Posterior Temporal Lobe Research Articles

Assessment of arousal recovery after cardiac arrest using diffusion kurtosis MRI with higher b-values: a pilot study

ABSTRACT Objective Comatose survivors of cardiac arrest (CA) pose a complex challenge for physicians reliant on imperfect studies to determine the extent of neurologic injury. Clinically available imaging is frequently relied upon despite limited sensitivity. We conducted a prospective pilot study comparing diffusion kurtosis imaging (DKI)-MRI and somatosensory evoked potentials (SSEPs) in comatose survivors of CA to investigate the benefit of utilizing higher diffusion b-values to enhance prediction of arousal recovery. Methods Survivors of CA admitted from June 2015 through November 2019 with DKI-MRI and SSEPs were evaluated. Advanced diffusion metrics differentiating present or absent SSEPs were analyzed using whole-brain voxelwise nonparametric permutation inference with threshold-free cluster enhancement. Results Twenty survivors of CA were included, mean age 52, 45% female and out-of-hospital arrests accounting for 75% of cases. Baseline characteristics and examination findings were not statistically different between groups at admission or 48 h after achieving normothermia. A decrease in mean diffusivity (MD) and increase in mean kurtosis (MK) was demonstrated in subjects without arousal recovery potential, most prominently in the posterior mesial temporal, parietal and occipital lobes. Conclusion DKI-MRI may improve early arousal recovery prediction during the immediate phase of post-CA care, especially where SSEPs are unavailable or unreliable.

Intracranial pleomorphic liposarcoma misclassified as a pleomorphic xanthoastrocytoma by a DNA methylation classifier: illustrative case.

Recently, it has been shown that DNA methylation arrays and German Cancer Research Center (Deutsches Krebsforschungszentrum) methylation classifiers are useful aids in brain tumor diagnosis for cases in which histopathological diagnosis is difficult. However, not enough is known about diagnostic aids for intracranial liposarcoma (LPS). An 18-year-old woman with a history of natural killer/T-cell lymphoma, which had been treated with a bone marrow transplant and total body irradiation at age 11 years, presented with diplopia. Magnetic resonance imaging revealed a brain tumor in the posterior left temporal lobe, which was removed by craniotomy. The tumor was initially diagnosed as pleomorphic xanthoastrocytoma through histopathological and DNA methylation examination. She also had a soft tissue tumor in her left thigh, which was removed. It contained spindle cells with oval nuclei and highly pleomorphic cells and was diagnosed as radiation-induced LPS. Histopathological re-examination of the brain tumor led to a final diagnosis of pleomorphic LPS. In this report, the authors describe the case of a patient with an intracranial pleomorphic LPS that was initially classified as a pleomorphic xanthoastrocytoma by a DNA methylation classifier. Although DNA methylation classifiers are useful as diagnostic aids in cases in which definitive pathology is difficult to determine, there is a risk of misdiagnosis in some types of tumors. https://thejns.org/doi/10.3171/CASE24465.

Connectivity of Fronto-Temporal Regions in Syntactic Structure Building During Speaking and Listening.

The neural infrastructure for sentence production and comprehension has been found to be mostly shared. The same regions are engaged during speaking and listening, with some differences in how strongly they activate depending on modality. In this study, we investigated how modality affects the connectivity between regions previously found to be involved in syntactic processing across modalities. We determined how constituent size and modality affected the connectivity of the pars triangularis of the left inferior frontal gyrus (LIFG) and of the left posterior temporal lobe (LPTL) with the pars opercularis of the LIFG, the left anterior temporal lobe (LATL), and the rest of the brain. We found that constituent size reliably increased the connectivity across these frontal and temporal ROIs. Connectivity between the two LIFG regions and the LPTL was enhanced as a function of constituent size in both modalities, and it was upregulated in production possibly because of linearization and motor planning in the frontal cortex. The connectivity of both ROIs with the LATL was lower and only enhanced for larger constituent sizes, suggesting a contributing role of the LATL in sentence processing in both modalities. These results thus show that the connectivity among fronto-temporal regions is upregulated for syntactic structure building in both sentence production and comprehension, providing further evidence for accounts of shared neural resources for sentence-level processing across modalities.

