Frontal Lobe Regions Research Articles

Transcranial blood-brain barrier opening in Alzheimer's disease patients using a portable focused ultrasound system with real-time 2-D cavitation mapping.

Background : Focused ultrasound (FUS) in combination with microbubbles has recently shown great promise in facilitating blood-brain barrier (BBB) opening for drug delivery and immunotherapy in Alzheimer's disease (AD). However, it is currently limited to systems integrated within the MRI suites or requiring post-surgical implants, thus restricting its widespread clinical adoption. In this pilot study, we investigate the clinical safety and feasibility of a portable, non-invasive neuronavigation-guided FUS (NgFUS) system with integrated real-time 2-D microbubble cavitation mapping. Methods : A phase 1 clinical study with mild to moderate AD patients (N = 6) underwent a single session of microbubble-mediated NgFUS to induce transient BBB opening (BBBO). Microbubble activity under FUS was monitored with real-time 2-D cavitation maps and dosing to ensure the efficacy and safety of the NgFUS treatment. Post-operative MRI was used for BBB opening and closure confirmation as well as safety assessment. Changes in AD biomarker levels in both blood serum and extracellular vesicles (EVs) were evaluated, while changes in amyloid-beta (Aβ) load in the brain were assessed through 18F-florbetapir PET. Results : BBBO was achieved in 5 out of 6 subjects with an average volume of 983 ± 626 mm3 following FUS at the right frontal lobe both in white and gray matter regions. The outpatient treatment was completed within 34.8 ± 10.7 min. Cavitation dose significantly correlated with the BBBO volume (R 2 > 0.9, N = 4), demonstrating the portable NgFUS system's capability of predicting opening volumes. The cavitation maps co-localized closely with the BBBO location, representing the first report of real-time transcranial 2-D cavitation mapping in the human brain. Larger opening volumes correlated with increased levels of AD biomarkers, including Aβ42 (R 2 = 0.74), Tau (R 2 = 0.95), and P-Tau181 (R 2 = 0.86), assayed in serum-derived EVs sampled 3 days after FUS (N = 5). From PET scans, subjects showed a lower Aβ load increase in the treated frontal lobe region compared to the contralateral region. Reduction in asymmetry standardized uptake value ratios (SUVR) correlated with the cavitation dose (R 2 > 0.9, N = 3). Clinical changes in the mini-mental state examination over 6 months were within the expected range of cognitive decline with no additional changes observed as a result of FUS. Conclusion : We showed the safety and feasibility of this cost-effective and time-efficient portable NgFUS treatment for BBBO in AD patients with the first demonstration of real-time 2-D cavitation mapping. The cavitation dose correlated with BBBO volume, a slowed increase in pathology, and serum detection of AD proteins. Our study highlights the potential for accessible FUS treatment in AD, with or without drug delivery.

The scalp time-varying network of auditory spatial attention in “cocktail-party” situations

Sound source localization in "cocktail-party" situations is a remarkable ability of the human auditory system. However, the neural mechanisms underlying auditory spatial attention are still largely unknown. In this study, the "cocktail-party" situations are simulated through multiple sound sources and presented through head-related transfer functions and headphones. Furthermore, the scalp time-varying network of auditory spatial attention is constructed using the high-temporal resolution electroencephalogram, and its network properties are measured quantitatively using graph theory analysis. The results show that the time-varying network of auditory spatial attention in "cocktail-party" situations is more complex and partially different than in simple acoustic situations, especially in the early- and middle-latency periods. The network coupling strength increases continuously over time, and the network hub shifts from the posterior temporal lobe to the parietal lobe and then to the frontal lobe region. In addition, the right hemisphere has a stronger network strength for processing auditory spatial information in "cocktail-party" situations, i.e., the right hemisphere has higher clustering levels, higher transmission efficiency, and more node degrees during the early- and middle-latency periods, while this phenomenon disappears and appears symmetrically during the late-latency period. These findings reveal different network patterns and properties of auditory spatial attention in "cocktail-party" situations during different periods and demonstrate the dominance of the right hemisphere in the dynamic processing of auditory spatial information.

Diffusion kurtosis imaging reveals abnormal gray matter and white matter development in some brain regions of children with attention-deficit/hyperactivity disorder.

