Search bioRxiv⌕ Search

bioRxiv · 10.1101/2023.02.14.519204

Neural Systems Underlying the Implementation of Working Memory Removal Operations

Abstract

Recently multi-voxel pattern analysis has verified the removal of information from working memory (WM) via three distinct operations replacement, suppression, or clearing compared to information being maintained (Kim et al., 2020). Univariate analyses and classifier importance maps indicate that some brain regions commonly contribute to these operations. This study aimed to use multivariate approaches to determine whether, within these commonly activated brain regions, each of these operations is being represented in a similar or distinct manner. To do so, we used Leiden community detection to identify brain networks that are characterized by similar multi-voxel patterns of activity with regard to these WM operations. Four networks were identified. The Visual Network shows similar multi-voxel patterns for maintain and replace, which are highly dissimilar from suppress and clear, suggesting this network differentiates whether an item is held in WM or not. The Somatomotor Network shows distinct multi-voxel patterns for clear relative to the other operations, suggesting that this network diff in clearing information from WM. The Default Mode Network has distinct patterns for suppress and clear, also suggesting that clearing information from WM is distinct from suppressing it. The Frontoparietal Control Network displays distinct multi-voxel patterns for each of the four operations, suggesting that this network has high involvement in regulating the flow of information within WM. These results indicate that how information is removed from WM depends on distinct brain networks that each have a particular manner in which their co-activation patterns represent these operations. SIGNIFICANCE STATEMENTThe ability to actively remove, manipulate and maintain information in working memory (WM) is required for encoding of new information and for controlling thoughts. This study revealed that different brain networks show characteristic multi-voxel activity patterns across four distinct WM operations: maintenance of information, replacement of one item by another, suppression of a specific item, and clearing the mind of all thought. One network, the Frontoparietal Control Network, differentiates all four operations, suggesting it may play a critical role in the controlled removal of information from WM.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

DeRosa, J., Kim, H., Lewis-Peacock, J., Banich, M.. 2023-02-15. Neural Systems Underlying the Implementation of Working Memory Removal Operations. https://doi.org/10.1101/2023.02.14.519204

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Rab10 and Arhgef7 interact to promote axon extension by linking vesicle supply and exocytosis

The formation of functional neural circuits begins with the extension of a single axon by immature neurons. Axon elongation requires an expansion of the plasma membrane that depends on the polarization of vesicle trafficking and exocytosis. It is not completely understood how the increased transport of vesicles into the growing axon is linked to their subsequent insertion into the plasma membrane. An analysis of early stages of neuronal differentiation indicates that an asymmetry in neurite length precedes axon specification and the accumulation of PPVs in the nascent axon. We show that increasing the transport of vesicles in unpolarized neurons is sufficient to promote the extension of additional axons. This effect indicates that an increased supply of vesicles stimulates their subsequent insertion into the membrane to allow neurite growth. The link between vesicle transport and exocytosis is mediated by the interaction of Rab10 with Arhgef7. Rab10 stimulates Arhgef7 activity on PPVs as a GEF for Cdc42b to promote axon extension through exocyst-dependent exocytosis, suggesting that their interaction links the increased supply of PPVs to their exocytosis.

neuroscience↗

Subcellular Spatial Profiling Unveils Links Between Neuritic Plaques with Selective Tau Vulnerability in Alzheimer's Disease

Alzheimer's disease (AD) features widespread extracellular amyloid-{beta} plaques but selective intraneuronal tau accumulation in cortical layers II/III and V, while layer IV remains relatively resistant. Here, we combined subcellular spatial transcriptomics with co-registered A{beta} and pTau immunohistochemistry to determine why neurons exposed to comparable plaque-associated pathology differ in somatic pTau accumulation. Plaque-associated neuritic stress occurred similarly across layers, but layer IV neurons showed attenuated pTau accumulation and reduced somatic expression of a shared neurite-soma stress program involving DCTN1, CALM3, NORAD, and PIN1. Trajectory analysis within layers identified tau-vulnerable and resistant neuronal states implicating calcium signaling, retrograde transport, and lysosomal function. Notably, astrocytic APOE-neuronal LRP1 co-expression increased significantly along the pTau-vulnerable trajectory, and APOE {epsilon}4 was associated with stronger coupling of local plaque pathology to pTau-associated molecular programs. These findings reveal neuronal programs and neuron-glia interactions underlying selective tau vulnerability and resistance in AD, highlighting potential tau-targeting therapeutics.

neuroscience↗

Widespread oscillatory suppression in autism persists in the absence of psychotropic medication.

Purpose: Investigate the neural oscillatory activity associated with autism spectrum disorder (ASD) using electroencephalographic (EEG) recordings in children and adolescents. Compare the corresponding oscillatory power between ASD patients taking psychotropic medication with a drug-naive group. Methods: ASD diagnosis was done using DSM-IV and CARS (Childhood Autism Rating Scale). EEG recordings employed 22 scalp electrodes (10/20 system). ASD vs. neurotypical groups were matched for sex and age (5 females; average age: ~10 years old). We analyzed the resting state (eyes open) EEG power spectrum during ~2-minute recordings. The multitaper FFT method was used to estimate spectral power for the delta, theta, alpha, beta and gamma frequency bands. We pooled together data from several electrodes to compute comprehensive power spectra and assess the oscillatory behavior of macro brain regions. Results: We observed widespread (~4Hz - 20Hz) oscillatory suppression comprising the theta, alpha and beta frequency bands. The most widespread and robust ASD-associated power suppression was in the high theta and alpha bands. Delta and gamma bands showed no significant power change for any of the brain regions studied. Results from a subgroup of patients (N = 9) who never used psychotropics confirmed these findings, indicating that they are not an artifact of medication. Conclusion: Suppression in theta, alpha and beta oscillations may offer insights into the neurophysiological underpinnings of autism and could be used as an accessible and comprehensive tool in ASD diagnosis, regardless of the patients being or not on medication.

neuroscience↗