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Review

Neuronal Plasticity and Age-Related Functional Decline in the Motor Cortex

by
Ritsuko Inoue
1 and
Hiroshi Nishimune
1,2,*
1
Laboratory of Neurobiology of Aging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo 173-0015, Japan
2
Department of Applied Biological Science, Tokyo University of Agriculture and Technology, 3-8-1 Harumicho, Fuchu-shi, Tokyo 183-8538, Japan
*
Author to whom correspondence should be addressed.
Cells 2023, 12(17), 2142; https://doi.org/10.3390/cells12172142
Submission received: 16 July 2023 / Revised: 16 August 2023 / Accepted: 23 August 2023 / Published: 25 August 2023
(This article belongs to the Special Issue Cellular Plasticity of the Neuromuscular System)
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Abstract

:
Physiological aging causes a decline of motor function due to impairment of motor cortex function, losses of motor neurons and neuromuscular junctions, sarcopenia, and frailty. There is increasing evidence suggesting that the changes in motor function start earlier in the middle-aged stage. The mechanism underlining the middle-aged decline in motor function seems to relate to the central nervous system rather than the peripheral neuromuscular system. The motor cortex is one of the responsible central nervous systems for coordinating and learning motor functions. The neuronal circuits in the motor cortex show plasticity in response to motor learning, including LTP. This motor cortex plasticity seems important for the intervention method mechanisms that revert the age-related decline of motor function. This review will focus on recent findings on the role of plasticity in the motor cortex for motor function and age-related changes. The review will also introduce our recent identification of an age-related decline of neuronal activity in the primary motor cortex of middle-aged mice using electrophysiological recordings of brain slices.

Graphical Abstract

1. Introduction

Voluntary activation of skeletal muscle tends to weaken with age, particularly in the elderly with sarcopenia or frailty [1,2]. Physiological aging causes a decline of motor function due to losses of muscle mass and strength, denervation of neuromuscular junctions (NMJs), a loss of motor neurons in the spinal cord, and impairment of motor cortex function. Losses of muscle mass and strength (sarcopenia) are more pronounced in the elderly [3,4,5,6,7]. Meanwhile, a decline in motor function has been reported in studies of middle-aged humans and rodents. Middle-aged healthy subjects (between the late 40s and late 50s) changed their kinetic characteristics of gait during walking and running [8]. The age-related decline of motor function has been reported in middle-aged rodents (between approximately 13 months and 19 months old) using behavioral tests that assess balance and motor coordination or gait [9,10,11]. These data suggest that a decline in motor function in rodents starts much earlier than a decline in survival rates, which is typically around 24 months old. In addition, the mechanism of motor function decline during the middle-aged stage seems different from that during the advanced-aged stage. This difference is suggested because NMJ denervation, motor neuron loss, and muscle atrophy are detected in the advanced-age stage, but NMJ denervation is not detected significantly in middle-aged mice at or earlier than 18 months old [12,13]. The preservation of NMJs suggests that the spinal motor neurons are maintained in middle-aged mice. Furthermore, a decline in muscle contractility is less severe in mice under 20 months old [14].
In the motor cortex, physiological aging also causes cortical atrophy, alteration of excitability, and decreased neurotransmitter levels (Figure 1) [15,16]. Notably, age-related alteration of excitability in the motor cortex has been linked to motor function decline in humans and animals. In the human motor cortex, physiological aging alters the balance of excitatory and inhibitory circuits [17,18]. Middle-aged and elderly individuals (between the late 50s and early 70s) have exhibited more intracortical inhibition and less intracortical facilitation in the motor cortex than young adults. The hypoexcitability in the motor cortex correlates with behavioral impairments in chronic obstructive pulmonary disease (COPD) and amyotrophic lateral sclerosis (ALS) patients [19,20]. Therefore, alteration of motor cortex function may be part of the underlying mechanism for the age-related decline of motor function, especially in the middle-aged stage.
Physiological aging alters synaptic plasticity. In rat hippocampal slices, NMDA receptor-dependent long-term potentiation (LTP) decreases with age [21,22]. Meanwhile, neuronal plasticity enhancers have been shown to accelerate the rehabilitation-like effect that improves motor function [23,24]. Rehabilitation training restores motor function after stroke and nervous system damage. Therefore, neuronal plasticity seems to play a role in the maintenance and/or improvement of motor function. However, there has been less focus on the role of synaptic plasticity in the study of age-related decline of motor cortex function. This review highlights recent articles reporting age-related alterations of neuronal activity and synaptic plasticity efficiency in the motor cortex, which may cause a decline in motor function. We will discuss potential intervention methods by supplementing brain substances that decrease with age. These endogenous substances can directly or indirectly enhance LTP and may ameliorate the age-related alterations of motor cortex function.

2. Motor Cortex

2.1. Pathway

The motor cortex is the center of cortical control of voluntary movements [25,26]. The functional involvement of motor cortex networks in motor control has long been studied mainly by microstimulation of the rodent motor cortex [27,28]. Recently, high-precision stimulation techniques using scanning laser light stimulation and optogenetics have revealed intralaminar excitatory connections in the motor cortex [29,30,31]. These cell-selective stimulation experiments demonstrate that the excitatory connection from layers II/III to V is the major intralaminar connection in the motor cortex [29,32,33,34]. Layer V of the motor cortex contains pyramidal neurons that are projection neurons [35]. Corticospinal and cortico-brainstem projection neurons are located in the deeper layer, layer Vb. Approximately 60% of total corticospinal projections originate from the primary motor cortex (M1) in humans [35,36].

2.2. Plasticity in the Motor Cortex

2.2.1. Synaptic Plasticity and Motor Learning

The motor cortex plays an essential role in motor learning [37]. Neuronal plasticity in the motor cortex during and after motor learning has been studied in humans and animals (Table 1) [38,39,40,41,42,43]. A rotor rod task induces glutamatergic or GABAergic synaptic plasticity in layer V pyramidal neurons of the rat primary motor cortex [41]. Motor learning in mice or stimulation of brain slices using electrodes can induce LTP in the motor cortex [39,40,44,45,46,47,48]. Changes in motor cortex excitability have a functional relationship with LTP. After LTP expression, field excitatory postsynaptic potential (fEPSP) shows enhanced amplitudes in the motor cortex [42,49,50]. A pellet-reaching task with one forelimb of rats increases the fEPSP amplitude of layer II/III horizontal connections in the brain slices of the trained side of the primary motor cortex [6,44]. When an LTP induction method has been applied to these slices, the amount of LTP induced in the trained contralateral side of the primary motor cortex has been less than that in the untrained ipsilateral side of the primary motor cortex in the same slice. This difference has been assumed that the trained side of the primary motor cortex had fewer LTP induction trials to reach LTP saturation, at which point LTP was no longer induced, than the untrained side of the primary motor cortex. Even under LTP saturation, LTP could be induced again if long-term depression (LTD) was induced by electrical stimulation in the motor cortex of the rat slice [42]. Similarly, the temporal occlusion of LTP in the human motor cortex is necessary to retain motor learning according to transcranial magnetic stimulation experiments [38,51,52,53]. Consequently, these studies in animals and humans have revealed that the mechanism of motor learning involves induction and occlusion of LTP.
Furthermore, the amount of LTP in the motor cortex is related to the success rate of motor learning. Several brain substances have been reported to affect the amount of LTP in the motor cortex. Impairment of dopaminergic signaling reduces the amount of LTP in layer II/III in the rat primary motor cortex, resulting in lower skill acquisition rates [55,59,63]. Blockade of Nogo-A, an inhibitor of axonal outgrowth and regeneration in the brain, enhances the amount of LTP in layer II/III in the rat primary motor cortex and improves motor learning [58]. These recent studies have shown that modulating neuronal plasticity in the motor cortex may alter motor learning performance.

2.2.2. Cortical Plasticity Induced by Non-Invasive Stimulation

Cortical plasticity in the motor cortex has been suggested in studies of motor function in healthy subjects [64,65], motor deficits in Parkinson’s disease [59,66,67], and rehabilitation after brain damage [24,68]. These studies indicate that the induction of cortical plasticity in the motor cortex could be beneficial for motor function. Cortical plasticity can be induced by non-invasive brain stimulation techniques like transcranial magnetic stimulation and transcranial direct current stimulation (tDCS) [69]. These non-invasive brain stimulation through the scalp to the motor cortex induces motor evoked potentials (MEPs), which are recorded from the muscles. Generally, human cortical plasticity in the motor cortex has been monitored by changes in the amplitude of peripherally recorded MEPs [64] because it is currently difficult to directly measure long-term changes in excitability in the human motor cortex. Importantly, tDCS has been suggested to directly induce synaptic plasticity based on studies using cortical slices of rodents [49,70,71]. When tDCS electrodes were used to stimulate brain slices, the stimulation-induced NMDA receptor-dependent synaptic potentiation in layer II/III of the mouse primary motor cortex in brain slices [50]. The brain slices of tDCS-treated mice showed LTP enhancement at layer II/III horizontal connections of the primary motor cortex [49].

