CITATION.cff

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title: Adaptive-SWTTEO
message: >-
  Local spike detection algorithm for extracellular neural
  signals. 
type: software
authors:
  - given-names: Tommaso
    family-names: Lambresa
    orcid: 'https://orcid.org/0009-0004-9201-6217'
  - given-names: Federico
    family-names: Barban
    email: federico.barban@unige.it
    orcid: 'https://orcid.org/0000-0002-5828-0282'
  - given-names: Michela
    family-names: Chiappalone
    orcid: 'https://orcid.org/0000-0003-1427-5147'
repository-code: 'https://github.com/barbaLab/Adaptive-SWTTEO'
abstract: >-
  Here we present a novel Matlab-based spike detection
  algorithm, Adaptive-SWTTEO, inspired by an existing method
  that has demonstrated superior performance compared to
  other approaches. The new algorithm’s performance was
  evaluated against the original method using a custom
  synthetic dataset that included both non-bursting and
  bursting neural activity. Results showed that the
  Adaptive-SWTTEO outperformed the original algorithm in
  terms of detection efficiency, reliability and speed.
license: LGPL-3.0+