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Investigations of neural attractor dynamics in human visual awareness
KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
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 [en]
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: urn:nbn:se:kth:diva-223744ISBN: 978-91-7729-706-2 (electronic)OAI: oai:DiVA.org:kth-223744DiVA, id: diva2:1187505
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
List of papers
1. Is attentional blink a byproduct of neocortical attractors?
Open this publication in new window or tab >>Is attentional blink a byproduct of neocortical attractors?
2011 (English)In: Frontiers in Computational Neuroscience, ISSN 1662-5188, E-ISSN 1662-5188, Vol. 5, article id 13Article in journal (Refereed) Published
Abstract [en]

This study proposes a computational model for attentional blink or "blink of the mind," a phenomenon where a human subject misses perception of a later expected visual pattern as two expected visual patterns are presented less than 500 ms apart. A neocortical patch modeled as an attractor network is stimulated with a sequence of 14 patterns 100 ms apart, two of which are expected targets. Patterns that become active attractors are considered recognized. A neocortical patch is represented as a square matrix of hypercolumns, each containing a set of minicolumns with synaptic connections within and across both minicolumns and hypercolumns. Each minicolumn consists of locally connected layer 2/3 pyramidal cells with interacting basket cells and layer 4 pyramidal cells for input stimulation. All neurons are implemented using the Hodgkin-Huxley multi-compartmental cell formalism and include calcium dynamics, and they interact via saturating and depressing AMPA/NMDA and GABA(A) synapses. Stored patterns are encoded with global connectivity of minicolumns across hypercolumns and active patterns compete as the result of lateral inhibition in the network. Stored patterns were stimulated over time intervals to create attractor interference measurable with synthetic spike traces. This setup corresponds with item presentations in human visual attentional blink studies. Stored target patterns were depolarized while distractor patterns where hyperpolarized to represent expectation of items in working memory. Simulations replicated the basic attentional blink phenomena and showed a reduced blink when targets were more salient. Studies on the inhibitory effect of benzodiazepines on attentional blink in human subjects were compared with neocortical simulations where the GABA(A) receptor conductance and decay time were increased. Simulations showed increases in the attentional blink duration, agreeing with observations in human studies. In addition, sensitivity analysis was performed on key parameters of the model, including Ca2+-gated K+ channel conductance, synaptic depression, GABA(A) channel conductance and the NMDA/AMPA ratio of charge entry.

Keywords
attentional blink, attention, neocortex, cortical dynamics, Hodgkin-Huxley model, attractor networks
National Category
Natural Sciences
Identifiers
urn:nbn:se:kth:diva-33975 (URN)10.3389/fncom.2011.00013 (DOI)000290168400001 ()2-s2.0-84959490431 (Scopus ID)
Funder
Swedish e‐Science Research CenterSwedish Foundation for Strategic Research Swedish Research Council, VR-621-2004-3807
Note

QC 20110530

Available from: 2011-05-30 Created: 2011-05-23 Last updated: 2018-03-05Bibliographically approved
2. Pathological Neural Attractor Dynamics in Slowly Growing Gliomas Supports an Optimal Time Frame for White Matter Plasticity
Open this publication in new window or tab >>Pathological Neural Attractor Dynamics in Slowly Growing Gliomas Supports an Optimal Time Frame for White Matter Plasticity
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.

Keywords
Low-Grade Gliomas, Brain-Tumors, Cortical Deafferentation, Conduction-Velocity, II Gliomas, Model, Invasion, Cortex, Classification, Sequelae
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:kth:diva-127766 (URN)10.1371/journal.pone.0069798 (DOI)000322838900084 ()2-s2.0-84880797598 (Scopus ID)
Funder
Swedish e‐Science Research Center
Note

QC 20130906

Available from: 2013-09-06 Created: 2013-09-05 Last updated: 2018-03-05Bibliographically approved
3. A computational investigation of feedforward and feedback processing in metacontrast backward masking
Open this publication in new window or tab >>A computational investigation of feedforward and feedback processing in metacontrast backward masking
2015 (English)In: Frontiers in Psychology, ISSN 1664-1078, E-ISSN 1664-1078, Vol. 6, article id 6Article in journal (Refereed) Published
Abstract [en]

