Habitual control of goal selection in humans
Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral contro...
Saved in:
| Published in | Proceedings of the National Academy of Sciences - PNAS Vol. 112; no. 45; pp. 13817 - 13822 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
United States
National Academy of Sciences
10.11.2015
National Acad Sciences |
| Series | From the Cover |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0027-8424 1091-6490 1091-6490 |
| DOI | 10.1073/pnas.1506367112 |
Cover
Loading…
| Abstract | Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral control, yetmany complex tasks instead favor their integration. We consider a hierarchical architecture that exploits the computational efficiency of habitual control to select goals while preserving the flexibility of planning to achieve those goals. We formalize this mechanism in a reinforcement learning setting, illustrate its costs and benefits, and experimentally demonstrate its spontaneous application in a sequential decision-making task. |
|---|---|
| AbstractList | Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral control, yet many complex tasks instead favor their integration. We consider a hierarchical architecture that exploits the computational efficiency of habitual control to select goals while preserving the flexibility of planning to achieve those goals. We formalize this mechanism in a reinforcement learning setting, illustrate its costs and benefits, and experimentally demonstrate its spontaneous application in a sequential decision-making task.Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral control, yet many complex tasks instead favor their integration. We consider a hierarchical architecture that exploits the computational efficiency of habitual control to select goals while preserving the flexibility of planning to achieve those goals. We formalize this mechanism in a reinforcement learning setting, illustrate its costs and benefits, and experimentally demonstrate its spontaneous application in a sequential decision-making task. Human cognition makes widespread use of goal-directed planning. However, exhaustive forward planning for tasks of real-world complexity is prohibitively computationally demanding. Much research aims to find efficient mechanisms for approximate planning. We describe an approach to this problem that exploits the computational efficiency of habit learning to select goal states that are subsequently used in planning. We also provide experimental evidence that humans implement this approach. Our findings illuminate the basis of learning and choice in humans, demonstrate an integration between mechanisms of habitual and planned control, and contribute to the development of computationally tractable planning algorithms. Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral control, yet many complex tasks instead favor their integration. We consider a hierarchical architecture that exploits the computational efficiency of habitual control to select goals while preserving the flexibility of planning to achieve those goals. We formalize this mechanism in a reinforcement learning setting, illustrate its costs and benefits, and experimentally demonstrate its spontaneous application in a sequential decision-making task. Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral control, yetmany complex tasks instead favor their integration. We consider a hierarchical architecture that exploits the computational efficiency of habitual control to select goals while preserving the flexibility of planning to achieve those goals. We formalize this mechanism in a reinforcement learning setting, illustrate its costs and benefits, and experimentally demonstrate its spontaneous application in a sequential decision-making task. Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning is computationally expensive but can adapt swiftly. Current research emphasizes the competition between habits and plans for behavioral control, yet many complex tasks instead favor their integration. We consider a hierarchical architecture that exploits the computational efficiency of habitual control to select goals while preserving the flexibility of planning to achieve those goals. We formalize this mechanism in a reinforcement learning setting, illustrate its costs and benefits, and experimentally demonstrate its spontaneous application in a sequential decision-making task. |
| Author | Morris, Adam Cushman, Fiery |
| Author_xml | – sequence: 1 givenname: Fiery surname: Cushman fullname: Cushman, Fiery – sequence: 2 givenname: Adam surname: Morris fullname: Morris, Adam |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26460050$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9kU1PGzEQhq0KVJK0Z06glbhwYGH8vXuphBAQJCQucLa8jh0cbeyw3q3Uf1-vEtLCgYs_NM-8887MFB2EGCxCxxguMUh6tQk6XWIOggqJMfmGJhhqXApWwwGaABBZVoywIzRNaQUANa_gOzoiggkADhN0MdeN7wfdFiaGvottEV2xjPmfbGtN72MofCheh7UO6Qc6dLpN9ufunqGXu9vnm3n5-HT_cHP9WBpOWV8K0QieX3VjCUjnGm2MqyiTxkkhgC84NsRWTFuttRPEOFw3vK5FZSyRDaEz9GuruxmatV0Ym53pVm06v9bdHxW1Vx8jwb-qZfytmOCUEJwFzncCXXwbbOrV2idj21YHG4eksKREAM7zyejZJ3QVhy7k9kaKSVqPxwyd_u9ob-V9kBm42gKmiyl11u0RDGpclRpXpf6tKmfwTxnG93oceG7Jt1_kFTsrY2BfBRPFuMK0wqPbky2ySn3sPpgVlFT0L5nEq1Y |
| CitedBy_id | crossref_primary_10_1073_pnas_1609094113 crossref_primary_10_5465_amr_2022_0518 crossref_primary_10_1038_s41386_021_01123_1 crossref_primary_10_1038_s41467_017_02750_3 crossref_primary_10_1177_1745691620931460 crossref_primary_10_1093_cercor_bhx210 crossref_primary_10_1016_j_tics_2024_10_006 crossref_primary_10_1016_j_nicl_2022_103083 crossref_primary_10_1038_s41593_018_0232_z crossref_primary_10_1016_j_copsyc_2018_11_014 crossref_primary_10_1038_s41583_020_0355_6 crossref_primary_10_1038_s41386_020_00899_y crossref_primary_10_1080_2331186X_2018_1429134 crossref_primary_10_1016_j_tics_2022_02_002 crossref_primary_10_3389_fpsyg_2019_01193 crossref_primary_10_1016_j_cub_2021_03_091 crossref_primary_10_1177_1059712316667203 crossref_primary_10_1111_spc3_12704 crossref_primary_10_1038_s42003_023_04500_2 crossref_primary_10_1162_jocn_a_01170 crossref_primary_10_3389_fncom_2016_00128 crossref_primary_10_1016_j_cognition_2016_02_002 crossref_primary_10_1016_j_addbeh_2021_106899 crossref_primary_10_1002_wcs_1629 crossref_primary_10_1111_nous_12501 crossref_primary_10_3758_s13423_022_02191_0 crossref_primary_10_1016_j_tics_2022_08_003 crossref_primary_10_1177_1088868317720362 crossref_primary_10_1017_S0265052518000134 crossref_primary_10_1038_nrn_2016_78 crossref_primary_10_3389_fpsyg_2019_02892 crossref_primary_10_1002_jeab_889 crossref_primary_10_1371_journal_pone_0162246 crossref_primary_10_1371_journal_pcbi_1007944 crossref_primary_10_1038_s41598_020_79929_0 crossref_primary_10_1038_nn_4238 crossref_primary_10_1016_j_physbeh_2017_04_001 crossref_primary_10_1146_annurev_psych_021323_040420 crossref_primary_10_1073_pnas_2016884118 crossref_primary_10_1016_j_neunet_2019_04_022 crossref_primary_10_1016_j_tics_2023_08_011 