Focal inputs are a potential origin of local field potential (LFP) in the brain regions without laminar structure


Autoři: Takuma Tanaka aff001;  Kouichi C. Nakamura aff002
Působiště autorů: Graduate School of Data Science, Shiga University, Hikone, Shiga, Japan aff001;  MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom aff002
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226028

Souhrn

Current sinks and sources spatially separated between the apical and basal dendrites have been believed to be essential in generating local field potentials (LFPs). According to this theory, LFPs would not be large enough to be observed in the regions without laminar structures, such as striatum and thalamus. However, LFPs are experimentally recorded in these regions. We hypothesized that focal excitatory input induces a concentric current sink and source generating LFPs in these regions. In this study, we tested this hypothesis by the numerical simulations of multicompartment neuron models and the analysis of simplified models. Both confirmed that focal excitatory input can generate LFPs on the order of 0.1 mV in a region without laminar structures. The present results suggest that LFPs in subcortical nuclei indicate localized excitatory input.

Klíčová slova:

Membrane potential – Neostriatum – Neuronal dendrites – Neurons – Radii – Simulation and modeling – Synapses – Dendritic structure


Zdroje

1. Einevoll GT, Kayser C, Logothetis NK, Panzeri S. Modelling and analysis of local field potentials for studying the function of cortical circuits. Nat Rev Neurosci. 2013;14: 770–785. doi: 10.1038/nrn3599 24135696

2. Goldberg JA. Spike Synchronization in the Cortex-Basal Ganglia Networks of Parkinsonian Primates Reflects Global Dynamics of the Local Field Potentials. J Neurosci. 2004;24: 6003–6010. doi: 10.1523/JNEUROSCI.4848-03.2004 15229247

3. Berke JD. Fast oscillations in cortical-striatal networks switch frequency following rewarding events and stimulant drugs. Eur J Neurosci. 2009;30: 848–859. doi: 10.1111/j.1460-9568.2009.06843.x 19659455

4. Van Der Meer MAA, Redish AD. Low and high gamma oscillations in rat ventral striatum have distinct relationships to behavior, reward, and spiking activity on a learned spatial decision task. Front Integr Neurosci. 2009;3. doi: 10.3389/neuro.07.009.2009 19562092

5. Lemaire N, Hernandez LF, Hu D, Kubota Y, Howe MW, Graybiel AM. Effects of dopamine depletion on LFP oscillations in striatum are task- and learning-dependent and selectively reversed by l-DOPA. Proc Natl Acad Sci. 2012;109: 18126–18131. doi: 10.1073/pnas.1216403109 23074253

6. Marsden JF, Ashby P, Limousin-Dowsey P, Rothwell JC, Brown P. Coherence between cerebellar thalamus, cortex and muscle in man: cerebellar thalamus interactions. Brain J Neurol. 2000;123 (Pt 7): 1459–1470.

7. Schiff ND, Shah SA, Hudson AE, Nauvel T, Kalik SF, Purpura KP. Gating of attentional effort through the central thalamus. J Neurophysiol. 2013;109: 1152–1163. doi: 10.1152/jn.00317.2011 23221415

8. Brazhnik E, McCoy AJ, Novikov N, Hatch CE, Walters JR. Ventral Medial Thalamic Nucleus Promotes Synchronization of Increased High Beta Oscillatory Activity in the Basal Ganglia–Thalamocortical Network of the Hemiparkinsonian Rat. J Neurosci. 2016;36: 4196–4208. doi: 10.1523/JNEUROSCI.3582-15.2016 27076419

9. Fiáth R, Beregszászi P, Horváth D, Wittner L, Aarts AAA, Ruther P, et al. Large-scale recording of thalamocortical circuits: in vivo electrophysiology with the two-dimensional electronic depth control silicon probe. J Neurophysiol. 2016;116: 2312–2330. doi: 10.1152/jn.00318.2016 27535370

10. Magill PJ, Sharott A, Bolam JP, Brown P. Brain State–Dependency of Coherent Oscillatory Activity in the Cerebral Cortex and Basal Ganglia of the Rat. J Neurophysiol. 2004;92: 2122–2136. doi: 10.1152/jn.00333.2004 15175372

11. Avila I, Parr-Brownlie LC, Brazhnik E, Castañeda E, Bergstrom DA, Walters JR. Beta frequency synchronization in basal ganglia output during rest and walk in a hemiparkinsonian rat. Exp Neurol. 2010;221: 307–319. doi: 10.1016/j.expneurol.2009.11.016 19948166

