Reinforcement Learning Signals in the Human Striatum Distinguish Learners from Nonlearners during Reward-Based Decision Making
The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed band...
Saved in:
Published in | The Journal of neuroscience Vol. 27; no. 47; pp. 12860 - 12867 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
Soc Neuroscience
21.11.2007
Society for Neuroscience |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans. |
---|---|
AbstractList | The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans.The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans. The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans. |
Author | Schonberg, Tom Joel, Daphna O'Doherty, John P Daw, Nathaniel D |
Author_xml | – sequence: 1 fullname: Schonberg, Tom – sequence: 2 fullname: Daw, Nathaniel D – sequence: 3 fullname: Joel, Daphna – sequence: 4 fullname: O'Doherty, John P |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/18032658$$D View this record in MEDLINE/PubMed |
BookMark | eNqFUk1v1DAUtFAR3Rb-QuUT4pLFH7GdSAiJbgstWlppl54tx3Y2hsQudsKKC78dr7ZdAZeeLL03M2_e85yAIx-8BeAMozlmhL79fHN5t7pdL67npKx5gcScICSegVnu1gUpET4CM0QEKngpymNwktI3lBEIixfgGFeIEs6qGfi9ss63IWo7WD_CpVXRO7-Ba7fxqk_QeTh2Fl5Ng_JwPUanxmmAFy6NGTW51O0pNibYxjDAm-D7x4KZ4k5qZbcqmuJcJWvghdUuueDhF_U9N1-C520eY189vKfg7uPl18VVsbz9dL34sCw0K8lYMKOZFcaYmjSactpyhElFmGmMrnXVNrzFVcmIJYJp3DQtK4XNdYqrtmYVp6fg_V73fmoGa3TeNape3kc3qPhLBuXkvx3vOrkJPyXngpIaZ4HXDwIx_JhsGuXgkrZ9r7wNU5K8YrTGnDwJJIhmQVFm4Nnflg5eHv8mA97tATqGlKJtpXajGvPxskPXS4zkLgryEAW5i4JEQu6ikOn8P_phwlPEN3ti5zbd1kUr06D6PtvEcrvdEiFLIfP5OaJ_ADRlyjI |
CitedBy_id | crossref_primary_10_1016_j_bbr_2012_02_006 crossref_primary_10_1016_j_biopsych_2024_06_027 crossref_primary_10_1016_j_neuroimage_2015_11_060 crossref_primary_10_1016_j_neuroimage_2012_04_024 crossref_primary_10_1002_hbm_24345 crossref_primary_10_1111_ejn_12802 crossref_primary_10_1177_2167702614531580 crossref_primary_10_1523_JNEUROSCI_0457_18_2018 crossref_primary_10_3389_fpsyg_2022_924578 crossref_primary_10_1007_s12311_015_0685_5 crossref_primary_10_1038_s41386_021_01108_0 crossref_primary_10_1523_JNEUROSCI_0757_14_2014 crossref_primary_10_1016_j_neuroimage_2011_11_058 crossref_primary_10_1038_nn_3364 crossref_primary_10_1002_ana_21825 crossref_primary_10_1016_j_cognition_2021_104660 crossref_primary_10_3389_fnbeh_2023_1302842 crossref_primary_10_1016_j_nlm_2011_08_006 crossref_primary_10_1177_1073191117714557 crossref_primary_10_1002_hbm_26078 crossref_primary_10_1371_journal_pcbi_1006707 crossref_primary_10_1016_j_neuropsychologia_2011_12_012 crossref_primary_10_1523_JNEUROSCI_2469_09_2009 crossref_primary_10_1523_JNEUROSCI_3086_12_2013 crossref_primary_10_1016_j_ynstr_2021_100412 crossref_primary_10_1007_s10209_025_01198_3 crossref_primary_10_1016_j_jmp_2016_03_007 crossref_primary_10_1523_JNEUROSCI_2701_11_2011 crossref_primary_10_1523_JNEUROSCI_4880_10_2011 crossref_primary_10_1007_s10899_024_10326_2 crossref_primary_10_1109_JPROC_2014_2307022 