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INVESTIGATION OF THE RELATION BETWEEN DOPAMINE DEPLETION AND THE SLOWING OF ALPHA RHYTHM IN ELECTROENCEPHALOGRAM OF THALAMUS

Year 2019, Volume: 4 Issue: 1, 22 - 27, 30.06.2019

Abstract

A hybrid computational model of thalamo-cortical
circuitry and basal ganglia is used to investigate the relation between the
electroencephalogram (EEG) changes within the alpha frequency bands in thalamic
region depending on the decrease in the dopamine level in striatum.  Since it is known that in the diseases such
as Alzheimer and Parkinson, the level of dopamine decreases, the related
changes in thalamic region is investigated considering the dopamine depletion. The
diseases affects the dopamine decrease in different ways, such that in
Parkinsonian disease (PD), the total amount of dopamine affecting striatal
neurons decreases whereas in Alzheimer disease (AD), the dopamine level
decreases mostly in D2 dopamine receptor neurons. Therefore, these differences
are analyzed to investigate the slowing of alpha rhythm on EEG of thalamus by
using the modified mass model of thalamic region. It is observed that the
decrease in the amount of dopamine causes shift of the power in alpha bands to
lower frequencies. When the dopamine level is decreased in D1 and D2 type MSN
neurons, the slowing of alpha rhythm in EEG of thalamus
is prominent. 

Supporting Institution

TUBITAK BIDEB

Project Number

2219

References

  • [1] L. Zurkovsky, E. Bychkov, E.L. Tsakem , C. Siedlecki, R.D. Blakely, E.V. Gurevich, “Cognitive effects of dopamine depletion in the context of diminished acetylcholine signaling capacity in mice”, Dis Model Mech. Vol. 6, No.1, 2013, pp.171–183.
  • [2] C. Liu, J. Wanga, H. Yua, B. Denga, X. Weia, H. Lic, K. A. Loparob, C. Fietkiewicz, “Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models”, Commun Nonlinear Sci Numer Simulat.,Vol. 28, 2015, pp. 10–26.
  • [3] A. Rani, R. K. Diwan, A. Rani, A. K. Pankaj, R. K. Verma, G. Sehgal, “Alzheimer’s Brain : Gross And Microscopic Study”, J. Anat. Sciences, Vol. 24, No. 1, 2016, pp. 1-6.
  • [4] S. J. Colloby, S. McParland, J.T. O’Brien, J. Attems, (2012) “Neuropathological correlates of dopaminergic imaging in Alzheimer’s disease and Lewy body dementias”, Brain, Vol.135, 2012, pp. 2798–2808.
  • [5] M. De Marco, A. Venneri, (2018) “Volume and connectivity of the ventral tegmental area are linked to neurocognitive signatures of alzheimer’s disease in humans”, Journal of Alzheimer's Disease, Vol. 63, No. 1, 2018, pp. 167-180.
  • [6] B. S. Bhattacharya, T. P. Bond, L. O’Hare, D. Turner, S. J. Durrant. (2016) “Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics”, Frontiers in Computational Neuroscience| November 2016, Vol. 10, No. 115, 2016, pp. 1-18.
