Logo do repositório
  • Página Inicial(current)
  • Buscar
    Por Data de PublicaçãoPor AutorPor TítuloPor Assunto
  • Tutoriais
  • Documentos
  • Sobre o RI
  • Eventos
    Repositório Institucional da UFRN: 15 anos de conexão com o conhecimento
  • Padrão
  • Amarelo
  • Azul
  • Verde
  • English
  • Português do Brasil
Entrar

SIGAA

  1. Início
  2. Pesquisar por Autor

Navegando por Autor "Huang, Yadong"

Filtrar resultados informando as primeiras letras
Agora exibindo 1 - 1 de 1
  • Resultados por página
  • Opções de Ordenação
  • Nenhuma Miniatura disponível
    Artigo
    Waveform-based classification of dentate spikes
    (Springer Science and Business Media LLC, 2024-02) Santiago, Rodrigo Marques de Melo; Santos, Vítor Lopes dos; Jones, Emily A. Aery; Huang, Yadong; Dupret, David; Tort, Adriano Bretanha Lopes
    Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer’s disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing
Repositório Institucional - UFRN Campus Universitário Lagoa NovaCEP 59078-970 Caixa postal 1524 Natal/RN - BrasilUniversidade Federal do Rio Grande do Norte© Copyright 2025. Todos os direitos reservados.
Contato+55 (84) 3342-2260 - R232Setor de Repositórios Digitaisrepositorio@bczm.ufrn.br
DSpaceIBICT
OasisBR
LAReferencia
Customizado pela CAT - BCZM