Temporal Brain Areas Research Articles

Frontoparietal Structural Network Disconnections Correlate With Outcome After a Severe Stroke.

Structural disconnectome analyses have provided valuable insights into how a stroke lesion results in widespread network disturbances and how these relate to deficits, recovery patterns, and outcomes. Previous analyses have primarily focused on patients with relatively mild to moderate deficits. However, outcomes vary among survivors of severe strokes, and the mechanisms of recovery remain poorly understood. This study assesses the association between lesion-induced network disconnection and outcome after severe stroke. Thirty-eight ischaemic stroke patients underwent MRI brain imaging early after stroke and longitudinal clinical follow-up. Lesion information was integrated with normative connectome data to infer individual disconnectome profiles on a localized regional and region-to-region pathway level. Ordinal logistic regressions were computed to link disconnectome information to the modified Rankin Scale after 3-6 months. Disconnections of ipsilesional frontal, parietal, and temporal cortical brain areas were significantly associated with a worse motor outcome after a severe stroke, adjusted for the initial deficit, lesion volume, and age. The analysis of the underlying pathways mediating this association revealed location-specific results: For frontal, prefrontal, and temporal brain areas, the association was primarily driven by relatively sparse intrahemispheric disconnections. In contrast, the ipsilesional primary motor cortex, the dorsal premotor cortex, and various parietal brain regions showed a remarkable involvement of either frontoparietal intrahemispheric or additionally interhemispheric disconnections. These results indicate that localized disconnection of multiple regions embedded in the structural frontoparietal network correlates with worse outcomes after severe stroke. Specifically, primary motor and parietal cortices might gain particular importance as they structurally link frontoparietal networks of both hemispheres. These data shed novel light on the significance of distinct brain networks for recovery after a severe stroke.

The role of alpha oscillations in free- and goal-directed semantic associations.

Alpha oscillations are known to play a central role in several higher-order cognitive functions, especially selective attention, working memory, semantic memory, and creative thinking. Nonetheless, we still know very little about the role of alpha in the generation of more remote semantic associations, which is key to creative and semantic cognition. Furthermore, it remains unclear how these oscillations are shaped by the intention to "be creative," which is the case in most creativity tasks. We aimed to address these gaps in two experiments. In Experiment 1, we compared alpha oscillatory activity (using a method which distinguishes genuine oscillatory activity from transient events) during the generation of free associations which were more vs. less distant from a given concept. In Experiment 2, we replicated these findings and also compared alpha oscillatory activity when people were generating free associations versus associations with the instruction to be creative (i.e. goal-directed). We found that alpha was consistently higher during the generation of more distant semantic associations, in both experiments. This effect was widespread, involving areas in both left and right hemispheres. Importantly, the instruction to be creative seems to increase alpha phase synchronisation from left to right temporal brain areas, suggesting that intention to be creative changed the flux of information in the brain, likely reflecting an increase in top-down control of semantic search processes. We conclude that goal-directed generation of remote associations relies on top-down mechanisms compared to when associations are freely generated.

A Study on the Correlation of Various Factors in Patients With Severe Traumatic Brain Injuries.

Traumatic brain injury (TBI), ranging from minor impacts to severe cases, affects temporal and frontal brain areas, contributing to mortality and disability worldwide. The Glasgow Coma Scale (GCS) evaluates consciousness levels, aiding in prioritizing emergency care, while the Disability Rating Score (DRS) assesses overall function, particularly in severe cases, with greater sensitivity than GCS for clinical changes in TBI patients. To correlate various factors with each other in patients presented with severe TBIs. The retrospective study analyzed data from patients with severe TBIsadmitted to the hospital from February 2023to April 2024. Patients' demographic and clinical data, including GCSand DRSscores, were collected. Statistical analysis, including logistic regression, assessed mortality predictors. The study revealed significant correlations (p<0.05) between age and marital status (p=0.002) and surgery (p=0.003). Surgery also correlated significantly with the mechanism of injury (p<0.001). Furthermore, a negative correlation was found between GCS after 24 hours and change in GCS (p<0.001), while a positive correlation existed between DRS after 24 hoursand DRS on the 14th day (p<0.001). These findings highlight the complex interplay between demographic factors, medical interventions, and clinical outcomes in TBI patients. The study found that older individuals, particularly those involved in road traffic accidents, had poorer recovery outcomes and higher rates of surgery, with a strong correlation between changes in GCSand DRSscores.

