Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation.
<p>Typical path of meaning extracted from sequential-presentation trial. Subsequent “training” stimuli do not affect initial hypothesis so long as consistent. If inconsistent, then a new hypothesis is generated (not depicted here).</p>
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2025
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| _version_ | 1852018745936969728 |
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| author | Spencer Caplan (10188380) |
| author_facet | Spencer Caplan (10188380) |
| author_role | author |
| dc.creator.none.fl_str_mv | Spencer Caplan (10188380) |
| dc.date.none.fl_str_mv | 2025-07-03T17:46:35Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0327615.g004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Algorithmic_flow_chart_highlighting_a_possible_path_of_NGM_behavior_under_sequential-presentation_/29472490 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Neuroscience Sociology Science Policy Mental Health Biological Sciences not elsewhere classified existing data demonstrates presented &# 8212 poodle &# 8221 na &# 239 sce )&# 8212 factors influencing generalization mechanistic processes rather guiding learner behavior training objects facilitates &# 8220 sce seems learner end generalization model dogs rather algorithmic processes training objects training items rational behavior independent behavior human behavior xlink "> vice versa unified way tuned output temporal manner statistical inference specified hypotheses specific subset semantic generalizations sample size quantitative parameter qualitative parameter previously referred possible interactions models based independent effect hierarchical relation global optimization fundamental question either simultaneously computational model category formation |
| dc.title.none.fl_str_mv | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Typical path of meaning extracted from sequential-presentation trial. Subsequent “training” stimuli do not affect initial hypothesis so long as consistent. If inconsistent, then a new hypothesis is generated (not depicted here).</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_32043cdc56d19cf0ecd4e171eaa9d389 |
| identifier_str_mv | 10.1371/journal.pone.0327615.g004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29472490 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation.Spencer Caplan (10188380)NeuroscienceSociologyScience PolicyMental HealthBiological Sciences not elsewhere classifiedexisting data demonstratespresented &# 8212poodle &# 8221na &# 239sce )&# 8212factors influencing generalizationmechanistic processes ratherguiding learner behaviortraining objects facilitates&# 8220sce seemslearner endgeneralization modeldogs ratheralgorithmic processestraining objectstraining itemsrational behaviorindependent behaviorhuman behaviorxlink ">vice versaunified waytuned outputtemporal mannerstatistical inferencespecified hypothesesspecific subsetsemantic generalizationssample sizequantitative parameterqualitative parameterpreviously referredpossible interactionsmodels basedindependent effecthierarchical relationglobal optimizationfundamental questioneither simultaneouslycomputational modelcategory formation<p>Typical path of meaning extracted from sequential-presentation trial. Subsequent “training” stimuli do not affect initial hypothesis so long as consistent. If inconsistent, then a new hypothesis is generated (not depicted here).</p>2025-07-03T17:46:35ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0327615.g004https://figshare.com/articles/figure/Algorithmic_flow_chart_highlighting_a_possible_path_of_NGM_behavior_under_sequential-presentation_/29472490CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/294724902025-07-03T17:46:35Z |
| spellingShingle | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. Spencer Caplan (10188380) Neuroscience Sociology Science Policy Mental Health Biological Sciences not elsewhere classified existing data demonstrates presented &# 8212 poodle &# 8221 na &# 239 sce )&# 8212 factors influencing generalization mechanistic processes rather guiding learner behavior training objects facilitates &# 8220 sce seems learner end generalization model dogs rather algorithmic processes training objects training items rational behavior independent behavior human behavior xlink "> vice versa unified way tuned output temporal manner statistical inference specified hypotheses specific subset semantic generalizations sample size quantitative parameter qualitative parameter previously referred possible interactions models based independent effect hierarchical relation global optimization fundamental question either simultaneously computational model category formation |
| status_str | publishedVersion |
| title | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. |
| title_full | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. |
| title_fullStr | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. |
| title_full_unstemmed | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. |
| title_short | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. |
| title_sort | Algorithmic flow chart highlighting a possible path of NGM behavior under sequential-presentation. |
| topic | Neuroscience Sociology Science Policy Mental Health Biological Sciences not elsewhere classified existing data demonstrates presented &# 8212 poodle &# 8221 na &# 239 sce )&# 8212 factors influencing generalization mechanistic processes rather guiding learner behavior training objects facilitates &# 8220 sce seems learner end generalization model dogs rather algorithmic processes training objects training items rational behavior independent behavior human behavior xlink "> vice versa unified way tuned output temporal manner statistical inference specified hypotheses specific subset semantic generalizations sample size quantitative parameter qualitative parameter previously referred possible interactions models based independent effect hierarchical relation global optimization fundamental question either simultaneously computational model category formation |