Utilization of Artificial Intelligence to Improve Door-In Door-Out Times for Mechanical Thrombectomy-Eligible Patients at a Hub-and-Spoke Community-Based Comprehensive Stroke Center: A Single Case Study Presentation

Background: Delays in the transfer of patients with hyperacute stroke may lead to treatment ineligibility due to the degree of cerebral hypoxic injury suffered. Cloud-based artificial intelligence applications may improve transfer times and expand access to advanced therapies. One case between a community-based comprehensive stroke center (CSC) and a primary stroke center (PSC) using a third-party telemedicine service and shared cloud-based artificial intelligence application may provide insight in opportunities to improve stroke systems of care. Case Presentation: A 62-year-old female with a past medical history of hypertension, current everyday tobacco smoker, and marijuana user presented to an outlying emergency department (ED) with dense left-sided hemiplegia affecting the arm and leg, right-sided gaze preference, and severe dysarthria. Her last known well (LKW) time was 0900 hours. CNS imaging revealed a right middle cerebral artery occlusion, visible to members of the CSC stroke team through the use of a cloud-based artificial intelligence cell phone application. The patient was treated with intravenous thrombolytics at the PSC, and she was transferred to the CSC, where she underwent a diagnostic cerebral arteriogram with carotid artery stenting. Later, Magnetic Resonance Imaging (MRI) of the brain revealed a 3.5 cm x 2.5 cm hemorrhagic lesion in the right frontal lobe and diffusion restriction in the right frontal and right posterior temporal lobes. The patient’s hospital stay was three days and, at the time of discharged, her modified Rankin score and NIHSS were zero. She was discharged on dual antiplatelet therapy, statin therapy, and nicotine replacement. Utilization of Artificial Intelligence: Transfer delays are complicated by organizing care at PSC and CSC and can be lengthy when communication across different facilities and subspecialties. Implementing cloud-based AI image sharing in stroke systems of care has reduced DIDO times by providing rapid imaging interpretation, streamlining communication, and enhancing coordination between PSCs and CSCs. Conclusions: Our case presentation showed how a hub-and-spoke model combined with cloud-based AI utilization can improve DIDO times and enhance stroke systems of care.

Abstract We127: Infective Endocarditis in COVID-19 - An Unusual Suspect

Introduction: The COVID-19 pandemic globally overwhelmed healthcare systems and the complications associated with this illness have contributed to poor outcomes. The hypercoagulable state associated with COVID-19 is well recognized in the literature. Thromboembolic complications such as left ventricular thrombus (LVT), deep venous thrombosis (DVT) and pulmonary embolism (PE) have been increasingly reported. Dhakal et al. published an association between COVID-19 and cardiovascular disease, including possible complication by infective endocarditis (IE) which was confirmed by Amir et al. reporting the first case. Since then, there have been few reported cases. We present a case of COVID-19 in a patient who developed LVT, complicated by non-valvular IE by an underreported organism, Granulicatella adiacens. Case Presentation: A 55-year-old male with history of dental caries, provoked DVT/PE, NSTEMI x2 and STEMI in-stent restenosis requiring thrombectomy presented to the hospital with a 2-day history of shortness of breath, fatigue, cough, change in mentation and right-sided weakness. He tested positive for COVID-19 by NAAT. CXR revealed cardiomegaly and multiple bilateral infiltrates. CT head demonstrated acute ischemic stroke of the left occipital, parietal and posterior temporal lobes, also confirmed on MRI. CTA neck showed 30% stenosis of left ICA. Blood cultures x2 resulted positive for G. adiacens. Echocardiogram was obtained, demonstrating reduced EF of 35% and the presence of a large, 2.7 x 2.2cm mobile thrombus in the apical-septal region of the left ventricle, not visualized on previous echocardiogram 6 months earlier. Methods: Data was collected from direct patient care and electronic medical records. Discussion: G. adiacens is a fastidious gram-positive coccus, part of the nutritionally variant streptococci (NVS) species, and part of the normal oral and gastrointestinal flora. It is also found in dental plaques and endodontic abscesses. NVS account for less than 5% of cases of bacteremia and IE. G. adiacens account for even fewer cases. Two separate meta-analyses conducted by Quintero-Martinez et al. and George et al. failed to reveal any cases of IE attributable to G. adiacens in the setting of COVID-19 infection. In conclusion, we believe that the hypercoagulable state of COVID-19 infection led to endocardial damage and development of LVT, thereby creating a nidus for microorganism adherence from underlying dental carries resulting in thromboembolic stroke.

Transsylvian transopercular peri-central core hemispherotomy for treating epilepsy: anatomy, surgical technique, and clinical outcome.

