Separate Principal Component Analyses Research Articles

The characteristics of music video experiences and their relationship to future listening outcomes

Music videos are a popular method of consuming music; however, the characteristics of these experiences and their effects on music perception are poorly understood. An online survey ( N = 155) was designed using theoretical insight from Dasovich-Wilson et al.’s (2022) Intention Attention Reaction and Retention (IARR) framework. The survey consisted of two parts: the first explored the key characteristics of music video experiences, and the second explored their effects on subsequent listening outcomes. Separate principal component analyses (PCAs) were performed on each part to differentiate between the experience itself (Experience components) and the effects on subsequent listens (Retention outcomes). Relationships between Experience components and Retention outcomes were explored using correlation and regression analyses. The results suggest that music video experiences characterized by performance gestures and narratives have the strongest influence on music perception. These findings shed light on how extramusical information from music videos influences mechanisms related to visual imagery and personal associations.

Measure of perceived social support from family, friends, and healthcare providers for Korean adolescents and young adults with cancer

ObjectiveAssessing the perceived social support (PSS) that adolescents and young adults (AYAs) with cancer receive from family, friends, and healthcare providers is critical to promoting their adjustment. This study developed a reliable and comprehensive self-report PSS assessment tool that measures various aspects of social support by translating existing measurements into Korean. MethodsThe translation was completed in accordance with international guidelines. To focus on cultural adaptation, the main ideas associated with items were translated to reflect the differences between Western and Eastern culture. In total, 144 Korean AYAs with cancer (mean age: 17.0 years; 45.8% female) completed the translated version. A separate principal component analysis (PCA) with an orthogonal quartimax rotation, a minimum eigenvalue of 1.0, and minimum factor loadings of 0.50 was used for each subscale. Cronbach's alpha coefficients were calculated for each PCA-derived subscale. ResultsFour subscales with 46 items were identified. Two subscales represented perceived emotional support within the family (PSS-ESF, 14 items) and the AYA's perceived helpfulness within the family (PSS-HWF, 3 items). The third scale represented the perceived support of friends (PSS-Friends, 14 items). The final scale represented the perceived support of healthcare providers (PSS-HCPs, 15 items). Excellent reliability per subscale was demonstrated (Cronbach's alpha: 0.93 for PSS-ESF, 0.73 for PSS-HWF, and 0.92 each for PSS-Friends and PSS-HCPs). ConclusionsA culturally adapted and reliable Korean version questionnaire with four independent subscales was developed. Further assessment of the Korean PSS is required and will contribute to the development of culturally adapted and tailored interventions.

A Novel Approach to Measuring Spatiotemporal Changes in Social Vulnerability at the Local Level in Portugal

Social vulnerability, as one of the risk components, partially explains the magnitude of the impacts observed after a disaster. In this study, a spatiotemporally comparable assessment of social vulnerability and its drivers was conducted in Portugal, at the civil parish level, for three census frames. The first challenging step consisted of the selection of meaningful and consistent variables over time. Data were normalized using the Adjusted Mazziotta-Pareto Index (AMPI) to obtain comparable adimensional-normalized values. A joint principal component analysis (PCA) was applied, resulting in a robust set of variables, interpretable from the point of view of their self-grouping around vulnerability drivers. A separate PCA for each census was also conducted, which proved to be useful in analyzing changes in the composition and type of drivers, although only the joint PCA allows the monitoring of spatiotemporal changes in social vulnerability scores and drivers from 1991 to 2011. A general improvement in social vulnerability was observed for Portugal. The two main drivers are the economic condition (PC1), and aging and depopulation (PC2). The remaining drivers highlighted are uprooting and internal mobility, and daily commuting. Census data proved their value in the territorial, social, and demographic characterization of the country, to support medium- and long-term disaster risk reduction measures.

MAO-B Polymorphism Associated with Progression in a Chinese Parkinson's Disease Cohort but Not in the PPMI Cohort.

