Short Time-Scale Sensory Coding in S1 during Discrimination of Whisker Vibrotactile Sequences.

Rodent whisker input consists of dense microvibration sequences that are often temporally integrated for perceptual discrimination. Whether primary somatosensory cortex (S1) participates in temporal integration is unknown. We trained rats to discriminate whisker impulse sequences that varied in single-impulse kinematics (5-20-ms time scale) and mean speed (150-ms time scale). Rats appeared to use the integrated feature, mean speed, to guide discrimination in this task, consistent with similar prior studies. Despite this, 52% of S1 units, including 73% of units in L4 and L2/3, encoded sequences at fast time scales (≤20 ms, mostly 5-10 ms), accurately reflecting single impulse kinematics. 17% of units, mostly in L5, showed weaker impulse responses and a slow firing rate increase during sequences. However, these units did not effectively integrate whisker impulses, but instead combined weak impulse responses with a distinct, slow signal correlated to behavioral choice. A neural decoder could identify sequences from fast unit spike trains and behavioral choice from slow units. Thus, S1 encoded fast time scale whisker input without substantial temporal integration across whisker impulses.

Development, Validation, and Clinical Utility of a Six-gene Signature to Predict Aggressive Prostate Cancer.

BACKGROUND: Molecular signatures in prostate cancer (PCa) tissue can provide useful prognostic information to improve the understanding of a patient's risk of harbouring aggressive disease. OBJECTIVE: To develop and validate a gene signature that adds independent prognostic information to clinical parameters for better treatment decisions and patient management. DESIGN, SETTING, AND PARTICIPANTS: Expression of 14 genes was evaluated in radical prostatectomy (RP) tissue from an Irish cohort of PCa patients (n = 426). A six-gene molecular risk score (MRS) was identified with strong prognostic performance to predict adverse pathology (AP) at RP or biochemical recurrence (BCR). The MRS was combined with the Cancer of the Prostate Risk Assessment (CAPRA) score, to create a molecular and clinical risk score (MCRS), and validated in a Swedish cohort (n = 203). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary AP outcome was assessed by the likelihood ratio statistics and area under the receiver operating characteristics curves (AUC) from logistic regression models. The secondary time to BCR outcome was assessed by likelihood ratio statistics and C-indexes from Cox proportional hazard regression models. RESULTS AND LIMITATIONS: The six-gene signature was significantly (p < 0.0001) prognostic and added significant prognostic value to clinicopathological features for AP and BCR outcomes. For both outcomes, both the MRS and the MCRS increased the AUC/C-index when added to European Association of Urology (EAU) and CAPRA scores. Limitations include the retrospective nature of this study. CONCLUSIONS: The six-gene signature has strong performance for the prediction of AP and BCR in an independent clinical validation study. MCRS improves prognostic evaluation and can optimise patient management after RP. PATIENT SUMMARY: We found that the expression panel of six genes can help predict whether a patient is likely to have a disease recurrence after radical prostatectomy surgery.

Heterogeneous representations in the superior parietal lobule are common across reaches to visual and proprioceptive targets.

The planning and control of sensory-guided movements requires the integration of multiple sensory streams. Although the information conveyed by different sensory modalities is often overlapping, the shared information is represented differently across modalities during the early stages of cortical processing. We ask how these diverse sensory signals are represented in multimodal sensorimotor areas of cortex in macaque monkeys. Although a common modality-independent representation might facilitate downstream readout, previous studies have found that modality-specific representations in multimodal cortex reflect upstream spatial representations. For example, visual signals have a more eye-centered representation. We recorded neural activity from two parietal areas involved in reach planning, area 5 and the medial intraparietal area (MIP), as animals reached to visual, combined visual and proprioceptive, and proprioceptive targets while fixing their gaze on another location. In contrast to other multimodal cortical areas, the same spatial representations are used to represent visual and proprioceptive signals in both area 5 and MIP. However, these representations are heterogeneous. Although we observed a posterior-to-anterior gradient in population responses in parietal cortex, from more eye-centered to more hand- or body-centered representations, we do not observe the simple and discrete reference frame representations suggested by studies that focused on identifying the "best-match" reference frame for a given cortical area. In summary, we find modality-independent representations of spatial information in parietal cortex, although these representations are complex and heterogeneous.

Formulating latent growth using an explanatory item response model approach.

In this paper, we present a way to extend the Hierarchical Generalized Linear Model (HGLM; Kamata (2001), Raudenbush (1995)) to include the many forms of measurement models available under the formulation known as the Random Coefficients Multinomial Logit (MRCML) Model (Adams, Wilson and Wang, 1997), and apply that to growth modeling. First, we review two different traditions in modeling growth studies: the first is based in the hierarchical linear modeling (HLM) tradition, and the second, which is the topic of this paper, is rooted in the Rasch measurement tradition - this is the linear Latent Growth Item Response Model (LG-IRM). Going beyond the linear case, the LG-IRM approach allows us to considerably extend the range of models available in the HLM tradition to incorporate several of the extensions of IRT models that are used in creating explanatory item response models (EIRM; De Boeck and Wilson, 2004). We next present a number of extensions - including polynomial growth modeling, differential item functioning (DIF) effects, growth functions that can be approximated by polynomial expressions, provision for polytomous responses, person and item covariates (and time varying covariates), and multiple dimensions of growth. We provide two empirical examples to illustrate several of the models, using the ConQuest software (Wu, Adams, Wilson and Haldane, 2008) to carry out the analyses. We also provide several simulations to investigate the success of the estimation procedures.

A comparative analysis of family adaptability and cohesion ratings among traumatized urban youth.