2.2.3. Structural Plasticity and Motor Learning

In addition, neurons in the motor cortex show structural plasticity concurrently to the LTP induced by motor learning or experimental induction methods. In the motor cortex of rats, spine dynamics differ in a laminar structure and cell-dependent manner [54,61]. Interestingly, motor learning causes the stabilization of new dendritic spines [56,57,72]. Furthermore, new dendritic branches and increased dendritic length have been observed among layer V pyramidal neurons of rats that learned a pellet-reaching task. After completing these motor tasks, the degree of these dendritic changes peaks in one month in the motor cortex, after which these newly formed dendrites are pruned [60].

3. Aging in the Motor Cortex

3.1. Structural and Functional Alteration in the Motor Cortex

Physiological aging induces changes in the human motor cortex, including cortical atrophy, impaired excitability, and decreased neurotransmitter levels [15,16,73,74]. Generally, cortical atrophy in physiological aging is considered to be due to structural changes in individual neurons, such as shrinkage in the soma size, a reduction in the dendrite arborization complexity and length, and a loss or regression of dendritic spines but not a decrease in cell number [75]. These age-related structural changes occur in parallel with alterations in the electrophysiological properties of neurons. In the aged primate prefrontal cortex, single action potential amplitude and fall time significantly decrease in layer II/III and layer V pyramidal neurons [76,77,78]. Furthermore, action potential firing rates in layer II/III increase with age and are related to cognitive function. Subjects with intermediate firing rates demonstrate higher performance in delayed non-match to sample (DNMS) basic learning, DNMS performance at 2 min delays, and the delayed recognition span task compared to subjects with low or very high firing rates [76,79]. Age-related alterations in the electrophysiological properties impair the excitability of neural networks at the cellular level in the cortex [80].
In the motor cortex, age-related structural changes in dendritic spines occur prior to neuronal cell death. Repeated in vivo imaging of the same dendrites has revealed that dendritic spine density increases and long-term spine survival decreases in layer V pyramidal neurons of aged mice (20 to 22 months old) compared to young mice (3 to 4 months old) [81].
According to young-adult rodent studies, the excitability of layer V in the motor cortex plays an important role in motor function. Layer V pyramidal neurons in the motor cortex control the rhythm of whisker movements [82]. Interestingly, enhancing the activity of layer V neurons in the motor cortex improves bradykinesia and hypokinesia in Parkinson’s disease model mice [31]. Human studies have demonstrated the age-related decline in motor cortex excitability by measuring peripheral neural activity that indirectly represents motor cortex activity [73,83]. However, age-related changes in motor cortex activity have not been recorded directly in humans or animals. Importantly, we have discovered an age-related decline in field excitatory postsynaptic potential (fEPSP) amplitude in the pathway from layers II/III to V of the primary motor cortex of middle-aged mice (15 to 18 months old) for the first time to the best of our knowledge [50]. These middle-aged mice performed slower on the pole test than younger mice (6 months old) [10,50]. Therefore, layer V neuronal activity may be a valuable target for examining the relationship between motor cortex excitability and age-related motor function decline.

3.2. Aging and Cortical Plasticity in the Motor Cortex

Age-related alteration of plasticity in the motor cortex is related to age-related reduction in motor function. As mentioned above, middle-aged mice show behavior impairment in the pole test compared to younger mice [10,50]. These mice show age-related alteration of neuronal plasticity in the pathway from layers II/III to V of the primary motor cortex, which will be described in detail in section four [50]. Aged mice (18 to 20 months old) could learn the pasta matrix reaching tasks as the young mice (3 to 5 months old). However, the brain mapping study using intracortical microstimulation of layer V in the motor cortex has revealed age-related alteration in the motor map plasticity after the reaching task [84]. In humans, magnetoencephalography and functional magnetic resonance imaging (fMRI) studies have shown age-related alteration of plasticity in the motor cortex by measuring movement-related beta desynchronization during motor execution in the elderly [85]. These studies about motor learning and motor function have shown that cortical plasticity in the motor cortex differs between young and older animals.

3.3. Aging and Mitochondria in the Motor Cortex

It is essential to maintain adequate mitochondrial activity for producing ATP to meet the high energy requirements of neurons. ATP production correlates highly with the complex I activity in mitochondrial oxidative phosphorylation. The non-synaptic and synaptic mitochondria in the brain have different ATP production efficiency. In non-synaptic mitochondria of the brain, ATP production is not affected until the complex I activity is reduced by 72% [86]. However, ATP production is significantly reduced when the complex I activity of synaptic mitochondria of the brain is reduced by 25% [87]. These findings suggest that ATP production at cortical synapses seems sensitive to modest dysfunction of mitochondria. Interestingly, mitochondrial activity is significantly impaired in synaptic mitochondria but not in non-synaptic mitochondria during physiological aging in middle-aged rodents (14 or 17 months old) [88,89].
Mitochondria affect synaptic activities, including age-related synaptic plasticity [90,91]. In the mouse brain, the complex I activity in mitochondrial oxidative phosphorylation decreases with age [10,92]. We have discovered age-related alteration of synaptic plasticity efficiency in the primary motor cortex in middle-aged mice. LTP in the primary motor cortex in middle-aged mice has been enhanced by high-frequency stimulation combined with the administration of the mitochondrial coenzyme, coenzyme Q10 (CoQ10), which declines with age [50]. However, the same stimulation with CoQ10 administration does not affect LTP in the primary motor cortex of young-adult mice [50]. These studies suggest that mitochondrial dysfunction results from brain aging [93] and is part of the mechanisms that alter neuronal plasticity in the motor cortex.