crossref_primary_10_1371_journal_pcbi_1011087 crossref_primary_10_1007_s13164_020_00515_4 crossref_primary_10_1111_ejn_14730 crossref_primary_10_7554_eLife_11305 crossref_primary_10_1016_j_neuroimage_2021_118780 crossref_primary_10_1080_10963758_2022_2034118 crossref_primary_10_1177_09567976211005702 crossref_primary_10_1007_s13164_021_00566_1 crossref_primary_10_1017_S0140525X19003261 crossref_primary_10_3389_fpsyg_2016_01821 crossref_primary_10_1177_09567976231200547 crossref_primary_10_1007_s11245_020_09715_0 crossref_primary_10_1038_s41562_021_01180_y crossref_primary_10_2147_NDT_S334403 crossref_primary_10_1038_s41467_019_08662_8 crossref_primary_10_1016_j_jrp_2019_03_001 crossref_primary_10_1146_annurev_psych_010416_044216 crossref_primary_10_1016_j_pnpbp_2022_110523 crossref_primary_10_1016_j_tics_2024_01_004 crossref_primary_10_1002_jnr_24545 crossref_primary_10_1177_09567976231180587 crossref_primary_10_1016_j_cobeha_2017_12_009 crossref_primary_10_1371_journal_pcbi_1010047 crossref_primary_10_1177_17456916231179146 crossref_primary_10_1177_0963721419868211 crossref_primary_10_1177_1745691621995752 crossref_primary_10_3389_fncom_2017_00080 crossref_primary_10_1016_j_robot_2020_103630 crossref_primary_10_1111_mila_12502 crossref_primary_10_7554_eLife_74402 crossref_primary_10_1016_j_cobeha_2017_12_001 crossref_primary_10_1016_j_cobeha_2018_01_015 crossref_primary_10_1146_annurev_psych_122414_033625 crossref_primary_10_1016_j_bpsc_2016_06_005 crossref_primary_10_1017_S0033291716002786 crossref_primary_10_52547_shefa_9_4_51 crossref_primary_10_1016_j_cognition_2022_105215 crossref_primary_10_1162_jocn_a_02150 crossref_primary_10_3389_fpsyg_2019_02735 crossref_primary_10_1108_JMD_07_2023_0220 crossref_primary_10_1038_s41467_021_25123_3 crossref_primary_10_7554_eLife_82390 crossref_primary_10_1016_j_neuron_2020_06_014 crossref_primary_10_1371_journal_pone_0195328 crossref_primary_10_1016_j_biopsych_2017_05_017 crossref_primary_10_1016_j_ijhcs_2021_102661 crossref_primary_10_1038_s41562_020_0905_y crossref_primary_10_1007_s11229_023_04168_5 crossref_primary_10_1016_j_cobeha_2019_04_009 crossref_primary_10_1016_j_pnpbp_2017_06_029 crossref_primary_10_1186_s41235_023_00497_8 crossref_primary_10_1073_pnas_1518488112 crossref_primary_10_1371_journal_pcbi_1008552 crossref_primary_10_3758_s13428_022_01789_5 crossref_primary_10_1002_evan_21948 crossref_primary_10_1111_spc3_12567 crossref_primary_10_1162_jocn_a_00945 crossref_primary_10_3389_fpsyg_2020_00380 |
| Cites_doi | 10.1098/rstb.2013.0480 10.1162/089976606775093909 10.1016/j.cognition.2008.08.011 10.1037/a0030844 10.1146/annurev.neuro.29.051605.112851 10.1016/j.neuron.2013.09.007 10.1017/S0140525X13000290 10.1145/1390156.1390211 10.1073/pnas.1414219112 10.1016/j.neuron.2013.08.009 10.3758/BF03199935 10.1037/h0092987 10.1093/brain/106.2.237 10.1016/S0896-6273(03)00154-5 10.1038/nn.3981 10.1371/journal.pbio.1001089 10.1371/journal.pcbi.1003364 10.1073/pnas.1417219112 10.1080/026432900380427 10.1177/0956797612463080 10.1016/S0004-3702(99)00052-1 10.1016/j.neuron.2005.05.020 10.1073/pnas.1312011110 10.3389/fpsyg.2013.00092 10.1016/S0896-6273(03)00169-7 10.1016/j.brainres.2009.07.007 10.3389/fnbeh.2013.00135 10.1016/j.neuroimage.2009.03.025 10.1016/j.neuron.2011.02.027 10.1038/nn1968 10.1016/j.neuron.2010.04.016 10.1016/j.tics.2008.02.009 10.1038/nn1560 10.1038/35036228 10.1016/j.conb.2012.05.011 10.1073/pnas.1100290108 10.1007/BF00302715 10.3102/0013189X018001016 10.1371/journal.pcbi.1002410 10.1037/0003-066X.51.4.355 10.1098/rstb.2013.0482 10.1037/a0030852 10.1162/jocn_a_00709 10.1521/soco.2008.26.5.593 10.1145/1390156.1390278 10.1109/TNN.1998.712192 10.1016/S0028-3908(98)00033-1 10.1007/978-1-4757-0629-1_1 10.1523/JNEUROSCI.4647-10.2011 10.1098/rstb.2013.0478 10.1073/pnas.0914630107 10.1037/h0062487 |
