Hasil untuk "Neurophysiology and neuropsychology"

Ying M, Wang T, Zhang T et al.

Miaofa Ying,1,* Tiantian Wang,2,* Ting Zhang,3 Ziyang Zhai,4 Lisan Zhang5 1Department of Pharmacy, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China; 2Department of Pharmacy, Qiantang Campus, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China; 3Hangzhou Medical College, Hangzhou, People’s Republic of China; 4Zhejiang University School of Medicine, Hangzhou, People’s Republic of China; 5Department of Neurology/Center for Sleep Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lisan Zhang, Department of Neurology/Center for Sleep Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China, Tel +86 13805752614, Email zls09@zju.edu.cnBackground: Restless legs syndrome (RLS) is a complex condition characterized by significant heterogeneity. Factors that affect medication efficacy remain unclear; different RLS subtypes may respond differently to various drugs.Objective: To identify factors associated with the ineffectiveness of pramipexole and pregabalin in patients with various subtypes of RLS.Methods: This retrospective nested case–control study enrolled 257 RLS patients prescribed pramipexole or pregabalin between March 2019 and April 2024 at the sleep center of Sir Run Run Shaw Hospital. All patients completed a semi-structured questionnaire, underwent polysomnography and laboratory evaluations, and participated in a telephone survey. To represent iron-storage status, one principal component score that included five indicators of peripheral iron metabolism was extracted by principal component analysis. Treatment effectiveness was assessed using the Clinical Global Impression-Improvement (CGI-I) scale, with scores of 1– 3 indicating effective treatment and higher scores reflecting ineffective treatment. Multivariate logistic regression was employed to assess the risk factors (or RLS subtypes) of medication ineffectiveness.Results: Of patients treated with pramipexole, 42.7% (70/164) reported poor outcomes. Early onset RLS (OR = 5.076; 95% CI, 1.836– 14.033) and relevant family history (OR = 4.537; 95% CI, 1.556– 13.437) increased pramipexole ineffectiveness risk. Among pregabalin users, 34.4% (32/93) reported ineffectiveness, which was associated with hemoglobin levels (OR = 1.039; 95% CI, 1.001– 1.079).Conclusion: These findings suggest that RLS patients with familial or early-onset characteristics may represent a distinct subtype that responds preferentially to α 2δ ligands over dopamine agonists, supporting personalized treatment approaches based on clinical phenotyping.Plain Language Summary: Restless legs syndrome (RLS) is a complex condition associated with significant heterogeneity. How can the best medications for RLS patients with different disease characteristics be chosen?This study aimed to identify predictors of treatment response in restless legs syndrome (RLS) by evaluating clinical, polysomnography, and lab results to differentiate the effectiveness of pramipexole versus pregabalin. Key findings revealed that pramipexole ineffectiveness was associated with early-onset RLS and family history, while only low hemoglobin levels were linked to pregabalin ineffectiveness. A subtype of RLS—early-onset patients or patients with a family history—was identified as a risk factor for pramipexole ineffectiveness, but not for pregabalin ineffectiveness.The above findings suggested that the disease subtype of RLS patients may be a critical factor that cannot be ignored when evaluating medication effectiveness. Prospective, randomized controlled trials are needed to evaluate the efficacy of pramipexole and pregabalin in these specific RLS subtypes.Keywords: restless legs syndrome, family history, early onset, pregabalin, pramipexole

Amirtha Shekar, Sreekanth Koneru, Charles Ákos Szabó

We present a 57 year-old right-handed female with a history of idiopathic generalized epilepsy since age two years old as well as mild-to-moderate intellectual impairment and behavioral dyscontrol. She was seizure free for many years on ethosuximide, but her absence seizures recurred as her dose was gradually decreased. After raising her dose, she also began to experience falls, at times with decreased responsiveness. She was admitted for inpatient video-EEG monitoring for quantification of her absence seizures and characterization of her falls. Our patient had 3–6 absence seizures per hour. In addition to a brief alteration of awareness, her absence seizures were frequently associated with belching and eyelid myoclonia lasting for 3–4 s. Her belching was correlated with a generalized ictal discharge and was not noted interictally. Several episodes of unsteadiness were noted, at times the patient falling backwards into her bed, but never falling to the ground from a standing position; none of these episodes associated with ictal EEG correlate. In summary, our patient demonstrated and absence seizures with ictal eructation or belching, which has not been reported as an ictal symptom of generalized seizures, and episodes of unsteadiness of unknown characterization.

