Search

Mapping the relationship between neural activity and motor behavior is a central aim of sensorimotor neuroscience and neurotechnology. While most progress to this end has relied on restricting complexity, the advent of foundation models instead proposes integrating a breadth of data as an alternate avenue for broadly advancing downstream modeling. We quantify this premise for motor decoding from intracortical microelectrode data, pretraining an autoregressive Transformer on 2000 hours of neural population spiking activity paired with diverse motor covariates from over 30 monkeys and humans. The resulting model is broadly useful, benefiting decoding on 8 downstream decoding tasks and generalizing to a variety of neural distribution shifts. However, we also highlight that scaling autoregressive Transformers seems unlikely to resolve limitations stemming from sensor variability and output stereotypy in neural datasets. Code: https://github.com/joel99/ndt3.

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal's control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject's control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination., Competing Interests: MS, RS, SB, RC, AB, PL, DS No competing interests declared, (© 2023, Sadeghi, Sharif Razavian et al.)

The most prominent characteristic of motor cortex is its activation during movement execution, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioural and imaging studies, it is unknown how the specific activity patterns and temporal dynamics in motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people who retain some residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population activity into three orthogonal subspaces, where one was similarly active during both action and imagery, and the others were active only during a single task type-action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamic features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by reorienting the components related to motor output and/or feedback into a unique, output-null imagery subspace., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

The molecular mechanism of COVID-19's pathogenic effects in leukemia patients is still poorly known. Our study investigated the possible disease mechanism of COVID-19 and its associated risk factors in patients with leukemia utilizing differential gene expression analysis. We also employed network-based approaches to identify molecular targets that could potentially diagnose and treat COVID-19-infected leukemia patients. Our study demonstrated a shared set of 60 genes that are expressed differentially among patients with leukemia and COVID-19. Most of these genes are expressed in blood and bone marrow tissues and are predominantly implicated in the pathogenesis of different hematologic malignancies, increasingly imperiling COVID-19 morbidity and mortality among the affected patients. Additionally, we also found that COVID-19 may influence the expression of several cancer-associated genes in leukemia patients, such as CCR7, LEF1, and 13 candidate cancer-driver genes. Furthermore, our findings reveal that COVID-19 may predispose leukemia patients to altered blood homeostasis, increase the risk of COVID-19-related liver injury, and deteriorate leukemia-associated injury and patient prognosis. Our findings imply that molecular signatures, like transcription factors, proteins such as TOP21, and 25 different microRNAs, may be potential targets for diagnosing and treating COVID-19-infected leukemia patients. Nevertheless, additional experimental studies will contribute to further validating the study's findings., Competing Interests: Conflict of interest disclosure: The authors declare that they have no conflict of interest regarding the publication of the paper., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Leukocyte Biology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Arsenic contamination is a global health concern, primarily through contaminated groundwater and its entry into the food chain. The association between arsenic exposure and cardiovascular diseases (CVDs) is particularly alarming due to CVDs being the leading cause of death worldwide. Arsenic exposure has also been linked to changes in telomere length, mitochondrial DNA copy number (mtDNAcn), and deletion, further increasing the risk of CVDs. We aimed to determine whether arsenic exposure alters telomere length and mtDNAcn and deletion in a total of 50 CVD patients who underwent open heart surgery hailed from known arsenic-affected and unaffected areas in Bangladesh. Amount of arsenic was determined from the collected nails and cardiac tissues. Relative telomere length and mtDNAcn and deletion were quantified by qRT-PCR. The patients from arsenic-contaminated areas had higher average arsenic deposits in their fingers and toenails (P < 0.05) and higher cardiac tissue injury scores (P < 0.05). Moreover, approximately 1.5-fold shorter telomere length (P < 0.05, r =  - 0.775), 1.2-fold decreased mtDNAcn (P < 0.05, r = - 0.797), and an 81-fold higher amount of mitochondrial DNA deletion (P < 0.05, r = 0.784) were observed in the patients who had higher arsenic deposition in their nails. Higher levels of arsenic exposure were found to be linked to shorter telomere length, decreased mtDNAcn, and increased mitochondrial DNA deletion in the patients from As-affected areas. It can also be anticipated that the correlation of arsenic exposure with telomere length, mtDNAcn, and deletion can be used as biomarkers for early diagnosis of arsenic-induced cardiovascular diseases., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Plants have diverse molecular mechanisms to protect themselves from biotic and abiotic stressors and adapt to changing environments. To uncover the genetic potential of plants, it is crucial to understand how they adapt to adverse conditions by analyzing their genomic data. We analyzed RNA-Seq data from different tomato genotypes, tissue types, and drought durations. We used a time series scale to identify early and late drought-responsive gene modules and applied a machine learning method to identify the best responsive genes to drought. We demonstrated six candidate genes of tomato viz. Fasciclin-like arabinogalactan protein 2 (FLA2), Amino acid transporter family protein (ASCT), Arginine decarboxylase 1 (ADC1), Protein NRT1/PTR family 7.3 (NPF7.3), BAG family molecular chaperone regulator 5 (BAG5) and Dicer-like 2b (DCL2b) were responsive to drought. We constructed gene association networks to identify their potential interactors and found them drought-responsive. The identified candidate genes can help to explore the adaptation of tomato plants to drought. Furthermore, these candidate genes can have far-reaching implications for molecular breeding and genome editing in tomatoes, providing insights into the molecular mechanisms that underlie drought adaptation. This research underscores the importance of the genetic basis of plant adaptation, particularly in changing climates and growing populations., (© 2023. The Author(s).)

