An exploratory analysis of head-tilting in dogs

Little is known about head-tilts in dogs. Based on previous investigations on the head turning and the lateralised brain pattern of human speech processing in dogs, we hypothesised that head-tilts may be related to increased attention and could be explained by lateralised mental functions. We observed 40 dogs during object-label knowledge tests and analysed head-tilts occurring while listening to humans requesting verbally to fetch a familiar toy. Our results indicate that only dogs that had learned the name of the objects tilted their heads frequently. Besides, the side of the tilt was stable across several months and tests. Thus, we suggest a relationship between head-tilting and processing relevant, meaningful stimuli.

Neural signatures of compression in the retelling of past events

When we retell our past experiences, we aim to reproduce some version of the original events; this reproduced version is often temporally compressed relative to the original. How does such compression of memories manifest in brain activity? One possibility is that a compressed retrieved memory manifests as a neural pattern which is more dissimilar to the original, relative to a more detailed or vivid memory. However, we argue that measuring raw dissimilarity alone is insufficient, as it confuses a variety of interesting and uninteresting changes. To address this problem, we examine brain pattern changes that are consistent across people. We show that temporal compression in individuals' retelling of past events predicts systematic encoding-to-recall transformations in a number of higher associative regions. These findings elucidate how neural representations are not simply reactivated, but can also be transformed due to temporal compression during a universal form of human memory expression: verbal retelling.

Meta Cognition Thinking and Its Relationship to Patterns of Brain Dominance among Jordanian University Students According to Gender and Specialization Variables

The study aimed to identify the level of Meta Cognition thinking and its relationship to dominant patterns of brain dominance among Jordanian university students, and to identify if there were differences in the level of Meta Cognition thinking and brain dominance patterns attributed to variables of gender and college. The study sample consisted male and female students at the academic year 2020/2021, and this sample was taken in a simple random way. Two measures were applied: Meta Cognition thinking, and brain dominance patterns, after confirming their psychometric properties. The results showed that the level of Meta Cognition thinking among Jordanian university students is (high), and that the dominant brain pattern among the study sample is the right pattern, followed by the left and then the integrated, and also there is no statistically significant relationship between the brain dominance patterns and the variables of gender and college, and there is statistically significant differences in Meta Cognition thinking among students with the (left) brain dominance pattern compared to those with the (integrated) brain control pattern and in favor of those with the left brain dominance type.

The progression of disorder-specific brain pattern expression in schizophrenia over 9 years

Age plays a crucial role in the performance of schizophrenia vs. controls (SZ-HC) neuroimaging-based machine learning (ML) models as the accuracy of identifying first-episode psychosis from controls is poor compared to chronic patients. Resolving whether this finding reflects longitudinal progression in a disorder-specific brain pattern or a systematic but non-disorder-specific deviation from a normal brain aging (BA) trajectory in schizophrenia would help the clinical translation of diagnostic ML models. We trained two ML models on structural MRI data: an SZ-HC model based on 70 schizophrenia patients and 74 controls and a BA model (based on 561 healthy individuals, age range = 66 years). We then investigated the two models’ predictions in the naturalistic longitudinal Northern Finland Birth Cohort 1966 (NFBC1966) following 29 schizophrenia and 61 controls for nine years. The SZ-HC model’s schizophrenia-specificity was further assessed by utilizing independent validation (62 schizophrenia, 95 controls) and depression samples (203 depression, 203 controls). We found better performance at the NFBC1966 follow-up (sensitivity = 75.9%, specificity = 83.6%) compared to the baseline (sensitivity = 58.6%, specificity = 86.9%). This finding resulted from progression in disorder-specific pattern expression in schizophrenia and was not explained by concomitant acceleration of brain aging. The disorder-specific pattern’s progression reflected longitudinal changes in cognition, outcomes, and local brain changes, while BA captured treatment-related and global brain alterations. The SZ-HC model was also generalizable to independent schizophrenia validation samples but classified depression as control subjects. Our research underlines the importance of taking account of longitudinal progression in a disorder-specific pattern in schizophrenia when developing ML classifiers for different age groups.