Wang Y, Wu M, Zhang J et al.

Yuting Wang,1 Minmin Wu,2 Jiongliang Zhang,1 Xinyue Li,1 Donghui Yu,1 Yumeng Su,1 Xiangyu Wei,1 Luwen Zhu2,3 1Second Clinical Medical College, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, People’s Republic of China; 2Rehabilitation Center, The Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, People’s Republic of China; 3Heilongjiang Provincial Key Laboratory of Brain Function and Neurorehabilitation, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, People’s Republic of ChinaCorrespondence: Luwen Zhu, Heilongjiang University of Chinese Medicine, 24 Heping Road, Xiangfang District, Harbin, Heilongjiang, 150000, People’s Republic of China, Email zhuluwen1983@126.comPurpose: To compare the efficacy differences between acupuncture and sham acupuncture in adult primary insomnia through Bayesian network meta-analysis, analyze the impact of different types of sham acupuncture on efficacy, and explore the basis for the control setting.Methods: A literature search of seven databases, including PubMed and Embase, until April 23, 2025, included randomized controlled trials (RCTs) comparing AT with noninvasive sham acupuncture (NISA), superficial acupuncture (SA), and non-acupuncture therapy (NAT) for treating PI in adults. The statistical analyses were conducted using R (version 4.4.1) and Stata (version 15.1). The protocol was registered with the International Prospective Register of Systematic Reviews (CRD420251012912).Results: This meta-analysis incorporated 33 RCTs encompassing 3004 participants, with most studies originating from China. The results showed that at the treatment endpoint and after 4 weeks, AT significantly improved subjective sleep quality (Pittsburgh Sleep Quality Index, PSQI) compared to SA and NISA, exceeding the minimum clinically important difference (MCID: 2.5 points). Specifically, at the endpoint, AT vs SA (MD: − 3.66; 95% CI: − 4.48 to − 2.84) and AT vs NISA (MD: − 4.35; 95% CI: − 5.67 to − 3) were significant, while differences among SA, NISA, and NAT were not. Based on the surface under the cumulative rank curve (SUCRA), AT ranked first (99.9%), followed by SA (47.8%), NAT (31.9%), and NISA (20.4%). No significant differences were found between AT, NISA, and SA regarding objective sleep parameters.Conclusion: AT significantly improved subjective sleep quality in patients with PI, though its impact on objective sleep measures was limited. When designing RCTs of acupuncture for PI, NISA is recommended as the sham acupuncture control. However, due to geographical limitations, the study results may be difficult to generalize. Future research should focus on monitoring objective sleep parameters and conducting international, multicenter RCTs involving diverse cultural populations. Keywords: primary insomnia, sham acupuncture, acupuncture therapy, Bayesian network meta-analysis, randomized controlled trial

Jiaxin Zhang, Zehong Zhu, Junye Deng et al.

Villages areas hold significant importance in the study of human-land relationships. However, with the advancement of urbanization, the gradual disappearance of spatial characteristics and the homogenization of landscapes have emerged as prominent issues. Existing studies primarily adopt a single-disciplinary perspective to analyze villages spatial morphology and its influencing factors, relying heavily on qualitative analysis methods. These efforts are often constrained by the lack of digital infrastructure and insufficient data. To address the current research limitations, this paper proposes a Hierarchical Graph Neural Network (HGNN) model that integrates multi-source data to conduct an in-depth analysis of villages spatial morphology. The framework includes two types of nodes-input nodes and communication nodes-and two types of edges-static input edges and dynamic communication edges. By combining Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT), the proposed model efficiently integrates multimodal features under a two-stage feature update mechanism. Additionally, based on existing principles for classifying villages spatial morphology, the paper introduces a relational pooling mechanism and implements a joint training strategy across 17 subtypes. Experimental results demonstrate that this method achieves significant performance improvements over existing approaches in multimodal fusion and classification tasks. Additionally, the proposed joint optimization of all sub-types lifts mean accuracy/F1 from 0.71/0.83 (independent models) to 0.82/0.90, driven by a 6% gain for parcel tasks. Our method provides scientific evidence for exploring villages spatial patterns and generative logic.

