Infant cortex responds to other humans from shortly after birth

A significant feature of the adult human brain is its ability to selectively process information about conspecifics. Much debate has centred on whether this specialization is primarily a result of phylogenetic adaptation, or whether the brain acquires expertise in processing social stimuli as a result of its being born into an intensely social environment. Here we study the haemodynamic response in cortical areas of newborns (1–5 days old) while they passively viewed dynamic human or mechanical action videos. We observed activation selective to a dynamic face stimulus over bilateral posterior temporal cortex, but no activation in response to a moving human arm. This selective activation to the social stimulus correlated with age in hours over the first few days post partum. Thus, even very limited experience of face-to-face interaction with other humans may be sufficient to elicit social stimulus activation of relevant cortical regions

Investigating hyper-vigilance for social threat of lonely children

The hypothesis that lonely children show hypervigilance for social threat was examined in a series of three studies that employed different methods including advanced eye-tracking technology. Hypervigilance for social threat was operationalized as hostility to ambiguously motivated social exclusion in a variation of the hostile attribution paradigm (Study 1), scores on the Children’s Rejection-Sensitivity Questionnaire (Study 2), and visual attention to socially rejecting stimuli (Study 3). The participants were 185 children (11 years-7 months to 12 years-6 months), 248 children (9 years-4 months to 11 years-8 months) and 140 children (8 years-10 months to 12 years-10 months) in the three studies, respectively. Regression analyses showed that, with depressive symptoms covaried, there were quadratic relations between loneliness and these different measures of hypervigilance to social threat. As hypothesized, only children in the upper range of loneliness demonstrated elevated hostility to ambiguously motivated social exclusion, higher scores on the rejection sensitivity questionnaire, and disengagement difficulties when viewing socially rejecting stimuli. We found that very lonely children are hypersensitive to social threat

Time spent with cats is never wasted: Lessons learned from feline acromegalic cardiomyopathy, a naturally occurring animal model of the human disease

<div><p>Background</p><p>In humans, acromegaly due to a pituitary somatotrophic adenoma is a recognized cause of increased left ventricular (LV) mass. Acromegalic cardiomyopathy is incompletely understood, and represents a major cause of morbidity and mortality. We describe the clinical, echocardiographic and histopathologic features of naturally occurring feline acromegalic cardiomyopathy, an emerging disease among domestic cats.</p><p>Methods</p><p>Cats with confirmed hypersomatotropism (IGF-1>1000ng/ml and pituitary mass; n = 67) were prospectively recruited, as were two control groups: diabetics (IGF-1<800ng/ml; n = 24) and healthy cats without known endocrinopathy or cardiovascular disease (n = 16). Echocardiography was performed in all cases, including after hypersomatotropism treatment where applicable. Additionally, tissue samples from deceased cats with hypersomatotropism, hypertrophic cardiomyopathy and age-matched controls (n = 21 each) were collected and systematically histopathologically reviewed and compared.</p><p>Results</p><p>By echocardiography, cats with hypersomatotropism had a greater maximum LV wall thickness (6.5mm, 4.1–10.1mm) than diabetic (5.9mm, 4.2–9.1mm; Mann Whitney, p<0.001) or control cats (5.2mm, 4.1–6.5mm; Mann Whitney, p<0.001). Left atrial diameter was also greater in cats with hypersomatotropism (16.6mm, 13.0–29.5mm) than in diabetic (15.4mm, 11.2–20.3mm; Mann Whitney, p<0.001) and control cats (14.0mm, 12.6–17.4mm; Mann Whitney, p<0.001). After hypophysectomy and normalization of IGF-1 concentration (n = 20), echocardiographic changes proved mostly reversible. As in humans, histopathology of the feline acromegalic heart was dominated by myocyte hypertrophy with interstitial fibrosis and minimal myofiber disarray.</p><p>Conclusions</p><p>These results demonstrate cats could be considered a naturally occurring model of acromegalic cardiomyopathy, and as such help elucidate mechanisms driving cardiovascular remodeling in this disease.</p></div

Description of the Immatures of the Ant, Myrmelachista catharinae

The Neotropical ant genus Myrmelachista Roger comprises 69 described species and subspecies, and still is a poorly studied group. Larvae play a paramount role in colony nutrition in social hymenopterans and bear considerable value in the reconstruction of group phylogenies, however, they are generally neglected. Larvae of different instars of Myrmelachista catharinae Mayr (Hymenoptera: Formicidae) are herein described in detail by light and scanning electron microscopy. The number of larval instars was estimated as three based on the frequency distribution of maximum head capsule widths. The described larvae confirmed some traits typical of the genus: general shape of body and mandibles, general aspect and distribution of body hairs, and the number of sensilla on the palps and galea. Differently from other Myrmelachista larvae previously described, M. catharinae presented two distinct kinds of second instars, some additional types of body hairs, different number of antennal sensilla, and a distinct labrum shape. M. catharinae presented ten pairs of spiracles, which is the first record for this genus

