Dectin-1 Mediated Regulation of Dendritic Cell Metabolism

Dendritic cells (DCs) are critical antigen presenting cells that link the innate and adaptive immune systems. DCs are activated through a variety of receptors and respond with a diverse array of metabolic changes that are not yet well understood. IL-1β is a key inflammatory cytokine produced by DCs when they are activated through both toll-like receptors and C-type lectin receptors. IL-1β is activated by the inflammasome signaling complex but how the inflammasome is controlled by glycolysis is not yet well understood. We demonstrate that DC activation through TLR or C-type lectin receptors induces a shift to aerobic glycolytic metabolism. We show that while the transcription of IL-1β in DCs activated through both these receptors is not under glycolytic control, whether or not translation of IL-1β is under glycolytic control remains unclear. These findings provide new information on Dectin-1 mediated metabolic reprogramming in DCs. Understanding the link between metabolic changes and Dectin-1-mediated DC activation has broad implications for improved vaccine design and clinical intervention to fungal infection

Neuronal activity in the human lateral temporal lobe. II. Responses to the subjects own voice.

We have recorded neuronal responses in the lateral temporal lobe of man to overt speech during open brain surgery for epilepsy. Tests included overt naming of objects and reading words or short sentences shown on a projector screen, repetition of tape recorded words or sentences presented over a loudspeaker, and free conversation. Neuronal activity in the dominant and non-dominant temporal lobe were about equally affected by overt speech. As during listening to language (see Creutzfeldt et al. 1989), responses differed between recordings from sites in the superior and the middle or inferior temporal gyrus. In the superior temporal gyrus all neurons responded clearly and each in a characteristic manner. Activation could be related to phonemic aspects, to segmentation or to the length of spoken words or sentences. However, neurons were mostly differently affected by listening to words and language as compared to overt speaking. In neuronal populations recorded simultaneously with one or two microelectrodes, some neurons responded predominantly to one or the other type of speech. Excitatory responses during overt speaking were always auditory. In the middle temporal gyrus more neurons (about 2/3) responded to overt speaking than to listening alone. Activations elicited during overt speech were seen in about 1/3 of our sample, but they were more sluggish than those recorded in the superior gyrus. A prominent feature was suppression of on-going activity, which we found in about 1/3 of middle and in some superior temporal gyrus neurons. This suppression could preced vocalization by up to a few hundred ms, and could outlast it by up to 1 s. Evoked ECoG-potentials to words heard or spoken were different, and those to overt speech were more widespread

Unsupervised decoding of long-term, naturalistic human neural recordings with automated video and audio annotations

Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Most ongoing efforts have focused on training decoders on specific, stereotyped tasks in laboratory settings. Implementing brain-computer interfaces (BCIs) in natural settings requires adaptive strategies and scalable algorithms that require minimal supervision. Here we propose an unsupervised approach to decoding neural states from human brain recordings acquired in a naturalistic context. We demonstrate our approach on continuous long-term electrocorticographic (ECoG) data recorded over many days from the brain surface of subjects in a hospital room, with simultaneous audio and video recordings. We first discovered clusters in high-dimensional ECoG recordings and then annotated coherent clusters using speech and movement labels extracted automatically from audio and video recordings. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Our results show that our unsupervised approach can discover distinct behaviors from ECoG data, including moving, speaking and resting. We verify the accuracy of our approach by comparing to manual annotations. Projecting the discovered cluster centers back onto the brain, this technique opens the door to automated functional brain mapping in natural settings

Anatomical Parcellation of Cortical Language Sites

Anatomical labeling of cerebral cortical stimulation (CSM) sites is necessary for intelligent computer querying of a rich and unique experimental database examining neural substrates underlying human language production. To this end, we have developed a parcellation scheme for the lateral surface of the human cerebral cortex. We then compared results generated utilizing this approach to those generated using an alternative method implemented in the Talairach Daemon

Dissociation of Action and Object Naming: Evidence From Cortical Stimulation Mapping

This cortical stimulation mapping study investigates the neural representation of action and object naming. Data from 13 neurosurgical subjects undergoing awake cortical mapping is presented. Our findings indicate clear evidence of differential disruption of noun and verb naming in the context of this naming task. At the individual level, evidence was found for punctuate regions of perisylvian cortex subserving noun and verb function. Across subjects, however, the location of these sites varied. This finding may help explain discrepancies between lesion and functional imaging studies of noun and verb naming. In addition, an alternative coding of these data served to highlight the grammatical class vulnerability of the target response. The use of this coding scheme implicates a role for the supramarginal gyrus in verb-naming behavior. These data are discussed with respect to a functional-anatomical pathway underlying verb naming

Visualization-Based Mapping of Language Function in the Brain

Cortical language maps, obtained through intraoperative electrical stimulation studies, provide a rich source of information for research on language organization. Previous studies have shown interesting correlations between the distribution of essential language sites and such behavioral indicators as verbal IQ and have provided suggestive evidence for regarding human language cortex as an organization of multiple distributed systems. Noninvasive studies using ECoG, PET, and functional MR lend support to this model; however, there as yet are no studies that integrate these two forms of information. In this paper we describe a method for mapping the stimulation data onto a 3-D MRI-based neuroanatomic model of the individual patient. The mapping is done by comparing an intraoperative photograph of the exposed cortical surface with a computer-based MR visualization of the surface, interactively indicating corresponding stimulation sites, and recording 3-D MR machine coordinates of the indicated sites. Repeatability studies were performed to validate the accuracy of the mapping technique. Six observers—a neurosurgeon, a radiologist, and four computer scientists, independently mapped 218 stimulation sites from 12 patients. The mean distance of a mapping from the mean location of each site was 2.07 mm, with a standard deviation of 1.5 mm, or within 5.07 mm with 95% confidence. Since the surgical sites are accurate within approximately 1 cm, these results show that the visualization-based approach is accurate within the limits of the stimulation maps. When incorporated within the kind of information system envisioned by the Human Brain Project, this anatomically based method will not only provide a key link between noninvasive and invasive approaches to understanding language organization, but will also provide the basis for studying the relationship between language function and anatomical variability

Lightweight XML-based query, integration and visualization of distributed, multimodality brain imaging data

A need of many neuroimaging researchers is to integrate multimodality brain data that may be stored in separate databases. To address this need we have developed a framework that provides a uniform XML-based query interface across multiple online data sources. The development of this framework is driven by the need to integrate neurosurgical and neuroimaging data related to language. The data sources for the language studies are 1) a web-accessible relational database of neurosurgical cortical stimulation mapping data (CSM) that includes patient-specific 3-D coordinates of each stimulation site mapped to an MRI reconstruction of the patient brain surface; and 2) an XML database of fMRI and structural MRI data and analysis results, created automatically by a batch program we have embedded in SPM. To make these sources available for querying each is wrapped as an XML view embedded in a web service. A top level web application accepts distributed XQueries over the sources, which are dispatched to the underlying web services. Returned results can be displayed as XML, HTML, CSV (Excel format), a 2-D schematic of a parcellated brain, or a 3-D brain visualization. In the latter case the CSM patient-specific coordinates returned by the query are sent to a transformation web-service for conversion to normalized space, after which they are sent to our 3-D visualization program MindSeer, which is accessed via Java WebStart through a generated link. The anatomical distribution of pooled CSM sites can then be visualized using various surfaces derived from brain atlases. As this framework is further developed and generalized we believe it will have appeal for researchers who wish to query, integrate and visualize results across their own databases as well as those of collaborators