Dental treatment as perceived etiology of temporomandibular disorders

ABSTRACT

Objective: To characterize patients who believe their temporomandibular disorders (TMD) symptoms are caused by their prior dental treatment.

Methods: A sample of 337 patients were selected and classified into dental treatment-related and non-dental treatment-related groups, according to their personal belief of their TMD etiology. The relationship between patients’ perceived etiology and patient characterization was analyzed using Chi-square and t-test.

Results: One-hundred and thirty-one patients perceived that the cause of their TMD was dental-related. Within this group, 27.5% of the 131 patients considered that their TMD was specifically caused by prior dental treatment. These patients possessed significantly greater disability (self-reported work disability, family interference, and higher level of depression) compared to the patients who did not believe their TMD was caused by dental treatment.

Conclusion: Dentists should recognize that their dental treatments could possibly be the cause of patients’ TMD symptoms, according to patients’ beliefs.     

护理管理者领导力现状调查及影响因素分析

目的：调查护理管理者领导力现状,并分析其影响因素。方法采用管理者实践量表、一般自我效能感量表、职业倦怠量表、角色认知量表对浙江省210名护理管理者进行问卷调查。结果共发放问卷210份,回收有效问卷182份,有效回收率为86．67％。本组护理管理者的领导力得分为（37．70±5．30）分;是否经常阅读管理书籍、是否参与护士长的分层培训、任命方式以及是否经过护士长岗前培训的护理管理者的领导力得分情况比较,差异有统计学意义（t值分别为－3．608,－7．136,2．343,－2．511;P＜0．05）。领导力与角色认知中的角色模糊、自我效能感以及职业倦怠中的个人成就感均呈正相关,与角色认知中的角色冲突以及职业倦怠中的情绪枯竭、去人格化因子呈负相关（ r值分别为0．589,0.521,0．509,－0．323,－0．291,－0．227;P＜0．01）。多元线性回归分析显示,角色认知中的角色模糊因子、是否参加护士长分层培训、职业倦怠中的个人成就感因子、自我效能感和是否阅读管理书籍为领导力的影响因素（P＜0．05）。结论领导力与护士长的角色认知、自我效能感、职业倦怠及是否分层培训均相关。管理者的分层培训有利于领导力的培养和提升,明确角色定位、降低职业倦怠和提高自我效能感同样可以提升护士长的领导力,另外护理管理者需加强经济管理学方面的知识培训。     

Clinical evaluation of music perception,appraisal and experience in cochlear implant users

Objectives: The objectives were to evaluate the relationships among music perception, appraisal, and experience in cochlear implant users in multiple clinical settings and to examine the viability of two assessments designed for clinical use. Design: Background questionnaires (IMBQ) were administered by audiologists in 14 clinics in the United States and Canada. The CAMP included tests of pitch-direction discrimination, and melody and timbre recognition. The IMBQ queried users on prior musical involvement, music listening habits pre and post implant, and music appraisals. Study sample: One-hundred forty-five users of Advanced Bionics and Cochlear Ltd cochlear implants. Results: Performance on pitch direction discrimination, melody recognition, and timbre recognition tests were consistent with previous studies with smaller cohorts, as well as with more extensive protocols conducted in other centers. Relationships between perceptual accuracy and music enjoyment were weak, suggesting that perception and appraisal are relatively independent for CI users. Conclusions: Perceptual abilities as measured by the CAMP had little to no relationship with music appraisals and little relationship with musical experience. The CAMP and IMBQ are feasible for routine clinical use, providing results consistent with previous thorough laboratory-based investigations.     

An Italian matrix sentence test for the evaluation of speech intelligibility in noise

Objective: Development of an Italian matrix sentence test for the assessment of speech intelligibility in noise. Design: The development of the test included the selection, recording, optimization with level adjustment, and evaluation of speech material. The training effect was assessed adaptively during the evaluation measurements with six lists of 20 sentences, using open- and closed-set response formats. Reference data were established for normal-hearing listeners with adaptive measurements. Equivalence of the test lists was investigated using the open-set response format at three signal-to-noise ratios (SNRs). Study sample: A total of 55 normal-hearing Italian mother-tongue listeners. Results: The evaluation measurements at fixed SNRs resulted in a mean speech reception threshold (SRT) of ? 7.3 ± 0.2 dB SNR and slope of 13.3 ± 1.2 %/dB. The major training effect of 1.5 dB was observed for the first two consecutive measurements. Mean SRTs of ? 6.7 ± 0.7 dB SNR and ? 7.4 ± 0.7 dB SNR were found from the third to the sixth adaptive measurement for open- and closed-set test response formats, respectively. Conclusions: A good agreement has been found between the SRTs and slope and those of other matrix tests. Since sentences are difficult to memorize, the Italian matrix test is suitable for repeated measurements.     

Distinct neural ensemble response statistics are associated with recognition and discrimination of natural sound textures

The perception of sound textures, a class of natural sounds defined by statistical sound structure such as fire, wind, and rain, has been proposed to arise through the integration of time-averaged summary statistics. Where and how the auditory system might encode these summary statistics to create internal representations of these stationary sounds, however, is unknown. Here, using natural textures and synthetic variants with reduced statistics, we show that summary statistics modulate the correlations between frequency organized neuron ensembles in the awake rabbit inferior colliculus (IC). These neural ensemble correlation statistics capture high-order sound structure and allow for accurate neural decoding in a single trial recognition task with evidence accumulation times approaching 1 s. In contrast, the average activity across the neural ensemble (neural spectrum) provides a fast (tens of milliseconds) and salient signal that contributes primarily to texture discrimination. Intriguingly, perceptual studies in human listeners reveal analogous trends: the sound spectrum is integrated quickly and serves as a salient discrimination cue while high-order sound statistics are integrated slowly and contribute substantially more toward recognition. The findings suggest statistical sound cues such as the sound spectrum and correlation structure are represented by distinct response statistics in auditory midbrain ensembles, and that these neural response statistics may have dissociable roles and time scales for the recognition and discrimination of natural sounds.