Introduction Genetic factors play an important role in Parkinson's disease (PD) risk. However, the genetic contribution to progression in Chinese PD patients has rarely been studied. This study investigated genetic associations with progression based on 30 PD risk loci common in a longitudinal cohort of Chinese PD patients and the Parkinson's Progression Markers Initiative (PPMI) cohort. Methods PD patients from the true world (TW) Chinese PD longitudinal cohort and the PPMI cohort with demographic information and assessment scales were assessed. A panel containing 30 PD risk single nucleotide polymorphisms was tested. Progression rates of each scale were derived from random-effect slope values of mixed-effects regression models. Progression rates of multiple assessments were combined by using principal component analysis (PCA) to derive scores for composite, motor, and nonmotor progression. The association of genetic polymorphism and separate scales or PCA progression was analysed via linear regression. Results In the Chinese PD cohort, MAOB rs1799836 was associated with progression based on the Montreal Cognitive Assessment, the top 3 principal components (PCs) of nonmotor PCA and PC1 of the composite PCA. In the PPMI cohort, both MDS-Unified Parkinson's Disease Rating Scale II and motor PC1 progression were associated with RIT2 rs12456492. The PARK16 haplotype was associated with Geriatric Depression Scale and the State-Trait Anxiety Inventory for Adults progression, and the SNCA haplotype was associated with the Hoehn-Yahr staging progression and motor PC1 progression. Ethnicity-stratified analysis showed that the association between MAOB rs1799836 and PD progression may be specific to Asian or Chinese patients. Conclusion MAOB rs1799836 was associated with the progression of nonmotor symptoms, especially cognitive impairment, and the composite progression of motor and nonmotor symptoms within our Chinese PD cohort. The RIT2 rs12456492 and SNCA haplotypes were associated with motor function decline, and the PARK16 haplotype was associated with progression in mood in the PPMI cohort.

Hip and knee joint angle patterns and kicking velocity in female and male professional soccer players: A principal component analysis of waveforms approach

ABSTRACT This study used principal component analysis (PCA) of waveforms to extract movement patterns from hip and knee angle time-series data; and determined if the extracted movement patterns were predictors of ball velocity during a soccer kick. Twenty-three female and nineteen male professional soccer players performed maximal effort instep kicks while motion capture and post-impact ball velocities data were recorded. Three-dimensional hip and knee joint angle time-series data were calculated from the beginning of the kicking leg’s backswing phase until the end of the follow-through phase and entered into separate PCAs for females and males. Three principal components (PC) (i.e., movement patterns) were extracted and PC scores were calculated. Pearson correlation coefficients were calculated to establish correlations between hip and knee PC scores and kicking velocity. Results showed better kicking performance in male players was associated with a greater difference between the hip extension at the end of the backswing/beginning of the leg cocking phases and hip flexion at the end of the follow-through phase (r = −0.519, p = 0.023) and a delayed internal rotation of the hip (r = 0.475, p = 0.040). No significant correlations between ball velocity and hip and knee kinematics were found for female players.

The dimensions underlying first impressions of older adult faces are similar, but not identical, for young and older adult perceivers

First impressions based on facial cues have the potential to influence how older adults (OAs), a vulnerable population, are treated by others. The present study used a data-driven approach to examine dimensions underlying first impressions of OAs and whether those dimensions vary by perceiver age. In Experiment 1, young adult (YA) and OA participants provided unconstrained, written descriptions in response to OA faces. From these descriptors, 18 trait categories were identified that were similar, but not identical, across age groups. In Experiment 2, YA and OA participants rated OA faces on the trait words identified for their age group in Experiment 1. In separate principal components analyses, dimensions of sternness and confidence emerged for both groups. In Experiment 3, YA and OA participants rated these same faces on new words encompassing traits, emotion cues, and other appearance cues. Correlations between these ratings and factor scores showed that sternness is analogous to approachability for both age groups. Confidence is analogous to competence for both age groups and related to perceived age/health/attractiveness. Confidence was related to shyness for YAs but dominance for OAs. The current research has implications for a lifespan perspective on first impressions and informs functional accounts.

A principal component analysis of polycyclic aromatic hydrocarbon emission in NGC 7023

ABSTRACT We carried out a principal component analysis (PCA) of the fluxes of five polycyclic aromatic hydrocarbon (PAH) bands at 6.2, 7.7, 8.6, 11.0, and 11.2 µm in the reflection nebula NGC 7023 comprising of the photodissociation region (PDR) and a cavity. We find that only two principal components (PCs) are required to explain the majority of the observed variance in PAH fluxes ( 98 per cent). The first PC ( PC1), which is the primary driver of the variance, represents the total PAH emission. The second PC (PC2) is related to the ionization state of PAHs across the nebula. This is consistent with the results of a similar analysis of the PAH emission in NGC 2023. The biplots and the correlations of PCs with the various PAH ratios show that there are two subsets of ionic bands with the 6.2 and 7.7 µm bands forming one subset and the 8.6 and 11.0 µm bands the other. However, the distinction between these subsets is only present in the PDR. We have also carried out a separate PCA analysis of the PAH fluxes, this time only considering variations in the cavity. This shows that in the cavity, PC2 is not related to the charge state of PAHs but possibly to structural molecular changes.