crossref_primary_10_1016_j_neuron_2011_02_027 crossref_primary_10_1016_j_neuroimage_2015_07_061 crossref_primary_10_22172_cogbio_2013_25_4_007 crossref_primary_10_1016_j_neuron_2010_03_025 crossref_primary_10_1016_j_lmot_2024_102051 crossref_primary_10_1523_JNEUROSCI_6421_10_2011 crossref_primary_10_1016_j_bandc_2020_105657 crossref_primary_10_1038_s41598_020_80593_7 crossref_primary_10_1016_j_neuroimage_2009_06_076 crossref_primary_10_1038_s41467_019_08922_7 crossref_primary_10_1162_jocn_a_00978 crossref_primary_10_3389_fpsyg_2017_00204 crossref_primary_10_1016_j_cobeha_2014_10_004 crossref_primary_10_1152_jn_00260_2015 crossref_primary_10_1017_pen_2018_14 crossref_primary_10_1111_ejn_13803 crossref_primary_10_1016_j_jpsychires_2012_02_014 crossref_primary_10_1111_j_1460_9568_2008_06117_x crossref_primary_10_3389_fpsyg_2016_00169 crossref_primary_10_3758_s13415_015_0377_0 crossref_primary_10_3758_CABN_9_4_343 crossref_primary_10_1038_s41598_018_35124_w crossref_primary_10_1016_j_neuron_2018_03_042 crossref_primary_10_1371_journal_pone_0072508 crossref_primary_10_1523_ENEURO_0167_16_2016 crossref_primary_10_1371_journal_pcbi_1002012 crossref_primary_10_1073_pnas_1519829113 crossref_primary_10_3389_fnins_2017_00598 crossref_primary_10_1177_17456916211031926 crossref_primary_10_1162_jocn_2011_21618 crossref_primary_10_1016_j_neuron_2023_09_015 crossref_primary_10_1017_S0954579408000576 crossref_primary_10_1523_JNEUROSCI_6486_10_2011 crossref_primary_10_3389_fncom_2014_00130 crossref_primary_10_1007_s00422_009_0305_x crossref_primary_10_1016_j_nicl_2020_102193 crossref_primary_10_1016_j_dcn_2016_04_005 crossref_primary_10_1523_JNEUROSCI_3141_14_2014 crossref_primary_10_3389_fnins_2022_889440 crossref_primary_10_1162_jocn_2009_21092 crossref_primary_10_1093_texcom_tgad008 crossref_primary_10_1016_j_neuron_2011_08_024 crossref_primary_10_1523_JNEUROSCI_2277_15_2015 crossref_primary_10_1038_s41467_020_17257_7 crossref_primary_10_1371_journal_pcbi_1003759 crossref_primary_10_1146_annurev_psych_010416_044216 crossref_primary_10_1016_j_neuroscience_2013_07_034 crossref_primary_10_1016_j_neuroimage_2022_119831 crossref_primary_10_1371_journal_pcbi_1005810 crossref_primary_10_1016_j_drugalcdep_2014_03_031 crossref_primary_10_7554_eLife_29718 crossref_primary_10_1016_j_neuropsychologia_2013_07_011 crossref_primary_10_1016_j_nlm_2014_05_002 crossref_primary_10_1016_j_dcn_2019_100668 crossref_primary_10_1002_wcs_1266 crossref_primary_10_1073_pnas_1014938108 crossref_primary_10_1016_j_bpsc_2020_12_015 crossref_primary_10_1016_j_neuroimage_2013_10_069 crossref_primary_10_1007_s42113_024_00198_5 crossref_primary_10_1016_j_nicl_2019_102073 crossref_primary_10_1523_JNEUROSCI_0204_14_2014 crossref_primary_10_1016_j_neuroimage_2012_12_001 crossref_primary_10_1523_JNEUROSCI_2972_11_2011 crossref_primary_10_7554_eLife_79027 crossref_primary_10_3389_fpsyt_2022_1008011 crossref_primary_10_1371_journal_pone_0021575 