Magnetic resonance fingerprinting (MRF) is a novel paradigm for magnetic resonance imaging (MRI) that efficiently generates multiparametric quantitative tissue property maps with a single acquisition. Its quantitative nature offers many advantages over conventional MRI. Although interest in MRF for epilepsy research has grown in recent years, systematic evaluation of its radiological and clinical value as a supplementary imaging modality is limited. We reviewed the diagnostic utility of MRF imaging for 100 epilepsy patients undergoing presurgical evaluation. MRF quantitative maps (T1, T2, gray matter fraction, and white matter fraction) were generated and reviewed alongside conventional MRI. MRF findings were classified as (1) consistent-MRF findings the same as conventional MRI; (2) additional-MRF revealed findings beyond those seen on conventional MRI; or (3) discrepant-findings on conventional MRI not reproduced on MRF. We further stratified results by radiological diagnosis or pathology if available. Observations were further classified based on whether T1 or T2 MRF maps provided greater diagnostic utility. MRF revealed additional findings in a total of 46 patients (46/100, 46%). In one patient, findings on conventional MRI were not recapitulated on MRF (1/100, 1%). In the remaining 53 patients, MRF findings were consistent with conventional MRI (53/100, 53%). Additional benefits of MRF included the following: improved lesion conspicuity (n = 16), improved visualization of lesion extent (n = 11) or asymmetry between bilateral mesial temporal regions (n = 9), differentiation between multiple lesions (n = 5), new lesion identified (n = 2), and visualization of connection between lesion and other areas (n = 1). Added value from MRF was particularly common in patients with focal cortical dysplasia (FCD) type IIa (p = .009 vs. FCD IIb) and periventricular nodular heterotopia. Our findings demonstrate the additional yield from MRF in the identification and definition of the extent of epileptogenic lesions, underscoring its potential as a valuable adjunct in presurgical epilepsy evaluation.

Chemotherapy-induced cognitive impairment (CICI) is a frequently reported complication in lung cancer patients, yet the underlying cerebral metabolic changes remain poorly characterized. This study aimed to evaluate chemotherapy-related alterations in brain glucose metabolism in patients with non-small cell lung cancer (NSCLC) using a longitudinal, within-subject voxel-based 18F-FDG PET approach. Forty NSCLC patients who underwent both pre- and post-chemotherapy FDG PET imaging were retrospectively enrolled. Voxel-wise comparisons were performed using SPM12 to identify regional metabolic changes. Patients were stratified based on chemotherapy intensity (standard: ≥4 cycles; short-course: 1-3 cycles) and recovery interval (short: <6 months; long: ≥6 months), with subgroup and interaction analyses conducted accordingly. Compared with baseline, post-treatment scans revealed regional metabolic reductions, predominantly in the right thalamus, left frontal lobe, and bilateral temporal regions. Patients receiving standard chemotherapy exhibited more extensive metabolic reductions than those receiving short-course treatment, particularly in the bilateral temporal and cingulate regions. Furthermore, patients scanned within six months post-chemotherapy showed more pronounced reductions than those with longer recovery intervals, suggesting a potential trend of metabolic recovery over time. In contrast, patients with limited initial metabolic changes (i.e., short-course group) exhibited minimal changes across intervals. This within-subject FDG PET study provides longitudinal evidence that chemotherapy independently contributes to brain metabolic alterations in NSCLC patients, predominantly involving the frontal, temporal, and limbic regions. These findings highlight vulnerable neural substrates and underscore the clinical value of functional neuroimaging in cancer survivorship research.

Language abilities are heterogeneous in autism spectrum disorder. Functional neuroimaging offers critical insights into the developmental trajectory of language in autism, with the potential to inform tailored supports. Unlike previous non-systematic or modality-specific reviews, this systematic review aimed to identify developmental trajectories in autistic children and elevated likelihood infants across functional neuroimaging modalities. Across the included 31 studies, EEG was the most common modality (39%), followed by fMRI (26%), MEG (26%), and fNIRS (9%). Most studies (77%) used passive awake tasks; around half employed simple speech stimuli (55%) while the remainder used complex speech (45%). There was an underrepresentation of minimally and nonspeaking autistic participants. fMRI and fNIRS studies found that elevated likelihood infants displayed hypoactivation in bilateral temporal regions, which did not consistently continue into mid-to-late childhood. EEG and MEG studies indicate that the timing and magnitude of auditory-perceptual and higher-order linguistic processing remained atypical (e.g., delayed latencies, larger amplitudes) from infancy to late childhood. Across modalities, findings were sometimes inconsistent, particularly when accounting for variability in language abilities. We highlight a strong need for caution in generalizing findings and argue that future research should prioritize more diverse samples to better elucidate the neural trajectory of language in autism.