4. Interventions for Age-Related Declines of Motor Function

Age-related declines in motor function may be caused partly by mitochondrial dysfunction. Physiological aging is known to cause mitochondrial dysfunction in skeletal muscles and NMJs of humans and animals. The mitochondria of human skeletal muscle are altered by physiological aging resulting in decreased enzyme activity, maximal respiration capacity, and total protein amount [94,95]. The NMJs of aged rats have megamitochondria, which is thought to be generated by age-related mitochondrial fusion [96,97]. A relationship between the mitochondria function and the motor function has been shown in exercise intervention studies, which activates mitochondrial biogenesis and improves muscle performance in humans and rodents [98].
Similarly, studies have reported correlations between age-related declines in brain mitochondrial function and motor function. The basal ganglia of aged monkeys have significantly reduced ATP production, pyruvate dehydrogenase activity, and calcium buffering capacity compared to younger animals. These reductions correlate with age-related decline in locomotor activity and movement speed [99]. Takahashi et al. have shown reductions in brain mitochondrial respiratory capacity, coenzyme Q (CoQ) content, and motor function in middle-aged mice compared to young mice [10]. CoQ is an essential mitochondrial coenzyme for ATP production [100,101,102]. Electrons are transported from complexes I and II to complex III by coenzyme Q10 in humans and coenzyme Q9 and Q10 in mice for ATP production [103,104,105]. However, CoQ levels decline with aging in the brain, blood, and other organs. The symptom onset of aging, CoQ10 deficiency, multiple-system atrophy, and Parkinson’s disease have been alleviated and/or delayed by CoQ10 supplementation in humans [106,107,108].
CoQ is a fat-soluble substance whose bioavailability varies between formulations [109,110,111]. Optimal concentrations and effective administration periods differ depending on the CoQ10 formulation supplemented. In a Parkinson’s disease model mouse, an intervention utilizing CoQ10 nano micelles with enhanced brain penetration capability has shown neuroprotection and improved motor function [112]. Another water-soluble nanoformula-type CoQ10 supplementation by drinking water has improved complex I activity in brain mitochondria, CoQ contents in the brain, and motor function in middle-aged mice [10,92]. We have discovered that CoQ10 supplementation by drinking water also improves the age-related decline of fEPSP amplitude in the pathway from layers II/III to V of the primary motor cortex of middle-aged mice. In addition, CoQ10 administration combined with high-frequency stimulation induces age-dependent LTP and enhances the basal fEPSP amplitude level in brain slices of the primary motor cortex. This LTP induction is age, CoQ10, and NMDA receptor-dependent [50]. Layer V of the motor cortex was thought to be a region unlikely to induce LTP compared to layer II/III of the motor cortex based on brain slice experiments [54]. However, layer V neurons in the primary motor cortex show dynamic alteration of synaptic plasticity after motor learning [41]. Stimulation of superficial layers of the motor cortex using a concentric bipolar electrode induces LTP in layer V pyramidal neurons in the M1 forelimb area [59]. Our data suggest that LTP could be induced in layer V neurons of the primary motor cortex in slice preparation under certain conditions. The CoQ10-dependent enhancement of NMDA receptor components in our study may be similar to the ability of growth hormone to reverse the age-related decrease in NMDA receptor function in basal excitatory transmission. This is because chronic growth hormone treatment restores NMDA receptor-dependent basal neuronal activity in aged rat hippocampus [113]. The LTP or related neuronal plasticity mechanism in vivo during CoQ10 supplementation may have boosted neuronal activity in the primary motor cortex and improved the motor function of middle-aged mice [50]. These findings indicate that restoration of mitochondrial function enhances neuronal activity and improves motor function, at least in middle-aged mice.
In addition, studies have reported correlations between CoQ10 and neurotrophin, brain-derived neurotrophic factor (BDNF). Rats exposed to chronic unpredictable mild stress or toxic propionic acid show a decline in BDNF protein levels. CoQ10 treatment in these rats results in a modest increase in BDNF protein [114,115]. BDNF is associated with synaptic plasticity in the hippocampus [116]. In the motor cortex, layer II/III and V neurons express BDNF protein. Running wheel exercise increases the number of BDNF-expressing pyramidal neurons in layer II/III and the expression level of BDNF protein in the mice motor cortex. However, reduced BDNF protein levels in conditional BDNF knockout mice impair motor learning [117], suggesting that BDNF protein is required in the motor cortex during motor learning. Fritsch et al. have suggested that direct current stimulation combined with repetitive low-frequency stimulation increases activity-dependent BDNF secretion and improves motor learning by enhancing NMDA receptor-dependent LTP at layer II/III in the primary motor cortex of mice [70]. These results are consistent with the study demonstrating that BDNF secretion modifies neuronal plasticity in an activity-dependent manner in the hippocampus [118]. Based on these results, intervention methods to improve motor function and learning via the effects of BDNF have been investigated in combination with stimuli such as exercise and tDCS [70,119,120]. The correlation between the amount of activity-dependent BDNF secretion and motor learning has been examined using BDNF valine-methionine substitution (Val66Met) polymorphism. The Val66Met polymorphism is a single nucleotide polymorphism in the BDNF gene related to episodic memory in humans and the activity-dependent secretion of BDNF [121,122]. The Val66Met substitution decreases activity-dependent secretion of BDNF in cultured rat hippocampal neurons [121]. Healthy subjects (mean age 22.7 ± 1.4 years) with the Met allele show reduced motor evoked potentials (MEPs) and brain motor map area changes with training using right index fingers compared to subjects without the polymorphism [123]. In both humans and mice, direct current stimulation enhances motor skill acquisition rates in Val/Val subjects without the polymorphism but not in Met allele carriers [70].
The BDNF mRNA expression level declines with age in the human prefrontal cortex [124] and the monkey motor cortex [125]. BDNF protein levels have affected motor function in the mice lacking one BDNF allele. These BDNF heterozygous mice at the middle-aged (11 to 13 months old) and the aged (19 to 21 months old) stages walk slower on a horizontal beam than age-matched wild-type mice. BDNF protein levels in the striatum of aged BDNF heterozygous mice are 15% lower compared to aged wild-type mice [126]. The relationship between age-related decline in BDNF levels and motor function in the elderly is not yet well understood. The serum BDNF level correlates positively with the eigenvector centrality obtained from resting-state fMRI data in the premotor and motor cortex of the elderly [127]. The eigenvector centrality analyzes connectivity patterns of the human brain in fMRI data [128]. Although the Val66Met polymorphism affects motor performance in young people, this effect is not well understood in the elderly. Healthy elderly subjects (mean age 73.2 ± 1.8 years) show slower reaction time speed, a larger baseline of brain motor map area, and smaller MEP amplitude compared to young subjects (mean age 24.3 ± 1.1 years) [129]. Among these healthy elderly subjects, the polymorphism difference between BDNF Val/Val and Val66Met has not affected reaction time speed, the motor tasks using hands or fingers, driving test of cognitive/motor learning, and change in MEPs with 30 min exercise [129]. The difference between these and the aforementioned results may imply that compensation for the long-term impacts of BDNF polymorphisms may have occurred. Some studies suggest that interventions reverting BDNF levels in the motor cortex might prevent the age-related decline in motor function. However, it is still debatable whether such intervention is truly beneficial [117,119,126,127].
Utilizing neuronal plasticity in the motor cortex to improve impaired brain function has been a research topic recently (Table 2). Some neuronal plasticity enhancers have improved motor learning in rodent studies [23,58]. The membrane protein Nogo-A and its receptor (NgR1) are expressed in layer II/III and V pyramidal neurons in the motor cortex. Functional blocking antibodies against Nogo-A or NgR1 enhance LTP in the layer II/III primary motor cortex and increase spine formation in vivo in the layer V neurons. Anti-Nogo-A antibody treatment using an osmotic minipump has improved the success rate in the pellet-reaching task of rats [58]. Meanwhile, a small compound edonerpic maleate facilitates synaptic delivery of AMPA receptors, enhances mEPSC amplitudes, and enhances LTP in layer II/III pyramidal neurons of the barrel cortex. This effect is abolished in the absence of whiskers, indicating that the effects of ednerpic maleate are exerted in an experience-dependent manner. The combination of edonerpic maleate administration and rehabilitative training has accelerated the success rate in the pellet-reaching task of the mice with cortex cryoinjury [23].

5. Conclusions

Many unanswered questions remain about the relationship between age-related alteration of synaptic plasticity and motor function decline in the motor cortex. Nevertheless, evidence from rehabilitation and other studies suggests that enhancing motor function by modulating synaptic plasticity can be an effective intervention for humans. The use of brain substances that decrease with age is an important aspect of developing preventive methods against age-related motor decline.

