RESUMO
Multiple oscillating time series are typically analyzed in the frequency domain, where coherence is usually said to represent the magnitude of the correlation between two signals at a particular frequency. The correlation being referenced is complex-valued and is similar to the real-valued Pearson correlation in some ways but not others. We discuss the dependence among oscillating series in the context of the multivariate complex normal distribution, which plays a role for vectors of complex random variables analogous to the usual multivariate normal distribution for vectors of real-valued random variables. We emphasize special cases that are valuable for the neural data we are interested in and provide new variations on existing results. We then introduce a complex latent variable model for narrowly band-pass-filtered signals at some frequency, and show that the resulting maximum likelihood estimate produces a latent coherence that is equivalent to the magnitude of the complex canonical correlation at the given frequency. We also derive an equivalence between partial coherence and the magnitude of complex partial correlation, at a given frequency. Our theoretical framework leads to interpretable results for an interesting multivariate dataset from the Allen Institute for Brain Science.
Les séries temporelles à oscillations multiples sont généralement étudiées dans le domaine fréquentiel, où la cohérence est souvent considérée comme l'amplitude de la corrélation entre deux signaux à une fréquence spécifique. Cette corrélation est à valeurs complexes et présente des similitudes avec la corrélation de Pearson pour les valeurs réelles, tout en présentant des différences distinctes. Dans cette étude, les auteurs explorent la dépendance entre les séries oscillantes en utilisant la distribution normale complexe multivariée. Cette distribution est l'équivalent de la distribution normale multivariée classique, mais adaptée aux vecteurs de variables aléatoires complexes plutôt qu'aux vecteurs de variables aléatoires réelles. Les auteurs mettent l'accent sur des cas spécifiques qui revêtent une importance particulière pour les données neuronales qui les intéressent, tout en proposant de nouvelles approches et des variations des résultats existants. Ils introduisent un modèle de variables latentes complexes pour les signaux filtrés en bande passante étroite à une fréquence donnée. Ils démontrent ensuite que l'estimation du maximum de vraisemblance dans ce modèle produit une cohérence latente équivalente à l'amplitude de la corrélation canonique complexe à la fréquence spécifiée. Ils établissent également une équivalence entre la cohérence partielle et l'amplitude de la corrélation partielle complexe, toujours à une fréquence donnée. Leur approche théorique conduit à des résultats interprétables pour un ensemble de données multivariées intéressant provenant de l'Allen Institute for Brain Science.
RESUMO
Angular measurements are often modeled as circular random variables, where there are natural circular analogues of moments, including correlation. Because a product of circles is a torus, a d-dimensional vector of circular random variables lies on a d-dimensional torus. For such vectors we present here a class of graphical models, which we call torus graphs, based on the full exponential family with pairwise interactions. The topological distinction between a torus and Euclidean space has several important consequences. Our development was motivated by the problem of identifying phase coupling among oscillatory signals recorded from multiple electrodes in the brain: oscillatory phases across electrodes might tend to advance or recede together, indicating coordination across brain areas. The data analyzed here consisted of 24 phase angles measured repeatedly across 840 experimental trials (replications) during a memory task, where the electrodes were in 4 distinct brain regions, all known to be active while memories are being stored or retrieved. In realistic numerical simulations, we found that a standard pairwise assessment, known as phase locking value, is unable to describe multivariate phase interactions, but that torus graphs can accurately identify conditional associations. Torus graphs generalize several more restrictive approaches that have appeared in various scientific literatures, and produced intuitive results in the data we analyzed. Torus graphs thus unify multivariate analysis of circular data and present fertile territory for future research.
RESUMO
Neural prostheses decode intention from cortical activity to restore upper extremity movement. Typical decoding algorithms extract velocity-a vector quantity with direction and magnitude (speed) -from neuronal firing rates. Standard decoding algorithms accurately recover arm direction, but the extraction of speed has proven more difficult. We show that this difficulty is due to the way speed is encoded by individual neurons and demonstrate how standard encoding-decoding procedures produce characteristic errors. These problems are addressed using alternative brain-computer interface (BCI) algorithms that accommodate nonlinear encoding of speed and direction. Our BCI approach leads to skillful control of both direction and speed as demonstrated by stereotypic bell-shaped speed profiles, straight trajectories, and steady cursor positions before and after the movement.
Assuntos
Braço/fisiologia , Córtex Motor/fisiologia , Movimento/fisiologia , Desempenho Psicomotor/fisiologia , Algoritmos , Animais , Eletroencefalografia , Intenção , Macaca mulatta , Masculino , Modelos Neurológicos , Córtex Motor/citologia , Neurônios/fisiologiaRESUMO
Much attention has been paid to the question of how Bayesian integration of information could be implemented by a simple neural mechanism. We show that population vectors based on point-process inputs combine evidence in a form that closely resembles Bayesian inference, with each input spike carrying information about the tuning of the input neuron. We also show that population vectors can combine information relatively accurately in the presence of noisy synaptic encoding of tuning curves.
