Evolutionary and developmental changes in the lateral frontoparietal network: a little goes a long way for higher-level cognition

Abstract

Relational thinking, or the ability to represent the relations between items, is widespread in the animal kingdom. However, humans are unparalleled in their ability to engage in the higher-order relational thinking required for reasoning and other forms of abstract thought. Here we propose that the versatile reasoning skills observed in humans can be traced back to developmental and evolutionary changes in the lateral frontoparietal network (LFPN). We first identify the regions within the LFPN that are most strongly linked to relational thinking, and show that stronger communication between these regions over the course of development supports improvements in relational reasoning. We then explore differences in the LFPN between humans and other primate species that could explain species differences in the capacity for relational reasoning. We conclude that fairly small neuroanatomical changes in specific regions of the LFPN and their connections have led to big ontogenetic and phylogenetic changes in cognition.

Figure 1. Relational Reasoning Tasks

Examples of tasks used to investigate relational reasoning (top), and schematics illustrating first- and second-order relations used within each task (bottom). (A) In order to solve the example analogy (blizzard: snowflake:: army: soldier) the reasoner must first recall the relationship between blizzard and snowflake (e.g., comprised of), and then compare this relation to one extracted from army and soldier. One’s ultimate decision is a higher-order comparison of two semantic relations abstracted from the perceptual objects. (B) A transitive inference problem in which the participant has to integrate the weight relationships among pairs of balls. In this example, orange balls are lighter than green ones, and green balls are lighter than purple ones, so by combining these two relations one can make the conclusion that purple is heavier than orange. (C) A geometric relational reasoning task in which one may jointly consider relations across rows (i.e., increase number of objects) and columns (i.e., change object shape) to come to the correct solution. Although this task does not require explicit representation of a second-order relation, the two first-order relations must be integrated to complete the missing piece of the array, highlighted in blue.

Figure 2. Meta-Analysis of fMRI Activations Associated with the Term “Relational”

Results from Neurosynth.org (Yarkoni et al., 2011) using the search term “relational.” Items in light blue represent regions that are reported more selectively with the term relational relative to 525 other keywords (reverse inference, Z ≥ 1.96). Items in dark blue represent regions that are consistently activated with the term relational (forward inference). LH, left hemisphere; RH, right hemisphere; RLPFC, rostrolateral prefrontal cortex; DLPFC, dorsolateral prefrontal cortex; IPL, inferior parietal lobule. Additional regions identified by the forward inference search, but not shown here, include hippocampus, in-sula, and posterior cingulate cortex. See Yarkoni et al. (2011) and Neurosynth.org for further information.

Figure 3. Overlapping Activation in RLPFC for Visuospatial and Semantic Relational Reasoning

(A) Time series analysis from Wendelken et al. (2012). Event-related time courses were extracted from selected regions by averaging across trial-specific time series for each condition. For the visuospatial condition, participants had to decide whether two objects had straight or curvy lines, or had to decide whether dots placed on the objects were both on the left or right side. For the semantic condition, participants had to answer whether the picture was an animal or vehicle, or whether the picture was of something that resides in water or on land. Comparison trials meant deciding whether a higher-order relationship existed between both pairs. Despite the visual display being exactly the same for first- and second-order relational decisions, and the fact that participants needed to make decisions on both pairs for all trials, BOLD signal in the RLPFC increased only for those conditions where multiple relations must be compared in order to successfully make a judgment. (B) Examples of stimuli used for nonverbal shapes (left) or semantic objects (right). See main text for description of the judgments made. Figure adapted with permission from Wendelken et al. (2012).

Figure 4. Functional Dissociation between RLPFC and More Posterior Lateral PFC

(A) Both DLPFC and VLPFC follow increased working memory load. Rather than tracking task difficulty, RLPFC activates more preferentially for trials in which relational information is present (i.e., the arrows). Figure adapted with permission from Wendelken et al. (2008a). (B) Participants were presented with four conditions in which they were given a relational term or had to extract a relation from a pair of related words, and in which they had to compare or complete the analogical expression. Relational structures are shown for the two conditions that are hypothesized to necessitate them. White boxes represent objects (e.g., painter), whereas boxes with an R inside represent relational terms (e.g., uses). RLPFC activation is greater when participants are asked to make comparisons (i.e., problem types 1 and 3), rather than complete an analogy (i.e., problem types 2 and 4), even though task difficulty is greater for trials in which participants have to extract a relation. Data from Wendelken et al. (2008b).