Author Contributions

R.I. and H.N. contributed to the conception and writing of this manuscript. Both authors contributed to the article and approved the submitted version. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from the Japan Society for the Promotion of Science (19K11407 and 22K11306 for R.I. and 19K24690 for H.N.).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We thank Michael Deschenes for the invitation to the special issue of Cells. We also thank Masami Miura for his valuable comments on the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Clark, B.C.; Taylor, J.L. Age-related changes in motor cortical properties and voluntary activation of skeletal muscle. Curr. Aging Sci. 2011, 4, 192–199. [Google Scholar] [CrossRef]
  2. Tieland, M.; Trouwborst, I.; Clark, B.C. Skeletal muscle performance and ageing. J. Cachexia Sarcopenia Muscle 2018, 9, 3–19. [Google Scholar] [CrossRef]
  3. Clark, B.C. Neuromuscular Changes with Aging and Sarcopenia. J. Frailty Aging 2019, 8, 7–9. [Google Scholar] [CrossRef] [PubMed]
  4. Gonzalez-Freire, M.; de Cabo, R.; Studenski, S.A.; Ferrucci, L. The Neuromuscular Junction: Aging at the Crossroad between Nerves and Muscle. Front. Aging Neurosci. 2014, 6, 208. [Google Scholar] [CrossRef] [PubMed]
  5. Manini, T.M.; Hong, S.L.; Clark, B.C. Aging and muscle: A neuron’s perspective. Curr. Opin. Clin. Nutr. Metab. Care 2013, 16, 21–26. [Google Scholar] [CrossRef] [PubMed]
  6. Roubenoff, R. Sarcopenia and its implications for the elderly. Eur. J. Clin. Nutr. 2000, 54 (Suppl. S3), S40–S47. [Google Scholar] [CrossRef] [PubMed]
  7. Willadt, S.; Nash, M.; Slater, C. Age-related changes in the structure and function of mammalian neuromuscular junctions. Ann. N. Y. Acad. Sci. 2018, 1412, 41–53. [Google Scholar] [CrossRef]
  8. Jin, L.; Hahn, M.E. Comparison of lower extremity joint mechanics between healthy active young and middle age people in walking and running gait. Sci. Rep. 2019, 9, 5568. [Google Scholar] [CrossRef]
  9. Yurek, D.M.; Hipkens, S.B.; Hebert, M.A.; Gash, D.M.; Gerhardt, G.A. Age-related decline in striatal dopamine release and motoric function in brown Norway/Fischer 344 hybrid rats. Brain Res. 1998, 791, 246–256. [Google Scholar] [CrossRef]
  10. Takahashi, K.; Ohsawa, I.; Shirasawa, T.; Takahashi, M. Early-onset motor impairment and increased accumulation of phosphorylated alpha-synuclein in the motor cortex of normal aging mice are ameliorated by coenzyme Q. Exp. Gerontol. 2016, 81, 65–75. [Google Scholar] [CrossRef]
  11. Broom, L.; Stephen, J.; Nayar, V.; VanderHorst, V.G. Shifts in Gait Signatures Mark the End of Lifespan in Mice, with Sex Differences in Timing. Front. Aging Neurosci. 2021, 13, 716993. [Google Scholar] [CrossRef] [PubMed]
  12. Valdez, G.; Tapia, J.C.; Kang, H.; Clemenson, G.D., Jr.; Gage, F.H.; Lichtman, J.W.; Sanes, J.R. Attenuation of age-related changes in mouse neuromuscular synapses by caloric restriction and exercise. Proc. Natl. Acad. Sci. USA 2010, 107, 14863–14868. [Google Scholar] [CrossRef]
  13. Sheth, K.A.; Iyer, C.C.; Wier, C.G.; Crum, A.E.; Bratasz, A.; Kolb, S.J.; Clark, B.C.; Burghes, A.H.M.; Arnold, W.D. Muscle strength and size are associated with motor unit connectivity in aged mice. Neurobiol. Aging 2018, 67, 128–136. [Google Scholar] [CrossRef]
  14. Chugh, D.; Iyer, C.C.; Wang, X.; Bobbili, P.; Rich, M.M.; Arnold, W.D. Neuromuscular junction transmission failure is a late phenotype in aging mice. Neurobiol. Aging 2020, 86, 182–190. [Google Scholar] [CrossRef]
  15. Seidler, R.D.; Bernard, J.A.; Burutolu, T.B.; Fling, B.W.; Gordon, M.T.; Gwin, J.T.; Kwak, Y.; Lipps, D.B. Motor control and aging: Links to age-related brain structural, functional, and biochemical effects. Neurosci. Biobehav. Rev. 2010, 34, 721–733. [Google Scholar] [CrossRef] [PubMed]
  16. Cassady, K.; Gagnon, H.; Lalwani, P.; Simmonite, M.; Foerster, B.; Park, D.; Peltier, S.J.; Petrou, M.; Taylor, S.F.; Weissman, D.H.; et al. Sensorimotor network segregation declines with age and is linked to GABA and to sensorimotor performance. Neuroimage 2019, 186, 234–244. [Google Scholar] [CrossRef]
  17. Kossev, A.R.; Schrader, C.; Dauper, J.; Dengler, R.; Rollnik, J.D. Increased intracortical inhibition in middle-aged humans; a study using paired-pulse transcranial magnetic stimulation. Neurosci. Lett. 2002, 333, 83–86. [Google Scholar] [CrossRef] [PubMed]
  18. McGinley, M.; Hoffman, R.L.; Russ, D.W.; Thomas, J.S.; Clark, B.C. Older adults exhibit more intracortical inhibition and less intracortical facilitation than young adults. Exp. Gerontol. 2010, 45, 671–678. [Google Scholar] [CrossRef]
  19. Alexandre, F.; Heraud, N.; Tremey, E.; Oliver, N.; Bourgouin, D.; Varray, A. Specific motor cortex hypoexcitability and hypoactivation in COPD patients with peripheral muscle weakness. BMC Pulm. Med. 2020, 20, 1. [Google Scholar] [CrossRef]
  20. Khedr, E.M.; Ahmed, M.A.; Hamdy, A.; Shawky, O.A. Cortical excitability of amyotrophic lateral sclerosis: Transcranial magnetic stimulation study. Neurophysiol. Clin. 2011, 41, 73–79. [Google Scholar] [CrossRef]
  21. Boric, K.; Munoz, P.; Gallagher, M.; Kirkwood, A. Potential adaptive function for altered long-term potentiation mechanisms in aging hippocampus. J. Neurosci. 2008, 28, 8034–8039. [Google Scholar] [CrossRef] [PubMed]
  22. Foster, T.C. Dissecting the age-related decline on spatial learning and memory tasks in rodent models: N-methyl-D-aspartate receptors and voltage-dependent Ca2+ channels in senescent synaptic plasticity. Prog. Neurobiol. 2012, 96, 283–303. [Google Scholar] [CrossRef]
  23. Abe, H.; Jitsuki, S.; Nakajima, W.; Murata, Y.; Jitsuki-Takahashi, A.; Katsuno, Y.; Tada, H.; Sano, A.; Suyama, K.; Mochizuki, N.; et al. CRMP2-binding compound, edonerpic maleate, accelerates motor function recovery from brain damage. Science 2018, 360, 50–57. [Google Scholar] [CrossRef] [PubMed]
  24. Takahashi, T. Novel synaptic plasticity enhancer drug to augment functional recovery with rehabilitation. Curr. Opin. Neurol. 2019, 32, 822–827. [Google Scholar] [CrossRef] [PubMed]
  25. Arber, S.; Costa, R.M. Connecting neuronal circuits for movement. Science 2018, 360, 1403–1404. [Google Scholar] [CrossRef] [PubMed]
  26. Gross, C.G. The discovery of motor cortex and its background. J. Hist. Neurosci. 2007, 16, 320–331. [Google Scholar] [CrossRef]
  27. Nudo, R.J.; Masterton, R.B. Descending pathways to the spinal cord, III: Sites of origin of the corticospinal tract. J. Comp. Neurol. 1990, 296, 559–583. [Google Scholar] [CrossRef]
  28. Tennant, K.A.; Adkins, D.L.; Donlan, N.A.; Asay, A.L.; Thomas, N.; Kleim, J.A.; Jones, T.A. The organization of the forelimb representation of the C57BL/6 mouse motor cortex as defined by intracortical microstimulation and cytoarchitecture. Cereb. Cortex 2011, 21, 865–876. [Google Scholar] [CrossRef]
  29. Weiler, N.; Wood, L.; Yu, J.; Solla, S.A.; Shepherd, G.M. Top-down laminar organization of the excitatory network in motor cortex. Nat. Neurosci. 2008, 11, 360–366. [Google Scholar] [CrossRef]
  30. Petreanu, L.; Mao, T.; Sternson, S.M.; Svoboda, K. The subcellular organization of neocortical excitatory connections. Nature 2009, 457, 1142–1145. [Google Scholar] [CrossRef]
  31. Sanders, T.H.; Jaeger, D. Optogenetic stimulation of cortico-subthalamic projections is sufficient to ameliorate bradykinesia in 6-ohda lesioned mice. Neurobiol. Dis. 2016, 95, 225–237. [Google Scholar] [CrossRef]
  32. Anderson, C.T.; Sheets, P.L.; Kiritani, T.; Shepherd, G.M. Sublayer-specific microcircuits of corticospinal and corticostriatal neurons in motor cortex. Nat. Neurosci. 2010, 13, 739–744. [Google Scholar] [CrossRef]
  33. Yu, J.; Anderson, C.T.; Kiritani, T.; Sheets, P.L.; Wokosin, D.L.; Wood, L.; Shepherd, G.M. Local-Circuit Phenotypes of Layer 5 Neurons in Motor-Frontal Cortex of YFP-H Mice. Front. Neural Circuits 2008, 2, 6. [Google Scholar] [CrossRef]
  34. Hooks, B.M.; Hires, S.A.; Zhang, Y.X.; Huber, D.; Petreanu, L.; Svoboda, K.; Shepherd, G.M. Laminar analysis of excitatory local circuits in vibrissal motor and sensory cortical areas. PLoS Biol. 2011, 9, e1000572. [Google Scholar] [CrossRef] [PubMed]
