Decoding across sensory modalities reveals common supramodal signatures of conscious perception.

An increasing number of studies highlight common brain regions and processes in mediating conscious sensory experience. While most studies have been performed in the visual modality, it is implicitly assumed that similar processes are involved in other sensory modalities. However, the existence of supramodal neural processes related to conscious perception has not been convincingly shown so far. Here, we aim to directly address this issue by investigating whether neural correlates of conscious perception in one modality can predict conscious perception in a different modality. In two separate experiments, we presented participants with successive blocks of near-threshold tasks involving subjective reports of tactile, visual, or auditory stimuli during the same magnetoencephalography (MEG) acquisition. Using decoding analysis in the poststimulus period between sensory modalities, our first experiment uncovered supramodal spatiotemporal neural activity patterns predicting conscious perception of the feeble stimulation. Strikingly, these supramodal patterns included activity in primary sensory regions not directly relevant to the task (e.g., neural activity in visual cortex predicting conscious perception of auditory near-threshold stimulation). We carefully replicate our results in a control experiment that furthermore show that the relevant patterns are independent of the type of report (i.e., whether conscious perception was reported by pressing or withholding a button press). Using standard paradigms for probing neural correlates of conscious perception, our findings reveal a common signature of conscious access across sensory modalities and illustrate the temporally late and widespread broadcasting of neural representations, even into task-unrelated primary sensory processing regions.

Impaired pitch perception and memory in congenital amusia: the deficit starts in the auditory cortex.

Congenital amusia is a lifelong disorder of music perception and production. The present study investigated the cerebral bases of impaired pitch perception and memory in congenital amusia using behavioural measures, magnetoencephalography and voxel-based morphometry. Congenital amusics and matched control subjects performed two melodic tasks (a melodic contour task and an easier transposition task); they had to indicate whether sequences of six tones (presented in pairs) were the same or different. Behavioural data indicated that in comparison with control participants, amusics' short-term memory was impaired for the melodic contour task, but not for the transposition task. The major finding was that pitch processing and short-term memory deficits can be traced down to amusics' early brain responses during encoding of the melodic information. Temporal and frontal generators of the N100m evoked by each note of the melody were abnormally recruited in the amusic brain. Dynamic causal modelling of the N100m further revealed decreased intrinsic connectivity in both auditory cortices, increased lateral connectivity between auditory cortices as well as a decreased right fronto-temporal backward connectivity in amusics relative to control subjects. Abnormal functioning of this fronto-temporal network was also shown during the retention interval and the retrieval of melodic information. In particular, induced gamma oscillations in right frontal areas were decreased in amusics during the retention interval. Using voxel-based morphometry, we confirmed morphological brain anomalies in terms of white and grey matter concentration in the right inferior frontal gyrus and the right superior temporal gyrus in the amusic brain. The convergence between functional and structural brain differences strengthens the hypothesis of abnormalities in the fronto-temporal pathway of the amusic brain. Our data provide first evidence of altered functioning of the auditory cortices during pitch perception and memory in congenital amusia. They further support the hypothesis that in neurodevelopmental disorders impacting high-level functions (here musical abilities), abnormalities in cerebral processing can be observed in early brain responses.

Solid pseudopapillary pancreatic tumor as a portal hypertension causal: the first reported case in Puerto Rico.

We describe the first reported case in Puerto Rico of Solid Pseudopapillary Tumor (SPT) of the pancreas causing portal hypertension. Clinical presentation and characteristic imaging findings are helpful to differentiate SPT from pancreatic carcinoma. Diagnosis can be confirmed by histopathological and immunohistochemical approach through biopsy. Timely surgical intervention can prevent portal hypertension as manifestation and be lifesaving in case of malignant degeneration, giving the patient an excellent prognosis after tumor surgical resection.

Disentangling sensory precision and prior expectation of change in autism during tactile discrimination.

