Dopamine Modulation of Spike-Timing-Dependent Plasticity for Spatio-Temporal Spike Pattern Detection in Single Neurons

preprint OA: closed
Full text JSON View at publisher

Abstract

A bstract Dopamine (DA) is an important neuromodulator that has been suggested to play key roles in a range of neuropsychiatric disorders. However, its computational impact at the neural circuit level has not been elucidated. Here, we extended a spike-timing-dependent plasticity (STDP)-based single-neuron spatio-temporal pattern detection model by incorporating a DA input and DA-type STDP modulation. We analyzed the direct effect of the DA-type STDP curve and the effect of DA release. We found that the DhA-type STDP curve accelerates learning but may promote coarse potentiation of the synaptic efficacy, which leads to false detections. It was also shown that DA can improve the pattern-detection performance up to a 44 % success rate (2.44 × control) with no false detection, but a DA release with an excessive amount or with too short a delay induces false detection. These results suggest that DA can maintain the pattern detection ability only when released within a limited concentration and a sufficient delay.
Full text 1,198 characters · extracted from oa-doi-fallback · click to expand
Abstract Dopamine (DA) is an important neuromodulator that has been suggested to play key roles in a range of neuropsychiatric disorders. However, its computational impact at the neural circuit level has not been elucidated. Here, we extended a spike-timing-dependent plasticity (STDP)-based single-neuron spatio-temporal pattern detection model by incorporating a DA input and DA-type STDP modulation. We analyzed the direct effect of the DA-type STDP curve and the effect of DA release. We found that the DhA-type STDP curve accelerates learning but may promote coarse potentiation of the synaptic efficacy, which leads to false detections. It was also shown that DA can improve the pattern-detection performance up to a 44 % success rate (2.44 × control) with no false detection, but a DA release with an excessive amount or with too short a delay induces false detection. These results suggest that DA can maintain the pattern detection ability only when released within a limited concentration and a sufficient delay. Competing Interest Statement The authors have declared no competing interest. Footnotes ayakakotajima{at}gmail.com furuichi{at}g.ecc.u-tokyo.ac.jp kohno{at}g.ecc.u-tokyo.ac.jp

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00