Inter-hemispheric recruitment as a function of task complexity, age and cognitive reserve

ABSTRACT

In a behavioral divided visual field study, we investigated the efficiency of inter-hemispheric cooperation according to (1) task computational complexity (physical-identity versus name-identity letter matching), (2) age (younger versus older adults) and (3) educational attainment, used as a proxy for cognitive reserve. Overall, the results indicated a shift from within- to across-hemisphere processing advantage with increasing task complexity, suggesting that bilateral engagement leads to enhanced performance under high-demand conditions. This pattern was influenced by age, with older adults showing no within-hemisphere advantage in the simpler task and a greater across-hemisphere advantage in the more complex one, consistent with an age-compensatory view of inter-hemispheric recruitment. Moreover, for older adults, more years of education was associated with a weaker across-hemisphere advantage. Thus, we propose that cognitive reserve may account for bilateral engagement efficiency. Finally, the groups differed in terms of laterality effects, with only younger adults demonstrating a left visual field advantage in the name-identity task, lending some support to the right hemi-aging hypothesis.

Keywords:

• Inter-hemispheric interaction
• De-differentiation
• Compensation
• Aging
• Cognitive reserve

We thank Maria Vittoria Meraviglia for helping in older subjects recruitment and Carlo Toneatto for programming the experiment.

Notes

¹ A clarification of the terminology used throughout the article is in order. We use the term “complexity” as a task-related factor, referring to the number of computational steps required to reach a decision (described in full later). A greater computational complexity is assumed to be associated with increased demand on cognitive resources. Thus, we use the expression “task demand” to refer to the cognitive and brain labor involved in information processing. Finally, we use the term “difficulty” to mean the effort made by the subjects in performing a task.

² Note that the PIT/NIT difference was subjected to carry-over effects due to the task order (1, which began with PIT; 2, which began with NIT). A 2 (PIT/NIT) × 2 (across-/within-hemifield conditions) × 2 (younger/older adults) × 2 (task order 1/task order 2) mixed ANOVA revealed a significant interaction between task and task order, F(1, 37) = 29.82, p < .001. Post hoc comparisons (Duncan’s Test) indicated an advantage in order 2 (611 ms) compared to order 1 (850 ms) in the PIT trials (p < .001). Moreover, while there was a significant advantage in the PIT trials (611 ms) compared to the NIT trials (887 ms) in order 2 (p < .001), the same advantage presented just a tendency to significance in order 1 (850 ms vs. 943 ms, respectively; p = .07). This means that performing the PIT before the NIT (order 1) reduced the task effect (and thus the effect of the manipulation of complexity).

³ Notice that this variable ranges more broadly than in prior studies, at least for our older participants.