A dataset for benchmarking Neotropical anuran calls identification in passive acoustic monitoring.

Global change is predicted to induce shifts in anuran acoustic behavior, which can be studied through passive acoustic monitoring (PAM). Understanding changes in calling behavior requires automatic identification of anuran species, which is challenging due to the particular characteristics of neotropical soundscapes. In this paper, we introduce a large-scale multi-species dataset of anuran amphibians calls recorded by PAM, that comprises 27 hours of expert annotations for 42 different species from two Brazilian biomes. We provide open access to the dataset, including the raw recordings, experimental setup code, and a benchmark with a baseline model of the fine-grained categorization problem. Additionally, we highlight the challenges of the dataset to encourage machine learning researchers to solve the problem of anuran call identification towards conservation policy. All our experiments and resources have been made available at https://soundclim.github.io/anuraweb/ .

An implementation of integrated information theory in resting-state fMRI.

Integrated Information Theory was developed to explain and quantify consciousness, arguing that conscious systems consist of elements that are integrated through their causal properties. This study presents an implementation of Integrated Information Theory 3.0, the latest version of this framework, to functional MRI data. Data were acquired from 17 healthy subjects who underwent sedation with propofol, a short-acting anaesthetic. Using the PyPhi software package, we systematically analyze how Φmax, a measure of integrated information, is modulated by the sedative in different resting-state networks. We compare Φmax to other proposed measures of conscious level, including the previous version of integrated information, Granger causality, and correlation-based functional connectivity. Our results indicate that Φmax presents a variety of sedative-induced behaviours for different networks. Notably, changes to Φmax closely reflect changes to subjects' conscious level in the frontoparietal and dorsal attention networks, which are responsible for higher-order cognitive functions. In conclusion, our findings present important insight into different measures of conscious level that will be useful in future implementations to functional MRI and other forms of neuroimaging.

Structural and functional connectivity of the ascending arousal network for prediction of outcome in patients with acute disorders of consciousness.

To determine the role of early acquisition of blood oxygen level-dependent (BOLD) signals and diffusion tensor imaging (DTI) for analysis of the connectivity of the ascending arousal network (AAN) in predicting neurological outcomes after acute traumatic brain injury (TBI), cardiopulmonary arrest (CPA), or stroke. A prospective analysis of 50 comatose patients was performed during their ICU stay. Image processing was conducted to assess structural and functional connectivity of the AAN. Outcomes were evaluated after 3 and 6 months. Nineteen patients (38%) had stroke, 18 (36%) CPA, and 13 (26%) TBI. Twenty-three patients were comatose (44%), 11 were in a minimally conscious state (20%), and 16 had unresponsive wakefulness syndrome (32%). Univariate analysis demonstrated that measurements of diffusivity, functional connectivity, and numbers of fibers in the gray matter, white matter, whole brain, midbrain reticular formation, and pontis oralis nucleus may serve as predictive biomarkers of outcome depending on the diagnosis. Multivariate analysis demonstrated a correlation of the predicted value and the real outcome for each separate diagnosis and for all the etiologies together. Findings suggest that the above imaging biomarkers may have a predictive role for the outcome of comatose patients after acute TBI, CPA, or stroke.

Modeling an auditory stimulated brain under altered states of consciousness using the generalized Ising model.

Propofol is a short-acting medication that results in decreased levels of consciousness and is used for general anesthesia. Although it is the most commonly used anesthetic in the world, much remains unknown about the mechanisms by which it induces a loss of consciousness. Characterizing anesthesia-induced alterations to brain network activity might provide a powerful framework for understanding the neural mechanisms of unconsciousness. The aim of this work was to model brain activity in healthy brains during various stages of consciousness, as induced by propofol, in the auditory paradigm. We used the generalized Ising model (GIM) to fit the empirical fMRI data of healthy subjects while they listened to an audio clip from a movie. The external stimulus (audio clip) is believed to be at least partially driving a synchronization process of the brain activity and provides a similar conscious experience in different subjects. In order to observe the common synchronization among the subjects, a novel technique called the inter subject correlation (ISC) was implemented. We showed that the GIM-modified to incorporate the naturalistic external field-was able to fit the empirical task fMRI data in the awake state, in mild sedation, in deep sedation, and in recovery, at a temperature T* which is well above the critical temperature. To our knowledge this is the first study that captures human brain activity in response to real-life external stimuli at different levels of conscious awareness using mathematical modeling. This study might be helpful in the future to assess the level of consciousness of patients with disorders of consciousness and help in regaining their consciousness.

Establishing an acquisition and processing protocol for resting state networks with a 1.5 T scanner: A case series in a middle-income country.

