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Pathological Neural Attractor Dynamics in Slowly Growing Gliomas Supports an Optimal Time Frame for White Matter Plasticity
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC.
2013 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 7, p. e69798-Article in journal (Refereed) Published
Abstract [en]

Neurological function in patients with slowly growing brain tumors can be preserved even after extensive tumor resection. However, the global process of cortical reshaping and cerebral redistribution cannot be understood without taking into account the white matter tracts. The aim of this study was to predict the functional consequences of tumor-induced white matter damage by computer simulation. A computational model was proposed, incorporating two cortical patches and the white matter connections of the uncinate fasciculus. Tumor-induced structural changes were modeled such that different aspects of the connectivity were altered, mimicking the biological heterogeneity of gliomas. The network performance was quantified by comparing memory pattern recall and the plastic compensatory capacity of the network was analyzed. The model predicts an optimal level of synaptic conductance boost that compensates for tumor-induced connectivity loss. Tumor density appears to change the optimal plasticity regime, but tumor size does not. Compensatory conductance values that are too high lead to performance loss in the network and eventually to epileptic activity. Tumors of different configurations show differences in memory recall performance with slightly lower plasticity values for dense tumors compared to more diffuse tumors. Simulation results also suggest an optimal noise level that is capable of increasing the recall performance in tumor-induced white matter damage. In conclusion, the model presented here is able to capture the influence of different tumor-related parameters on memory pattern recall decline and provides a new way to study the functional consequences of white matter invasion by slowly growing brain tumors.

Place, publisher, year, edition, pages
2013. Vol. 8, no 7, p. e69798-
Keywords [en]
Low-Grade Gliomas, Brain-Tumors, Cortical Deafferentation, Conduction-Velocity, II Gliomas, Model, Invasion, Cortex, Classification, Sequelae
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:kth:diva-127766DOI: 10.1371/journal.pone.0069798ISI: 000322838900084Scopus ID: 2-s2.0-84880797598OAI: oai:DiVA.org:kth-127766DiVA, id: diva2:646015
Funder
Swedish e‐Science Research Center
Note

QC 20130906

Available from: 2013-09-06 Created: 2013-09-05 Last updated: 2018-03-05Bibliographically approved
In thesis
1. Investigations of neural attractor dynamics in human visual awareness
Open this publication in new window or tab >>Investigations of neural attractor dynamics in human visual awareness
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

What we see, how we see it and what emotions may arise from stimuli has long been studied by philosophers, psychologists, medical doctors and neuroscientists. This thesis work investigates a particular view on the possible dynamics, utilizing computational models of spiking neural attractor networks. From neurological studies on humans and other primates, we know visual perception and recognition of objects occur partly along the visual ventral stream, from V1 to V2, V4, IT and downstream to other areas. This visual awareness can be both conscious and unconscious and may also trigger an emotional response. As seen from many psychophysical experiments in backward masking (BM) and attentional blink (AB), some spatial and temporal dynamics can determine what becomes visually conscious and what does not. To explore this computationally, biophysical models of BM and AB were implemented and simulated to mimic human experiments, with the assumption that neural assemblies as attractor networks activate and propagate along the ventral stream and beyond. It was observed that attractor interference between percepts in sensory and associative cortex can occur during this activity. During typical human AB experimental trials in which two expected target symbols amongst distractors are presented less than 500 ms apart, the second target is often not reported as seen. When simulating this paradigm as two expected target neural attractors amongst distractors, it was observed in the present work that an initial attractor in associative cortex can impede the activation and propagation of a following attractor, which mimics missing conscious perception of the second target. It was also observed that simulating the presence of benzodiazepines (GABA agonists) will slow cortical dynamics and increase the AB, as previously shown in human experiments.

During typical human BM experimental trials in which a brief target stimulus is followed by a masking stimulus after a short interval of less than 100 ms, recognition of the target can be impaired when in close spatial proximity. When simulating this paradigm using a biophysical model of V1 and V2 with feedforward and feedback connections, attractor targets were activated in V1 before imposition of a proximal metacontrast mask. If an activating target attractor in V1 is quiesced enough with lateral inhibition from a mask, or not reinforced by recurrent feedback from feedforward activation in V2, it is more likely to burn out before becoming fully active and progressing through V2 and beyond. BM was also simulated with an increasing stimulus interval and with the presence and absence of feedback activity. This showed that recurrent feedback diminishes BM effects and can make conscious perception more likely.

To better understand possible emotional components of visual perception and early regulation, visual signaling pathways to the amygdala were investigated and proposed for emotional salience and the possible onset of fear. While one subcortical and likely unconscious pathway (before amydala efferent signaling) was affirmed via the superior colliculus and pulvinar, four others traversed through the ventral stream. One traversed though IT on recognition, another via the OFC on conditioning, and two other possibly conscious pathways traversed though the parietal and then prefrontal cortex, one excitatory pathway via the ventral-medial area and one regulatory pathway via the ventral-lateral area. Predicted latencies were determined for these signaling pathways, which can be experimentally testable. The conscious feeling of fear itself may not occur until after interoceptive inspection.

A pathology of attractor dynamics was also investigated, which can occur from the presence of a brain tumor in white matter. Due to degradation from tumor invasion of white matter projections between two simulated neocortical patches, information transfer between separate neural attractors degraded, leading first to recall errors and later to epileptic-like activity. Neural plasticity could partially compensate up to a point, before transmission failure. This suggests that once epileptic seizures start in glioma patients, compensatory plasticity may already be exhausted. Interestingly, the presence of additional noise could also partially compensate for white matter loss.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2018
Series
TRITA-EECS-AVL ; 2018:18
Keywords
attractor dynamics, visual awareness, visual perception, visual attention, attentional blink, backward masking, gliomas, brain tumor, white matter, cell assemblies, neocortical model, threat response, fear signaling, amygdala
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Neurosciences
Research subject
Biological Physics; Computer Science; Applied and Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-223744 (URN)978-91-7729-706-2 (ISBN)
Public defence
2018-03-26, air/fire at SciLifeLab, Tomtebodavägen 23a, Solna, 13:30 (English)
Opponent
Supervisors
Funder
Swedish Foundation for Strategic Research , A3 05:190Swedish e‐Science Research Center
Note

QC 20180305

Available from: 2018-03-05 Created: 2018-03-05 Last updated: 2018-03-28Bibliographically approved

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