Modulation of pain ratings by expectation and uncertainty: Behavioral characteristics and anticipatory neural correlates.

Expectations about the magnitude of impending pain exert a substantial effect on subsequent perception. However, the neural mechanisms that underlie the predictive processes that modulate pain are poorly understood. In a combined behavioral and high-density electrophysiological study we measured anticipatory neural responses to heat stimuli to determine how predictions of pain intensity, and certainty about those predictions, modulate brain activity and subjective pain ratings. Prior to receiving randomized laser heat stimuli at different intensities (low, medium or high) subjects (n=15) viewed cues that either accurately informed them of forthcoming intensity (certain expectation) or not (uncertain expectation). Pain ratings were biased towards prior expectations of either high or low intensity. Anticipatory neural responses increased with expectations of painful vs. non-painful heat intensity, suggesting the presence of neural responses that represent predicted heat stimulus intensity. These anticipatory responses also correlated with the amplitude of the Laser-Evoked Potential (LEP) response to painful stimuli when the intensity was predictable. Source analysis (LORETA) revealed that uncertainty about expected heat intensity involves an anticipatory cortical network commonly associated with attention (left dorsolateral prefrontal, posterior cingulate and bilateral inferior parietal cortices). Relative certainty, however, involves cortical areas previously associated with semantic and prospective memory (left inferior frontal and inferior temporal cortex, and right anterior prefrontal cortex). This suggests that biasing of pain reports and LEPs by expectation involves temporally precise activity in specific cortical networks.

Exploring the use of sensors to measure behavioral interactions: an experimental evaluation of using hand trajectories.

Humans appear to be sensitive to relative small changes in their surroundings. These changes are often initially perceived as irrelevant, but they can cause significant changes in behavior. However, how exactly people's behavior changes is often hard to quantify. A reliable and valid tool is needed in order to address such a question, ideally measuring an important point of interaction, such as the hand. Wearable-body-sensor systems can be used to obtain valuable, behavioral information. These systems are particularly useful for assessing functional interactions that occur between the endpoints of the upper limbs and our surroundings. A new method is explored that consists of computing hand position using a wearable sensor system and validating it against a gold standard reference measurement (optical tracking device). Initial outcomes related well to the gold standard measurements (r = 0.81) showing an acceptable average root mean square error of 0.09 meters. Subsequently, the use of this approach was further investigated by measuring differences in motor behavior, in response to a changing environment. Three subjects were asked to perform a water pouring task with three slightly different containers. Wavelet analysis was introduced to assess how motor consistency was affected by these small environmental changes. Results showed that the behavioral motor adjustments to a variable environment could be assessed by applying wavelet coherence techniques. Applying these procedures in everyday life, combined with correct research methodologies, can assist in quantifying how environmental changes can cause alterations in our motor behavior.

Self-stabilization and behavioral diversity of embodied adaptive locomotion

Locomotion is of fundamental importance in understanding adaptive behavior. In this paper we present two case studies of robot locomotion that demonstrate how higher level of behavioral diversity can be achieved while observing the principle of cheap design. More precisely, it is shown that, by exploiting the dynamics of the system-environment interaction, very simple controllers can be designed which is essential to achieve rapid locomotion. Special consideration must be given to the choice of body materials. We conclude with some speculation about the importance of locomotion for understanding cognition. © Springer-Verlag Berlin Heidelberg 2004.

Characterization of diurnal photosynthetic rhythms in the marine diatom Skeletonema costatum grown in synchronous culture under ambient and elevated CO2

Photosynthetic performance was examined in Skeletonema costatum (Greville) Cleve. under 12: 12-h light: dark (LD) cycle at ambient CO2 (350 muL L-1) and elevated CO2 (1000 muL L-1). At ambient CO2, the cellular chlorophyll a content, the light-saturated photosynthetic rate (P-m), the initial slope of the light saturation curves ( a), the photochemical efficiency of PSII (F-v/F-m), the apparent carboxylating efficiency (ACE) and the photosynthetic affinity for CO2 [1/K-m (CO2)] all showed rhythmical changes with different amplitudes during the light period. The P-m had similar changing pattern in the light period with the ACE and 1/K-m (CO2) rather than with the alpha and F-v/F-m, indicating that rhythmical changes of photosynthetic capacity may be mainly controlled by the activity of C- reduction associated with CO2 uptake during the light period. The CO2 enrichment reduced the ACE and the affinity to CO2, and increased the a, cellular chlorophyll a content and P m based on cell number. By contrast, the changing patterns of all photosynthetic parameters examined here during the light period had almost the same for cells grown at ambient CO2 and elevated CO2, suggesting that the photosynthetic rhythms of S. costatum are not affected by CO2 enrichment.