The most prominent role of motor cortex is generating patterns of neural activity that lead to movement, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioral and imaging studies, it is unknown how the specific activity patterns and temporal dynamics within motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people with residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population-level activity into orthogonal subspaces such that one set of components was similarly active during both action and imagery, and others were only active during a single task typeâ€"action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamical features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by recreating the missing components related to motor output and/or feedback within a unique imagery-only subspace.

Achieving state-of-the-art performance with deep neural population dynamics models requires extensive hyperparameter tuning for each dataset. AutoLFADS is a model-tuning framework that automatically produces high-performing autoencoding models on data from a variety of brain areas and tasks, without behavioral or task information. We demonstrate its broad applicability on several rhesus macaque datasets: from motor cortex during free-paced reaching, somatosensory cortex during reaching with perturbations, and dorsomedial frontal cortex during a cognitive timing task., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Animals rapidly adapt their movements to external perturbations, a process paralleled by changes in neural activity in the motor cortex. Experimental studies suggest that these changes originate from altered inputs (H input ) rather than from changes in local connectivity (H local ), as neural covariance is largely preserved during adaptation. Since measuring synaptic changes in vivo remains very challenging, we used a modular recurrent neural network to qualitatively test this interpretation. As expected, H input resulted in small activity changes and largely preserved covariance. Surprisingly given the presumed dependence of stable covariance on preserved circuit connectivity, H local led to only slightly larger changes in activity and covariance, still within the range of experimental recordings. This similarity is due to H local only requiring small, correlated connectivity changes for successful adaptation. Simulations of tasks that impose increasingly larger behavioural changes revealed a growing difference between H input and H local , which could be exploited when designing future experiments., (© 2022. The Author(s).)

The spiking activity of populations of cortical neurons is well described by the dynamics of a small number of population-wide covariance patterns, whose activation we refer to as 'latent dynamics'. These latent dynamics are largely driven by the same correlated synaptic currents across the circuit that determine the generation of local field potentials (LFPs). Yet, the relationship between latent dynamics and LFPs remains largely unexplored. Here, we characterised this relationship for three different regions of primate sensorimotor cortex during reaching. The correlation between latent dynamics and LFPs was frequency-dependent and varied across regions. However, for any given region, this relationship remained stable throughout the behaviour: in each of primary motor and premotor cortices, the LFP-latent dynamics correlation profile was remarkably similar between movement planning and execution. These robust associations between LFPs and neural population latent dynamics help bridge the wealth of studies reporting neural correlates of behaviour using either type of recordings., Competing Interests: CG, MP, RC, LM, JG No competing interests declared, (© 2022, Gallego-Carracedo et al.)

