Computational analysis of 140 years of US political speeches reveals more positive but increasingly polarized framing of immigration.

We classify and analyze 200,000 US congressional speeches and 5,000 presidential communications related to immigration from 1880 to the present. Despite the salience of antiimmigration rhetoric today, we find that political speech about immigration is now much more positive on average than in the past, with the shift largely taking place between World War II and the passage of the Immigration and Nationality Act in 1965. However, since the late 1970s, political parties have become increasingly polarized in their expressed attitudes toward immigration, such that Republican speeches today are as negative as the average congressional speech was in the 1920s, an era of strict immigration quotas. Using an approach based on contextual embeddings of text, we find that modern Republicans are significantly more likely to use language that is suggestive of metaphors long associated with immigration, such as "animals" and "cargo," and make greater use of frames like "crime" and "legality." The tone of speeches also differs strongly based on which nationalities are mentioned, with a striking similarity between how Mexican immigrants are framed today and how Chinese immigrants were framed during the era of Chinese exclusion in the late 19th century. Overall, despite more favorable attitudes toward immigrants and the formal elimination of race-based restrictions, nationality is still a major factor in how immigrants are spoken of in Congress.

Cerebral maturation in the early preterm period-A magnetization transfer and diffusion tensor imaging study using voxel-based analysis.

The magnetization transfer ratio (MTR) and diffusion tensor imaging (DTI) correlates of early brain development were examined in cohort of 18 very preterm neonates (27-31 gestational weeks) presenting with normal radiological findings scanned within 2weeks after birth (28-32 gestational weeks). A combination of non-linear image registration, tissue segmentation, and voxel-wise regression was used to map the age dependent changes in MTR and DTI-derived parameters in 3D across the brain based on the cross-sectional in vivo preterm data. The regression coefficient maps obtained differed between brain regions and between the different quantitative MRI indices. Significant linear increases as well as decreases in MTR and DTI-derived parameters were observed throughout the preterm brain. In particular, the lamination pattern in the cerebral wall was evident on parametric and regression coefficient maps. The frontal white matter area (subplate and intermediate zone) demonstrated a linear decrease in MTR. While the intermediate zone showed an unexpected decrease in fractional anisotropy (FA) with age, with this decrease (and the increase in mean diffusivity (MD)) driven primarily by an increase in radial diffusivity (RD) values, the subplate showed no change in FA (and an increase in MD). The latter was the result of a concomitant similar increase in axial diffusivity (AD) and RD values. Interpreting the in vivo results in terms of available histological data, we present a biophysical model that describes the relation between various microstructural changes measured by complementary quantitative methods available on clinical scanners and a range of maturational processes in brain tissue.

Deep grey matter growth predicts neurodevelopmental outcomes in very preterm children.

We evaluated whether the volume and growth rate of critical brain structures measured by MRI in the first weeks of life following very preterm (<32/40 weeks) birth could predict subsequent neurodevelopmental outcomes at 4 years of age. A significant proportion of children born very prematurely have cognitive deficits, but these problems are often only detected at early school age. Structural T2-weighted magnetic resonance images were acquired in 96 very preterm neonates scanned within 2 weeks of birth and 70 of these at term-equivalent age. An automated 3D image analysis procedure was used to measure the volume of selected brain structures across all scans and time points. At 4 years of age, 53 children returned for neuropsychological assessments evaluating IQ, language and visual motor integration. Associations with maternal education and perinatal measures were also explored. Multiple regression analyses revealed that growth of the caudate and globus pallidus between preterm birth and term-equivalent age predicted visual motor integration scores after controlling for sex and gestational age. Further associations were found between caudate and putamen growth with IQ and language scores. Analyses at either preterm or term-equivalent age only found associations between normalized deep grey matter growth and visual motor integration scores at term-equivalent age. Maternal education levels were associated with measures of IQ and language, but not visual motor integration. Thalamic growth was additionally linked with perinatal measures and presence of white matter lesions. These results highlight deep grey matter growth rates as promising biomarkers of long-term outcomes following very preterm birth, and contribute to our understanding of the brain-behaviour relations in these children.

An archival perspective on pretraining data.