Renrong Shao, Wei Zhang, Kangyang Luo et al.

Source-free domain adaptation (SFDA) aims to address the challenge of adapting to a target domain without accessing the source domain directly. However, due to the inaccessibility of source domain data, deterministic invariable features cannot be obtained. Current mainstream methods primarily focus on evaluating invariant features in the target domain that closely resemble those in the source domain, subsequently aligning the target domain with the source domain. However, these methods are susceptible to hard samples and influenced by domain bias. In this paper, we propose a Consistent Assistant Domains Transformer for SFDA, abbreviated as CADTrans, which solves the issue by constructing invariable feature representations of domain consistency. Concretely, we develop an assistant domain module for CADTrans to obtain diversified representations from the intermediate aggregated global attentions, which addresses the limitation of existing methods in adequately representing diversity. Based on assistant and target domains, invariable feature representations are obtained by multiple consistent strategies, which can be used to distinguish easy and hard samples. Finally, to align the hard samples to the corresponding easy samples, we construct a conditional multi-kernel max mean discrepancy (CMK-MMD) strategy to distinguish between samples of the same category and those of different categories. Extensive experiments are conducted on various benchmarks such as Office-31, Office-Home, VISDA-C, and DomainNet-126, proving the significant performance improvements achieved by our proposed approaches. Code is available at https://github.com/RoryShao/CADTrans.git.

Mingming Cao, Weiyi Kong, Dachun Yang et al.

In this article, we establish the parabolic version of the celebrated Rubio de Francia extrapolation theorem. As applications, we obtain new characterizations of parabolic BMO-type spaces in terms of various commutators of parabolic fractional operators with time lag. The key tools to achieve these include to establish the appropriate form in the parabolic setting of the parabolic Rubio de Francia iteration algorithm, the Cauchy integral trick, and a modified Fourier series expansion argument adapted to the parabolic geometry. The novelty of these results lies in the fact that, for the first time, we not only introduce a new class of commutators associated with parabolic fractional integral operators with time lag, but also utilize them to provide a characterization of the parabolic BMO-type space in the high-dimensional case.

Julian D. Schiller, Lars Grüne, and Matthias A. Müller

In this paper, we develop novel accuracy and performance guarantees for optimal state estimation of general nonlinear systems (in particular, moving horizon estimation, MHE). Our results rely on a turnpike property of the optimal state estimation problem, which essentially states that the omniscient infinite-horizon solution involving all past and future data serves as turnpike for the solutions of finite-horizon estimation problems involving a subset of the data. This leads to the surprising observation that MHE problems naturally exhibit a leaving arc, which may have a strong negative impact on the estimation accuracy. To address this, we propose a delayed MHE scheme, and we show that the resulting performance (both averaged and non-averaged) is approximately optimal and achieves bounded dynamic regret with respect to the infinite-horizon solution, with error terms that can be made arbitrarily small by an appropriate choice of the delay. In various simulation examples, we observe that already a very small delay in the MHE scheme is sufficient to significantly improve the overall estimation error by 20-25 % compared to standard MHE (without delay). This finding is of great importance for practical applications (especially for monitoring, fault detection, and parameter estimation) where a small delay in the estimation is rather irrelevant but may significantly improve the estimation results.

Sotaro Katayama, Noriaki Takasugi, Mitsuhisa Kaneko et al.

This paper presents a stochastic/robust nonlinear model predictive control (NMPC) to enhance the robustness of model-based legged locomotion against contact uncertainties. We integrate the contact uncertainties into the covariance propagation of stochastic/robust NMPC framework by leveraging the guard saltation matrix and an extended Kalman filter-like covariance update. We achieve fast stochastic/robust NMPC computation by utilizing the zero-order algorithm with additional improvements in computational efficiency concerning the feedback gains. We conducted numerical experiments and demonstrate that the proposed method can accurately forecast future state covariance and generate trajectories that satisfies constraints even in the presence of the contact uncertainties. Hardware experiments on the perceptive locomotion of a wheeled-legged robot were also carried out, validating the feasibility of the proposed method in a real-world system with limited on-board computation.

