Big data approaches to identifying sex differences in long-term memory.
Big data approaches to identifying sex differences in long-term memory.
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DOI：
10.1080/17588928.2020.1866520
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发表时间：
2021-07
影响因子：
2
通讯作者：
Scheinost D
中科院分区：
文献类型：
--
作者：
Tejavibulya L;Scheinost D
无论是神经递质还是大规模电路。性别差异一直是神经科学的兴趣所在。Spets和Slotnick对长期记忆的fMRI研究进行了荟萃分析，以确定大脑行为关联中的性别差异，表明性别差异在长期记忆的许多子类型中普遍存在。荟萃分析是一种工具，可以聚合更大的样本量，以更全面地了解这些主题。然而，更多的研究对于阐明fMRI信号如何转化为行为结果的复杂关系至关重要。我们建议大数据和开放科学作为一种解决方案，以找到大脑行为关联中的强大性别差异。
Whether in neurotransmitters or large-scale circuits. Sex differences have long been of interest in neuroscience. Spets and Slotnick conducted a meta-analysis of fMRI studies of long-term memory to identify sex differences in brain-behavior associations, demonstrating that sex differences are pervasive across many sub-types of long-term memory. Meta-analyses are a workhorse towards aggregating larger sample sizes to arrive at a more comprehensive understanding of such topics. However, more research is crucial to elucidate complex relationships in how fMRI signals translate to behavioral outcomes. We propose that big data and open-science as a solution towards finding robust sex differences in brain-behavior associations.
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影响因子：
14.8
作者：
Shen X;Finn ES;Scheinost D;Rosenberg MD;Chun MM;Papademetris X;Constable RT
通讯作者：
Constable RT
DOI：
10.1093/cercor/bhy109
发表时间：
2018-08-01
期刊：
Cerebral cortex (New York, N.Y. : 1991)
影响因子：
--
作者：
Ritchie SJ;Cox SR;Shen X;Lombardo MV;Reus LM;Alloza C;Harris MA;Alderson HL;Hunter S;Neilson E;Liewald DCM;Auyeung B;Whalley HC;Lawrie SM;Gale CR;Bastin ME;McIntosh AM;Deary IJ
通讯作者：
Deary IJ
基于连接组的个体化智商和子领域分数预测中的性别差异。
影响因子：
3.7
作者：
Jiang, Rongtao;Calhoun, Vince D.;Sui, Jing
通讯作者：
Sui, Jing
影响因子：
5.7
作者：
Noble S;Scheinost D;Constable RT
通讯作者：
Constable RT
许多团队对单个神经影像数据集的分析存在差异
影响因子：
64.8
作者：
Botvinik-Nezer R;Holzmeister F;Camerer CF;Dreber A;Huber J;Johannesson M;Kirchler M;Iwanir R;Mumford JA;Adcock RA;Avesani P;Baczkowski BM;Bajracharya A;Bakst L;Ball S;Barilari M;Bault N;Beaton D;Beitner J;Benoit RG;Berkers RMWJ;Bhanji JP;Biswal BB;Bobadilla-Suarez S;Bortolini T;Bottenhorn KL;Bowring A;Braem S;Brooks HR;Brudner EG;Calderon CB;Camilleri JA;Castrellon JJ;Cecchetti L;Cieslik EC;Cole ZJ;Collignon O;Cox RW;Cunningham WA;Czoschke S;Dadi K;Davis CP;Luca A;Delgado MR;Demetriou L;Dennison JB;Di X;Dickie EW;Dobryakova E;Donnat CL;Dukart J;Duncan NW;Durnez J;Eed A;Eickhoff SB;Erhart A;Fontanesi L;Fricke GM;Fu S;Galván A;Gau R;Genon S;Glatard T;Glerean E;Goeman JJ;Golowin SAE;González-García C;Gorgolewski KJ;Grady CL;Green MA;Guassi Moreira JF;Guest O;Hakimi S;Hamilton JP;Hancock R;Handjaras G;Harry BB;Hawco C;Herholz P;Herman G;Heunis S;Hoffstaedter F;Hogeveen J;Holmes S;Hu CP;Huettel SA;Hughes ME;Iacovella V;Iordan AD;Isager PM;Isik AI;Jahn A;Johnson MR;Johnstone T;Joseph MJE;Juliano AC;Kable JW;Kassinopoulos M;Koba C;Kong XZ;Koscik TR;Kucukboyaci NE;Kuhl BA;Kupek S;Laird AR;Lamm C;Langner R;Lauharatanahirun N;Lee H;Lee S;Leemans A;Leo A;Lesage E;Li F;Li MYC;Lim PC;Lintz EN;Liphardt SW;Losecaat Vermeer AB;Love BC;Mack ML;Malpica N;Marins T;Maumet C;McDonald K;McGuire JT;Melero H;Méndez Leal AS;Meyer B;Meyer KN;Mihai G;Mitsis GD;Moll J;Nielson DM;Nilsonne G;Notter MP;Olivetti E;Onicas AI;Papale P;Patil KR;Peelle JE;Pérez A;Pischedda D;Poline JB;Prystauka Y;Ray S;Reuter-Lorenz PA;Reynolds RC;Ricciardi E;Rieck JR;Rodriguez-Thompson AM;Romyn A;Salo T;Samanez-Larkin GR;Sanz-Morales E;Schlichting ML;Schultz DH;Shen Q;Sheridan MA;Silvers JA;Skagerlund K;Smith A;Smith DV;Sokol-Hessner P;Steinkamp SR;Tashjian SM;Thirion B;Thorp JN;Tinghög G;Tisdall L;Tompson SH;Toro-Serey C;Torre Tresols JJ;Tozzi L;Truong V;Turella L;van 't Veer AE;Verguts T;Vettel JM;Vijayarajah S;Vo K;Wall MB;Weeda WD;Weis S;White DJ;Wisniewski D;Xifra-Porxas A;Yearling EA;Yoon S;Yuan R;Yuen KSL;Zhang L;Zhang X;Zosky JE;Nichols TE;Poldrack RA;Schonberg T
通讯作者：
Schonberg T