The objective of this study was to display the anatomical landmarks, surgical technique, and clinical outcome of transsylvian transopercular peri-central core hemispherotomy (TTPH) for treating refractory epilepsy. From 2011 to 2023, 26 patients (12 with Rasmussen syndrome, 8 with hemimegalencephaly/cortical malformations, and 6 with hypoxic-ischemic encephalopathy; mean [range] age 11.3 years [16 months to 35 years]; 13 females; and 13 with right-side pathology) underwent TTPH. The mean (range) follow-up was 88 (14-156) months. The intradural surgical time, use and amount of blood transfusion, postoperative fever, hospital stay, weight at surgery, and seizure onset to surgery interval are reported. TTPH consists of 1) sylvian fissure opening, 2) coagulation of the M2 and M3 branches, 3) frontoparietal opercula removal, 4) suprainsular resection, 5) insula removal, 6) selective amygdalohippocampectomy, 7) disconnection of the posterior temporal and occipital lobes using the tentorium and falx as landmarks, 8) intraventricular callosotomy, and 9) disconnection of the basal frontal lobe. In cortical malformation, the gray-white matter interface serves as a landmark. The average intradural operating time was 7 hours 18 minutes (3 hours 33 minutes to 13 hours 45 minutes); all patients were Engel class I; and 2 patients presented with procedure-related complications (meningitis and transient abducens nerve palsy). No patient required shunt surgery or reoperation. TTPH offers anatomical landmarks as intraoperative guides and has achieved good seizure control and low complication rates.

Analyzing brain-activation responses to auditory stimuli improves the diagnosis of a disorder of consciousness by non-linear dynamic analysis of the EEG

Although auditory stimuli benefit patients with disorders of consciousness (DOC), the optimal stimulus remains unclear. We explored the most effective electroencephalography (EEG)-tracking method for eliciting brain responses to auditory stimuli and assessed its potential as a neural marker to improve DOC diagnosis. We collected 58 EEG recordings from patients with DOC to evaluate the classification model’s performance and optimal auditory stimulus. Using non-linear dynamic analysis (approximate entropy [ApEn]), we assessed EEG responses to various auditory stimuli (resting state, preferred music, subject’s own name [SON], and familiar music) in 40 patients. The diagnostic performance of the optimal stimulus-induced EEG classification for vegetative state (VS)/unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) was compared with the Coma Recovery Scale-Revision in 18 patients using the machine learning cascade forward backpropagation neural network model. Regardless of patient status, preferred music significantly activated the cerebral cortex. Patients in MCS showed increased activity in the prefrontal pole and central, occipital, and temporal cortices, whereas those in VS/UWS showed activity in the prefrontal and anterior temporal lobes. Patients in VS/UWS exhibited the lowest preferred music-induced ApEn differences in the central, middle, and posterior temporal lobes compared with those in MCS. The resting state ApEn value of the prefrontal pole (0.77) distinguished VS/UWS from MCS with 61.11% accuracy. The cascade forward backpropagation neural network tested for ApEn values in the resting state and preferred music-induced ApEn differences achieved an average of 83.33% accuracy in distinguishing VS/UWS from MCS (based on K-fold cross-validation). EEG non-linear analysis quantifies cortical responses in patients with DOC, with preferred music inducing more intense EEG responses than SON and familiar music. Machine learning algorithms combined with auditory stimuli showed strong potential for improving DOC diagnosis. Future studies should explore the optimal multimodal sensory stimuli tailored for individual patients.Trial registration: The study is registered in the Chinese Registry of Clinical Trials (Approval no: KYLL-2023-414, Registration code: ChiCTR2300079310).

Brain Function and Marijuana: Are there Changes after Abstinence of Consumption? Preliminary Results.