Hyperbaric oxygen therapy vs. pharmacological intervention in adults with fibromyalgia related to childhood sexual abuse: prospective, randomized clinical trial

Fibromyalgia syndrome (FMS) is a chronic pain syndrome characterized by disruptions in pain processing within the central nervous system. It exhibits a high prevalence among patients with a history of traumatic experiences, notably childhood sexual abuse (CSA). This study compared the efficacy of hyperbaric oxygen therapy (HBOT) to the current pharmacological standard of care for individuals suffering from CSA-related FMS. Forty-eight participants diagnosed with FMS and a history of CSA were randomly assigned to either the HBOT group (60 sessions of 100% oxygen at 2 ATA for 90 min, with air breaks every 5 min) or the medication (MED) group (FDA-approved medications, Pregabalin and Duloxetine). The primary endpoint was the Fibromyalgia impact questionnaire (FIQ) score, while secondary endpoints encompassed emotional status and daily functioning questionnaires, as well as pain thresholds and conditioned pain modulation tests. Brain activity was evaluated through single photon emission computed tomography (SPECT). Results revealed a significant group-by-time interaction for the FIQ score favoring HBOT over MED (p < 0.001), with a large effect size (Cohen's d = − 1.27). Similar findings were observed in emotional symptoms and functional measures. SPECT imaging demonstrated an increase in activity in pre-frontal and temporal brain areas, which correlated with symptoms improvement. In conclusion, HBOT exhibited superior benefits over medications in terms of physical, functional, and emotional improvements among FMS patients with a history of CSA. This associated with increased activity in pre-frontal and temporal brain areas, highlighting the neuroplasticity effect of HBOT.

The neural networks of touch observation

Abstract Studies have consistently demonstrated that the mere observation of touch engages our own somatosensory cortices. However, a systematic evaluation of the involved networks is missing. Here, we present results of a meta-analytic connectivity modeling (MACM) approach based on clusters revealed by activation likelihood estimation (ALE) combined with resting-state analysis to detect networks subserving our ability to empathize with tactile experiences of other people. ALE analysis revealed 8 clusters in frontal, temporal, and parietal brain areas, which behavioral domain profiles predominantly refer to cognition and perception. The MACM analysis further identified distinct networks that are subserved by subcortical structures, revealed that all clusters involved in touch observation are connected to dorso-medial frontal and anterior cingulate cortex control regions, and showed that medial temporal lobe memory structures do not inform network activation during touch observation (confirmed by post hoc resting-state connectivity analyses). Our data highlight the importance of higher-level control areas and suggest only a minor role for past bodily experiences in the ad hoc perception of other people’s experiences.

Cardiorespiratory fitness is associated with cortical thickness of medial temporal brain areas associated with spatial cognition in young but not older adults.

Cardiorespiratory fitness has a potent effect on neurocognitive health, especially regarding the hippocampal memory system. However, less is known about the impact of cardiorespiratory fitness on medial temporal lobe extrahippocampal neocortical regions. Specifically, it is unclear how cardiorespiratory fitness modulates these brain regions in young adulthood and if these regions are differentially related to cardiorespiratory fitness in young versus older adults. The primary goal of this study was to investigate if cardiorespiratory fitness predicted medial temporal lobe cortical thickness which, with the hippocampus, are critical for spatial learning and memory. Additionally, given the established role of these cortices in spatial navigation, we sought to determine if cardiorespiratory fitness and medial temporal lobe cortical thickness would predict greater subjective sense of direction in both young and older adults. Cross-sectional data from 56 young adults (20-35 years) and 44 older adults (55-85 years) were included. FreeSurfer 6.0 was used to automatically segment participants' 3T T1-weighted images. Using hierarchical multiple regression analyses, we confirmed significant associations between greater cardiorespiratory fitness and greater left entorhinal, left parahippocampal, and left perirhinal cortical thickness in young, but not older, adults. Left parahippocampal cortical thickness interacted with age group to differentially predict subjective sense of direction in young and older adults. Young adults displayed a positive, and older adults a negative, correlation between left parahippocampal cortical thickness and sense of direction. Our findings extend previous work on the association between cardiorespiratory fitness and hippocampal subfield structure in young adults to left medial temporal lobe neocortical regions.

