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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Psychiatric Illnesses as Disorders of Network Dynamics · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1809.06303/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1809.06303/feed.xml" rel="self" type="application/rss+xml" /><item><title>Psychiatric Illnesses as Disorders of Network Dynamics — mentioned by outlace</title><link>https://news.ycombinator.com/item?id=20834053</link><guid isPermaLink="false">urn:hackerpapers:mention:1809.06303:20834053</guid><pubDate>Thu, 29 Aug 2019 21:50:27 GMT</pubDate><description>&lt;p&gt;My inspiration comes from this: https://arxiv.org/pdf/1809.06303.pdf There&amp;#x27;s a long history of using differential equation models to model high-level brain function (see also neural mass models and neural field models) but I think there are advantages to using discrete time approximations such as neural networks in an RL setting to investigate how the dynamics (e.g. attractor states, etc) map onto behavior.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1809.06303/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>q-bio.NC</category></item></channel></rss>
