An illustrated guide to the fields of neuroscience. It begins by establishing a basic background of knowledge about brain anatomy and organization, with a particular emphasis on neurons and how they communicate. Later chapters discuss the organization of the visual system in detail.

BACKGROUND:Early detection and intervention are considered important determinants of long-term outcomes of severe mental disorders. Preliminary evidence has shown that in Crete/Greece in rural areas there is a significant delay in seeking mental health care for patients with psychosis or bipolar disorder. AIMS/OBJECTIVES:The primary aim of this study is to examine: the mean age and percentage of involuntary admissions of patients with psychotic spectrum or bipolar disorder at first admission/visit; and whether these associations were affected over the 10 years of the mobile mental health unit (MMHU) operation (2013-2023). A secondary objective is to analyze demographic and clinical differences between younger and older patients at first admission/visit. METHODS:Participants were adults >15 years, diagnosed with psychotic spectrum disorder or bipolar disorder, living within a well-defined catchment-area in Crete/Greece. We compared age of first admission/visit for psychotic or bipolar patients at three time points, specifically years 2013, 2018, and 2023 and differences of patients' demographic and clinical characteristics based on age of first admission/visit. RESULTS:The average age of first admission/visit for patients with psychotic spectrum disorders ranges from 39.7 to 43.1, while the average age range for those with bipolar disorder is approximately 40.7 to 45.97 years. Notably, there was no reduction of the age of first admission/visit over the ten years of the MMHU operation (2013-2023), whereas there was a high percentage of involuntary admissions. Finally, patients who are single, abuse drugs, and have a higher education are more prone to seek psychiatric help earlier. CONCLUSIONS:In rural Crete/Greece the average age of seeking mental care for both disorders was and remains markedly high. The lack of consistent and reliable mental health services coupled with the fear of stigma and cultural characteristics of Greek families and small rural towns, discourages individuals seeking mental health care early.

We investigated neural correlates of Emotion Recognition Accuracy (ERA) using the Assessment of Contextualized Emotions (ACE). ACE infuses context by presenting emotion expressions in a naturalistic group setting and distinguishes between accurately perceiving intended emotions (signal), and bias due to perceiving additional, secondary emotions (noise). This social perception process is argued to induce perspective taking in addition to pattern matching in ERA. Thirty participants were presented with an fMRI-compatible adaptation of the ACE consisting of blocks of neutral and emotional faces in single and group-embedded settings. Participants rated the central character's expressions categorically or using scalar scales in consequent fMRI scans. Distinct brain activations were associated with the perception of emotional vs. neutral faces in the four conditions. Moreover, accuracy and bias scores from the original ACE task performed on another day were associated with brain activation during the scalar (vs. categorical) condition for emotional (vs. neutral) faces embedded in group. These findings suggest distinct cognitive mechanisms linked to each type of emotional rating and highlight the importance of considering cognitive bias in the assessment of social emotion perception.

We examined associations between objective sleep duration and cognitive status in older adults initially categorized as cognitively non-impaired (CNI, n = 57) or diagnosed with mild cognitive impairment (MCI, n = 53). On follow-up, 8 years later, all participants underwent neuropsychiatric/neuropsychological evaluation and 7-day 24-h actigraphy. On re-assessment 62.7% of participants were cognitively declined. Patients who developed dementia had significantly longer night total sleep time (TST) than persons with MCI who, in turn, had longer night TST than CNI participants. Objective long sleep duration is a marker of worse cognitive status in elderly with MCI/dementia and this association is very strong in older adults.