Alongside an explosion in research and development related to large language models, there has been a concomitant rise in the creation of pretraining datasets-massive collections of text, typically scraped from the web. Drawing on the field of archival studies, we analyze pretraining datasets as informal archives-heterogeneous collections of diverse material that mediate access to knowledge. We use this framework to identify impacts of pretraining data creation and use beyond directly shaping model behavior and reveal how choices about what is included in pretraining data necessarily involve subjective decisions about values. In doing so, the archival perspective helps us identify opportunities for researchers who study the social impacts of technology to contribute to confronting the challenges and trade-offs that arise in creating pretraining datasets at this scale.

Quantitative MRI in the very preterm brain: assessing tissue organization and myelination using magnetization transfer, diffusion tensor and T1 imaging.

Magnetization transfer ratio (MTR), diffusion tensor imaging (DTI) parameters and T(1) relaxometry values were used to create parametric maps characterizing the tissue microstructure of the neonatal brain in infants born very premature (24-32 gestational weeks) and scanned at preterm and term equivalent age. Group-wise image registration was used to determine anatomical correspondence between individual scans and the pooled parametric data at the preterm and term ages. These parametric maps showed distinct contrasts whose interrelations varied across brain regions and between the preterm and term period. Discrete patterns of regional variation were observed for the different quantitative parameters, providing evidence that MRI is sensitive to multiple independent aspects of brain maturation. MTR values showed a marked change in the pattern of regional variation at term equivalent age compared to the preterm period such that the ordinal ranking of regions by signal contrast changed. This was unlike all other parameters where the regional ranking was preserved at the two time points. Interpreting the data in terms of myelination and structural organization, we report on the concordance with available histological data and demonstrate the value of quantitative MRI for tracking brain maturation over the neonatal period.

Brain metabolite concentrations are associated with illness severity scores and white matter abnormalities in very preterm infants.

BACKGROUND: Magnetic resonance spectroscopy allows for the noninvasive study of brain metabolism and therefore may provide useful information about brain injuries. We examined the associations of brain metabolite ratios in very preterm infants with white matter lesions and overall health status at birth. METHODS: Spectroscopy data were obtained from 99 very preterm infants (born ≤32 wk gestation) imaged shortly after birth and from 67 of these infants at term-equivalent age. These data were processed using LCModel. Multiple regression was used to examine the association of metabolite ratios with focal noncystic white matter lesions visible on conventional magnetic resonance imaging (MRI) and with at-birth illness severity scores. RESULTS: Within 2 wk of birth, the ratio of N-acetylaspartate + N-acetylaspartylglutamate to creatine + phosphocreatine was significantly lower in those infants showing white matter abnormalities on conventional MRI. Increased lactate to creatine + phosphocreatine and lactate to glycerophosphocholine + phosphocholine ratios were significantly associated with increasing severity of Clinical Risk Index for Babies II and Apgar scores taken at 1 and 5 min after birth. CONCLUSION: Both overall health status at birth and white matter injury in preterm neonates are reflected in metabolite ratios measured shortly after birth. Long-term follow-up will provide additional insight into the prognostic value of these measures.

Alterations in frontostriatal pathways in children born very preterm.

AIM: Children born very preterm (<32wks' gestation) are at risk of white matter injury, particularly in frontostriatal pathways that mediate executive functioning. However, it is unclear whether very preterm children without evidence of neonatal brain injury manifest long-term white matter microstructural differences once they reach school age and if this is related to cognitive impairments. METHOD: Twenty school-aged children born very preterm (11 males, nine females; mean age 8y 6mo, standard error [SE] 1.68mo, range 7y 7mo-9y 6mo; gestational age range 24-30wks, mean gestational age 26.9wks, SE 0.4wk; birthweight 988 g, SE 46 g, range 570-1424 g) without evidence of neonatal brain injury, and 20 sex- and age-matched term-born children (mean age 8y 4.8mo, SE 1.92mo; range 7y 2mo-9y-10.8mo) underwent neurodevelopmental assessment and diffusion tensor imaging. RESULTS: Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated within all white matter pathways and within frontostriatal projections. Children born preterm had decreased fractional anisotropy in the territories of the left external capsule, superior longitudinal fasciculus, uncinate fasciculus, and inferior fronto-occipital fasciculus. Measures of intelligence were negatively correlated with frontostriatal fractional anisotropy only in males born preterm. INTERPRETATION: Results indicate that very preterm-born children exhibit white matter disturbances that persist into middle childhood, with potential sex differences in the association between these white matter alterations and cognitive function.