| ContentType | Journal Article |
| Copyright | Volumes 1–89 and 106–112, copyright as a collective work only; author(s) retains copyright to individual articles Copyright National Academy of Sciences Nov 10, 2015 |
| Copyright_xml | – notice: Volumes 1–89 and 106–112, copyright as a collective work only; author(s) retains copyright to individual articles – notice: Copyright National Academy of Sciences Nov 10, 2015 |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QG 7QL 7QP 7QR 7SN 7SS 7T5 7TK 7TM 7TO 7U9 8FD C1K FR3 H94 M7N P64 RC3 7X8 5PM |
| DOI | 10.1073/pnas.1506367112 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Calcium & Calcified Tissue Abstracts Chemoreception Abstracts Ecology Abstracts Entomology Abstracts (Full archive) Immunology Abstracts Neurosciences Abstracts Nucleic Acids Abstracts Oncogenes and Growth Factors Abstracts Virology and AIDS Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database AIDS and Cancer Research Abstracts Algology Mycology and Protozoology Abstracts (Microbiology C) Biotechnology and BioEngineering Abstracts Genetics Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Virology and AIDS Abstracts Oncogenes and Growth Factors Abstracts Technology Research Database Nucleic Acids Abstracts Ecology Abstracts Neurosciences Abstracts Biotechnology and BioEngineering Abstracts Environmental Sciences and Pollution Management Entomology Abstracts Genetics Abstracts Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) AIDS and Cancer Research Abstracts Chemoreception Abstracts Immunology Abstracts Engineering Research Database Calcium & Calcified Tissue Abstracts MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic CrossRef MEDLINE Virology and AIDS Abstracts |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Sciences (General) |
| DocumentTitleAlternate | Habitual control of goal selection |
| EISSN | 1091-6490 |
| EndPage | 13822 |
| ExternalDocumentID | PMC4653221 3871771741 26460050 10_1073_pnas_1506367112 112_45_13817 26466328 |
| Genre | Research Support, U.S. Gov't, Non-P.H.S Journal Article Feature |
| GrantInformation_xml | – fundername: DOD | Office of Naval Research (ONR) grantid: N00014-14-1-0800 |
| GroupedDBID | --- -DZ -~X .55 0R~ 123 29P 2AX 2FS 2WC 4.4 53G 5RE 5VS 85S AACGO AAFWJ AANCE ABBHK ABOCM ABPLY ABPPZ ABTLG ABXSQ ABZEH ACGOD ACHIC ACIWK ACNCT ACPRK ADQXQ ADULT AENEX AEUPB AEXZC AFFNX AFOSN AFRAH ALMA_UNASSIGNED_HOLDINGS AQVQM BKOMP CS3 D0L DCCCD DIK DU5 E3Z EBS EJD F5P FRP GX1 H13 HH5 HYE IPSME JAAYA JBMMH JENOY JHFFW JKQEH JLS JLXEF JPM JSG JST KQ8 L7B LU7 N9A N~3 O9- OK1 PNE PQQKQ R.V RHI RNA RNS RPM RXW SA0 SJN TAE TN5 UKR W8F WH7 WOQ WOW X7M XSW Y6R YBH YKV YSK ZCA ~02 ~KM - 02 0R 1AW 55 AAPBV ABFLS ABPTK ADACO ADZLD ASUFR DNJUQ DOOOF DWIUU DZ F20 JSODD KM PQEST RHF VQA X XHC ZA5 AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QG 7QL 7QP 7QR 7SN 7SS 7T5 7TK 7TM 7TO 7U9 8FD C1K FR3 H94 M7N P64 RC3 7X8 5PM |
| ID | FETCH-LOGICAL-c534t-66b655349be207ffbaccf8347cf76605d51c2e84aeaaaf62cf19b59968ce27b23 |
| ISSN | 0027-8424 1091-6490 |
