scholarly journals Development of the P300 from childhood to adulthood: a multimodal EEG and MRI study

2018 ◽  
Author(s):  
Knut Overbye ◽  
Rene J. Huster ◽  
Kristine B. Walhovd ◽  
Anders M. Fjell ◽  
Christian K. Tamnes
Keyword(s):  
Surface Area ◽  
Temporal Cortex ◽  
Relevant Information ◽  
Inferior Temporal Cortex ◽  
Cross Sectional ◽  
Attentional Processes ◽  
Age Related ◽  
Brain Responses ◽  
Component Strength ◽  
Mri Study

ABSTRACTMaturation of attentional processes is central to cognitive development. The electrophysiological P300 is associated with rapid allocation of attention, and bridges stimulus and response processing. P300 is among the most studied and robust electrophysiological components, but how different subcomponents of the P300 develop from childhood to adulthood and relate to structural properties of the cerebral cortex is not well understood. We investigated age-related differences in both early visual and P300 components, and how individual differences in these components related to cortical structure in a cross-sectional sample of participants 8-19 years (n=86). Participants completed a three-stimulus visual oddball task while high-density EEG was recorded. Cortical surface area and thickness were estimated from T1-weighthed MRI. Group-level blind source separation of the EEG data identified two P300-like components, a fronto-central P300 and a parietal P300, as well as a component reflecting N1 and P2. Differences in activity across age were found for the parietal P300, N1 and P2, with the parietal P300 showing stronger activity for older participants, while N1 and P2 were stronger for younger participants. Stronger P300 components were positively associated with task performance, independently of age, while negative associations were found for P2 strength. Parietal P300 strength was age-independently associated with larger surface area in a region in left lateral inferior temporal cortex. We suggest that the age differences in component strength reflect development of attentional mechanisms, with increased brain responses to task-relevant stimuli representing an increasing ability to focus on relevant information and to respond accurately and efficiently.

scholarly journals Daily Medication Management and Adherence in the Polymedicated Elderly: A Cross-Sectional Study in Portugal

2019 ◽  
Vol 17 (1) ◽  
pp. 200 ◽  
Author(s):  
Daniel Gomes ◽  
Ana Isabel Placido ◽  
Rita Mó ◽  
João Lindo Simões ◽  
Odete Amaral ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Side Effects ◽  
Medication Management ◽  
Relevant Information ◽  
Cross Sectional Study ◽  
Daily Routine ◽  
Improve Medication Adherence ◽  
Related Factors ◽  
Cross Sectional ◽  
Age Related

The presence of age-related comorbidities prone elderly patients to the phenomenon of polypharmacy and consequently to a higher risk of nonadherence. Thus, this paper aims to characterize the medication consumption profile and explore the relationship of beliefs and daily medication management on medication adherence by home-dwelling polymedicated elderly people. A questionnaire on adherence, managing, and beliefs of medicines was applied to polymedicated patients with ≥65 years old, in primary care centers of the central region of Portugal. Of the 1089 participants, 47.7% were considered nonadherent. Forgetfulness (38.8%), difficulties in managing medication (14.3%), concerns with side effects (10.7%), and the price of medication (9.2%) were pointed as relevant medication nonadherence-related factors. It was observed that patients who had difficulties managing medicines, common forgetfulness, concerns with side effects, doubting the need for the medication, considered prices expensive, and had a lack of trust for some medicines had a higher risk of being nonadherent. This study provides relevant information concerning the daily routine and management of medicines that can be useful to the development of educational strategies to promote health literacy and improve medication adherence in polymedicated home-dwelling elderly.

scholarly journals Dynamic Population Coding of Category Information in Inferior Temporal and Prefrontal Cortex

2008 ◽  
Vol 100 (3) ◽  
pp. 1407-1419 ◽  
Author(s):  
Ethan M. Meyers ◽  
David J. Freedman ◽  
Gabriel Kreiman ◽  
Earl K. Miller ◽  
Tomaso Poggio
Keyword(s):  
Prefrontal Cortex ◽  
Visual Information ◽  
Activity Patterns ◽  
Temporal Cortex ◽  
Relevant Information ◽  
Population Coding ◽  
Inferior Temporal Cortex ◽  
Category Information ◽  
Almost All ◽  
Dynamic Population

