Marmoset Auditory Dataset 02 (DataID: 12471)

Authors: Zenas C Chao1*, Misako Komatsu2,3,4*, Madoka Matsumoto5, Kazuki Iijima5, Keiko Nakagaki4, Noritaka Ichinohe4*

1. International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo
2. Institute of Innovative Research, Tokyo Institute of Technology
3. RIKEN Center for Brain Science
4. Department of Ultrastructural Research, National Center of Neurology and Psychiatry
5. Department of Preventive Intervention for Psychiatric Disorders, National Center of Neurology and Psychiatry

*corresponding author: Misako Komatsu (mskkomatsu@gmail.com); Noritaka Ichinohe (nichino@ncnp.go.jp); Zenas C. Chao (zenas.c.chao@gmail.com)

DATASET DESCRIPTION

We adopted a Local-Global paradigm. Two tones with different pitches (Tone A = 800Hz; Tone B = 1600Hz) were synthesized. Each tone was 50 ms in duration. Series of five tones were presented with a 150 ms inter-tone interval, with 950-1150 ms was set between the offset of the last tone of a sequence and the onset of the first tone of the following sequence (see Figure 1A). Four different stimulus blocks were used: AAAAA, BBBBB, AAAAB, and BBBBA blocks. In AAAAA blocks, 20 AAAAA sequences were delivered, followed by a random mixture of 64 AAAAA and 16 AAAAB. In BBBBB blocks, 20 BBBBB sequences were delivered, followed by a random mixture of 64 BBBBB and 16 BBBBA. In AAAAB blocks, 20 AAAAB sequences were delivered, followed by a random mixture of 64 AAAAB and 16 AAAAA. In BBBBA blocks, 20 BBBBA sequences were delivered, followed by a random mixture of 64 BBBBA and 16 BBBBB. In each experimental day, we conducted ECoG recordings on 1~8 blocks, depending on the animal’s condition. For each animal, we performed 7-9 recordings for each block.
Epidural ECoG recordings were taken in the passive listening condition while monkeys were awake.ECoG data were sampled at 1KHz (for Monkey Ji and Rc) or 1017.25Hz (for Monkey Yo, Ca, and Rm).

Data format information can be found on TychoWiki.

CITATION

Chao, Zenas C; Komatsu, Misako; Matsumoto, Madoka; Iijima, Kazuki; Nakagaki, Keiko; Ichinohe, Noritaka : Brain/MINDS Marmoset Brain ECoG Auditory Dataset 02 (DataID: 12471)

RELATED PUBLICATION(S)

Chao ZC; Komatsu M; Matsumoto M; Iijima K; Nakagaki K; Ichinohe N (2024): Diverse Configurations of Erroneous Predictive Coding Across Brain Hierarchies in a Non-Human Primate Model of Autism Spectrum Disorder. Biological Communications 7(1), 851.

LICENSE

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

DOWNLOAD

Data Name Data Type Marmoset ID Condition Download
Ji20181207S4.zip MAT(ECoG96, Event) R03_0024_CM622M RIKEN-HC
Ji20181210S4.zip MAT(ECoG96, Event) R03_0024_CM622M RIKEN-HC
Ji20181210S5.zip MAT(ECoG96, Event) R03_0024_CM622M RIKEN-HC
Ji20181220S4.zip MAT(ECoG96, Event) R03_0024_CM622M RIKEN-HC
Ji20181220S5.zip MAT(ECoG96, Event) R03_0024_CM622M RIKEN-HC
Ji20181227S4.zip MAT(ECoG96, Event) R03_0024_CM622M RIKEN-HC
Ji20181227S7.zip MAT(ECoG96, Event) R03_0024_CM622M RIKEN-HC
Rc20181205S4.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181205S5.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181205S6.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181207S4.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181207S5.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181210S4.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181210S5.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181219S7.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Rc20181219S8.zip MAT(ECoG93, Event) R03_0044_CM997M RIKEN-HC
Yo20190625S3.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Yo20190709S1.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Yo20190709S2.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Yo20190709S3.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Yo20190709S4.zip MAT(ECoG93, TriG) CM16074M NCNP-HC
Yo20190710S1.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Yo20190710S4.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Yo20190712S1.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Yo20200221S1.zip MAT(ECoG96, TriG) CM16074M NCNP-HC
Ca20191224S2.zip MAT(ECoG96,TriG) CM16043M NCNP-VPA
Ca20191225S1.zip MAT(ECoG96, TriG) CM16043M NCNP-VPA
Ca20200127S1.zip MAT(ECoG96, TriG) CM16043M NCNP-VPA
Ca20200210S1.zip MAT(ECoG96, TriG) CM16043M NCNP-VPA
Ca20200214S1.zip MAT(ECoG96, TriG) CM16043M NCNP-VPA
Ca20200225S2.zip MAT(ECoG96, TriG) CM16043M NCNP-VPA
Ca20200226S1.zip MAT(ECoG96, TriG) CM16043M NCNP-VPA
Ca20200227S1.zip MAT(ECoG96, TriG) CM16043M NCNP-VPA
Rm20200127S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200128S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200129S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200131S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200207S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200210S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200218S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200219S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA
Rm20200227S1.zip MAT(ECoG96, TriG) CM17029M NCNP-VPA

[Update history]

2024/07/08: The page was released.