In this study, we explored the application of diffusion kurtosis imaging (DKI) technology in the brains of children with attention-deficit/hyperactivity disorder (ADHD). Seventy-two children with ADHD and 79 age- and sex-matched healthy controls were included in the study. All children were examined by means of 3D T1-weighted image, DKI, and conventional sequence scanning. The volume and DKI parameters of each brain region were obtained by software postprocessing (GE ADW 4.6 workstation) and compared between the two groups of children to determine the imaging characteristics of children with ADHD. The result showed the total brain volume was lower in children with ADHD than in healthy children (p < .05). The gray and white matter volumes in the frontal lobe, temporal lobe, hippocampus, caudate nucleus, putamen, globus pallidus, and other brain regions were lower in children with ADHD than in healthy children (p < .05). The axial kurtosis (Ka), mean kurtosis (MK), fractional anisotropy (FA), and radial kurtosis(Kr) values in the frontal lobe, temporal lobe, and caudate nucleus of children with ADHD were lower than those of healthy children, while the mean diffusivity(MD) and fractional anisotropy of kurtosis (FAK) values were higher than those of healthy children (p < .05). Additionally, the Ka, MK, FA, and Kr values in the frontal lobe, caudate nucleus, and temporal lobe could be used to distinguish children with ADHD (AUC > .05, p < .05). In conclusion, DKI showed abnormal gray matter and white matter development in some brain regions of children with ADHD.

Generalized Calibrated BOLD fMRI for the Relationship between Cerebral Metabolism and Hypertensive Status

AbstractBackgroundElevated blood pressure levels during mid‐life have been found to be associated with an increased susceptibility to developing dementia later in life, particularly vascular dementia. Quantitative imaging biomarkers, such as Oxygen Extraction Fraction (OEF) and Cerebral Metabolism Rate of Oxygen (CMRO2), can be indicators of impaired cerebral metabolism. Calibrated Blood Oxygen Level Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) is a multi‐parametric approach utilizing hyperoxic and hypercapnic gas challenges (Figure 1). The impact of hypertension on OEF and CMRO2 has been investigated.MethodA cohort of 84 participants was recruited from the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core (Table 1). Among all the covariates, participants with prediabetes and diabetes were considered diabetic, and those who exhibited high blood pressure or were using medication to manage hypertension were classified as hypertensive. The MRI was conducted using a 3T Siemens Skyra MRI scanner with a 32‐channel head coil. Dynamic Pseudocontinuous Arterial Spin Labeling (PCASL) was used to acquire cerebral blood flow (CBF) and BOLD images during respiratory challenges with an end‐tidal forcing system. The ROI values in the frontal lobe, temporal lobe, parietal lobe, and occipital lobe regions were chosen. The correlation between hypertensive status and OEF and CMRO2 in the ROI was analyzed with a linear mixed model, with covariates of age, sex, cognitive status, APOE genotype, diabetic status, and hypertensive status.ResultA negative correlation was found between CBF, OEF, and CMRO2 with hypertensive status in frontal lobe region (Figure 2). Statistical significance was observed for OEF and CMRO2 (p = 0.049 and p = 0.028, respectively), indicating the potential influence of hypertensive status on these biomarkers.ConclusionThe study concludes that there is a significant negative association between hypertensive status and both OEF and CMRO2, particularly in the frontal lobe region. The observed reduction in OEF and CMRO2 is not solely due to decreased CBF, but rather complex and multifactorial processes involving vascular remodeling and altered oxygen metabolism. Additional research is necessary to fully understand the underlying pathophysiological mechanisms that link hypertension to decreased OEF and CMRO2, particularly in the context of regional specificity.

Graph Theory Analysis of Structural Connectivity in Limbic‐predominant Age‐related TDP‐43 Encephalopathy Neuropathological Change (LATE‐NC)

