Cholinergic neurons in the pedunculopontine nucleus guide reversal learning by signaling the changing reward contingency

Ruan, Yang; Li, Kaiyuan; Zheng, Ran; Yan, Yiqun; Wang, Zhong-Xuan; Chen, Ying; Liu, Yi; Tian, Jun; Zhu, Liya; Lou, Huifang; Yu, Yan-Qin; Pu, Jiali; Zhang, Baorong

doi:10.1016/j.celrep.2022.110437

Cited by 12 publications

(5 citation statements)

References 64 publications

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“…Optogenetic inhibition of PPN ChAT + neurons slowed down by increasing extensor burst duration, and this slowing down effect was surprisingly similar to that resulting from their optogenetic activation ( Josset and others 2018 ). Chemogenetic inhibition of PPN ChAT + neurons did not change the distance traveled in an open field in rats ( Dautan and others 2020 ) and mice ( Ruan and others 2022 ).…”

Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 94%

“…Optogenetic activation of ascending PPN ChAT + projections to SNc increased locomotor activity in an open field, and their inhibition decreased locomotion ( Xiao and others 2016 ). In contrast, another team reported that optogenetic activation of the ascending PPN ChAT + projections to A9 did not modify the distance traveled or locomotor speed in an open field in mice ( Ruan and others 2022 ). The reason for such discrepancy is unclear.…”

Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 98%

“…In the three aforementioned studies, optogenetic activation did not initiate locomotion. Chemogenetic activation of PPN ChAT + neurons did not affect the distance traveled in an open field in mice ( Ruan and others 2022 ). This is in contrast with the prolocomotor effect of PPN ChAT + neurons noted in PD conditions in rats (see Stimulation in a PD Model in the PPN Cholinergic Neurons section; Pienaar, Gartside, and others 2015 ; Sharma and others 2020 ).…”

Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 99%

“…A third target of PPN cholinergic neurons is the thalamus (Huerta-Ocampo and others 2020; Figure 4B). Optogenetic stimulation of the ascending projections of PPN ChAT + neurons to either the mediodorsal thalamic nucleus or the parafascicular thalamus nucleus did not modify the distance traveled or the locomotor speed in an open field (Ruan and others 2022). These ascending PPN ChAT + inputs to thalamus likely play a role in nonlocomotor aspects such as control of sleep or arousal (Gut and Mena-Segovia 2019;Mena-Segovia and Bolam 2017;Ni and others 2016) or in cognitive flexibility such as reversal learning (Ruan and others 2022).…”

Section: Target-specific Effectsmentioning

confidence: 99%

“…Their activity increased after a pinch of the hindpaw that increased cortical activity, and PPN ChAT + neuron activation preceded cortical activation (for review, Mena-Segovia and Bolam 2017 ; Petzold and others 2015 ). PPN cholinergic neurons also responded to rewards, and these responses were influenced by rule switching in the behavioral task ( Ruan and others 2022 ).…”

Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 99%

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The Mesencephalic Locomotor Region: Multiple Cell Types, Multiple Behavioral Roles, and Multiple Implications for Disease

Ryczko

2022

Neuroscientist

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The mesencephalic locomotor region (MLR) controls locomotion in vertebrates. In humans with Parkinson disease, locomotor deficits are increasingly associated with decreased activity in the MLR. This brainstem region, commonly considered to include the cuneiform and pedunculopontine nuclei, has been explored as a target for deep brain stimulation to improve locomotor function, but the results are variable, from modest to promising. However, the MLR is a heterogeneous structure, and identification of the best cell type to target is only beginning. Here, I review the studies that uncovered the role of genetically defined MLR cell types, and I highlight the cells whose activation improves locomotor function in animal models of Parkinson disease. The promising cell types to activate comprise some glutamatergic neurons in the cuneiform and caudal pedunculopontine nuclei, as well as some cholinergic neurons of the pedunculopontine nucleus. Activation of MLR GABAergic neurons should be avoided, since they stop locomotion or evoke bouts flanked with numerous stops. MLR is also considered a potential target in spinal cord injury, supranuclear palsy, primary progressive freezing of gait, or stroke. Better targeting of the MLR cell types should be achieved through optimized deep brain stimulation protocols, pharmacotherapy, or the development of optogenetics for human use.

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Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 94%

Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 98%

Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 99%

Section: Target-specific Effectsmentioning

confidence: 99%

Section: Ppn Cholinergic Neurons: a Complex Rolementioning

confidence: 99%

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The Mesencephalic Locomotor Region: Multiple Cell Types, Multiple Behavioral Roles, and Multiple Implications for Disease

Ryczko

2022

Neuroscientist

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Learning search algorithm: framework and comprehensive performance for solving optimization problems

Qu,

Peng,

Zeng

2024

Artif Intell Rev

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In this study, the Learning Search Algorithm (LSA) is introduced as an innovative optimization algorithm that draws inspiration from swarm intelligence principles and mimics the social learning behavior observed in humans. The LSA algorithm optimizes the search process by integrating historical experience and real-time social information, enabling it to effectively navigate complex problem spaces. By doing so, it enhances its global development capability and provides efficient solutions to challenging optimization tasks. Additionally, the algorithm improves the collective learning capacity by incorporating teaching and active learning behaviors within the population, leading to improved local development capabilities. Furthermore, a dynamic adaptive control factor is utilized to regulate the algorithm’s global exploration and local development abilities. The proposed algorithm is rigorously evaluated using 40 benchmark test functions from IEEE CEC 2014 and CEC 2020, and compared against nine established evolutionary algorithms as well as 11 recently improved algorithms. The experimental results demonstrate the superiority of the LSA algorithm, as it achieves the top rank in the Friedman rank-sum test, highlighting its power and competitiveness. Moreover, the LSA algorithm is successfully applied to solve six real-world engineering problems and 15 UCI datasets of feature selection problems, showcasing its significant advantages and potential for practical applications in engineering problems and feature selection problems.

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Dopamine-sensitive neurons in the mesencephalic locomotor region control locomotion initiation, stop, and turns

Juárez Tello,

van der Zouwen,

Dejas

et al. 2024

Cell Reports

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Cholinergic neurons in the pedunculopontine nucleus guide reversal learning by signaling the changing reward contingency

Cited by 12 publications

References 64 publications

The Mesencephalic Locomotor Region: Multiple Cell Types, Multiple Behavioral Roles, and Multiple Implications for Disease

The Mesencephalic Locomotor Region: Multiple Cell Types, Multiple Behavioral Roles, and Multiple Implications for Disease

Learning search algorithm: framework and comprehensive performance for solving optimization problems

Dopamine-sensitive neurons in the mesencephalic locomotor region control locomotion initiation, stop, and turns

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