Much remains unknown about the transformation of proprioceptive afferent input from the periphery to the cortex. Until recently, the only recordings from neurons in the cuneate nucleus (CN) were from anesthetized animals. We are beginning to learn more about how the sense of proprioception is transformed as it propagates centrally. Recent recordings from microelectrode arrays chronically implanted in CN have revealed that CN neurons with muscle-like properties have a greater sensitivity to active reaching movements than to passive limb displacement, and we find that these neurons have receptive fields that resemble single muscles. In this review, we focus on the varied uses of proprioceptive input and the possible role of CN in processing this information., Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Inorganic arsenic (iAs) exposure has been reported to have an impact on cardiovascular diseases (CVD). However, there is not much known about the cardiac tissue injury of CVD patients in relation to iAs exposure and potential role of single nucleotide polymorphisms (SNPs) of genes related to iAs metabolism, oxidative stress, endothelial dysfunction and inflammation which may play important roles in such CVD cases. In this dual center cross-sectional study, based on the exclusion and inclusion criteria, we have recruited 50 patients out of 270, who came from known arsenic-affected and- unaffected areas of mainly Chittagong, Dhaka and Rajshahi divisions of Bangladesh and underwent open-heart surgery at the selected centers during July 2017 to June 2018. We found that the patients from arsenic affected areas contained significantly higher average iAs concentrations in their urine (6.72 ± 0.54 ppb, P = 0.028), nail (529.29 ± 38.76 ppb, P < 0.05) and cardiac tissue (4.83 ± 0.50 ppb, P < 0.05) samples. Patients' age, sex, BMI, hypertension and diabetes status adjusted analysis showed that patients from arsenic-affected areas had significantly higher iAs concentration in cardiac tissue (2.854, 95%CI 1.017-8.012, P = 0.046) reflecting higher cardiac tissue injury among them (1.831, 95%CI 1.032-3.249, P = 0.039), which in turn allowed the analysis to assume that the iAs exposure have played a vital role in patients' disease condition. Adjusted analysis showed significant association between urinary iAs concentration with AA (P = 0.012) and AG (P = 0.034) genotypes and cardiac iAs concentration with AA (P = 0.017) genotype of AS3MT rs10748835. The AG genotype of AS3MT rs10748835 (13.333 95%CI 1.280-138.845, P = 0.013), AA genotype of NOS3 rs3918181 (25.333 95%CI 2.065-310.757, P = 0.002), GG genotype of ICAM1 rs281432 (12.000 95%CI 1.325-108.674, P = 0.010) and AA genotype of SOD2 rs2758331 (13.333 95%CI 1.280-138.845, P = 0.013) were found significantly associated with CVD patients from arsenic-affected areas. Again, adjusted analysis showed significant association of AA genotype of AS3MT rs10748835 with CVD patients from arsenic affected areas. In comparison to the reference genotypes of the selected SNPs, AA of AS3MT 10748835, AG of NOS3 rs3918181 and AC of rs3918188, GG of ICAM1 rs281432, TT of VCAM1 rs3176867, AA of SOD2 rs2758331 and GT of APOE rs405509 significantly increased odds of cardiac tissue injury of CVD patients from arsenic affected areas. The results showed that the selected SNPs played a susceptibility role towards cardiac tissue iAs concentration and injury among CVD patients from iAs affected areas.

Backgrounds: Approximately, half of the population in the world including tropical and sub-tropical climates region is at risk of dengue. Being an endemic country, Bangladesh has experienced the largest dengue epidemic in 2019. The present study aimed at evaluating the clinical and laboratory profile of dengue patients in northern Bangladesh during the epidemic., Methods: This cross-sectional study included 319 serologically confirmed dengue patients admitted in Shaheed Ziaur Rahman Medical College Hospital in Bogra district. It is one of the main tertiary care hospitals in northern Bangladesh. Data were collected from July to September 2019. Patients' clinical and laboratory data were extracted from clinical records. Patients were classified into two classes according to the WHO 2009 dengue classification such as (i) non-severe dengue and (ii) severe dengue. Chi-square test and independent t-test were used in this study., Results: Of the 319 patients, 94.1% had non-severe dengue and the remaining 5.9% had severe dengue (severe plasma leakage 68.4%, severe organ involvement 68.4%, and severe clinical bleeding 10.5%). Most of the patients were suffering from primary dengue infection. The most common clinical presentation was fever followed by headache and myalgia. Vomiting and abdominal pain were the most prevalent warning signs. The common hematological findings on admission were leukopenia (63.3%), thrombocytopenia (30.4%) and increased hematocrit (26.6%). Raised serum ALT or AST was observed in 14.1% cases whereas raised serum creatinine was observed in 6.6% cases. Signs of plasma leakage (pleural effusion, respiratory distress, and ascites, rise of hematocrit >20% during hospital stay) and hepatic or renal involvement (serum ALT >42UI/L or serum creatinine >1.2 mg/dL) on admission were mostly associated with severe dengue., Conclusion: The study provides clinical evidence on presentation as well as hematological and biochemical profile of dengue patients in northern Bangladesh that should be implicated in effective patient management., Competing Interests: The authors have declared that no competing interests exist.