A tutorial on the use of temporal principal component analysis in developmental ERP research – Opportunities and challenges

Developmental researchers are often interested in event-related potentials (ERPs). Data-analytic approaches based on the observed ERP suffer from major problems such as arbitrary definition of analysis time windows and regions of interest and the observed ERP being a mixture of latent underlying components. Temporal principal component analysis (PCA) can reduce these problems. However, its application in developmental research comes with the unique challenge that the component structure differs between age groups (so-called measurement non-invariance). Separate PCAs for the groups can cope with this challenge. We demonstrate how to make results from separate PCAs accessible for inferential statistics by re-scaling to original units. This tutorial enables readers with a focus on developmental research to conduct a PCA-based ERP analysis of amplitude differences. We explain the benefits of a PCA-based approach, introduce the PCA model and demonstrate its application to a developmental research question using real-data from a child and an adult group (code and data openly available). Finally, we discuss how to cope with typical challenges during the analysis and name potential limitations such as suboptimal decomposition results, data-driven analysis decisions and latency shifts.

The Effects of Concentrative Meditation on the Electroencephalogram in Novice Meditators.

Following investigations into the benefits of meditation on psychological health and well-being, research is now seeking to understand the mechanisms underlying these outcomes. This study aimed to identify natural alpha and theta frequency components during eyes-closed resting and concentrative meditation states and examined their differences within and between two testing sessions. Novice meditators had their EEG recorded during eyes-closed resting and concentrative meditation conditions, before and after engaging in a brief daily concentrative meditation practice for approximately one-month. Separate frequency Principal Components Analyses (f-PCA) yielded four spectral components of interest, congruent between both conditions and sessions: Delta-Theta-Alpha, Low Alpha, High Alpha, and Alpha-Beta. While all four components showed some increase in the meditation condition at the second session, only Low Alpha (∼9.5-10.0 Hz) showed similar increases while resting. These findings support the use of f-PCA as a novel method of data analysis in the investigation of psychophysiological states in meditation.

Comparing and combining sliding semilandmarks and weighted spherical harmonics for shape analysis.

Quantifying morphological variation is critical for conducting anatomical research. Three-dimensional geometric morphometric (3D GM) landmark analyses quantify shape using homologous Cartesian coordinates (landmarks). Setting up a high-density landmark set and placing it on all specimens, however, can be a time-consuming task. Weighted spherical harmonics (SPHARM) provides an alternative method for analyzing the shape of such objects. Here we compare sliding semilandmark and SPHARM analyses of the calcaneus of Gorilla gorilla gorilla (n=20), Pan troglodytes troglodytes (n=20), and Homo sapiens (n=20) to determine whether the SPHARM and sliding semilandmark analyses capture comparable levels of shape variation. We also compare both the sliding semilandmark and SPHARM analyses to a novel combination of the two methods, here termed SPHARM-sliding. In SPHARM-sliding, the vertices of the surface models produced from the SPHARM analysis (that are the same in number and relative location) are used as the starting landmark positions for a sliding semilandmark analysis. Calcaneal shape variation quantified by all three analyses was summarized using separate principal components analyses. Results were compared using the root mean square (RMS) and maximum distance between surface models of species averages scaled (up) to centroid size created from each analysis. The average RMS was 0.23mm between sliding semilandmark and SPHARM average surface models, 0.19mm between SPHARM and SPHARM sliding average surface models, and 0.22mm between sliding semilandmark and SPHARM sliding average surface models. Although results indicate that all three analyses are comparable methods for 3D shape analysis, there are advantages and disadvantages to each. While the SPHARM analysis is less time-intensive, it is unable to capture the same level of detail around the sharp edges of articular facets on average surface models as the sliding semilandmark analysis. The SPHARM analysis also does not allow for individual articular facets to be analyzed in isolation. SPHARM-sliding, however, captures the same level of detail as the sliding semilandmark analysis, and (as in the sliding semilandmark analysis) allows for the evaluation of individual portions of bone. SPHARM is a comparable method to a 3D GM analysis for small, irregularly shaped bones, such as the calcaneus, and SPHARM-sliding allows for an expedited set up process for a sliding semilandmark analysis.

