Linking biophysical properties of the neurons and circuit dynamics to the computations and different behavioral states
Robustness and circuit dynamics of reciprocally inhibitory neural circuits
One of the big questions in understanding the brain is why individuals are differentially resilient to stress and injury. We explore how small reciprocally inhibitory neural circuits produce reliable yet flexible output to adapt their activity in response environmental needs and challenges. Reciprocal inhibition is a common circuit motif in the brain that underlies the production of rhythmic neural activity patterns. It is important for motor and sensory systems, and crucial in setting the excitation/inhibition balance required for appropriate cortical function. We built reciprocally inhibitory networks of two crab motor neurons by connecting them with artificial reciprocal inhibitory synapses and adding hyperpolarization-activated inward current via dynamic clamp. In this hybrid circuit, we have a control over the computer-generated parameters critical for production of the neural activity patterns, allowing us to comprehensively investigate how circuit dynamics emerge from intrinsic and synaptic properties of neurons. Our results demonstrate that reciprocally inhibitory circuits with different underlying mechanisms of oscillations, “release” or “escape”, are distinctly modulated by their intrinsic conductances, neurotransmitters and global perturbations, such as temperature. These networks smoothly slide through changes in oscillatory mechanisms as the temperature changes, thus, extending the dynamical range over which they can function.
Custom written RTXI module for constructing reciprocally inhibitory circuits is available on GitHub
Neural adaptation to elevated [K+] concentration
Nervous system must be resilient to environmental challenges and perturbations. Elevated extracellular potassium concentration ([K+]) is a physiologically relevant perturbation associated with a wide array of pathological conditions including thermal stress, epileptic seizures, kidney failure, traumatic brain injury, and stroke. Experimentally, increased extracellular [K+] is often used to depolarize neurons, with the aim of increasing their activity. We studied the response of a crab central-pattern generator (CPG) to elevated [K+]. CPG neurons exhibited rapid adaptation to the disruptive stimulus of increased extracellular [K+] on the timescale of minutes. A shift in intrinsic excitability enabled the neurons to adapt to global depolarization. Interaction between circuit-level effects and cell-intrinsic excitability in response to simple changes in ion concentrations produce complex and nonstationary effects on neuronal activity.
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Excitability type of the dopaminergic neurons and its role in computations
Dopaminergic neurons play a central role in guiding motivated behaviors. However, complete understanding of the computations these neurons perform to encode rewarding and salient stimuli is still forthcoming. Using a biophysical model of the dopaminergic neurons, we attempted to link biophysical properties of these neurons with the computations they perform in the brain. An increasing body of literature links the neuronal excitability type to the coding strategy of the neurons. We found that depending on the intrinsic current composition and synaptic inputs these neurons can exhibit either type I or type II excitability. In the absence of synaptic inputs or under balanced excitation/inhibition dopaminergic neurons exhibit type I excitability. The ability of type I dopaminergic neurons to smoothly encode stimulus intensity is critical for the unique computational role of calculating the reward prediction error, i.e. calculating the difference between predicted and received reward. Potentiation of hyperpolarization-activated inward current, tonic activation of AMPAR and/or depolarization of GABAR reversal potential, switches the dopaminergic neurons to type II excitability. Such a switch to type II excitability might play a significant role in detecting environmentally salient stimuli and producing enhanced transient dopamine.
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Biophysical model of the dopaminergic neuron
Cholinergic and nicotinic modulation of the reward circuit of the brain
Nicotine, the substance that makes tobacco addictive, does so by increasing the release of the dopamine, a “reward” signal in the brain. Nicotine activates the same class of receptors as acetylcholine, which is naturally produced in the brain. Cholinergic receptors are found on dopaminergic neurons, as well as GABAergic neurons that inhibit dopamine neurons, raising questions about how the circuit interacts to produce the final output. Removing these receptors from both neurons reduced activity of dopamine neurons as expected, while replacing them only in inhibitory neurons and not dopamine neurons paradoxically increased the activity of dopamine neurons. Conversely, the application of nicotine in this scenario suppressed the dopamine neurons. All these effects are explained by our model of the circuit interactions between dopaminergic and GABAergic neurons. We found that the temporal dynamics of inhibition are key to explaining these effects, including the need for inhibitory activation for phasic dopamine release in an intact circuit.
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Computational model of cholinergic and nicotinic regulation of dopamine neuron firing
Publications
- L. S. He, * M. C.P. Rue*, E. O. Morozova*, D. J. Powell, E. J. James, M. Kar, and E. Marder. Rapid Adaptation to Elevated Extracellular Potassium in the Pyloric Circuit of the Crab, Cancer borealis. Journal of neurophysiology, doi: 10.1152/jn.00135.2020, 22 April 2020. Read
- E. O. Morozova, P. Faure, B. Gutkin, C. Lapish, A. Kuznetsov. Distinct temporal structure of nicotinic ACh receptor activation determines responses of VTA neurons to endogenous ACh and nicotine. eNeuro, doi: 10.1523/ENEURO.0418-19.2020, eNeuro 31 July 2020. Read
- D. Kushinsky*, E. O. Morozova*, E. Marder. In vivo effects of temperature on the heart and pyloric rhythms in the crab, Cancer Borealis. Journal of experimental biology, doi: 10.1242/jeb.199190, 1 March 2019. Read
- M. di Volo, E. O. Morozova, C. C. Lapish, A. Kuznetsov, B. Gutkin. Dynamical Ventral Tegmental Area Circuit Mechanisms of Alcohol-Dependent Dopamine Release. European Journal of Neuroscience, doi 10.1111/ejn.14147, 14 September 2018. Read
- O.V. Lebedeva, Grebenev I.V., Morozova E.O. Inquiry-Based Learning for Physics Courses within the Russian Schooling System. Integration of education. Vol 2, no 4. 2017 (in Russian)
- E. O. Morozova*, D. Zakharov*, B. Gutkin, C. C Lapish, A. Kuznetsov. The influence of intrinsic and synaptic currents on the type of excitability of the dopamine neuron. PLoS computational biology, doi 10.1371/journal.pcbi.1005233, 8 December 2016. Read
- E. O. Morozova, M. Myroshnychenko, D. Zakharov, M di Volo, B. Gutkin, C. C Lapish, A. Kuznetsov. Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting. Journal of neurophysiology, doi 10.1152/jn.00232.2016, 20 July 2016. Read
- E. Morozova*, Y. Yoo*, M. V. Zaretskaia, D. E. Rusyniak, D. V. Zaretsky, Y. I. Molkov. Amphetamine enhances endurance by increasing heat dissipation. Physiological reports, doi: 10.14814/phy2.12955, Vol 4, issue 17, 11 August 2016. Read
- Grebenev I.V., Lozovskaya L. B., Morozova E.O. Methodology of determining student’s cognitive styles and its application for teaching physics. SpringerPlus, volume 3, issue 1, August 2014. Read
- Morozova E.O., Morozov O.A., Kazantsev V.B. Stimulation of signal transmission in the model of neurons interacting with an active transistor substrate. Radiophysics and Quantum Electronics, Vol. 55, No. 12 May 2013, pp 709-718. Read
- Morozova E.O., Ovchinnikov P.E., Semenova M.Yu. Neural network for monopulse radar signal processing. Vestnik of Lobachevsky state university of Nizhny Novgorod, No. 6(1), pp. 62-66, 2013. (in Russian)