crossref_primary_10_1016_j_neuroimage_2008_05_032 crossref_primary_10_1016_j_neucom_2013_02_061 crossref_primary_10_1523_JNEUROSCI_2700_16_2017 crossref_primary_10_1038_ncomms10785 crossref_primary_10_1371_journal_pcbi_1007475 crossref_primary_10_1016_j_brainres_2016_06_006 crossref_primary_10_1371_journal_pone_0176205 crossref_primary_10_1016_j_jad_2024_09_066 crossref_primary_10_1007_s11682_017_9786_8 crossref_primary_10_1371_journal_pone_0024390 crossref_primary_10_7554_eLife_26424 crossref_primary_10_1002_hbm_22804 crossref_primary_10_1371_journal_pcbi_1011950 crossref_primary_10_1016_j_jneumeth_2019_01_006 crossref_primary_10_1016_j_heliyon_2024_e32731 crossref_primary_10_1016_j_neuron_2014_08_012 crossref_primary_10_1152_jn_00498_2016 crossref_primary_10_1007_s11031_014_9434_1 crossref_primary_10_1523_JNEUROSCI_0626_12_2012 crossref_primary_10_1016_j_neuroimage_2016_03_064 crossref_primary_10_1371_journal_pbio_2000756 crossref_primary_10_1002_hbm_24184 crossref_primary_10_1016_j_dcn_2015_03_002 crossref_primary_10_1371_journal_pcbi_1008738 crossref_primary_10_1152_jn_00164_2012 crossref_primary_10_1093_cercor_bhr198 crossref_primary_10_1162_jocn_2010_21584 crossref_primary_10_1152_jn_00333_2015 crossref_primary_10_1162_jocn_a_01447 crossref_primary_10_1162_jocn_a_00237 crossref_primary_10_1016_j_cub_2010_08_048 crossref_primary_10_1007_s10802_024_01227_4 crossref_primary_10_1186_s40359_024_01952_x crossref_primary_10_1523_JNEUROSCI_4467_08_2009 crossref_primary_10_1002_hbm_25948 crossref_primary_10_1002_hbm_24859 crossref_primary_10_5334_jeps_cv crossref_primary_10_1093_brain_awad162 crossref_primary_10_1523_JNEUROSCI_5498_10_2012 crossref_primary_10_7554_eLife_51260 crossref_primary_10_1038_npp_2016_143 crossref_primary_10_1523_JNEUROSCI_2636_14_2015 crossref_primary_10_1002_hbm_22665 crossref_primary_10_1073_pnas_1407535111 crossref_primary_10_1093_cercor_bhy166 crossref_primary_10_3724_SP_J_1042_2018_01642 crossref_primary_10_1080_17470919_2017_1370010 crossref_primary_10_1111_j_1460_9568_2012_08017_x crossref_primary_10_1016_j_neuropsychologia_2019_06_002 crossref_primary_10_1038_srep41028 crossref_primary_10_1111_j_1539_6924_2012_01792_x crossref_primary_10_1152_jn_00393_2013 crossref_primary_10_1097_WNR_0b013e3283383482 crossref_primary_10_3389_fpsyg_2017_01253 crossref_primary_10_3389_fnbeh_2022_763220 crossref_primary_10_1073_pnas_1001709107 crossref_primary_10_1016_j_neuron_2014_09_002 crossref_primary_10_3758_s13415_014_0269_8 crossref_primary_10_1523_JNEUROSCI_3524_09_2009 crossref_primary_10_1016_j_jebo_2018_06_014 crossref_primary_10_1016_j_neuroimage_2017_05_041 crossref_primary_10_1016_j_biopsycho_2014_07_013 crossref_primary_10_1016_j_bbr_2015_11_016 crossref_primary_10_1093_schbul_sbw045 crossref_primary_10_1016_j_nicl_2024_103729 crossref_primary_10_1007_s00213_013_3313_4 crossref_primary_10_1556_2006_2021_00010 crossref_primary_10_1002_eat_20984 crossref_primary_10_1098_rstb_2008_0161 