| IngestDate | Thu Aug 21 14:35:02 EDT 2025 Thu Jul 10 23:27:23 EDT 2025 Mon Jun 30 07:41:44 EDT 2025 Thu Apr 03 07:05:24 EDT 2025 Tue Jul 01 01:53:34 EDT 2025 Thu Apr 24 23:03:51 EDT 2025 Wed Nov 11 00:29:30 EST 2020 Fri May 30 12:01:41 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 45 |
| Keywords | planning goal selection habit hierarchical control reinforcement learning |
| Language | English |
| License | Freely available online through the PNAS open access option. |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c534t-66b655349be207ffbaccf8347cf76605d51c2e84aeaaaf62cf19b59968ce27b23 |
| Notes | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 Author contributions: F.C. and A.M. designed research; F.C. and A.M. performed research; A.M. analyzed data; and F.C. and A.M. wrote the paper. Edited by Terrence J. Sejnowski, Salk Institute for Biological Studies, La Jolla, CA, and approved September 10, 2015 (received for review March 31, 2015) |
| ORCID | 0000-0002-6929-9982 |
| OpenAccessLink | https://www.pnas.org/content/pnas/112/45/13817.full.pdf |
| PMID | 26460050 |
| PQID | 1734739347 |
| PQPubID | 42026 |
| PageCount | 6 |
| ParticipantIDs | crossref_primary_10_1073_pnas_1506367112 pnas_primary_112_45_13817 proquest_miscellaneous_1732601002 crossref_citationtrail_10_1073_pnas_1506367112 jstor_primary_26466328 proquest_journals_1734739347 pubmed_primary_26460050 pubmedcentral_primary_oai_pubmedcentral_nih_gov_4653221 |
| ProviderPackageCode | RNA PNE CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2015-11-10 |
| PublicationDateYYYYMMDD | 2015-11-10 |
| PublicationDate_xml | – month: 11 year: 2015 text: 2015-11-10 day: 10 |
| PublicationDecade | 2010 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: Washington |
| PublicationSeriesTitle | From the Cover |
| PublicationTitle | Proceedings of the National Academy of Sciences - PNAS |
| PublicationTitleAlternate | Proc Natl Acad Sci U S A |
| PublicationYear | 2015 |
| Publisher | National Academy of Sciences National Acad Sciences |
| Publisher_xml | – name: National Academy of Sciences – name: National Acad Sciences |
| References | e_1_3_3_50_2 Zhang NL (e_1_3_3_40_2) 1997 e_1_3_3_16_2 e_1_3_3_18_2 e_1_3_3_12_2 e_1_3_3_37_2 e_1_3_3_58_2 e_1_3_3_14_2 e_1_3_3_35_2 e_1_3_3_56_2 e_1_3_3_33_2 e_1_3_3_54_2 e_1_3_3_10_2 e_1_3_3_31_2 e_1_3_3_52_2 Lashley KS (e_1_3_3_15_2) 1951 e_1_3_3_5_2 e_1_3_3_7_2 e_1_3_3_9_2 e_1_3_3_27_2 e_1_3_3_29_2 e_1_3_3_23_2 e_1_3_3_48_2 e_1_3_3_25_2 e_1_3_3_46_2 e_1_3_3_1_2 e_1_3_3_44_2 e_1_3_3_3_2 e_1_3_3_21_2 e_1_3_3_42_2 e_1_3_3_51_2 e_1_3_3_17_2 e_1_3_3_19_2 e_1_3_3_38_2 e_1_3_3_13_2 e_1_3_3_36_2 e_1_3_3_34_2 e_1_3_3_32_2 e_1_3_3_11_2 e_1_3_3_30_2 e_1_3_3_53_2 Boyan JA (e_1_3_3_39_2) 1996 Burnham KP (e_1_3_3_57_2) 2002 e_1_3_3_6_2 e_1_3_3_8_2 e_1_3_3_28_2 e_1_3_3_49_2 e_1_3_3_24_2 e_1_3_3_47_2 McFadden D (e_1_3_3_59_2) 1974 e_1_3_3_26_2 e_1_3_3_45_2 e_1_3_3_2_2 e_1_3_3_20_2 e_1_3_3_43_2 R Development Core Team (e_1_3_3_55_2) 2009 e_1_3_3_4_2 e_1_3_3_22_2 e_1_3_3_41_2 18420448 - Trends Cogn Sci. 2008 May;12(5):201-8 22412360 - PLoS Comput Biol. 2012;8(3):e1002410 16378516 - Neural Comput. 2006 Feb;18(2):283-328 21713027 - PLoS Biol. 2011 Jun;9(6):e1001089 25267824 - Philos Trans R Soc Lond B Biol Sci. 2014 Nov 5;369(1655). pii: 20130482. doi: 10.1098/rstb.2013.0482 6850269 - Brain. 1983 Jun;106 (Pt 2):237-55 22704797 - Curr Opin Neurobiol. 2012 Dec;22(6):1068-74 20510862 - Neuron. 2010 May 27;66(4):585-95 25799041 - Nat Neurosci. 2015 May;18(5):767-72 21435563 - Neuron. 2011 Mar 24;69(6):1204-15 24775120 - Behav Brain Sci. 2014 Apr;37(2):121-35 24324166 - Proc Natl Acad Sci U S A. 2013 Dec 24;110(52):20941-6 18926527 - Cognition. 