The legalization of cannabis use and false claims about the plant Cannabis sativa to be considered a pharmaceutical product have been found to increase consumption, lower risk perception, and lead to more health problems, without reducing criminal activity. Brain function, typically assessed by neuropsychological tests, shows abnormalities with acute marijuana use, but inconsistent results have been published after abstinence, with a maximum follow-up of 28 days. Our previous research, using neuropsychological tests and brain perfusion single photon emission computed tomography (neuroSPECT), demonstrated consistent abnormalities in brain function among schoolchildren who consume marijuana compared to their non-consuming peers. The aim of this study is to investigate whether brain function changes in 20 adult marijuana users after 6 months of abstinence. Comparison of neuropsychological tests (Rey Complex Figure; Porteus Maze; Four subtests of WAIS-IV Intellectual Tests; STROOP; D2) and perfusion neuroSPECT (functional images), obtained in relation to recent consumption and after 6 months of serial drug-screening test confirmed abstinence. In a one-year period (2020-2021) only five compliant participants were recruited. The COVID-19 pandemic was a limiting factor. Preliminary results of neuropsychological tests, functional brain perfusion images and limited statistical analysis are presented. The results of the neuropsychological tests of the three subjects who completed the abstinence period so far show some improvement in working memory and attention after abstinence. NeuroSPECT shows disorganized hypoperfusion of variable severity in relation to recent consumption, involving areas associated with cognitive function such as the posterior cingulate and temporal lobes, in our five initially enrolled patients, when compared to a normal database. Of these, only two participants have already been re-evaluated with neuroSPECT after 6 months of abstinence, one of whom showed some improvement on the post-abstinence images. We analyze the methodological challenges of this research, including the pandemic, to incorporate the appropriate corrections in the next phase of our investigation. Our final findings may provide clinicians and users with information about the long-term effects of marijuana use on brain function.

Lower nonword syllable sequence repetition accuracy in adults who stutter is related to differences in audio-motor oscillations

ObjectiveThe goal of this study was to use independent component analysis (ICA) of high-density electroencephalography (EEG) to investigate whether differences in audio-motor neural oscillations are related to nonword syllable repetition accuracy in a group of adults who stutter compared to typically fluent speakers. MethodsEEG was recorded using 128 channels from 23 typically fluent speakers and 23 adults who stutter matched for age, sex, and handedness. EEG was recorded during delayed, 2 and 4 bilabial nonword syllable repetition conditions. Scalp-topography, dipole source estimates, and power spectral density (PSD) were computed for each independent component (IC) and used to cluster similar ICs across participants. Event-related spectral perturbations (ERSPs) were computed for each IC cluster to examine changes over time in the repetition conditions and to examine how dynamic changes in ERSPs are related to syllable repetition accuracy. ResultsFindings indicated significantly lower accuracy on a measure of percentage correct trials in the AWS group and for a normalized measure of syllable load performance across conditions. Analysis of ERSPs revealed significantly lower alpha/beta ERD in left and right μ ICs and in left and right posterior temporal lobe α ICs in AWS compared to TFS (CC p < 0.05). Pearson correlations with %CT for frequency across time showed strong relationships with accuracy (FWE<0.05) during maintenance in the TFS group and during execution in the AWS group. ConclusionsFindings implicate lower alpha/beta ERD (8–30 Hz) during syllable encoding over posterior temporal ICs and execution in left temporal/sensorimotor components. Strong correlations with accuracy and interindividual differences in ∼6–8 Hz ERSPs during execution implicate differences in motor and auditory-sensory monitoring during syllable sequence execution in AWS.

Neural representation of phonological wordform in temporal cortex.

While the neural bases of the earliest stages of speech categorization have been widely explored using neural decoding methods, there is still a lack of consensus on questions as basic as how wordforms are represented and in what way this word-level representation influences downstream processing in the brain. Isolating and localizing the neural representations of wordform is challenging because spoken words activate a variety of representations (e.g., segmental, semantic, articulatory) in addition to form-based representations. We addressed these challenges through a novel integrated neural decoding and effective connectivity design using region of interest (ROI)-based, source-reconstructed magnetoencephalography/electroencephalography (MEG/EEG) data collected during a lexical decision task. To identify wordform representations, we trained classifiers on words and nonwords from different phonological neighborhoods and then tested the classifiers' ability to discriminate between untrained target words that overlapped phonologically with the trained items. Training with word neighbors supported significantly better decoding than training with nonword neighbors in the period immediately following target presentation. Decoding regions included mostly right hemisphere regions in the posterior temporal lobe implicated in phonetic and lexical representation. Additionally, neighbors that aligned with target word beginnings (critical for word recognition) supported decoding, but equivalent phonological overlap with word codas did not, suggesting lexical mediation. Effective connectivity analyses showed a rich pattern of interaction between ROIs that support decoding based on training with lexical neighbors, especially driven by right posterior middle temporal gyrus. Collectively, these results evidence functional representation of wordforms in temporal lobes isolated from phonemic or semantic representations.