In human perception studies, visual backward masking has been used to understand the temporal dynamics of subliminal vs. conscious perception. When a brief target stimulus is followed by a masking stimulus after a short interval of <100 ms, performance on the target is impaired when the target and mask are in close spatial proximity. While the psychophysical properties of backward masking have been studied extensively, there is still debate on the underlying cortical dynamics. One prevailing theory suggests that the impairment of target performance due to the mask is the result of lateral inhibition between the target and mask in feedforward processing. Another prevailing theory suggests that this impairment is due to the interruption of feedback processing of the target by the mask. This computational study demonstrates that both aspects of these theories may be correct. Using a biophysical model of V1 and V2, visual processing was modeled as interacting neocortical attractors, which must propagate up the visual stream. If an activating target attractor in V1 is quiesced enough with lateral inhibition from a mask, or not reinforced by recurrent feedback, it is more likely to burn out before becoming fully active and progressing through V2 and beyond. Results are presented which simulate metacontrast backward masking with an increasing stimulus interval and with the presence and absence of feedback activity. This showed that recurrent feedback diminishes backward masking effects and can make conscious perception more likely. One model configuration presented a metacontrast noise mask in the same hypercolumns as the target, and produced type-A masking. A second model configuration presented a target line with two parallel adjacent masking lines, and produced type-B masking. Future work should examine how the model extends to more complex spatial mask configurations.

Place, publisher, year, edition, pages
Frontiers Research Foundation, 2015
National Category
Psychology
Identifiers
urn:nbn:se:kth:diva-161954 (URN)10.3389/FPSYG.2015.00006 (DOI)000349837400001 ()2-s2.0-84926456233 (Scopus ID)
Funder
Swedish Foundation for Strategic Research Swedish Research Council, VR-621-2004-3807Swedish e‐Science Research Center
Note

QC 20150408. QC 20160226

Available from: 2015-04-08 Created: 2015-03-20 Last updated: 2018-03-05Bibliographically approved
4. A multi-pathway hypothesis for human visual fear signaling
Open this publication in new window or tab >>A multi-pathway hypothesis for human visual fear signaling
2015 (English)In: Frontiers in Systems Neuroscience, ISSN 1662-5137, E-ISSN 1662-5137, Vol. 9, article id 101Article in journal (Refereed) Published
Abstract [en]

A hypothesis is proposed for five visual fear signaling pathways in humans, based on an analysis of anatomical connectivity from primate studies and human functional connectvity and tractography from brain imaging studies. Earlier work has identified possible subcortical and cortical fear pathways known as the “low road” and “high road,” which arrive at the amygdala independently. In addition to a subcortical pathway, we propose four cortical signaling pathways in humans along the visual ventral stream. All four of these traverse through the LGN to the visual cortex (VC) and branching off at the inferior temporal area, with one projection directly to the amygdala; another traversing the orbitofrontal cortex; and two others passing through the parietal and then prefrontal cortex, one excitatory pathway via the ventral-medial area and one regulatory pathway via the ventral-lateral area. These pathways have progressively longer propagation latencies and may have progressively evolved with brain development to take advantage of higher-level processing. Using the anatomical path lengths and latency estimates for each of these five pathways, predictions are made for the relative processing times at selective ROIs and arrival at the amygdala, based on the presentation of a fear-relevant visual stimulus. Partial verification of the temporal dynamics of this hypothesis might be accomplished using experimental MEG analysis. Possible experimental protocols are suggested.

National Category
Behavioral Sciences Biology Biological Systematics
Identifiers
urn:nbn:se:kth:diva-172458 (URN)10.3389/fnsys.2015.00101 (DOI)000363850400001 ()2-s2.0-84941085608 (Scopus ID)
Funder
Swedish Foundation for Strategic Research Swedish e‐Science Research Center
Note

QC 20150825

Available from: 2015-08-24 Created: 2015-08-24 Last updated: 2018-03-05Bibliographically approved

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