  35. Davidoff, R.A. The pyramidal tract. Neurology 1990, 40, 332–339. [Google Scholar] [CrossRef]
  36. Jane, J.A.; Yashon, D.; DeMyer, W.; Bucy, P.C. The contribution of the precentral gyrus to the pyramidal tract of man. J. Neurosurg. 1967, 26, 244–248. [Google Scholar] [CrossRef] [PubMed]
  37. Kawai, R.; Markman, T.; Poddar, R.; Ko, R.; Fantana, A.L.; Dhawale, A.K.; Kampff, A.R.; Olveczky, B.P. Motor cortex is required for learning but not for executing a motor skill. Neuron 2015, 86, 800–812. [Google Scholar] [CrossRef] [PubMed]
  38. Cantarero, G.; Lloyd, A.; Celnik, P. Reversal of long-term potentiation-like plasticity processes after motor learning disrupts skill retention. J. Neurosci. 2013, 33, 12862–12869. [Google Scholar] [CrossRef]
  39. Papale, A.E.; Hooks, B.M. Circuit changes in motor cortex during motor skill learning. Neuroscience 2018, 368, 283–297. [Google Scholar] [CrossRef]
  40. Kida, H.; Tsuda, Y.; Ito, N.; Yamamoto, Y.; Owada, Y.; Kamiya, Y.; Mitsushima, D. Motor Training Promotes Both Synaptic and Intrinsic Plasticity of Layer II/III Pyramidal Neurons in the Primary Motor Cortex. Cereb. Cortex 2016, 26, 3494–3507. [Google Scholar] [CrossRef]
  41. Kida, H.; Kawakami, R.; Sakai, K.; Otaku, H.; Imamura, K.; Han, T.Z.; Sakimoto, Y.; Mitsushima, D. Motor training promotes both synaptic and intrinsic plasticity of layer V pyramidal neurons in the primary motor cortex. J. Physiol. 2023, 601, 335–353. [Google Scholar] [CrossRef] [PubMed]
  42. Rioult-Pedotti, M.S.; Friedman, D.; Donoghue, J.P. Learning-induced LTP in neocortex. Science 2000, 290, 533–536. [Google Scholar] [CrossRef]
  43. Rioult-Pedotti, M.S.; Donoghue, J.P.; Dunaevsky, A. Plasticity of the synaptic modification range. J. Neurophysiol. 2007, 98, 3688–3695. [Google Scholar] [CrossRef] [PubMed]
  44. Rioult-Pedotti, M.S.; Friedman, D.; Hess, G.; Donoghue, J.P. Strengthening of horizontal cortical connections following skill learning. Nat. Neurosci. 1998, 1, 230–234. [Google Scholar] [CrossRef]
  45. Hodgson, R.A.; Ji, Z.; Standish, S.; Boyd-Hodgson, T.E.; Henderson, A.K.; Racine, R.J. Training-induced and electrically induced potentiation in the neocortex. Neurobiol. Learn. Mem. 2005, 83, 22–32. [Google Scholar] [CrossRef] [PubMed]
  46. Monfils, M.H.; Teskey, G.C. Skilled-learning-induced potentiation in rat sensorimotor cortex: A transient form of behavioural long-term potentiation. Neuroscience 2004, 125, 329–336. [Google Scholar] [CrossRef]
  47. Biane, J.S.; Takashima, Y.; Scanziani, M.; Conner, J.M.; Tuszynski, M.H. Thalamocortical Projections onto Behaviorally Relevant Neurons Exhibit Plasticity during Adult Motor Learning. Neuron 2016, 89, 1173–1179. [Google Scholar] [CrossRef]
  48. Kida, H.; Mitsushima, D. Mechanisms of motor learning mediated by synaptic plasticity in rat primary motor cortex. Neurosci. Res. 2018, 128, 14–18. [Google Scholar] [CrossRef]
  49. Barbati, S.A.; Cocco, S.; Longo, V.; Spinelli, M.; Gironi, K.; Mattera, A.; Paciello, F.; Colussi, C.; Podda, M.V.; Grassi, C. Enhancing Plasticity Mechanisms in the Mouse Motor Cortex by Anodal Transcranial Direct-Current Stimulation: The Contribution of Nitric Oxide Signaling. Cereb. Cortex 2020, 30, 2972–2985. [Google Scholar] [CrossRef]
  50. Inoue, R.; Miura, M.; Yanai, S.; Nishimune, H. Coenzyme Q(10) supplementation improves the motor function of middle-aged mice by restoring the neuronal activity of the motor cortex. Sci. Rep. 2023, 13, 4323. [Google Scholar] [CrossRef]
  51. Ziemann, U.; Ilic, T.V.; Pauli, C.; Meintzschel, F.; Ruge, D. Learning modifies subsequent induction of long-term potentiation-like and long-term depression-like plasticity in human motor cortex. J. Neurosci. 2004, 24, 1666–1672. [Google Scholar] [CrossRef]
  52. Rosenkranz, K.; Kacar, A.; Rothwell, J.C. Differential modulation of motor cortical plasticity and excitability in early and late phases of human motor learning. J. Neurosci. 2007, 27, 12058–12066. [Google Scholar] [CrossRef] [PubMed]
  53. Cantarero, G.; Tang, B.; O’Malley, R.; Salas, R.; Celnik, P. Motor learning interference is proportional to occlusion of LTP-like plasticity. J. Neurosci. 2013, 33, 4634–4641. [Google Scholar] [CrossRef] [PubMed]
  54. Ji, Z.; Boyd, T.E.; Froc, D.J.; Racine, R.J. Laminar differences in field potential morphology and long-term potentiation in motor cortex coronal slices from both unstimulated and previously potentiated rats. Eur. J. Neurosci. 2005, 22, 1455–1462. [Google Scholar] [CrossRef]
  55. Molina-Luna, K.; Pekanovic, A.; Rohrich, S.; Hertler, B.; Schubring-Giese, M.; Rioult-Pedotti, M.S.; Luft, A.R. Dopamine in motor cortex is necessary for skill learning and synaptic plasticity. PLoS ONE 2009, 4, e7082. [Google Scholar] [CrossRef]
  56. Yang, G.; Pan, F.; Gan, W.B. Stably maintained dendritic spines are associated with lifelong memories. Nature 2009, 462, 920–924. [Google Scholar] [CrossRef] [PubMed]
  57. Xu, T.; Yu, X.; Perlik, A.J.; Tobin, W.F.; Zweig, J.A.; Tennant, K.; Jones, T.; Zuo, Y. Rapid formation and selective stabilization of synapses for enduring motor memories. Nature 2009, 462, 915–919. [Google Scholar] [CrossRef] [PubMed]
  58. Zemmar, A.; Weinmann, O.; Kellner, Y.; Yu, X.; Vicente, R.; Gullo, M.; Kasper, H.; Lussi, K.; Ristic, Z.; Luft, A.R.; et al. Neutralization of Nogo-A enhances synaptic plasticity in the rodent motor cortex and improves motor learning in vivo. J. Neurosci. 2014, 34, 8685–8698. [Google Scholar] [CrossRef]
  59. Guo, L.; Xiong, H.; Kim, J.I.; Wu, Y.W.; Lalchandani, R.R.; Cui, Y.; Shu, Y.; Xu, T.; Ding, J.B. Dynamic rewiring of neural circuits in the motor cortex in mouse models of Parkinson’s disease. Nat. Neurosci. 2015, 18, 1299–1309. [Google Scholar] [CrossRef]
  60. Gloor, C.; Luft, A.R.; Hosp, J.A. Biphasic plasticity of dendritic fields in layer V motor neurons in response to motor learning. Neurobiol. Learn. Mem. 2015, 125, 189–194. [Google Scholar] [CrossRef]
  61. Tjia, M.; Yu, X.; Jammu, L.S.; Lu, J.; Zuo, Y. Pyramidal Neurons in Different Cortical Layers Exhibit Distinct Dynamics and Plasticity of Apical Dendritic Spines. Front. Neural Circuits 2017, 11, 43. [Google Scholar] [CrossRef]
  62. Donoghue, J.P.; Wise, S.P. The motor cortex of the rat: Cytoarchitecture and microstimulation mapping. J. Comp. Neurol. 1982, 212, 76–88. [Google Scholar] [CrossRef] [PubMed]
  63. Hosp, J.A.; Pekanovic, A.; Rioult-Pedotti, M.S.; Luft, A.R. Dopaminergic projections from midbrain to primary motor cortex mediate motor skill learning. J. Neurosci. 2011, 31, 2481–2487. [Google Scholar] [CrossRef] [PubMed]
  64. Ridding, M.C.; Ziemann, U. Determinants of the induction of cortical plasticity by non-invasive brain stimulation in healthy subjects. J. Physiol. 2010, 588, 2291–2304. [Google Scholar] [CrossRef]
  65. Nudo, R.J.; Milliken, G.W.; Jenkins, W.M.; Merzenich, M.M. Use-dependent alterations of movement representations in primary motor cortex of adult squirrel monkeys. J. Neurosci. 1996, 16, 785–807. [Google Scholar] [CrossRef]
  66. Wu, A.D.; Fregni, F.; Simon, D.K.; Deblieck, C.; Pascual-Leone, A. Noninvasive brain stimulation for Parkinson’s disease and dystonia. Neurotherapeutics 2008, 5, 345–361. [Google Scholar] [CrossRef]
  67. Godeiro, C.; Franca, C.; Carra, R.B.; Saba, F.; Saba, R.; Maia, D.; Brandao, P.; Allam, N.; Rieder, C.R.M.; Freitas, F.C.; et al. Use of non-invasive stimulation in movement disorders: A critical review. Arq. Neuropsiquiatr. 2021, 79, 630–646. [Google Scholar] [CrossRef] [PubMed]
  68. Liew, S.L.; Santarnecchi, E.; Buch, E.R.; Cohen, L.G. Non-invasive brain stimulation in neurorehabilitation: Local and distant effects for motor recovery. Front. Hum. Neurosci. 2014, 8, 378. [Google Scholar] [CrossRef] [PubMed]
  69. Liebetanz, D.; Nitsche, M.A.; Tergau, F.; Paulus, W. Pharmacological approach to the mechanisms of transcranial DC-stimulation-induced after-effects of human motor cortex excitability. Brain 2002, 125, 2238–2247. [Google Scholar] [CrossRef] [PubMed]
  70. Fritsch, B.; Reis, J.; Martinowich, K.; Schambra, H.M.; Ji, Y.; Cohen, L.G.; Lu, B. Direct current stimulation promotes BDNF-dependent synaptic plasticity: Potential implications for motor learning. Neuron 2010, 66, 198–204. [Google Scholar] [CrossRef]