AbstractBackgroundThe anatomical distribution of limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC) typically involves the amygdala, hippocampus, and other subcortical, temporal and frontal lobe regions. But its impact on the structural integrity of this network of regions remains unknown. In this study, we tested the hypothesis that LATE‐NC is associated with abnormalities in graph theoretic measures of structural connectivity in the network of regions known to be involved in LATE‐NC.MethodThis study included 148 deceased older adults participating in Rush Memory and Aging Project and Religious Orders Study (Fig.1A). Ex‐vivo diffusion tensor imaging (DTI) scans were acquired on 3T scanners, followed by detailed neuropathologic examination by a board‐certified neuropathologist (Fig.1B). Fractional anisotropy (FA) maps derived from DTI scans were used to define region‐to‐region structural connectivity in a network of 19 regions known to be involved in LATE‐NC using graph theory‐based network measures (Fig.2). General linear models were used to investigate the association of global and local graph measures with LATE‐NC stages, controlling for other neuropathologies (Alzheimer’s disease, Lewy bodies, arteriolosclerosis, atherosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts), demographics (age at death, sex, education), total white matter hyperintensity volume, postmortem intervals and scanner variables. Statistical significance was set at p&lt;0.05.ResultLinear regression revealed that greater LATE‐NC stage was associated with increased characteristic path length and with lower values of the remaining global network measures (p&lt;0.05) (Fig.3A). LATE‐NC was also associated with lower local efficiency, increased path length, lower nodal strength, and lower clustering coefficient in 74%, 79%, 32%, and 63% of the nodes, respectively (p&lt;0.05) (Fig.3B). Finally, LATE‐NC was associated with both greater (in 21% of nodes) and lower (in 16% of nodes) eigenvector centrality, and with both greater and lower betweenness centrality in 21% of nodes, respectively (p&lt;0.05) (Fig.3B).ConclusionUsing graph theory and a hypothesis‐driven approach, we found significant degradation of structural integrity in white matter of the network of regions affected by LATE‐NC. These findings may shed light on the effects of LATE‐NC on brain connectivity, and in combination with other imaging and clinical information, may aid towards the development of tools for in‐vivo detection of this devastating neuropathology.

Psychological characteristics and emotional difficulties underlying school refusal in adolescents using functional near-infrared spectroscopy

BackgroundThis study aims to explore the psychological characteristics, related emotional problems and potential NIR brain function mechanism of adolescents who refuse to attend school.MethodsThe study included 38 adolescents (12–18 years old) who were not attending school and 35 healthy controls (12–18 years old) who are attending school regularly. Participants completed (1) general demographics, (2) Eysenck Personality Questionnaire (EPQ), (3) Zung Self-Rating Depression Scale (SDS), (4) Zung Self-Rating Anxiety Scale (SAS), and (5) Symptom Checklist-90 (SCL-90). In addition to the clinical tests, participants completed functional near-infrared spectroscopy (fNIRS). Mental health, personality, and emotional state were evaluated in both groups to explore the differences and to understand the underlying mechanisms of school refusal during adolescence.ResultsAdolescents who did not attend school had higher neuroticism scores on the Eysenck Personality Questionnaire than healthy controls (p(FDR) < 0.001), introversion and concealment scores were lower than those of healthy controls (p(FDR) < 0.001), there was no significant difference in psychoticism scores between groups. SDS, SAS, SCL-90 scores and factor scores were higher than those of healthy control group (p(FDR) < 0.001), NIR functional brain imaging was different from healthy control group in the 12 and 27 channels (p(FDR) = 0.030, p(FDR) = 0.018), and no difference was found in the remaining channels (p(FDR) > 0.05). There were statistically significant differences in age and gender between the adolescents who refused school and the control group (p(FDR) < 0.001).ConclusionSchool refusal adolescents are relatively introverted and sensitive and need more attention in daily life. Although the adolescents’ emotional problems did not reach the diagnostic criteria of depressive disorder and anxiety disorder, their scores were still higher than those of the control group, suggesting that we should pay more attention to their emotional problems in order to better help them return to school. Using fNIRS, it was found that abnormalities in frontal lobe regions in adolescents with school refusal behaviors, which would contribute to early diagnosis and timely intervention of school refusal behaviors.

Graph Theory Analysis of Structural Connectivity in Limbic‐predominant Age‐related TDP‐43 Encephalopathy Neuropathological Change (LATE‐NC)