  • [7] R. Lizio, F. Vecchio, G. B. Frisoni, R. Ferri, G. Rodriguez, C. Babiloni, “Electroencephalographic Rhythms in Alzheimer’s Disease”, SAGE-Hindawi Access to Research International Journal of Alzheimer’s Disease, 2011, pp. 1-11.
  • [8] B. S. Bhattacharya, D. Coyle, L. P. Maguire, “Alpha and Theta Rhythm Abnormality in Alzheimer’s Disease: A Study Using a Computational Model” From Brains to Systems. Advances in Experimental Medicine and Biology Brain-Inspired Cognitive Systems, Springer New York Dordrecht Heidelberg, London, 2010, pp. 57-73.
  • [9] C. Huang, L. O. Wahlund, T. Dierks, P. Julin, B. Winblada, V. Jeli, “Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study”, Clinical Neurophysiology, Vol. 111, 2000, pp. 1961-1967.
  • [10] J. Jeong, “EEG dynamics in patients with Alzheimer’s disease”, Clinical Neurophysiology, Vol. 115, No. 7, 2004, pp. 1490– 1505.
  • [11] N. Kemppainen, M. Laine, M. P. Laakso, V. Kaasinen, K. Nagren, T. Vahlberg, T. Kurki, J. O. Rinne, “Hippocampal dopamine D2 receptors correlate with memory functions in Alzheimer's disease”, European Journal of Neuroscience, Vol. 18, 2003, pp. 149-154.
  • [12] S. J. van Albada, P. A. Robinson, “Mean-field modeling of the basal ganglia-thalamocortical system. I Firing rates in healthy and parkinsonian states”, Journal of Theoretical Biology, Vol. 257, 2009, pp. 642–663.
  • [13] B. S. Bhattacharya, Y. Cakir, N.S. Sengor, L. Maguire, D. Coylev, “Model-based bifurcation and power spectral analyses of thalamocortical alpha rhythm slowing in Alzheimer’s Disease” Neurocomputing, 115, 2013, pp 11–22.
  • [14] Y. Cakir, “Modeling of the BOLD signal relates to underlying neural activity of striatum and Alzhemier disease”, 2019, (under review)
  • [15] M. D. Humphries, R. Wood, K. Gurney, “Dopamine-modulated dynamic cell assemblies generated by the GABAergic striatal microcircuit”, Neural Networks, Vol. 22, No. 8, 2009, pp. 1174-1188.
  • [16] D. Guo, Q. Wang, M. Perc, “Complex synchronous behavior in interneuronal networks with delayed inhibitory and fast electrical synapses”, Phys Rev E., Vol. 85, 061905, 2012, pp. 1-8.
  • [17] Y. Cakir, “Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks” Network: Computation in Neural Systems, Vol.27 No. 4, 2016, pp. 289-305.
  • [18] Y. Cakir, “Modeling influences of dopamine on synchronization behavior of striatum”, Network: Computation in Neural Systems, Vol. 28, No 1, 2017, pp. 28-52.
  • [19] O. David, K. J. Friston, “A neural mass model for MEG/EEG: coupling and neuronal dynamics”, NeuroImage, Vol. 20, 2003, pp. 1743–1755.
Year 2019, Volume: 4 Issue: 1, 22 - 27, 30.06.2019