An Accurate and Fast Behavioral Model for PLL Frequency Synthesizer Phase Noise/Spurs Prediction

This paper presents a behavior model for PLL Frequency Synthesizer. All the noise sources are modeled with noise voltages or currents in time-domain. An accurate VCO noise model is introduced, including both thermal noise and 1/f noise. The behavioral model can be co-simulated with transistor level circuits with fast speed and provides more accurate phase noise and spurs prediction. Comparison shows that simulation results match very well with measurement results.

Circadian rhythms in the growth and reproduction of the brown alga Undaria pinnatifida and gametogenesis under different photoperiods

Circadian growth rhythm of the juvenile sporophyte of the brown alga Undaria pirznatifida was measured with the computer-aided image analysis system in constant florescent white light under constant temperature (10 degrees C). The growth rhythm persisted for 4 d in constant light with a free-running period of 25. 6 h. Egg release from filamentous gametophytes pre-cultured in the light - dark regime was evaluated for six consecutive days at fixed time intervals in constant white light and 12 h light per day. Egg release rhythm persisted for 3 d in both regimes, indicating the endogenous nature. Temporal scale of egg release and gametogenesis in 18, 16, 12 and 8 h light per day were evaluated respectively using vegetatively propagated filamentous gametophytes. Egg release occurred 2 h after the onset of dark phase and peaked at midnight. Evaluation of the rates of oogonium formation, egg release or fertilization revealed no significant differences in four light-dark regimes, indicating; the great plasticity of sexual reproduction. No photoperiodic effect in gametogenesis in terms of oogonium formation and egg release was found, but fertilization in short days was significantly higher than in long days. Results of this investigation further confirmed the general occurrence of circadian rhythms in inter-tidal seaweed species.

Behavioral responses of tilapia (Oreochromis niloticus) to acute fluctuations in dissolved oxygen levels as monitored by computer vision

Behavioral and ventilatory parameters have the possibility of predicting the stress state of fish in vivo and in situ. This paper presents a new image-processing algorithm for quantifying the average swimming speed of a fish school in an aquarium. This method is based on the alteration in projected area caused by the movement of individual fish during frame sequences captured at given time intervals. The image enhancement method increases the contrast between fish and background, and is thus suitable for use in turbid aquaculture water. Behavioral parameters (swimming activity and distribution parameters) and changes in ventilation frequency (VF) of tilapia (Oreochromis niloticus) responded to acute fluctuations in dissolved oxygen (DO) which were monitored continuously in the course of normoxia, falling DO level, maintenance of hypoxia (three levels of 1.5, 0.8 and 0.3 mg l(-1)) and subsequent recovery to normoxia. These parameters responded sensitively to acute variations in DO level; they displayed significant changes (P < 0.05) during severe hypoxia (0.8 and 0.3 mg l(-1) level) compared with normoxic condition, but there was no significant difference under conditions of mild hypoxia (1.5 mg l(-1) level). There was no significant difference in VF between two levels of severe hypoxia 0.8 and 0.3 mg l(-1) level during the low DO condition. The activity and distribution parameters displayed distinguishable differences between the 0.8 and 0.3 mg l(-1) levels. The behavioral parameters are thus capable of distinguishing between different degrees of severe hypoxia, though there were relatively large fluctuations. (c) 2006 Elsevier B.V. All rights reserved.

Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives

A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model-the N-STREAMS neural network model-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.

Space, Time and Learning in the Hippocampus: How Fine Spatial and Temporal Scales Are Expanded into Population Codes for Behavioral Control

The hippocampus participates in multiple functions, including spatial navigation, adaptive timing, and declarative (notably, episodic) memory. How does it carry out these particular functions? The present article proposes that hippocampal spatial and temporal processing are carried out by parallel circuits within entorhinal cortex, dentate gyrus, and CA3 that are variations of the same circuit design. In particular, interactions between these brain regions transform fine spatial and temporal scales into population codes that are capable of representing the much larger spatial and temporal scales that are needed to control adaptive behaviors. Previous models of adaptively timed learning propose how a spectrum of cells tuned to brief but different delays are combined and modulated by learning to create a population code for controlling goal-oriented behaviors that span hundreds of milliseconds or even seconds. Here it is proposed how projections from entorhinal grid cells can undergo a similar learning process to create hippocampal place cells that can cover a space of many meters that are needed to control navigational behaviors. The suggested homology between spatial and temporal processing may clarify how spatial and temporal information may be integrated into an episodic memory.

The implementation of a translational study involving a primary care based behavioral program to improve blood pressure control: The HTN-IMPROVE study protocol (01295).

