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Kelley C, Antic SD, Carnevale NT, Kubie JL, Lytton WW. Simulations predict differing phase responses to excitation vs. inhibition in theta-resonant pyramidal neurons. J Neurophysiol 2023; 130:910-924. [PMID: 37609720 PMCID: PMC10648938 DOI: 10.1152/jn.00160.2023] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 08/21/2023] [Accepted: 08/21/2023] [Indexed: 08/24/2023] Open
Abstract
Rhythmic activity is ubiquitous in neural systems, with theta-resonant pyramidal neurons integrating rhythmic inputs in many cortical structures. Impedance analysis has been widely used to examine frequency-dependent responses of neuronal membranes to rhythmic inputs, but it assumes that the neuronal membrane is a linear system, requiring the use of small signals to stay in a near-linear regime. However, postsynaptic potentials are often large and trigger nonlinear mechanisms (voltage-gated ion channels). The goals of this work were to 1) develop an analysis method to evaluate membrane responses in this nonlinear domain and 2) explore phase relationships between rhythmic stimuli and subthreshold and spiking membrane potential (Vmemb) responses in models of theta-resonant pyramidal neurons. Responses in these output regimes were asymmetrical, with different phase shifts during hyperpolarizing and depolarizing half-cycles. Suprathreshold theta-rhythmic stimuli produced nonstationary Vmemb responses. Sinusoidal inputs produced "phase retreat": action potentials occurred progressively later in cycles of the input stimulus, resulting from adaptation. Sinusoidal current with increasing amplitude over cycles produced "phase advance": action potentials occurred progressively earlier. Phase retreat, phase advance, and subthreshold phase shifts were modulated by multiple ion channel conductances. Our results suggest differential responses of cortical neurons depending on the frequency of oscillatory input, which will play a role in neuronal responses to shifts in network state. We hypothesize that intrinsic cellular properties complement network properties and contribute to in vivo phase-shift phenomena such as phase precession, seen in place and grid cells, and phase roll, also observed in hippocampal CA1 neurons.NEW & NOTEWORTHY We augmented electrical impedance analysis to characterize phase shifts between large-amplitude current stimuli and nonlinear, asymmetric membrane potential responses. We predict different frequency-dependent phase shifts in response excitation vs. inhibition, as well as shifts in spike timing over multiple input cycles, in theta-resonant pyramidal neurons. We hypothesize that these effects contribute to navigation-related phenomena such as phase precession and phase roll. Our neuron-level hypothesis complements, rather than falsifies, prior network-level explanations of these phenomena.
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Affiliation(s)
- Craig Kelley
- Program in Biomedical Engineering, SUNY Downstate Health Sciences University and NYU Tandon School of Engineering, Brooklyn, New York, United States
| | - Srdjan D Antic
- Institute of Systems Genomics, Neuroscience Department, University of Connecticut Health, Farmington, Connecticut, United States
| | - Nicholas T Carnevale
- Department of Neuroscience, Yale University, New Haven, Connecticut, United States
| | - John L Kubie
- The Robert F. Furchgott Center for Neural and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, New York, United States
- Department of Cell Biology, SUNY Downstate Health Sciences University, Brooklyn, New York, United States
| | - William W Lytton
- Program in Biomedical Engineering, SUNY Downstate Health Sciences University and NYU Tandon School of Engineering, Brooklyn, New York, United States
- The Robert F. Furchgott Center for Neural and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, New York, United States
- Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, New York, United States
- Department of Neurology, SUNY Downstate Health Sciences University, Brooklyn, New York, United States
- Department of Neurology, Kings County Hospital Center, Brooklyn, New York, United States
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, Maryland, United States
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Dedola F, Severino FPU, Meneghetti N, Lemaire T, Cafarelli A, Ricotti L, Menciassi A, Cutrone A, Mazzoni A, Micera S. Ultrasound Stimulations Induce Prolonged Depolarization and Fast Action Potentials in Leech Neurons. IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY 2020; 1:23-32. [PMID: 35402964 PMCID: PMC8979621 DOI: 10.1109/ojemb.2019.2963474] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 12/19/2019] [Accepted: 12/20/2019] [Indexed: 11/10/2022] Open
Abstract
Objective: Ultrasound (US) stimulation carries the promise of a selective, reversible, and non-invasive modulation of neural activity without the need for genetic manipulation of neural structures. However, the mechanisms of US-induced generation of action potentials (APs) are still unclear. Methods: Here we address this issue by analyzing intracellularly recorded responses of leech nociceptive neurons to controlled delivery of US. Results: US induced a depolarization linearly accumulating in time and outlasting the duration of the stimulation. Spiking activity was reliably induced for an optimal US intensity range. Moreover, we found that APs induced by US differ in smaller amplitude and faster repolarization from those induced by electrical stimulation in the same cell but display the same repolarization rate. Conclusions: These results shed light on the mechanism by which spikes are induced by US and pave the way for designing more efficient US stimulation patterns.
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Affiliation(s)
- Francesca Dedola
- 1 The Biorobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
| | | | - Nicolo Meneghetti
- 1 The Biorobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
| | - Theo Lemaire
- 3 Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and Institute of BioengineeringSchool of Engineering, Ecole Polytechnique Federale de Lausanne Lausanne 1015 Switzerland
| | - Andrea Cafarelli
- 1 The Biorobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
| | - Leonardo Ricotti
- 1 The Biorobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
| | - Arianna Menciassi
- 1 The Biorobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
| | - Annarita Cutrone
- 1 The Biorobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
| | - Alberto Mazzoni
- 1 The Biorobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
| | - Silvestro Micera
- 4 BioRobotics InstituteScuola Superiore Sant'Anna Pisa 56025 Italy
- Department of Excellence in Robotics and AIScuola Superiore Sant'Anna Pisa 56025 Italy
- Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and Institute of BioengineeringSchool of Engineering, Ecole Polytechnique Federale de Lausanne Lausanne 1015 Switzerland
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