Membrane electrical properties of mouse hippocampal CA1 pyramidal neurons during strong inputs

Bianchi, Daniela; Migliore, Rosanna; Vitale, Paola; Garad, Machhindra; Pousinha, Paula A.; Marie, Hélène; Leßmann, Volkmar; Migliore, Michele

doi:10.1016/j.bpj.2022.01.002

Cited by 5 publications

(5 citation statements)

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“…DBLO kicks in whenever the postsynaptic cell is firing briskly such as in bursts (Moore et al, 2009). (Bianchi et al, 2022) showed in their computational study that low DBLO models attenuated theta range synaptic activity while high DBLO models amplified gamma range synaptic activity. The presence of a high baseline can more than double the effective weight of a typical GABA-ergic synapse due to the increase in driving force.…”

Section: Discussionmentioning

confidence: 99%

“…As we analyze below, several models of CA1 pyramidal neurons on ModelDB do not show the experimentally expected level of DBLO upon current clamp. Recently, Bianchi et al, 2019 addressed this issue and suggested that the high Depolarization Baseline may be due to an injection-current dependent shift in reversal potential on ion channels as well as their kinetics (Bianchi et al, 2022). The mechanistic basis for such a proposed current-dependent shift is uncertain.…”

Section: Introductionmentioning

confidence: 99%

“…in understanding back propagating action potentials (M. Migliore et al, 1999) and calcium spikes (Miyasho et al, 2001), some key details have remained understudied. One such detail is the high Depolarization BaseLine Offset (DBLO) seen in somatic recordings when long pulses of current are injected into a neuron (Bianchi et al, 2022). High DBLO can be seen in current clamp recordings of almost all pyramidal neuron subtypes: hippocampal CA1 (Dwivedi et al, 2019), CA3 (Hunt et al, 2018), cortical L2/3 (Moradi Chameh et al, 2021) and L5 (Kim et al, 2015; Moberg & Takahashi, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Mechanisms and implications of high depolarization baseline offsets in conductance-based neuronal models

Kumar,

Shahul,

Bhalla

2024

Preprint

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Somatic current-step injection is a routinely used protocol to characterize neurons and measure their electrophysiological properties. A signature feature of the responses of many neuronal types is an elevated baseline of action potential firing from the resting membrane potential, the depolarization baseline level offset (DBLO). We find that four key factors together account for high DBLO: Liquid Junction Potential correction, subthreshold impedance amplitude profile, fast potassium delayed rectifier kinetics, and appropriate transient sodium current kinetics. We show that simple mechanisms for DBLO, such as Ohmic depolarization due to current input, fail to explain the effect, and many sophisticated conductance-based models also do not correctly manifest DBLO. Neither low pass filtering effect of membrane nor high reversal potential of potassium channels are able to explain high DBLO. Using stochastic parameter search in conductance-based models of CA1 pyramidal neurons, we explore cellular morphology configurations and channel kinetics. Multi-compartment models which matched experimental subthreshold impedance amplitude profiles had higher DBLO than single compartment models. DBLO was further increased in models that exhibited rapid deactivation time-constants in the dominant potassium conductance. We also saw that certain transient sodium current kinetics resulted in higher DBLO than others. We emphasize that correct expression of DBLO in conductance-based models is important to make quantitative predictions about the levels of ion channels in a neuron and also to correctly predict mechanisms underlying cellular function, such as the role of persistent sodium in imparting firing bistability to a neuron.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mechanisms and implications of high depolarization baseline offsets in conductance-based neuronal models

Kumar,

Shahul,

Bhalla

2024

Preprint

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“…This leads to a spike (amplitude ≈80 mV, duration ≈2 ms) when it surpasses the threshold (≈−40 mV). In response to the inhibitory input current pulse, the membrane potential decreases from its resting potential (≈−70 mV) [14]. A spike can also occur following the cessation of a potent, long-lasting hyperpolarizing input [15].…”

Section: Introductionmentioning

confidence: 99%

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation

Hore,

Bandyopadhyay,

Chakrabarti

2024

J. Neural Eng.

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Objective. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIRE) phenomenon into a neuronal circuit. Excitatory and inhibitory synapses are designed to establish a connection between two hardware neurons, effectively forming a network. The model demonstrates the occurrence of PIRE under strong inhibitory input. Emphasizing the significance of incorporating PIRE in neuromorphic circuits, the study showcases generation of persistent activity within cyclic and recurrent spiking neuronal networks. Approach. The neuronal and synaptic circuits are designed and simulated in Cadence Virtuoso using TSMC 180 nm technology. The operating mechanism of the PIRE phenomenon integrated into a hardware neuron is discussed. The proposed circuit encompasses several parameters for effectively controlling multiple electrophysiological features of a neuron. Main results. The neuronal circuit has been tuned to match the response of a biological neuron. The efficiency of this circuit is evaluated by computing the average power dissipation and energy consumption per spike through simulation. The sustained firing of neural spikes is observed till 1.7 s using the two neuronal networks. Significance. Persistent activity has significant implications for various cognitive functions such as working memory, decision-making, and attention. Therefore, hardware implementation of these functions will require our PIRE-integrated model. Energy-efficient neuromorphic systems are useful in many artificial intelligence applications, including human-machine interaction, IoT devices, autonomous systems, and brain-computer interfaces.

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“…A neuron generates a spike (height ≈ 80 mV and width ≈ 2 ms) of its own when the membrane potential crosses a spiking threshold (≈ -40 mV). When a neuron receives inhibitory input spikes hyperpolarization occurs and membrane potential decreases from its resting potential [12]. Responses of various biological cells for known input current stimuli are provided in the Allen Institute of Brain Science (AIBS) dataset [13].…”

Section: Introductionmentioning

confidence: 99%

CMOS Spiking Neuron Incorporating Post-Inhibitory Rebound Excitation

Hore¹,

Bandyopadhyay²,

Chakrabarti³

2023

Preprint

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<p> This work shows the simulation of a CMOS spiking neuron model that can mimic the behaviour of a biological neuron for both hyperpolarizing and depolarizing currents. The proposed schematic design can exhibit the post-inhibitory rebound excitation (PIRE) or anode break excitation (ABE) phenomena. The model has multiple control parameters for regulating the operation of a neuron. It is shown that the electrophysiological properties of a neuron, such as spiking frequency, spike height, resting potential, and mean inter-spike interval, can be varied by adjusting two control parameters of the developed schematic. Schematic of excitatory and inhibitory synapses to link two neuronal models are designed using CMOS. Average power dissipation and energy consumed per spike of the schematic designs are examined. Furthermore, PIRE is demonstrated for a strong inhibitory synaptic current. The significance of including PIRE in such a neuronal model is shown by its necessity in the generation of persistent activity in the network, which mimics the realization of working memory or attention. A network of such neuronal designs with the appropriate realization of the synaptic region has implications for human-to-machine interfaces and pattern recognition problems </p>

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Membrane electrical properties of mouse hippocampal CA1 pyramidal neurons during strong inputs

Cited by 5 publications

References 50 publications

Mechanisms and implications of high depolarization baseline offsets in conductance-based neuronal models

Mechanisms and implications of high depolarization baseline offsets in conductance-based neuronal models

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation

CMOS Spiking Neuron Incorporating Post-Inhibitory Rebound Excitation

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