Major depressive disorder diagnosis from electroencephalogram data and potential treatment with dimethyltryptamine

In recent times, there has been increasing interest in utilizing EEG-based techniques for studying Major Depressive Disorder as a dynamic method. Although it is frequently used for identifying depression, the method is still difficult to interpret. The conventional treatment of MDD involves medications such as Selective Serotonin Reuptake Inhibitors, which often have adverse effects. On the other hand, the use of dimethyltryptamine to stimulate brain activity in regions where MDD patients show lower activity has demonstrated promising results. This study analyzed resting-state EEG signals from MDD patients, DMT users, and healthy controls to evaluate and validated a computer-aided approach. The brain activity of DMT users was recorded and compared with MDD individuals and healthy controls. Using Welch's method, the power of several frequency bands was analyzed from the EEG dataset for comparison and diagnosis. The extracted EEG data underwent noise removal and feature extraction. The features from all controls were concatenated to form a data matrix. Furthermore, the data matrix was standardized using the Z-score standardization method. The classifier model logistic regression was employed to train and test the extracted features. The results of the investigations have demonstrated the most important features, such as signal power of the EEG data from the frontal, temporal, parietal, and occipital brain areas, to be significant.

Altered brain functional connectivity in vegetative state and minimally conscious state.

The pathological mechanism for a disorder of consciousness (DoC) is still not fully understood. Based on traditional behavioral scales, there is a high rate of misdiagnosis for subtypes of DoC. We aimed to explore whether topological characterization may explain the pathological mechanisms of DoC and be effective in diagnosing the subtypes of DoC. Using resting-state functional magnetic resonance imaging data, the weighted brain functional networks for normal control subjects and patients with vegetative state (VS) and minimally conscious state (MCS) were constructed. Global and local network characteristics of each group were analyzed. A support vector machine was employed to identify MCS and VS patients. The average connection strength was reduced in DoC patients and roughly equivalent in MCS and VS groups. Global efficiency, local efficiency, and clustering coefficients were reduced, and characteristic path length was increased in DoC patients (p < 0.05). For patients of both groups, global network measures were not significantly different (p > 0.05). Nodal efficiency, nodal local efficiency, and nodal clustering coefficient were reduced in frontoparietal brain areas, limbic structures, and occipital and temporal brain areas (p < 0.05). The comparison of nodal centrality suggested that DoC causes reorganization of the network structure on a large scale, especially the thalamus. Lobal network measures emphasized that the differences between the two groups of patients mainly involved frontoparietal brain areas. The accuracy, sensitivity, and specificity of the classifier for identifying MCS and VS patients were 89.83, 78.95, and 95%, respectively. There is an association between altered network structures and clinical symptoms of DoC. With the help of network metrics, it is feasible to differentiate MCS and VS patients.

Triangulating causality between childhood obesity and neurobehavior: Behavioral genetic and longitudinal evidence.

