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Untangling Cortico-Striatal Circuitry and its Role in Health and Disease - A computational investigation
KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The basal ganglia (BG) play a critical role in a variety of regular motor and cognitive functions. Many brain diseases, such as Parkinson’s diseases, Huntington’s disease and dyskinesia, are directly related to malfunctions of the BG nuclei. One of those nuclei, the input nucleus called the striatum, is heavily connected to the cortex and receives afferents from nearly all cortical areas. The striatum is a recurrent inhibitory network that contains several distinct cell types. About 95% of neurons in the striatum are medium spiny neurons (MSNs) that form the only output from the striatum. Two of the most examined sources of GABAergic inhibition into MSNs are the feedback inhibition (FB) from the axon collaterals of the MSNs themselves, and the feedforward inhibition (FF) via the small population (1-2% of striatal neurons) of fast spiking interneurons (FSIs). The cortex sends direct projections to the striatum, while the striatum can affect the cortex only indirectly through other BG nuclei and the thalamus. Understanding how different components of the striatal network interact with each other and influence the striatal response to cortical inputs has crucial importance for clarifying the overall functions and dysfunctions of the BG.

    In this thesis I have employed advanced experimental data analysis techniques as well as computational modelling, to study the complex nature of cortico-striatal interactions. I found that for pathological states, such as Parkinson’s disease and L-DOPA-induced dyskinesia, effective connectivity is bidirectional with an accent on the striatal influence on the cortex. Interestingly, in the case of L-DOPA-induced dyskinesia, there was a high increase in effective connectivity at ~80 Hz and the results also showed a large relative decrease in the modulation of the local field potential amplitude (recorded in the primary motor cortex and sensorimotor striatum in awake, freely behaving, 6-OHDA lesioned hemi-parkinsonian rats) at ~80 Hz by the phase of low frequency oscillations. These results suggest a lack of coupling between the low frequency activity of a presumably larger neuronal population and the synchronized activity of a presumably smaller group of neurons active at 80 Hz.

    Next, I used a spiking neuron network model of the striatum to isolate the mechanisms underlying the transmission of cortical oscillations to the MSN population. I showed that FSIs play a crucial role in efficient propagation of cortical oscillations to the MSNs that did not receive direct cortical oscillations. Further, I have identified multiple factors such as the number of activated neurons, ongoing activity, connectivity, and synchronicity of inputs that influenced the transfer of oscillations by modifying the levels of FB and FF inhibitions. Overall, these findings reveal a new role of FSIs in modulating the transfer of information from the cortex to striatum. By modulating the activity and properties of the FSIs, striatal oscillations can be controlled very efficiently. Finally, I explored the interactions in the striatal network with different oscillation frequencies and showed that the features of those oscillations, such as amplitude and frequency fluctuations, can be influenced by a change in the input intensities into MSNs and FSIs and that these fluctuations are also highly dependent on the selected frequencies in addition to the phase offset between different cortical inputs.

    Lastly, I investigated how the striatum responds to cortical neuronal avalanches. Recordings in the striatum revealed that striatal activity was also characterized by spatiotemporal clusters that followed a power law distribution albeit, with significantly steeper slope. In this study, an abstract computational model was developed to elucidate the influence of intrastriatal inhibition and cortico-striatal interplay as important factors to understand the experimental findings. I showed that one particularly high activation threshold of striatal nodes can reproduce a power law-like distribution with a coefficient similar to the one found experimentally. By changing the ratio of excitation and inhibition in the cortical model, I saw that increased activity in the cortex strongly influenced striatal dynamics, which was reflected in a less negative slope of cluster size distributions in the striatum.  Finally, when inhibition was added to the model, cluster size distributions had a prominently earlier deviation from the power law distribution compared to the case when inhibition was not present. 

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. , p. 88
Series
TRITA-EECS-AVL ; 2018:9
Keyword [en]
cortico-striatal circuits, levodopa-induced dyskinesia, Parkinson’s disease, effective connectivity, cross-frequency coupling, corticostriatal network, network oscillations, GABAergic transmission. basal ganglia, striatum, cortex, fast spiking interneurons, medium spiny neurons, neuronal avalanches
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-222467ISBN: 978-91-7729-676-8 (print)OAI: oai:DiVA.org:kth-222467DiVA: diva2:1181680
Public defence
2018-03-05, F3, Lindstedtsvägen 26, KTH Campus, Stockholm, 13:15 (English)
Opponent
Supervisors
Note

QC 20180209

Available from: 2018-02-09 Created: 2018-02-09 Last updated: 2018-02-09Bibliographically approved
List of papers
1. Untangling cortico-striatal connectivity and cross-frequency coupling in L-DOPA-induced dyskinesia
Open this publication in new window or tab >>Untangling cortico-striatal connectivity and cross-frequency coupling in L-DOPA-induced dyskinesia
Show others...
2016 (English)In: Frontiers in Systems Neuroscience, ISSN 1662-5137, E-ISSN 1662-5137, Vol. 10, no 26, p. 1-12Article in journal (Refereed) Published
Abstract [en]

