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. 2015 Apr 15;10(4):e0121804.
doi: 10.1371/journal.pone.0121804. eCollection 2015.

Cognitive demands of lower paleolithic toolmaking

Affiliations

Cognitive demands of lower paleolithic toolmaking

Dietrich Stout et al. PLoS One. .

Erratum in

Abstract

Stone tools provide some of the most abundant, continuous, and high resolution evidence of behavioral change over human evolution, but their implications for cognitive evolution have remained unclear. We investigated the neurophysiological demands of stone toolmaking by training modern subjects in known Paleolithic methods ("Oldowan", "Acheulean") and collecting structural and functional brain imaging data as they made technical judgments (outcome prediction, strategic appropriateness) about planned actions on partially completed tools. Results show that this task affected neural activity and functional connectivity in dorsal prefrontal cortex, that effect magnitude correlated with the frequency of correct strategic judgments, and that the frequency of correct strategic judgments was predictive of success in Acheulean, but not Oldowan, toolmaking. This corroborates hypothesized cognitive control demands of Acheulean toolmaking, specifically including information monitoring and manipulation functions attributed to the "central executive" of working memory. More broadly, it develops empirical methods for assessing the differential cognitive demands of Paleolithic technologies, and expands the scope of evolutionary hypotheses that can be tested using the available archaeological record.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Handaxes produced for the first (left) and last (right) evaluations, ranked by T3 fMRI task performance (circled numbers).
Fig 2
Fig 2. Location of the significant 3-way interaction in left SFG (top) and the relation of fMRI signal change to task performance (bottom).
Arrows a—d indicate significant pairwise differences across time and tasks. e is a regression line (r = 0.294).
Fig 3
Fig 3. fMRI main effect of Time in (from left to right) left middle occipital gyrus, right posterior intrapareital sulcus, and right precentral gyrus.
Brackets indicate significant post-hoc comparisons.
Fig 4
Fig 4. Anatomical and functional connectivity of the left SFG cluster.
(a) Radar plot of top targets for SFG sub-regions using data reported by Li et al. [40] (blue: lSFGam, red: lSFGdl, green: lSFGp) and our own analysis of the lSFG cluster reported here (purple). ACC: anterior cingulate cortex, Cau: caudate, MFG: middle frontal gyrus, IFG_Tri: inferior frontal gyrus pars triangularis, IFG_Oper: inferior frontal gyrus pars opercularis, PreCG: precnetral gyrus, Th: thalamus, PCC: posterior cingulate cortex, MCC: middle cingulate cortex. (b) Surface renders of significant experimental effects on functional connectivity (hot scale: increased for Prediction vs. Strategy, cold scale: increased for Strategy vs. Prediction, tangerine: Task x Time interaction). (c) Regression coefficients for the Task x Time interaction with significant post-hoc comparisons indicated by brackets.
Fig 5
Fig 5. fcMRI interaction of Time and Technology in middle temporal gyrus and cerebellum.
Brackets indicate significant post-hoc comparisons.
Fig 6
Fig 6. fcMRI interaction of Time, Technology, and Task in right Superior Frontal Gyrus.
Brackets indicate significant post-hoc comparisons.

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