Childhood obesity is a serious health concern that is not yet fully understood. Previous research has linked obesity with neurobehavioral factors such as behavior, cognition, and brain morphology. The causal directions of these relationships remain mostly untested. We filled this gap by using the Adolescent Brain Cognitive Development study cohort comprising 11,875 children aged 9-10. First, correlations between the age- and sex-specific 95th BMI percentile (%BMIp95) and neurobehavioral measures were cross-sectionally analyzed. Effects were then aggregated by neurobehavioral domain for causal analyses. Behavioral genetic Direction of Causation modeling was used to test the direction of each relationship. Findings were validated by longitudinal cross-lagged panel modeling. %BMIp95 correlated with impulsivity, motivation, psychopathology, eating behavior, and cognitive tests (executive functioning, language, memory, perception, working memory). Greater %BMIp95 was also associated with reduced cortical thickness in frontal and temporal brain areas but with increased thickness in parietal and occipital areas. Similar although weaker patterns emerged for cortical surface area and volume. Behavioral genetic modeling suggested causal effects of %BMIp95 on eating behavior (β=0.26), cognition (β=0.05), cortical thickness (β=0.15), and cortical surface area (β=0.07). Personality/psychopathology (β=0.09) and eating behavior (β=0.16) appeared to influence %BMIp95. Longitudinal evidence broadly supported these findings. Results regarding cortical volume were inconsistent. Results supported causal effects of obesity on brain functioning and morphology. The present study highlights the importance of physical health for brain development and may inform interventions aimed at preventing or reducing pediatric obesity. RESEARCH HIGHLIGHTS: A continuous measure related to obesity, %BMIp95, has correlations with various measures of brain functioning and structure Behavioral genetic and longitudinal modeling suggest causal links from personality, psychopathology, and eating behavior to %BMIp95 Results also indicate directional links from %BMIp95 to eating behavior, cognition, cortical thickness, and cortical surface area Obesity may play a role for healthy brain development during childhood.

Neuroanatomical correlates of genetic risk for obesity in children

Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity.

Separate neural subsystems support goal-directed speech listening

How do humans excel at tracking the narrative of a particular speaker with a distracting noisy background? This feat places great demands on the collaboration between speech processing and goal-related regulatory functions. Here, we propose that separate subsystems with different cross-task dynamic activity properties and distinct functional purposes support goal-directed speech listening. We adopted a naturalistic dichotic speech listening paradigm in which listeners were instructed to attend to only one narrative from two competing inputs. Using functional magnetic resonance imaging with inter- and intra-subject correlation techniques, we discovered a dissociation in response consistency in temporal, parietal and frontal brain areas as the task demand varied. Specifically, some areas in the bilateral temporal cortex (SomMotB_Aud and TempPar) and lateral prefrontal cortex (DefaultB_PFCl and ContA_PFCl) always showed consistent activation across subjects and across scan runs, regardless of the task demand. In contrast, some areas in the parietal cortex (DefaultA_pCunPCC and ContC_pCun) responded reliably only when the task goal remained the same. These results suggested two dissociated functional neural networks that were independently validated by performing a data-driven clustering analysis of voxelwise functional connectivity patterns. A subsequent meta-analysis revealed distinct functional profiles for these two brain correlation maps. The different-task correlation map was strongly associated with language-related processes (e.g., listening, speech and sentences), whereas the same-task versus different-task correlation map was linked to self-referencing functions (e.g., default mode, theory of mind and autobiographical topics). Altogether, the three-pronged findings revealed two anatomically and functionally dissociated subsystems supporting goal-directed speech listening.

Change in Latent Gray-Matter Structural Integrity Is Associated With Change in Cardiovascular Fitness in Older Adults Who Engage in At-Home Aerobic Exercise.

In aging humans, aerobic exercise interventions have been found to be associated with more positive or less negative changes in frontal and temporal brain areas, such as the anterior cingulate cortex (ACC) and hippocampus, relative to no-exercise control conditions. However, individual measures such as gray-matter (GM) probability may afford less reliable and valid conclusions about maintenance or losses in structural brain integrity than a latent construct based on multiple indicators. Here, we established a latent factor of GM structural integrity based on GM probability assessed by voxel-based morphometry, magnetization transfer saturation, and mean diffusivity. Based on this latent factor, we investigated changes in structural brain integrity during a six-month exercise intervention in brain regions previously reported in studies using volumetric approaches. Seventy-five healthy, previously sedentary older adults aged 63–76 years completed an at-home intervention study in either an exercise group (EG; n = 40) or in an active control group (ACG; n = 35). Measures of peak oxygen uptake (VO2peak) taken before and after the intervention revealed a time-by-group interaction, with positive average change in the EG and no reliable mean change in the ACG. Significant group differences in structural brain integrity changes were observed in the right and left ACC, right posterior cingulate cortex (PCC), and left juxtapositional lobule cortex (JLC). In all instances, average changes in the EG did not differ reliably from zero, whereas average changes in the ACG were negative, pointing to maintenance of structural brain integrity in the EG, and to losses in the ACG. Significant individual differences in change were observed for right ACC and left JLC. Following up on these differences, we found that exercising participants with greater fitness gains also showed more positive changes in structural integrity. We discuss the benefits and limitations of a latent-factor approach to changes in structural brain integrity, and conclude that aerobic fitness interventions are likely to contribute to brain maintenance in old age.