We simultaneously recorded local field potentials in the primary motor cortex and sensorimotor striatum in awake, freely behaving, 6-OHDA lesioned hemi-parkinsonian rats in order to study the features directly related to pathological states such as parkinsonian state and levodopa-induced dyskinesia. We analysed the spectral characteristics of the obtained signals and observed that during dyskinesia the most prominent feature was a relative power increase in the high gamma frequency range at around 80 Hz, while for the parkinsonian state it was in the beta frequency range. Here we show that during both pathological states effective connectivity in terms of Granger causality is bidirectional with an accent on the striatal influence on the cortex. In the case of dyskinesia, we also found a high increase in effective connectivity at 80 Hz. In order to further understand the 80- Hz phenomenon, we performed cross-frequency analysis and observed characteristic patterns in the case of dyskinesia but not in the case of the parkinsonian state or the healthy state. We noted a large decrease in the modulation of the amplitude at 80 Hz by the phase of low frequency oscillations (up to ~10 Hz) across both structures in the case of dyskinesia. This may suggest a lack of coupling between the low frequency activity of the recorded network and the group of neurons active at ~80 Hz.

Place, publisher, year, edition, pages
Frontiers, 2016
Keyword
Cortico-striatal circuits, Levodopa-induced dyskinesia, Parkinson’s disease, effective connectivity, Cross-frequency coupling
National Category
Medical and Health Sciences Natural Sciences
Identifiers
urn:nbn:se:kth:diva-184005 (URN)10.3389/fnsys.2016.00026 (DOI)000372965400001 ()2-s2.0-84964898882 (Scopus ID)
External cooperation:
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceSwedish Research Council
Note

QC 20160419

Available from: 2016-03-22 Created: 2016-03-22 Last updated: 2018-02-09Bibliographically approved
2. Behavior Discrimination Using a Discrete Wavelet Based Approach for Feature Extraction on Local Field Potentials in the Cortex and Striatum
Open this publication in new window or tab >>Behavior Discrimination Using a Discrete Wavelet Based Approach for Feature Extraction on Local Field Potentials in the Cortex and Striatum
Show others...
2015 (English)In: 7th International IEEE/EMBS Conference on Neural Engineering (NER), IEEE conference proceedings, 2015, Vol. 7, p. 964-967Conference paper, Published paper (Refereed)
Abstract [en]

Linkage between behavioral states and neural activity is one of the most important challenges in neuroscience. The network activity patterns in the awake resting state and in the actively behaving state in rodents are not well understood, and a better tool for differentiating these states can provide insights on healthy brain functions and its alteration with disease. Therefore, we simultaneously recorded local field potentials (LFPs) bilaterally in motor cortex and striatum, and measured locomotion from healthy, freely behaving rats. Here we analyze spectral characteristics of the obtained signals and present an algorithm for automatic discrimination of the awake resting and the behavioral states. We used the Support Vector Machine (SVM) classifier and utilized features obtained by applying discrete wavelet transform (DWT) on LFPs, which arose as a solution with high accuracy.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015
National Category
Engineering and Technology Natural Sciences
Identifiers
urn:nbn:se:kth:diva-168488 (URN)10.1109/NER.2015.7146786 (DOI)000377414600242 ()2-s2.0-84940386288 (Scopus ID)
Conference
7th Annual International IEEE EMBS Conference on Neural Engineering
Note

QC 20150623

Available from: 2015-06-04 Created: 2015-06-04 Last updated: 2018-02-09Bibliographically approved
3. Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations
Open this publication in new window or tab >>Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations
2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 4, p. 1-17Article in journal (Refereed) Published
Abstract [en]

Network oscillations are ubiquitous across many brain regions. In the basal ganglia, oscillations are also present at many levels and a wide range of characteristic frequencies have been reported to occur during both health and disease. The striatum, the main input nucleus of the basal ganglia, receives massive glutamatergic inputs from the cortex and is highly susceptible to external oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, external stimuli propagate through the striatal circuitry. Using a network model of the striatum and corticostriatal projections, we try to elucidate the importance of specific GABAergic neurons and their interactions in shaping striatal oscillatory activity. Here, we propose that fast-spiking interneurons can perform an important role in transferring cortical oscillations to the striatum especially to those medium spiny neurons that are not directly driven by the cortical oscillations. We show how the activity levels of different populations, the strengths of different inhibitory synapses, degree of outgoing projections of striatal cells, ongoing activity and synchronicity of inputs can influence network activity. These results suggest that the propagation of oscillatory inputs into the medium spiny neuron population is most efficient, if conveyed via the fast-spiking interneurons. Therefore, pharmaceuticals that target fast-spiking interneurons may provide a novel treatment for regaining the spectral characteristics of striatal activity that correspond to the healthy state.