OBJECTIVE: Given the need to identify psychological risk factors among traumatized youth, this study examined the family functioning of traumatized youth with or without PTSD and a nonclinical sample. METHOD: The Family Adaptability and Cohesion Evaluation Scales, second edition (FACES II; Olson, Portner, & Bell, 1982), scores of youth with posttraumatic stress disorder (PTSD; n = 29) were compared with the scores of trauma-exposed youth without PTSD (n = 48) and a nontraumatized comparison group (n = 44). Child diagnostic interviews determined that all participants were free of major comorbid disorders. RESULTS: The FACES II scores of the participants with PTSD were not significantly different from the scores of trauma-exposed youth without PTSD and the nontraumatized comparison group. FACES II scores were also not significantly different between the trauma-exposed youth without PTSD and the nontraumatized comparison group. CONCLUSIONS: PTSD and trauma-exposure without PTSD were not associated with variations in the perception of family functioning as measured by the FACES II. (PsycINFO Database Record

Sensory transformations and the use of multiple reference frames for reach planning.

The sensory signals that drive movement planning arrive in a variety of 'reference frames', and integrating or comparing them requires sensory transformations. We propose a model in which the statistical properties of sensory signals and their transformations determine how these signals are used. This model incorporates the patterns of gaze-dependent errors that we found in our human psychophysics experiment when the sensory signals available for reach planning were varied. These results challenge the widely held ideas that error patterns directly reflect the reference frame of the underlying neural representation and that it is preferable to use a single common reference frame for movement planning. We found that gaze-dependent error patterns, often cited as evidence for retinotopic reach planning, can be explained by a transformation bias and are not exclusively linked to retinotopic representations. Furthermore, the presence of multiple reference frames allows for optimal use of available sensory information and explains task-dependent reweighting of sensory signals.

A multiprotein trafficking complex composed of SAP97, CASK, Veli, and Mint1 is associated with inward rectifier Kir2 potassium channels.

Strong inward rectifier potassium (Kir2) channels are important in the control of cell excitability, and their functions are modulated by interactions with intracellular proteins. Here we identified a complex of scaffolding/trafficking proteins in brain that associate with Kir2.1, Kir2.2, and Kir2.3 channels. By using a combination of affinity interaction pulldown assays and co-immunoprecipitations from brain and transfected cells, we demonstrated that a complex composed of SAP97, CASK, Veli, and Mint1 associates with Kir2 channels via the C-terminal PDZ-binding motif. We further demonstrated by using in vitro protein interaction assays that SAP97, Veli-1, or Veli-3 binds directly to the Kir2.2 C terminus and recruits CASK. Co-immunoprecipitations indicated that specific Veli isoforms participate in forming distinct protein complexes in brain, where Veli-1 stably associates with CASK and SAP97, Veli-2 associates with CASK and Mint1, and Veli-3 associates with CASK, SAP97, and Mint1. Additionally, immunocytochemistry of rat cerebellum revealed overlapping expression of Kir2.2, SAP97, CASK, Mint1, with Veli-1 in the granule cell layer and Veli-3 in the molecular layer. We propose a model whereby Kir2.2 associates with distinct SAP97-CASK-Veli-Mint1 complexes. In one complex, SAP97 interacts directly with the Kir2 channels and recruits CASK, Veli, and Mint1. Alternatively, Veli-1 or Veli-3 interacts directly with the Kir2 channels and recruits CASK and SAP97; association of Mint1 with the complex requires Veli-3. Expression of Kir2.2 in polarized epithelial cells resulted in targeting of the channels to the basolateral membrane and co-localization with SAP97 and CASK, whereas a dominant interfering form of CASK caused the channels to mislocalize. Therefore, CASK appears to be a central protein of a macromolecular complex that participates in trafficking and plasma membrane localization of Kir2 channels.

Protein trafficking and anchoring complexes revealed by proteomic analysis of inward rectifier potassium channel (Kir2.x)-associated proteins.

Inward rectifier potassium (Kir) channels play important roles in the maintenance and control of cell excitability. Both intracellular trafficking and modulation of Kir channel activity are regulated by protein-protein interactions. We adopted a proteomics approach to identify proteins associated with Kir2 channels via the channel C-terminal PDZ binding motif. Detergent-solubilized rat brain and heart extracts were subjected to affinity chromatography using a Kir2.2 C-terminal matrix to purify channel-interacting proteins. Proteins were identified with multidimensional high pressure liquid chromatography coupled with electrospray ionization tandem mass spectrometry, N-terminal microsequencing, and immunoblotting with specific antibodies. We identified eight members of the MAGUK family of proteins (SAP97, PSD-95, Chapsyn-110, SAP102, CASK, Dlg2, Dlg3, and Pals2), two isoforms of Veli (Veli-1 and Veli-3), Mint1, and actin-binding LIM protein (abLIM) as Kir2.2-associated brain proteins. From heart extract purifications, SAP97, CASK, Veli-3, and Mint1 also were found to associate with Kir2 channels. Furthermore, we demonstrate for the first time that components of the dystrophin-associated protein complex, including alpha1-, beta1-, and beta2-syntrophin, dystrophin, and dystrobrevin, interact with Kir2 channels, as demonstrated by immunoaffinity purification and affinity chromatography from skeletal and cardiac muscle and brain. Affinity pull-down experiments revealed that Kir2.1, Kir2.2, Kir2.3, and Kir4.1 all bind to scaffolding proteins but with different affinities for the dystrophin-associated protein complex and SAP97, CASK, and Veli. Immunofluorescent localization studies demonstrated that Kir2.2 co-localizes with syntrophin, dystrophin, and dystrobrevin at skeletal muscle neuromuscular junctions. These results suggest that Kir2 channels associate with protein complexes that may be important to target and traffic channels to specific subcellular locations, as well as anchor and stabilize channels in the plasma membrane.