Autism spectrum disorder diagnosis with EEG signals using time series maps of brain functional connectivity and a combined CNN–LSTM model

Background and Objective:People with autism spectrum disorder (ASD) often have cognitive impairments. Effective connectivity between different areas of the brain is essential for normal cognition. Electroencephalography (EEG) has been widely used in the detection of neurological diseases. Previous studies on detecting ASD with EEG data have focused on frequency-related features. Most of these studies have augmented data by splitting the dataset into time slices or sliding windows. However, such approaches to data augmentation may cause the testing data to be contaminated by the training data. To solve this problem, this study developed a novel method for detecting ASD with EEG data. Methods:This study quantified the functional connectivity of the subject’s brain from EEG signals and defined the individual to be the unit of analysis. Publicly available EEG data were gathered from 97 and 92 subjects with ASD and typical development (TD), respectively, while they were at rest or performing a task. Time-series maps of brain functional connectivity were constructed, and the data were augmented using a deep convolutional generative adversarial network. In addition, a combined network for ASD detection, based on convolutional neural network (CNN) and long short-term memory (LSTM), was designed and implemented. Results:Based on functional connectivity, the network achieved classification accuracies of 81.08% and 74.55% on resting state and task state data, respectively. In addition, we found that the functional connectivity of ASD differed from TD primarily in the short-distance functional connectivity of the parietal and occipital lobes and in the distant connections from the right temporoparietal junction region to the left posterior temporal lobe. Conclusions:This paper provides a new perspective for better utilizing EEG to understand ASD. The method proposed in our study is expected to be a reliable tool to assist in the diagnosis of ASD.

Depersonalization and derealization as sequelae of a temporal lobe lesion: a case report

BackgroundDepersonalization and derealization can occur not just from psychiatric causes but also from various organic etiologies, such as seizures and intracerebral structural abnormalities. However, there have been no previous reported cases to the authors’ knowledge detailing isolated depersonalization and derealization in the absence of clinical seizure activity or other psychiatric pathology, as sequelae of structural intracerebral lesions.Case presentationIn this case report, we detail the unique presentation of a 68-year-old woman under the care of palliative medicine who experienced depersonalization and derealization secondary to a metastatic lesion in her temporal lobe, in the parahippocampal gyrus to medial occipitotemporal gyrus region. These symptoms were present in the absence of any clinical seizure activity or other psychiatric symptomatology and largely resolved with the use of steroidal therapy, before returning secondary to disease progression.ConclusionsWe discuss the relationship among isolated depersonalization and derealization with pathology of the left posterior temporal lobe in the context of this interesting case. This case expands our knowledge of the neurobiology of these phenomena, given the specific localization of the intracerebral pathology and temporal specificity of symptoms relative to tumor growth and treatment course.

Decoding Semantics from Dynamic Brain Activation Patterns: From Trials to Task in EEG/MEG Source Space.

The temporal dynamics within the semantic brain network and its dependence on stimulus and task parameters are still not well understood. Here, we addressed this by decoding task as well as stimulus information from source-estimated EEG/MEG human data. We presented the same visual word stimuli in a lexical decision (LD) and three semantic decision (SD) tasks. The meanings of the presented words varied across five semantic categories. Source space decoding was applied over time in five ROIs in the left hemisphere (anterior and posterior temporal lobe, inferior frontal gyrus, primary visual areas, and angular gyrus) and one in the right hemisphere (anterior temporal lobe). Task decoding produced sustained significant effects in all ROIs from 50 to 100 ms, both when categorizing tasks with different semantic demands (LD-SD) as well as for similar semantic tasks (SD-SD). In contrast, a semantic word category could only be decoded in lATL, rATL, PTC, and IFG, between 250 and 500 ms. Furthermore, we compared two approaches to source space decoding: conventional ROI-by-ROI decoding and combined-ROI decoding with back-projected activation patterns. The former produced more reliable results for word category decoding while the latter was more informative for task decoding. This indicates that task effects are distributed across the whole semantic network while stimulus effects are more focal. Our results demonstrate that the semantic network is widely distributed but that bilateral anterior temporal lobes together with control regions are particularly relevant for the processing of semantic information.

Transcranial direct current stimulation over the left posterior temporal lobe modulates semantic control: Evidence from episodic memory distortions

Evidence accumulates to show that semantic cognition requires, in addition to semantic representations, control processes that regulate the accessibility and use of semantic knowledge in a task- and time-appropriate fashion. Semantic control has been recently proposed to rely on a distributed network that includes the posterior temporal cortex. Along these lines, recent meta-analyses of neuroimaging data and studies with patients suffering from semantic aphasia have suggested that the left posterior middle temporal gyrus (pMTG) is critically involved whenever situational context must constrain semantic retrieval. In the present experiment, we used transcranial direct current stimulation over the left posterior temporal lobe in an attempt to interfere with semantic control while participants performed a DRM task, a procedure for inducing conceptually-based false recognition that is contingent on both activation and control processes. Paralleling findings with patients suffering from brain damage restricted to the temporoparietal cortex, anodal stimulation (relative to sham stimulation) resulted in increased false recognition but intact true recognition. These findings fit well with the idea that the left pMTG is a key component of a semantic control network, the alteration of which results in memory performance that is affected by the intrusion of contextually-inappropriate semantic information.

