<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Li M</submitter><funding>NIDA NIH HHS</funding><funding>Ministry of Science and Technology of the People&amp;apos;s Republic of China</funding><funding>Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology)</funding><funding>NIH HHS</funding><pagination>7786</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11379965</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>15(1)</volume><pubmed_abstract>Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors s</pubmed_abstract><journal>Nature communications</journal><pubmed_title>Cognitive processing speed and accuracy are intrinsically different in genetic architecture and brain phenotypes.</pubmed_title><pmcid>PMC11379965</pmcid><funding_grant_id>U01 DA041117</funding_grant_id><funding_grant_id>U24 DA041123</funding_grant_id><funding_grant_id>U24 DA041147</funding_grant_id><funding_grant_id>U01DA041106</funding_grant_id><funding_grant_id>U01 DA041174</funding_grant_id><funding_grant_id>U01DA041028</funding_grant_id><funding_grant_id>U01DA041148</funding_grant_id><funding_grant_id>U01DA041048</funding_grant_id><funding_grant_id>U01DA041025</funding_grant_id><funding_grant_id>U01 DA041156</funding_grant_id><funding_grant_id>U01 DA041134</funding_grant_id><funding_grant_id>U01DA041089</funding_grant_id><funding_grant_id>U01DA041022</funding_grant_id><funding_grant_id>U01DA041120</funding_grant_id><funding_grant_id>2021ZD0200202</funding_grant_id><funding_grant_id>U01DA050987</funding_grant_id><funding_grant_id>U01DA050988</funding_grant_id><funding_grant_id>U01 DA041093</funding_grant_id><funding_grant_id>U01DA051039</funding_grant_id><funding_grant_id>U01DA051038</funding_grant_id><funding_grant_id>U01DA051016</funding_grant_id><funding_grant_id>U01DA051018</funding_grant_id><funding_grant_id>U01DA051037</funding_grant_id><funding_grant_id>U01 DA051037</funding_grant_id><funding_grant_id>U01 DA041106</funding_grant_id><funding_grant_id>U01 DA041028</funding_grant_id><funding_grant_id>U01 DA041089</funding_grant_id><funding_grant_id>U01 DA041022</funding_grant_id><funding_grant_id>U01 DA041120</funding_grant_id><funding_grant_id>U01DA041117</funding_grant_id><funding_grant_id>U01 DA041148</funding_grant_id><funding_grant_id>U24DA041147</funding_grant_id><funding_grant_id>U01 DA041048</funding_grant_id><funding_grant_id>U24DA041123</funding_grant_id><funding_grant_id>U01 DA041025</funding_grant_id><funding_grant_id>U01DA041134</funding_grant_id><funding_grant_id>U01DA041156</funding_grant_id><funding_grant_id>U01 DA051039</funding_grant_id><funding_grant_id>U01 DA051038</funding_grant_id><funding_grant_id>U01 DA051016</funding_grant_id><funding_grant_id>U01 DA051018</funding_grant_id><funding_grant_id>U01DA041174</funding_grant_id><funding_grant_id>U01 DA050988</funding_grant_id><funding_grant_id>U01 DA050987</funding_grant_id><funding_grant_id>U01 DA050989</funding_grant_id><funding_grant_id>U01DA041093</funding_grant_id><pubmed_authors>Chen Z</pubmed_authors><pubmed_authors>Chen Y</pubmed_authors><pubmed_authors>Wu D</pubmed_authors><pubmed_authors>Xu X</pubmed_authors><pubmed_authors>Dang X</pubmed_authors><pubmed_authors>Zhao Z</pubmed_authors><pubmed_authors>Li M</pubmed_authors></additional><is_claimable>false</is_claimable><name>Cognitive processing speed and accuracy are intrinsically different in genetic architecture and brain phenotypes.</name><description>Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors s</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Sep</publication><modification>2026-06-01T06:49:47.367Z</modification><creation>2025-04-03T23:55:22.47Z</creation></dates><accession>S-EPMC11379965</accession><cross_references><pubmed>39242605</pubmed><doi>10.1038/s41467-024-52222-8</doi></cross_references></HashMap>