2009 Dec;113(3):262-80 16286932 - Nat Neurosci. 2005 Dec;8(12):1704-11 25267822 - Philos Trans R Soc Lond B Biol Sci. 2014 Nov 5;369(1655). pii: 20130480. doi: 10.1098/rstb.2013.0480 18558860 - Annu Rev Neurosci. 2008;31:359-87 23356780 - Psychol Rev. 2013 Jan;120(1):190-229 13000071 - J Exp Psychol. 1952 Oct;44(4):288-91 24339762 - PLoS Comput Biol. 2013;9(12):e1003364 25170791 - J Cogn Neurosci. 2015 Feb;27(2):319-33 25267820 - Philos Trans R Soc Lond B Biol Sci. 2014 Nov 5;369(1655). pii: 20130478. doi: 10.1098/rstb.2013.0478 24206669 - Neuron. 2013 Nov 20;80(4):914-9 24139036 - Neuron. 2013 Oct 16;80(2):312-25 23459512 - Front Psychol. 2013 Mar 04;4:92 21690340 - Proc Natl Acad Sci U S A. 2011 Jun 28;108 Suppl 2:10918-25 26489651 - Proc Natl Acad Sci U S A. 2015 Nov 10;112(45):13749-50 11252769 - Nat Rev Neurosci. 2000 Oct;1(1):59-65 25605941 - Proc Natl Acad Sci U S A. 2015 Feb 3;112(5):1595-600 21471389 - J Neurosci. 2011 Apr 6;31(14):5526-39 9704982 - Neuropharmacology. 1998 Apr-May;37(4-5):407-19 20945185 - Cogn Neuropsychol. 2000 Jun 1;17(4):297-338 25675480 - Proc Natl Acad Sci U S A. 2015 Mar 10;112(10):3098-103 20445094 - Proc Natl Acad Sci U S A. 2010 May 11;107 Suppl 2:8993-9 23558545 - Psychol Sci. 2013 May;24(5):751-61 17726475 - Nat Neurosci. 2007 Sep;10(9):1095-102 12718865 - Neuron. 2003 Apr 24;38(2):329-37 15996553 - Neuron. 2005 Jul 7;47(1):129-41 19306932 - Neuroimage. 2009 Jul 15;46(4):1004-17 23230992 - J Exp Psychol Gen. 2014 Feb;143(1):182-94 19595993 - Brain Res. 2009 Nov 24;1299:74-94 12718866 - Neuron. 2003 Apr 24;38(2):339-46 24167476 - Front Behav Neurosci. 2013 Oct 23;7:135 |
| References_xml | – ident: e_1_3_3_13_2 doi: 10.1098/rstb.2013.0480 – ident: e_1_3_3_20_2 doi: 10.1162/089976606775093909 – ident: e_1_3_3_16_2 doi: 10.1016/j.cognition.2008.08.011 – start-page: 112 volume-title: Cerebral Mechanisms in Behavior year: 1951 ident: e_1_3_3_15_2 – ident: e_1_3_3_8_2 doi: 10.1037/a0030844 – ident: e_1_3_3_19_2 doi: 10.1146/annurev.neuro.29.051605.112851 – ident: e_1_3_3_1_2 doi: 10.1016/j.neuron.2013.09.007 – start-page: 63 volume-title: ICML-96 year: 1996 ident: e_1_3_3_39_2 – volume-title: Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach year: 2002 ident: e_1_3_3_57_2 – ident: e_1_3_3_41_2 doi: 10.1017/S0140525X13000290 – ident: e_1_3_3_17_2 doi: 10.1145/1390156.1390211 – ident: e_1_3_3_49_2 doi: 10.1073/pnas.1414219112 – ident: e_1_3_3_35_2 doi: 10.1016/j.neuron.2013.08.009 – ident: e_1_3_3_25_2 doi: 10.3758/BF03199935 – ident: e_1_3_3_2_2 doi: 10.1037/h0092987 – ident: e_1_3_3_42_2 doi: 10.1093/brain/106.2.237 – ident: e_1_3_3_27_2 doi: 10.1016/S0896-6273(03)00154-5 – ident: e_1_3_3_38_2 doi: 10.1038/nn.3981 – ident: e_1_3_3_51_2 doi: 10.1371/journal.pbio.1001089 – ident: e_1_3_3_10_2 doi: 10.1371/journal.pcbi.1003364 – ident: e_1_3_3_31_2 doi: 10.1073/pnas.1417219112 – ident: e_1_3_3_34_2 doi: 10.1080/026432900380427 – ident: e_1_3_3_5_2 doi: 10.1177/0956797612463080 – ident: e_1_3_3_12_2 doi: 10.1016/S0004-3702(99)00052-1 – ident: e_1_3_3_26_2 doi: 10.1016/j.neuron.2005.05.020 – ident: e_1_3_3_36_2 doi: 10.1073/pnas.1312011110 – ident: e_1_3_3_46_2 doi: 10.3389/fpsyg.2013.00092 – ident: e_1_3_3_28_2 doi: 10.1016/S0896-6273(03)00169-7 – ident: e_1_3_3_52_2 doi: 10.1016/j.brainres.2009.07.007 – ident: e_1_3_3_11_2 doi: 10.3389/fnbeh.2013.00135 – start-page: 489 volume-title: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence year: 1997 ident: e_1_3_3_40_2 – ident: e_1_3_3_58_2 doi: 10.1016/j.neuroimage.2009.03.025 – ident: e_1_3_3_24_2 doi: 10.1016/j.neuron.2011.02.027 – ident: e_1_3_3_50_2 doi: 10.1038/nn1968 – ident: e_1_3_3_30_2 doi: 10.1016/j.neuron.2010.04.016 – ident: e_1_3_3_14_2 doi: 10.1016/j.tics.2008.02.009 – ident: e_1_3_3_7_2 doi: 10.1038/nn1560 – ident: e_1_3_3_22_2 doi: 10.1038/35036228 – ident: e_1_3_3_18_2 doi: 10.1016/j.conb.2012.05.011 – ident: e_1_3_3_53_2 doi: 10.1073/pnas.1100290108 – ident: e_1_3_3_44_2 doi: 10.1007/BF00302715 – ident: e_1_3_3_45_2 doi: 10.3102/0013189X018001016 – ident: e_1_3_3_56_2 – ident: e_1_3_3_32_2 doi: 10.1371/journal.pcbi.1002410 – ident: e_1_3_3_33_2 doi: 10.1037/0003-066X.51.4.355 – ident: e_1_3_3_9_2 doi: 10.1098/rstb.2013.0482 – ident: e_1_3_3_21_2 doi: 10.1037/a0030852 – ident: e_1_3_3_37_2 doi: 10.1162/jocn_a_00709 – ident: e_1_3_3_6_2 doi: 10.1521/soco.2008.26.5.593 – ident: e_1_3_3_47_2 doi: 10.1145/1390156.1390278 – volume-title: R: A Language and Environment for Statistical Computing year: 2009 ident: e_1_3_3_55_2 – ident: e_1_3_3_23_2 doi: 10.1109/TNN.1998.712192 – ident: e_1_3_3_4_2 doi: 10.1016/S0028-3908(98)00033-1 – ident: e_1_3_3_3_2 doi: 10.1007/978-1-4757-0629-1_1 – ident: e_1_3_3_29_2 doi: 10.1523/JNEUROSCI.4647-10.2011 – ident: e_1_3_3_48_2 doi: 10.1098/rstb.2013.0478 – ident: e_1_3_3_54_2 doi: 10.1073/pnas.0914630107 – start-page: 105 volume-title: Frontiers in Econometrics year: 1974 ident: e_1_3_3_59_2 – ident: e_1_3_3_43_2 doi: 10.1037/h0062487 – reference: 23459512 - Front Psychol. 2013 Mar 04;4:92 – reference: 23558545 - Psychol Sci. 2013 May;24(5):751-61 – reference: 18558860 - Annu Rev Neurosci. 2008;31:359-87 – reference: 17726475 - Nat Neurosci. 2007 Sep;10(9):1095-102 – reference: 21690340 - Proc Natl Acad Sci U S A. 2011 Jun 28;108 Suppl 2:10918-25 – reference: 25799041 - Nat Neurosci. 2015 May;18(5):767-72 – reference: 19595993 - Brain Res. 2009 Nov 24;1299:74-94 – reference: 18420448 - Trends Cogn Sci. 2008 May;12(5):201-8 – reference: 12718866 - Neuron. 2003 Apr 24;38(2):339-46 – reference: 24206669 - Neuron. 2013 Nov 20;80(4):914-9 – reference: 13000071 - J Exp Psychol. 1952 Oct;44(4):288-91 – reference: 16286932 - Nat Neurosci. 2005 Dec;8(12):1704-11 – reference: 20510862 - Neuron. 2010 May 27;66(4):585-95 – reference: 22412360 - PLoS Comput Biol. 2012;8(3):e1002410 – reference: 21435563 - Neuron. 2011 Mar 24;69(6):1204-15 – reference: 16378516 - Neural Comput. 2006 Feb;18(2):283-328 – reference: 24167476 - Front Behav Neurosci. 2013 Oct 23;7:135 – reference: 23356780 - Psychol Rev. 2013 Jan;120(1):190-229 – reference: 25267822 - Philos Trans R Soc Lond B Biol Sci. 2014 Nov 5;369(1655). pii: 20130480. doi: 10.1098/rstb.2013.0480 – reference: 21471389 - J Neurosci. 2011 Apr 6;31(14):5526-39 – reference: 9704982 - Neuropharmacology. 1998 Apr-May;37(4-5):407-19 – reference: 25605941 - Proc Natl Acad Sci U S A. 2015 Feb 3;112(5):1595-600 – reference: 25267824 - Philos Trans R Soc Lond B Biol Sci. 2014 Nov 5;369(1655). pii: 20130482. doi: 10.1098/rstb.2013.0482 – reference: 21713027 - PLoS Biol. 2011 Jun;9(6):e1001089 – reference: 15996553 - Neuron. 2005 Jul 7;47(1):129-41 – reference: 19306932 - Neuroimage. 2009 Jul 15;46(4):1004-17 – reference: 26489651 - Proc Natl Acad Sci U S A. 2015 Nov 10;112(45):13749-50 – reference: 20945185 - Cogn Neuropsychol. 2000 Jun 1;17(4):297-338 – reference: 25675480 - Proc Natl Acad Sci U S A. 2015 Mar 10;112(10):3098-103 – reference: 24324166 - Proc Natl Acad Sci U S A. 2013 Dec 24;110(52):20941-6 – reference: 24775120 - Behav Brain Sci. 2014 Apr;37(2):121-35 – reference: 12718865 - Neuron. 