Most electrophysiology studies analyze the activity of each neuron separately. While such studies have given much insight into properties of the visual system, they have also potentially overlooked important aspects of information coded in changing patterns of activity that are distributed over larger populations of neurons. In this work, we apply a population decoding method to better estimate what information is available in neuronal ensembles and how this information is coded in dynamic patterns of neural activity in data recorded from inferior temporal cortex (ITC) and prefrontal cortex (PFC) as macaque monkeys engaged in a delayed match-to-category task. Analyses of activity patterns in ITC and PFC revealed that both areas contain “abstract” category information (i.e., category information that is not directly correlated with properties of the stimuli); however, in general, PFC has more task-relevant information, and ITC has more detailed visual information. Analyses examining how information coded in these areas show that almost all category information is available in a small fraction of the neurons in the population. Most remarkably, our results also show that category information is coded by a nonstationary pattern of activity that changes over the course of a trial with individual neurons containing information on much shorter time scales than the population as a whole.

scholarly journals Large-scale hyperparameter search for predicting human brain responses in the Algonauts challenge

2019 ◽  
Author(s):  
Kamila M. Jozwik ◽  
Michael Lee ◽  
Tiago Marques ◽  
Martin Schrimpf ◽  
Pouya Bashivan
Keyword(s):  
Large Scale ◽  
Visual Stimuli ◽  
Temporal Cortex ◽  
Image Features ◽  
Inferior Temporal Cortex ◽  
Network Architectures ◽  
Image Preprocessing ◽  
Neural Representations ◽  
Brain Responses ◽  
Early Visual Cortex

Image features computed by specific convolutional artificial neural networks (ANNs) can be used to make state-of-the-art predictions of primate ventral stream responses to visual stimuli.However, in addition to selecting the specific ANN and layer that is used, the modeler makes other choices in preprocessing the stimulus image and generating brain predictions from ANN features. The effect of these choices on brain predictivity is currently underexplored.Here, we directly evaluated many of these choices by performing a grid search over network architectures, layers, image preprocessing strategies, feature pooling mechanisms, and the use of dimensionality reduction. Our goal was to identify model configurations that produce responses to visual stimuli that are most similar to the human neural representations, as measured by human fMRI and MEG responses. In total, we evaluated more than 140,338 model configurations. We found that specific configurations of CORnet-S best predicted fMRI responses in early visual cortex, and CORnet-R and SqueezeNet models best predicted fMRI responses in inferior temporal cortex. We found specific configurations of VGG-16 and CORnet-S models that best predicted the MEG responses.We also observed that downsizing input images to ~50-75% of the input tensor size lead to better performing models compared to no downsizing (the default choice in most brain models for vision). Taken together, we present evidence that brain predictivity is sensitive not only to which ANN architecture and layer is used, but choices in image preprocessing and feature postprocessing, and these choices should be further explored.

scholarly journals Witnessed apneas are associated with elevated tau-PET levels in cognitively unimpaired elderly

Neurology ◽  
2020 ◽  
Vol 94 (17) ◽  
pp. e1793-e1802 ◽  
Author(s):  
Diego Z. Carvalho ◽  
Erik K. St. Louis ◽  
Christopher G. Schwarz ◽  
Val J. Lowe ◽  
Bradley F. Boeve ◽  
...  
Keyword(s):  
Linear Models ◽  
Temporal Cortex ◽  
Standardized Uptake Value ◽  
Brain Regions ◽  
Population Based ◽  
Inferior Temporal Cortex ◽  
Elderly Persons ◽  
Cross Sectional ◽  
Tau Pet ◽  
Close Relatives

ObjectiveTo assess whether informant-reported apneas during sleep (witnessed apneas) in cognitively unimpaired (CU) elderly persons are associated with higher levels of brain tau.MethodsFrom the population-based Mayo Clinic Study of Aging, we identified 292 CU elderly ≥65 years of age with both AV-1451 tau-PET and Pittsburgh compound B (PiB)-PET scans and whose bed partners and close relatives had completed a questionnaire that assessed whether participants had witnessed apneas during sleep. For this cross-sectional analysis, we selected the entorhinal and inferior temporal cortices as our regions of interest (ROIs) because they are highly susceptible to tau accumulation. PET signal was scaled to the cerebellum crus to calculate standardized uptake value ratio (SUVR). We fit linear models to assess the association between regional tau and witnessed apneas while controlling for age, sex, years of education, body mass index, hypertension, hyperlipidemia, diabetes, reduced sleep, excessive daytime sleepiness, and global PiB.ResultsForty-three participants (14.7%) were found to have witnessed apneas during sleep. The report of witnessed apneas was associated with higher tau-PET SUVR elevation in our ROIs: 0.049 SUVR (95% confidence interval [CI] 0.010–0.087, p = 0.015) in the entorhinal cortex and 0.037 SUVR (95% CI 0.006–0.067, p = 0.019) in the inferior temporal cortex after controlling for confounders.ConclusionWe identified a significant association between witnessed apneas in CU elderly and elevated tau-PET signal in tau-susceptible brain regions. These results suggest a plausible mechanism that could contribute to cognitive impairment and the development of Alzheimer disease. Longitudinal observations are necessary to determine direction of causality.