Surprise and recency in novelty detection in the primate brain

Primates and other animals must detect novel objects. However, the neuronal mechanisms of novelty detection remain unclear. Prominent theories propose that visual object novelty is either derived from the computation of recency(how long ago a stimulus was experienced) or is a form of sensory surprise(stimulus unpredictability). Here, we use high-channel electrophysiology in primates to show that in many primate prefrontal, temporal, and subcortical brain areas, object novelty detection is intertwined with the computations of recency and sensory surprise. Also, distinct circuits could be engaged by expected versus unexpected sensory surprise. Finally, we studied neuronal novelty-to-familiarity transformations during learning across many days. We found a diversity of timescales in neurons' learning rates and between-session forgetting rates, both within and across brain areas, that are well suited to support flexible behavior and learning in response to novelty. Our findings show that novelty sensitivity arises on multiple timescales across single neurons due to diverse but related computations of sensory surprise and recency and shed light on the computational underpinnings of novelty detection in the primate brain.

Cognitive and affective theory of mind double dissociation after parietal and temporal lobe tumours

Abstract Extensive neuroimaging literature suggests that understanding others’ thoughts and emotions engages a wide network encompassing parietal, temporal and medial frontal brain areas. However, the causal role played by these regions in social inferential abilities is still unclear. Moreover very little is known about theory of mind deficits in brain tumours and whether potential anatomical substrates are comparable to those identified in functional MRI literature. This study evaluated the performance of 105 tumour patients, before and immediately after brain surgery, on a cartoon-based non-verbal task evaluating cognitive (intention attribution) and affective (emotion attribution) theory of mind, as well as a non-social control condition (causal inference). Across multiple analyses, we found converging evidence of a double dissociation between patients with right superior parietal damage, selectively impaired in intention attribution, and those with right anteromedial temporal lesion, exhibiting deficits only in emotion attribution. Instead, patients with damage to the frontal cortex were impaired in all kinds of inferential processes, including those from the non-social control conditions. Overall, our data provide novel reliable causal evidence of segregation between different aspects of the theory of mind network from both the cognitive and also the anatomical point of view.

Altered structural brain networks in linguistic variants of frontotemporal dementia

Semantic (svPPA) and nonfluent (nfvPPA) variants of primary progressive aphasia (PPA) have recently been associated with distinct patterns of white matter and functional network alterations in left frontoinsular and anterior temporal regions, respectively. Little information exists, however, about the topological characteristics of gray matter covariance networks in these two PPA variants. In the present study, we used a graph theory approach to describe the structural covariance network organization in 34 patients with svPPA, 34 patients with nfvPPA and 110 healthy controls. All participants underwent a 3 T structural MRI. Next, we used cortical thickness values and subcortical volumes to define subject-specific connectivity networks. Patients with svPPA and nfvPPA were characterized by higher values of normalized characteristic path length compared with controls. Moreover, svPPA patients had lower values of normalized clustering coefficient relative to healthy controls. At a regional level, patients with svPPA showed a reduced connectivity and impaired information processing in temporal and limbic brain areas relative to controls and nfvPPA patients. By contrast, local network changes in patients with nfvPPA were focused on frontal brain regions such as the pars opercularis and the middle frontal cortex. Of note, a predominance of local metric changes was observed in the left hemisphere in both nfvPPA and svPPA brain networks. Taken together, these findings provide new evidences of a suboptimal topological organization of the structural covariance networks in svPPA and nfvPPA patients. Moreover, we further confirm that distinct patterns of structural network alterations are related to neurodegenerative mechanisms underlying each PPA variant.

