The metabolic costs of cognition.

Cognition and behavior are emergent properties of brain systems that seek to maximize complex and adaptive behaviors while minimizing energy utilization. Different species reconcile this trade-off in different ways, but in humans the outcome is biased towards complex behaviors and hence relatively high energy use. However, even in energy-intensive brains, numerous parsimonious processes operate to optimize energy use.

Large language models surpass human experts in predicting neuroscience results.

Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offer a solution. LLMs trained on the vast scientific literature could potentially integrate noisy yet interrelated findings to forecast novel results better than human experts.

The interplay of age, gender and amyloid on brain and cognition in mid-life and older adults.

Deficits in memory are seen as a canonical sign of aging and a prodrome to dementia in older adults. However, our understanding of age-related cognition and brain morphology occurring throughout a broader spectrum of adulthood remains limited. We quantified the relationship between cognitive function and brain morphology (sulcal width, SW) using three cross-sectional observational datasets (PISA, AIBL, ADNI) from mid-life to older adulthood, assessing the influence of age, sex, amyloid (Aβ) and genetic risk for dementia.

A central role of sulcal width in the associations of sleep duration and depression with cognition in mid to late life.

Study Objectives: Evidence suggests that poor sleep impacts cognition, brain health, and dementia risk but the nature of the association is poorly understood. This study examined how self-reported sleep duration, napping, and subjective depression symptoms are associated with the brain-cognition relationship in older adults, using sulcal width as a measure of relative brain health.

Methods: A canonical partial least squares analysis was used to obtain two composite variables that relate cognition and sulcal width in a cross-sectional study of 137 adults aged 46-72.

Patterns of small involuntary fixation saccades (SIFSs) in different neurodegenerative diseases: the role of noise.

During the attempt to steadily fixate at a single spot, sequences of small involuntary fixation saccades (SIFSs, known also as microsaccades οr intrusions) occur which form spatio-temporal patterns such as square wave jerks (SWJs), a pattern characterised by alternating centrifugal and centripetal movements of similar magnitude. In many neurodegenerative disorders, SIFSs exhibit elevated amplitudes and frequencies. Elevated SIFS amplitudes have been shown to favour the occurrence of SWJs ("SWJ coupling").

Diffusion Tensor Imaging in Amyotrophic Lateral Sclerosis: Machine Learning for Biomarker Development.

Diffusion tensor imaging (DTI) allows the in vivo imaging of pathological white matter alterations, either with unbiased voxel-wise or hypothesis-guided tract-based analysis. Alterations of diffusion metrics are indicative of the cerebral status of patients with amyotrophic lateral sclerosis (ALS) at the individual level. Using machine learning (ML) models to analyze complex and high-dimensional neuroimaging data sets, new opportunities for DTI-based biomarkers in ALS arise.

Sequential alterations in diffusion metrics as correlates of disease severity in amyotrophic lateral sclerosis.

Background And Objective: The neuropathology of amyotrophic lateral sclerosis (ALS) follows a regional distribution pattern in the brain with four stages. Using diffusion tensor imaging (DTI), this pattern can be translated into a tract-based staging scheme to assess cerebral progression in vivo. This study investigates the association between the sequential alteration pattern and disease severity in patients with ALS.

Morphological alterations of the hypothalamus in idiopathic intracranial hypertension.

Background: The pathophysiology of idiopathic intracranial hypertension (IIH), a condition characterized by raised intracranial pressure, is not well understood.

Objectives: We hypothesized that the hypothalamus might exhibit alterations in patients with IIH, based on its established association with obesity and the potential role of hormonal and metabolic factors in IIH.

Design: Retrospective single-center cohort study.

Artificial neural networks for non-linear age correction of diffusion metrics in the brain.

Human aging is characterized by progressive loss of physiological functions. To assess changes in the brain that occur with increasing age, the concept of brain aging has gained momentum in neuroimaging with recent advancements in statistical regression and machine learning (ML). A common technique to assess the brain age of a person is, first, fitting a regression model to neuroimaging data from a group of healthy subjects, and then, using the resulting model for age prediction.

Longitudinal monitoring of amyotrophic lateral sclerosis by diffusion tensor imaging: Power calculations for group studies.

Introduction: Diffusion tensor imaging (DTI) can be used to map disease progression in amyotrophic lateral sclerosis (ALS) and therefore is a promising candidate for a biomarker in ALS. To this end, longitudinal study protocols need to be optimized and validated regarding group sizes and time intervals between visits. The objective of this study was to assess the influences of sample size, the schedule of follow-up measurements, and measurement uncertainties on the statistical power to optimize longitudinal DTI study protocols in ALS.

A multivariate Bayesian classification algorithm for cerebral stage prediction by diffusion tensor imaging in amyotrophic lateral sclerosis.

Background And Objective: Diffusion tensor imaging (DTI) can be used to tract-wise map correlates of the sequential disease progression and, therefore, to assess disease stages of amyotrophic lateral sclerosis (ALS) in vivo. According to a threshold-based sequential scheme, a classification of ALS patients into disease stages is possible, however, several patients cannot be staged for methodological reasons. This study aims to implement a multivariate Bayesian classification algorithm for disease stage prediction at an individual ALS patient level based on DTI metrics of involved tract systems to improve disease stage mapping.

Multimodal in vivo staging in amyotrophic lateral sclerosis using artificial intelligence.

