Structured sequence learning across sensory modalities in humans and nonhuman primates
Tài liệu tham khảo
Saffran, 2001, The acquisition of language by children, Proc Natl Acad Sci U S A, 98, 12874, 10.1073/pnas.231498898
Turk-Browne, 2009, Neural evidence of statistical learning: efficient detection of visual regularities without awareness, J Cogn Neurosci, 21, 1934, 10.1162/jocn.2009.21131
Grafton, 1995, Functional mapping of sequence learning in normal humans, J Cogn Neurosci, 7, 497, 10.1162/jocn.1995.7.4.497
Courville, 2006, Bayesian theories of conditioning in a changing world, Trends Cogn Sci, 10, 294, 10.1016/j.tics.2006.05.004
Altmann, 1995, Modality independence of implicitly learned grammatical knowledge, J Exp Psychol Learn Mem Cogn, 21, 899, 10.1037/0278-7393.21.4.899
Conway, 2005, Modality-constrained statistical learning of tactile, visual, and auditory sequences, J Exp Psychol Learn Mem Cogn, 31, 24, 10.1037/0278-7393.31.1.24
Conway, 2006, Statistical learning within and between modalities: pitting abstract against stimulus-specific representations, Psychol Sci, 17, 905, 10.1111/j.1467-9280.2006.01801.x
Emberson, 2011, Timing is everything: changes in presentation rate have opposite effects on auditory and visual implicit statistical learning, Q J, 69, 2390
Frost, 2015, Domain generality versus modality specificity: the paradox of statistical learning, Trends Cogn Sci, 19, 117, 10.1016/j.tics.2014.12.010
Reber, 1967, Implicit learning of artificial grammars, J Verb Learn Verb Behav, 6, 855, 10.1016/S0022-5371(67)80149-X
Saffran, 1996, Statistical learning by 8-month-old infants, Science, 274, 1926, 10.1126/science.274.5294.1926
Christiansen MH: Implicit-statistical learning: a tale of two literatures. Top Cogn Sci [in press].
Conway, 2008, Neurocognitive basis of implicit learning of sequential structure and its relation to language processing, Ann N Y Acad Sci, 1145, 113, 10.1196/annals.1416.009
Kidd, 2016, Individual differences in statistical learning predict children's comprehension of syntax, Child Dev, 87, 184, 10.1111/cdev.12461
Misyak, 2012, Statistical learning and language: an individual differences study, Lang Learn, 62, 302, 10.1111/j.1467-9922.2010.00626.x
Wilson, 2013, Auditory artificial grammar learning in macaque and marmoset monkeys, J Neurosci, 33, 18825, 10.1523/JNEUROSCI.2414-13.2013
Wilson, 2017, Conserved sequence processing in primate frontal cortex, Trends Neurosci, 40, 72, 10.1016/j.tins.2016.11.004
Santolin, 2017, Constraints on statistical learning across species, Trends Cogn Sci
Christiansen, 2015, The language faculty that wasn’t: a usage-based account of natural language recursion, Front Psychol, 6, 1182, 10.3389/fpsyg.2015.01182
Uddén J, Männel CM: AGL and its neurobiology in relation to language processing and development. Oxford Handbook of Psycholinguistics [in press] https://doi.org/10.17605/OSF.IO/FDT69.