2003 Apr 24;38(2):329-37 – reference: 11252769 - Nat Rev Neurosci. 2000 Oct;1(1):59-65 – reference: 25170791 - J Cogn Neurosci. 2015 Feb;27(2):319-33 – reference: 22704797 - Curr Opin Neurobiol. 2012 Dec;22(6):1068-74 – reference: 24339762 - PLoS Comput Biol. 2013;9(12):e1003364 – reference: 24139036 - Neuron. 2013 Oct 16;80(2):312-25 – reference: 25267820 - Philos Trans R Soc Lond B Biol Sci. 2014 Nov 5;369(1655). pii: 20130478. doi: 10.1098/rstb.2013.0478 – reference: 20445094 - Proc Natl Acad Sci U S A. 2010 May 11;107 Suppl 2:8993-9 – reference: 23230992 - J Exp Psychol Gen. 2014 Feb;143(1):182-94 – reference: 6850269 - Brain. 1983 Jun;106 (Pt 2):237-55 – reference: 18926527 - Cognition. 2009 Dec;113(3):262-80 |
| SSID | ssj0009580 |
| Score | 2.5252657 |
| Snippet | Humans choose actions based on both habit and planning. Habitual control is computationally frugal but adapts slowly to novel circumstances, whereas planning... Human cognition makes widespread use of goal-directed planning. However, exhaustive forward planning for tasks of real-world complexity is prohibitively... |
| SourceID | pubmedcentral proquest pubmed crossref pnas jstor |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 13817 |
| SubjectTerms | Algorithms Choice Behavior - physiology Decision making Goals Habits Human subjects Humans Learning Learning - physiology Logistic Models Models, Psychological Objectives Planning Planning Techniques Social Sciences |
| Title | Habitual control of goal selection in humans |
| URI | https://www.jstor.org/stable/26466328 http://www.pnas.org/content/112/45/13817.abstract https://www.ncbi.nlm.nih.gov/pubmed/26460050 https://www.proquest.com/docview/1734739347 https://www.proquest.com/docview/1732601002 https://pubmed.ncbi.nlm.nih.gov/PMC4653221 |
| Volume | 112 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELfQeOEFscEgbENB4mFopNSOEyeP07RSoVH20Ep9i2zHYZVGMjXty_76nT_yNZUJkCorii9247tc7py73yH0KWH5OM_DcUCITAMaMdCDBMtApkpyqQoe5zpR-Mcsni7o92W07OJ0TXbJRozk_c68kv_hKpwDvuos2X_gbDsonIBj4C-0wGFo_4rHUy5WJv-jCTgHy-9XpTNATHUbF8ZoyvDVfSv0un1r1U2MwKzZFDzvUkzcc1-fBWfXs65g8cW2vnH7ppOV6oURV-u1K26c89_97QQcBSakrYu2eGK2vh4lwFNqs59HyqpOsDyCmNrin61uxaQnRDTqqUqssQF3KnHQOrrycMnrkcY_DGPWDDOAy579zCaLq6tsfrmcD3vt6xlcQQY_jWrwnIATodX2tyXuQTInNkHJ3UsD_MTCr4_mHtgsNmxVY-EC0S6_5HF4bc9emb9CL52j4Z9bqdlHz1R5gPabRfZPHd7459foSyNGvhMjvyp8LUZ-K0b-qvStGL1Bi8nl_GIauCIagYxCugniWMQRHKVCkTErCsGlLJKQajiqGHzZPMKSqIRyxTkvYiILnAqN2ZNIRZgg4SHaK6tSvUM-mDFRWvCxyHFKcQGeOkmlyDnjlIFVyz00apYpkw5hXhc6uc1MpAMLM71kWbeuHjptL7iz4Cp_Jj00697SgSEPxjJJPOQZ0vZ6TDIaZUa6PHTccCdzjy2MyeDmwxQaD31su0Gp6i9lvFTV1tBoqD0QDQ-9tcwcTKxRkzzEBmxuCTRg-7CnXN0Y4HaNZUgIfv_03zpCL7oH8xjtbdZbdQKW70Z8MAL8AFycq58 |
| linkProvider | Geneva Foundation for Medical Education and Research |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Habitual+control+of+goal+selection+in+humans&rft.jtitle=Proceedings+of+the+National+Academy+of+Sciences+-+PNAS&rft.au=Cushman%2C+Fiery&rft.au=Morris%2C+Adam&rft.date=2015-11-10&rft.pub=National+Academy+of+Sciences&rft.issn=0027-8424&rft.eissn=1091-6490&rft.volume=112&rft.issue=45&rft.spage=13817&rft_id=info:doi/10.1073%2Fpnas.1506367112&rft.externalDBID=NO_FULL_TEXT&rft.externalDocID=3871771741 |
| thumbnail_m | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.pnas.org%2Fcontent%2F112%2F45.cover.gif |
| thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.pnas.org%2Fcontent%2F112%2F45.cover.gif |