  71. Rahman, A.; Reato, D.; Arlotti, M.; Gasca, F.; Datta, A.; Parra, L.C.; Bikson, M. Cellular effects of acute direct current stimulation: Somatic and synaptic terminal effects. J. Physiol. 2013, 591, 2563–2578. [Google Scholar] [CrossRef] [PubMed]
  72. Hill, T.C.; Zito, K. LTP-induced long-term stabilization of individual nascent dendritic spines. J. Neurosci. 2013, 33, 678–686. [Google Scholar] [CrossRef] [PubMed]
  73. Oliviero, A.; Profice, P.; Tonali, P.A.; Pilato, F.; Saturno, E.; Dileone, M.; Ranieri, F.; Di Lazzaro, V. Effects of aging on motor cortex excitability. Neurosci. Res. 2006, 55, 74–77. [Google Scholar] [CrossRef] [PubMed]
  74. Petitet, P.; Spitz, G.; Emir, U.E.; Johansen-Berg, H.; O’Shea, J. Age-related decline in cortical inhibitory tone strengthens motor memory. Neuroimage 2021, 245, 118681. [Google Scholar] [CrossRef] [PubMed]
  75. Dickstein, D.L.; Kabaso, D.; Rocher, A.B.; Luebke, J.I.; Wearne, S.L.; Hof, P.R. Changes in the structural complexity of the aged brain. Aging Cell 2007, 6, 275–284. [Google Scholar] [CrossRef]
  76. Chang, Y.M.; Rosene, D.L.; Killiany, R.J.; Mangiamele, L.A.; Luebke, J.I. Increased action potential firing rates of layer 2/3 pyramidal cells in the prefrontal cortex are significantly related to cognitive performance in aged monkeys. Cereb. Cortex 2005, 15, 409–418. [Google Scholar] [CrossRef]
  77. Luebke, J.I.; Chang, Y.M. Effects of aging on the electrophysiological properties of layer 5 pyramidal cells in the monkey prefrontal cortex. Neuroscience 2007, 150, 556–562. [Google Scholar] [CrossRef]
  78. Coskren, P.J.; Luebke, J.I.; Kabaso, D.; Wearne, S.L.; Yadav, A.; Rumbell, T.; Hof, P.R.; Weaver, C.M. Functional consequences of age-related morphologic changes to pyramidal neurons of the rhesus monkey prefrontal cortex. J. Comput. Neurosci. 2015, 38, 263–283. [Google Scholar] [CrossRef]
  79. Luebke, J.I.; Chang, Y.M.; Moore, T.L.; Rosene, D.L. Normal aging results in decreased synaptic excitation and increased synaptic inhibition of layer 2/3 pyramidal cells in the monkey prefrontal cortex. Neuroscience 2004, 125, 277–288. [Google Scholar] [CrossRef]
  80. Rizzo, V.; Richman, J.; Puthanveettil, S.V. Dissecting mechanisms of brain aging by studying the intrinsic excitability of neurons. Front. Aging Neurosci. 2014, 6, 337. [Google Scholar] [CrossRef]
  81. Davidson, A.M.; Mejia-Gomez, H.; Jacobowitz, M.; Mostany, R. Dendritic Spine Density and Dynamics of Layer 5 Pyramidal Neurons of the Primary Motor Cortex Are Elevated With Aging. Cereb. Cortex 2020, 30, 767–777. [Google Scholar] [CrossRef]
  82. Brecht, M.; Schneider, M.; Sakmann, B.; Margrie, T.W. Whisker movements evoked by stimulation of single pyramidal cells in rat motor cortex. Nature 2004, 427, 704–710. [Google Scholar] [CrossRef] [PubMed]
  83. Kishore, A.; Popa, T.; James, P.; Yahia-Cherif, L.; Backer, F.; Varughese Chacko, L.; Govind, P.; Pradeep, S.; Meunier, S. Age-related decline in the responsiveness of motor cortex to plastic forces reverses with levodopa or cerebellar stimulation. Neurobiol. Aging 2014, 35, 2541–2551. [Google Scholar] [CrossRef] [PubMed]
  84. Tennant, K.A.; Adkins, D.L.; Scalco, M.D.; Donlan, N.A.; Asay, A.L.; Thomas, N.; Kleim, J.A.; Jones, T.A. Skill learning induced plasticity of motor cortical representations is time and age-dependent. Neurobiol. Learn. Mem. 2012, 98, 291–302. [Google Scholar] [CrossRef] [PubMed]
  85. Burianova, H.; Marstaller, L.; Rich, A.N.; Williams, M.A.; Savage, G.; Ryan, M.; Sowman, P.F. Motor neuroplasticity: A MEG-fMRI study of motor imagery and execution in healthy ageing. Neuropsychologia 2020, 146, 107539. [Google Scholar] [CrossRef]
  86. Davey, G.P.; Clark, J.B. Threshold effects and control of oxidative phosphorylation in nonsynaptic rat brain mitochondria. J. Neurochem. 1996, 66, 1617–1624. [Google Scholar] [CrossRef]
  87. Davey, G.P.; Peuchen, S.; Clark, J.B. Energy thresholds in brain mitochondria. Potential involvement in neurodegeneration. J. Biol. Chem. 1998, 273, 12753–12757. [Google Scholar] [CrossRef]
  88. Lores-Arnaiz, S.; Bustamante, J. Age-related alterations in mitochondrial physiological parameters and nitric oxide production in synaptic and non-synaptic brain cortex mitochondria. Neuroscience 2011, 188, 117–124. [Google Scholar] [CrossRef]
  89. Lores-Arnaiz, S.; Lombardi, P.; Karadayian, A.G.; Orgambide, F.; Cicerchia, D.; Bustamante, J. Brain cortex mitochondrial bioenergetics in synaptosomes and non-synaptic mitochondria during aging. Neurochem. Res. 2016, 41, 353–363. [Google Scholar] [CrossRef]
  90. Todorova, V.; Blokland, A. Mitochondria and Synaptic Plasticity in the Mature and Aging Nervous System. Curr. Neuropharmacol. 2017, 15, 166–173. [Google Scholar] [CrossRef]
  91. Mattson, M.P. Mitochondrial regulation of neuronal plasticity. Neurochem. Res. 2007, 32, 707–715. [Google Scholar] [CrossRef] [PubMed]
  92. Takahashi, K.; Takahashi, M. Exogenous administration of coenzyme Q10 restores mitochondrial oxygen consumption in the aged mouse brain. Mech. Ageing Dev. 2013, 134, 580–586. [Google Scholar] [CrossRef] [PubMed]
  93. Grimm, A.; Eckert, A. Brain aging and neurodegeneration: From a mitochondrial point of view. J. Neurochem. 2017, 143, 418–431. [Google Scholar] [CrossRef] [PubMed]
  94. Peterson, C.M.; Johannsen, D.L.; Ravussin, E. Skeletal muscle mitochondria and aging: A review. J. Aging Res. 2012, 2012, 194821. [Google Scholar] [CrossRef]
  95. Short, K.R.; Bigelow, M.L.; Kahl, J.; Singh, R.; Coenen-Schimke, J.; Raghavakaimal, S.; Nair, K.S. Decline in skeletal muscle mitochondrial function with aging in humans. Proc. Natl. Acad. Sci. USA 2005, 102, 5618–5623. [Google Scholar] [CrossRef]
  96. Garcia, M.L.; Fernandez, A.; Solas, M.T. Mitochondria, motor neurons and aging. J. Neurol. Sci. 2013, 330, 18–26. [Google Scholar] [CrossRef]
  97. Anagnostou, M.E.; Hepple, R.T. Mitochondrial Mechanisms of Neuromuscular Junction Degeneration with Aging. Cells 2020, 9, 197. [Google Scholar] [CrossRef]
  98. Carter, H.N.; Chen, C.C.; Hood, D.A. Mitochondria, muscle health, and exercise with advancing age. Physiology 2015, 30, 208–223. [Google Scholar] [CrossRef]
  99. Pandya, J.D.; Grondin, R.; Yonutas, H.M.; Haghnazar, H.; Gash, D.M.; Zhang, Z.; Sullivan, P.G. Decreased mitochondrial bioenergetics and calcium buffering capacity in the basal ganglia correlates with motor deficits in a nonhuman primate model of aging. Neurobiol. Aging 2015, 36, 1903–1913. [Google Scholar] [CrossRef]
  100. Niklowitz, P.; Onur, S.; Fischer, A.; Laudes, M.; Palussen, M.; Menke, T.; Doring, F. Coenzyme Q10 serum concentration and redox status in European adults: Influence of age, sex, and lipoprotein concentration. J. Clin. Biochem. Nutr. 2016, 58, 240–245. [Google Scholar] [CrossRef]
  101. Kalen, A.; Appelkvist, E.L.; Dallner, G. Age-related changes in the lipid compositions of rat and human tissues. Lipids 1989, 24, 579–584. [Google Scholar] [CrossRef] [PubMed]
  102. Soderberg, M.; Edlund, C.; Kristensson, K.; Dallner, G. Lipid compositions of different regions of the human brain during aging. J. Neurochem. 1990, 54, 415–423. [Google Scholar] [CrossRef]
  103. Friedrich, T.; van Heek, P.; Leif, H.; Ohnishi, T.; Forche, E.; Kunze, B.; Jansen, R.; Trowitzsch-Kienast, W.; Hofle, G.; Reichenbach, H.; et al. Two binding sites of inhibitors in NADH: Ubiquinone oxidoreductase (complex I). Relationship of one site with the ubiquinone-binding site of bacterial glucose:ubiquinone oxidoreductase. Eur. J. Biochem. 1994, 219, 691–698. [Google Scholar] [CrossRef]
  104. Brandt, U. Proton-translocation by membrane-bound NADH:ubiquinone-oxidoreductase (complex I) through redox-gated ligand conduction. Biochim. Biophys. Acta 1997, 1318, 79–91. [Google Scholar] [CrossRef] [PubMed]
  105. Scheffler, I.E. Molecular genetics of succinate:quinone oxidoreductase in eukaryotes. Prog. Nucleic Acid. Res. Mol. Biol. 1998, 60, 267–315. [Google Scholar] [CrossRef] [PubMed]
  106. Hernandez-Camacho, J.D.; Bernier, M.; Lopez-Lluch, G.; Navas, P. Coenzyme Q10 Supplementation in Aging and Disease. Front. Physiol. 2018, 9, 44. [Google Scholar] [CrossRef] [PubMed]
