Dream Imagery and Emotion.

The relationship between prominent visual imagery and emotion within dreams was investigated in relation to E. Hartmann's (1996) contextualizing image (CI) theory and M. Seligman and A. Yellen's (1987) dual imagery theory. Fifty-nine students recorded dreams over a 2-week period and submitted 115 dreams for analysis. Participants recorded ratings of emotion type and emotion intensity in each scene. Prominent visual images were identified and scored for intensity and detail by independent judges. As hypothesized from Hartmann's theory, there was a significant positive relationship between CI intensity and emotion intensity in the CI scene, emotion intensity generally peaked in the CI scene, and dreams containing a CI had higher overall ratings of emotion intensity than non-CI dreams. The result for the correlation of detail of prominent imagery with emotion was inconclusive, with a low positive correlation across CI scenes. This raises the possibility that the CI is not a unitary construct. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Relaxation with biofeedback-assisted guided imagery: The importance of breathing rate as an index of hypoarousal

Fifteen men and 35 women, suffering from a number of psychological and somatic disorders, were taught to relax by biofeedback-assisted deep-diaphragmatic breathing together with guided mental imagery. No instructions were given about rate. Breathing rate and pattern, PETCO2, and EEG were monitored before training and after the first three 2-minute training trials (session 1). In 27 subjects (54%), breathing patterns and rate were noted to resemble those reported by meditation practitioners (3 to 5 b/min). The PETCO2 and EEG changes support a hypothesis of metabolic hypoarousal. Four subjects spontaneously reported experiencing altered awareness. A centrally mediated hypoarousal response is tentatively implicated.     

Three major mesoplanktonic communities resolved by in situ imaging in the upper 500 m of the global ocean

Aim

The distribution of mesoplankton communities has been poorly studied at global scale, especially from in situ instruments. This study aims to (1) describe the global distribution of mesoplankton communities in relation to their environment and (2) assess the ability of various environmental-based ocean regionalizations to explain the distribution of these communities.

Location

Global ocean, 0–500 m depth.

Time Period

2008–2019.

Major Taxa Studied

Twenty-eight groups of large mesoplanktonic and macroplanktonic organisms, covering Metazoa, Rhizaria and Cyanobacteria.

Methods

From a global data set of 2500 vertical profiles making use of the Underwater Vision Profiler 5 (UVP5), an in situ imaging instrument, we studied the global distribution of large (>600 μm) mesoplanktonic organisms. Among the 6.8 million imaged objects, 330,000 were large zooplanktonic organisms and phytoplankton colonies, the rest consisting of marine snow particles. Multivariate ordination (PCA) and clustering were used to describe patterns in community composition, while comparison with existing regionalizations was performed with regression methods (RDA).

Results

Within the observed size range, epipelagic plankton communities were Trichodesmium-enriched in the intertropical Atlantic, Copepoda-enriched at high latitudes and in upwelling areas, and Rhizaria-enriched in oligotrophic areas. In the mesopelagic layer, Copepoda-enriched communities were also found at high latitudes and in the Atlantic Ocean, while Rhizaria-enriched communities prevailed in the Peruvian upwelling system and a few mixed communities were found elsewhere. The comparison between the distribution of these communities and a set of existing regionalizations of the ocean suggested that the structure of plankton communities described above is mostly driven by basin-level environmental conditions.

Main Conclusions

In both layers, three types of plankton communities emerged and seemed to be mostly driven by regional environmental conditions. This work sheds light on the role not only of metazoans, but also of unexpected large protists and cyanobacteria in structuring large mesoplankton communities.     