Figure 5. Development of Reasoning Ability

(A) Developmental pattern of reasoning ability in 165 typically developing children and adolescents. Red, green, and blue dots indicate performance on the participant’s first, second, or third behavioral testing session, respectively. Red lines show changes in performance from the first to the second visit, and green lines show changes from the second to the third visit. The average delay between assessments was approximately 1.5 years. (B) Increases in white matter integrity of a left frontoparietal tract connecting L RLPFC and L IPL increases nonlinearly across age. The dashed bar represents the mean, and each gray bar represents 0.5 SDs. (C) Partial correlations plot demonstrating that participants’ changes in reasoning ability across sessions 1.5 years apart are positively correlated with a change in fractional anisotropy in this left frontoparietal tract. Figures reprinted with permission from Whitaker (2012).

Figure 6. Age-Related Changes in the Brain that Support Reasoning Development

(A) Task illustration from Wendelken et al. (2011). Each trial consisted of a yes/no judgment based on a stimulus array that contained four patterned shapes. On Shape and Pattern trials participants determined whether there was a shape or pattern match in either pair, respectively. On Match trials, participants decided whether the bottom pair of stimuli matched along the same dimension (i.e., Shape or Pattern) as the top pair of stimuli. Shape or Pattern trials require first-order relational processing, whereas Match trials require second-order relational integration. (B) Whole-brain activation for the second-order > first-order contrast for 7- to 10-year-olds (red), 11-to 14-year-olds (green), and 15- to 18-year-olds (blue). Note: the lack of RLPFC and IPL for the younger-aged groups is due to the fact that these regions were equivalently engaged for first- and second-order relational trials. (C) Across childhood and adolescence, left RLPFC became less engaged for first-order relational trials. (D) Cortical thickness diminishes across age in the IPL. Functional specificity displayed in L RLPFC across age was negatively related to cortical thickness in IPL, such that the thinner the IPL cortex was, the more functional specificity observed in L RLPFC (data not shown). Figures adapted with permission from Wendelken et al. (2011).

Figure 7. Cortical Expansion Differences between Primate Species

(A) Areas showing greatest (in yellow) amount of cortical expansion from macaques to humans and chimpanzees to humans. Again, the area of greatest cortical expansion between species is anterior prefrontal cortex (BA 10). Numbers in the horizontal bars represent the amount of expansion in humans compared to macaques (left) and chimpanzees (right). Figure adapted with permission from Buckner and Krienen (2013). (B) Cortical regions showing a shared amount of cortical expansion across evolution (relative to macaques) and across human development. Note the lateral prefrontal and posterior parietal regions are found to be associated with higher cognition in humans. Figure adapted with permission from Fjell et al. (2013).

Figure 8. Cytoarchitectonic Differences in Anterior PFC between Primate Species

Increased horizontal spacing distance (HSD) between humans and chimpanzee in the anterior PFC (BA 10). Greater HSD is a proxy for increased cortical expansion, and the relatively smaller number of pyramidal cells in these regions for humans likely reflects the extensive density of dendrites and dendritic spines, useful for integrating information. Slices taken from anterior prefrontal cortex (i.e., BA 10 in humans). Figures adapted with permission from Semendeferi et al. (2011). Note: locations for figure insets are approximate.

Figure 9. Functional Connectivity Differences between Primate Species

(A) Interspecies comparison of node degree, or the number of functional connections a particular region has to all other regions. Blue colors represent regions where macaques have a higher node degree, and red colors represent regions where humans have higher node degree than macaques. Notice that humans have more highly connected hubs distributed within a lateral frontoparietal network. Figure adapted with permission from Miranda-Dominguez et al. (2014). (B) Intrinsic functional connectivity maps for DLPFC and RLPFC seeds in humans and macaques. Using DTI, the authors found ten different parcellations of parietal cortex, and used these regions as “seed” regions for resting state fMRI (rsfMRI). Seed regions are regions used in a regression analysis to identify other cortical and subcortical regions sharing a similar time course during a task-free fMRI scan. Although there was much similarity for frontoparietal functional connectivity when using the DLPFC as a seed region, there was no macaque analog for the frontoparietal connections observed between RLPFC and posterior parietal cortex, even when using a much less conservative statistical threshold. Figure adapted with permission from Mars et al. (2011).