AbstractBackgroundThe anatomical distribution of limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC) typically involves the amygdala, hippocampus, and other subcortical, temporal and frontal lobe regions. But its impact on the structural integrity of this network of regions remains unknown. In this study, we tested the hypothesis that LATE‐NC is associated with abnormalities in graph theoretic measures of structural connectivity in the network of regions known to be involved in LATE‐NC.MethodThis study included 148 deceased older adults participating in Rush Memory and Aging Project and Religious Orders Study (Fig.1A). Ex‐vivo diffusion tensor imaging (DTI) scans were acquired on 3T scanners, followed by detailed neuropathologic examination by a board‐certified neuropathologist (Fig.1B). Fractional anisotropy (FA) maps derived from DTI scans were used to define region‐to‐region structural connectivity in a network of 19 regions known to be involved in LATE‐NC using graph theory‐based network measures (Fig.2).General linear models were used to investigate the association of global and local graph measures with LATE‐NC stages, controlling for other neuropathologies (Alzheimer’s disease, Lewy bodies, arteriolosclerosis, atherosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts), demographics (age at death, sex, education), total white matter hyperintensity volume, postmortem intervals and scanner variables. Statistical significance was set at p&lt;0.05.ResultLinear regression revealed that greater LATE‐NC stage was associated with increased characteristic path length and with lower values of the remaining global network measures (p&lt;0.05) (Fig.3A). LATE‐NC was also associated with lower local efficiency, increased path length, lower nodal strength, and lower clustering coefficient in 74%, 79%, 32%, and 63% of the nodes, respectively (p&lt;0.05) (Fig.3B). Finally, LATE‐NC was associated with both greater (in 21% of nodes) and lower (in 16% of nodes) eigenvector centrality, and with both greater and lower betweenness centrality in 21% of nodes, respectively (p&lt;0.05) (Fig.3B).ConclusionUsing graph theory and a hypothesis‐driven approach, we found significant degradation of structural integrity in white matter of the network of regions affected by LATE‐NC. These findings may shed light on the effects of LATE‐NC on brain connectivity, and in combination with other imaging and clinical information, may aid towards the development of tools for in‐vivo detection of this devastating neuropathology.

Associations Between Social Network Characteristics and Brain Structure Among Older Adults.

Social connectedness is associated with slower cognitive decline among older adults. Recent research suggests that distinct aspects of social networks may have differential effects on cognitive resilience, but few studies analyze brain structure. This study includes 117 cognitively impaired and 59 unimpaired older adults. The effects of social network characteristics (bridging/bonding) on brain regions of interests were analyzed using linear regressions and voxel-wise multiple linear regressions of gray matter density. Increased social bridging was associated with greater bilateral amygdala volume and insular thickness, and left frontal lobe thickness, putamen, and thalamic volumes. Increased social bonding was associated with greater bilateral medial orbitofrontal and caudal anterior cingulate thickness, as well as right frontal lobe thickness, putamen, and amygdala volumes. The associations between social connectedness and brain structure vary depending on the types of social enrichment accessible through social networks, suggesting that psychosocial interventions could mitigate neurodegeneration. Distinct forms of social capital are uniquely linked to gray matter density (GMD). Bridging is associated with preserved GMD in limbic system structures. Bonding is associated with preserved GMD in frontal lobe regions. Bridging is associated with increased brain reserve in sensory processing regions. Bonding is associated with increased brain reserve in regions of stress modulation.

Supershear Rayleigh wave imaging for quantitative assessment of biomechanical properties of brain using air-coupled optical coherence elastography.

Recently, supershear Rayleigh waves (SRWs) have been proposed to characterize the biomechanical properties of soft tissues. The SRWs propagate along the surface of the medium, unlike surface Rayleigh waves, SRWs propagate faster than bulk shear waves. However, their behavior and application in biological tissues is still elusive. In brain tissue elastography, shear waves combined with magnetic resonance elastography or ultrasound elastography are generally used to quantify the shear modulus, but high spatial resolution elasticity assessment in 10 μm scale is still improving. Here, we develop an air-coupled ultrasonic transducer for noncontact excitation of SRWs and Rayleigh waves in brain tissue, use optical coherent elastography (OCE) to detect, and reconstruct the SRW propagation process; in combing with a derived theoretical model of SRWs on a free boundary surface, we quantify the shear modulus of brain tissue with high spatial resolution. We first complete validation experiments using a homogeneous isotropic agar phantom, and the experimental results clearly show the SRW is 1.9649 times faster than the bulk shear waves. Furthermore, the propagation velocity of SRWs in both the frontal and parietal lobe regions of the brain is all 1.87 times faster than the bulk shear wave velocity. Finally, we evaluated the anisotropy in different brain regions, and the medulla oblongata region had the highest anisotropy index. Our study shows that the OCE system using the SRW model is a new potential approach for high-resolution assessment of the biomechanical properties of brain tissue.