An integrated machine learning framework for a discriminative analysis of schizophrenia using multi-biological data

Finding effective and objective biomarkers to inform the diagnosis of schizophrenia is of great importance yet remains challenging. Relatively little work has been conducted on multi-biological data for the diagnosis of schizophrenia. In this cross-sectional study, we extracted multiple features from three types of biological data, including gut microbiota data, blood data, and electroencephalogram data. Then, an integrated framework of machine learning consisting of five classifiers, three feature selection algorithms, and four cross validation methods was used to discriminate patients with schizophrenia from healthy controls. Our results show that the support vector machine classifier without feature selection using the input features of multi-biological data achieved the best performance, with an accuracy of 91.7% and an AUC of 96.5% (p < 0.05). These results indicate that multi-biological data showed better discriminative capacity for patients with schizophrenia than single biological data. The top 5% discriminative features selected from the optimal model include the gut microbiota features (Lactobacillus, Haemophilus, and Prevotella), the blood features (superoxide dismutase level, monocyte-lymphocyte ratio, and neutrophil count), and the electroencephalogram features (nodal local efficiency, nodal efficiency, and nodal shortest path length in the temporal and frontal-parietal brain areas). The proposed integrated framework may be helpful for understanding the pathophysiology of schizophrenia and developing biomarkers for schizophrenia using multi-biological data.

Classification of first-episode psychosis using cortical thickness: A large multicenter MRI study

Machine learning classifications of first-episode psychosis (FEP) using neuroimaging have predominantly analyzed brain volumes. Some studies examined cortical thickness, but most of them have used parcellation approaches with data from single sites, which limits claims of generalizability. To address these limitations, we conducted a large-scale, multi-site analysis of cortical thickness comparing parcellations and vertex-wise approaches. By leveraging the multi-site nature of the study, we further investigated how different demographical and site-dependent variables affected predictions. Finally, we assessed relationships between predictions and clinical variables. 428 subjects (147 females, mean age 27.14) with FEP and 448 (230 females, mean age 27.06) healthy controls were enrolled in 8 centers by the ClassiFEP group. All subjects underwent a structural MRI and were clinically assessed. Cortical thickness parcellation (68 areas) and full cortical maps (20,484 vertices) were extracted. Linear Support Vector Machine was used for classification within a repeated nested cross-validation framework. Vertex-wise thickness maps outperformed parcellation-based methods with a balanced accuracy of 66.2% and an Area Under the Curve of 72%. By stratifying our sample for MRI scanner, we increased generalizability across sites. Temporal brain areas resulted as the most influential in the classification. The predictive decision scores significantly correlated with age at onset, duration of treatment, and positive symptoms. In conclusion, although far from the threshold of clinical relevance, temporal cortical thickness proved to classify between FEP subjects and healthy individuals. The assessment of site-dependent variables permitted an increase in the across-site generalizability, thus attempting to address an important machine learning limitation.

Mild traumatic brain injury is associated with dysregulated neural network functioning in children and adolescents.

