{"podcast":{"title":"Theoretical Neuroscience Podcast","slug":"theoretical-neuroscience-podcast-6657149","podcast_index_feed_id":6657149,"rss_url":"https://feeds.libsyn.com/489902/rss","website_url":"https://www.theoreticalneuroscience.no/","image_url":"https://static.libsyn.com/p/assets/8/9/9/6/8996f0080a40777888c4a68c3ddbc4f2/logo_square.png","author":"Gaute Einevoll","episode_count":42,"summary":"The podcast focuses on topics in theoretical/computational neuroscience and is primarily aimed at students and researchers in the field.","last_synced_at":"2026-06-20T12:20:43.984204+00:00","page_url":"https://stenobird.com/podcast/theoretical-neuroscience-podcast-6657149"},"episode":{"title":"On extracting spiking network models from experiments - with Richard Gao - #38","slug":"on-extracting-spiking-network-models-from-experiments-with-richard-gao-38","published_at":"2026-02-28T06:00:00+00:00","page_url":"https://stenobird.com/podcast/theoretical-neuroscience-podcast-6657149/on-extracting-spiking-network-models-from-experiments-with-richard-gao-38","show_page_url":"https://stenobird.com/podcast/theoretical-neuroscience-podcast-6657149","url":"https://431c9cd0-a1ff-4f9a-ac41-4fca68240d88.libsyn.com/on-extracting-spiking-network-models-from-experiments-with-richard-gao-38","audio_url":"https://traffic.libsyn.com/secure/431c9cd0-a1ff-4f9a-ac41-4fca68240d88/ThN-038-RichardGao_mixdown.mp3?dest-id=4181327","summary":"While some models aim to explain qualitative features of brain activity, other aim to reproduce experimental data quantitatively. If so, model parameters must be adjusted to make the model predictions fit the experimental data. A complication is that in most neurobiological applications, there is not a unique best fit: many parameter combinations give equally good model fits. Recently, the guest, together with colleagues, made the tool AutoMIND to fit spiking network models to data.","meta_description":"While some models aim to explain qualitative features of brain activity, other aim to reproduce experimental data quantitatively. If so, model parameters…","key_points":[],"chapters":[],"topics":[],"duration_seconds":5734,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/theoretical-neuroscience-podcast-6657149/episodes/on-extracting-spiking-network-models-from-experiments-with-richard-gao-38/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/theoretical-neuroscience-podcast-6657149/on-extracting-spiking-network-models-from-experiments-with-richard-gao-38.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}