Study of blood supply to functional brain areas under memory load based on bioimpedance technology

The cerebral blood supply is crucial for normal brain function. This paper aims to detect and describe alterations in blood supply within functional brain regions during working memory (WM), utilizing bioimpedance technology. Methods: We propose a bioimpedance-based method to detect blood supply to functional brain regions. We introduce the impedance systolic wave height and the impedance rise time to characterize cerebral blood flow (CBF) and small artery vasodilation velocity in functional regions. Lastly, we explore blood supply to frontal lobe regions by utilizing changes in impedance parameters under WM loads. Results: Under low WM load, frontal lobe impedance systolic wave height increased by 0.0051–0.0084 Ω, CBF increased by 14.42–22.24 %, impedance rise time decreased by 0.0332–0.0441 s, and small artery vasodilation velocity increased by 9.80–14.36 %. Under high WM load, the impedance systolic wave height increased by 0.0062–0.0104 Ω, CBF increased by 18.62–30.98 %, impedance rise time decreased by 0.0370–0.0597 s, and small artery vasodilation velocity increased by 12.17–19.42 %. Differences in blood supply between the bilateral frontal lobes due to different WM loads and division of labor between brain regions. Conclusion: The bioimpedance technique is effective in detecting blood supply changes in functional brain regions and quantifying CBF and small artery vasodilation velocity by impedance systolic wave height and impedance rise time, which reveal the differences in blood supply in functional brain regions. The method proposed in this paper provides more information for the study of blood supply in functional brain regions and lays the foundation for further research on bioimpedance detection of brain function.

Research on pathfinding cognition in complex underground public space utilizing eye movement and EEG synchronous detection

The complex underground public space brings challenge on pathfinding cognition. This research took Luoxiong Road Station in Wuhan as experimental site, using eye movement and electroencephalogram (EEG) synchronous detection, through pathway analysis and space-time fault method, exploring relationship between pathfinding cognition and complex underground public space. It was found that pathfinding habits and pathfinding decision-making were mainly affected by personal factors and environmental factors, respectively. Pathfinders influenced by personal factors, had behaviors such as left-walking or right-walking tendency, and the ratio of brain wave β/α was low (impression ratio ≤1). Pathfinders influenced by environmental factors, interested in the other side situation, vertical traffic and so on, and the ratio of brain wave β/α was high (impression ratio >1), with the frontal and parietal occipital lobe regions of brain being more active. These conclusions provided theoretical and data supplements for underground rail transit environment optimizing design in future.

Resolving heterogeneity in Alzheimer's disease based on individualized structural covariance network

The heterogeneity of Alzheimer's disease (AD) poses a challenge to precision medicine. We aimed to identify distinct subtypes of AD based on the individualized structural covariance network (IDSCN) analysis and to research the underlying neurobiology mechanisms. In this study, 187 patients with AD (age = 73.57 ± 6.00, 50% female) and 143 matched normal controls (age = 74.30 ± 7.80, 44% female) were recruited from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project database, and T1 images were acquired. We utilized the IDSCN analysis to generate individual-level altered structural covariance network and performed k-means clustering to subtype AD based on structural covariance network. Cognition, disease progression, morphological features, and gene expression profiles were further compared between subtypes, to characterize the heterogeneity in AD. Two distinct AD subtypes were identified in a reproducible manner, and we named the two subtypes as slow progression type (subtype 1, n = 104, age = 76.15 ± 6.44, 42% female) and rapid progression type (subtype 2, n = 83, age = 71.98 ± 8.72, 47% female), separately. Subtype 1 had better baseline visuospatial function than subtype 2 (p < 0.05), whereas subtype 2 had better baseline memory function than subtype 1 (p < 0.05). Subtype 2 showed worse progression in memory (p = 0.003), language (p = 0.003), visuospatial function (p = 0.020), and mental state (p = 0.038) than subtype 1. Subtype 1 often shared increased structural covariance network, mainly in the frontal lobe and temporal lobe regions, whereas subtype 2 often shared increased structural covariance network, mainly in occipital lobe regions and temporal lobe regions. Functional annotation further revealed that all differential structural covariance network between the two AD subtypes were mainly implicated in memory, learning, emotion, and cognition. Additionally, differences in gray matter volume (GMV) between AD subtypes were identified, and genes associated with GMV differences were found to be enriched in the terms potassium ion transport, synapse organization, and histone modification and the pathways viral infection, neurodegeneration-multiple diseases, and long-term depression. The two distinct AD subtypes were identified and characterized with neuroanatomy, cognitive trajectories, and gene expression profiles. These comprehensive results have implications for neurobiology mechanisms and precision medicine.

A - 34 A Suspected Case of Early-Onset Frontal Variant of Alzheimer's Disease in a 64-Year-Old Male.

