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Corticostriatal circuits and their role in disease

Jovana Belic1, 2*, Pär Halje3, Ulrike Richter3, Per Petersson3 and Jeanette Hellgren Kotaleski1, 4
  • 1 KTH Royal Institute of Technology, Department of Computational Biology, Sweden
  • 2 University of Freiburg, Bernstein Center Freiburg, Germany
  • 3 Lund University, Department of Experimental Medical Science, Sweden
  • 4 Karolinska Institutet, Department of Neuroscience, Sweden

The basal ganglia (BG) represent subcortical structures considered to be involved in action selection and decision making [1]. Dysfunction of the BG circuitry leads to many motor and cognitive disorders such as Parkinson’s disease (PD), Tourette syndrome, Huntington’s disease, obsessive compulsive disorder and many others. Therefore, we simultaneously recorded local field potentials (LFPs) in primary motor cortex and sensorimotor striatum to study features directly related to healthy versus pathological states such as Parkinson disease and levodopa-induced dyskinesia [2], [3]. The striatum, the input stage of the basal ganglia (BG), is an inhibitory network that contains several distinct cell types and receives massive excitatory inputs from the cortex. Cortex sends direct projections to the striatum, while striatum can affect cortex only indirectly through other BG nuclei and thalamus. Firstly we analyzed 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 around 80 Hz, while for PD it was the beta frequency range. Secondly our preliminary results have shown that during both pathological states effective connectivity in terms of Granger causality is bidirectional with an accent on striatal influence on cortex. In the case of dyskinesia we have also found a specifically high increase in effective connectivity at 80 Hz. In order to further understand the 80-Hz phenomenon we have performed cross-frequency analysis across all states and both structures and observed characteristic patterns in the case of dyskinesia in both structures but not in the case of PD and healthy state. We have seen a large relative decrease in the modulation of the amplitude at 80Hz by the phase of low frequency oscillations (up to ~10Hz). It has been suggested that the activity of local neural populations is modulated according to the global neuronal dynamics in the way that populations oscillate and synchronize at lower frequencies and smaller ensembles are active at higher frequencies Our results suggest unexpectedly a lack of coupling between the low frequency activity of a larger population and the synchronized activity of a smaller group of neurons active at 80Hz.

References

1. Grillner, S., Hellgren Kotaleski, J., Menard, A., Saitoh, K., Wikström, M. (2005). Mechanisms for selection of basic motor programs--roles for the striatum and pallidum. Trends in Neuroscience 28, 364-70.
2. Halje, P., Tamte, M., Richter, U., Mohammed, M., Cenci, A., Petersson, P. (2012). Levodopa-Induced Dyskinesia Is Strongly Associated with Resonant Cortical Oscillations. J Neurosci. 32, 16541-16551.
3. Belić, J., Halje, P., Richter, U., Petersson, P., Hellgren Kotaleski, J. (2015). Behavior Discrimination Using a Discrete Wavelet Based Approach for Feature Extraction on Local Field Potentials in the Cortex and Striatum. IEEE/EMBS Conf Proc. Neural Engineering (NER) 7, Montpellier, France.

Keywords: Corticostriatal circuits, Levodopa-induced dyskinesia, Parkinson’s disease, effective connectivity, Cross-Frequency Couplings

Conference: Neuroinformatics 2015, Cairns, Australia, 20 Aug - 22 Aug, 2015.

Presentation Type: Poster, to be considered for oral presentation

Topic: Electrophysiology

Citation: Belic J, Halje P, Richter U, Petersson P and Hellgren Kotaleski J (2015). Corticostriatal circuits and their role in disease. Front. Neurosci. Conference Abstract: Neuroinformatics 2015. doi: 10.3389/conf.fnins.2015.91.00017

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Received: 07 Apr 2015; Published Online: 05 Aug 2015.

* Correspondence: Ms. Jovana Belic, KTH Royal Institute of Technology, Department of Computational Biology, Stockholm, 10044, Sweden, belic@kth.se