crossref_primary_10_1111_tops_12389 crossref_primary_10_3758_s13415_011_0066_6 crossref_primary_10_1111_j_1460_9568_2012_07990_x crossref_primary_10_1002_hbm_26323 crossref_primary_10_1038_s41598_023_33008_2 crossref_primary_10_1016_j_biopsych_2017_02_1183 crossref_primary_10_1007_s12662_012_0230_3 crossref_primary_10_1016_j_brainres_2009_07_007 crossref_primary_10_1371_journal_pone_0080683 crossref_primary_10_1038_nn_3842 crossref_primary_10_1523_JNEUROSCI_2978_14_2015 crossref_primary_10_1007_s12311_021_01282_3 crossref_primary_10_3758_s13415_014_0261_3 crossref_primary_10_7554_eLife_65074 crossref_primary_10_1523_JNEUROSCI_2265_08_2008 crossref_primary_10_1016_j_biopsych_2009_12_027 crossref_primary_10_3171_2009_4_FOCUS0975 crossref_primary_10_1016_j_neubiorev_2016_09_002 crossref_primary_10_1111_nyas_13703 crossref_primary_10_1016_j_bbr_2008_09_029 crossref_primary_10_1016_j_cub_2010_04_055 crossref_primary_10_1016_j_jmp_2008_12_005 crossref_primary_10_1073_pnas_0905191106 crossref_primary_10_1093_scan_nsaa040 crossref_primary_10_1111_tops_12138 crossref_primary_10_1016_j_jpsychires_2015_02_014 crossref_primary_10_1152_jn_00784_2009 crossref_primary_10_1038_nn_3832 crossref_primary_10_1016_j_biopsych_2021_01_009 crossref_primary_10_4306_pi_2013_10_3_266 crossref_primary_10_1016_j_cobeha_2015_08_006 crossref_primary_10_1016_j_neuron_2008_11_027 crossref_primary_10_1093_scan_nst095 crossref_primary_10_1371_journal_pone_0119710 crossref_primary_10_1093_brain_awx025 crossref_primary_10_1016_j_biopsych_2009_06_021 crossref_primary_10_1016_j_neuroimage_2009_11_083 crossref_primary_10_3758_s13415_011_0027_0 crossref_primary_10_1016_j_mehy_2012_01_034 crossref_primary_10_1093_schbul_sbq005 crossref_primary_10_1371_journal_pcbi_1004237 crossref_primary_10_1523_JNEUROSCI_4647_10_2011 crossref_primary_10_3758_s13415_015_0338_7 crossref_primary_10_1016_j_euroneuro_2018_07_102 crossref_primary_10_1146_annurev_clinpsy_032816_044957 crossref_primary_10_1111_j_1460_9568_2011_07920_x crossref_primary_10_1523_JNEUROSCI_6316_10_2011 crossref_primary_10_1007_s10551_016_3058_1 crossref_primary_10_1016_j_neuron_2011_12_025 crossref_primary_10_1016_j_celrep_2018_11_026 crossref_primary_10_1016_j_bpsc_2025_02_014 crossref_primary_10_1038_s42003_025_07561_7 crossref_primary_10_1111_risa_12511 crossref_primary_10_1038_s41598_022_08863_0 crossref_primary_10_1038_s41467_018_04055_5 crossref_primary_10_1016_j_neuroimage_2009_08_011 crossref_primary_10_1523_JNEUROSCI_1859_15_2015 crossref_primary_10_1523_JNEUROSCI_5445_12_2013 crossref_primary_10_1371_journal_pcbi_1003015 crossref_primary_10_1016_j_dcn_2011_07_006 crossref_primary_10_1111_j_1460_9568_2011_07980_x crossref_primary_10_1016_j_conb_2008_08_003 crossref_primary_10_1016_j_neuropsychologia_2016_05_023 crossref_primary_10_1523_JNEUROSCI_1186_22_2022 crossref_primary_10_1371_journal_pcbi_1003387 crossref_primary_10_1016_j_cognition_2018_11_004 crossref_primary_10_3758_s13415_021_00943_4 crossref_primary_10_1523_JNEUROSCI_4341_08_2009 crossref_primary_10_1016_j_biopsych_2012_01_023 crossref_primary_10_1038_npp_2009_131 crossref_primary_10_3758_s13415_014_0297_4 |