Mild traumatic brain injury is highly prevalent in paediatric populations, and can result in chronic physical, cognitive and emotional impairment, known as persistent post-concussive symptoms. Magnetoencephalography has been used to investigate neurophysiological dysregulation in mild traumatic brain injury in adults; however, whether neural dysrhythmia persists in chronic mild traumatic brain injury in children and adolescents is largely unknown. We predicted that children and adolescents would show similar dysfunction as adults, including pathological slow-wave oscillations and maladaptive, frequency-specific, alterations to neural connectivity. Using magnetoencephalography, we investigated regional oscillatory power and distributed brain-wide networks in a cross-sectional sample of children and adolescents in the chronic stages of mild traumatic brain injury. Additionally, we used a machine learning pipeline to identify the most relevant magnetoencephalography features for classifying mild traumatic brain injury and to test the relative classification performance of regional power versus functional coupling. Results revealed that the majority of participants with chronic mild traumatic brain injury reported persistent post-concussive symptoms. For neurophysiological imaging, we found increased regional power in the delta band in chronic mild traumatic brain injury, predominantly in bilateral occipital cortices and in the right inferior temporal gyrus. Those with chronic mild traumatic brain injury also showed dysregulated neuronal coupling, including decreased connectivity in the delta range, as well as hyper-connectivity in the theta, low gamma and high gamma bands, primarily involving frontal, temporal and occipital brain areas. Furthermore, our multivariate classification approach combined with functional connectivity data outperformed regional power in terms of between-group classification accuracy. For the first time, we establish that local and large-scale neural activity are altered in youth in the chronic phase of mild traumatic brain injury, with the majority presenting persistent post-concussive symptoms, and that dysregulated interregional neural communication is a reliable marker of lingering paediatric ‘mild’ traumatic brain injury.

Cognitive reserve hypothesis in frontotemporal dementia: A FDG-PET study

Background and objectiveReserve is defined as the ability to maintain cognitive functions relatively well at a given level of pathology. Early life experiences such as education are associated with lower dementia risk in general. However, whether more years of education guards against the impact of brain alterations also in frontotemporal dementia (FTD) has not been shown in a large patient collective. Therefore, we assessed whether education is associated with relatively high cognitive performance despite the presence of [18F]-fluorodeoxyglucose positron-emission-tomography (FDG-PET) hypometabolism in FTD. MethodsSixty-six FTD subjects (age 67 ± 8 years) and twenty-four cognitively healthy controls (HC) were evaluated. Brain regions with FTD-related glucose hypometabolism in the contrast against HC and brain regions that correlate with the cognitive function were defined by a voxel-based analysis and individual FDG-PET values were extracted from all frontotemporal brain areas. Linear regression analysis served to test if education is associated with residualized cognitive performance and regional FDG-PET hypometabolism after controlling for global cognition. ResultsCompared to healthy controls, patients with FTD showed glucose hypometabolism in bilateral frontal and temporal brain areas whereas cognition was only associated with deteriorated glucose metabolism in the left temporal lobe. The education level was significantly correlated with the residualized cognitive performance (residuals from regression analysis between hypometabolism and cognitive function as a quantitative index of reserve) and also negatively correlated with left temporal FDG-PET hypometabolism after controlling for cognition. ConclusionsIn patients with FTD, the education level predicts the existing left temporal FDG-PET hypometabolism at the same cognition level, supporting the cognitive reserve hypothesis in FTD.

Frontal, Parietal, and Temporal Brain Areas Are Differentially Activated When Disambiguating Potential Objects of Joint Attention.

Humans establish joint attention with others by following the other’s gaze. Previous work has suggested that a cortical patch (gaze-following patch, GFP) close to the posterior superior temporal sulcus (pSTS) may serve as a link between the extraction of the other’s gaze direction and the resulting shifts of attention, mediated by human lateral intraparietal area (hLIP). However, it is not clear how the brain copes with situations in which information on gaze direction alone is insufficient to identify the target object because more than one may lie along the gaze vector. In this fMRI study, we tested human subjects on a paradigm that allowed the identification of a target object based on the integration of the other’s gaze direction and information provided by an auditory cue on the relevant object category. Whereas the GFP activity turned out to be fully determined by the use of gaze direction, activity in hLIP reflected the total information needed to pinpoint the target. Moreover, in an exploratory analysis, we found that a region in the inferior frontal junction (IFJ) was sensitive to the total information on the target. An examination of the BOLD time courses in the three identified areas suggests functionally complementary roles. Although the GFP seems to primarily process directional information stemming from the other’s gaze, the IFJ may help to analyze the scene when gaze direction and auditory information are not sufficient to pinpoint the target. Finally, hLIP integrates both streams of information to shift attention to distinct spatial locations.