Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory

Redundant, weakly connected prefrontal hemispheres balance precision and capacity in spatial working memory

How the prefrontal hemispheres coordinate to adapt to spatial working memory (WM) demands remains an open question. Recently, two models have been proposed: A specialized model, where each hemisphere governs contralateral behavior, and a redundant model, where both hemispheres equally guide behavior in the full visual space. To explore these alternatives, we analyzed simultaneous bilateral prefrontal cortex recordings from three macaque monkeys performing a visuo-spatial WM task. Each hemisphere represented targets across the full visual field and equally predicted behavioral imprecisions. Furthermore, memory errors were weakly correlated between hemispheres, suggesting that redundant, weakly coupled prefrontal hemispheres support spatial WM. Attractor model simulations showed that the hemispheric redundancy improved precision in simple tasks, whereas weak inter-hemispheric coupling allowed for specialized hemispheres in complex tasks. This interhemispheric architecture reconciles previous findings thought to support distinct models into a unified architecture, providing a versatile interhemispheric architecture that adapts to varying cognitive demands.

Alpha phase-coding supports feature binding during working memory maintenance

The ability to successfully retain and manipulate information in working memory (WM) requires that objects' individual features are bound into cohesive representations; yet, the mechanisms supporting feature binding remain unclear. Binding (or swap) errors, where memorized features are erroneously associated with the wrong object, can provide a window into the intrinsic limits in capacity of WM that represent a key bottleneck in our cognitive ability. We tested the hypothesis that binding in WM is accomplished via neural phase synchrony and that swap errors result from perturbations in this synchrony. Using magnetoencephalography data collected from human subjects in a task designed to induce swap errors, we showed that swaps are characterized by reduced phase-locked oscillatory activity during memory retention, as predicted by an attractor model of spiking neural networks. Further, we found that this reduction arises from increased phase-coding variability in the alpha-band over a distributed network of sensorimotor areas. Our findings demonstrate that feature binding in WM is accomplished through phase-coding dynamics that emerge from the competition between different memories.

Causal evidence for the higher-order origin of serial dependence suggests a multi-area account

There has been recent interest in whether serial dependence, a temporal bias in working memory and perception, is generated by higher-order cognitive or sensory areas. Based on the literature suggesting prefrontal areas combined with a recent article by de Azevedo Neto & Bartels (1), providing causal evidence for serial dependence relying on premotor cortex but not the visual area hV5/MT+, I here argue for a higher-order and multi-area origin of serial dependence.