The link between creativity and serious mental illness (SMI) is widely discussed. Jackson Pollock is one example of a giant in the field of art who was both highly creative and experiencing an SMI. Pollock created a new genre of art known as abstract expressionism (“action painting”) defined as showing the frenetic actions of painting. The question arises whether his SMI played any role in the way he created his drip paintings, especially when he was overactive and manic. Furthermore, did visual hallucinations or enhanced visual perception associated with mania or psychosis facilitate Pollock in embedding and camouflaging images under layers of thrown paint? Seeing images in Pollocks drip paintings has been a controversy ever since these paintings were created. Some experts attribute this to pareidolia—perceiving specific images out of random or ambiguous visual patterns—a phenomenon known to be enhanced by fractal fuzzy edges such as seen in Rorschach ink blots as well as in Pollock drip paintings. So, are Pollock’s drip paintings merely giant Rorschach images, or did Pollock insert polloglyphs—images that are encrypted that tell a story about Pollock’s inner being—into his paintings and then disguise them with drippings? Here, we explore answers to these questions and discuss images that Pollock included in his earliest sketches and used repeatedly in his abstract paintings and later in his drip paintings to argue that these images are not accidental.

Experts have been fascinated with Jackson Pollock (born 1912, died 1956) and his famous “drip paintings” ever since he began producing them in the 1940s. It is well documented that Pollock began to have mood swings as a child, with symptoms of social anxiety relieved by alcoholic binges from his teen years until his death. He received psychoanalytic psychotherapy, psychiatric hospitalization and some psychopharmacologic treatments from age 23 until his death at age 44. Most of his treatment was by psychiatrists trained in Jungian or Freudian psychoanalysis. Pollock was first hospitalized at New York Westchester Hospital in 1938 with his first “breakdown,” likely a manic/hypomanic or psychotic episode combined with alcohol intoxication. Without modern antipsychotic medications or lithium at the time, he was allowed to rest and improve and at that time was tested extensively with Rorschach ink blots, a new technology at the time, and which undoubtedly influenced the Polloglyphs embedded in his later works.

Pollock was afflicted with hallucinatory spells, particularly visual. With his eyes wide open, he would suddenly begin to see whirling images, and Pollock himself realized that for his drip paintings he had seen those images before he painted them. Bipolar experts have written about altered sensory phenomena experienced in bipolar disorder and even theorized a suprasensory world for some patients with enhanced visual perceptual abilities especially when manic or hypomanic. Although Jackson according to his biographers was variably diagnosed as “alcoholic psychosis,” “schizoid” or “a schizophrenia like disorder characterized by alternating periods of violent agitation and paralysis or withdrawal,” in today’s world he would more likely be diagnosed as bipolar. This is supported by other comments from his biography that “more and more the schizophrenic like state described by his psychiatrist was playing itself out in a binary drama of depression and elation.” His older brother Charles was hospitalized in 1942 for a “nervous breakdown” possibly a bipolar episode, suggesting a positive family history of bipolar disorder in the Pollock family.

About 1947 he began his drip paintings and his longest period of uninterrupted productivity until about 1950. During this period, he created his masterpieces, especially during the years between 1948 and 1950, a time when he drank little and was treated with the early mood stabilizers Dilantin and phenobarbital. He stopped his meds and eventually crashed his car after drinking and died at age 44. Experts have long pondered the relationship between creativity/genius and bipolar disorder. For Pollock, the Polloglyphs in his drip paintings seem to be linked to his creativity and genius shaped by bipolar disorder thus expressing his inner emotions as camouflaged images on canvas.

There recently has been growing interest in the study of psychological and neurological processes at an individual level. One goal in such endeavors is to construct person-specific dynamic assessments using time series techniques such as Vector Autoregressive (VAR) models. However, two problems exist with current VAR specifications: (1) VAR models are restricted in that contemporaneous relations are typically modeled either as undirected relations among residuals or directed relations among observed variables, but not both; (2) current estimation frameworks are limited by the reliance on stepwise model building procedures. This study adopts a new modeling approach. We first extended the current unified SEM (uSEM) framework, a widely used structural VAR model, to a hybrid representation (i.e., “huSEM”) to include both undirected and directed contemporaneous effects, and then replaced the stepwise modeling with a LASSO-type regularization for a global search of the optimal sparse model. Our simulation study showed that regularized huSEM performed uniformly the best over alternative VAR representations and/or modeling approaches, with respect to accurately recovering the presence and directionality of hybrid relations and reliably removing false relations when the data are generated to have two types of contemporaneous relations. The present study to our knowledge is the first application of the recently developed regularized SEM technique to the estimation of huSEM, which points to a promising future for statistical learning in psychometric models.