Madelene C. Holm, Esten H. Leonardsen, Dani Beck et al.

The temporal characteristics of adolescent neurodevelopment are shaped by a complex interplay of genetic, biological, and environmental factors. Using a large longitudinal dataset of children aged 9–13 from the Adolescent Brain Cognitive Development (ABCD) study we tested the associations between pubertal status and brain maturation. Brain maturation was assessed using brain age prediction based on convolutional neural networks and minimally processed T1-weighted structural MRI data. Brain age prediction provided highly accurate and reliable estimates of individual age, with an overall mean absolute error of 0.7 and 1.4 years at the two timepoints respectively, and an intraclass correlation of 0.65. Linear mixed effects (LME) models accounting for age and sex showed that on average, a one unit increase in pubertal maturational level was associated with a 2.22 months higher brain age across time points (β = 0.10, p < .001). Moreover, annualized change in pubertal development was weakly related to the rate of change in brain age (β = .047, p = 0.04). These results demonstrate a link between sexual development and brain maturation in early adolescence, and provides a basis for further investigations of the complex sociobiological impacts of puberty on life outcomes.

Priyanka Subash, Alex Gray, Misque Boswell et al.

As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.

Shengzhe Wang, Zhixin Meng, and Peiqiang Yan et al.

We present a cold atomic beam source based on a two-dimensional (2D)+ magneto-optical trap (MOT), capable of generating a continuous cold beam of 87Rb atoms with a flux up to 4.3*10^9 atoms/s, a mean velocity of 10.96(2.20) m/s, and a transverse temperature of 16.90(1.56) uK. Investigating the influence of high cooling laser intensity, we observe a significant population loss of atoms to hyperfine-level dark states. To account for this, we employ a multiple hyperfine level model to calculate the cooling efficiency associated with the population in dark states, subsequently modifying the scattering force. Simulations of beam flux at different cooling and repumping laser intensities using the modified scattering force are in agreement with experimental results. Optimizing repumping and cooling intensities enhances the flux by 50%. The influence of phase modulation on both the pushing and cooling lasers is experimentally studied, revealing that the mean velocity of cold atoms can be tuned from 9.5 m/s to 14.6 m/s with a phase-modulated pushing laser. The versatility of this continuous beam source, featuring high flux, controlled velocity, and narrow transverse temperature, renders it valuable for applications in atom interferometers and clocks, ultimately enhancing bandwidth, sensitivity, and signal contrast in these devices.

Fernandez FX

Fabian-Xosé Fernandez Department of Psychology, University of Arizona, Tucson, AZ, USACorrespondence: Fabian-Xosé FernandezDepartment of Psychology, University of Arizona, Tucson, Az, USAEmail FabianF@email.arizona.eduAbstract: This perspective considers the possibility that daytime’s intrusion into night made possible by electric lighting may not be as pernicious to sleep and circadian health as the encroachment of nighttime into day wrought by 20th century architectural practices that have left many people estranged from sunlight.Keywords: human-centric lighting, sleep, circadian entrainment, photohistory, sunlight, daylight

Abolfazl Rahmani Badi, Davood Taghvaei, Zabih Pirani

Aim and Background: Students with academic self-regulation are hard-working and innovative learners and do not simply give up in dealing with issues and problems. They consider learning as an active process during which somehow take responsibility for it and, if faced with problems, try to figure out what they need to do to solve it. The aim of this study was to develop a self-regulatory model of learning based on successful intelligence and emotional adjustment with the mediating role of psychological well-being. Methods and Materials: The research method was correlational and the statistical population of the present study was male and female high school students in Tehran. Four hundred and fifty-six of them were selected in a multi cluster sampling and were asked to complete the self-regulatory learning scale (SRQ-A), the Successful Intelligence Questionnaire, the Psychological Well-Being scale, and the Emotional Adjustment Scale (EAM). The obtained results were analyzed using AMOS software and path analysis method. Findings: The results showed that emotional adjustment and successful intelligence mediated by psychological well-being predict positively and significantly (p <0.01) self-regulation of learning. Conclusions: According to the results of the present study, it can be suggested that the higher the successful intelligence and emotional adjustment, the direct and mediated psychological well-being have a positive and significant effect on promoting learning self-regulation. Therefore, parents and educational authorities to strengthen academic self-regulation should provide rich environments to strengthen these three components.