RESUMO
Recent electrophysiological studies have suggested surges in electrical correlates of consciousness (i.e., elevated gamma power and connectivity) after cardiac arrest (CA). This study examines electrocorticogram (ECoG) activity and coherence of the dying brain during asphyxial CA. Male Wistar rats (n = 16) were induced with isoflurane anesthesia, which was washed out before asphyxial CA. Mean phase coherence and ECoG power were compared during different stages of the asphyxial period to assess potential neural correlates of consciousness. After asphyxia, the ECoG progressed through four distinct stages (asphyxial stages 1-4 [AS1-4]), including a transient period of near-electrocerebral silence lasting several seconds (AS3). Electrocerebral silence (AS4) occurred within 1 min of the start of asphyxia, and pulseless electrical activity followed the start of AS4 by 1-2 min. AS3 was linked to a significant increase in frontal coherence between the left and right motor cortices (p < 0.05), with no corresponding increase in ECoG power. AS3 was also associated with a significant posterior shift of ECoG power, favoring the visual cortices (p < 0.05). Although the ECoG during AS3 appears visually flat or silent when viewed with standard clinical settings, our study suggests that this period of transient near-electrocerebral silence contains distinctive neural activity. Specifically, the burst in frontal coherence and posterior shift of ECoG power that we find during this period immediately preceding CA may be a neural correlate of conscious processing.
Assuntos
Encéfalo/fisiopatologia , Estado de Consciência/fisiologia , Parada Cardíaca/fisiopatologia , Neurônios/fisiologia , Animais , Asfixia/fisiopatologia , Modelos Animais de Doenças , Eletroencefalografia , Masculino , Ratos , Ratos WistarRESUMO
Neuroprosthetic devices that interface with the nervous system to restore functional motor activity offer a viable alternative to nerve regeneration, especially in proximal nerve injuries like brachial plexus injuries where muscle atrophy may set in before nerve re-innervation occurs. Prior studies have used control signals from muscle or cortical activity. However, nerve signals are preferred in many cases since they permit more natural and precise control when compared to muscle activity, and can be accessed with much lower risk than cortical activity. Identification of nerve signals that control the appropriate muscles is essential for the development of such a `bionic link'. Here we examine the correlation between muscle and nerve signals responsible for hand grasping in the M. fascicularis. Simultaneous recordings were performed using a 4-channel thin-film longitudinal intra-fascicular electrode (tf-LIFE) and 9 bipolar endomysial muscle electrodes while the animal performed grasping movements. We were able to identify a high degree of correlation (r > 0.6) between nerve signals from the median nerve and movement-dependent muscle activity from the flexor muscles of the forearm, with a delay that corresponded to 25 m/s nerve conduction velocity. The phase of the flexion could be identified using a wavelet approximation of the ENG. This result confirms this approach for a future neuroprosthetic device for the treatment of peripheral nerve injuries.
Assuntos
Plexo Braquial/lesões , Força da Mão/fisiologia , Nervo Mediano/fisiologia , Movimento/fisiologia , Músculo Esquelético/fisiologia , Amplitude de Movimento Articular , Animais , Estimulação Elétrica , Eletrodos , Eletrodos Implantados , Macaca fascicularis , Tecido Nervoso , Condução Nervosa , Neurônios/fisiologia , Nervos Periféricos/patologiaRESUMO
BACKGROUND: Vascular hemodynamics is central to the regulation of neuro-metabolism and plays important roles in peripheral nerves diseases and their prevention. However, at present there are only a few techniques capable of directly measuring peripheral nerve vascular hemodynamics. METHOD: Here, we investigate the use of dark-field functional photoacoustic microscopy (fPAM) for intrinsic visualizing of the relative hemodynamics of the rat sciatic nerve in response to localized temperature modulation (i.e., cooling and rewarming). RESULTS AND CONCLUSION: Our main results show that the relative functional total hemoglobin concentration (HbT) is more significantly correlated with localized temperature changes than the hemoglobin oxygen saturation (SO2) changes in the sciatic nerve. Our study also indicates that the relative HbT changes are better markers of neuronal activation than SO2 during nerve temperature changes. Our results show that fPAM is a promising candidate for in vivo imaging of peripheral nerve hemodynamics without the use of contrast agents. Additionally, this technique may shed light on the neuroprotective effect of hypothermia on peripheral nerves by visualizing their intrinsic hemodynamics.
Assuntos
Hemodinâmica , Microscopia Confocal/métodos , Técnicas Fotoacústicas/métodos , Nervo Isquiático/fisiologia , Temperatura , Animais , Regulação da Temperatura Corporal/fisiologia , Feminino , Hemoglobinas/metabolismo , Oxigênio/metabolismo , Ratos , Ratos Wistar , Nervo Isquiático/metabolismoRESUMO
Optical imaging techniques reflect different biochemical processes in the brain, which is closely related with neural activity. Scientists and clinicians employ a variety of optical imaging technologies to visualize and study the relationship between neurons, glial cells and blood vessels. In this paper, we present an overview of the current optical approaches used for the in vivo imaging of neurovascular coupling events in small animal models. These techniques include 2-photon microscopy, laser speckle contrast imaging (LSCI), voltage-sensitive dye imaging (VSDi), functional photoacoustic microscopy (fPAM), functional near-infrared spectroscopy imaging (fNIRS) and multimodal imaging techniques. The basic principles of each technique are described in detail, followed by examples of current applications from cutting-edge studies of cerebral neurovascular coupling functions and metabolic. Moreover, we provide a glimpse of the possible ways in which these techniques might be translated to human studies for clinical investigations of pathophysiology and disease. In vivo optical imaging techniques continue to expand and evolve, allowing us to discover fundamental basis of neurovascular coupling roles in cerebral physiology and pathophysiology.