De Vries, 2011, Learning recursion: multiple nested and crossed dependencies, Biolinguistics, 5, 010, 10.5964/bioling.8825
Milne, 2017, Auditory and visual sequence learning in humans and monkeys using an artificial grammar learning paradigm, Neuroscience
Tunney, 1999, The transfer effect in artificial grammar learning: reappraising the evidence on the transfer of sequential dependencies, J Exp Psychol Learn Mem Cogn, 25, 1322, 10.1037/0278-7393.25.5.1322
Daltrozzo, 2014, Neurocognitive mechanisms of statistical-sequential learning: what do event-related potentials tell us?, Front Hum Neurosci, 8, 1, 10.3389/fnhum.2014.00437
Gomez, 2000, The basis of transfer in artificial grammar learning, Mem Cognit, 28, 253, 10.3758/BF03213804
Onnis, 2013, Language experience changes subsequent learning, Cognition, 126, 268, 10.1016/j.cognition.2012.10.008
Seitz, 2007, Simultaneous and independent acquisition of multisensory and unisensory associations, Percept Lond, 36, 1445, 10.1068/p5843
Cope, 2017, Artificial grammar learning in vascular and progressive non-fluent aphasias, Neuropsychologia, 10.1016/j.neuropsychologia.2017.08.022
Walk, 2016, Cross-domain statistical-sequential dependencies are difficult to learn, Front Psychol, 7, 1, 10.3389/fpsyg.2016.00250
Siegelman, 2017, Towards a theory of individual differences in statistical learning, Philos Trans R Soc B Biol Sci, 372, 20160059, 10.1098/rstb.2016.0059
Fitch, 2010
Hauser, 2009, Can free-ranging rhesus monkeys (Macaca mulatta) extract artificially created rules comprised of natural vocalizations?, J Comp Psychol, 123, 161, 10.1037/a0015584
Newport, 2004, Learning at a distance II. Statistical learning of non-adjacent dependencies in a non-human primate, Cogn Psychol, 49, 85, 10.1016/j.cogpsych.2003.12.002
Ravignani, 2013, Action at a distance: dependency sensitivity in a New World primate, Biol Lett, 9, 20130852, 10.1098/rsbl.2013.0852
Sonnweber, 2015, Non-adjacent visual dependency learning in chimpanzees, Anim Cogn, 18, 733, 10.1007/s10071-015-0840-x
Heimbauer, 2012, A Serial Reaction Time (SRT) task with symmetrical joystick responding for nonhuman primates, Behav Res Methods, 44, 733, 10.3758/s13428-011-0177-6
Saffran, 2008, Grammatical pattern learning by human infants and cotton-top tamarin monkeys, Cognition, 107, 479, 10.1016/j.cognition.2007.10.010
Conway, 2001, Review: sequential learning in non-human primates, Trends Cogn Sci, 5, 539, 10.1016/S1364-6613(00)01800-3
Hauser, 2001, Segmentation of the speech stream in a non-human primate: statistical learning in cotton-top tamarins, Cognition, 78, B53, 10.1016/S0010-0277(00)00132-3
Attaheri, 2015, EEG potentials associated with artificial grammar learning in the primate brain, Brain Lang, 148, 74, 10.1016/j.bandl.2014.11.006
Milne, 2016, Evolutionary origins of non-adjacent sequence processing in primate brain potentials, Sci Rep, 6, 36259, 10.1038/srep36259
Wang, 2015, Representation of numerical and sequential patterns in macaque and human brains, Curr Biol, 25, 1966, 10.1016/j.cub.2015.06.035
Wilson, 2015, Auditory sequence processing reveals evolutionarily conserved regions of frontal cortex in macaques and humans, Nat Commun, 6, 1, 10.1038/ncomms9901
Ravignani, 2017, Chimpanzees process structural isomorphisms across sensory modalities, Cognition, 161, 74, 10.1016/j.cognition.2017.01.005
Siegelman, 2017, Re-defining ‘learning’ in statistical learning: what does an online measure reveal about the assimilation of visual regularities?, Cogn Sci
Fagot, 2014, Effects of freely accessible computerized test systems on the spontaneous behaviors and stress level of Guinea baboons (Papio papio), Am J Primatol, 76, 56, 10.1002/ajp.22193
Grainger, 2012, Orthographic processing in Baboons (Papio papio), Science, 336, 245, 10.1126/science.1218152
Bekinschtein, 2009, Neural signature of the conscious processing of auditory regularities, Proc Natl Acad Sci U S A, 106, 1672, 10.1073/pnas.0809667106
Friederici, 2006, The brain differentiates human and non-human grammars: functional localization and structural connectivity, Proc Natl Acad Sci U S A, 103, 2458, 10.1073/pnas.0509389103