Cites_doi | 10.1162/neco.2006.18.7.1637 10.1006/nimg.2000.0593 10.1016/S0893-6080(02)00047-3 10.1016/S0896-6273(02)00963-7 10.1016/j.conb.2004.10.016 10.1038/nn1743 10.1016/S0896-6273(02)00967-4 10.1521/pedi.1993.7.4.285 10.3758/BF03194383 10.1038/nature05051 10.1901/jeab.2005.110-04 10.1038/nature04766 10.1016/S1474-6670(17)38315-5 10.1016/S0896-6273(03)00154-5 10.1038/nn802 10.1177/1073858404263526 10.1016/j.conb.2006.03.006 10.1126/science.1094285 10.1523/JNEUROSCI.3401-04.2005 10.1016/S0896-6273(03)00169-7 10.1016/S0893-6080(02)00046-1 10.1016/S0896-6273(03)00848-1 10.1037/1040-3590.14.4.485 10.1017/S0140525X00003435 10.1016/j.neuroimage.2005.08.006 10.1016/j.bbr.2004.07.006 10.1098/rsta.2004.1468 10.1016/j.tics.2004.11.005 10.1001/archpsyc.1961.01710120031004 10.1523/JNEUROSCI.16-05-01936.1996 10.1037/1040-3590.4.1.5 10.1002/hbm.20186 10.1073/pnas.0608842104 10.1152/jn.2000.84.6.3072 10.1126/science.275.5306.1593 10.1002/(SICI)1099-0771(199809)11:3<161::AID-BDM296>3.0.CO;2-S 10.1016/S0166-2236(98)01373-3 |
ContentType | Journal Article |
Copyright | Copyright © 2007 Society for Neuroscience 0270-6474/07/2712860-08$15.00/0 2007 |
Copyright_xml | – notice: Copyright © 2007 Society for Neuroscience 0270-6474/07/2712860-08$15.00/0 2007 |
DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7TK 7X8 5PM |
DOI | 10.1523/JNEUROSCI.2496-07.2007 |
DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Neurosciences Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Neurosciences Abstracts MEDLINE - Academic |
DatabaseTitleList | MEDLINE - Academic CrossRef MEDLINE Neurosciences 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 | Anatomy & Physiology |
EISSN | 1529-2401 |
EndPage | 12867 |
ExternalDocumentID | PMC6673291 18032658 10_1523_JNEUROSCI_2496_07_2007 www27_47_12860 |
Genre | Research Support, U.S. Gov't, Non-P.H.S Comparative Study Research Support, Non-U.S. Gov't Journal Article |
GroupedDBID | - 2WC 34G 39C 3O- 53G 55 5GY 5RE 5VS ABFLS ABIVO ABPTK ABUFD ACNCT ADACO ADBBV ADCOW AENEX AETEA AFFNX AFMIJ AIZTS AJYGW ALMA_UNASSIGNED_HOLDINGS BAWUL CS3 DIK DL DU5 DZ E3Z EBS EJD F5P FA8 FH7 GX1 H13 HYE H~9 KQ8 L7B MVM O0- OK1 P0W P2P QZG R.V RHF RHI RPM TFN UQL WH7 WOQ X X7M XJT ZA5 --- -DZ -~X .55 18M AAFWJ AAJMC AAYXX ABBAR ACGUR ADHGD ADXHL AFCFT AFOSN AFSQR AHWXS AOIJS BTFSW CITATION TR2 W8F YBU YHG YKV YNH YSK CGR CUY CVF ECM EIF NPM 7TK 7X8 5PM |
ID | FETCH-LOGICAL-c542t-5dc5e7ddd92bc363f6012825dbdc9c8fb6f18452e275c1bbf547ec8f318f95863 |
ISSN | 0270-6474 1529-2401 |
IngestDate | Thu Aug 21 14:14:32 EDT 2025 Fri Jul 11 12:13:53 EDT 2025 Fri Jul 11 07:30:27 EDT 2025 Mon Jul 21 06:02:39 EDT 2025 Tue Jul 01 02:58:50 EDT 2025 Thu Apr 24 22:58:41 EDT 2025 Tue Nov 10 19:50:54 EST 2020 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 47 |