scholarly journals Cortical Activation to Social and Mechanical Stimuli in the Infant Brain

2021 ◽  
Vol 15 ◽  
Author(s):  
Marisa Biondi ◽  
Amy Hirshkowitz ◽  
Jacqueline Stotler ◽  
Teresa Wilcox
Keyword(s):  
Social Interaction ◽  
Age Groups ◽  
Temporal Cortex ◽  
Cortical Activation ◽  
Mechanical Stimuli ◽  
Mechanical Interaction ◽  
Cross Sectional ◽  
Age Related ◽  
The Right ◽  
The Hill

From the early days of life infants distinguish between social and non-social physical entities and have different expectations for the way these two entities should move and interact. At the same time, we know very little about the cortical systems that support this early emerging ability. The goal of the current research was to assess the extent to which infant’s processing of social and non-social physical entities is mediated by distinct information processing systems in the temporal cortex. Using a cross-sectional design, infants aged 6–9 months (Experiment 1) and 11–18 months (Experiment 2) were presented with two types of events: social interaction and mechanical interaction. In the social interaction event (patterned after Hamlin et al., 2007), an entity with googly eyes, hair tufts, and an implied goal of moving up the hill was either helped up, or pushed down, a hill through the actions of another social entity. In the mechanical interaction event, the googly eyes and hair tufts were replaced with vertical black dots and a hook and clasp, and the objects moved up or down the hill via mechanical interactions. FNIRS was used to measure activation from temporal cortex while infants viewed the test events. In both age groups, viewing social and mechanical interaction events elicited different patterns of activation in the right temporal cortex, although responses were more specialized in the older age group. Activation was not obtained in these areas when the objects moved in synchrony without interacting, suggesting that the causal nature of the interaction events may be responsible, in part, to the results obtained. This is one of the few fNIRS studies that has investigated age-related patterns of cortical activation and the first to provide insight into the functional development of networks specialized for processing of social and non-social physical entities engaged in interaction events.

scholarly journals Limbic Predominant Age-Related TDP-43 Encephalopathy (LATE): Clinical and Neuropathological Associations

2019 ◽  
Vol 79 (3) ◽  
pp. 305-313 ◽  
Author(s):  
Lilah M Besser ◽  
Merilee A Teylan ◽  
Peter T Nelson
Keyword(s):  
Hippocampal Sclerosis ◽  
Temporal Cortex ◽  
Lewy Body Disease ◽  
Inferior Temporal Cortex ◽  
Common Disease ◽  
Predominant Symptom ◽  
Age Related ◽  
Motor Problems ◽  
Potential Risk Factors ◽  
Immunohistochemical Studies

Abstract Recently, a consensus working group provided new terminology for a common disease entity, limbic predominant age-related TDP-43 encephalopathy (LATE), and its neuropathological substrate (LATE-NC). LATE-NC not only often co-occurs with Alzheimer disease neuropathological change (ADNC), but also may present in isolation. The present study aimed to investigate potential risk factors and neuropathological characteristics associated with LATE-NC. A sample of 616 autopsied participants (>75 years at death), with TDP-43 immunohistochemical studies performed, was obtained from the National Alzheimer’s Coordinating Center. Logistic regression analyses examined associations between demographic, clinical and neuropathological characteristics and LATE-NC (TDP-43 in amygdala, hippocampus, or entorhinal/inferior temporal cortex) (alpha = 0.05). Adjusted models indicated that ADNC, hippocampal sclerosis (HS), arteriolosclerosis, and limbic or amygdala-predominant Lewy body disease (LBD), but not other LBD subtypes, were associated with higher odds of LATE-NC, whereas congestive heart failure (CHF) and motor problems as first predominant symptom were associated with lower odds of LATE-NC. Our findings corroborate previous studies indicating associations between LATE-NC and ADNC, HS, and arteriolosclerosis. Novel findings suggest the association with LATE-NC is restricted to amygdala/limbic-predominant subtype of LBD, and a possible protective (or competing risk) association with CHF. This study may inform future hypothesis-driven research on LATE-NC, a common brain disease of aging.