OBJECTIVE: The aim of this study was to characterize the capability of detection of the resting state networks (RSNs) with functional magnetic resonance imaging (fMRI) in healthy subjects using a 1.5T scanner in a middle-income country. MATERIALS AND METHODS: Ten subjects underwent a complete blood-oxygen-level dependent imaging (BOLD) acquisition on a 1.5T scanner. For the imaging analysis, we used the spatial independent component analysis (sICA). We designed a computer tool for 1.5 T (or above) scanners for imaging processing. We used it to separate and delineate the different components of the RSNs of the BOLD signal. The sICA was also used to differentiate the RSNs from noise artifact generated by breathing and cardiac cycles. RESULTS: For each subject, 20 independent components (IC) were computed from the sICA (a total of 200 ICs). From these ICs, a spatial pattern consistent with RSNs was identified in 161 (80.5%). From the 161, 131 (65.5%) were fit for study. The networks that were found in all subjects were: the default mode network, the right executive control network, the medial visual network, and the cerebellar network. In 90% of the subjects, the left executive control network and the sensory/motor network were observed. The occipital visual network was present in 80% of the subjects. In 39 (19.5%) of the images, no any neural network was identified. CONCLUSIONS: Reproduction and differentiation of the most representative RSNs was achieved using a 1.5T scanner acquisitions and sICA processing of BOLD imaging in healthy subjects.

Time-Delay Latency of Resting-State Blood Oxygen Level-Dependent Signal Related to the Level of Consciousness in Patients with Severe Consciousness Impairment.

Recent evidence on resting-state functional magnetic resonance imaging (rs-fMRI) suggests that healthy human brains have a temporal organization represented in a widely complex time-delay structure. This structure seems to underlie brain communication flow, integration/propagation of brain activity, as well as information processing. Therefore, it is probably linked to the emergence of highly coordinated complex brain phenomena, such as consciousness. Nevertheless, possible changes in this structure during an altered state of consciousness remain poorly investigated. In this work, we hypothesized that due to a disruption in high-order functions and alterations of the brain communication flow, patients with disorders of consciousness (DOC) might exhibit changes in their time-delay structure of spontaneous brain activity. We explored this hypothesis by comparing the time-delay projections from fMRI resting-state data acquired in resting state from 48 patients with DOC and 27 healthy controls (HC) subjects. Results suggest that time-delay structure modifies for patients with DOC conditions when compared with HC. Specifically, the average value and the directionality of latency inside the midcingulate cortex (mCC) shift with the level of consciousness. In particular, positive values of latency inside the mCC relate to preserved states of consciousness, whereas negative values change proportionally with the level of consciousness in patients with DOC. These results suggest that the mCC may play a critical role as an integrator of brain activity in HC subjects, but this role vanishes in an altered state of consciousness.

Reconfiguration of large-scale functional connectivity in patients with disorders of consciousness.

INTRODUCTION: Functional connectivity alterations within individual resting state networks (RSNs) are linked to disorders of consciousness (DOC). If these alterations influence the interaction quality with other RNSs, then, brain alterations in patients with DOC would be characterized by connectivity changes in the large-scale model composed of RSNs. How are functional interactions between RSNs influenced by internal alterations of individual RSNs? Do the functional alterations induced by DOC change some key properties of the large-scale network, which have been suggested to be critical for the consciousness emergence? Here, we use network analysis to measure functional connectivity in patients with DOC and address these questions. We hypothesized that network properties provide descriptions of brain functional reconfiguration associated with consciousness alterations. METHODS: We apply nodal and global network measurements to study the reconfiguration linked with the disease severity. We study changes in integration, segregation, and centrality properties of the functional connectivity between the RSNs in subjects with different levels of consciousness. RESULTS: Our analysis indicates that nodal measurements are more sensitive to disease severity than global measurements, particularly, for functional connectivity of sensory and cognitively related RSNs. CONCLUSION: The network property alterations of functional connectivity in different consciousness levels suggest a whole-brain topological reorganization of the large-scale functional connectivity in patients with DOC.

Volumetría de fascículos cerebrales en población sana / Brain fascicles volumetry in healthy population