Language | English |
License | https://creativecommons.org/licenses/by-nc-sa/4.0 |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-c542t-5dc5e7ddd92bc363f6012825dbdc9c8fb6f18452e275c1bbf547ec8f318f95863 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
OpenAccessLink | https://www.jneurosci.org/content/jneuro/27/47/12860.full.pdf |
PMID | 18032658 |
PQID | 20332974 |
PQPubID | 23462 |
PageCount | 8 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_6673291 proquest_miscellaneous_68539162 proquest_miscellaneous_20332974 pubmed_primary_18032658 crossref_citationtrail_10_1523_JNEUROSCI_2496_07_2007 crossref_primary_10_1523_JNEUROSCI_2496_07_2007 highwire_smallpub1_www27_47_12860 |
ProviderPackageCode | RHF RHI CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2007-11-21 |
PublicationDateYYYYMMDD | 2007-11-21 |
PublicationDate_xml | – month: 11 year: 2007 text: 2007-11-21 day: 21 |
PublicationDecade | 2000 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States |
PublicationTitle | The Journal of neuroscience |
PublicationTitleAlternate | J Neurosci |
PublicationYear | 2007 |
Publisher | Soc Neuroscience Society for Neuroscience |
Publisher_xml | – name: Soc Neuroscience – name: Society for Neuroscience |
References | 2023041303284256000_27.47.12860.29 2023041303284256000_27.47.12860.27 2023041303284256000_27.47.12860.28 2023041303284256000_27.47.12860.14 2023041303284256000_27.47.12860.36 2023041303284256000_27.47.12860.15 2023041303284256000_27.47.12860.37 2023041303284256000_27.47.12860.12 2023041303284256000_27.47.12860.34 2023041303284256000_27.47.12860.13 2023041303284256000_27.47.12860.10 2023041303284256000_27.47.12860.32 Delgado (2023041303284256000_27.47.12860.11) 2000; 84 2023041303284256000_27.47.12860.33 2023041303284256000_27.47.12860.30 2023041303284256000_27.47.12860.31 2023041303284256000_27.47.12860.5 2023041303284256000_27.47.12860.6 2023041303284256000_27.47.12860.3 2023041303284256000_27.47.12860.4 2023041303284256000_27.47.12860.9 2023041303284256000_27.47.12860.7 2023041303284256000_27.47.12860.8 Montague (2023041303284256000_27.47.12860.22) 1996; 16 2023041303284256000_27.47.12860.1 2023041303284256000_27.47.12860.18 2023041303284256000_27.47.12860.2 2023041303284256000_27.47.12860.19 2023041303284256000_27.47.12860.16 2023041303284256000_27.47.12860.38 2023041303284256000_27.47.12860.17 2023041303284256000_27.47.12860.39 2023041303284256000_27.47.12860.25 2023041303284256000_27.47.12860.26 2023041303284256000_27.47.12860.23 2023041303284256000_27.47.12860.24 Stanovich (2023041303284256000_27.47.12860.35) 2003; 31 2023041303284256000_27.47.12860.21 2023041303284256000_27.47.12860.20 2023041303284256000_27.47.12860.40 |
