Behavior discrimination using a discrete wavelet based approach for feature extraction on local field potentials in the cortex and striatum

Jovana J Belić, Pär Halje, Ulrike Richter, Per Petersson, Jeanette Hellgren Kotaleski

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review

Sammanfattning

Linkage between behavioral states and neural activity is one of the most important challenges in neuroscience. The network activity patterns in the awake resting state and in the actively behaving state in rodents are not well understood, and a better tool for differentiating these states can provide insights on healthy brain functions and its alteration with disease. Therefore, we simultaneously recorded local field potentials (LFPs) bilaterally in motor cortex and striatum, and measured locomotion from healthy, freely behaving rats. Here we analyze spectral characteristics of the obtained signals and present an algorithm for automatic discrimination of the awake resting and the behavioral states. We used the Support Vector Machine (SVM) classifier and utilized features obtained by applying discrete wavelet transform (DWT) on LFPs, which arose as a solution with high accuracy.

Originalspråkengelska
Titel på värdpublikation7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
FörlagIEEE Computer Society
Sidor964-967
ISBN (elektroniskt)9781467363891
DOI
StatusPublished - 2015 juli 1
Evenemang7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, Frankrike
Varaktighet: 2015 apr. 222015 apr. 24

Konferens

Konferens7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
Land/TerritoriumFrankrike
OrtMontpellier
Period2015/04/222015/04/24

Ämnesklassifikation (UKÄ)

  • Neurovetenskaper
  • Annan medicinteknik

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