Objetivo Desde la aparición de la tractografía, al tratarse de una técnica no invasiva y que usa la ampliamente conocida resonancia magnética (RM), el estudio de la sustancia blanca se ha facilitado. A partir de eso, se han logrado grandes descubrimientos en cuanto a fascículos cerebrales involucrados en funciones cognitivas. Sin embargo, su evaluación sigue siendo subjetiva y depende de la experiencia y entrenamiento del evaluador, razón por la cual se ha limitado su aplicabilidad en la práctica clínica. En ese sentido, es conveniente parametrizar volúmenes cerebrales de sustancia blanca en población sana a través de una herramienta electrónica que se pueda reproducir y así poderlo aplicar en enfermos. Materiales y métodos Se reportan 10 sujetos sanos desde el punto de vista neurológico. Para cada sujeto, se adquirieron imágenes ponderadas por difusión y los resultados se visualizaron mediante FiberNavigator (http://scilus.github.io/fibernavigator). Finalmente, esa misma herramienta fue utilizada para purificar los fascículos objeto de estudio y realizar el conteo de las fibras. Resultados Se obtuvieron valores de volumetría del fascículo longitudinal superior (FLS), fascículo longitudinal inferior (FLI), fascículo frontoccipital inferior (FFI), fascículo uncinado (FU) y fascículo del cíngulo (FC), identificando que no existen diferencias estadísticamente significativas entre el número de fibras que componen los fascículos cerebrales. Discusión Los resultados alcanzados de la anatomía y la direccionalidad de fibras de los fascículos cerebrales de este estudio coinciden con el resto de la evidencia publicada hasta el momento, sin encontrar diferencias en cuanto a su organización y recorrido. Conclusión Aunque esos resultados no sirven como valores de referencia para ser aplicados en pacientes con patología neurológica, brindamos información inexistente hasta el momento, con ese equipo en específico y la reproducción entre los distintos usuarios y el software.

Objective Since the appearance of tractography, as it is a non-invasive technique and uses the widely known magnetic resonance (MR), the study of white matter has been facilitated. After this, great discoveries have been made regarding the brain fascicles involved in cognitive functions. However, its evaluation continues to be subjective and depends on the evaluator's experience and training. That the reason why its applicability has been limited in clinical practice. Because of this, it is convenient to parametrize cerebral volumes of white matter in healthy population through an electronic, reproducible tool that could be applied in patients. Materials and Methods Ten neurologically healthy subjects are reported, for each subject we acquired images weighted by diffusion and the results were visualized by means of FiberNavigator (http://scilus.github.io/fibernavigator). Finally, this same tool was used to purify the fascicles under study and perform the fiber count. Results Volumetric values of the upper longitudinal fasciculus, inferior longitudinal fasciculus, inferior frontoccipital fasciculus, uncinated fasciculus and cingulate fasciculus were obtained, identifying that there are not statistically significant differences in the number of fibers that make up the cerebral fascicles. Discussion The results achieved of the anatomical and fiber directionality of the cerebral fascicles of this study, coincide with the rest of the evidence published up to now, without finding differences regarding its organization and route. Conclusion Although these results do not serve as reference values to be applied in patients with neurological pathology, do we provide nonexistent information so far, with this specific equipment and the reproducibility between the different users and the software.

Structural and functional connectivity of ascending reticular activating system in a patient with impaired consciousness after a cardiac arrest: A case report.

RATIONALE: Diffusion tensor imaging (DTI), diffusion tensor tractography (DTT), as well as resting-state-functional magnetic resonance imaging (rsfMRI) are promising methods for assessing patients with disorders of consciousness (DOCs). PATIENT CONCERNS: This work describes the main findings using DTI, DTT, and rsfMRI in a patient with a DOC secondary to an anoxic encephalopathy who had a fatal outcome. She was an 85-year-old woman who presented a cardiac arrest and underwent cardiopulmonary resuscitation for 20 minutes then returning to spontaneous circulation. After sedation withdrawal, 2 days after the event, she remained with a Glasgow Coma Scale score of 3/15 and with an absence of brainstem reflexes. DIAGNOSES: DOC secondary to an anoxic encephalopathy after cardiovascular resuscitation. INTERVENTIONS: A complete brain MRI scan was performed 72 hours after the initial event, including DTI, DTT, and rsfMRI. DTT demonstrated disruption of both ventral and dorsal tegmental tracts bilaterally. DTI showed a reduction of fractional anisotropic level in the mesencephalic nuclei. Moreover, changes in the number of fiber tracts were not evidenced in any portions of the ascending reticular activating system (ARAS). Finally, an increase in the anticorrelated and correlated association among the nuclei in the ARAS and the cortex was evidenced. OUTCOMES: Patient deceased. LESSONS: Neuroimaging demonstrated low FA values in the ARAS, destruction of dorsal and ventral tegmental tracts, as well as hyper-connective (highly correlated or anti-correlated) association among ARAS and cortical nuclei compared with 3 healthy control subjects.

A method for functional network connectivity using distance correlation.

In this paper, we present a novel approach for functional network connectivity in fMRI resting activity using distance correlation. The proposed method accounts for nonlinear relationships between the resting state networks and can be used for both single subject and group level analyses. We showed that the new strategy improves the capacity of characterization of pathological populations, such as, patients with disorder of consciousness, when compared to related approaches.