To examine hemodynamic and functional connectivity alterations and their association with neurocognitive and mental health indices in patients with chronic mild traumatic brain injury (mTBI). Resting-state functional MRI (rs-fMRI) and neuropsychological assessment of 37 patients with chronic mTBI were performed. Intrinsic connectivity contrast (ICC) and time-shift analysis (TSA) of the rs-fMRI data allowed the assessment of regional hemodynamic and functional connectivity disturbances and their coupling (or uncoupling). Thirty-nine healthy age- and gender-matched participants were also examined. Patients with chronic mTBI displayed hypoconnectivity in bilateral hippocampi and parahippocampal gyri and increased connectivity in parietal areas (right angular gyrus and left superior parietal lobule (SPL)). Slower perfusion (hemodynamic lag) in the left anterior hippocampus was associated with higher self-reported symptoms of depression (r = − 0.53, p = .0006) and anxiety (r = − 0.484, p = .002), while faster perfusion (hemodynamic lead) in the left SPL was associated with lower semantic fluency (r = − 0.474, p = .002). Finally, functional coupling (high connectivity and hemodynamic lead) in the right anterior cingulate cortex (ACC)) was associated with lower performance on attention and visuomotor coordination (r = − 0.50, p = .001), while dysfunctional coupling (low connectivity and hemodynamic lag) in the left ventral posterior cingulate cortex (PCC) and right SPL was associated with lower scores on immediate passage memory (r = − 0.52, p = .001; r = − 0.53, p = .0006, respectively). Uncoupling in the right extrastriate visual cortex and posterior middle temporal gyrus was negatively associated with cognitive flexibility (r = − 0.50, p = .001). Hemodynamic and functional connectivity differences, indicating neurovascular (un)coupling, may be linked to mental health and neurocognitive indices in patients with chronic mTBI.

BACKGROUND Penetrating traumatic brain injury (TBI) caused by gunshots is a rare type of TBI that leads to poor outcomes and high mortality rates. Conducting a formal neuropsychological evaluation concerning a patient's neurologic status during the chronic recovery phase can be challenging. Furthermore, the clinical assessment of survivors of penetrating TBI has not been adequately documented in the available literature. Severe TBI in patients can provide valuable information about the functional significance of the damaged brain regions. This information can help inform our understanding of the brain's intricate neural network. CASE REPORT We present a case of a 29-year-old right-handed man who sustained a left-hemisphere TBI after a gunshot, causing extensive diffuse damage to the left cerebral and cerebellar hemispheres, mainly sparing the right hemisphere. The patient survived. The patient experienced spastic right-sided hemiplegia, facial hemiparesis, left hemiparesis, and right hemianopsia. Additionally, he had severe global aphasia, which caused difficulty comprehending verbal commands and recognizing printed letters or words within his visual field. However, his spontaneous facial expressions indicating emotions were preserved. The patient received a thorough neuropsychological assessment to evaluate his functional progress following a severe TBI and is deemed to have had a favorable outcome. CONCLUSIONS Research on cognitive function recovery following loss of the right cerebral hemisphere typically focuses on pediatric populations undergoing elective surgery to treat severe neurological disorders. In this rare instance of a favorable outcome, we assessed the capacity of the fully developed right hemisphere to sustain cognitive and emotional abilities, such as language.