We would like to describe the clinical course of a 61-year-old gentleman with the background history of Stage IV left lower lobe lung adenocarcinoma who presented to the outpatient department at Changi General Hospital, Singapore on March 2019 with unintentional loss of weight, easy fatigability and breast pain while showering for last four months. He was started on pembrolizumab immunotherapy about 9 months before presentation which he tolerated well. Subsequent endocrine work ups revealed features consistent with hypophysitis that lead to hypopituitarism in the form of secondary adrenal insufficiency and hypothyroidism. While more and more patients are receiving novel anti-cancer treatment for example immunotherapy, we should never forget and address the side effects it brings along. This study certainly supports above mentioned suggestion.

Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve decoding performance. This tutorial describes how to effectively apply these algorithms for typical decoding problems. We provide descriptions, best practices, and code for applying common machine learning methods, including neural networks and gradient boosting. We also provide detailed comparisons of the performance of various methods at the task of decoding spiking activity in motor cortex, somatosensory cortex, and hippocampus. Modern methods, particularly neural networks and ensembles, significantly outperform traditional approaches, such as Wiener and Kalman filters. Improving the performance of neural decoding algorithms allows neuroscientists to better understand the information contained in a neural population and can help to advance engineering applications such as brain-machine interfaces. Our code package is available at github.com/kordinglab/neural&#95;decoding., (Copyright © 2020 Glaser et al.)

Animals readily execute learned behaviors in a consistent manner over long periods of time, and yet no equally stable neural correlate has been demonstrated. How does the cortex achieve this stable control? Using the sensorimotor system as a model of cortical processing, we investigated the hypothesis that the dynamics of neural latent activity, which captures the dominant co-variation patterns within the neural population, must be preserved across time. We recorded from populations of neurons in premotor, primary motor and somatosensory cortices as monkeys performed a reaching task, for up to 2 years. Intriguingly, despite a steady turnover in the recorded neurons, the low-dimensional latent dynamics remained stable. The stability allowed reliable decoding of behavioral features for the entire timespan, while fixed decoders based directly on the recorded neural activity degraded substantially. We posit that stable latent cortical dynamics within the manifold are the fundamental building blocks underlying consistent behavioral execution.

Proprioception, the sense of body position, movement, and associated forces, remains poorly understood, despite its critical role in movement. Most studies of area 2, a proprioceptive area of somatosensory cortex, have simply compared neurons' activities to the movement of the hand through space. Using motion tracking, we sought to elaborate this relationship by characterizing how area 2 activity relates to whole arm movements. We found that a whole-arm model, unlike classic models, successfully predicted how features of neural activity changed as monkeys reached to targets in two workspaces. However, when we then evaluated this whole-arm model across active and passive movements, we found that many neurons did not consistently represent the whole arm over both conditions. These results suggest that 1) neural activity in area 2 includes representation of the whole arm during reaching and 2) many of these neurons represented limb state differently during active and passive movements., Competing Interests: RC, JG, LM No competing interests declared, (© 2020, Chowdhury et al.)

We are going to report a case study of dengue fever (DF) affecting myocardium and explore the literature. A gentleman of 28 years old experienced DF which was complicated by acute myocarditis, acute kidney injury and hepatitis in the Emergency Department of Apollo Hospitals, Dhaka, Bangladesh on 5th August 2017. Clinically it was considered as an acute coronary syndrome due to depressed ST segment in chest leads ECG, extreme bradycardia but normal serum troponin-I level. He had to undergo temporary pacemaker insertion for symptomatic bradycardia and later on, he was monitored closely. Fortunately, he recovered; pacemaker was removed on day 8 of his admission without any further complication. After 3 days, patient recovered with symptomatic treatment. In different publications, various manifestations of cardiac complications occurred, from self-limiting tachy-brady arrhythmia to severe damage of the myocardium, causing reduced blood pressure and pulmonary edema. To reduce morbidity and mortality, physicians should suspect for cardiac complications in patients with dengue fever and should manage these complications.

Neuroscience has long focused on finding encoding models that effectively ask "what predicts neural spiking?" and generalized linear models (GLMs) are a typical approach. It is often unknown how much of explainable neural activity is captured, or missed, when fitting a model. Here we compared the predictive performance of simple models to three leading machine learning methods: feedforward neural networks, gradient boosted trees (using XGBoost), and stacked ensembles that combine the predictions of several methods. We predicted spike counts in macaque motor (M1) and somatosensory (S1) cortices from standard representations of reaching kinematics, and in rat hippocampal cells from open field location and orientation. Of these methods, XGBoost and the ensemble consistently produced more accurate spike rate predictions and were less sensitive to the preprocessing of features. These methods can thus be applied quickly to detect if feature sets relate to neural activity in a manner not captured by simpler methods. Encoding models built with a machine learning approach accurately predict spike rates and can offer meaningful benchmarks for simpler models.