  107. Emmanuele, V.; Lopez, L.C.; Berardo, A.; Naini, A.; Tadesse, S.; Wen, B.; D’Agostino, E.; Solomon, M.; DiMauro, S.; Quinzii, C.; et al. Heterogeneity of coenzyme Q10 deficiency: Patient study and literature review. Arch. Neurol. 2012, 69, 978–983. [Google Scholar] [CrossRef]
  108. Mitsui, J.; Matsukawa, T.; Uemura, Y.; Kawahara, T.; Chikada, A.; Porto, K.J.L.; Naruse, H.; Tanaka, M.; Ishiura, H.; Toda, T.; et al. High-dose ubiquinol supplementation in multiple-system atrophy: A multicentre, randomised, double-blinded, placebo-controlled phase 2 trial. eClinicalMedicine 2023, 101920. [Google Scholar] [CrossRef]
  109. Lopez-Lluch, G.; Del Pozo-Cruz, J.; Sanchez-Cuesta, A.; Cortes-Rodriguez, A.B.; Navas, P. Bioavailability of coenzyme Q10 supplements depends on carrier lipids and solubilization. Nutrition 2019, 57, 133–140. [Google Scholar] [CrossRef] [PubMed]
  110. Belhaj, N.; Dupuis, F.; Arab-Tehrany, E.; Denis, F.M.; Paris, C.; Lartaud, I.; Linder, M. Formulation, characterization and pharmacokinetic studies of coenzyme Q(1)(0) PUFA’s nanoemulsions. Eur. J. Pharm. Sci. 2012, 47, 305–312. [Google Scholar] [CrossRef]
  111. Hatanaka, J.; Kimura, Y.; Lai-Fu, Z.; Onoue, S.; Yamada, S. Physicochemical and pharmacokinetic characterization of water-soluble Coenzyme Q(10) formulations. Int. J. Pharm. 2008, 363, 112–117. [Google Scholar] [CrossRef] [PubMed]
  112. Sikorska, M.; Lanthier, P.; Miller, H.; Beyers, M.; Sodja, C.; Zurakowski, B.; Gangaraju, S.; Pandey, S.; Sandhu, J.K. Nanomicellar formulation of coenzyme Q10 (Ubisol-Q10) effectively blocks ongoing neurodegeneration in the mouse 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine model: Potential use as an adjuvant treatment in Parkinson’s disease. Neurobiol. Aging 2014, 35, 2329–2346. [Google Scholar] [CrossRef] [PubMed]
  113. Molina, D.P.; Ariwodola, O.J.; Linville, C.; Sonntag, W.E.; Weiner, J.L.; Brunso-Bechtold, J.K.; Adams, M.M. Growth hormone modulates hippocampal excitatory synaptic transmission and plasticity in old rats. Neurobiol. Aging 2012, 33, 1938–1949. [Google Scholar] [CrossRef] [PubMed]
  114. Abuelezz, S.A.; Hendawy, N.; Magdy, Y. The potential benefit of combined versus monotherapy of coenzyme Q10 and fluoxetine on depressive-like behaviors and intermediates coupled to Gsk-3beta in rats. Toxicol. Appl. Pharmacol. 2018, 340, 39–48. [Google Scholar] [CrossRef] [PubMed]
  115. Alhusaini, A.; Hasan, I.H.; Alrumayyan, B.; Alesikri, M.; Alanazi, K.; Almasoud, R.; Almarshad, S. Neuroprotective efficacy of nano-CoQ against propionic acid toxicity in rats: Role of BDNF and CREB protein expressions. J. Biochem. Mol. Toxicol. 2020, 34, e22449. [Google Scholar] [CrossRef] [PubMed]
  116. Zagrebelsky, M.; Korte, M. Form follows function: BDNF and its involvement in sculpting the function and structure of synapses. Neuropharmacology 2014, 76 Pt C, 628–638. [Google Scholar] [CrossRef]
  117. Andreska, T.; Rauskolb, S.; Schukraft, N.; Luningschror, P.; Sasi, M.; Signoret-Genest, J.; Behringer, M.; Blum, R.; Sauer, M.; Tovote, P.; et al. Induction of BDNF Expression in Layer II/III and Layer V Neurons of the Motor Cortex Is Essential for Motor Learning. J. Neurosci. 2020, 40, 6289–6308. [Google Scholar] [CrossRef]
  118. Castren, E.; Antila, H. Neuronal plasticity and neurotrophic factors in drug responses. Mol. Psychiatry 2017, 22, 1085–1095. [Google Scholar] [CrossRef]
  119. Zhou, B.; Wang, Z.; Zhu, L.; Huang, G.; Li, B.; Chen, C.; Huang, J.; Ma, F.; Liu, T.C. Effects of different physical activities on brain-derived neurotrophic factor: A systematic review and bayesian network meta-analysis. Front. Aging Neurosci. 2022, 14, 981002. [Google Scholar] [CrossRef]
  120. van der Vliet, R.; Ribbers, G.M.; Vandermeeren, Y.; Frens, M.A.; Selles, R.W. BDNF Val66Met but not transcranial direct current stimulation affects motor learning after stroke. Brain Stimul. 2017, 10, 882–892. [Google Scholar] [CrossRef]
  121. Egan, M.F.; Kojima, M.; Callicott, J.H.; Goldberg, T.E.; Kolachana, B.S.; Bertolino, A.; Zaitsev, E.; Gold, B.; Goldman, D.; Dean, M.; et al. The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell 2003, 112, 257–269. [Google Scholar] [CrossRef] [PubMed]
  122. Kuczewski, N.; Porcher, C.; Gaiarsa, J.L. Activity-dependent dendritic secretion of brain-derived neurotrophic factor modulates synaptic plasticity. Eur. J. Neurosci. 2010, 32, 1239–1244. [Google Scholar] [CrossRef] [PubMed]
  123. Kleim, J.A.; Chan, S.; Pringle, E.; Schallert, K.; Procaccio, V.; Jimenez, R.; Cramer, S.C. BDNF val66met polymorphism is associated with modified experience-dependent plasticity in human motor cortex. Nat. Neurosci. 2006, 9, 735–737. [Google Scholar] [CrossRef] [PubMed]
  124. Webster, M.J.; Weickert, C.S.; Herman, M.M.; Kleinman, J.E. BDNF mRNA expression during postnatal development, maturation and aging of the human prefrontal cortex. Brain Res. Dev. Brain Res. 2002, 139, 139–150. [Google Scholar] [CrossRef]
  125. Hayashi, M.; Yamashita, A.; Shimizu, K. Somatostatin and brain-derived neurotrophic factor mRNA expression in the primate brain: Decreased levels of mRNAs during aging. Brain Res. 1997, 749, 283–289. [Google Scholar] [CrossRef]
  126. Dluzen, D.E.; McDermott, J.L.; Anderson, L.I.; Kucera, J.; Joyce, J.N.; Osredkar, T.; Walro, J.M. Age-related changes in nigrostriatal dopaminergic function are accentuated in +/- brain-derived neurotrophic factor mice. Neuroscience 2004, 128, 201–208. [Google Scholar] [CrossRef]
  127. Mueller, K.; Arelin, K.; Moller, H.E.; Sacher, J.; Kratzsch, J.; Luck, T.; Riedel-Heller, S.; Villringer, A.; Schroeter, M.L. Serum BDNF correlates with connectivity in the (pre)motor hub in the aging human brain--a resting-state fMRI pilot study. Neurobiol. Aging 2016, 38, 181–187. [Google Scholar] [CrossRef]
  128. Lohmann, G.; Margulies, D.S.; Horstmann, A.; Pleger, B.; Lepsien, J.; Goldhahn, D.; Schloegl, H.; Stumvoll, M.; Villringer, A.; Turner, R. Eigenvector centrality mapping for analyzing connectivity patterns in fMRI data of the human brain. PLoS ONE 2010, 5, e10232. [Google Scholar] [CrossRef]
  129. McHughen, S.A.; Cramer, S.C. The BDNF val(66)met polymorphism is not related to motor function or short-term cortical plasticity in elderly subjects. Brain Res. 2013, 1495, 1–10. [Google Scholar] [CrossRef]
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Figure 1. Age-related changes in the motor cortex excitatory connections. Physiological and structural properties change in the motor cortex excitatory connections during physiological aging. These age-related changes cause impairment of motor cortex excitability. The excitatory connection from layers II/III to V is the major intralaminar connection in the motor cortex. Gray arrows from pyramidal neurons in layers II/III or V indicate intralaminar horizontal connections. Abbreviations: CST, corticospinal tract; AP, action potential; fEPSP, field excitatory postsynaptic potential.
Figure 1. Age-related changes in the motor cortex excitatory connections. Physiological and structural properties change in the motor cortex excitatory connections during physiological aging. These age-related changes cause impairment of motor cortex excitability. The excitatory connection from layers II/III to V is the major intralaminar connection in the motor cortex. Gray arrows from pyramidal neurons in layers II/III or V indicate intralaminar horizontal connections. Abbreviations: CST, corticospinal tract; AP, action potential; fEPSP, field excitatory postsynaptic potential.
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Table 1. Plasticity in the motor cortex.
Table 1. Plasticity in the motor cortex.
Species AgeMotor Learning Task or In Vivo StimulationStimulation Layer/AreaRecording Layer/NeuronPlasticity TypeAmount of PlasticityRecording or Measurement MethodReferences
Female ratsAdultPellet-reaching taskLayer II/III at 500 μm horizontally from the recording electrode in the M1 forelimb area *Layer II/III at 200–350 μm below the pial surface in the M1 forelimb area *LTPFP amplitude ↑Field potential recording[42,43,44]