Early-onset frontal variant of Alzheimer's disease (fvAD) is characterized by apathy, disinhibition, and executive dysfunction. As such, fvAD is often difficult to clinically distinguish from behavioral variant frontotemporal dementia (bvFTD). However, research suggests that a differentiating feature among the two conditions is that fvAD typically presents with more pronounced memory impairment. Therefore, neuropsychological testing in the context of a comprehensive multidisciplinary assessment can be a valuable tool to aid with differential diagnosis. A 64-year-old male with gradually progressive difficulties in cognition and behavioral-emotional functioning over the past 8-9years presented to a multidisciplinary neurology clinic. MRI showed mild atrophy in the frontal, temporal, and parietal lobe regions. Concerns were raised by his neurologist for early-onset ad versus bvFTD so the patient was referred for neuropsychological evaluation. Neuropsychological testing showed a largely amnestic memory profile along with deficits in executive functioning and semantic fluency. His spouse endorsed concerns for apathy and executive dysfunction on a frontal system rating questionnaire in addition to concerns for disinhibition during the clinical interview. Taken together, the patient's profile appeared to be consistent with early-onset fvAD. Follow-up FDG-PET scan showed decreased uptake in the anteromesial temporal lobes, posterior cingulate cortices, and posterior temporoparietal regions which was consistent with an ad profile. Early-onset fvAD and bvFTD are often difficult to clinically distinguish from each other. However, neuropsychological testing in conjunction with comprehensive multidisciplinary assessment can serve an important role in helping to facilitate differential diagnosis for these two neurodegenerative disorders with overlapping features.

ADHD-related sex differences in frontal lobe white matter microstructure and associations with response control under conditions of varying cognitive load and motivational contingencies.

Children with attention-deficit/hyperactivity disorder (ADHD) demonstrate reduced response inhibition, increased response time variability, and atypical frontal lobe white matter microstructure with emerging evidence of sex differences. This study aims to examine whether frontal lobe white matter microstructure is differentially impacted in ADHD by sex and whether this relates to Go/No-Go (GNG) task performance. Diffusion tensor imaging (DTI) from 187 children (8-12 years), including ADHD (n = 94) and typically developing controls (TD; n = 93). Participants completed three GNG tasks with varying cognitive demands and incentives (standard, cognitive, and motivational). Fractional anisotropy (FA) was examined as an index of white matter microstructure within bilateral frontal lobe regions of interest. Children with ADHD showed reduced FA in primary motor (M1) and supplementary motor area (SMA) regardless of sex. Sex-based dissociation for the effect of diagnosis was observed in medial orbitofrontal cortex (mOFC), with higher FA in girls with ADHD and lower FA in boys with ADHD. Both diagnosis and sex contributed to performance on measures of response inhibition and reaction time (RT) variability, with all children with ADHD demonstrating poorer performance on all GNG tasks, but boys with ADHD demonstrating more impulsivity on standard and motivational behavioral paradigms compared to girls with ADHD. Analyses revealed associations between reduced FA in M1, SMA, and mOFC and increased response inhibition and RT variability with some sex-based differences. These findings provide novel insights regarding the brain basis of ADHD and associated impairments in response inhibition and RT variability, and contribute to our understanding of sexual dimorphic behavioral outcomes.

Distinct Lateral Prefrontal Regions Are Organized in an Anterior-Posterior Functional Gradient.

The dorsolateral prefrontal cortex (dlPFC) is composed of multiple anatomically defined regions involved in higher-order cognitive processes, including working memory and selective attention. It is organized in an anterior-posterior global gradient where posterior regions track changes in the environment, whereas anterior regions support abstract neural representations. However, it remains unknown if such a global gradient results from a smooth gradient that spans regions or an emergent property arising from functionally distinct regions, that is, an areal gradient. Here, we recorded single neurons in the dlPFC of nonhuman primates trained to perform a memory-guided saccade task with an interfering distractor and analyzed their physiological properties along the anterior-posterior axis. We found that these physiological properties were best described by an areal gradient. Further, population analyses revealed that there is a distributed representation of spatial information across the dlPFC. Our results validate the functional boundaries between anatomically defined dlPFC regions and highlight the distributed nature of computations underlying working memory across the dlPFC.SIGNIFICANCE STATEMENT Activity of frontal lobe regions is known to possess an anterior-posterior functional gradient. However, it is not known whether this gradient is the result of individual brain regions organized in a gradient (like a staircase), or a smooth gradient that spans regions (like a slide). Analysis of physiological properties of individual neurons in the primate frontal regions suggest that individual regions are organized as a gradient, rather than a smooth gradient. At the population level, working memory was more prominent in posterior regions, although it was also present in anterior regions. This is consistent with the functional segregation of brain regions that is also observed in other systems (i.e., the visual system).