On Consequentialism and Fairness.

Recent work on fairness in machine learning has primarily emphasized how to define, quantify, and encourage "fair" outcomes. Less attention has been paid, however, to the ethical foundations which underlie such efforts. Among the ethical perspectives that should be taken into consideration is consequentialism, the position that, roughly speaking, outcomes are all that matter. Although consequentialism is not free from difficulties, and although it does not necessarily provide a tractable way of choosing actions (because of the combined problems of uncertainty, subjectivity, and aggregation), it nevertheless provides a powerful foundation from which to critique the existing literature on machine learning fairness. Moreover, it brings to the fore some of the tradeoffs involved, including the problem of who counts, the pros and cons of using a policy, and the relative value of the distant future. In this paper we provide a consequentialist critique of common definitions of fairness within machine learning, as well as a machine learning perspective on consequentialism. We conclude with a broader discussion of the issues of learning and randomization, which have important implications for the ethics of automated decision making systems.

Self-injurious behaviours are associated with alterations in the somatosensory system in children with autism spectrum disorder.

Children with autism spectrum disorder (ASD) frequently engage in self-injurious behaviours, often in the absence of reporting pain. Previous research suggests that altered pain sensitivity and repeated exposure to noxious stimuli are associated with morphological changes in somatosensory and limbic cortices. Further evidence from postmortem studies with self-injurious adults has indicated alterations in the structure and organization of the temporal lobes; however, the effect of self-injurious behaviour on cortical development in children with ASD has not yet been determined. Thirty children and adolescents (mean age = 10.6 ± 2.5 years; range 7-15 years; 29 males) with a clinical diagnosis of ASD and 30 typically developing children (N = 30, mean age = 10.7 ± 2.5 years; range 7-15 years, 26 males) underwent T1-weighted magnetic resonance and diffusion tensor imaging. No between-group differences were seen in cerebral volume, surface area or cortical thickness. Within the ASD group, self-injury scores negatively correlated with thickness in the right superior parietal lobule t = 6.3, p < 0.0001, bilateral primary somatosensory cortices (SI) (right: t = 4.4, p = 0.02; left: t = 4.48, p = 0.004) and the volume of the left ventroposterior (VP) nucleus of the thalamus (r = -0.52, p = 0.008). Based on these findings, we performed an atlas-based region-of-interest diffusion tensor imaging analysis between SI and the VP nucleus and found that children who engaged in self-injury had significantly lower fractional anisotropy (r = -0.4, p = 0.04) and higher mean diffusivity (r = 0.5, p = 0.03) values in the territory of the left posterior limb of the internal capsule. Additionally, greater incidence of self-injury was associated with increased radial diffusivity values in bilateral posterior limbs of the internal capsule (left: r = 0.5, p = 0.02; right: r = 0.5, p = 0.009) and corona radiata (left: r = 0.6, p = 0.005; right: r = 0.5, p = 0.009). Results indicate that self-injury is related to alterations in somatosensory cortical and subcortical regions and their supporting white-matter pathways. Findings could reflect use-dependent plasticity in the somatosensory system or disrupted brain development that could serve as a risk marker for self-injury.

Metabolic mapping of deep brain structures and associations with symptomatology in autism spectrum disorders.

Structural neuroimaging studies in autism report atypical volume in deep brain structures which are related to symptomatology. Little is known about metabolic changes in these regions, and how they vary with age and sex, and/or relate to clinical behaviors. Using magnetic resonance spectroscopy we measured N-acetylaspartate, choline, creatine, myoinositol and glutamate in the caudate, putamen, and thalamus of 20 children with autism and 16 typically developing controls (7-18 years). Relative to controls, individuals with autism had elevated glutamate/creatine in the putamen. In addition, both groups showed age-related increases in glutamate in this region. Boys, relative to girls had increased choline/creatine in the thalamus. Lastly, there were correlations between glutamate, choline, and myoinositol in all three regions, and behavioral scores in the ASD group. These findings suggest changes in deep gray matter neurochemistry, which are sensitive to diagnosis, age and sex, and are associated with behavioral differences.