Male ratsNot mentionedPellet reaching taskLayer II/III at 3.0 mm lateral to the midlineLayer II/III at 2.0 mm lateral to the midline in the M1 forelimb area *LTPfEPSP amplitude ↑Field potential recording
In vivo recording		[45]
Male ratsNot mentionedIn vivo white matter stimulation (previously potentiated rat)Layer II/III in the primary motor cortex
Layer V in the primary motor cortex		Layer II/III in the primary motor cortex
Layer V in the primary motor cortex		FPFP amplitude ↑
FP amplitude ↔		Field potential recording[54]
Male rats8–10 weeksNoneLayer II/III at 2–2.5 mm lateral to the midlineLayer II/III at 500 μm lateral to the stimulation electrode in the M1 forelimb area *LTPfEPSP amplitude ↓ (D1 or D2 receptor antagonist after LTP induction vs. control)Field potential recording[55]
Mice1 month
>4 months
1 month		Accelerated rotor rod task Layer V pyramidal neurons in the M1 forelimb area *Structural plasticity (2-days trained mice)
Structural plasticity (After previous 2-days training)		Spine formation ↑ (2-days)
Spine formation ↔ (Next 2-days)		In vivo two-photon imaging[56]
Mice1 monthPellet reaching task Layer V pyramidal neurons in the motor cortexStructural plasticitySpine formation ↑
Spine elimination ↔		In vivo two-photon imaging[57]
Male rats
Male and female mice		5–6 weeks
1 month		None
None
Pellet reaching task		Layer II/III 2–4 mm lateral to the midlineLayer II/III at 500 μm lateral to the stimulating electrode
Layer V neurons in the motor cortex
Layer II/III pyramidal neurons in the motor cortex		LTP
Structural plasticity
Structural plasticity		fEPSP amplitude ↑ (anti-Nogo A vs. control)
Spine formation ↑ (anti-Nogo A vs. control)
Spine density ↑ (sham and anti-Nogo A)		Field potential recording
In vivo two-photon imaging		[58]
Male and female PD model mice1–3 monthsDopamine depletion Superficial layers of the motor cortexLayer V pyramidal neurons in the M1 forelimb area *
Layer V pyramidal neurons 10–100 μm below the cortical surface in the motor cortex		LTP
Structural plasticity		EPSC amplitude ↓ (DA depletion vs. control)
Spine turnover in the dendritic spine ↑ (DA depletion vs. control)		Whole-cell recording
In vivo two-photon imaging		[59]
Male rats10–12 weeksPellet reaching task Layer V neuronsStructural plasticityDendritic length ↑ (after 1 month)Histological analysis[60]
Rats55–59 daysPellet reaching taskEntire cortical slice centered over the recorded neurons in the primary motor cortex Layer V neurons in the caudal forelimb areaPhoto-induced EPSCEPSC amplitude↑
PPR ↔ 		Whole-cell recording[47]
Male Rats4 weeksAccelerated rotor rod taskLayer II/III at 200–300 μm laterally from the recorded neurons in the primary motor cortexLayer II/III pyramidal neurons in the M1 forelimb area *mEPSC
mIPSC		Amplitude ↑ (1-day and 2-days trained) Frequency ↔ (1-day), ↑ (2-days trained)
AMPA/NMDA ↑ (1 day), ↔ (2-days trained)
PPR ↔ (1-day), ↓ (2-days trained)
Amplitude ↔ (1-day), ↔ (2-days trained)
Frequency ↓ (1 day), ↔ (2-days trained)
PPR ↑ (1 day), ↔ (2-days trained)		Whole-cell recording[40,48]
Male and female mice1 month,
4 months		Pellet reaching task Layer II/III pyramidal neurons
Layer V pyramidal neurons		Structural plasticity
Structural plasticity		Spine formation and elimination ↔
Spine formation and elimination ↑		In vivo two-photon imaging[61]
Male mice30–45 daysRepeated tDCSLayer II/III in the primary motor cortexLayer II/III at ~200 μm lateral to the stimulation electrode in the primary motor cortexLTP
mEPSC
mIPSC
Structural plasticity		fEPSP amplitude ↑
PPR (interval: 20 ms) ↓
AMPA/NMDA ratio ↑
Amplitude ↔, Frequency ↑
Amplitude and frequency ↔
Spine density ↑		Field potential recording
Whole-cell recording
Histological analysis		[49]
Male mice15–18 months CoQ10 suppllementation
None		Layer II/III in the radial direction from the recording electrode Layer V in the primary motor cortexfEPSP
LTP		fEPSP amplitude ↑ (CoQ10 middle-aged vs. age-matched control)
fEPSP amplitude ↑ (CoQ10 during LTP induction vs. age-matched control)		Field potential recording[50]
Male rats
Male mice		4 weeks
8–10 weeks		Accelerated rotor rod task
Accelerated rotor rod task		Layer II/III at 200–300 μm laterally from the recorded neurons in the primary motor cortexLayer V pyramidal neurons in the M1 forelimb area *
Layer V pyramidal neurons in the motor cortex		mEPSC
mIPSC
Structural plasticity		Amplitude ↔ (1 day), ↑ (2 days trained) Frequency ↔ (1 day), ↑ (2 days trained)
AMPA/NMDA ratio ↔ (1 day), ↑ (2 days trained)
PPR ↔ (1 day and 2 days trained)
Amplitude ↓ (1 day), ↔ (2 days trained) Frequency ↓ (1 day), ↔ (2 days trained)
PPR ↑ (1 day), ↔ (2 days trained)
Volume of spines ↑		Whole-cell recording
In vivo two-photon imaging		[41]
Abbreviations: ↑, increase; ↓, decrease; ↔, no change; the M1 forelimb area *, the region corresponding to forelimb representation in the primary motor cortex * [62]; FP, field potential; fEPSP, field excitatory postsynaptic potential; mEPSC, miniature excitatory postsynaptic current; mIPSC, miniature inhibitory postsynaptic current; PPR, paired-pulse ratio; PD, Parkinson’s disease model.
Table 2. Intervention methods for targeting CNS for the decline of motor function.
Table 2. Intervention methods for targeting CNS for the decline of motor function.
Intervention TypeAdministration MethodSpeciesAgeEffects on Motor FunctionCell or Brain RegionTarget MechanismCommercial AvailabilityReferences
Nanomicellar formulation of CoQ10 supplementationOralMale MPTP treated-mice8–10 weeksDecrease of hindlimb faults number during the beam walk testSubstantia nigra, StriatumNeuroprotection, Astrocytic activation in the midbrainYes[112]
Water-soluble nano formula-type CoQ10 (ubiquinone) supplementationOralMale and female mice15 monthsImprovement of the pole test latency Motor cortexBrain mitochondrial oxidative phosphorylation dysfunctionYes[10]
OralMale mice15–18 monthsImprovement of the pole test latency Primary motor cortexAge-related decline of neuronal activity in layer V in the primary motor cortex, Brain mitochondrial oxidative phosphorylation dysfunctionYes[50]
High-dose CoQ10 (ubiquinol) supplementationOralMale and female multiple-system atrophy patientsMedian age 61.0 yearsImprovement of SARA score and time required to walk 10 mCerebellum, Motor cortex, PutamenCoQ10 deficiency (COQ2 mutation)Yes[108]
Anti-Nogo-A antibodies treatmentContinuous intrathecal infusion Male rats5–6 weeksIncrease in the success rate of the pellet-reaching taskLayer II/III and V neurons in the motor cortexSpine formation, Spine density modulation upon motor learning in the primary motor cortexLimited[58]
Combination of edonerpic maleate administration and rehabilitative trainingOralMale mice after motor cortex cryoinjured
Male monkey after motor cortex cryoinjured		5–13 weeks
5 or 6 years		Facilitation of recovery from injury of the motor cortex (the food-reaching task performance)Layer V pyramidal neurons in the motor cortexExperience-dependent synaptic AMPA receptor deliveryLimited[23]
Exercise
(Increase in activity-dependent BDNF secretion/TrkB phosphorylation)		 Mice/HumanNot mentionedImprovement of motor learningLayer II/III neurons in the motor cortexActivity-dependent BDNF secretion/TrkB phosphorylation, BDNF-mediated synaptic plasticity (LTP)Not
applicable		[70,117,119,120,126,127]
Abbreviations: CNS, central nervous system; CoQ10, coenzyme Q10; BDNF, brain-derived neurotrophic factor; TrkB, BDNF tyrosine receptor kinase B; SARA score, Scale for the Assessment and Rating of Ataxia score.
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Inoue, R.; Nishimune, H. Neuronal Plasticity and Age-Related Functional Decline in the Motor Cortex. Cells 2023, 12, 2142. https://doi.org/10.3390/cells12172142

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Inoue R, Nishimune H. Neuronal Plasticity and Age-Related Functional Decline in the Motor Cortex. Cells. 2023; 12(17):2142. https://doi.org/10.3390/cells12172142

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Inoue, Ritsuko, and Hiroshi Nishimune. 2023. "Neuronal Plasticity and Age-Related Functional Decline in the Motor Cortex" Cells 12, no. 17: 2142. https://doi.org/10.3390/cells12172142

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