Visual form predictions facilitate auditory processing at the N1.

Auditory-visual (AV) events often involve a leading visual cue (e.g. auditory-visual speech) that allows the perceiver to generate predictions about the upcoming auditory event. Electrophysiological evidence suggests that when an auditory event is predicted, processing is sped up, i.e., the N1 component of the ERP occurs earlier (N1 facilitation). However, it is not clear (1) whether N1 facilitation is based specifically on predictive rather than multisensory integration and (2) which particular properties of the visual cue it is based on. The current experiment used artificial AV stimuli in which visual cues predicted but did not co-occur with auditory cues. Visual form cues (high and low salience) and the auditory-visual pairing were manipulated so that auditory predictions could be based on form and timing or on timing only. The results showed that N1 facilitation occurred only for combined form and temporal predictions. These results suggest that faster auditory processing (as indicated by N1 facilitation) is based on predictive processing generated by a visual cue that clearly predicts both what and when the auditory stimulus will occur.

The Processing of Attended and Predicted Sounds in Time.

Neural responses to an attended event are typically enhanced relative to those from an unattended one (attention enhancement). Conversely, neural responses to a predicted event are typically reduced relative to those from an unpredicted one (prediction suppression). What remains to be established is what happens with attended and predicted events. To examine the interaction between attention and prediction, we combined two robust paradigms developed for studying attention and prediction effects on ERPs into an orthogonal design. Participants were presented with sounds in attended or unattended intervals with onsets that were either predicted by a moving visual cue or unpredicted (no cue was provided). We demonstrated an N1 enhancement effect for attended sounds and an N1 suppression effect for predicted sounds; furthermore, an interaction between these effects was found that emerged early in the N1 (50-95 msec), indicating that attention enhancement only occurred when the sound was unpredicted. This pattern of results can be explained by the precision of the predictive cue that reduces the need for attention selection in the attended and predicted condition.

Using EEG and stimulus context to probe the modelling of auditory-visual speech.

We investigated whether internal models of the relationship between lip movements and corresponding speech sounds [Auditory-Visual (AV) speech] could be updated via experience. AV associations were indexed by early and late event related potentials (ERPs) and by oscillatory power and phase locking. Different AV experience was produced via a context manipulation. Participants were presented with valid (the conventional pairing) and invalid AV speech items in either a 'reliable' context (80% AVvalid items) or an 'unreliable' context (80% AVinvalid items). The results showed that for the reliable context, there was N1 facilitation for AV compared to auditory only speech. This N1 facilitation was not affected by AV validity. Later ERPs showed a difference in amplitude between valid and invalid AV speech and there was significant enhancement of power for valid versus invalid AV speech. These response patterns did not change over the context manipulation, suggesting that the internal models of AV speech were not updated by experience. The results also showed that the facilitation of N1 responses did not vary as a function of the salience of visual speech (as previously reported); in post-hoc analyses, it appeared instead that N1 facilitation varied according to the relative time of the acoustic onset, suggesting for AV events N1 may be more sensitive to the relationship of AV timing than form.

Visual speech form influences the speed of auditory speech processing.

An important property of visual speech (movements of the lips and mouth) is that it generally begins before auditory speech. Research using brain-based paradigms has demonstrated that seeing visual speech speeds up the activation of the listener's auditory cortex but it is not clear whether these observed neural processes link to behaviour. It was hypothesized that the very early portion of visual speech (occurring before auditory speech) will allow listeners to predict the following auditory event and so facilitate the speed of speech perception. This was tested in the current behavioural experiments. Further, we tested whether the salience of the visual speech played a role in this speech facilitation effect (Experiment 1). We also determined the relative contributions that visual form (what) and temporal (when) cues made (Experiment 2). The results showed that visual speech cues facilitated response times and that this was based on form rather than temporal cues.

Assessing health-related quality of life in gynecologic oncology: a systematic review of questionnaires and their ability to detect clinically important differences and change.

OBJECTIVES: Researchers wishing to assess the health-related quality of life (HRQoL) of women with gynecologic cancers have a range of questionnaires to choose from. In general, disease-, treatment-, or symptom-specific questionnaires are assumed to be better able to identify between-group differences (sensitivity) and changes over time (responsiveness) than are cancer-specific or generic questionnaires. However, little work has tested this assumption in oncology. We set out to (a) identify all multidimensional HRQoL questionnaires used in studies with women with gynecologic cancer and (b) evaluate their track records in identifying minimal clinically important differences (MCIDs), with a view to making recommendations. METHODS: We searched MEDLINE using the term quality of life and each gynecologic cancer type, as well as the names of identified questionnaires. We used 10% of the scale range as the threshold for an MCID. RESULTS: We identified 1 generic (SF-36/SF-12), 3 cancer-specific (European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire [EORTC QLQ] C30, Functional Assessment of Cancer Therapy-General [FACT-G], and short-form Cancer Rehabilitation Evaluation System [CARES-SF]), and 1 disease-specific (QOL-Ovarian Cancer Patient Version) HRQoL questionnaires and 5 disease-specific (QLQ-OV28, FACT-O for ovarian, QLQ-CX24, FACT-Cx for cervical and FACT-V for vulvar), 1 treatment-specific (FACT and Gynecologic Oncology Group-Ntx for neurotoxicity), and 2 symptom-specific (FACT-Anemia and Functional Assessment of Chronic Illness and Therapy [FACIT]-Fatigue) modules. Twenty-seven articles reported results from 26 studies in which an MCID had been identified. The FACIT's anemia and fatigue subscales were more sensitive, and the neurotoxicity subscale more sensitive and responsive than the FACT-G on at least 1 comparison. However, we found no evidence for superior performance by the FACT-G compared with the SF-36 or EORTC and FACIT disease-specific modules versus the QLQ-C30 and FACT-G. There was also little evidence to favor EORTC versus FACIT questionnaires or vice versa. CONCLUSIONS: The evidence we reviewed offered little support for the hypothesis that disease-, symptom-, or treatment-specific instruments are more sensitive and responsive than cancer-specific or generic questionnaires. However, conclusions were limited by the small number of head-to-head comparisons available. We summarize the clinical contexts in which each instrument identified an MCID to inform choice of questionnaire(s), sample size calculations, and interpretation of results in future studies.