Structural and Functional Maturation of Rat Primary Motor Cortex Layer V Neurons

Abstract

Rodent neocortical neurons undergo prominent postnatal development and maturation. The process is associated with structural and functional maturation of the axon initial segment (AIS), the site of action potential initiation. In this regard, cell size and optimal AIS length are interconnected. In sensory cortices, developmental onset of sensory input and consequent changes in network activity cause phasic AIS plasticity that can also control functional output. In non-sensory cortices, network input driving phasic events should be less prominent. We, therefore, explored the relationship between postnatal functional maturation and AIS maturation in principal neurons of the primary motor cortex layer V (M1LV), a non-sensory area of the rat brain. We hypothesized that a rather continuous process of AIS maturation and elongation would reflect cell growth, accompanied by progressive refinement of functional output properties. We found that, in the first two postnatal weeks, cell growth prompted substantial decline of neuronal input resistance, such that older neurons needed larger input current to reach rheobase and fire action potentials. In the same period, we observed the most prominent AIS elongation and significant maturation of functional output properties. Alternating phases of AIS plasticity did not occur, and changes in functional output properties were largely justified by AIS elongation. From the third postnatal week up to five months of age, cell growth, AIS elongation, and functional output maturation were marginal. Thus, AIS maturation in M1LV is a continuous process that attunes the functional output of pyramidal neurons and associates with early postnatal development to counterbalance increasing electrical leakage due to cell growth.

Uncovering network mechanism underlying thalamic Deep Brain Stimulation using a novel firing rate model

“…In Figure 5 , we compared the model fitting results of two networks: (1) the typical Hebbian network with the lowest ρ inh,D shown in Figure 4C ; and (2) the typical BA network, which is the network with the optimal model parameters ( Figure 2 ). In the BA network, the model simulated firing rates ( r D , r E and r I , Figure 5C – E ) and the predicted time constants ( τ e and τ i , Equation 1 , table in Figure 2 ) are all within the appropriate physiological ranges consistent with anatomical literature and experimental data 9,51,52,53,55,39,64,56 . For the firing rate of the external excitatory nuclei ( r E ), during strong inputs, the bursting firing rate could be ∼200Hz for both cerebellar 64 and M1 Layer 5 nuclei 39 .…”

“…In the experimental recordings from mice, the regular firing rate of cerebellum dentate nucleus ranged from 10 to 80Hz 52,54 . For M1 Layer 5 and 6 neurons in mice, the firing rate ranged from 10 to 60Hz 53,55 . Thus, we constrained r E,b in [10,70]Hz, and initialize it at r E,b ,0 = 40Hz.…”

“…The undetermined parameter set to be optimized was Φ = { w ee , w ie , w ei , w ii , τ i , τ e , r E,b , c, s, k } ( Equation 1 ). The route optimization process started with a set of initial parameters Φ ini = { w ee ,0 , w ie ,0 , w ei ,0 , w ii ,0 , τ i ,0 , τ e ,0 , r E,b ,0 , c 0 , s 0 , k 0 } ( Table S4 ), which were determined as follows: (i) The initial connectivity strength parameters ({ w ee ,0 , w ie ,0 , w ei ,0 , w ii ,0 }) were all set to be 1; (ii) { τ i ,0 , τ e ,0 , r E,b ,0 } were from the anatomical and experimental literature 103,9,52,54,53,104 (iii) { c 0 , s 0 , k 0 } were from fitting the reference firing rate with our previous single-ensemble model of the Vim neural group receiving DBS 22 . Starting from the initial parameter set Φ ini , we did a preliminary model fit based on Stabilized Feature (i.e., stressing data from both low and high frequencies of DBS), and the weight of each DBS frequency was given by the vector g pre ( Equation 10, Table S3 ).…”

“…We chose 𝑟 𝐷,0 = 25Hz to be consistent with the human Vim experimental recordings in our previous work Milosevic et al (2021) 9 , and 𝑟 𝐼,0 = 5Hz to be consistent with the experimental data recorded in both TRN (human) 9 and thalamic interneurons (mice) 51 . Since the external excitatory nuclei (group " 𝐸 ") are originated from multiple sources with highly variable firing rates 52,53 , the corresponding baseline firing rate (𝑟 𝐸,𝑏 ) is left as an unknown variable (Equation 1). In the experimental recordings from mice, the regular firing rate of cerebellum dentate nucleus ranged from 10 to 80Hz 52,54 .…”

The awakening of dormant neuronal precursors in the adult and aged brain

“…Hyperpolarizing steps started at −20 pA, adding 5 pA to each consecutive step, until rheobase was reached. To determine the relationship between input current and action potential frequency, larger steps were used (20 pA), starting at −20 pA, and up to 250–300 pA. During inter‐step intervals, the membrane was kept at resting potential for 500 ms. During the inter‐step interval, the membrane was kept at resting potential for 500 ms. Series resistance ( R s ), input resistance ( R in ), and cell capacitance ( C M ) were derived from currents elicited by 50 ms voltage pulses as described in previous work (Benedetti et al, 2020 ). Postsynaptic current (PSC) frequency and amplitude were determined with voltage‐clamp experiments, using a holding potential of −70 mV.…”