Significant heterogeneity in network structures reflecting individuals’ dynamic processes can exist within subgroups of people (e.g., diagnostic category, gender). This makes it difficult to make inferences regarding these predefined subgroups. For this reason, researchers sometimes wish to identify subsets of individuals who have similarities in their dynamic processes regardless of any predefined category. This requires unsupervised classification of individuals based on similarities in their dynamic processes, or equivalently, in this case, similarities in their network structures of edges. The present paper tests a recently developed algorithm, S-GIMME, that takes into account heterogeneity across individuals with the aim of providing subgroup membership and precise information about the specific network structures that differentiate subgroups. The algorithm has previously provided robust and accurate classification when evaluated with large-scale simulation studies but has not yet been validated on empirical data. Here, we investigate S-GIMME’s ability to differentiate, in a purely data-driven manner, between brain states explicitly induced through different tasks in a new fMRI dataset. The results provide new evidence that the algorithm was able to resolve, in an unsupervised data-driven manner, the differences between different active brain states in empirical fMRI data to segregate individuals and arrive at subgroup-specific network structures of edges. The ability to arrive at subgroups that correspond to empirically designed fMRI task conditions, with no biasing or priors, suggests this data-driven approach can be a powerful addition to existing methods for unsupervised classification of individuals based on their dynamic processes.

This article develops a class of models called sender/receiver finite mixture exponential random graph models (SRFM-ERGMs). This class of models extends the existing exponential random graph modeling framework to allow analysts to model unobserved heterogeneity in the effects of nodal covariates and network features without a block structure. An empirical example regarding substance use among adolescents is presented. Simulations across a variety of conditions are used to evaluate the performance of this technique. We conclude that unobserved heterogeneity in effects of nodal covariates can be a major cause of misfit in network models, and the SRFM-ERGM approach can alleviate this misfit. Implications for the analysis of social networks in psychological science are discussed.

Research questions in the human sciences often seek to answer if and when a process changes across time. In functional MRI studies, for instance, researchers may seek to assess the onset of a shift in brain state. For daily diary studies, the researcher may seek to identify when a person’s psychological process shifts following treatment. The timing and presence of such a change may be meaningful in terms of understanding state changes. Currently, dynamic processes are typically quantified as static networks where edges indicate temporal relations among nodes, which may be variables reflecting emotions, behaviors, or brain activity. Here we describe three methods for detecting changes in such correlation networks from a data-driven perspective. Networks here are quantified using the lag-0 pair-wise correlation (or covariance) estimates as the representation of the dynamic relations among variables. We present three methods for change point detection: dynamic connectivity regression, max-type method, and a PCA-based method. The change point detection methods each include different ways to test if two given correlation network patterns from different segments in time are significantly different. These tests can also be used outside of the change point detection approaches to test any two given blocks of data. We compare the three methods for change point detection as well as the complementary significance testing approaches on simulated and empirical functional connectivity fMRI data examples.

Spearman (Am J Psychol 15(1):201–293, 1904. https://doi.org/10.2307/1412107) marks the birth of factor analysis. Many articles and books have extended his landmark paper in permitting multiple factors and determining the number of factors, developing ideas about simple structure and factor rotation, and distinguishing between confirmatory and exploratory factor analysis (CFA and EFA). We propose a new model implied instrumental variable (MIIV) approach to EFA that allows intercepts for the measurement equations, correlated common factors, correlated errors, standard errors of factor loadings and measurement intercepts, overidentification tests of equations, and a procedure for determining the number of factors. We also permit simpler structures by removing nonsignificant loadings. Simulations of factor analysis models with and without cross-loadings demonstrate the impressive performance of the MIIV-EFA procedure in recovering the correct number of factors and in recovering the primary and secondary loadings. For example, in nearly all replications MIIV-EFA finds the correct number of factors when N is 100 or more. Even the primary and secondary loadings of the most complex models were recovered when the sample sizes were at least 500. We discuss limitations and future research areas. Two appendices describe alternative MIIV-EFA algorithms and the sensitivity of the algorithm to cross-loadings.

The effect of acid type and concentration on the reaction rate and products of dissolution of hectorite in inorganic acids was investigated. The dissolution of hectorite in hydrochloric (HCl), nitric (HNO3) and sulphuric (H2SO4) acids was characterized using quantitative chemical analysis, infrared (IR) and multinuclear MAS NMR spectroscopies. The rate of dissolution increased with acid concentration and decreased in the order HCl ≥ HNO3 = H2SO4 at the same molar concentration. No differences were found in the reaction products of hectorite treated with the three acids. The rate of Li dissolution was slightly greater than that of Mg at lesser acid concentrations (0.25 M), indicating that protons preferentially attack Li octahedra. The gradual changes in the Si-O IR bands reflects the extent of hectorite dissolution. The analysis of 29Si MAS NMR spectra relative peak intensities with dissolution time and acid concentration provided direct dissolution rates for tetrahedral (Q3) Si. After acid dissolution, most Si was bound in a three dimensional framework site (Q4), but a substantial part also occurred in the Si(OSi)3OH (Q31OH) and Si(OSi)2(OH)2 (Q220H) environments. These three sites probably occur in a hydrous amorphous silica phase. Both AlJV and AlVt rapidly disappeared from 27Al MAS NMR spectra of the dissolution products with acid treatment. The changes in IR and MAS NMR spectra of hectorite due to acid dissolution are similar to those of montmorillonite.