Absorption and imagery locate immune responses in the body

Imagery instructions specifying mucosal immunity should alter mucosal immunoglobulin A (m-IgA) levels in high absorbers, whose intent concentration evokes intense physiological responses. After screening for health status, 121 high or low absorbers were randomly assigned to either Relaxation Alone (R), Relaxation with Mucosal Immune Imagery (RI), or Vigilance Task control (VT). Before and after one 60-min intervention, subjects reported theory-relevant psychological variables and provided 5ml whole saliva, which was immediately frozen and assayed lateren masse with enzyme-linked immunoabsorbence (ELISA). MANOVA analysis of psychological variables replicated past research. ANOVA on residualized m-IgA found Time × Absorption interaction and Condition main effects. High more than low absorbers responded to relaxation with mucosal immune imagery by producing higher m-IgA. High absorbers appear able to locate where their immune systems will respond. Individual differences like absorption level need to be emphasized in diagnosis and treatment responsiveness.National Institutes of HealthM. Banks (Jasnoski) Gregerson, Department of Psychology, The George Washington University, changed to The Family Therapy Institute; Ingram M. Roberts, The George Washington University Medical Center, changed to Department of Medicine, Bridgeport Hospital; and Michael M. Amiri, The George Washington University Medical Center, changed to the Department of Neuroscience, NINDS Branch, National Institutes of Health. This research supported by an intra-mural BioMedical Research Grant from The George Washington University, was presented at the 1992 Annual Meeting of the Eastern Psychological Association, Boston, Massachusetts. Special thanks are extended to the following students who assisted instrumentally at various stages: undergraduates Lina Alathari, S. Theodor King, Beth Lieberman, Parisa Lotfi, Anita McClenon, and Karen Siscoe, and graduate student Mariken Hasert.     

Quantifying the recent expansion of native invasive rush species in a UK upland environment

Rushes, such as soft rush (Juncus effusus L.), hard rush (Juncus inflexus L.), and compact rush (Juncus conglomeratus L.) have become problem species within upland grasslands across the United Kingdom and the coastal grasslands of western Norway. Indeed, being largely unpalatable to livestock and having a vigorous reproductive ecology means that they can rapidly come to dominate swards. However, rush dominance results in a reduction in grassland biodiversity and farm productivity. Anecdotal evidence from the United Kingdom suggests that rush cover within marginal upland grasslands has increased considerably in recent decades. Yet, there is currently no published evidence to support this observation. Here, we use recent and historical Google Earth imagery to measure changes in rush frequency over a 13-year period within four survey years: 2005, 2009, 2015, and 2018. During each survey year, we quantified rush presence or absence using a series of quadrats located within 300 upland grassland plots in the West Pennine Moors, United Kingdom. Data were analysed in two stages, first, by calculating mean rush frequencies per sample year using all the available plot-year combinations (the full dataset), and second by examining differences in rush frequency using only the plots for which rush frequency data were available in every sample year (the continuous dataset). The full dataset indicated that rush frequency has increased by 82% between 2005 and 2018. Similarly, the continuous dataset suggested that rush frequency has increased by 174% over the same period, with the increases in frequency being statistically significant (p < .05) between 2005–2018 and 2009–2018. We discuss the potential drivers of rush expansion in the West Pennine Moors, the ecological and agronomic implications of grassland rush infestations, and priorities for future research.     

TIME-OF-DAY EFFECTS ON THE INTERNAL SIMULATION OF MOTOR ACTIONS: PSYCHOPHYSICAL EVIDENCE FROM POINTING MOVEMENTS WITH THE DOMINANT AND NON-DOMINANT ARM

It is well known that circadian rhythms modulate human physiology and behavior at various levels. However, chronobiological data concerning mental and sensorimotor states of motor actions are still lacking in the literature. In the present study, we examined the effects of time-of-day on two important aspects of the human motor behavior: prediction and laterality. Motor prediction was experimentally investigated by means of imagined movements and laterality by comparing the difference in temporal performance between right and left arm movements. Ten healthy participants had to actually perform or to imagine performing arm-pointing movements between two targets at different hours of the day (i.e., 08:00, 11:00, 14:00, 17:00, 20:00, and 23:00?h). Executed and imagined movements were accomplished with both the right and left arm. We found that both imagined and executed arm pointing movements significantly fluctuated through the day. Furthermore, the accuracy of motor prediction, investigated by the temporal discrepancy between executed and imagined movements, was significantly better in the afternoon (i.e., 14:00, 17:00, and 20:00?h) than morning (08:00 and 11:00?h) and evening (23:00?h). Our results also revealed that laterality was not stable throughout the day. Indeed, the smallest temporal differences between the two arms appeared at 08:00 and 23:00?h, whereas the largest ones occurred at the end of the morning (11:00?h). The daily variation of motor imagery may suggest that internal predictive models are flexible entities that are continuously updated throughout the day. Likewise, the variations in temporal performance between the right and the left arm during the day may indicate a relative independence of the two body sides in terms of circadian rhythms. In general, our findings suggest that cognitive (i.e., mental imagery) and motor (i.e., laterality) states of human behavior are modulated by circadian rhythms. (Author correspondence: charalambos.papaxanthis@u-bourgogne.fr)     