Proprioception, the sense of limb position and motion, arises from individual muscle receptors. An important question is how and where in the neuroaxis our high level "extrinsic" sense of limb movement originates. In the 1990s, a series of papers detailed the properties of neurons in the dorsal spinocerebellar tract (DSCT) of the cat. Despite their direct projections from sensory receptors, it appeared that half of these neurons had consistent, high-level tuning to paw position rather than to joint angles (or muscle lengths). These results suggested that many DSCT neurons compute paw position from lower level sensory information. We examined the contribution of musculoskeletal geometry to this apparent extrinsic representation by simulating a three-joint hindlimb with mono- and biarticular muscles, each providing a muscle spindlelike signal, modulated by the muscle length. We simulated neurons driven by randomly weighted combinations of these signals and moved the paw to different positions under two joint-covariance conditions similar to the original experiments. Our results paralleled those experiments in a number of respects: 1 ) Many neurons were tuned to paw position relative to the hip under both conditions. 2 ) The distribution of tuning was strongly bimodal, with most neurons driven by whole-leg flexion or extension. 3 ) The change in tuning between conditions clustered around zero (median absolute change ~20°). These results indicate that, at least for these constraint conditions, extrinsic-like representation can be achieved simply through musculoskeletal geometry and convergent muscle length inputs. Consequently, they suggest a reinterpretation of the earlier results may be required. NEW & NOTEWORTHY A classic experiment concluding that many dorsal spinocerebellar tract neurons encode paw position rather than joint angles has been cited by many studies as evidence for high-level computation occurring within a single synapse of the sensors. However, our study provides evidence that such a computation is not required to explain the results. Using simulation, we replicated many of the original results with purely random connectivity, suggesting that a reinterpretation of the classic experiment is needed., (Copyright © 2017 the American Physiological Society.)

Stroke is a leading cause of death and disability worldwide. While the immediate consequence of stroke include permanent cognitive deficits, paralysis, visual impairment and sensory disturbances; stroke also results in long term dysregulation of sleep and mood, which may be equally disabling. The influence of ischemic stroke on circadian rhythm regulation, which is strongly linked to sleep and mood, may thus potentially influence long term recovery in stroke patients. Stroke induces immediate changes in the timing of pineal melatonin secretion, indicating that cortical and basal ganglia infarction impacts the timing of melatonin rhythms. This study was done to find out the time of onset of most of the ischemic stroke attack and to determine the outcome of ischemic stroke during hospital stay. All ischemic stroke patients admitted in Medicine wards in Comilla Medical College Hospital during the period of 1st November 2010 to 30th April 2011 included in this study. After admission, a careful history and a thorough clinical examination was carried out. Data collection was done on a preset questionnaire which involved to identify the risk factors, the time of onset of ischemic stroke, and outcome during hospital stay. All the cases were investigated. Among the 50 ischemic stroke patients, 68% were male and 32% female. Maximum age groups were 61-70 years (50%). By occupational category, maximum were retired persons (46%); 68% were hypertensive, 38% smoker and 16% had diabetes. Dyslipidemia was present in 44% patients. Most of the ischemic stroke (44%) occurred in the morning to late morning (6:01AM-12:00PM) and majority (80%) of the patients was discharged with residual neurological dysfunction. This study supports the presence of a circadian pattern in the onset of ischemic stroke, with higher risk in the morning to late morning. Most of the patients were discharged with residual neurological dysfunction.

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.

Background: Evidence-based medicine has increasingly become an integral part of clinical research and practice. The purpose of this study was to assess the trends in the level of evidence in leading facial plastic surgery journals in recent years., Methods: All scientific articles within the field of facial plastic surgery published in The Laryngoscope, Archives of Facial Plastic Surgery, Otolaryngology-Head and Neck Surgery, Journal of Plastic Surgery, and Plastic and Reconstructive Surgery from 1999, 2002, 2005, and 2008 were rated for level of evidence. The presence of p values and confidence intervals was also noted., Results: Of 975 articles reviewed, 88 percent were clinical and 88 percent were therapy articles. Overall, there was an increase in the average level of evidence of articles published from 1999 to 2008. There was also a significant increase in the proportion of articles reporting p values and confidence intervals. However, the number of articles containing level 1 or 2 evidence remains low., Conclusions: With the increased demand for evidence-based medicine, facial plastic surgery literature has seen an overall increase in the quantity of higher level evidence research published. However, articles representing level 1 and 2 evidence remain rare.