Predictive coding theories suggest that core symptoms in autism spectrum disorders (ASD) may stem from atypical mechanisms of perceptual inference (i.e., inferring the hidden causes of sensations). Specifically, there would be an imbalance in the precision or weight ascribed to sensory inputs relative to prior expectations. Using three tactile behavioral tasks and computational modeling, we specifically targeted the implicit dynamics of sensory adaptation and perceptual learning in ASD. Participants were neurotypical and autistic adults without intellectual disability. In Experiment I, tactile detection thresholds and adaptation effects were measured to assess sensory precision. Experiments II and III relied on two-alternative forced choice tasks designed to elicit a time-order effect, where prior knowledge biases perceptual decisions. Our results suggest a subtler explanation than a simple imbalance in the prior/sensory weights, having to do with the dynamic nature of perception, that is the adjustment of precision weights to context. Compared to neurotypicals, autistic adults showed no difference in average performance and sensory sensitivity. Both groups managed to implicitly learn and adjust a prior that biased their perception. However, depending on the context, autistic participants showed no, normal or slower adaptation, a phenomenon that computational modeling of trial-to-trial responses helped us to associate with a higher expectation for sameness in ASD, and to dissociate from another observed robust difference in terms of response bias. These results point to atypical perceptual learning rather than altered perceptual inference per se, calling for further empirical and computational studies to refine the current predictive coding theories of ASD.

Head magnetomyography (hMMG): A novel approach to monitor face and whole head muscular activity.

Muscular activity recording is of high basic science and clinical relevance and is typically achieved using electromyography (EMG). While providing detailed information about the state of a specific muscle, this technique has limitations such as the need for a priori assumptions about electrode placement and difficulty with recording muscular activity patterns from extended body areas at once. For head and face muscle activity, the present work aimed to overcome these restrictions by exploiting magnetoencephalography (MEG) as a whole head myographic recorder (head magnetomyography, hMMG). This is in contrast to common MEG studies, which treat muscular activity as artifact in electromagnetic brain activity. In a first proof-of-concept step, participants imitated emotional facial expressions performed by a model. Exploiting source projection algorithms, we were able to reconstruct muscular activity, showing spatial activation patterns in accord with the hypothesized muscular contractions. Going one step further, participants passively observed affective pictures with negative, neutral, or positive valence. Applying multivariate pattern analysis to the reconstructed hMMG signal, we were able to decode above chance the valence category of the presented pictures. Underlining the potential of hMMG, a searchlight analysis revealed that generally neglected neck muscles exhibit information on stimulus valence. Results confirm the utility of hMMG as a whole head electromyographic recorder to quantify muscular activation patterns including muscular regions that are typically not recorded with EMG. This key advantage beyond conventional EMG has substantial scientific and clinical potential.

EEG artifact correction strategies for online trial-by-trial analysis.

Brain-machine interfaces (BMIs) use brain signals to control closed-loop systems in real-time. This comes with substantial challenges, such as having to remove artifacts in order to extract reliable features, especially when using electroencephalography (EEG). Some approaches have been described in the literature to address online artifact correction. However, none are being used as a 'gold-standard' method, and no research has been conducted to analyze and compare their respective effects on statistical data analysis (inference-based decision). OBJECTIVE: In this paper, we evaluate methods for artifact correction and describe the necessary adjustments to implement them for online EEG data analysis. APPROACH: We investigate the following methods: artifact subspace reconstruction (ASR), fully online and automated artifact removal for brain-computer interfacing (FORCe), online empirical model decomposition (EMD), and online independent component analysis. For assessment, we simulated online data processing using real data from an auditory oddball task. We compared the above methods with classical offline data processing, in their ability (i) to reveal a significant mismatch negativity (MMN) response to auditory stimuli; (ii) to reveal the more subtle modulation of the MMN by contextual changes (namely, the predictability of the sound sequence), and (iii) to identify the most likely learning process that explains the MMN response. MAIN RESULTS: Our results show that ASR and EMD are both able to reveal a significant MMN and its modulation by predictability, and even appear more sensitive than the offline analysis when comparing alternative models of perception underlying auditory evoked responses. SIGNIFICANCE: ASR and EMD show many advantages when compared to other online artifact correction methods. Besides, subtle modulation analysis of the MMN, embedded in perception computational models is a novel method for assessing the quality of artifact correction methods.

Automatic and feature-specific prediction-related neural activity in the human auditory system.