Speech and lexico-semantic errors during direct cortical stimulation mapping of the language-dominant hemisphere: effects of object and action naming.

In this retrospective study, the authors aimed to establish the stereotactically defined probability distribution for speech (i.e., anarthria, speech arrest) and lexico-semantic errors (i.e., anomia) through direct cortical stimulation (DCS) by using two tasks: action naming and object naming. They also analyzed the patterns of interindividual variability in the localization of the language sites involved, and investigated whether any patient or lesion location factors were associated with greater variability. Eighty-one Italian-speaking patients who underwent awake surgery between 2010 and 2021 for low- and high-grade gliomas in eloquent areas of the language-dominant hemisphere were entered in the analyses. The intraoperative DCS protocol included automatic speech tasks, object naming, and action naming. The position of the tags, as depicted on the intraoperative video or photograph, was transposed into Montreal Neurological Institute space. Subsequently, a 2D scatterplot and cluster analysis were performed. Associations between various clinical and radiological characteristics and the quantity of positive stimulated sites were determined by univariate analyses using binary logistic regression. Associated variables (p < 0.2) were included in stepwise multivariate logistic regression with backward elimination (p < 0.05). A total of 1380 cortical sites were stimulated, with a positive response in 511 cases (37%). Most anarthric errors were triggered when stimulating the left precentral gyrus, and most speech arrest errors were elicited when stimulating the left posterior inferior frontal gyrus. Anomias were found in the left inferior frontal gyrus and in the posterior part of the left temporal lobe for object naming. DCS to the left dorsal premotor cortex elicited anomic errors for action naming. Anomias were also elicited during DCS to the left posterior temporal lobe, with both object and action naming. The distribution of speech and lexico-semantic errors is in line with the current literature. The action-naming results are new and mostly involve the dorsal premotor cortex. These findings stress the importance of maximizing the use of different language tasks during surgery, because even when looking for the same type of errors, different tasks may be better suited to map specific brain regions. DCS with action and object naming identifies more positive sites than object naming alone.

3D convolutional neural network for schizophrenia detection using as EEG-based functional brain network

Schizophrenia (ScZ) is a chronic mental disorder affecting the function of the brain, which causes emotional, social, and cognitive problems. This paper explored the functional brain network and deep learning methods to detect ScZ using electroencephalogram (EEG) signals. Functional brain network analysis was proposed and implemented using a multivariate autoregressive model and coherence connectivity algorithm. The three machine learning techniques and 3D-convolutional neural network (CNN) models were applied to classify the ScZ patients and health control subjects, and then the public LMSU database was utilized to assess the performance. The proposed 3D-CNN method achieved the performance of a 98.47 ± 1.47 % in accuracy, 99.26 ± 1.07 % in sensitivity, and 97.23 ± 3.76 % in specificity. Moreover, in addition to the default mode network region, the temporal and posterior temporal lobes of both right and left hemispheres were found as the significant difference areas in ScZ brain network analysis.

Longitudinal tau binding in tau‐PET negative patients with clinical Alzheimer’s disease