What makes a sound natural, and what are the neural codes that support recognition and discrimination of real-world natural sounds? Although it is known that the early auditory system decomposes sounds along fundamental acoustic dimensions such as intensity and frequency, the higher-level neural computations that mediate natural sound recognition are poorly understood. This general lack of understanding is in part attributed to the structural complexity of natural sounds, which is difficult to study with traditional auditory test stimuli, such as tones, noise, or modulated sequences. Such stimuli can reveal details of the neural representation for relatively low-level acoustic cues, yet they don’t capture the rich and diverse statistical structure of natural sounds. Thus, they cannot reveal many of the computations associated with higher-level sound properties that facilitate auditory tasks such as natural sound recognition or discrimination. A class of stationary natural sounds termed textures, such as the random sounds emanating from a running stream, a crowded restaurant, or a chorus of birds, have been proposed as alternative natural stimuli which allow for manipulating high-level acoustic structure (1). Texture sounds are composed of spatially and temporally distributed acoustic elements that are collectively perceived as a single source and are defined by their statistical features. Identification of these natural sounds has been proposed to be mediated through the integration of time-averaged summary statistics, which account for high-level structures such as the sparsity and time-frequency correlation structure found in many natural sounds (1–3). Using a generative model of the auditory system to measure summary statistics from natural texture sounds, it is possible to synthesize highly realistic synthetic auditory textures (1). This suggests that high-order statistical cues are perceptually salient and that the brain might extract these statistical features to build internal representations of sounds.Although neural activity throughout the auditory pathway is sensitive to a variety of statistical cues such as the sound contrast, modulation power spectrum, and correlation structure (4–12), how sound summary statistics contribute toward basic auditory tasks such as recognition and discrimination of sounds is poorly understood. Furthermore, it is unclear where along the auditory pathway summary statistics are represented and how they are reflected in neural activity. The inferior colliculus (IC) is one candidate midlevel structure for representing such summary statistics. As the principal midbrain auditory nucleus, the IC receives highly convergent brainstem inputs with varied sound selectivities. Neurons in the IC are selective over most of the perceptually relevant range of sound modulations and neural activity is strongly driven by multiple high-order sound statistics (4–7, 10). In previous work, we showed the correlation statistics of natural sounds are highly informative about stimulus identity and they appear to be represented in the correlation statistics of auditory midbrain neuron ensembles (4). Correlations between neurons have also been proposed as mechanisms for pitch identification (13) and sound localization (14). This broadly supports the hypotheses that high-order sound statistics are reflected in the response statistics of neural ensembles and that these neural response statistics could potentially subserve basic auditory tasks.Here using natural and synthetic texture sounds, we test the hypothesis that statistical structure in natural texture sounds modulates the response statistics of neural ensembles in the IC of unanesthetized rabbits, and that distinct neural response statistics have the potential to contribute toward sound recognition and discrimination behaviors. By comparing the performance of neural decoders with human texture perception, we find that place rate representation of sounds (neural spectrum) accumulates evidence about the sounds on relatively fast time scales (tens of milliseconds) exhibiting decoding trends that mirror those seen for human texture discrimination. High-order statistical sound cues, by comparison, are reflected in the correlation statistics of neural ensembles, which require substantially longer evidence accumulation times (>500 ms) and follow trends that mirror those measured for human texture recognition. Collectively, the findings suggest that spectrum cues and accompanying place rate representation (neural spectrum) may contribute surprisingly little toward the recognition of auditory textures. Instead, high-order statistical sound structure is reflected in the distributed patterns of correlated activity across IC neural ensembles and such neural response structure has the potential to contribute toward the recognition of natural auditory textures.     

Real-time modulation of visual feedback on human full-body movements in a virtual mirror: development and proof-of-concept

Background

Virtual reality (VR) provides interactive multimodal sensory stimuli and biofeedback, and can be a powerful tool for physical and cognitive rehabilitation. However, existing systems have generally not implemented realistic full-body avatars and/or a scaling of visual movement feedback. We developed a “virtual mirror” that displays a realistic full-body avatar that responds to full-body movements in all movement planes in real-time, and that allows for the scaling of visual feedback on movements in real-time. The primary objective of this proof-of-concept study was to assess the ability of healthy subjects to detect scaled feedback on trunk flexion movements.

Methods

The “virtual mirror” was developed by integrating motion capture, virtual reality and projection systems. A protocol was developed to provide both augmented and reduced feedback on trunk flexion movements while sitting and standing. The task required reliance on both visual and proprioceptive feedback. The ability to detect scaled feedback was assessed in healthy subjects (n = 10) using a two-alternative forced choice paradigm. Additionally, immersion in the VR environment and task adherence (flexion angles, velocity, and fluency) were assessed.

Results

The ability to detect scaled feedback could be modelled using a sigmoid curve with a high goodness of fit (R² range 89-98%). The point of subjective equivalence was not significantly different from 0 (i.e. not shifted), indicating an unbiased perception. The just noticeable difference was 0.035 ± 0.007, indicating that subjects were able to discriminate different scaling levels consistently. VR immersion was reported to be good, despite some perceived delays between movements and VR projections. Movement kinematic analysis confirmed task adherence.

Conclusions

The new “virtual mirror” extends existing VR systems for motor and pain rehabilitation by enabling the use of realistic full-body avatars and scaled feedback. Proof-of-concept was demonstrated for the assessment of body perception during active movement in healthy controls. The next step will be to apply this system to assessment of body perception disturbances in patients with chronic pain.