Mark D'Esposito

Working memory (WM) is the ability to retain and manipulate information in mind, which allows mnemonic representations to flexibly guide behavior. Successful WM requires that objects’ individual features are bound into cohesive representations, however the mechanisms supporting feature binding remain unclear. Binding errors (or swaps) provide a window into the intrinsic limits in capacity of WM. We tested the hypothesis that binding in WM is accomplished via neural phase synchrony and swaps result from its perturbations. Using magnetoencephalography data collected from human subjects, in a task designed to induce swaps, we showed that swaps are characterized by reduced phase-locked oscillatory activity during memory retention. We found that this reduction arises from increased phase-coding variability in the alpha-band, over a distributed network of sensorimotor areas. Our findings support the notion that feature binding in WM is accomplished through phase-coding dynamics that emerge from the competition between different memories.

It is increasingly recognized that cognitive control requires integration across large-scale brain networks anchored in frontal and parietal cortices. While the functional role of individual networks has been studied extensively, their cross-network interactions in the service of cognitive control are poorly understood. Beyond in-the-moment regulation of goal-relevant information processing (e.g., of sensory information), cognitive control encompasses preparatory processes in anticipation of upcoming stimuli and actions. Such preparatory control is often endogenous, that is, it is based on internal representations without relying on external cues or events. Here, we assessed network interactions that support such endogenously driven preparatory control. We recorded fMRI (N = 25) during a perceptual decision task with highly variable intertrial intervals. In half of the blocks, trial onset was cued, while in the remaining …

Erratum Page 1 Erratum In Louis, CC, Jacobs, E., D’Esposito, M., & Moser, J. (2023). Estradiol and the catechol-o-methyltransferase gene interact to predict working memory performance: A replication and extension. Journal of Cognitive Neuroscience, 35, 1144–1153. CORRECTIONS TO “METHODS” SECTION (PAGES 1146–1147) The following, as reported in Louis et al. (2023), is erroneous: “The 0-back load condition consisted of 160 trials (targets: 128; nontargets: 32), and 2- and 3-back conditions consisted of 80 trials each (targets: 52; nontargets: 16; lures: 12).” The correct information is: “The 0-back load condition consisted of 160 trials (targets: 32; nontargets: 128), and 2- and 3-back conditions consisted of 80 trials each (targets: 16; nontargets: 52; lures: 12).” [Add related-article link to https://doi.org/10.1162/jocn _a_02001] © 2024 Massachusetts Institute of Technology Journal of Cognitive Neuroscience X:Y, …

Stimulus–response habits benefit behavior by automatizing the selection of rewarding actions. However, this automaticity can come at the cost of reduced flexibility to adapt behavior when circumstances change. The goal-directed system is thought to counteract the habit system by providing the flexibility to pursue context-appropriate behaviors. The dichotomy between habitual action selection and flexible goal-directed behavior has recently been challenged by findings showing that rewards bias both action and goal selection. Here, we test whether reward reinforcement can give rise to habitual goal selection much as it gives rise to habitual action selection. We designed a rewarded, context-based perceptual discrimination task in which performance on one rule was reinforced. Using drift-diffusion models and psychometric analyses, we found that reward facilitates the initiation and execution of rules …

The goal of precision brain health is to accurately predict individuals’ longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21–65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart. Hemodynamic response functions (HRFs) were parameterized using traditional (amplitude, dispersion, latency) and novel (curvature, canonicality) metrics, serving as inputs to a neural network model that predicted gain on indices of brain health (cognitive factor scores) for each participant. The optimal neural network model successfully predicted substantial gain on the cognitive index of brain health with 90% accuracy (determined by 5-fold cross-validation) from 3 HRF parameters: amplitude change, dispersion change, and similarity to a …

Human brain imaging research using functional MRI (fMRI) has uncovered flexible variations in the functional connectivity between brain regions. While some of this variability likely arises from the pattern of information flow through circuits, it may also be influenced by rapid changes in effective synaptic strength at the molecular level, a phenomenon called Dynamic Network Connectivity (DNC) discovered in non-human primate circuits. These neuromodulatory molecular mechanisms are found in layer III of the macaque dorsolateral prefrontal cortex (dlPFC), the site of the microcircuits shown by Goldman-Rakic to be critical for working memory. This research has shown that the neuromodulators acetylcholine, norepinephrine, and dopamine can rapidly change the strength of synaptic connections in layer III dlPFC by (1) modifying the depolarization state of the post-synaptic density needed for NMDA receptor neurotransmission and (2) altering the open state of nearby potassium channels to rapidly weaken or strengthen synaptic efficacy and the strength of persistent neuronal firing. Many of these actions involve increased cAMP-calcium signaling in dendritic spines, where varying levels can coordinate the arousal state with the cognitive state. The current review examines the hypothesis that some of the dynamic changes in correlative strength between cortical regions observed in human fMRI studies may arise from these molecular underpinnings, as has been seen when pharmacological agents or genetic alterations alter the functional connectivity of the dlPFC consistent with the macaque physiology. These DNC mechanisms provide essential …

There is increasing evidence that the left lateral frontal cortex is hierarchically organized such that higher-order regions have an asymmetric top–down influence over lower order regions. However, questions remain about the underlying neuroarchitecture of this hierarchical control organization. Within the frontal cortex, dopamine plays an important role in cognitive control functions, and we hypothesized that dopamine may preferentially influence top–down connections within the lateral frontal hierarchy. Using a randomized, double-blind, within-subject design, we analyzed resting-state fMRI data of 66 healthy young participants who were scanned once each after administration of bromocriptine (a dopamine agonist with preferential affinity for D2 receptor), tolcapone (an inhibitor of catechol-O-methyltransferase), and placebo, to determine whether dopaminergic stimulation modulated effective functional connectivity …

Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the “timescale” over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter‐regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are …