Rachna B. Reddy, Aaron A. Sandel, Ronald E. Dahl

In humans, puberty initiates a period of rapid growth, change, and formative neurobehavioral development. Brain and behavior changes during this maturational window contribute to opportunities for social learning. Here we provide new insights into adolescence as a unique period of social learning and development by describing field studies of our closest living relatives, chimpanzees. Like humans, chimpanzees have a multiyear juvenile life stage between weaning and puberty onset followed by a multiyear adolescent life stage after pubertal onset but prior to socially-recognized adulthood. As they develop increasing autonomy from caregivers, adolescent chimpanzees explore and develop many different types of social relationships with a wide range of individuals in a highly flexible social environment. We describe how adolescent social motivations and experiences differ from those of juveniles and adults and expose adolescents to high levels of uncertainty, risk, and vulnerability, as well as opportunities for adaptive social learning. We discuss how these adolescent learning experiences may be shaped by early life and in turn shape varied adult social outcomes. We outline how future chimpanzee field research can contribute in new ways to a more integrative interdisciplinary understanding of adolescence as a developmental window of adaptive social learning and resilience.

Sadie J. Zacharek, Sahana Kribakaran, Elizabeth R. Kitt et al.

Anxiety disorders are the most prevalent psychiatric condition among youth, with symptoms commonly emerging prior to or during adolescence. Delineating neurodevelopmental trajectories associated with anxiety disorders is important for understanding the pathophysiology of pediatric anxiety and for early risk identification. While a growing literature has yielded valuable insights into the nature of brain structure and function in pediatric anxiety, progress has been limited by inconsistent findings and challenges common to neuroimaging research. In this review, we first discuss these challenges and the promise of ‘big data’ to map neurodevelopmental trajectories in pediatric anxiety. Next, we review evidence of age-related differences in neural structure and function among anxious youth, with a focus on anxiety-relevant processes such as threat and safety learning. We then highlight large-scale cross-sectional and longitudinal studies that assess anxiety and are well positioned to inform our understanding of neurodevelopment in pediatric anxiety. Finally, we detail relevant challenges of ‘big data’ and propose future directions through which large publicly available datasets can advance knowledge of deviations from normative brain development in anxiety. Leveraging ‘big data’ will be essential for continued progress in understanding the neurobiology of pediatric anxiety, with implications for identifying markers of risk and novel treatment targets.

R. Becket Ebitz, Benjamin Y. Hayden

A major shift is happening within neurophysiology: a population doctrine is drawing level with the single-neuron doctrine that has long dominated the field. Population-level ideas have so far had their greatest impact in motor neuroscience, but they hold great promise for resolving open questions in cognition as well. Here, we codify the population doctrine and survey recent work that leverages this view to specifically probe cognition. Our discussion is organized around five core concepts that provide a foundation for population-level thinking: (1) state spaces, (2) manifolds, (3) coding dimensions, (4) subspaces, and (5) dynamics. The work we review illustrates the progress and promise that population neurophysiology holds for cognitive neuroscience$-$for delivering new insight into attention, working memory, decision-making, executive function, learning, and reward processing.

Chen Cheng, Zsuzsa Kaldy, Erik Blaser

Attention turns looking, into seeing. Yet, little developmental research has examined the interface of attention and visual working memory (VWM), where what is seen is maintained for use in ongoing visual tasks. Using the task-evoked pupil response – a sensitive, real-time, involuntary measure of focused attention that has been shown to correlate with VWM performance in adults and older children – we examined the relationship between focused attention and VWM in 13-month-olds. We used a Delayed Match Retrieval paradigm, to test infants’ VWM for object-location bindings – what went where – while recording anticipatory gaze responses and pupil dilation. We found that infants with greater focused attention during memory encoding showed significantly better memory performance. As well, trials that ended in a correct response had significantly greater pupil response during memory encoding than incorrect trials. Taken together, this shows that pupillometry can be used as a measure of focused attention in infants, and a means to identify those individuals, or moments, where cognitive effort is maximized. Keywords: Visual working memory, Focused attention, Pupillometry, Task-evoked pupil responses, Infants, Cognitive effort, Eye-tracking

Jonathan R. Burgos, Britt-Marie Iresjö, Linda Olsson et al.