Do self-ratings of the Pittsburgh Sleep Quality Index reflect actigraphy recordings of sleep quality or variability? An exploratory study of bipolar disorders versus healthy controls.

Sleep disturbances are typical symptoms of acute episodes of bipolar disorder (BD) and differentiate euthymic BD cases from healthy controls (HC). Researchers often employ objective recordings to evaluate sleep patterns, such as actigraphy, whilst clinicians often use subjective ratings, such as the Pittsburgh Sleep Quality Index (PSQI). As evidence suggests the measures may disagree, we decided to compare subjective (PSQI) and objective (3weeks of actigraphy) sleep profiles in BD cases and HC (n=154). We examined whether a dimensional approach helps to illustrate different patterns of sleep disturbances and whether the concordance between subjective and objective recordings varies according to clinical status (BD versus HC). Principal component analysis (PCA) extracted two factors from the PSQI, and separate PCAs of actigraphy recordings extracted two factors for mean values of sleep parameters and one factor for intra-individual variability. Correlational and linear regression analyses of PCA-derived dimensions demonstrated that, in both BD and HC, a PSQI "Sleep duration-efficiency" factor was significantly correlated with an actigraphy "Sleep initiation-duration" factor. Furthermore, in BD cases only, the PSQI total score and a PSQI "Sleep Impairments" factor were each significantly correlated with an actigraphy "Sleep Variability" factor. Overall, we found that subjective experiences of sleep may be modulated by different components of objectively recorded sleep in BD compared with HC. Also, the use of PCA enabled us to consider the multi-dimensional nature of subjective sleep, whilst the inclusion of intra-individual sleep variability afforded a more subtle evaluation of objective sleep.

Application of Principal Component Analysis of Sows' Behavioral Indicators of the Welfare Quality® Protocol to Determine Main Components of Behavior

Understanding behavior is important in terms of welfare assessments to be able to evaluate possible changes in behavior among different husbandry systems. The present study applied principal component analysis (PCA) to reveal relationships between behavioral indicators to identify the main components of sows' behavior promoting feasibility of welfare assessments by providing possibilities for variable reduction and aggregation. The indicators of the Welfare Quality®protocol's principle to assess behavior were repeatedly applied by two observers on 13 farms in Northern Germany. This included Qualitative Behavior Assessments (QBA) to evaluate animals' body language using 20 pre-defined adjectives, assessments of social and exploratory behavior, stereotypies, and human–animal relationship tests. Two separate PCA were performed with respect to the QBA: (1) adjectives were included as independent variables and (2) adjectives were pre-aggregated using the calculation rules of the Welfare Quality®protocol for fattening pigs since a calculation for sows does not yet exist. In both analyses, two components described sows' behavior. Most variance was explained by the solution with adjectives as independent variables (51.0%). Other behavioral elements not captured as indicators by the protocol may still be important for all-inclusive welfare assessments as the required variance of 70% was not achieved in the analyses. Component loadings were used to determine components' labels as (1) “satisfaction of exploratory behavior” and (2) “social resting”. Both components reflected characteristics of sows' natural behavior and can subsequently be used for variable reduction but also for development of component scores for aggregation. As defined for PCA, component 1 explained more variance than component 2. PCA is useful to determine the main components of sows' behavior, which can be used to enhance feasibility of welfare assessments.