AbstractBackgroundDifferent tau‐PET patterns have been observed in Alzheimer’s disease (AD) which may be associated with demographic factors, copathology and resilience. We and others previously found that not all Aβ‐positive AD patients are tau‐PET positive. It is currently not known whether tau pathology develops in these groups over time. Therefore, we aimed to examine longitudinal tau binding in tau‐PET negative individuals with symptomatic AD.MethodWe included 97 Aβ‐positive participants with clinical diagnosis of mild cognitive impairment or dementia due to AD (MCI/AD) of which 12 (13%) were tau‐PET negative. To compare, we included 131 tau‐PET negative cognitively unimpaired individuals (CU) of which 93 (71%) were Aβ‐negative and 38 (29%) Aβ‐positive. Tau‐status was defined by [18F]flortaucipir PET consensus visual read of two nuclear physicians according to US Food and Drug Administration‐approved guidelines. [18F]flortaucipir SUVr at baseline (N = 225) and after ±2 years (N = 81) was quantified in an early tau region reflecting Braak I (entorhinal cortex), the medial temporal lobe (MTL), and a combined visual read region of interest (ROI) (parietal, occipital, and posterior lateral temporal lobe). We used age‐and sex‐adjusted linear mixed models to compare tau accumulation.ResultDemographics are shown in table 1. Compared to MCI/AD A+T+, MCI/AD A+T‐ were older (p&lt;0.001) and more often male (p = 0.015). MCI/AD A+T‐ did not differ from CU A‐T‐ in baseline tau‐PET SUVr, but had a slightly lower SUVr in Braak I compared to CU A+T‐ (p = 0.040) (figure 1). After ±2 years, all MCI/AD A+T‐ participants who underwent follow up remained visual read tau negative. However, MCI/AD A+T‐ showed a steeper increase in Braak I and MTL tau‐PET SUVr compared to CU A‐T‐ (figure 2A,B) and in Braak I compared to CU A+T‐ (β = 0.31, p = 0.036). Interestingly, MCI/AD A+T‐ showed a significantly steeper tau‐PET SUVr increase compared to MCI/AD A+T+ in Braak I (β = 0.29, p = 0.029) (figure 2A).ConclusionAlthough visual read tau‐PET status remains stable over time, our results indicate that tau‐negative MCI/AD patients do accumulate tau over time, most pronounced in early tau regions. This highlights the relevance of quantifying tau regionally over time in tau‐PET negative individuals with clinical AD diagnosis.

Dysfunctional cerebral glucose transport in Alzheimer’s Disease

AbstractBackgroundGlucose is the primary energy source required for the homeostatic function of the brain. Glucose transporter 1 (GLUT1) present at the blood‐brain barrier is a key regulator of glucose transport into the brain. Reduced GLUT1 expression is shown to exacerbate Alzheimer’s pathology in rodent models. Here we aimed to establish whether there are regional differences in ineffective glucose transport amongst people living with Alzheimer’s disease.Method125 participants diagnosed with Alzheimer’s dementia, with an [18F]FDG scan with atrial input were enrolled. All participants underwent 3‐tesla magnetic resonance imaging and [18F]FDG scan with continuous and discrete arterial sampling. Spectral analysis was performed to create 1‐minute input‐response function parametric maps. To produce glucose transfer maps we applied the following equation; K1 ⁎ Ca / τ (K1 = 1‐minute IRF map, Ca = Plasma glucose concentration, τ = 1.48 a lumped constant). Glucose transfer maps were then coregistered to the participants’ structural MRI and normalised to MNI space. Regional mean glucose transfer was then calculated for the anterior cingulate cortex, frontal lobe, hippocampus, parahippocampus, occipital lobe, parietal lobe, posterior cingulate cortex, striatum, temporal lobe, and thalamus. A within‐subject ANOVA was then performed to evaluate the regional differences in cerebral glucose transport.ResultThe parahippocampus exhibited the lowest rate of glucose transfer in comparison to all other regions (p &lt; 0.001), followed by the hippocampus. The striatum and occipital lobe demonstrated the regions of the highest mean glucose transportation from blood to the brain. In terms of brain lobes, the temporal lobe showed the lowest rates of glucose transfer, followed by the parietal lobe, then frontal and occipital (p &lt; 0.001).ConclusionWe demonstrate dysfunctional BBB glucose transport in Alzheimer’s disease, with prominent glucose transport abnormalities localised in the parahippocampus. Impaired glucose transport was most apparent within temporal lobe structures. Targeting glucose transfer may be an effective way of treating Alzheimer’s disease.

Hypoconnectivity of the Amygdala in Patients with Low-Back-Related Leg Pain Linked to Individual Mechanical Pain Sensitivity: A Resting-State Functional MRI Study.

