{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T06:03:27Z","timestamp":1784527407392,"version":"3.55.0"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"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:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive behaviors, with incomplete response to current treatments suggesting limitations in prevailing neurotransmitter-focused models. Epidemiological data indicate lifetime DSM-IV OCD in approximately 2.3% and 12-month OCD in approximately 1.2% of US adults, while subthreshold obsessions or compulsions are substantially more common. One mechanistic possibility is that abnormal synaptic pruning contributes to persistent cortico-striato-thalamo-cortical circuit rigidity. This idea remains indirect in OCD, but is supported by convergent synaptic-marker findings in OCD and by complement-linked pruning mechanisms shown most clearly in schizophrenia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed a modular gated recurrent unit network approximating cortico-striato-thalamo-cortical dynamics, trained on a rule-switching task sensitive to perseveration. The architecture included a recurrent cortical integration layer, a schematic striatal \u201chabit\u201d module, and a thalamic confidence-gating scalar. Excessive pruning was implemented as 60% activity-dependent pruning, using a composite of low recent gradient-based usage and low weight magnitude, with partial protection of recurrent and habit-related weights. From identical pruned baselines, three mechanistically distinct interventions were simulated: rapid gradient-guided structural reopening, treated as a ketamine-like synaptogenesis motif, prolonged low-learning-rate adaptation with stress-noise annealing (SSRI-like), and tonic inhibitory scaling (neurosteroid-like). An iso-dose pipeline recorded L1 and L2 weight-change norms, synaptic turnover, and change in sparsity; linear interpolation was used when bracketing sweep points existed, and residual mismatch was reported otherwise. Multi-seed statistics and sensitivity analyses were performed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>At 60% activity-dependent pruning, the untreated network showed impaired accuracy (0.4972) and elevated perseveration (0.5247). In the fixed-parameter comparison, ketamine-like structural repair reduced perseveration to 0.2582, SSRI-like adaptation to 0.3209, and neurosteroid-like inhibition to 0.2654. Relapse vulnerability differed by mechanism: cumulative relapse increased perseveration by +0.1086 after ketamine-like repair, +0.0259 after SSRI-like adaptation, and \u22120.0017 after neurosteroid-like inhibition in the representative seed. Across five seeds, best acute perseveration was lowest for ketamine-like repair (0.2330\u202f\u00b1\u202f0.0065), followed by neurosteroid-like inhibition (0.2413\u202f\u00b1\u202f0.0021) and SSRI-like adaptation (0.2831\u202f\u00b1\u202f0.0099). SSRI-like adaptation showed the highest mean efficiency because it produced smaller absolute weight changes. Sensitivity analyses showed that untreated perseveration increased with pruning severity, from 0.2627 at 40% pruning to 0.6218 at 70% pruning, while ketamine-like repair remained relatively stable across the same range.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These findings support excessive synaptic pruning as a plausible contributor to OCD-like cognitive inflexibility and illustrate that structural and functional interventions offer different trade-offs within a highly abstract computational model. Structural repair produced the most robust acute rescue and remained resilient across pruning severities, whereas functional mechanisms showed advantages in dose efficiency or relapse stability. The results are hypothesis-generating only and should not be read as clinical evidence for treatment ranking.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fncom.2026.1799705","type":"journal-article","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T05:33:55Z","timestamp":1784525635000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Structural synaptogenesis superior to functional modulation in a pruning-based recurrent network model of OCD"],"prefix":"10.3389","volume":"20","author":[{"given":"Ngo","family":"Cheung","sequence":"first","affiliation":[{"name":"Independent Researcher","place":["Hong Kong, Hong Kong SAR, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,20]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1136\/jnnp-2015-310737","article-title":"Computational psychiatry: towards a mathematically informed understanding of mental illness","volume":"87","author":"Adams","year":"2016","journal-title":"J. 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