10.1016\/j.visres.2009.08.005","article-title":"Vision in autism spectrum disorders","volume":"49","author":"Simmons","year":"2009","journal-title":"Vision Res"},{"key":"B36","doi-asserted-by":"publisher","first-page":"1080668","DOI":"10.3389\/fpsyt.2023.1080668","article-title":"Simulating developmental diversity: impact of neural stochasticity on atypical flexibility and hierarchy","volume":"14","author":"Soda","year":"2023","journal-title":"Front. Psychiatry"},{"key":"B37","doi-asserted-by":"publisher","first-page":"2564","DOI":"10.1587\/transinf.E95.D.2564","article-title":"On kernel parameter selection in hilbert-schmidt independence criterion","volume":"95","author":"Sugiyama","year":"2012","journal-title":"IEICE Trans. Inf. Syst"},{"key":"B38","doi-asserted-by":"publisher","first-page":"15982","DOI":"10.1038\/s41598-017-16316-2","article-title":"A Deep-Dream virtual reality platform for studying altered perceptual phenomenology","volume":"7","author":"Suzuki","year":"2017","journal-title":"Sci. Rep"},{"key":"B39","doi-asserted-by":"publisher","first-page":"1159821","DOI":"10.3389\/fnhum.2023.1159821","article-title":"Modelling phenomenological differences in aetiologically distinct visual hallucinations using deep neural networks","volume":"17","author":"Suzuki","year":"2024","journal-title":"Front. Hum. Neurosci"},{"key":"B40","doi-asserted-by":"publisher","first-page":"14684","DOI":"10.1038\/s41598-021-94067-x","article-title":"Neural network modeling of altered facial expression recognition in autism spectrum disorders based on predictive processing framework","volume":"11","author":"Takahashi","year":"2021","journal-title":"Sci. Rep"},{"key":"B41","first-page":"1","article-title":"\u201cChainer: a next-generation open source framework for deep learning,\u201d","volume-title":"Proceedings of workshop on machine learning systems (LearningSys) in the twenty-ninth annual conference on neural information processing systems (NIPS)","author":"Tokui","year":"2015"},{"key":"B42","doi-asserted-by":"publisher","first-page":"345","DOI":"10.3389\/fpsyg.2018.00345","article-title":"Illusory motion reproduced by deep neural networks trained for prediction","volume":"9","author":"Watanabe","year":"2018","journal-title":"Front. Psychol"},{"key":"B43","first-page":"5266","article-title":"\u201cDeep predictive coding network for object recognition,\u201d","volume-title":"International conference on machine learning","author":"Wen","year":"2018"},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.05408","article-title":"\u201cDependency bottleneck\u201d","author":"Wu","year":"2018"},{"key":"B45","doi-asserted-by":"publisher","first-page":"19145","DOI":"10.52202\/075280-0839","article-title":"Statistical insights into HSIC in high dimensions","volume":"36","author":"Zhang","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst"}],"container-title":["Frontiers in Computational Neuroscience"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fncom.2026.1869519\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T05:48:01Z","timestamp":1783403281000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fncom.2026.1869519\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,7]]},"references-count":45,"alternative-id":["10.3389\/fncom.2026.1869519"],"URL":"https:\/\/doi.org\/10.3389\/fncom.2026.1869519","relation":{},"ISSN":["1662-5188"],"issn-type":[{"value":"1662-5188","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,7]]},"article-number":"1869519"}}