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A computational model of visually guided locomotion in lamprey
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
Karolinska Institutet. (Department of Neuroscience)
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2013 (English)In: Biological Cybernetics, ISSN 0340-1200, E-ISSN 1432-0770, Vol. 107, no 5, 497-512 p.Article in journal (Refereed) Published
Abstract [en]

This study addresses mechanisms for the generation and selection of visual behaviors in anamniotes. To demonstrate the function of these mechanisms, we have constructed an experimental platform where a simulated animal swims around in a virtual environment containing visually detectable objects. The simulated animal moves as a result of simulated mechanical forces between the water and its body. The undulations of the body are generated by contraction of simulated muscles attached to realistic body components. Muscles are driven by simulated motoneurons within networks of central pattern generators. Reticulospinal neurons, which drive the spinal pattern generators, are in turn driven directly and indirectly by visuomotor centers in the brainstem. The neural networks representing visuomotor centers receive sensory input from a simplified retina. The model also includes major components of the basal ganglia, as these are hypothesized to be key components in behavior selection. We have hypothesized that sensorimotor transformation in tectum and pretectum transforms the place-coded retinal information into rate-coded turning commands in the reticulospinal neurons via a recruitment network mimicking the layered structure of tectal areas. Via engagement of the basal ganglia, the system proves to be capable of selecting among several possible responses, even if exposed to conflicting stimuli. The anatomically based structure of the control system makes it possible to disconnect different neural components, yielding concrete predictions of how animals with corresponding lesions would behave. The model confirms that the neural networks identified in the lamprey are capable of responding appropriately to simple, multiple, and conflicting stimuli.

Place, publisher, year, edition, pages
2013. Vol. 107, no 5, 497-512 p.
Keyword [en]
Tectum, Pretectum, Basal ganglia, Mesencephalic locomotor region, Reticulospinal, Central pattern generator, Lamprey
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-104455DOI: 10.1007/s00422-012-0524-4ISI: 000325101800002Scopus ID: 2-s2.0-84885469474OAI: oai:DiVA.org:kth-104455DiVA: diva2:564734
Funder
EU, FP7, Seventh Framework Programme, ICT-2007.8.3Swedish Research Council
Note

QC 20131106

Available from: 2012-11-02 Created: 2012-11-02 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Subsystems of the basal ganglia and motor infrastructure
Open this publication in new window or tab >>Subsystems of the basal ganglia and motor infrastructure
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The motor nervous system is one of the main systems of the body and is our principle means ofbehavior. Some of the most debilitating and wide spread disorders are motor systempathologies. In particular the basal ganglia are complex networks of the brain that control someaspects of movement in all vertebrates. Although these networks have been extensively studied,lack of proper methods to study them on a system level has hindered the process ofunderstanding what they do and how they do it. In order to facilitate this process I have usedcomputational models as an approach that can faithfully take into account many aspects of ahigh dimensional multi faceted system.In order to minimize the complexity of the system, I first took agnathan fish and amphibians asmodeling animals. These animals have rather simple neuronal networks and have been wellstudied so that developing their biologically plausible models is more feasible. I developedmodels of sensory motor transformation centers that are capable of generating basic behaviorsof approach, avoidance and escape. The networks in these models used a similar layeredstructure having a sensory map in one layer and a motor map on other layers. The visualinformation was received as place coded information, but was converted into population codedand ultimately into rate coded signals usable for muscle contractions.In parallel to developing models of visuomotor centers, I developed a novel model of the basalganglia. The model suggests that a subsystem of the basal ganglia is in charge of resolvingconflicts between motor programs suggested by different motor centers in the nervous system.This subsystem that is composed of the subthalamic nucleus and pallidum is called thearbitration system. Another subsystem of the basal ganglia called the extension system which iscomposed of the striatum and pallidum can bias decisions made by an animal towards theactions leading to lower cost and higher outcome by learning to associate proper actions todifferent states. Such states are generally complex states and the novel hypothesis I developedsuggests that the extension system is capable of learning such complex states and linking themto appropriate actions. In this framework, striatal neurons play the role of conjunction (BooleanAND) neurons while pallidal neurons can be envisioned as disjunction (Boolean OR) neurons.In the next set of experiments I tried to take the idea of basal ganglia subsystems to a new levelby dividing the rodent arbitration system into two functional subunits. A rostral group of ratpallidal neurons form dense local inhibition among themselves and even send inhibitoryprojections to the caudal segment. The caudal segment does not project back to its rostralcounterpart, but both segments send inhibitory projections to the output nuclei of the rat basalganglia i.e. the entopeduncular nucleus and substantia nigra. The rostral subsystems is capableof precisely detecting one (or several) components of a rudimentary action and suppress othercomponents. The components that are reinforced are those which lead to rewarding stateswhereas those that are suppressed are those which do not. The hypothesis explains neuronalmechanisms involved in this process and suggests that this subsystem is a means of generatingsimple but precise movements (such as using a single digit) from innate crude actions that theanimal can perform even at birth (such as general movement of the whole limb). In this way, therostral subsystem may play important role in exploration based learning.In an attempt to more precisely describe the relation between the arbitration and extensionsystems, we investigated the effect of dynamic synapses between subthalamic, pallidal andstriatal neurons and output neurons of the basal ganglia. The results imply that output neuronsare sensitive to striatal bursts and pallidal irregular firing. They also suggest that few striatalneurons are enough to fully suppress output neurons. Finally the results show that the globuspallidus exerts its effect on output neurons by direct inhibition rather than indirect influence viathe subthalamic nucleus.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. vii, 76 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2913:14
Keyword
Basal Ganglia, Action Selection, Motor Learning, Tectum, Superior Colliculus, Mesencephalic Locomotor Region, Reticulospinal Neurons, Computational Models
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-136745 (URN)978-91-7501-968-0 (ISBN)
Public defence
2013-12-19, Kollegiesalen, Brinellvägen 8, KTH, Stockholm, 10:00 (English)
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Note

QC 20131209

Available from: 2013-12-09 Created: 2013-12-09 Last updated: 2014-02-11Bibliographically approved

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