To explore resting-state functional connectivity (rsFC) of the amygdala in patients with low-back-related leg pain (LBLP). For this prospective study, a total of 35 LBLP patients and 30 healthy controls (HCs) were included and underwent functional MRI and clinical assessments. Then, patients with LBLP were divided into acute LBLP (aLBLP) and chronic LBLP (cLBLP) subgroups. We further evaluated the between-group rsFC differences using left and right amygdala seeds in a whole-brain voxel analysis strategy. Finally, we performed correlation analysis between the rsFC values of altered regions and clinical indices. Compared to HCs, hypoconnectivity of the amygdala was observed in LBLP patients (P < 0.01, with correction). The amygdala's rsFC pattern was different between aLBLP and cLBLP patients: decreased the amygdala's FC to the right putamen, to the right paracentral lobule (PCL), or to the right posterior temporal lobe in aLBLP patients, while right amygdala to the bilateral anterior cingulate cortex (ACC) and the left postcentral gyrus (PoCG) in cLBLP patients. Correlation analysis showed that lower rsFC of the left amygdala to the right PCL was correlated with the von Frey filament (vF) test values of the left lumbar (p = 0.025) and right lumbar (p = 0.019) regions, and rsFC of the right amygdala to the left PoCG was correlated with lower vF test values of the left lumbar (p = 0.017), right lumbar spine (p = 0.003); to right PoCG was correlated with calf (p = 0.015); the rsFC of the right amygdala to bilateral ACC was negatively correlated with the pain rating index (p = 0.003). LBLP patients showed amygdala hypoconnectivity, and the altered pattern of amygdala rsFC was different in the acute and chronic phases. Moreover, the amygdala hypoconnectivity was related to individual mechanical sensitivity (vF test) in LBLP patients.

6 Posterior cerebral artery-defined white matter hyperintensities are associated with object domain memory and transentorhinal volume independently of global beta-amyloid burden

Objective:White matter hyperintensities (WMH) are a radiological marker of small vessel cerebrovascular disease that are related to cognition and memory decline in aging and Alzheimer’s disease (AD). However, the mechanisms that link WMH to memory impairment and whether they interact with or act independently of AD pathophysiology are unclear. The transentorhinal cortex (BA35) is among the earliest anatomical regions to show tau deposition and subsequent atrophy, and baseline posterior WMH is related to longitudinal cortical thinning of the entorhinal cortex. However, it is unclear whether regional WMH are related to BA35 volume specifically, and whether this relationship is influenced by amyloid-β (Aβ) burden. We hypothesized that WMH in the vascular territory of the posterior cerebral artery (PCA), which perfuses both posterior and medial temporal lobe regions, would be associated with reduced BA35 volume and with lower memory in older adults independently of Aβ.Participants and Methods:114 older adults without dementia, aged 60 to 98 years (mean (SD) = 78.31 (11.02), 71 (62.8%) women), were included. Regional WMH volumes were derived from T2-FLAIR images using ANTs, a vascular territory atlas and manual editing. Global Aβ was assessed with 18F-florbetapir PET, using SUVR of a cortical composite region (FBP mean SUVR) with a cerebellar reference region. Total transentorhinal (BA35) volume was derived using T1 and T2-weighted images using ASHS. To assess hippocampal pattern separation ability, an index of episodic memory, participants completed both object (MDT-O) and spatial (MDT-S) versions of a mnemonic discrimination task, with the lure discrimination index as the outcome. Using linear regressions, we first tested for associations among PCA-defined WMH, Aβ, BA35 volume, and MDT-S and MDT-O scores. We then tested whether the relationship between PCA-defined WMH and MDT-O performance was mediated by BA35 volume and whether this mediation was moderated by Aβ. All models adjusted for age, sex, and education.Results:PCA-defined WMH were related to higher FBP mean SUVR (b=0.287, p=0.042) and lower BA35 volume (b=-0.222, p=0.038). PCA-defined WMH were also negatively related to MDT-O performance (b=-0.229, p=0.044), but not to MDT-S (b=-0.171, p=0.118). FBP mean SUVR was not related to BA35 volume (b=-0.131, p=0.344) or MDT performance (MDT-S: b=-0.138, p=0.348; MDT-O: b=0.059, p=0.690). Furthermore, FBP mean SUVR did not interact with PCA-defined WMH to predict memory performance (interaction b=-0.039, p=0.973), nor BA35 volume (interaction b=-0.140, p=0.894). The association of PCA-defined WMH to MDT-O was fully mediated by BA35 volume (indirect effect b=-0.0005, 95% CI (-0.0014, -0.0003)). This mediation was not moderated by FBP mean SUVR (indirect effect b=-0.00001, 95% CI (-0.001, 0.001)).Conclusions:We found that PCA-defined WMH were related to memory performance in older adults, and this association is fully mediated by transentorhinal volume. While PCA-defined WMH are related to higher global Aβ burden, there is no interaction between PCA-defined WMH and Aβ on BA35 volume. These findings point to an amyloid-independent vascular pathway towards memory decline in aging and AD. Future work should examine whether the pathway linking PCA-defined WMH to transentorhinal cortex atrophy and subsequent memory decline is mediated by regional tau pathology.