Environmental influences on neural systems of relational complexity

Abstract

Constructivist learning theory contends that we construct knowledge by experience and that environmental context influences learning. To explore this principle, we examined the cognitive process relational complexity (RC), defined as the number of visual dimensions considered during problem solving on a matrix reasoning task and a well-documented measure of mature reasoning capacity. We sought to determine how the visual environment influences RC by examining the influence of color and visual contrast on RC in a neuroimaging task. To specify the contributions of sensory demand and relational integration to reasoning, our participants performed a non-verbal matrix task comprised of color, no-color line, or black-white visual contrast conditions parametrically varied by complexity (relations 0, 1, 2). The use of matrix reasoning is ecologically valid for its psychometric relevance and for its potential to link the processing of psychophysically specific visual properties with various levels of RC during reasoning. The role of these elements is important because matrix tests assess intellectual aptitude based on these seemingly context-less exercises. This experiment is a first step toward examining the psychophysical underpinnings of performance on these types of problems. The importance of this is increased in light of recent evidence that intelligence can be linked to visual discrimination. We submit three main findings. First, color and black-white visual contrast (BWVC) add demand at a basic sensory level, but contributions from color and from BWVC are dissociable in cortex such that color engages a "reasoning heuristic" and BWVC engages a "sensory heuristic." Second, color supports contextual sense-making by boosting salience resulting in faster problem solving. Lastly, when visual complexity reaches 2-relations, color and visual contrast relinquish salience to other dimensions of problem solving.

Keywords: color perception; constructivist learning; event-related fMRI; heuristic processing; prefrontal cortex; reasoning; relational complexity; visual contrast.

Figure 1

Examples of matrix reasoning stimuli at (A) 0-relational, (B) 1-relational, and (C) 2-relational complexity. All matrix problems were experienced in No-Color (A), Color (B), and Black-white visual contrast (C) conditions.

Figure 2

Color relational complexity (CRC) fMRI task sequence. CRC task was a self-paced, event-related design with runs administered in counterbalanced order. Color, No-Color, and Black-white visual contrast matrix items were randomly distributed across three functional runs containing 13 trials of each condition at 0, 1, and 2 levels of complexity.

Figure 3

Bar graph representation of response times associated with No-Color, Color, and Black-white Visual Contrast task itemsfor 0, 1, and 2 levels of relational complexity. *, indicates a statistically significant difference between conditions.

Figure 4

Dissociations in prefrontal and visual-parietal regions for Color 2 > 1 and BWVC 2 > 1 relational complexity contrast results based on an RT-convolved HRF (FDR corrected, p < 0.05). BOLD regions consist of at least 7 voxels (threshold Z > 3.09).

Figure 5

Results from a functional ROI analysis of areas comprising the RLPFC for signal intensity at Color at 0, 1, and 2 levels of relational complexity. (A) Relative signal change in RLPFC across levels of complexity, (B) Percent signal change in Brodmann 6 across levels of complexity, (C) Percent signal change in Brodmann 8 across levels of complexity, (D) Percent signal change in Brodmann 10 across levels of complexity.

Figure 6

Finite input response (FIR) curves modeling the timecourse of the RT-convolved BOLD response for Color 2-relational (red) > 1-relational contrast (blue) in each statistically significant ROI that links processing in RLPFC with the parietal and visual cortices. ROIs are reported with the associated Brodmann Area and specific Talairach coordinates of the signal maxima from Table 3.