Anatomical predictors of need for decompressive craniectomy after stroke using voxel-based lesion symptom mapping.

Malignant cerebral edema (MCE) secondary to ischemic stroke is a highly morbid condition. Decompressive craniectomy (DC) is the only treatment for MCE that has been shown to reduce mortality. We examined whether early infarction and/or hypoperfusion in specific topographic regions was predictive of the need for later DC. A retrospective database of patients evaluated for large vessel occlusion (LVO) stroke at Stanford between 2010 and 2019 was used. Thirty patients with LVO and baseline perfusion MRI who underwent DC were evaluated. Propensity matching based on age, lesion size, and recanalization status was performed on the remaining cohort. Baseline masks of apparent diffusion coefficient (ADC)+Tmax >6seconds lesions were generated using automated perfusion software. Voxel-based lesion symptom maping was used to perform logistic regression at each voxel to generate statistical maps of lesion location associated with DC. Hemispheres were combined to increase statistical power. Sixty patients were analyzed. After adjusting for age, lesion size, and recanalization status as covariates, scattered cortical regions, predominately within the temporal and frontal lobe, were mildly to moderately predictive of the need for DC (z-scores: 2.4-6.74, p<.01). Scattered temporal and frontal lobe regions on baseline diffusion and perfusion MRI were found to be mildly to moderately predictive of the need for subsequent DC in patients with LVO stroke.

Anatomical and radiological evaluation of frontal lobe morphometry in healthy and dementia people and machine learning-based prediction of dementia

Purpose: This paper aimed to determine the morphometry of the frontal lobe and central brain region using magnetic resonance imaging in patients having dementia and healthy subjects. &#x0D; Materials and Methods: 243 subjects (121 subjects having dementia; 122 subjects healthy group) aged 60-90 years over for 2 years between January 2018 and 2020 were included in this study. Also, the supervised Machine learning based (ML based) detection of dementia has been studied on this obtained real world data.&#x0D; Results: The gender-related changes of frontal region measurements in dementia and healthy subjects were analyzed and, there were differences of measurements’ mean values in gender. In healthy subjects, significance differences were found in all measurements (except the distance from anterior commissure to posterior commissure and outermost of corpus callosum genu to innermost of corpus callosum genu). The means of the measurements were found higher in males than in females.&#x0D; Conclusions: We believe that the knowledge of our study will provide valuable reference data for our population and will help for a surgeon in planning an operation by considering measurements related to the frontal lobe. In addition, ML based supervised methods that were trained on the collected data for detection of dementia showed that it is required to provide as many attributes and instances as possible to train an accurate estimator. However, if this is not possible, by creating new features based on the hidden patterns between attributes and instances we could increase the success of the estimators up to 96.3% f-score value.

Exploring the association between tau‐PET and Aβ‐amyloid Centiloid value using deep learning

AbstractBackgroundThe study of how extracellular Aβ‐amyloid (Aβ) drives intracellular, heterogeneous tau accumulation in Alzheimer’s disease has been approached using linear models under an implicit assumption of regionally independent tau accumulation (Lockhart et al, 2017; Iaccarino et al, 2017). Multivariate, non‐linear models which enable relaxation of this assumption can be used; we employed a convolutional neural network (CNN) to identify critical tau topographic changes associated with Aβ‐burden in a cohort with a range of Aβ values, and compared results with linear analyses.Method134 subjects with [NAV4694 (Aβ) and [MK6240 (tau) scans were considered. A CNN was trained to map normalised tau (input) to Aβ Centiloid values (CL). CNN models were interpreted using saliency maps, denoting the importance of corresponding voxels to the output. The CNN approach was compared with linear analysis by testing the following voxel‐wise models: estimating tau SUVR from Aβ CL, and saliency from Aβ CL. All models were tested with minimum cluster extent of 200 after controlling for age and sex. Occlusion analysis was used to assess the importance of CNN‐identified salient clusters, which quantified the change in output after removing salient clusters from the input tau images.ResultThe Aβ CL values were well predicted by tau topography using the CNN (training R2 = 0.86, validation R2 = 0.75, testing R2 = 0.72). Linear analysis identified widespread correlation between Aβ CL and tau‐SUVR in the brain, while CNN analysis demonstrated focal clusters in frontal lobes, middle cingulate, precuneus, postcentral gyrus and bilateral medial temporal lobes. At low Aβ levels, information from the frontal lobe, middle cingulate and precuneus regions was more predictive of Aβ CL while the information from medial temporal lobes was more predictive of high Aβ levels.ConclusionThe nonlinear data‐driven CNN approach, relaxing the assumption of independent regional tau accumulation, has revealed new associations between tau topography and Aβ burden.