Abstract Introduction Processing speed is an early index of cognitive decline in elderly. Also, sleep quality predicts memory deficits in this age group. However, the relationship between sleep fragmentation and processing speed remains controversial. Our aim was examine the longitudinal associations between sleep quality and processing speed in non-demented community dwelling elderly. Methods A sub-sample of 148 participants diagnosed with Mild Cognitive Impairment (MCI;n=79) or cognitively non-impaired (CNI;n=69) from the Cretan Aging Cohort, a large population-based cohort of 3,140 older adults (>60 years; baseline) were followed-up 8 years later (follow-up). Mean age at baseline was 74.9±6.33 and 70.4 ±6.24 years for MCI and CNI persons. Processing speed was assessed based on age and education adjusted z-scores of the Symbol Digit Modality Test. Sleep fragmentation (wake after sleep onset; WASO) was assessed using a 3-day actigraphy at baseline and follow-up. Change between the two time points was calculated using paired sample t-tests. The direct and indirect effects of baseline WASO on subsequent processing speed after controlling for sociodemographic covariates were estimated using panel models in AMOS. Results Average WASO among MCI and CNI participants was 80.6±41min and 72.3±31.2min; p=0.1 and 75.7±34.8min and 59.3±20.6min; p< 0.001 at baseline and follow-up, respectively. Average processing speed decreased between the two measurement points (CNI: 0.23±0.97 and -0.40±1.04; p< 0.001 and MCI: -0.75±0.60 and -1.09±0.72; p< 0.001 at baseline and follow-up, respectively). Baseline WASO directly predicted processing speed (β=-0.201; p=0.04) among MCI persons, while WASO at follow-up fully mediated the relationship between baseline WASO and subsequent processing speed (β=-0.098; p=0.004) in the CNI group. Conclusion Sleep fragmentation predicts diminished processing speed among non-demented elderly. Given the significance of processing speed on cognitive function, interventions improving sleep quality in elderly may prevent/delay cognitive decline. Support (if any) National Strategic Reference Framework (NSRF) - Research Funding Program: THALES entitled “UOC-Multidisciplinary network for the study of Alzheimer’s Disease” Grant Cod: MIS 377299 HELLENIC FOUNDATION FOR REASEARCH AND INNOVATION (HFRI)- Research Funding Program: ELIDEK entitled “Sleep Apnea (OSA) and poor sleep as Risk Factors for decreased cognitive performance in patients with Mild Cognitive Impairment: the Cretan Aging Cohort (CAC)”, Grant Cod: HFRI-FM17-4397

Major depressive disorder (MDD) patients’ personality traits and illness representations are linked to MDD severity. However, the associations between personality and illness representations in MDD and the mediating role of illness representations between personality and MDD severity have not been investigated. This study aimed to prospectively investigate the aforementioned associations and the possible mediating role of illness representations between personality and MDD severity. One hundred twenty-five patients with a MDD diagnosis, aged 48.18 ± 13.92 (84

The purpose of this longitudinal study was to examine the development of spelling in a large sample (N = 503, boys: N = 219) of Greek-speaking children with (N = 41) and without (N = 462) reading difficulties. Children were initially tested in Grades 2–4 and then at five consecutive measurement points over a 3-year period, focusing on how initial reading ability, grade, and gender may moderate the rate of spelling growth. Individual growth curve modeling revealed continuous growth of spelling performance in the total sample, although the growth rate decreased over time for children first tested in Grades 3–4. Spelling growth rate was also significantly slower among children with reading difficulties between Grades 2–4 and 3–5. The two reading groups displayed similar growth rates between Grades 4 and 6. Spelling growth rates did not vary significantly with gender. Overall, our study highlights the persistence of spelling difficulties even after 6 years of systematic teaching in children with reading difficulties. The severe and persistent spelling deficits of Greek-speaking children with reading difficulties may be attributed to the rich morphological system of the Greek language, the intermediate Greek orthographic transparency (in the direction of writing), and their limited experience with print.

Traumatic brain injury (TBI) is currently one of the leading causes of mortality and disability worldwide. At present, no reliable inflammatory or specific molecular neurobiomarker exists in any of the standard models proposed for TBI classification or prognostication. Therefore, the present study was designed to assess the value of a group of inflammatory mediators for evaluating acute TBI, in combination with clinical, laboratory and radiological indices and prognostic clinical scales. In the present single-centre, prospective observational study, 109 adult patients with TBI, 20 adult healthy controls and a pilot group of 17 paediatric patients with TBI from a Neurosurgical Department and two intensive care units of University General Hospital of Heraklion, Greece were recruited. Blood measurements using the ELISA method, of cytokines IL-6, IL-8 and IL-10, ubiquitin C-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein, were performed. Compared with those in healthy control individuals, elevated IL-6 and IL-10 but reduced levels of IL-8 were found on day 1 in adult patients with TBI. In terms of TBI severity classifications, higher levels of IL-6 (P=0.001) and IL-10 (P=0.009) on day 1 in the adult group were found to be associated with more severe TBI according to widely used clinical and functional scales. Moreover, elevated IL-6 and IL-10 in adults were found to be associated with more serious brain imaging findings (r(s)<0.442; P<0.007). Subsequent multivariate logistic regression analysis in adults revealed that early-measured (day 1) IL-6 [odds ratio (OR)=0.987; P=0.025] and UCH-L1 (OR=0.993; P=0.032) are significant independent predictors of an unfavourable outcome. In conclusion, results from the present study suggest that inflammatory molecular biomarkers may prove to be valuable diagnostic and prognostic tools for TBI.