Decision Models and Technology Can Help Psychiatry Develop Biomarkers

Why is psychiatry unable to define clinically useful biomarkers? We explore this question from the vantage of data and decision science and consider biomarkers as a form of phenotypic data that resolves a well-defined clinical decision. We introduce a framework that systematizes different forms of phenotypic data and further introduce the concept of decision model to describe the strategies a clinician uses to seek out, combine, and act on clinical data. Though many medical specialties rely on quantitative clinical data and operationalized decision models, we observe that, in psychiatry, clinical data are gathered and used in idiosyncratic decision models that exist solely in the clinician's mind and therefore are outside empirical evaluation. This, we argue, is a fundamental reason why psychiatry is unable to define clinically useful biomarkers: because psychiatry does not currently quantify clinical data, decision models cannot be operationalized and, in the absence of an operationalized decision model, it is impossible to define how a biomarker might be of use. Here, psychiatry might benefit from digital technologies that have recently emerged specifically to quantify clinically relevant facets of human behavior. We propose that digital tools might help psychiatry in two ways: first, by quantifying data already present in the standard clinical interaction and by allowing decision models to be operationalized and evaluated; second, by testing whether new forms of data might have value within an operationalized decision model. We reference successes from other medical specialties to illustrate how quantitative data and operationalized decision models improve patient care

Simple, Fast and Accurate Implementation of the Diffusion Approximation Algorithm for Stochastic Ion Channels with Multiple States

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects that channel noise can have on neural dynamics are generally studied using numerical simulations of stochastic models. Algorithms based on discrete Markov Chains (MC) seem to be the most reliable and trustworthy, but even optimized algorithms come with a non-negligible computational cost. Diffusion Approximation (DA) methods use Stochastic Differential Equations (SDE) to approximate the behavior of a number of MCs, considerably speeding up simulation times. However, model comparisons have suggested that DA methods did not lead to the same results as in MC modeling in terms of channel noise statistics and effects on excitability. Recently, it was shown that the difference arose because MCs were modeled with coupled activation subunits, while the DA was modeled using uncoupled activation subunits. Implementations of DA with coupled subunits, in the context of a specific kinetic scheme, yielded similar results to MC. However, it remained unclear how to generalize these implementations to different kinetic schemes, or whether they were faster than MC algorithms. Additionally, a steady state approximation was used for the stochastic terms, which, as we show here, can introduce significant inaccuracies. We derived the SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable - allowing an easy and efficient DA implementation. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods.Comment: 32 text pages, 10 figures, 1 supplementary text + figur

Biomarkers in dementia: clinical utility and new directions.

Imaging, cerebrospinal fluid (CSF) and blood-based biomarkers have the potential to improve the accuracy by which specific causes of dementia can be diagnosed in vivo, provide insights into the underlying pathophysiology, and may be used as inclusion criteria and outcome measures for clinical trials. While a number of imaging and CSF biomarkers are currently used for each of these purposes, this is an evolving field, with numerous potential biomarkers in varying stages of research and development. We review the currently available biomarkers for the three most common forms of neurodegenerative dementia, and give an overview of research techniques that may in due course make their way into the clinic

Focusing the Neuroscience and Societal Implications of Cognitive Enhancers.

Cognitive enhancement can benefit the individual and society, but also has associated risks and ethical concerns. Cognitive-enhancing drugs are used in the treatment of neuropsychiatric disorders. Nonpharmacological strategies are also emerging, which have the potential to improve motivational deficits associated with neuropsychiatric symptoms and should be prioritized for development. The increasing lifestyle use of "smart" and other drugs indicates the desire for healthy people to improve themselves. Safety and ethical implications are discussed.Janssen/J&J, Wallitt FoundationThis is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/cpt.45

Associations between plasma neurofilament light, in vivo brain pathology, and cognition in non-demented individuals with autosomal-dominant Alzheimer's disease

BACKGROUND: Neurofilament light (NfL) is a promising biomarker of early neurodegeneration in Alzheimer's disease (AD). We examined whether plasma NfL was associated with in vivo amyloid beta and tau, and cognitive performance in non-demented presenilin-1 (PSEN1) E280A mutation carriers. METHODS: Twenty-five mutation carriers and 19 non-carriers (age range: 28 to 49 years) were included in this study. Participants underwent 11C Pittsburgh compound B (PiB)-PET (positron emission tomography), flortaucipir-PET, blood sampling, and cognitive testing. RESULTS: Mutation carriers exhibited higher plasma NfL levels than non-carriers. In carriers, higher NfL levels were related to greater regional tau burden and worse cognition, but not amyloid beta load. When we adjusted for age, a proxy of disease progression, elevated plasma NfL levels were only correlated with worse memory recall. CONCLUSIONS: Findings support an association between plasma NfL, cognition, and tau pathology in non-demented individuals at genetic risk for developing AD dementia. Plasma NfL may be useful for selecting individuals at increased risk and tracking disease progression in AD