Petersson, 2004, Artificial syntactic violations activate Broca's region, Cogn Sci, 28, 383
Christiansen, 2014, Cultural recycling of neural substrates during language evolution and development, 675
Kikuchi, 2017, Sequence learning modulates neural responses and oscillatory coupling in human and monkey auditory cortex, PLOS Biol, 15, e2000219, 10.1371/journal.pbio.2000219
Hasson, 2017, The neurobiology of uncertainty: implications for statistical learning, Philos Trans R Soc B Biol Sci, 372, 20160048, 10.1098/rstb.2016.0048
Lieberman, 2004, An event-related fMRI study of artificial grammar learning in a balanced chunk strength design, J Cogn Neurosci, 16, 427, 10.1162/089892904322926764
Folia, 2014, Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect, Front Psychol, 5, 1, 10.3389/fpsyg.2014.00041
Meyer, 2011, Statistical learning of visual transitions in monkey inferotemporal cortex, Proc Natl Acad Sci U S A, 108, 19401, 10.1073/pnas.1112895108
Meyer, 2014, Statistical learning of serial visual transitions by neurons in monkey inferotemporal cortex, J Neurosci, 34, 9332, 10.1523/JNEUROSCI.1215-14.2014
Conway, 2009, Seeing and hearing in space and time: effects of modality and presentation rate on implicit statistical learning, Eur J Cogn Psychol, 21, 561, 10.1080/09541440802097951
Zimmerer, 2011, Individual behavior in learning of an artificial grammar, Mem Cognit, 39, 491, 10.3758/s13421-010-0039-y
Durrant, 2016, Cross-modal transfer of statistical information benefits from sleep, Cortex, 78, 85, 10.1016/j.cortex.2016.02.011
Mitchel, 2011, Learning across senses: cross-modal effects in multisensory statistical learning, J Exp Psychol Learn Mem Cogn, 37, 1081, 10.1037/a0023700
Mitchel, 2014, Multimodal integration in statistical learning: evidence from the McGurk illusion, Front Psychol, 5
Robinson, 2007, Visual processing speed: effects of auditory input on visual processing, Dev Sci, 10, 734, 10.1111/j.1467-7687.2007.00627.x
van den Bos, 2012, Statistical learning of probabilistic nonadjacent dependencies by multiple-cue integration, J Mem Lang, 67, 507, 10.1016/j.jml.2012.07.008
Siegelman, 2015, Statistical learning as an individual ability: theoretical perspectives and empirical evidence, J Mem Lang, 81, 105, 10.1016/j.jml.2015.02.001
Cunillera, 2009, Time course and functional neuroanatomy of speech segmentation in adults, Neuroimage, 48, 541, 10.1016/j.neuroimage.2009.06.069
Goranskaya, 2016, Fronto-parietal contributions to phonological processes in successful artificial grammar learning, Front Hum Neurosci, 10, 551, 10.3389/fnhum.2016.00551
Karuza, 2013, The neural correlates of statistical learning in a word segmentation task: an fMRI study, Brain Lang, 127, 46, 10.1016/j.bandl.2012.11.007
Bahlmann, 2008, Hierarchical artificial grammar processing engages Broca's area, Neuroimage, 42, 525, 10.1016/j.neuroimage.2008.04.249
Bahlmann, 2012, Levels of integration in cognitive control and sequence processing in the prefrontal cortex, PLoS ONE, 7, e43774, 10.1371/journal.pone.0043774
Forkstam, 2006, Neural correlates of artificial syntactic structure classification, Neuroimage, 32, 956, 10.1016/j.neuroimage.2006.03.057
Hauser, 2012, Rule and similarity in grammar: their interplay and individual differences in the brain, Neuroimage, 60, 2019, 10.1016/j.neuroimage.2012.02.016
Kepinska, 2017, On neural correlates of individual differences in novel grammar learning: an fMRI study, Neuropsychologia, 98, 156, 10.1016/j.neuropsychologia.2016.06.014
Aizenstein, 2004, Regional brain activation during concurrent implicit and explicit sequence learning, Cereb Cortex, 14, 199, 10.1093/cercor/bhg119
Bahlmann, 2009, Neural circuits of hierarchical visuo-spatial sequence processing, Brain Res, 1298, 161, 10.1016/j.brainres.2009.08.017
Thiel, 2003, Neuronal correlates of familiarity-driven decisions in artificial grammar learning, Neuroreport, 14, 131, 10.1097/00001756-200301200-00024
Van Opstal, 2009, The neural representation of extensively trained ordered sequences, Neuroimage, 47, 367, 10.1016/j.neuroimage.2009.04.035