Heresenes's Short Life under a "Starry Night"

Heresenes is a mummified 25th Dynasty (ca. 746–653 B.C.) Egyptian woman from Luxor, Egypt. Nondestructive evaluation through computerized tomography (CT) showed a failed attempt at excerebration, leaving Heresenes’s meninges and brain in situ. The brain structure shows numerous millimetric dense calcific nodules, a CT brain pattern dubbed “starry night,” which is consistent with a diagnosis of neurocysticercosis in a nodular calcified stage. A similar speckled pattern in the upper spinal cord and in the heart supports the identification of a disseminated stage of this parasitic disease. If this were the case, then this would be the oldest documented case of this disease known in ancient Egypt, and the first nondestructive radiological diagnosis of it in a completely wrapped Egyptian mummy.Heresenes est une femme Égyptienne momifiée de la 25e dynastie (c. 746 aC–653 aC). L'évaluation non destructive par tomodensitométrie (TDM) a montré l'échec de la tentative d'excérébration, laissant les méninges et le cerveau d'Heresenes in situ. La structure cérébrale présente de nombreux nodules calciques denses millimétriques, une apparence en TDM surnommé «nuit étoilée», ce qui est cohérent avec un diagnostic de neurocysticercose dans un stade nodulaire calcifié. Un motif similaire dans la moelle épinière supérieure et dans le coeur soutien l´identification dun processus disséminé de cette maladie parasitaire. Si tel était le cas, ce serait le plus ancien cas documenté de cette maladie connue dans l'Égypte ancienne, et le premier diagnostic radiologique non destructif dans une momie égyptienne complètement enveloppée.

Morphometric network differences in ageing versus Alzheimer’s disease dementia

Age being the main risk factor for Alzheimer’s disease, it is particularly challenging to disentangle structural changes related to normal brain ageing from those specific to Alzheimer’s disease. Most studies aiming to make this distinction focused on older adults only and on a priori anatomical regions. Drawing on a large, multi-cohort dataset ranging from young adults (n = 468; age range 18–35 years), to older adults with intact cognition (n = 431; age range 55–90 years) and with Alzheimer’s disease (n = 50 with late mild cognitive impairment and 71 with Alzheimer’s dementia, age range 56–88 years), we investigated grey matter organization and volume differences in ageing and Alzheimer’s disease. Using independent component analysis on all participants’ structural MRI, we first derived morphometric networks and extracted grey matter volume in each network. We also derived a measure of whole-brain grey matter pattern organization by correlating grey matter volume in all networks across all participants from the same cohort. We used logistic regressions and receiver operating characteristic analyses to evaluate how well grey matter volume in each network and whole-brain pattern could discriminate between ageing and Alzheimer’s disease. Because increased heterogeneity is often reported as one of the main features characterizing brain ageing, we also evaluated interindividual heterogeneity within morphometric networks and across the whole-brain organization in ageing and Alzheimer’s disease. Finally, to investigate the clinical validity of the different grey matter features, we evaluated whether grey matter volume or whole-brain pattern was related to clinical progression in cognitively normal older adults. Ageing and Alzheimer’s disease contributed additive effects on grey matter volume in nearly all networks, except frontal lobe networks, where differences in grey matter were more specific to ageing. While no networks specifically discriminated Alzheimer’s disease from ageing, heterogeneity in grey matter volumes across morphometric networks and in the whole-brain grey matter pattern characterized individuals with cognitive impairments. Preservation of the whole-brain grey matter pattern was also related to lower risk of developing cognitive impairment, more so than grey matter volume. These results suggest both ageing and Alzheimer’s disease involve widespread atrophy, but that the clinical expression of Alzheimer’s disease is uniquely associated with disruption of morphometric organization.