12. Lindén H, Pettersen KH, Einevoll GT. Intrinsic dendritic filtering gives low-pass power spectra of local field potentials. J Comput Neurosci. 2010;29: 423–444. doi: 10.1007/s10827-010-0245-4 20502952

13. Buzsáki G, Anastassiou CA, Koch C. The origin of extracellular fields and currents—EEG, ECoG, LFP and spikes. Nat Rev Neurosci. 2012;13: 407–420. doi: 10.1038/nrn3241 22595786

14. Brown P, Williams D. Basal ganglia local field potential activity: Character and functional significance in the human. Clin Neurophysiol. 2005;116: 2510–2519. doi: 10.1016/j.clinph.2005.05.009 16029963

15. Boraud T, Brown P, Goldberg JA, Graybiel AM, Magill PJ. Oscillations in the Basal Ganglia: The good, the bad, and the unexpected. In: Bolam JP, Ingham CA, Magill PJ, editors. The Basal Ganglia VIII. Boston: Kluwer Academic Publishers; 2005. pp. 1–24. doi: 10.1007/0-387-28066-9_1

16. Carnevale NT, Hines ML. The NEURON Book. Cambridge: Cambridge University Press; 2006. doi: 10.1017/CBO9780511541612

17. Hines ML, Davison AP, Muller E. NEURON and Python. Front Neuroinformatics. 2009;3. doi: 10.3389/neuro.11.001.2009 19198661

18. Lindén H, Hagen E, Łęski S, Norheim ES, Pettersen KH, Einevoll GT. LFPy: a tool for biophysical simulation of extracellular potentials generated by detailed model neurons. Front Neuroinformatics. 2014;7. doi: 10.3389/fninf.2013.00041 24474916

19. Hämäläinen M, Hari R, Ilmoniemi RJ, Knuutila J, Lounasmaa OV. Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev Mod Phys. 1993;65: 413–497. doi: 10.1103/RevModPhys.65.413

20. Bédard C, Kröger H, Destexhe A. Modeling Extracellular Field Potentials and the Frequency-Filtering Properties of Extracellular Space. Biophys J. 2004;86: 1829–1842. doi: 10.1016/S0006-3495(04)74250-2 14990509

21. Mainen ZF, Sejnowski TJ. Influence of dendritic structure on firing pattern in model neocortical neurons. Nature. 1996;382: 363–366. doi: 10.1038/382363a0 8684467

22. Schüz A, Palm G. Density of neurons and synapses in the cerebral cortex of the mouse. J Comp Neurol. 1989;286: 442–455. doi: 10.1002/cne.902860404 2778101

23. Nakano T, Yoshimoto J, Doya K. A model-based prediction of the calcium responses in the striatal synaptic spines depending on the timing of cortical and dopaminergic inputs and post-synaptic spikes. Front Comput Neurosci. 2013;7. doi: 10.3389/fncom.2013.00119 24062681

24. Shepherd GM, editor. The Synaptic Organization of the Brain. 5. ed. Oxford: Oxford Univ. Press; 2004.

25. Meitzen J, Pflepsen KR, Stern CM, Meisel RL, Mermelstein PG. Measurements of neuron soma size and density in rat dorsal striatum, nucleus accumbens core and nucleus accumbens shell: differences between striatal region and brain hemisphere, but not sex. Neurosci Lett. 2011;487: 177–181. doi: 10.1016/j.neulet.2010.10.017 20951763

26. Wennberg RA, Lozano AM. Intracranial volume conduction of cortical spikes and sleep potentials recorded with deep brain stimulating electrodes. Clin Neurophysiol. 2003;114: 1403–1418. doi: 10.1016/s1388-2457(03)00152-4 12888022

27. Lalla L, Rueda Orozco PE, Jurado-Parras M-T, Brovelli A, Robbe D. Local or Not Local: Investigating the Nature of Striatal Theta Oscillations in Behaving Rats. eneuro. 2017;4: ENEURO.0128–17.2017. doi: 10.1523/ENEURO.0128-17.2017 28966971

28. Telkes I, Viswanathan A, Jimenez-Shahed J, Abosch A, Ozturk M, Gupte A, et al. Local field potentials of subthalamic nucleus contain electrophysiological footprints of motor subtypes of Parkinson’s disease. Proc Natl Acad Sci. 2018;115: E8567–E8576. doi: 10.1073/pnas.1810589115 30131429


Článek vyšel v časopise

PLOS One


2019 Číslo 12