Motor Imagery EEG Spectral-Spatial Feature Optimization Using Dual-Tree Complex Wavelet and Neighbourhood Component Analysis

BackgroundFrequency band optimization improves the performance of common spatial pattern (CSP) in motor imagery (MI) tasks classification because MI-related electroencephalograms (EEGs) are highly frequency specific. Many variants of CSP algorithm divided the EEG into various sub bands and then applied CSP. However, the feature dimension of MI-EEG data increases with addition of frequency sub bands and requires efficient feature selection algorithms. The performance of CSP also depends on filtering techniques.MethodIn this study, we designed a dual tree complex wavelet transform based filter bank to filter the EEG into sub bands, instead of traditional filtering methods, which improved the spatial feature extraction efficiency. Further, after filtering EEG into different sub bands, we extracted spatial features from each sub band using CSP and optimized them by a proposed supervised learning framework based on neighbourhood component analysis (NCA). Subsequently, a support vector machine (SVM) is trained to perform classification.ResultsAn experimental study, conducted on two datasets (BCI Competition IV (Dataset 2b), and BCI competition III (Dataset IIIa)), validated the MI classification effectiveness of the proposed method in comparison with standard algorithms such as CSP, Filter bank CSP (CSP), and Discriminative FBCSP (DFBCSP). The average classification accuracy obtained by the proposed method for BCI Competition IV (Dataset 2b), and BCI Competition III (Dataset IIIa) are 84.02 ± 12.2 and 89.1 ± 7.50, respectively and found significant than that achieved by standard methods.ConclusionAchieved superior results suggest that the proposed algorithm can improve the performance of MI-based Brain-computer interface devices.     

From military training area to National Park over 20 years: Indicators for outcome evaluation in a large-scale restoration project in alpine Norway

There is a need for large-scale demonstrations to address the challenges and possibilities for upscaling of ecosystem restoration, and for learning and sharing knowledge across professions and habitats. Large-scale and complex restoration projects need new perspectives on goal formulation, indicators for success, and evaluation to encompass both scientific approaches and the tacit knowledge held by practitioners. The objective of this paper is to use the restoration of a 165 km² former military training area in alpine central Norway into National Park to demonstrate the challenges of upscaling and integration. Main tasks were to remove roads and technical infrastructure, prepare for natural recovery and remove undetonated ordnance. In total, 19 indicators were used to evaluate the restoration outcome, related to four overall restoration goals formulated by the Norwegian Parliament: nature protection, considerable nature benefit, safe civilian use, and restoration back to natural state. Despite an overall linear project cycle, a dynamic and adaptive process of planning, implementation and evaluation was performed at the individual site scale. A dynamic dialogue between all involved professions allowed for exchanging scientific and tacit knowledge, and continuous improvement of solutions. The study demonstrated the relevance of qualitative assessments combined with quantitative indicators – i.e., use of expert opinions and the continuous evaluation to feed back into planning and improving the implementation of restoration measures. A “Green training” procedure was developed, linking top-down formally defined settings of the project with bottom-up hand-on solutions. This procedure can be directly transferred to other large-scale mitigation and restoration projects. Demonstration sites like the one described here, are valuable to develop an expanded vision of restoration to meet the UN Sustainable Goals.