Literature DB >> 26212883

Representation of numerical and sequential patterns in macaque and human brains.

Liping Wang1, Lynn Uhrig2, Bechir Jarraya3, Stanislas Dehaene4.   

Abstract

The ability to extract deep structures from auditory sequences is a fundamental prerequisite of language acquisition. Using fMRI in untrained macaques and humans, we investigated the brain areas involved in representing two abstract properties of a series of tones: total number of items and tone-repetition pattern. Both species represented the number of tones in intraparietal and dorsal premotor areas and the tone-repetition pattern in ventral prefrontal cortex and basal ganglia. However, we observed a joint sensitivity to both parameters only in humans, within bilateral inferior frontal and superior temporal regions. In the left hemisphere, those sites coincided with areas involved in language processing. Thus, while some abstract properties of auditory sequences are available to non-human primates, a recently evolved circuit may endow humans with a unique ability for representing linguistic and non-linguistic sequences in a unified manner.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 26212883     DOI: 10.1016/j.cub.2015.06.035

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  37 in total

1.  Sequential Control Underlies Robust Ramping Dynamics in the Rostrolateral Prefrontal Cortex.

Authors:  Theresa M Desrochers; Anne G E Collins; David Badre
Journal:  J Neurosci       Date:  2018-12-21       Impact factor: 6.167

2.  fMRI reveals language-specific predictive coding during naturalistic sentence comprehension.

Authors:  Cory Shain; Idan Asher Blank; Marten van Schijndel; William Schuler; Evelina Fedorenko
Journal:  Neuropsychologia       Date:  2019-12-24       Impact factor: 3.139

Review 3.  Broca's Area Is Not a Natural Kind.

Authors:  Evelina Fedorenko; Idan A Blank
Journal:  Trends Cogn Sci       Date:  2020-02-20       Impact factor: 20.229

4.  Brain networks for confidence weighting and hierarchical inference during probabilistic learning.

Authors:  Florent Meyniel; Stanislas Dehaene
Journal:  Proc Natl Acad Sci U S A       Date:  2017-04-24       Impact factor: 11.205

Review 5.  Empirical approaches to the study of language evolution.

Authors:  W Tecumseh Fitch
Journal:  Psychon Bull Rev       Date:  2017-02

6.  Symbolic labeling in 5-month-old human infants.

Authors:  Claire Kabdebon; Ghislaine Dehaene-Lambertz
Journal:  Proc Natl Acad Sci U S A       Date:  2019-03-05       Impact factor: 11.205

7.  Origins of the brain networks for advanced mathematics in expert mathematicians.

Authors:  Marie Amalric; Stanislas Dehaene
Journal:  Proc Natl Acad Sci U S A       Date:  2016-04-11       Impact factor: 11.205

8.  Lack of selectivity for syntax relative to word meanings throughout the language network.

Authors:  Evelina Fedorenko; Idan Asher Blank; Matthew Siegelman; Zachary Mineroff
Journal:  Cognition       Date:  2020-06-20

9.  Infants' representations of same and different in match- and non-match-to-sample.

Authors:  Jean-Rémy Hochmann; Shilpa Mody; Susan Carey
Journal:  Cogn Psychol       Date:  2016-03-09       Impact factor: 3.468

Review 10.  Language and thought are not the same thing: evidence from neuroimaging and neurological patients.

Authors:  Evelina Fedorenko; Rosemary Varley
Journal:  Ann N Y Acad Sci       Date:  2016-04-20       Impact factor: 5.691

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