Abstract

Project Number

2219

References

  • [1] L. Zurkovsky, E. Bychkov, E.L. Tsakem , C. Siedlecki, R.D. Blakely, E.V. Gurevich, “Cognitive effects of dopamine depletion in the context of diminished acetylcholine signaling capacity in mice”, Dis Model Mech. Vol. 6, No.1, 2013, pp.171–183.
  • [2] C. Liu, J. Wanga, H. Yua, B. Denga, X. Weia, H. Lic, K. A. Loparob, C. Fietkiewicz, “Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models”, Commun Nonlinear Sci Numer Simulat.,Vol. 28, 2015, pp. 10–26.
  • [3] A. Rani, R. K. Diwan, A. Rani, A. K. Pankaj, R. K. Verma, G. Sehgal, “Alzheimer’s Brain : Gross And Microscopic Study”, J. Anat. Sciences, Vol. 24, No. 1, 2016, pp. 1-6.
  • [4] S. J. Colloby, S. McParland, J.T. O’Brien, J. Attems, (2012) “Neuropathological correlates of dopaminergic imaging in Alzheimer’s disease and Lewy body dementias”, Brain, Vol.135, 2012, pp. 2798–2808.
  • [5] M. De Marco, A. Venneri, (2018) “Volume and connectivity of the ventral tegmental area are linked to neurocognitive signatures of alzheimer’s disease in humans”, Journal of Alzheimer's Disease, Vol. 63, No. 1, 2018, pp. 167-180.
  • [6] B. S. Bhattacharya, T. P. Bond, L. O’Hare, D. Turner, S. J. Durrant. (2016) “Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics”, Frontiers in Computational Neuroscience| November 2016, Vol. 10, No. 115, 2016, pp. 1-18.
  • [7] R. Lizio, F. Vecchio, G. B. Frisoni, R. Ferri, G. Rodriguez, C. Babiloni, “Electroencephalographic Rhythms in Alzheimer’s Disease”, SAGE-Hindawi Access to Research International Journal of Alzheimer’s Disease, 2011, pp. 1-11.
  • [8] B. S. Bhattacharya, D. Coyle, L. P. Maguire, “Alpha and Theta Rhythm Abnormality in Alzheimer’s Disease: A Study Using a Computational Model” From Brains to Systems. Advances in Experimental Medicine and Biology Brain-Inspired Cognitive Systems, Springer New York Dordrecht Heidelberg, London, 2010, pp. 57-73.
  • [9] C. Huang, L. O. Wahlund, T. Dierks, P. Julin, B. Winblada, V. Jeli, “Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study”, Clinical Neurophysiology, Vol. 111, 2000, pp. 1961-1967.
  • [10] J. Jeong, “EEG dynamics in patients with Alzheimer’s disease”, Clinical Neurophysiology, Vol. 115, No. 7, 2004, pp. 1490– 1505.
  • [11] N. Kemppainen, M. Laine, M. P. Laakso, V. Kaasinen, K. Nagren, T. Vahlberg, T. Kurki, J. O. Rinne, “Hippocampal dopamine D2 receptors correlate with memory functions in Alzheimer's disease”, European Journal of Neuroscience, Vol. 18, 2003, pp. 149-154.
  • [12] S. J. van Albada, P. A. Robinson, “Mean-field modeling of the basal ganglia-thalamocortical system. I Firing rates in healthy and parkinsonian states”, Journal of Theoretical Biology, Vol. 257, 2009, pp. 642–663.
  • [13] B. S. Bhattacharya, Y. Cakir, N.S. Sengor, L. Maguire, D. Coylev, “Model-based bifurcation and power spectral analyses of thalamocortical alpha rhythm slowing in Alzheimer’s Disease” Neurocomputing, 115, 2013, pp 11–22.
  • [14] Y. Cakir, “Modeling of the BOLD signal relates to underlying neural activity of striatum and Alzhemier disease”, 2019, (under review)
  • [15] M. D. Humphries, R. Wood, K. Gurney, “Dopamine-modulated dynamic cell assemblies generated by the GABAergic striatal microcircuit”, Neural Networks, Vol. 22, No. 8, 2009, pp. 1174-1188.
  • [16] D. Guo, Q. Wang, M. Perc, “Complex synchronous behavior in interneuronal networks with delayed inhibitory and fast electrical synapses”, Phys Rev E., Vol. 85, 061905, 2012, pp. 1-8.
  • [17] Y. Cakir, “Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks” Network: Computation in Neural Systems, Vol.27 No. 4, 2016, pp. 289-305.
  • [18] Y. Cakir, “Modeling influences of dopamine on synchronization behavior of striatum”, Network: Computation in Neural Systems, Vol. 28, No 1, 2017, pp. 28-52.
  • [19] O. David, K. J. Friston, “A neural mass model for MEG/EEG: coupling and neuronal dynamics”, NeuroImage, Vol. 20, 2003, pp. 1743–1755.
There are 19 citations in total.

Details

Primary Language English
Subjects Electrical Engineering
Journal Section Articles
Authors

Yüksel Çakir 0000-0002-4238-8504

Project Number 2219
Publication Date June 30, 2019
Published in Issue Year 2019 Volume: 4 Issue: 1

Cite

APA Çakir, Y. (2019). INVESTIGATION OF THE RELATION BETWEEN DOPAMINE DEPLETION AND THE SLOWING OF ALPHA RHYTHM IN ELECTROENCEPHALOGRAM OF THALAMUS. The Journal of Cognitive Systems, 4(1), 22-27.