Identification of autism spectrum disorder based on functional near-infrared spectroscopy using adaptive spatiotemporal graph convolution network.

The accurate diagnosis of autism spectrum disorder (ASD) is of great practical significance in clinical practice. The spontaneous hemodynamic fluctuations were collected by functional near-infrared spectroscopy (fNIRS) from the bilateral frontal and temporal cortices of typically developing (TD) children and children with ASD. Since traditional machine learning and deep learning methods cannot make full use of the potential spatial dependence between variable pairs, and require a long time series to diagnose ASD. Therefore, we use adaptive spatiotemporal graph convolution network (ASGCN) and short time series to classify ASD and TD. To capture spatial and temporal features of fNIRS multivariable time series without the pre-defined graph, we combined the improved adaptive graph convolution network (GCN) and gated recurrent units (GRU). We conducted a series of experiments on the fNIRS dataset, and found that only using 2.1 s short time series could achieve high precision classification, with an accuracy of 95.4%. This suggests that our approach may have the potential to detect pathological signals in autism patients within 2.1 s. In different brain regions, the left frontal lobe has the best classification effect, and the abnormalities occur more frequently in left hemisphere and frontal lobe region. Moreover, we also found that there were correlations between multiple channels, which had different degrees of influence on the classification of ASD. From this, we can also generalize to a wider range, there may be potential correlations between different brain regions. This may help to better understand the cortical mechanism of ASD.

Dynamic cortical and tractography atlases of proactive and reactive alpha and high-gamma activities.

Alpha waves-posterior dominant rhythms at 8-12 Hz reactive to eye opening and closure-are among the most fundamental EEG findings in clinical practice and research since Hans Berger first documented them in the early 20th century. Yet, the exact network dynamics of alpha waves in regard to eye movements remains unknown. High-gamma activity at 70-110 Hz is also reactive to eye movements and a summary measure of local cortical activation supporting sensorimotor or cognitive function. We aimed to build the first-ever brain atlases directly visualizing the network dynamics of eye movement-related alpha and high-gamma modulations, at cortical and white matter levels. We studied 28 patients (age: 5-20 years) who underwent intracranial EEG and electro-oculography recordings. We measured alpha and high-gamma modulations at 2167 electrode sites outside the seizure onset zone, interictal spike-generating areas and MRI-visible structural lesions. Dynamic tractography animated white matter streamlines modulated significantly and simultaneously beyond chance, on a millisecond scale. Before eye-closure onset, significant alpha augmentation occurred at the occipital and frontal cortices. After eye-closure onset, alpha-based functional connectivity was strengthened, while high gamma-based connectivity was weakened extensively in both intra-hemispheric and inter-hemispheric pathways involving the central visual areas. The inferior fronto-occipital fasciculus supported the strengthened alpha co-augmentation-based functional connectivity between occipital and frontal lobe regions, whereas the posterior corpus callosum supported the inter-hemispheric functional connectivity between the occipital lobes. After eye-opening offset, significant high-gamma augmentation and alpha attenuation occurred at occipital, fusiform and inferior parietal cortices. High gamma co-augmentation-based functional connectivity was strengthened, whereas alpha-based connectivity was weakened in the posterior inter-hemispheric and intra-hemispheric white matter pathways involving central and peripheral visual areas. Our results do not support the notion that eye closure-related alpha augmentation uniformly reflects feedforward or feedback rhythms propagating from lower to higher order visual cortex, or vice versa. Rather, proactive and reactive alpha waves involve extensive, distinct white matter networks that include the frontal lobe cortices, along with low- and high-order visual areas. High-gamma co-attenuation coupled to alpha co-augmentation in shared brain circuitry after eye closure supports the notion of an idling role for alpha waves during eye closure. These normative dynamic tractography atlases may improve understanding of the significance of EEG alpha waves in assessing the functional integrity of brain networks in clinical practice; they also may help elucidate the effects of eye movements on task-related brain network measures observed in cognitive neuroscience research.