The crystal structure of deracoxib has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Deracoxib crystallizes in space group Pbca (#61) with a = 9.68338(11), b = 9.50690(5), c = 38.2934(4) Å, V = 3525.25(3) Å3, and Z = 8. The molecules stack in layers parallel to the ab-plane. N–H⋯O hydrogen bonds link the molecules along the b-axis, in chains with the graph set C1,1(4), as well as more-complex patterns. N–H⋯N hydrogen bonds link the layers. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

The crystal structure of imepitoin has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Imepitoin crystallizes in space group Pbca (#61) with a = 12.35541(2), b = 28.43308(8), c = 7.340917(7) Å, V = 2578.882(7) Å3, and Z = 8. The roughly planar molecules stack along the c-axis. There are no traditional hydrogen bonds in the structure, but several intramolecular and intermolecular C–H⋯O, C–H⋯N, and C–H⋯Cl hydrogen bonds contribute to the crystal energy. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

The crystal structure of nequinate has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional techniques. Nequinate crystallizes in the space group P21/c (#14) with a = 18.35662(20), b = 11.68784(6), c = 9.06122(4) Å, β = 99.3314(5)°, V = 1918.352(13) Å3, and Z = 4. The crystal structure is dominated by the stacking of the approximately planar molecules. N–H⋯O hydrogen bonds link adjacent molecules into chains parallel to the b-axis. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

The crystal structure of altrenogest has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Altrenogest crystallizes in space group P212121 (#19) with a = 7.286 916(16), b = 10.580 333(19), c = 22.266 08(7) Å, V = 1716.671(6) Å3, and Z = 4 at 295 K. Thermal expansion between 113 and 295 K is anisotropic. An O–H⋯O hydrogen bond links the molecules into chains along the c-axis. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

The crystal structure of aminopentamide hydrogen sulfate has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Aminopentamide hydrogen sulfate crystallizes in space group P21/c (#14) with a = 17.62255(14), b = 6.35534(4), c = 17.82499(10) Å, β = 96.4005(6)°, V = 1983.906(14) Å3, and Z = 4. The structure consists of layers parallel to the bc-plane with hydrogen sulfate anions at the core and aminopentamide cations on the outside. There is a strong charge-assisted O49–H53⋯O52 hydrogen bond between the hydrogen sulfate anions. This hydrogen bond links the anions in a chain parallel to the b-axis. The cation forms a discrete N–H⋯O hydrogen bond to the anion. The amide group also forms two weaker discrete hydrogen bonds to the anion. The three N–H⋯O hydrogen bonds link the cations and anions into columns parallel to the b-axis. This commercial material from USP contained an unidentified impurity, the powder pattern of which could be indexed on a monoclinic unit cell. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

The crystal structure of fulvestrant hydrate (ethyl acetate) has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. This solvate of fulvestrant crystallizes in space group R3 (#146) with a = 23.39188(16), c = 16.50885(13) Å, V = 7823.08(7) Å3, and Z = 9. The crystal structure is composed of triangular hydrogen-bonded chains of molecules around one of the threefold axes. The fluorinated ends of the molecules cluster around another threefold axis. Voids around a threefold axis occupy 8.1% of the unit cell volume, and are partially occupied by the water and ethyl acetate molecules. Both hydroxyl groups act as donors in O–H⋯O hydrogen bonds. These H-bonds form a large ring. The powder pattern has been submitted to ICDD® for inclusion in the Powder Diffraction File™ (PDF®).

The crystal structure of merimepodib has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Merimepodib crystallizes in space group P212121 (#19) with a = 4.60827(3), b = 12.30400(14), c = 37.9583(4) Å, V = 2152.241(20) Å3, and Z = 4. The crystal structure is dominated by two chains of N–H⋯O hydrogen bonds along the a-axis. The solid-state conformation has a similar general shape to the minimum-energy conformation, but different orientations of several of the rings. The differences indicate that intermolecular interactions are important in determining the solid-state conformation. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

The crystal structure of baricitinib has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional techniques. Baricitinib crystallizes in space group I2/a (#15) with a = 11.81128(11), b = 7.06724(6), c = 42.5293(3) Å, β = 91.9280(4)°, V = 3548.05(5) Å3, and Z = 8. The crystal structure is characterized by hydrogen-bonded double layers parallel to the ab-planes. The dimers form a graph set R2,2(8). The sulfone ends of the molecules reside in the interlayer regions. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

Five international consensus statements on concussion in sports have been published. This commentary argues that there is a strong need for a new approach to them that foregrounds public health expertise and patient-centered guidance. Doing so will help players, parents and practitioners keep perspective about these potentially life-altering injuries especially when they recur.