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Biology subjects

Henry, T. R.

Publications and source records attributed to Henry, T. R..

2 recordsLinked to original sources

Differential reconfiguration of brain networks in children in response to standard versus rewarded go/no-go task demands

Response inhibition and sustained attention are critical for higher-order cognition and rely upon specific patterns of functional brain network organization. This study investigated how functional brain networks reconfigure to execute these cognitive processes during a go/no-go task with and without the presence of rewards in 26 children between the ages of 8 and 12 years. First, we compared task performance between standard and rewarded versions of a go/no-go task. We found that the presence of rewards reduced commission error rate, a measure considered to indicate improved response inhibition. Tau, thought to index sustained attention, did not change across task conditions. Next, changes in functional brain network organization were assessed between the resting state, the standard go/no-go task, and the rewarded go/no-go task. Relative to the resting state, integration decreased and segregation increased during the standard go/no-go task. A further decrease in integration and increase in segregation was observed when rewards were introduced. These patterns of reconfiguration were present globally and across several key brain networks of interest, as well as in individual regions implicated in the processes of response inhibition, attention, and reward processing. These findings align with patterns of brain network organization found to support the cognitive strategy of sustained attention, rather than response inhibition, during go/no-go task performance and suggest that rewards enhance this organization. Overall, this study used large-scale brain network organization and a within-subjects multi-task design to examine different cognitive strategies and the influence of rewards on response inhibition and sustained attention in late childhood.

neuroscience↗

A Simple Model of Cortical Intraregional Metastability

Transient synchronization of bursting activity in neural networks, which occurs in patterns of metastable phase relationships between neurons, is a notable feature of network dynamics observed in vivo. However, the mechanisms that contribute to this dynamical complexity in neural circuits are not well understood. Local circuits in cortical regions consist of populations of neurons with diverse intrinsic oscillatory features. In this study, we numerically show that the phenomenon of transient synchronization, also referred to as metastability, emerges in an inhibitory neural population when the neurons intrinsic fast-spiking dynamics are appropriately modulated by slower inputs from an excitatory neural population. Using a compact model of a mesoscopic-scale network consisting of excitatory pyramidal and inhibitory fast-spiking neurons, our work demonstrates a relationship between the frequency of neural oscillations and the features of emergent metastability. In addition, a novel metric is formulated to characterize collective transitions in metastable networks. Finally, we discuss a blueprint to model the whole-brain resting-state dynamics using our scalable representation of intraregional network metastability.

neuroscience↗