Detecting Distal Radius Fractures Using a Segmentation-Based Deep Learning Model.

Deep learning algorithms can be used to classify medical images. In distal radius fracture treatment, fracture detection and radiographic assessment of fracture displacement are critical steps. The aim of this study was to use pixel-level annotations of fractures to develop a deep learning model for precise distal radius fracture detection. We randomly divided 3785 consecutive emergency wrist radiograph examinations from six hospitals to a training set (3399 examinations) and test set (386 examinations). The training set was used to develop the deep learning model and the test set to assess its validity. The consensus of three hand surgeons was used as the gold standard for the test set. The area under the ROC curve was 0.97 (CI 0.95-0.98) and 0.95 (CI 0.92-0.98) for examinations without a cast. Fractures were identified with higher accuracy in the postero-anterior radiographs than in the lateral radiographs. Our deep learning model performed well in our multi-hospital and multi-radiograph system manufacturer settings. Thus, segmentation-based deep learning models may provide additional benefit. Further research is needed with algorithm comparison and external validation.

Enhanced Memory Consolidation Via Automatic Sound Stimulation During Non-REM Sleep.

Introduction: Slow-wave sleep (SWS) slow waves and sleep spindle activity have been shown to be crucial for memory consolidation. Recently, memory consolidation has been causally facilitated in human participants via auditory stimuli phase-locked to SWS slow waves. Aims: Here, we aimed to develop a new acoustic stimulus protocol to facilitate learning and to validate it using different memory tasks. Most importantly, the stimulation setup was automated to be applicable for ambulatory home use. Methods: Fifteen healthy participants slept 3 nights in the laboratory. Learning was tested with 4 memory tasks (word pairs, serial finger tapping, picture recognition, and face-name association). Additional questionnaires addressed subjective sleep quality and overnight changes in mood. During the stimulus night, auditory stimuli were adjusted and targeted by an unsupervised algorithm to be phase-locked to the negative peak of slow waves in SWS. During the control night no sounds were presented. Results: Results showed that the sound stimulation increased both slow wave (p = .002) and sleep spindle activity (p < .001). When overnight improvement of memory performance was compared between stimulus and control nights, we found a significant effect in word pair task but not in other memory tasks. The stimulation did not affect sleep structure or subjective sleep quality. Conclusions: We showed that the memory effect of the SWS-targeted individually triggered single-sound stimulation is specific to verbal associative memory. Moreover, the ambulatory and automated sound stimulus setup was promising and allows for a broad range of potential follow-up studies in the future.

Acquisition and consolidation of novel morphology in human neocortex: A neuromagnetic study.

Research into neurobiological mechanisms of morphosyntactic processing of language has suggested specialised systems for decomposition and storage, which are used flexibly during the processing of complex polymorphemic words (such as those formed through affixation, e.g., boy + s = noun + plural marker or boy + ish = noun plus attenuator). However, neural underpinnings of acquisition of novel morphology are still unknown. We implicitly trained our participants with new derivational affixes through a word-picture association task and investigated the neural processes underlying formation of neural memory traces for new affixes. The participants' brain activity was recorded using magnetoencephalography (MEG), as they passively listened to the newly trained and untrained suffixes combined with real word and pseudoword stems. The MEG recording was repeated after a night's sleep using the same stimuli, to test the effects of overnight consolidation. The newly trained suffixes combined with real stems elicited stronger source activity in the left inferior frontal gyrus (LIFG) at ∼50 msec after the suffix onset than untrained suffixes, suggesting memory trace formation for the newly learned suffixes already on the same day. The following day, the suffix learning effect spread to the left superior temporal gyrus (STG) where it was again manifest as a response enhancement, particularly at ∼200-300 msec after the suffix onset, which might reflect an additional effect of overnight consolidation. Overall, the results demonstrate the rapid and dynamic processes of both immediate build-up and longer-term consolidation of neocortical memory traces for novel morphology, taking place after a short period of exposure to novel morphology and involving fronto-temporal perisylvian language circuitry.

Time course of the neural processing of spoken derived words: an event-related potential study.

Event-related potentials were recorded to examine the time course of the neural processing of spoken (i) existing derived words, (ii) morphologically legal, and (iii) illegal pseudowords in the Finnish language. The stimuli were matched by (complex) uniqueness/deviation points and event-related potentials were time-locked to stimulus onset and suffix onset. Illegal pseudowords elicited a larger negativity than existing words approximately 300 ms after suffix onset, suggesting a difficulty to semantically integrate morphemes. The magnitude of the negativity effect was similar for legal pseudowords and existing words, reflecting successful licensing and integration of morphemes for legal pseudowords. The results suggest parallel full-form and morpheme-based processing of spoken derived stimuli and emphasize the role of semantic interpretability in morphological parsing.

A compact electroencephalogram recording device with integrated audio stimulation system.

A compact (96 x 128 x 32 mm(3), 374 g), battery-powered, eight-channel electroencephalogram recording device with an integrated audio stimulation system and a wireless interface is presented. The recording device is capable of producing high-quality data, while the operating time is also reasonable for evoked potential studies. The effective measurement resolution is about 4 nV at 200 Hz sample rate, typical noise level is below 0.7 microV(rms) at 0.16-70 Hz, and the estimated operating time is 1.5 h. An embedded audio decoder circuit reads and plays wave sound files stored on a memory card. The activities are controlled by an 8 bit main control unit which allows accurate timing of the stimuli. The interstimulus interval jitter measured is less than 1 ms. Wireless communication is made through bluetooth and the data recorded are transmitted to an external personal computer (PC) interface in real time. The PC interface is implemented with LABVIEW and in addition to data acquisition it also allows online signal processing, data storage, and control of measurement activities such as contact impedance measurement, for example. The practical application of the device is demonstrated in mismatch negativity experiment with three test subjects.

Development of a method to compensate for signal quality variations in repeated auditory event-related potential recordings.

Reliable measurements are mandatory in clinically relevant auditory event-related potential (AERP)-based tools and applications. The comparability of the results gets worse as a result of variations in the remaining measurement error. A potential method is studied that allows optimization of the length of the recording session according to the concurrent quality of the recorded data. In this way, the sufficiency of the trials can be better guaranteed, which enables control of the remaining measurement error. The suggested method is based on monitoring the signal-to-noise ratio (SNR) and remaining measurement error which are compared to predefined threshold values. The SNR test is well defined, but the criterion for the measurement error test still requires further empirical testing in practice. According to the results, the reproducibility of average AERPs in repeated experiments is improved in comparison to a case where the number of recorded trials is constant. The test-retest reliability is not significantly changed on average but the between-subject variation in the value is reduced by 33-35%. The optimization of the number of trials also prevents excessive recordings which might be of practical interest especially in the clinical context. The efficiency of the method may be further increased by implementing online tools that improve data consistency.