Keyword
striatum, fast-spiking interneurons, network oscillations, medium spiny neurons, GABAergic transmission, corticostriatal interactions
National Category
Computer Sciences Biological Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-205220 (URN)10.1371/journal.pone.0175135 (DOI)000399371900097 ()2-s2.0-85017146743 (Scopus ID)
Note

QC 20170411

Available from: 2017-04-10 Created: 2017-04-10 Last updated: 2018-02-09Bibliographically approved
4. Interactions in the Striatal Network with Different Oscillation Frequencies
Open this publication in new window or tab >>Interactions in the Striatal Network with Different Oscillation Frequencies
2017 (English)In: Artificial Neural Networks and Machine Learning – ICANN. Lecture Notes in Computer Science, Springer, 2017, Vol. 10613, p. 129-136Conference paper, Published paper (Refereed)
Abstract [en]

Simultaneous oscillations in different frequency bands are implicated in the striatum, and understanding their interactions will bring us one step closer to restoring the spectral characteristics of striatal activity that correspond to the healthy state. We constructed a computational model of the striatum in order to investigate how different, simultaneously present, and externally induced oscillations propagate through striatal circuitry and which stimulation parameters have a significant contribution. Our results show that features of these oscillations and their interactions can be influenced via amplitude, input frequencies, and the phase offset between different external inputs. Our findings provide further untangling of the oscillatory activity that can be seen within the striatal network.

Place, publisher, year, edition, pages
Springer, 2017
Keyword
Corticostriatal network, Network oscillations, GABAergic transmission, Basal ganglia, Cortex
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-217110 (URN)10.1007/978-3-319-68600-4_16 (DOI)978-3-319-68599-1 (ISBN)
Conference
Artificial Neural Networks and Machine Learning – ICANN 2017.
Note

QC 20171101

Available from: 2017-10-31 Created: 2017-10-31 Last updated: 2018-02-09Bibliographically approved
5. Mapping of Cortical Avalanches to the Striatum
Open this publication in new window or tab >>Mapping of Cortical Avalanches to the Striatum
2015 (English)In: Advances in Cognitive Neurodynamics, Springer Netherlands, 2015, 4, p. 291-297Chapter in book (Refereed)
Abstract [en]

Neuronal avalanches are found in the resting state activity of the mammaliancortex. Here we studied whether and how cortical avalanches are mappedonto the striatal circuitry, the first stage of the basal ganglia. We first demonstrate using organotypic cortex-striatum-substantia nigra cultures from rat that indeed striatal neurons respond to cortical avalanches originating in superficial layers. We simultaneously recorded spontaneous local field potentials (LFPs) in the cortical and striatal tissue using high-density microelectrode arrays. In the cortex, spontaneous neuronal avalanches were characterized by intermittent spatiotemporal activity clusters with a cluster size distribution that followed a power law with exponent 1.5. In the striatum, intermittent spatiotemporal activity was found to correlate with cortical avalanches. However, striatal negative LFP peaks (nLFPs) did not showavalanche signatures, but formed a cluster size distribution that had a much steeper drop-off, i.e., lacked large spatial clusters that are commonly expected for avalanche dynamics. The underlying de-correlation of striatal activity could have its origin in the striatum through local inhibition and/or could result from a particular mapping in the corticostriatal pathway. Here we show, using modeling, that highly convergent corticostriatal projections can map spatially extended cortical activity into spatially restricted striatal regimes.

Place, publisher, year, edition, pages
Springer Netherlands, 2015 Edition: 4
Keyword
Neuronal avalanches, Striatum, Cortico-striatal network, Cortex, Basal ganglia
National Category
Natural Sciences
Identifiers
urn:nbn:se:kth:diva-168104 (URN)10.1007/978-94-017-9548-7_41 (DOI)000380362800041 ()978-94-017-9547-0 (ISBN)
Note

QC 20150623

Available from: 2015-05-27 Created: 2015-05-27 Last updated: 2018-02-09Bibliographically approved
6. Striatal processing of cortical neuronal avalanches – A computational investigation
Open this publication in new window or tab >>Striatal processing of cortical neuronal avalanches – A computational investigation
2016 (English)In: Artificial Neural Networks and Machine Learning - ICANN. Lecture Notes in Computer Science, Springer, 2016, Vol. 9886, p. 72-79Conference paper, Published paper (Refereed)
Abstract [en]

In the cortex, spontaneous neuronal avalanches can be characterized by spatiotemporal activity clusters with a cluster size distribution that follows a power law with exponent –1.5. Recordings in the striatum revealed that striatal activity was also characterized by spatiotemporal clusters that followed a power law distribution albeit, with significantly steeper slope, i.e., they lacked the large spatial clusters that are commonly expected for avalanche dynamics. In this study, we used computational modeling to investigate the influence of intrastriatal inhibition and corticostriatal interplay as important factors to understand the experimental findings and overall information transmission among these circuits.

Place, publisher, year, edition, pages
Springer, 2016
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 9886
Keyword
Corticostriatal network, Neuronal avalanches, Striatum, Basal ganglia, Cortex
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-191313 (URN)10.1007/978-3-319-44778-0_9 (DOI)000389086300009 ()2-s2.0-84987956630 (Scopus ID)978-3-319-44778-0 (ISBN)978-3-319-44777-3 (ISBN)
Conference
25th International Conference on Artificial Neural Networks, ICANN 2016, Barcelona, Spain, 6 September 2016 through 9 September 2016
Note

QC 20160829

Available from: 2016-08-28 Created: 2016-08-28 Last updated: 2018-02-09Bibliographically approved

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