Prior experience enables the formation of expectations of upcoming sensory events. However, in the auditory modality, it is not known whether prediction-related neural signals carry feature-specific information. Here, using magnetoencephalography (MEG), we examined whether predictions of future auditory stimuli carry tonotopic specific information. Participants passively listened to sound sequences of four carrier frequencies (tones) with a fixed presentation rate, ensuring strong temporal expectations of when the next stimulus would occur. Expectation of which frequency would occur was parametrically modulated across the sequences, and sounds were occasionally omitted. We show that increasing the regularity of the sequence boosts carrier-frequency-specific neural activity patterns during both the anticipatory and omission periods, indicating that prediction-related neural activity is indeed feature-specific. Our results illustrate that even without bottom-up input, auditory predictions can activate tonotopically specific templates.

The impact of a rapid imaging protocol in acute cholecystitis-prospective cohort study.

INTRODUCTION: In this study we assess the impact of a "rapid imaging protocol" (RIP) on outcomes in patients with suspected acute cholecystitis (AC). METHODS: From January 2017 to January 2018, a prospective cohort study was implemented using a RIP with hepatoscintigraphy (HIDA) or CT scan (first available, goal within 4 h) in patients (n = 52) presenting with highly suspected AC and a clinical feature score of ≥1. For the latter, the following presenting features were scored as follows: 1 point for WBC count ≥10,000 (109/L), 1.5 points for glucose ≥140 (mg/dl), and/or 1 point for age ≥50 yrs. The historical control was all patients admitted with suspected AC in a 1.5-year period (n = 117) under our previous "delayed imaging protocol" (DIP), which used US ± HIDA (post-admission) in select patients. Primary end points included: compare outcome and quality measures between the groups, evaluate diagnostic imaging performance for AC, and evaluate our proposed clinical feature score in the setting of AC. RESULTS: Histopathologic features consistent with AC was more frequent in patients in the RIP (64% vs 39%, p = 0.008). The pooled positive predictive value of HIDA and CT scan for AC were 85% vs 94%, respectively. The RIP was associated with a significant reduction in time to surgery, length of stay, and conversions to open (p < 0.001, respectively). A clinical feature score of 3.5 predicted the likelihood of AC in 95% of the cases (x2 for linear trend = 42, p < 0.001). CONCLUSION: A protocol centered around rapid identification, defined clinical criteria (i.e. clinical feature score), and confirmation with non-user dependent imaging modalities has resulted in favorable outcomes. CT may be the study of choice when the likelihood of AC is high because it is superior at identifying severity.

Active SAmpling Protocol (ASAP) to Optimize Individual Neurocognitive Hypothesis Testing: A BCI-Inspired Dynamic Experimental Design.

The relatively young field of Brain-Computer Interfaces has promoted the use of electrophysiology and neuroimaging in real-time. In the meantime, cognitive neuroscience studies, which make extensive use of functional exploration techniques, have evolved toward model-based experiments and fine hypothesis testing protocols. Although these two developments are mostly unrelated, we argue that, brought together, they may trigger an important shift in the way experimental paradigms are being designed, which should prove fruitful to both endeavors. This change simply consists in using real-time neuroimaging in order to optimize advanced neurocognitive hypothesis testing. We refer to this new approach as the instantiation of an Active SAmpling Protocol (ASAP). As opposed to classical (static) experimental protocols, ASAP implements online model comparison, enabling the optimization of design parameters (e.g., stimuli) during the course of data acquisition. This follows the well-known principle of sequential hypothesis testing. What is radically new, however, is our ability to perform online processing of the huge amount of complex data that brain imaging techniques provide. This is all the more relevant at a time when physiological and psychological processes are beginning to be approached using more realistic, generative models which may be difficult to tease apart empirically. Based upon Bayesian inference, ASAP proposes a generic and principled way to optimize experimental design adaptively. In this perspective paper, we summarize the main steps in ASAP. Using synthetic data we illustrate its superiority in selecting the right perceptual model compared to a classical design. Finally, we briefly discuss its future potential for basic and clinical neuroscience as well as some remaining challenges.

Clinical implications of hepatobiliary scintigraphy and ultrasound in the diagnosis of acute cholecystitis.