Tactical analysis of individual and team behaviour in professional Australian Football

ABSTRACT Introduction This study sought to reduce the dimensionality of commonly reported spatiotemporal characteristics obtained from Australian Football games to facilitate their practical use and interpretability. Methods A retrospective longitudinal design was utilised with team and individual spatiotemporal variables, measured via global navigation satellite system devices, collected during official Australian Football League matched over three seasons. Two separate principal component analyses were conducted at the team and individual level to reduce correlated spatiotemporal characteristics into a smaller set of uncorrelated components. Results At the team level, eighteen variables were reduced to five components pertaining to dispersive coordination, lateral predictability and spacing, multidirectional synchrony, longitudinal predictability and longitudinal behaviour whilst maintaining 69% of variance in the original dataset. At the individual level, fifteen variables were reduced to four components pertaining to multidirectional and spacing synchrony, unpredictability, player movement and player positioning whilst maintaining 64% of variance. Conclusion This study is the first to provide a simplified, novel method for analysing spatiotemporal behaviour in an Australian Football context with both the team- and individual- derived metrics revealing useful information for coaches and practitioners. Components may provide insight into behaviours that emerge and persist throughout a game and allow coaches to distinguish between different playing/behavioural styles

Does time since concussion alter the factor structure of a multidomain assessment in adolescents?

ABSTRACT The utilization of principal component analysis (PCA) approaches to concussion is beneficial to inform the interpretation of clinical outcome data in adolescent patients. While researchers have identified factors using post-concussive symptom scales and cognitive testing, there has yet to be a PCA that incorporates vestibular or oculomotor outcomes, or that focuses exclusively on adolescents. Moreover, the role of time since injury has not been examined in relation to concussion factors in this at-risk population. PCA methods were applied to two independent samples of 237 adolescents who presented to an outpatient concussion clinic: 1) ≤7 days (n = 145), and 2) 8 days-1 month (n = 92). The two separate PCAs included nine clinical assessments comprised of: a) four symptoms factors (cognitive/fatigue/migraine, affective, somatic, sleep), b) memory and speeded cognitive performance, c) near point of convergence (NPC), d) oculomotor, and e) vestibular outcomes. A three-component model including 1) symptoms, 2) cognitive, and 3) vestibular/oculomotor factors that accounted for 69.2% of the variance was supported for the ≤7 days sample. All items except somatic symptoms loaded. A different three-component model was supported for the 8 days-1 month sample, including 1) vestibulo-ocular migraine, 2) visuo-cognitive, and 3) affective-sleep that accounted for 72.1% of the variance, with all items loading. The findings supported two different concussion factor models that highlight the influence of time since injury and importance of considering vestibular and oculomotor outcomes in adolescents. Clinicians should evaluate these different factors using a comprehensive, multi domain approach to better inform assessment and monitor recovery in adolescent patients following concussion. Abbreviations: Principal Components Analysis (PCA), Immediate Post-concussion Assessment and Cognitive Testing (ImPACT), Post-concussion Symptom Scale (PCSS), Vestibular/Ocular Motor Screening (VOMS)

Compounds from plantar foot sweat, nesting material, and urine show strain patterns associated with agonistic and affiliative behaviors in group housed male mice, Mus musculus.

Excessive home cage aggression often results in severe injury and subsequent premature euthanasia of male laboratory mice. Aggression can be reduced by transferring used nesting material during cage cleaning, which is thought to contain aggression appeasing odors from the plantar sweat glands. However, neither the composition of plantar sweat nor the deposits on used nesting material have been evaluated. The aims of this study were to (1) identify and quantify volatile compounds deposited in the nest site and (2) determine if nest and sweat compounds correlate with social behavior. Home cage aggression and affiliative behavior were evaluated in 3 strains: SJL, C57BL/6N, and A/J. Individual social rank was assessed via the tube test, because ranking may influence compound levels. Sweat and urine from the dominant and subordinate mouse in each cage, plus cage level nest samples were analyzed for volatile compound content using gas chromatography-mass spectrometry. Behavior data and odors from the nest, sweat, and urine were statistically analyzed with separate principal component analyses (PCA). Significant components, from each sample analysis, and strain were run in mixed models to test if odors were associated with behavior. Aggressive and affiliative behaviors were primarily impacted by strain. However, compound PCs were also impacted by strain, showing that strain accounts for any relationship between odors and behavior. C57BL/6N cages displayed the most allo-grooming behavior and had high scores on sweat PC1. SJL cages displayed the most aggression, with high scores on urine PC2 and low scores on nest PC1. These data show that certain compounds in nesting material, urine, and sweat display strain specific patterns which match strain specific behavior patterns. These results provide preliminary information about the connection between home cage compounds and behavior. Salient compounds will be candidates for future controlled studies to determine their direct effect on mouse social behavior.

How do rootstocks of citron watermelon (Citrullus lanatus var. citroides) affect the yield and quality of watermelon under deficit irrigation?

