Complementary topology of maintenance and manipulation brain networks in working memory.

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2018-12-13

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Abstract

Working memory (WM) is assumed to consist of a process that sustains memory representations in an active state (maintenance) and a process that operates on these activated representations (manipulation). We examined evidence for two distinct, concurrent cognitive functions supporting maintenance and manipulation abilities by testing brain activity as participants performed a WM alphabetization task. Maintenance was investigated by varying the number of letters held in WM and manipulation by varying the number of moves required to sort the list alphabetically. We found that both maintenance and manipulation demand had significant effects on behavior that were associated with different cortical regions: maintenance was associated with bilateral prefrontal and left parietal cortex, and manipulation with right parietal activity, a link that is consistent with the role of parietal cortex in symbolic computations. Both structural and functional architecture of these systems suggested that these cognitive functions are supported by two dissociable brain networks. Critically, maintenance and manipulation functional networks became increasingly segregated with increasing demand, an effect that was positively associated with individual WM ability. These results provide evidence that network segregation may act as a protective mechanism to enable successful performance under increasing WM demand.

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10.1038/s41598-018-35887-2

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Davis, SW, CA Crowell, L Beynel, L Deng, D Lakhlani, SA Hilbig, W Lim, D Nguyen, et al. (2018). Complementary topology of maintenance and manipulation brain networks in working memory. Scientific reports, 8(1). p. 17827. 10.1038/s41598-018-35887-2 Retrieved from https://hdl.handle.net/10161/20732.

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Scholars@Duke

Davis

Simon Wilton Davis

Associate Professor in Neurology

My research centers around the use of structural and functional imaging measures to study the shifts in network architecture in the aging brain. I am specifically interested in changes in how changes in structural and functional connectivity associated with aging impact the semantic retrieval of word or fact knowledge. Currently this involves asking why older adults have particular difficulty in certain kinds of semantic retrieval, despite the fact that vocabularies and knowledge stores typically improve with age.

A second line of research involves asking questions about how this semantic system is organized in young adults, understanding which helps form a basis for asking questions about older adults. To what degree are these semantic retrieval processes lateralized? What cognitive factors affect this laterality? How are brain structures like the corpus callosum involved in mediating distributed activation patterns associated with semantic retrieval? 

Peterchev

Angel V Peterchev

Professor in Psychiatry and Behavioral Sciences

I direct the Brain Stimulation Engineering Lab (BSEL) which focuses on the development, modeling, and application of devices and paradigms for transcranial brain stimulation. Transcranial brain stimulation involves non-invasive delivery of fields (e.g., electric and magnetic) to the brain that modulate neural activity. It is widely used as a tool for research and a therapeutic intervention in neurology and psychiatry, including several FDA-cleared indications. BSEL develops devices for transcranial magnetic stimulation (TMS) and other forms of magnetic stimulation such as magnetogenetics that leverage design techniques from power electronics and computational electromagnetics to enable more flexible stimulus control, focal stimulation, and quiet operation. We also deploy these devices in experimental studies to characterize and optimize the brain response to TMS. Another line of work is multi-scale computational models that couple simulations of the electromagnetic fields, single neuron responses, and neural population modulation induced by electric and magnetic brain stimulation. These models are calibrated and validated with experimental neural recordings through various collaborations. Apart from understanding of mechanisms, we develop modeling, algorithmic, and targeting tools for response estimation, dose individualization, and precise localization of transcranial brain stimulation using advanced techniques such as artificial neural networks and machine learning. Moreover, BSEL is involved in the integration of transcranial brain stimulation with robotics, neuronavigation, intracranial electrophysiology recordings, and imaging modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), as well as the evaluation of the safety of device–device interactions, for example between transcranial stimulators and implants. Importantly, we collaborate widely with neuroscientists and clinicians at Duke and other institutions to translate developments from the lab to research and clinical applications. For over 17 years, BSEL has been continuously supported with multiple NIH grants as well as funding by DARPA, NSF, Brain & Behavior Research Foundation, Coulter Foundation, Duke Institute for Brain Sciences, MEDx, Duke University Energy Initiative, and industry. Further, some of our technology has been commercialized, for example as ElevateTMS cTMS, or incorporated in free software packages, such as SimNIBS and SAMT. In recognition of “excellence in non-invasive brain stimulation research that stimulates further work at a higher scientific level” I received the Brainbox Initiative John Rothwell Award in 2024.

Cabeza

Roberto Cabeza

Professor of Psychology and Neuroscience

My laboratory investigates the neural correlates of memory and cognition in young and older adults using fMRI. We have three main lines of research: First, we distinguish the neural correlates of various episodic memory processes. For example, we have compared encoding vs. retrieval, item vs. source memory, recall vs. recognition, true vs. false memory, and emotional vs. nonemotional memory. We are particularly interested in the contribution of prefrontal cortex (PFC) and medial temporal lobe (MTL) subregions and their interactions. Second, we investigate similarities and differences between the neural correlates of episodic memory and other memory and cognitive functions (working, semantic, implicit, and procedural memory; attention; perception, etc.). The main goal of this cross-functional approach is to understand the contributions of brain regions shared by different cognitive functions. Finally, in both episodic memory and cross-function studies, we also examine the effects of healthy and pathological aging. Regarding episodic memory, we have linked processes differentially affected by aging (e.g., item vs. source memory, recall vs. recognition) to the effects of aging on specific PFC and MTL subregions. Regarding cross-function comparisons, we identify age-related changes in activity that are common to various functions. For example, we have found an age-related increase in bilaterality that occurs for many functions (memory, attention, language, perception, and motor) and is associated with functional compensation.


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