BACKGROUND: Despite the impact of hypertension and widely accepted target values for blood pressure (BP), interventions to improve BP control have had limited success. OBJECTIVES: We describe the design of a 'translational' study that examines the implementation, impact, sustainability, and cost of an evidence-based nurse-delivered tailored behavioral self-management intervention to improve BP control as it moves from a research context to healthcare delivery. The study addresses four specific aims: assess the implementation of an evidence-based behavioral self-management intervention to improve BP levels; evaluate the clinical impact of the intervention as it is implemented; assess organizational factors associated with the sustainability of the intervention; and assess the cost of implementing and sustaining the intervention. METHODS: The project involves three geographically diverse VA intervention facilities and nine control sites. We first conduct an evaluation of barriers and facilitators for implementing the intervention at intervention sites. We examine the impact of the intervention by comparing 12-month pre/post changes in BP control between patients in intervention sites versus patients in the matched control sites. Next, we examine the sustainability of the intervention and organizational factors facilitating or hindering the sustained implementation. Finally, we examine the costs of intervention implementation. Key outcomes are acceptability and costs of the program, as well as changes in BP. Outcomes will be assessed using mixed methods (e.g., qualitative analyses--pattern matching; quantitative methods--linear mixed models). DISCUSSION: The study results will provide information about the challenges and costs to implement and sustain the intervention, and what clinical impact can be expected.

Changes in midbrain pain receptor expression, gait and behavioral sensitivity in a rat model of radiculopathy.

Intervertebral disc herniation may contribute to inflammatory processes that associate with radicular pain and motor deficits. Molecular changes at the affected dorsal root ganglion (DRG), spinal cord, and even midbrain, have been documented in rat models of radiculopathy or nerve injury. The objective of this study was to evaluate gait and the expression of key pain receptors in the midbrain in a rodent model of radiculopathy. Radiculopathy was induced by harvesting tail nucleus pulposus (NP) and placing upon the right L5 DRG in rats (NP-treated, n=12). Tail NP was discarded in sham-operated animals (n=12). Mechanical allodynia, weight-bearing, and gait were evaluated in all animals over time. At 1 and 4 weeks after surgery, astrocyte and microglial activation was tested in DRG sections. Midbrain sections were similarly evaluated for immunoreactivity to serotonin (5HT(2B)), mu-opioid (µ-OR), and metabotropic glutamate (mGluR4 and 5) receptor antibodies. NP-treated animals placed less weight on the affected limb 1 week after surgery and experienced mechanical hypersensitivity over the duration of the study. Astroctye activation was observed at DRGs only at 4 weeks after surgery. Findings for pain receptors in the midbrain of NP-treated rats included an increased expression of 5HT(2B) at 1, but not 4 weeks; increased expression of µ-OR and mGluR5 at 1 and 4 weeks (periaqueductal gray region only); and no changes in expression of mGluR4 at any point in this study. These observations provide support for the hypothesis that the midbrain responds to DRG injury with a transient change in receptors regulating pain responses.

Rapid behavioral and genomic responses to social opportunity.

From primates to bees, social status regulates reproduction. In the cichlid fish Astatotilapia (Haplochromis) burtoni, subordinate males have reduced fertility and must become dominant to reproduce. This increase in sexual capacity is orchestrated by neurons in the preoptic area, which enlarge in response to dominance and increase expression of gonadotropin-releasing hormone 1 (GnRH1), a peptide critical for reproduction. Using a novel behavioral paradigm, we show for the first time that subordinate males can become dominant within minutes of an opportunity to do so, displaying dramatic changes in body coloration and behavior. We also found that social opportunity induced expression of the immediate-early gene egr-1 in the anterior preoptic area, peaking in regions with high densities of GnRH1 neurons, and not in brain regions that express the related peptides GnRH2 and GnRH3. This genomic response did not occur in stable subordinate or stable dominant males even though stable dominants, like ascending males, displayed dominance behaviors. Moreover, egr-1 in the optic tectum and the cerebellum was similarly induced in all experimental groups, showing that egr-1 induction in the anterior preoptic area of ascending males was specific to this brain region. Because egr-1 codes for a transcription factor important in neural plasticity, induction of egr-1 in the anterior preoptic area by social opportunity could be an early trigger in the molecular cascade that culminates in enhanced fertility and other long-term physiological changes associated with dominance.

Can Genetics Predict Response to Complex Behavioral Interventions? Evidence from a Genetic Analysis of the Fast Track Randomized Control Trial.

Early interventions are a preferred method for addressing behavioral problems in high-risk children, but often have only modest effects. Identifying sources of variation in intervention effects can suggest means to improve efficiency. One potential source of such variation is the genome. We conducted a genetic analysis of the Fast Track randomized control trial, a 10-year-long intervention to prevent high-risk kindergarteners from developing adult externalizing problems including substance abuse and antisocial behavior. We tested whether variants of the glucocorticoid receptor gene NR3C1 were associated with differences in response to the Fast Track intervention. We found that in European-American children, a variant of NR3C1 identified by the single-nucleotide polymorphism rs10482672 was associated with increased risk for externalizing psychopathology in control group children and decreased risk for externalizing psychopathology in intervention group children. Variation in NR3C1 measured in this study was not associated with differential intervention response in African-American children. We discuss implications for efforts to prevent externalizing problems in high-risk children and for public policy in the genomic era.

Computer vision tools for the non-invasive assessment of autism-related behavioral markers

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.