BACKGROUND: We assess the performance of ultrasound (US) and hepatobiliary scintigraphy (HIDA) as confirmatory studies in acute cholecystitis (AC) and demonstrate our current imaging protocol's impact on outcomes. STUDY DESIGN: Between January 2013 to July 2014, 117 patients were admitted through the emergency room with a preliminary diagnosis of AC. Overall, 106/117 (91%) of the patients received US preadmission and 34/117 (29%) received a HIDA post admission. Primary end points included: 1) diagnostic test reliability for AC, and 2) outcome and quality measures (time to surgery, LOS, costs, etc.). RESULTS: Laparoscopic cholecystectomy was performed in 96/117 (82%) and open cholecystectomy in 21/117 (18%) of the patients. Overall, histopathologic features consistent with AC was present in 46/117 (39%). AC alone was present in 23/117 (20%), and AC superimposed on chronic cholecystitis was present in 23/117 (20%). For AC, US had a sensitivity and specificity of 26% and 80%, respectively. HIDA scan had a sensitivity and specificity of 87% and 79%, respectively. Time to surgery (TTS) was 4 vs 2.3 days in patients who received HIDA vs US alone (p = 0.001), and length of stay (LOS) was 6.7 vs 4.3 days, respectively (p = 0.001). Age >50 years, glucose >140 (mg/dl), and WBC count >10 (×109 /L) were statistically significant independent variables associated with AC. CONCLUSION: HIDA scan is superior to US as a diagnostic study in the setting of AC. Our current protocol of delayed HIDA (post-admission) was associated with increased TTS, LOS, and overall costs. Early confirmation with HIDA in high risk patients may hasten treatment allocation and improve outcomes in the setting of AC.

Altered retrieval of melodic information in congenital amusia: insights from dynamic causal modeling of MEG data.

Congenital amusia is a neuro-developmental disorder that primarily manifests as a difficulty in the perception and memory of pitch-based materials, including music. Recent findings have shown that the amusic brain exhibits altered functioning of a fronto-temporal network during pitch perception and short-term memory. Within this network, during the encoding of melodies, a decreased right backward frontal-to-temporal connectivity was reported in amusia, along with an abnormal connectivity within and between auditory cortices. The present study investigated whether connectivity patterns between these regions were affected during the short-term memory retrieval of melodies. Amusics and controls had to indicate whether sequences of six tones that were presented in pairs were the same or different. When melodies were different only one tone changed in the second melody. Brain responses to the changed tone in "Different" trials and to its equivalent (original) tone in "Same" trials were compared between groups using Dynamic Causal Modeling (DCM). DCM results confirmed that congenital amusia is characterized by an altered effective connectivity within and between the two auditory cortices during sound processing. Furthermore, right temporal-to-frontal message passing was altered in comparison to controls, with notably an increase in "Same" trials. An additional analysis in control participants emphasized that the detection of an unexpected event in the typically functioning brain is supported by right fronto-temporal connections. The results can be interpreted in a predictive coding framework as reflecting an abnormal prediction error sent by temporal auditory regions towards frontal areas in the amusic brain.

Toward a new application of real-time electrophysiology: online optimization of cognitive neurosciences hypothesis testing.

Brain-computer interfaces (BCIs) mostly rely on electrophysiological brain signals. Methodological and technical progress has largely solved the challenge of processing these signals online. The main issue that remains, however, is the identification of a reliable mapping between electrophysiological measures and relevant states of mind. This is why BCIs are highly dependent upon advances in cognitive neuroscience and neuroimaging research. Recently, psychological theories became more biologically plausible, leading to more realistic generative models of psychophysiological observations. Such complex interpretations of empirical data call for efficient and robust computational approaches that can deal with statistical model comparison, such as approximate Bayesian inference schemes. Importantly, the latter enable the optimization of a model selection error rate with respect to experimental control variables, yielding maximally powerful designs. In this paper, we use a Bayesian decision theoretic approach to cast model comparison in an online adaptive design optimization procedure. We show how to maximize design efficiency for individual healthy subjects or patients. Using simulated data, we demonstrate the face- and construct-validity of this approach and illustrate its extension to electrophysiology and multiple hypothesis testing based on recent psychophysiological models of perception. Finally, we discuss its implications for basic neuroscience and BCI itself.