References_xml | – ident: 2023041303284256000_27.47.12860.7 doi: 10.1162/neco.2006.18.7.1637 – ident: 2023041303284256000_27.47.12860.17 doi: 10.1006/nimg.2000.0593 – ident: 2023041303284256000_27.47.12860.14 doi: 10.1016/S0893-6080(02)00047-3 – ident: 2023041303284256000_27.47.12860.10 doi: 10.1016/S0896-6273(02)00963-7 – ident: 2023041303284256000_27.47.12860.26 doi: 10.1016/j.conb.2004.10.016 – ident: 2023041303284256000_27.47.12860.23 doi: 10.1038/nn1743 – ident: 2023041303284256000_27.47.12860.32 doi: 10.1016/S0896-6273(02)00967-4 – ident: 2023041303284256000_27.47.12860.16 doi: 10.1521/pedi.1993.7.4.285 – volume: 31 start-page: 243 year: 2003 ident: 2023041303284256000_27.47.12860.35 article-title: Is probability matching smart? Associations between probabilistic choices and cognitive ability publication-title: Mem Cognit doi: 10.3758/BF03194383 – ident: 2023041303284256000_27.47.12860.29 doi: 10.1038/nature05051 – ident: 2023041303284256000_27.47.12860.18 doi: 10.1901/jeab.2005.110-04 – ident: 2023041303284256000_27.47.12860.8 doi: 10.1038/nature04766 – ident: 2023041303284256000_27.47.12860.38 doi: 10.1016/S1474-6670(17)38315-5 – ident: 2023041303284256000_27.47.12860.9 – ident: 2023041303284256000_27.47.12860.20 doi: 10.1016/S0896-6273(03)00154-5 – ident: 2023041303284256000_27.47.12860.28 doi: 10.1038/nn802 – ident: 2023041303284256000_27.47.12860.5 – ident: 2023041303284256000_27.47.12860.21 doi: 10.1177/1073858404263526 – ident: 2023041303284256000_27.47.12860.6 doi: 10.1016/j.conb.2006.03.006 – ident: 2023041303284256000_27.47.12860.25 doi: 10.1126/science.1094285 – ident: 2023041303284256000_27.47.12860.1 – ident: 2023041303284256000_27.47.12860.34 doi: 10.1523/JNEUROSCI.3401-04.2005 – ident: 2023041303284256000_27.47.12860.27 doi: 10.1016/S0896-6273(03)00169-7 – ident: 2023041303284256000_27.47.12860.37 doi: 10.1016/S0893-6080(02)00046-1 – ident: 2023041303284256000_27.47.12860.39 doi: 10.1016/S0896-6273(03)00848-1 – ident: 2023041303284256000_27.47.12860.12 doi: 10.1037/1040-3590.14.4.485 – ident: 2023041303284256000_27.47.12860.36 doi: 10.1017/S0140525X00003435 – ident: 2023041303284256000_27.47.12860.40 doi: 10.1016/j.neuroimage.2005.08.006 – ident: 2023041303284256000_27.47.12860.15 doi: 10.1016/j.bbr.2004.07.006 – ident: 2023041303284256000_27.47.12860.3 doi: 10.1098/rsta.2004.1468 – ident: 2023041303284256000_27.47.12860.24 doi: 10.1016/j.tics.2004.11.005 – ident: 2023041303284256000_27.47.12860.2 doi: 10.1001/archpsyc.1961.01710120031004 – volume: 16 start-page: 1936 year: 1996 ident: 2023041303284256000_27.47.12860.22 article-title: A framework for mesencephalic dopamine systems based on predictive Hebbian learning publication-title: J Neurosci doi: 10.1523/JNEUROSCI.16-05-01936.1996 – ident: 2023041303284256000_27.47.12860.4 doi: 10.1037/1040-3590.4.1.5 – ident: 2023041303284256000_27.47.12860.31 doi: 10.1002/hbm.20186 – ident: 2023041303284256000_27.47.12860.19 doi: 10.1073/pnas.0608842104 – volume: 84 start-page: 3072 year: 2000 ident: 2023041303284256000_27.47.12860.11 article-title: Tracking the hemodynamic responses to reward and punishment in the striatum publication-title: J Neurophysiol doi: 10.1152/jn.2000.84.6.3072 – ident: 2023041303284256000_27.47.12860.33 doi: 10.1126/science.275.5306.1593 – ident: 2023041303284256000_27.47.12860.13 doi: 10.1002/(SICI)1099-0771(199809)11:3<161::AID-BDM296>3.0.CO;2-S – ident: 2023041303284256000_27.47.12860.30 doi: 10.1016/S0166-2236(98)01373-3 |
