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Flexible Prefrontal Bias Signals Regulate Capacity and Access to Working Memory
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
2008 (English)Manuscript (preprint) (Other academic)
Place, publisher, year, edition, pages
National Category
Biological Sciences
URN: urn:nbn:se:kth:diva-7812OAI: diva2:12945

QC 20100705

Available from: 2007-12-12 Created: 2007-12-12 Last updated: 2016-02-02Bibliographically approved
In thesis
1. Neural Mechanisms Determining Visuospatial Working Memory Tasks: Biophysical Modeling, Functional MRI and EEG
Open this publication in new window or tab >>Neural Mechanisms Determining Visuospatial Working Memory Tasks: Biophysical Modeling, Functional MRI and EEG
2007 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Visuospatial working memory (vsWM) is the ability to temporarily retain goal-relevant visuospatial information in memory. It is a key cognitive function related to general intelligence, and it improves throughout childhood and through WM training. Information is maintained in vsWM through persistent neuronal activity in a fronto-parietal network that consists of the intraparietal sulcus (IPS) and the frontal eye field (FEF). This network is regulated by the dorsolateral prefrontal cortex (dlPFC).

The features of brain structure and activity that regulate the access to and storage capacity of visuospatial WM (vsWM) are still unknown. The aim of my doctoral work has been to find such features by combining a biophysically based model of vsWM activity with functional MRI (fMRI) and EEG experiments.

In study I, we combined modeling and fMRI and showed that stronger fronto-parietal synaptic connections result in developmental increases in brain activity and in improved vsWM during development. This causal relationship was established by ruling out other previously suggested mechanisms, such as myelination or synaptic pruning,

In study II, we combined modeling and EEG to further explore the connectivity of the network. We showed that FEF→IPS connections are stronger than IPS→FEF connections, and that stimuli enter IPS. This arrangement of connections prevents distracting stimuli from being stored.

Study III was a theoretical study showing that errors in measurements of the amplitude of brain activity affect the estimation of effective connection strength.

In study IV, we analyzed EEG data from WM training in children with epilepsy. Improvements on the trained task were accompanied by increased frontal and parietal signal power, but not fronto-parietal coherence. This indicates that local changes in FEF and IPS could underlie improvements on the trained task.

dlPFC is important for the performance on a large variety of cognitive tasks.

In study V, we combined modeling with fMRI to test the hypothesis that dlPFC improves vsWM capacity by providing stabilizing excitatory inputs to IPS, and that dlPFC filters distracters by specifically lowering the capacity of neurons storing distracters. fMRI data confirmed the model hypothesis. We further showed that a dysfunctional dlPFC could explain the link between vsWM capacity and distractibility, as is found in ADHD. The model suggests that dlPFC carries out its multifaceted behavior not by performing advanced calculations itself, but by providing bias signals that control operations performed in the regions it connects to.

A specific aim of this thesis has been to describe the mechanistic model in a way that is accessible to people without a modeling background.

Place, publisher, year, edition, pages
Stockhollm: KTH, 2007. vi, 57 p.
Trita-CSC-A, ISSN 1653-5723 ; 2007:23
National Category
Computer Science
urn:nbn:se:kth:diva-4577 (URN)978-91-7178-832-0 (ISBN)
Public defence
2008-01-11, Sal D2, KTH, Lindstedtsvägen 5, Stockholm, 13:00
QC 20100705Available from: 2007-12-12 Created: 2007-12-12 Last updated: 2010-07-05Bibliographically approved

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