Deficit irrigation practices and utilization of rootstocks that are tolerant to water stress are critical strategies for the protection of water resources and sustainable irrigation management, especially in arid and semi-arid areas. Therefore, this study was carried out to investigate the yield and quality of watermelon grafted onto different rootstocks under deficit irrigation conditions during 2017 and 2018 in the Konya Plain of Turkey, where the semi-arid climate is prevalent. In this study, five different plant materials, such as citroides1 (A1), citroides2 (A2), gourd (A3), hybrid TZ148 (A4) rootstocks grafted with the Crimson Tide variety, and non-grafted Crimson Tide as control (K1), were used as the main-plots. Five different irrigation levels, calculated by taking into account the amounts of cumulative water (Ep) that evaporated at 7-day intervals from Class A Pan (I100 = 1.00Ep; I75 = 0.75Ep; I50 = 0.50Ep; I35 = 0.35Ep, and I0 = rain-fed), were used as the sub-plots.When the average of experimental years was considered, the highest rate of evapotranspiration (ET) was found in the plot A4I100 (615 mm). The highest fruit yield was obtained from the A4I100 (93.4 t/ha), and an increase in yield of up to 35 % was achieved in the A4I100, compared to non-grafted plants applied I100 irrigation level (K1I100). The analysis of data by both separate evaluation and principal component analysis (PCA) revealed that the yield values obtained from plants grafted onto A4, A1, and A2 rootstocks applied I75 irrigation level were higher than non-grafted plants applied I100 irrigation level. The water productivity (WP) and irrigation water productivity (IWP) ranged between 7.1–17.4 kg/m3 and 11.7–25.0 kg/m3, respectively, and a significant increase in the values of WP and IWP was achieved by grafting. This two-year study revealed that the performances of citron watermelon rootstocks were found close to the TZ148 rootstock in terms of fruit yield, certain yield components, WP, and IWP. Thus, it has also been demonstrated that the citron watermelons could be used commercially as watermelon rootstocks, and citron watermelon rootstocks could be used as watermelon rootstocks in breeding programs, in order to save water, especially in arid and semi-arid regions.

Development of Concise Physical Performance Test Batteries in Young Athletes.

This study aimed 1) to define the principal components of physical function assessed by 10 common lower extremity physical performance tests and 2) to derive a reduced-item set of physical performance tests that efficiently and accurately measures raw performance and limb symmetry on each underlying component in pediatric and adolescent athletes. This study included healthy, uninjured volunteers (n = 100) between the ages 6 and 18 yr (mean age = 11.7 ± 3.6 yr; 52 females). Subjects performed the stork balance, stork balance on BOSU® Balance Trainer, single leg squat (SLS), SLS on BOSU, clockwise and counterclockwise quadrant single leg hop (SLH), forward SLH, timed SLH, triple crossover SLH, and lower quarter Y-Balance Test™. Item reduction was performed using principal components analysis (PCA). We developed separate principal components analysis for average raw performance and side-to-side limb symmetry, with secondary analyses to evaluate consistency of results by age and sex. We identified two components for average raw performance (accounting for 65.2% of the variance in total test battery) with a reduced-item set composed of five tests, and four components for limb symmetry (accounting for 62.9% of the variance in total test battery) with a reduced-item set of seven tests. The most parsimonious test suitable for screening both average raw performance and limb symmetry would consist of five tests (stork balance on BOSU, SLS on BOSU, forward SLH, timed SLH, and lower quarter Y-Balance Test™). Age- and sex-specific test batteries may be warranted. Comprehensive screening for lower extremity average raw performance and limb symmetry is possible with short physical performance test batteries.

The relative contribution of training intensity and duration to daily measures of training load in professional rugby league and union

ABSTRACT This study examined the relative contribution of exercise duration and intensity to team-sport athlete’s training load. Male, professional rugby league (n = 10) and union (n = 22) players were monitored over 6- and 52-week training periods, respectively. Whole-session (load) and per-minute (intensity) metrics were monitored (league: session rating of perceived exertion training load [sRPE-TL], individualised training impulse, total distance, BodyLoad™; union: sRPE-TL, total distance, high-speed running distance, PlayerLoad™). Separate principal component analyses were conducted on the load and intensity measures to consolidate raw data into principal components (PC, k = 4). The first load PC captured 70% and 74% of the total variance in the rugby league and rugby union datasets, respectively. Multiple linear regression subsequently revealed that session duration explained 73% and 57% of the variance in first load PC, respectively, while the four intensity PCs explained an additional 24% and 34%, respectively. Across two professional rugby training programmes, the majority of the variability in training load measures was explained by session duration (~60–70%), while a smaller proportion was explained by session intensity (~30%). When modelling the training load, training intensity and duration should be disaggregated to better account for their between-session variability.