scholarly journals The Costs of Emotional Attention: Affective Processing Inhibits Subsequent Lexico-semantic Analysis

2007 ◽  
Vol 19 (12) ◽  
pp. 1932-1949 ◽  
Author(s):  
Niklas Ihssen ◽  
Sabine Heim ◽  
Andreas Keil
Keyword(s):  
Semantic Analysis ◽  
Word Identification ◽  
Temporal Cortex ◽  
Semantic Networks ◽  
Semantic Category ◽  
Relevant Information ◽  
Inferior Temporal Cortex ◽  
Spatial Proximity ◽  
Affective Processing ◽  
Source Modeling

The human brain has evolved to process motivationally relevant information in an optimized manner. The perceptual benefit for emotionally arousing material, termed motivated attention, is indexed by electrocortical amplification at various levels of stimulus analysis. An outstanding issue, particularly on a neuronal level, refers to whether and how perceptual enhancement for arousing signals translates into modified processing of information presented in temporal or spatial proximity to the affective cue. The present studies aimed to examine facilitation and interference effects of task-irrelevant emotional pictures on subsequent word identification. In the context of forced-choice lexical decision tasks, pictures varying in hedonic valence and emotional arousal preceded word/ pseudoword targets. Across measures and experiments, high-arousing compared to low-arousing pictures were associated with impaired processing of word targets. Arousing pleasant and unpleasant pictures prolonged word reaction times irrespective of stimulus-onset asynchrony (80 msec, 200 msec, 440 msec) and salient semantic category differences (e.g., erotica vs. mutilation pictures). On a neuronal level, interference was reflected in reduced N1 responses (204–264 msec) to both target types. Paralleling behavioral effects, suppression of the late positivity (404–704 msec) was more pronounced for word compared to pseudoword targets. Regional source modeling indicated that early reduction effects originated from inhibited cortical activity in posterior areas of the left inferior temporal cortex associated with orthographic processing. Modeling of later reduction effects argues for interference in distributed semantic networks comprising left anterior temporal and parietal sources. Thus, affective processing interferes with subsequent lexico-semantic analysis along the ventral stream.

scholarly journals Deep Learning-Based Brain Transcriptomic Signatures Associated with the Neuropathological and Clinical Severity of Alzheimer's Disease

2021 ◽  
Author(s):  
Qi Wang ◽  
Benjamin Readhead ◽  
Kewei Chen ◽  
Yi Su ◽  
Eric M Reiman ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Temporal Cortex ◽  
Amyloid Β ◽  
Clinical Severity ◽  
Molecular Networks ◽  
Cross Sectional ◽  
Age Related ◽  
Gene Modules

Brain tissue gene expression from donors with and without Alzheimer's disease (AD) have been used to help inform the molecular changes associated with the development and potential treatment of this disorder. Here, we use a deep learning method to analyze RNA-seq data from 1,114 brain donors from the AMP-AD consortium to characterize post-mortem brain transcriptome signatures associated with amyloid-β plaque, tau neurofibrillary tangles, and clinical severity in multiple AD dementia populations. Starting from the cross-sectional data in the ROSMAP cohort (n = 634), a deep learning framework was built to obtain a trajectory that mirrors AD progression. A severity index (SI) was defined to quantitatively measure the progression based on the trajectory. Network analysis was then carried out to identify key gene (index gene) modules present in the model underlying the progression. Within this dataset, SIs were found to be very closely correlated with all the AD neuropathology biomarkers (R ~ 0.5, p < 1e-11) and global cognitive function (R = -0.68, p < 2.2e-16). We then applied the model to additional transcriptomic datasets from different brain regions (MAYO, n = 266; MSBB, n = 214), and observed that the model remained significantly predictive (p < 1e-3) of neuropathology and clinical severity. The index genes that significantly contributed to the model were integrated with AD co-expression regulatory networks, resolving two discrete gene modules that are implicated in vascular and metabolic dysfunction in different cell types respectively. Our work demonstrates the generalizability of this signature to frontal and temporal cortex measurements and additional brain donors with AD, other age-related neurological disorders and controls; and revealed the transcriptomic network modules contribute to neuropathological and clinical disease severity. This study illustrates the promise of using deep learning methods to analyze heterogeneous omics data and discover potentially targetable molecular networks that can inform the development, treatment and prevention of neurodegenerative diseases like AD.

