Neural substrates of data-driven scientific discovery: An fMRI study during performance of number series completion task

Abstract

Although much has been known about how humans psychologically perform data-driven scientific discovery, less has been known about its brain mechanism. The number series completion is a typical data-driven scientific discovery task, and has been demonstrated to possess the priming effect, which is attributed to the regularity identification and its subsequent extrapolation. In order to reduce the heterogeneities and make the experimental task proper for a brain imaging study, the number magnitude and arithmetic operation involved in number series completion tasks are further restricted. Behavioral performance in Experiment 1 shows the reliable priming effect for targets as expected. Then, a factorial design (the priming effect: prime vs. target; the period length: simple vs. complex) of event-related functional magnetic resonance imaging (fMRI) is used in Experiment 2 to examine the neural basis of data-driven scientific discovery. The fMRI results reveal a double dissociation of the left DLPFC (dorsolateral prefrontal cortex) and the left APFC (anterior prefrontal cortex) between the simple (period length=1) and the complex (period length=2) number series completion task. The priming effect in the left DLPFC is more significant for the simple task than for the complex task, while the priming effect in the left APFC is more significant for the complex task than for the simple task. The reliable double dissociation may suggest the different roles of the left DLPFC and left APFC in data-driven scientific discovery. The left DLPFC (BA 46) may play a crucial role in rule identification, while the left APFC (BA 10) may be related to mental set maintenance needed during rule identification and extrapolation. dorsolateral prefrontal cortex (DLPFC), functional MRI, data-driven scientific discovery, number series completion Citation:Zhong N, Liang P P, Qin Y L, et al. Neural substrates of data-driven scientific discovery: An fMRI study during performance of number series completion task.

The Structural and Functional Organization of Cognition

“…In humans, brain imaging has revealed that this area of the PFC is activated in many different experimental paradigms, each revealing a specific role in meeting the cognitive challenge associated with a particular task. Thus, BA46-9/46 has been reported to engage in tasks requiring, strategic deception in a two-person bargaining game (Bhatt et al, 2010 ), concentration (Koch et al, 2006 ), sustained monitoring and detection of visuomotor incongruence (Schnell et al, 2007 ), arithmetic processing (Menon et al, 2002 ), sustained attention to motion (Thakral and Slotnick, 2009 ), imaging moving stimuli (Roland and Gulyás, 1995 ; Goebel et al, 1998 ; Schendan and Stern, 2007 ), counteracting susceptibility to proactive interference (Wolf et al, 2010 ), integration demand and expectation of integration (De Pisapia et al, 2007 ), high-level cognitive planning and mental manipulation (Amiez and Petrides, 2007 ), maintenance of WM and concentration requiring mental effort (Zarahn et al, 2005 ), decisional processes governing oculomotor behavior (Pierrot-Deseilligny et al, 2005 ), language switching (Wang et al, 2007 ), maintenance of task performance in Tourette’s syndrome (Marsh et al, 2007 ), selection from WM and of movements in willed task actions (Rowe et al, 2000 ), active maintenance of distractor-resistant memory (Sakai et al, 2002 ) and data-driven scientific discovery (Zhong et al, 2011 ). Activation of the DLPFC or middle frontal gyrus (often interpreted as homologous to BA46-9/46) has been reported when a task required executive control (Kübler et al, 2006 ), low confidence, high risk decisions requiring concentration (Fleck et al, 2006 ), verbal fluency (Abrahams et al, 2003 ), manipulation of information (Marvel and Desmond, 2010 ), the mental rotation of objects (Just et al, 2001 ), automatic retrieval of technical problems and breaking of mental sets (Dandan et al, 2013 ), self-control (Friese et al, 2013 ), higher levels of cognitive control/processing (Volle et al, 2008 ), a domain-independent, extra-mnemonic device to focus attention on items to be remembered (Curtis and D’Esposito, 2003 ), inhibition of the stereotyped responses (Kadota et al, 2010 ), higher-order rule switching (Yoshida et al, 2010 ) and critical cognitive control (Koric et al, 2012 ).…”

“…The word abstract, “existing in thought or as an idea but not having a physical or concrete existence” (Stevenson and Oxford University, 2010 ), best describes the domain of cognition served by BA46-9/46—a domain that is developmentally driven to embody intangible phenomena into what can only ever be a hypothetical entities, be they physical entities, be they physical entities such as gravity or a set of relationships hidden within a mathematical function. Without such a domain of intelligence, we would be unable to create intelligently-contrived hypotheses that are the foundation for all significant scientific exploration (Zhong et al, 2011 ). I therefore propose that the cortical area responsible for exclusively elaborating the hypothetical, can best be referred to as the abstract mind, an area of the cortex responsible for our abstract intelligence that is a powerful determinate of success in exploring the mysteries of our universe and ourselves (Figure 1 ).…”

The Relationship of Four Brain Regions to an Information-Processing Model of Numerical Inductive Reasoning Process: An fMRI Study

“…Several brain imaging studies have investigated the neural correlates of inductive reasoning by using normal subjects [7][8][20][21][22][23][24] and patients [25]. These studies concern the neural correlates of priming effect [24], or the cognitive components of simple number series completion tasks [21], or the strategy effects [20], and or complexity effect [22][23], among which the important role of the (dorsal/lateral) prefrontal cortex (PFC) in inductive reasoning during rule identification was mainly discussed. In the present study, we assume that there is induction-based network responsible for inductive reasoning including a fusiform gyrus region-of-interest (ROI) where a stimulus is visually recognized, a DLPFC ROI where an underlying rule is identified, a caudate ROI where a rule is applied, and a motor ROI where hand movements are programmed.…”

Activity in the fronto-parietal network indicates numerical inductive reasoning beyond calculation: An fMRI study combined with a cognitive model

“…Human beings have the capacity, called numerical inductive reasoning, to identify and extrapolate numeric rule/patterns involved in numeric materials derived from such diverse areas as scientific discovery, economics, and the weather. Numerical inductive reasoning is associated with calculation, and activity in the fronto-parietal regions of the brain revealed in numerical inductive reasoning 1 2 3 4 5 6 was also observed in calculation 7 8 . This leads to the suggestion that numerical inductive reasoning (at least when using simple rules) may correspond to a general calculation process rather than necessarily including relation detection and integration (which is critical and unique to reasoning) 9 10 .…”