Preferred EEG brain states at stimulus onset in normal ageing: Explorations in a fixed interstimulus interval Go/NoGo task

Some 40 years ago, Erol Başar began an interesting line of brain dynamics research on the phase of oscillatory EEG activity. Stimuli presented at a fixed interstimulus interval (ISI) were reported to produce a “preferred phase angle” at stimulus onset in the ongoing EEG oscillations, so that cortical negativity occurred more often than expected. Our previous work has confirmed this phenomenon in young adults, and linked it to enhancements in stimulus-elicited ERP components and behaviour. The present study sought evidence for this phenomenon in older adults. Twenty healthy independent-living participants (5 males) aged 59.8 to 74.8 years (M = 68.2) completed a fixed ISI equiprobable auditory oddball task. EEG phases in four traditional bands were computed separately for each artefact-free Go and NoGo trial. These were used to group accepted trials according to the phase quartile at stimulus onset in each band, forming 16 mean ERPs for each participant at each phase quartile/band combination, separately for Go and NoGo. The 32 mean ERPs were decomposed by separate Principal Component Analyses, and the N1 and P3 components were examined as a function of EEG phase at stimulus onset in each band. Differential preferential occurrence of phase states was found in all bands, generally confirming prior results in young adults despite important age differences in both EEG spectra and ERP morphology. Substantial effects on N1 and P3 components, as well as prestimulus CNVs, are discussed. The stability of this phenomenon across age indicates its important role in perception and cognition.

Comparison of the shape and temporal evolution of even and odd solar cycles

Aims. We study the difference in the shape of solar cycles for even and odd cycles using the Wolf sunspot numbers and group sunspot numbers of solar cycles 1−23. We furthermore analyse the data of sunspot area sizes for even and odd cycles SC12−SC23 and sunspot group data for even and odd cycles SC8−SC23 to compare the temporal evolution of even and odd cycles. Methods. We applied the principal component analysis (PCA) to sunspot cycle data and studied the first two components, which describe the average cycle shape and cycle asymmetry. We used a distribution analysis to analyse the temporal evolution of the even and odd cycles and determined the skewness and kurtosis for even and odd cycles of sunspot group data. Results. The PCA confirms the existence of the Gnevyshev gap (GG) for solar cycles at about 40% from the start of the cycle. The temporal evolution of sunspot area data for even cycles shows that the GG exists at least at the 95% confidence level for all sizes of sunspots. On the other hand, the GG is shorter and statistically insignificant for the odd cycles of aerial sunspot data. Furthermore, the analysis of sunspot area sizes for even and odd cycles of SC12−SC23 shows that the greatest difference is at 4.2−4.6 years, where even cycles have a far smaller total area than odd cycles. The average area of the individual sunspots of even cycles is also smaller in this interval. The statistical analysis of the temporal evolution shows that northern sunspot groups maximise earlier than southern groups for even cycles, but are concurrent for odd cycles. Furthermore, the temporal distributions of odd cycles are slightly more leptokurtic than distributions of even cycles. The skewnesses are 0.37 and 0.49 and the kurtoses 2.79 and 2.94 for even and odd cycles, respectively. The correlation coefficient between skewness and kurtosis for even cycles is 0.69, and for odd cycles, it is 0.90. Conclusions. The separate PCAs for even and odd sunspot cycles show that odd cycles are more inhomogeneous than even cycles, especially in GSN data. Even cycles, however, have two anomalous cycles: SC4 and SC6. The variation in the shape of the early sunspot cycles suggests that there are too few and/or inaccurate measurements before SC8. According to the analysis of the sunspot area size data, the GG is more distinct in even than odd cycles. This may be partly due to sunspot groups maximizing earlier in the northern than in the southern hemisphere for even cycles. We also present another Waldmeier-type rule, that is, we find a correlation between skewness and kurtosis of the sunspot group cycles.