Spartinou, Anastasiaa; Karageorgos, Vlassisb; Sorokos, Konstantinosb; Darivianaki, Panagiotab; Fraidakis, Othonc; Nyktari, Vasileiad; Rovithis, Michaile; Simos, Panagiotisf; Papaioannou, Alexandrag Author Information

Identifying modifiable factors that may predict long-term cognitive decline in the elderly with adequate daily functionality is critical. Such factors may include poor sleep quality and quantity, sleep-related breathing disorders, inflammatory cytokines and stress hormones, as well as mental health problems. This work reports the methodology and descriptive characteristics of a long-term, multidisciplinary study on modifiable risk factors for cognitive status progression, focusing on the 7-year follow-up. Participants were recruited from a large community-dwelling cohort residing in Crete, Greece (CAC; Cretan Aging Cohort). Baseline assessments were conducted in 2013–2014 (Phase I and II, circa 6-month time interval) and follow-up in 2020–2022 (Phase III). In total, 151 individuals completed the Phase III evaluation. Of those, 71 were cognitively non-impaired (CNI group) in Phase II and 80 had been diagnosed with mild cognitive impairment (MCI). In addition to sociodemographic, lifestyle, medical, neuropsychological, and neuropsychiatric data, objective sleep was assessed based on actigraphy (Phase II and III) and home polysomnography (Phase III), while inflammation markers and stress hormones were measured in both phases. Despite the homogeneity of the sample in most sociodemographic indices, MCI persons were significantly older (mean age = 75.03 years, SD = 6.34) and genetically predisposed for cognitive deterioration (APOE ε4 allele carriership). Also, at follow-up, we detected a significant increase in self-reported anxiety symptoms along with a substantial rise in psychotropic medication use and incidence of major medical morbidities. The longitudinal design of the CAC study may provide significant data on possible modifiable factors in the course of cognitive progression in the community-dwelling elderly.

Abstract Introduction Previous cross-sectional studies have shown that insomnia symptoms and objective short sleep are associated with disease severity in patients with Mild Cognitive Impairment (MCI) and Dementia. Our aim was to examine the longitudinal associations between sleep quality/quantity with cognitive progression in non-demented community-dwelling elderly. Methods A sub-sample of 105 participants (77.5% females) from a large population-based cohort in Crete, Greece of 3,140 older adults (>60 years; baseline) were followed up 8 years later (follow-up). All participants underwent neuropsychiatric/neuropsychological evaluation on both phases. At baseline, subjective sleep complaints and objective sleep variables based on 3-day 24 hour actigraphy were assessed. The impact of baseline objective sleep characteristics and/or insomnia (as defined by at least two subjective sleep complaints) on cognitive progression was assessed with univariate and multivariate models controlling for confounders. Results At baseline 50 participants were diagnosed as CNI and 55 as MCI; at follow-up 60 participants (57.1%) displayed clinically significant cognitive deterioration while the remaining showed relatively stable cognitive status. The frequency of persons reporting insomnia symptoms at baseline was higher among those who displayed cognitive deterioration (31.7%) than those in the cognitively stable group (13.3%, p=0.037). Logistic regression analysis showed that participants with insomnia symptoms at baseline, were significantly more likely to deteriorate cognitively at follow-up (p=0.05, OR=2.90). Also, among objective sleep variables added to the model, it was poor sleep efficiency that was associated with cognitive deterioration (p=0.035, OR=3.48). Conclusion More than half of the participants displayed significant cognitive deterioration over 8 years and this decline was predicted by insomnia symptoms and objective poor sleep efficiency at baseline. Improving both quality and quantity of sleep may significantly delay the deterioration of cognitive function in non-demented community-dwelling elderly. Support (if any) National Strategic Reference Framework (NSRF) - Research Funding Program: THALES entitled “UOC-Multidisciplinary network for the study of Alzheimer’s Disease” Grant Cod: MIS 377299 HELLENIC FOUNDATION FOR REASEARCH AND INNOVATION (HFRI)- Research Funding Program: ELIDEK entitled “Sleep Apnea (OSA) and poor sleep as Risk Factors for decreased cognitive performance in patients with Mild Cognitive Impairment: the Cretan Aging Cohort (CAC)”, Grant Cod: HFR1-FM17-4397