Abstract Background The aim was to examine the impact of lipopolysaccharide-induced systemic inflammation on expression of mRNA for cocaine- and amphetamine-regulated transcript (CART) and the thyrotropin receptor (TSHR) and its ligands in CNS areas of relevance for feeding controls and metabolism. Lipopolysaccharide effects on plasma levels of TSH and CART peptides were also examined. Methods Lipopolysaccharide (150–200 μg/mouse) was injected in C57BL/6J mice and tissue and plasma samples taken after 24 h. To establish if plasma increase in CART peptide levels were prostanoid dependent, indomethacin was given via the drinking water beginning 48 h prior to LPS. We evaluated mRNA expression for CART, TSHR, TSHβ, and thyrostimulin in brain and pituitary extracts. Plasma levels of TSH, CARTp, and serum amyloid P component were analyzed by ELISA. Results Lipopolysaccharide suppressed TSHR mRNA expression in the arcuate nucleus and the pituitary. CART mRNA expression was reduced in the arcuate nucleus but elevated in the pituitary of mice treated with Lipopolysaccharide, whereas plasma TSH remained unchanged. Plasma CART peptide concentration increased after LPS treatment in a prostanoid-independent manner, and CART peptide levels correlated positively to degree of inflammation. Conclusions Our findings suggest that central and peripheral CART is affected by acute inflammation. Considering the role of the arcuate nucleus in feeding controls, our data highlight TSHR and CART as putative neuroendocrine signaling components that respond to inflammation, perhaps to maintain weight and metabolic homeostasis during states of disease.

Ting Qi, Gesa Schaadt, Angela D. Friederici

The humans’ brain asymmetry is observed in the early stages of life and known to change further with age. The developmental trajectory of such an asymmetry has been observed for language, as one of the most lateralized cognitive functions. However, it remains unclear how these age-related changes in structural asymmetry are related to changes in language performance. We collected longitudinal structural magnetic resonance imaging data of children from 5 to 6 years to investigate structural asymmetry development and its linkage to the improvement of language comprehension abilities. Our results showed substantial changes of language performance across time, which were associated with changes of cortical thickness asymmetry in the triangular part of the inferior frontal gyrus (IFG), constituting a portion of Broca’s area. This suggests that language improvement is influenced by larger cortical thinning in the left triangular IFG compared to the right. This asymmetry in children’s brain at age 5 and 6 years was further associated with the language performance at 7 years. To our knowledge, this is the first longitudinal study to demonstrate that children’s improvement in sentence comprehension seems to depend on structural asymmetry changes in the IFG, further highlighting its crucial role in language acquisition. Keywords: Language development, Sentence comprehension, Structural asymmetry, Cortical thickness, Longitudinal study

Zhiyao Tang, Liang Sun, Lu Cao et al.

We provide in this paper a comprehensive solution to the design, performance analysis, and optimization of a multi-antenna non-orthogonal multiple access (NOMA) system for multiuser downlink communications under a general limited channel state information (CSI) feedback framework for frequency division duplex mode. We design a general framework including user clustering, joint power and bits allocation, CSI quantization and feedback, signal superposition coding, transmit beamforming, and successive interference cancellation at receivers. Then, we conduct a mathematically strict performance analysis of the considered system, and obtain a closed-form lower bound on the ergodic rate of each user in terms of transmit power, CSI quantization accuracy and channel conditions. For exploiting the potentials of multiple-antenna techniques in NOMA systems, we jointly optimize two key parameters, i.e., transmit power and the number of feedback bits allocated to each user, and propose low-complexity closed-form solutions. Moreover, through asymptotic analysis, we reveal the interactions between the main system parameters and their impacts on the joint power and feedback bits allocation result, and hence show some guidelines on the system design. Finally, numerical results validate the correctness of our theoretical analysis and demonstrate the advantages of the proposed algorithms over the most related state of the art.