At the core of reasoning: Dissociating deductive and non‐deductive load

Abstract

In recent years, neuroimaging methods have been used to investigate how the human mind carries out deductive reasoning. According to some, the neural substrate of language is integral to deductive reasoning. According to others, deductive reasoning is supported by a language-independent distributed network including left frontopolar and frontomedial cortices. However, it has been suggested that activity in these frontal regions might instead reflect non-deductive factors such as working memory load and general cognitive difficulty. To address this issue, 20 healthy volunteers participated in an fMRI experiment in which they evaluated matched simple and complex deductive and non-deductive arguments in a 2 × 2 design. The contrast of complex versus simple deductive trials resulted in a pattern of activation closely matching previous work, including frontopolar and frontomedial "core" areas of deduction as well as other "cognitive support" areas in frontoparietal cortices. Conversely, the contrast of complex and simple non-deductive trials resulted in a pattern of activation that does not include any of the aforementioned "core" areas. Direct comparison of the load effect across deductive and non-deductive trials further supports the view that activity in the regions previously interpreted as "core" to deductive reasoning cannot merely reflect non-deductive load, but instead might reflect processes specific to the deductive calculus. Finally, consistent with previous reports, the classical language areas in left inferior frontal gyrus and posterior temporal cortex do not appear to participate in deductive inference beyond their role in encoding stimuli presented in linguistic format.

Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network

“…Rather than recruiting perisylvian fronto-temporal areas, mathematics and logic recruit a frontoparietal network, including the dorsolateral prefrontal cortex and the intraparietal sulcus (IPS) as well as putative symbol representations (i.e. numberform area) in inferior temporal cortex (Amalric & Dehaene, 2016;Coetzee & Monti, 2018;Goel et al, 2007;Monti, Parsons, & Osherson, 2009). This fronto-parietal network overlaps partially with the so called central executive/working memory system, which is implicated in a variety of cognitive tasks that involve maintaining and manipulating information in working memory, processes that are part and parcel of understanding and writing code (Brooks, 1977;Duncan, 2010;Letovsky, 1987;Miller & Cohen, 2001;Soloway & Ehrlich, 1984;Weinberg, 1971;Zanto & Gazzaley, 2013)(for a review of the cognitive models of code comprehension, see (Von Mayrhauser & Vans, 1995)).…”

“…Logic and math activate a similar network but also have unique neural signatures. Within the prefrontal cortex, logic recruits more anterior regions associated with more advanced forms of reasoning and symbol manipulation (Coetzee & Monti, 2018;Ramnani & Owen, 2004).…”

Dissociating language and thought in human reasoning

“…This should have been perhaps 157 expected, given the general understanding that deduction might well rely on the 158 "concerted operation of several, functionally distinct, brain areas" [43], thus making it a 159 harder process to disrupt with single-location stimulation. Consistent with this 160 understanding, we have previously voiced the view that "core" deductive processes 161 might be implemented in multiple brain areas, including both the mesial BA8 target as 162 well as left rostrolateral prefrontal cortex, in BA10 [28,33]. 163 The lack of a cTBS effect on three versus four variable items is relevant to two 164 ongoing debates.…”

“…??a). Given the randomized task order, a small "M" or "G" 283 block letter at the top left of the screen served as a reminder of which tasks participants 284 were expected to perform at each trial (as we have done in previous work [28]).…”

“…The trial terminated upon button-press or 291 upon the elapsing of the allotted 15 For each participant, the FMIRB Software Library (FSL) [49] was used to transform the 295 individual T1-weighted structural MRI -which had been obtained, with consent, from 296 previous studies they had taken part in -into standard space (MNI template space). [25,28], and a control site in the LTOS (x = -25, 301 y = -85, z = 25) [32]. Two additional targets were used for the active motor 302 thresholding (AMT) procedure.…”