Background: The underlying neuropathological process of amyotrophic lateral sclerosis (ALS) can be classified in a four-stage sequential pTDP-43 cerebral propagation scheme. Using diffusion tensor imaging (DTI), in vivo imaging of these stages has already been shown to be feasible for the specific corticoefferent tract systems. Because both cognitive and oculomotor dysfunctions are associated with microstructural changes at the brain level in ALS, a cognitive and an oculomotor staging classification were developed, respectively.

Segmental alterations of the corpus callosum in motor neuron disease: A DTI and texture analysis in 575 patients.

Introduction: Within the core neuroimaging signature of amyotrophic lateral sclerosis (ALS), the corpus callosum (CC) is increasingly recognized as a consistent feature. The aim of this study was to investigate the sensitivity and specificity of the microstructural segmental CC morphology, assessed by diffusion tensor imaging (DTI) and high-resolution T1-weighted (T1w) imaging, in a large cohort of ALS patients including different clinical phenotypes.

Methods: In a single-centre study, 575 patients with ALS (classical phenotype, N  = 432; restricted phenotypes primary lateral sclerosis (PLS) N = 55, flail arm syndrome (FAS) N = 45, progressive bulbar palsy (PBP) N = 22, lower motor neuron disease (LMND) N = 21) and 112 healthy controls underwent multiparametric MRI, i.

Multiparametric Microstructural MRI and Machine Learning Classification Yields High Diagnostic Accuracy in Amyotrophic Lateral Sclerosis: Proof of Concept.

The potential of multiparametric quantitative neuroimaging has been extensively discussed as a diagnostic tool in amyotrophic lateral sclerosis (ALS). In the past, the integration of multimodal, quantitative data into a useful diagnostic classifier was a major challenge. With recent advances in the field, machine learning in a data driven approach is a potential solution: neuroimaging biomarkers in ALS are mainly observed in the cerebral microstructure, with diffusion tensor imaging (DTI) and texture analysis as promising approaches.

How to Arrange Follow-Up Time-Intervals for Longitudinal Brain MRI Studies in Neurodegenerative Diseases.

Background: Longitudinal brain MRI monitoring in neurodegeneration potentially provides substantial insights into the temporal dynamics of the underlying biological process, but is time- and cost-intensive and may be a burden to patients with disabling neurological diseases. Thus, the conceptualization of follow-up time-intervals in longitudinal MRI studies is an essential challenge and substantial for the results. The objective of this work is to discuss the association of time-intervals and the results of longitudinal trends in the frequently used design of one baseline and two follow-up scans.

Making America Great Again? National Nostalgia's Effect on Outgroup Perceptions.

Nostalgia is a fond longing for the past that has been shown to increase feelings of meaning, social connectedness, and self-continuity. Although nostalgia for personal memories provides intra- and interpersonal benefits, there may be negative consequences of group-based nostalgia on the perception and acceptance of others. The presented research examined national nostalgia (a form of collective nostalgia), and its effects on group identification and political attitudes in the United States.

Segmental involvement of the corpus callosum in associated ALS: a tract of interest-based DTI study.

Background: hexanucleotide repeat expansions are associated with widespread cerebral alterations, including white matter alterations. However, there is lack of information on changes in commissure fibres. Diffusion tensor imaging (DTI) can identify amyotrophic lateral sclerosis (ALS)-associated patterns of regional brain alterations at the group level.

Diagnostic value of video-oculography in progressive supranuclear palsy: a controlled study in 100 patients.

Background: The eponymous feature of progressive supranuclear palsy (PSP) is oculomotor impairment which is one of the relevant domains in the Movement Disorder Society diagnostic criteria.

Objective: We aimed to investigate the value of specific video-oculographic parameters for the use as diagnostic markers in PSP.

Methods: An analysis of video-oculography recordings of 100 PSP patients and 49 age-matched healthy control subjects was performed.

Eye movement alterations in presymptomatic C9orf72 expansion gene carriers.

Objective: The clinical manifestation of amyotrophic lateral sclerosis (ALS) is characterized by motor neuron degeneration, whereas frontotemporal dementia (FTD) patients show alterations of behavior and cognition. Both share repeat expansions in C9orf72 as the most prevalent genetic cause. Before disease-defining symptoms onset, structural and functional changes at cortical level may emerge in C9orf72 carriers.

Why Can't I Resist Those "Puppy Dog" (or "Kitty Cat") Eyes? A Study of Owner Attachment and Factors Associated with Pet Obesity.

Attachment theory posits that patterns of interaction derived from the attachment system provide a starting point for understanding how people both receive and provide care. Extending this theory to human-animal interactions provides insights into how human psychology affects pets, such as pet obesity. The goal of this study was to determine how attachment anxiety and avoidance might contribute to pet obesity.

Gray (Literature) Matters: Evidence of Selective Hypothesis Reporting in Social Psychological Research.

Selective reporting practices (SRPs)-adding, dropping, or altering study elements when preparing reports for publication-are thought to increase false positives in scientific research. Yet analyses of SRPs have been limited to self-reports or analyses of pre-registered and published studies. To assess SRPs in social psychological research more broadly, we compared doctoral dissertations defended between 1999 and 2017 with the publications based on those dissertations.

To Help or To Harm? Assessing the Impact of Envy on Prosocial and Antisocial Behaviors.

Two studies examined how envy influences prosocial and antisocial behavior. In Experiment 1, participants in an envious state (relative to a neutral state) were less helpful: They picked up fewer dropped pencils in their immediate vicinity. We expanded upon these findings by examining how envy affected both helping and harming behavior in a competitive scenario.