Identifying individual patient characteristics that contribute to long-term mental health deterioration following diagnosis of breast cancer (BC) is critical in clinical practice. The present study employed a supervised machine learning pipeline to address this issue in a subset of data from a prospective, multinational cohort of women diagnosed with stage I–III BC with a curative treatment intention. Patients were classified as displaying stable HADS scores (Stable Group; n = 328) or reporting a significant increase in symptomatology between BC diagnosis and 12 months later (Deteriorated Group; n = 50). Sociodemographic, life-style, psychosocial, and medical variables collected on the first visit to their oncologist and three months later served as potential predictors of patient risk stratification. The flexible and comprehensive machine learning (ML) pipeline used entailed feature selection, model training, validation and testing. Model-agnostic analyses aided interpretation of model results at the variable- and patient-level. The two groups were discriminated with a high degree of accuracy (Area Under the Curve = 0.864) and a fair balance of sensitivity (0.85) and specificity (0.87). Both psychological (negative affect, certain coping with cancer reactions, lack of sense of control/positive expectations, and difficulties in regulating negative emotions) and biological variables (baseline percentage of neutrophils, thrombocyte count) emerged as important predictors of mental health deterioration in the long run. Personalized break-down profiles revealed the relative impact of specific variables toward successful model predictions for each patient. Identifying key risk factors for mental health deterioration is an essential first step toward prevention. Supervised ML models may guide clinical recommendations toward successful illness adaptation.

IntroductionAlthough the link between sleep and memory function is well established, associations between sleep macrostructure and memory function in normal cognition and Mild Cognitive Impairment remain unclear. We aimed to investigate the longitudinal associations of baseline objectively assessed sleep quality and duration, as well as time in bed, with verbal memory capacity over a 7–9 year period. Participants are a well-characterized subsample of 148 persons (mean age at baseline: 72.8 ± 6.7 years) from the Cretan Aging Cohort. Based on comprehensive neuropsychiatric and neuropsychological evaluation at baseline, participants were diagnosed with Mild Cognitive Impairment (MCI; n = 79) or found to be cognitively unimpaired (CNI; n = 69). Sleep quality/quantity was estimated from a 3-day consecutive actigraphy recording, whereas verbal memory capacity was examined using the Rey Auditory Verbal Learning Test (RAVLT) and the Greek Passage Memory Test at baseline and follow-up. Panel models were applied to the data using AMOS including several sociodemographic and clinical covariates.ResultsSleep efficiency at baseline directly predicted subsequent memory performance in the total group (immediate passage recall: β = 0.266, p = 0.001; immediate word list recall: β = 0.172, p = 0.01; delayed passage retrieval: β = 0.214, p = 0.002) with the effects in Passage Memory reaching significance in both clinical groups. Wake after sleep onset time directly predicted follow-up immediate passage recall in the total sample (β = −0.211, p = 0.001) and in the MCI group (β = −0.235, p = 0.02). In the total sample, longer 24-h sleep duration was associated with reduced memory performance indirectly through increased sleep duration at follow-up (immediate passage recall: β = −0.045, p = 0.01; passage retention index: β = −0.051, p = 0.01; RAVLT-delayed recall: β = −0.048, p = 0.009; RAVLT-retention index:β = −0.066, p = 0.004). Similar indirect effects were found for baseline 24-h time in bed. Indirect effects of sleep duration/time in bed were found predominantly in the MCI group.DiscussionFindings corroborate and expand previous work suggesting that poor sleep quality and long sleep duration predict worse memory function in elderly. Timely interventions to improve sleep could help prevent or delay age-related memory decline among non-demented elderly.