scholarly journals Sexual Regional Dimorphism of Post-Adolescent and Middle Age Brain Maturation. A Multi-center 3T MRI Study

2021 ◽  
Vol 13 ◽  
Author(s):  
Giuseppe Delvecchio ◽  
Eleonora Maggioni ◽  
Alessandro Pigoni ◽  
B. Crespo-Facorro ◽  
Igor Nenadić ◽  
...  
Keyword(s):  
Brain Maturation ◽  
Cross Sectional ◽  
Sex Effects ◽  
Age Related ◽  
Neurologic Disorders ◽  
Multiple Regions ◽  
3.0 T ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Study ◽  
Developmental Phases

Sex-related differences are tied into neurodevelopmental and lifespan processes, beginning early in the perinatal and developmental phases and continue into adulthood. The present study was designed to investigate sexual dimorphism of changes in gray matter (GM) volume in post-adolescence, with a focus on early and middle-adulthood using a structural magnetic resonance imaging (MRI) dataset of healthy controls from the European Network on Psychosis, Affective disorders and Cognitive Trajectory (ENPACT). Three hundred and seventy three subjects underwent a 3.0 T MRI session across four European Centers. Age by sex effects on GM volumes were investigated using voxel-based morphometry (VBM) and the Automated Anatomical Labeling atlas regions (ROI). Females and males showed overlapping and non-overlapping patterns of GM volume changes during aging. Overlapping age-related changes emerged in bilateral frontal and temporal cortices, insula and thalamus. Both VBM and ROI analyses revealed non-overlapping changes in multiple regions, including cerebellum and vermis, bilateral mid frontal, mid occipital cortices, left inferior temporal and precentral gyri. These findings highlight the importance of accounting for sex differences in cross-sectional analyses, not only in the study of normative changes, but particularly in the context of psychiatric and neurologic disorders, wherein sex effects may be confounded with disease-related changes.

Neuroanatomical markers of familial risk in adolescents with conduct disorder and their unaffected relatives

2021 ◽  
pp. 1-11
Author(s):  
Graeme Fairchild ◽  
Kate Sully ◽  
Luca Passamonti ◽  
Marlene Staginnus ◽  
Angela Darekar ◽  
...  
Keyword(s):  
Conduct Disorder ◽  
Surface Area ◽  
Brain Structure ◽  
Structural Changes ◽  
Familial Risk ◽  
Temporal Cortex ◽  
Lower Surface ◽  
Anterior Cingulate ◽  
Inferior Temporal Cortex ◽  
Group Differences

Abstract Background Previous studies have reported brain structure abnormalities in conduct disorder (CD), but it is unclear whether these neuroanatomical alterations mediate the effects of familial (genetic and environmental) risk for CD. We investigated brain structure in adolescents with CD and their unaffected relatives (URs) to identify neuroanatomical markers of familial risk for CD. Methods Forty-one adolescents with CD, 24 URs of CD probands, and 38 healthy controls (aged 12–18), underwent structural magnetic resonance imaging. We performed surface-based morphometry analyses, testing for group differences in cortical volume, thickness, surface area, and folding. We also assessed the volume of key subcortical structures. Results The CD and UR groups both displayed structural alterations (lower surface area and folding) in left inferior parietal cortex compared with controls. In contrast, CD participants showed lower insula and pars opercularis volume than controls, and lower surface area and folding in these regions than controls and URs. The URs showed greater folding in rostral anterior cingulate and inferior temporal cortex than controls and greater medial orbitofrontal folding than CD participants. The surface area and volume differences were not significant when controlling for attention-deficit/hyperactivity disorder comorbidity. There were no group differences in subcortical volumes. Conclusions These findings suggest that alterations in inferior parietal cortical structure partly mediate the effects of familial risk for CD. These structural changes merit investigation as candidate endophenotypes for CD. Neuroanatomical changes in medial orbitofrontal and anterior cingulate cortex differentiated between URs and the other groups, potentially reflecting neural mechanisms of resilience to CD.

Sign in / Sign up

Export Citation Format

Share Document