SSID | ssj0007017 |
Score | 2.4106307 |
Snippet | The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and... |
SourceID | pubmedcentral proquest pubmed crossref highwire |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 12860 |
SubjectTerms | Adult Corpus Striatum - physiology Decision Making - physiology Female Humans Learning - physiology Male Psychomotor Performance - physiology Reinforcement (Psychology) Reward |
Title | Reinforcement Learning Signals in the Human Striatum Distinguish Learners from Nonlearners during Reward-Based Decision Making |
URI | http://www.jneurosci.org/cgi/content/abstract/27/47/12860 https://www.ncbi.nlm.nih.gov/pubmed/18032658 https://www.proquest.com/docview/20332974 https://www.proquest.com/docview/68539162 https://pubmed.ncbi.nlm.nih.gov/PMC6673291 |
Volume | 27 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1bb9owFLZQ97KXaVt3YVdPmvaCQsGx4_DY0k1dp6KutFLfosRxChIEtAah7WF_dn9k59jOBcS0rS8RGDuYnA_72P7Odwh5H4dx7PcGypPgbHtcKu4laZZ6vha-0LGfhpblOwpOrvjptbhutX41WEurIumqHzvjSu5iVSgDu2KU7H9YtropFMBrsC9cwcJw_ScbX2ije6rMFl8plXrTGU9vjCqyozDaffox5ucoVnPU20Sq8wqljEwTDOE1USajRT4rC1z44oU2rNojmOuQsWzz8XTOTAqrpl9bR5gZ37ahklkBZ6wmeCp_FFSUskv7SOxG-dqO9biTP9UwFHdrbo8lEhzHy0leTSJI0jleTFAZuGQUd867G3sYEoP5WL2H0SSojrY7aMdCJmGVy21Cn652YzUzh0P95mBuhQYcaK2WpxuaYSK2mQvcPI_v5c5JRBgxi9MRcinHw89dWKEGXk8a2YJmAwDDcm6g1Q974AZbDfot-e7zsyFmVmWosHCPwVoG02x8-VpL2sueSQtd_UIXxg6dONjdBdS5dd-36UyVAte7FkvbnN-GE3X5kDxwCKGHFsqPSEvnj8n-YR4Xi_l3-oEaPrI56NknPzfQTUt0U4duOs0poJsadNMS3bSBblqimyK6aQPd1KKbNtFNS3RTi-4n5OrTx8vhieeyhXhKcFZ4IlVCyzRNByxRfuBnAfpeTKRJqgYqzJIg64dcMM2kUP0kyQSXGsphUssGIgz8p2QvX-T6OaGc9eI4hYpQi3PFwjRTaRaAvyd4EodJm4jysUfKSeljRpdZhEtqsFxUWS5Cy0U9ieleZZscVO2WVkzmry3elVaNbufxbAZG7Efr9ZrJiMvIYLpN3pbmjmBuwAO_ONeL1S3cwQfgSf7nGgF467BAZG3yzMKj7peDWJvIDeBUFVCXfvOTfDox-vQO7y_u3PIluV-PEq_IXvFtpV-D718kb8x_5zfdCwgP |
linkProvider | Colorado Alliance of Research Libraries |
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=Reinforcement+Learning+Signals+in+the+Human+Striatum+Distinguish+Learners+from+Nonlearners+during+Reward-Based+Decision+Making&rft.jtitle=The+Journal+of+neuroscience&rft.au=Sch%C3%B6nberg%2C+Tom&rft.au=Daw%2C+Nathaniel+D.&rft.au=Joel%2C+Daphna&rft.au=O%27Doherty%2C+John+P.&rft.date=2007-11-21&rft.pub=Society+for+Neuroscience&rft.issn=0270-6474&rft.eissn=1529-2401&rft.volume=27&rft.issue=47&rft.spage=12860&rft.epage=12867&rft_id=info:doi/10.1523%2FJNEUROSCI.2496-07.2007&rft_id=info%3Apmid%2F18032658&rft.externalDocID=PMC6673291 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0270-6474&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0270-6474&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0270-6474&client=summon |