Using exome sequencing, we analyzed 196 participants of the Cretan Aging Cohort (CAC; 95 with Alzheimer's disease [AD], 20 with mild cognitive impairment [MCI], and 81 cognitively normal controls). The APOE 84 allele was more common in AD patients (23.2%) than in controls (7.4%; p < 0.01) and the PSEN2 p.Arg29His and p.Cys391Arg variants were found in 3 AD and 1 MCI patient, respectively. Also, we found the frontotemporal dementia (FTD)-associated TARDBP gene p.Ile383Val variant in 2 elderly patients diagnosed with AD and in 2 patients, non CAC members, with the amyotrophic lateral sclerosis/FTD phenotype. Furthermore, the p.Ser498Ala variant in the positively selected GLUD2 gene was less frequent in AD patients (2.11%) than in controls (16%; p < 0.01), suggesting a possible protective effect. While the same trend was found in another local replication cohort (n = 406) and in section of the ADNI cohort (n = 808), this finding did not reach statistical significance and therefore it should be considered preliminary. Our results attest to the value of genetic testing to study aged adults with AD phenotype.(c) 2022 Elsevier Inc. All rights reserved.

Depression prevalence increases significantly during adolescence/early adulthood. Depression in youth may present suicidal ideation, while suicide represents the leading cause of death in this age group. Moreover, adolescents/young adults frequently report sleep complaints that may partially be due to depressive symptoms. Studies on the associations between depression, sleep complaints and suicidality in this age group are limited. We aimed to examine associations between depressive symptoms, sleep complaints and suicidal ideation in a large (n = 2771), representative sample of adolescents (age: 15-17 years, n = 512) and young adults (age: 18-24 years, n = 2259) from the general population in Greece. A telephone structured questionnaire was administered. Depressive symptoms were assessed using the modified Patient Health-7 questionnaire score, while presence of suicidal ideation and sleep complaints were assessed using the ninth and third question of Patient Health-9 questionnaire, respectively. Mediation logistic regression analysis revealed significant direct paths from depressive symptoms to sleep complaints (odds ratio [OR] 1.22, 95% confidence interval [CI] 1.19-1.24; OR 1.21, 95% CI 1.18-1.24) and suicidal ideation (OR 1.18, 95% CI 1.14-1.22; OR 1.18, 95% CI 1.14-1.22), as well as sleep complaints and suicidal ideation (OR 1.82, 95% CI 1.32-2.50; OR 1.91, 95% CI 1.33-2.76) in the total group and in young adults, respectively, but not among adolescents. Moreover, we detected a significant indirect effect of depressive symptoms on suicidal ideation mediated by sleep complaints (18.8%) in young adults. These findings support the hypothesis that treatment of sleep disturbances among youth with depression may independently further reduce suicidal risk.

Proper and well-timed interventions may improve breast cancer patient adaptation and quality of life (QoL) through treatment and recovery. The challenge is to identify those patients who would benefit most from a particular intervention. The aim of this study was to measure whether the machine learning prediction incorporated in the clinical decision support system (CDSS) improves clinicians’ performance to predict patients’ QoL during treatment process. We conducted two user experiments in which clinicians used a CDSS to predict QoL of breast cancer patients. In both experiments each patient was evaluated both with and without the aid of a machine learning (ML) prediction. In Experiment I, 60 breast cancer patients were evaluated by 6 clinicians. In Experiment II, 90 patients were evaluated by 9 clinicians. The task of clinicians was to predict the patient’s quality of life at either 6 (Experiment I) or 12 months post-diagnosis (Experiment II). Taking into account input from the machine learning prediction considerably improved clinicians’ prediction accuracy. Accuracy of clinicians for predicting QoL of patients at 6 months post-diagnosis was .745 (95