Abstract The integration of sensory information in humans may be confined to a time window of 2–3 seconds. In language, this time window constrains the grouping of words into multi-word chunks, required for comprehension. Chunk boundaries are known to elicit a characteristic event-related brain potential, the Closure Positive Shift (CPS). The likelihood of a CPS increases with the duration of the chunk. In the frequency-domain, boundaries have been associated with neural oscillations in the delta band (&amp;lt;4 Hz). Here, we assessed whether the pace for chunking might be imposed by electrophysiological processing cycles of the brain with phase-locking of such activity underlying the CPS. We recorded participants’ magnetoencephalogram while they listened to globally ambiguous sentences allowing for two alternative ways of chunking. Chunking was not externally imposed, but the temporal limits of integration windows influenced chunk termination. Phase-locking of narrow-band low-frequency neural activity (i.e., &amp;lt;4 Hz) at the boundaries of multi-word chunks increased with sentence duration, and covaried with event-related fields. Behavioral data further indicate subtle interindividual differences in the duration of the integration time window. Source localization revealed neural generators in bilateral posterior temporal and right anterior regions. The brain appears to project duration-limited integration windows onto the incoming auditory speech signal, thus structuring language comprehension in time.

Background: Auditory hallucinations (AHs)—perceptions of sound without external stimuli—are common in clinical populations but rarely investigated in healthy individuals. This study aimed to employ Pavlovian conditioning to induce AH-like experiences in healthy subjects and to examine their neural correlations using electroencephalography (EEG). Methods: Seven healthy volunteers were exposed to auditory, non-auditory, and conditioned non-auditory stimuli while recording their EEG with a 32-channel system. Results: When comparing “sound” (auditory) and “conditioned no sound” (conditioned non-auditory) scenarios, the differences in average EEG power were much less pronounced compared to regular sound/no sound scenario. However, significant alterations (p = 0.05) in β and γ rhythms were observed in bilateral temporal regions when comparing the “no sound” and “conditioned no sound” scenario, resembling the spectral patterns observed during real sound perception. These EEG alterations indicate successful induction of hallucination-like auditory experiences through Pavlovian conditioning. A three-class k-nearest neighbor (kNN) classifier detected AH-like events with &gt;80% accuracy in six out of seven participants. Conclusions: Pavlovian conditioning can induce AH-like perceptions in healthy individuals, accompanied by measurable EEG alterations. Therefore, EEG-based methods have the potential for objective detection and assessment of auditory hallucinations and offer a foundation for future research on their neural mechanisms.

Hyposmia is a common early non-motor symptom of Parkinson disease (PD) and has been linked to cognitive decline. This study investigated whether striatal dopaminergic degeneration and cerebral perfusion deficits mediate the relationship between hyposmia and cognition in PD. We retrospectively analyzed 343 newly diagnosed PD patients who underwent the Cross-Cultural Smell Identification Test (CCSIT) and dual-phase 18F-FP-CIT PET. Early-phase PET was used as a surrogate of regional cerebral blood perfusion, and late-phase PET measured dopamine transporter (DAT) availability in 6 striatal subregions. A subset of 219 patients completed baseline neuropsychological testing and were followed for a mean of 4.2 years to assess dementia conversion. Baseline CCSIT scores were positively correlated with DAT availability across striatal regions, strongest in the posterior putamen (β=0.21, P<0.001). Hyposmia was associated with cortical hypoperfusion in bilateral entorhinal, inferior parietal, inferior temporal, and parieto-occipital regions. Lower CCSIT scores predicted poorer baseline cognitive performance (language, memory, executive function; all P<0.05) and a higher risk of dementia (HR=0.83, P=0.001). In models adjusted for DAT and perfusion markers, direct associations between olfaction and cognition were markedly reduced. Mediation analyses revealed that posterior cortical hypoperfusion explained the olfaction-memory link, whereas both dopaminergic loss and hypoperfusion mediated dementia conversion. Olfactory loss in PD reflects widespread neurodegeneration involving nigrostriatal and posterior cortical networks. Integrating olfactory assessment with imaging markers may better identify patients at risk for cognitive decline, supporting improved risk stratification and early intervention.

Pediatric spinal cord injury (SCI) induces extensive neuroplastic changes in the developing brain; however, the patterns of cortical remodeling associated with complete (CSCI) and incomplete (ICSCI) injuries remain poorly understood. In this study, high-resolution structural magnetic resonance imaging was used to assess cortical morphological alterations in 72 pediatric SCI patients (38 CSCI and 34 ICSCI) and 37 age-matched healthy controls (HCs). Key cortical metrics-including surface area, thickness, volume, and curvature-were analyzed to characterize injury-related reorganization. Significant group differences were identified across multiple cortical regions. Compared with HCs, both CSCI and ICSCI patients exhibited reduced surface area in the left primary somatosensory cortex (S1), with CSCI patients showing significantly greater surface area than ICSCI. In the left posterior cingulate cortex (PCC), surface area was significantly reduced in the CSCI group compared with ICSCI. Cortical thickness analysis revealed that both patient groups showed increased thickness in the bilateral superior and middle temporal regions, but decreased thickness in the left paracentral lobule, inferior insula, and right supramarginal gyrus (SMG). Notably, CSCI patients had significantly lower thickness in the right SMG than ICSCI patients. For cortical volume, both SCI groups exhibited increased volume in the bilateral transverse frontopolar cortex, with the CSCI group showing significantly greater volume in the right hemisphere compared with ICSCI. No significant differences were found in cortical curvature across groups. Correlation analyses showed that surface area in the left PCC was positively associated with sensory scores across all patients. In ICSCI patients, right frontopolar volume positively correlated with both motor and sensory scores. Receiver operating characteristic analysis demonstrated that surface area (left S1, PCC), cortical thickness (right SMG), and cortical volume (right transverse frontopolar cortex) could differentiate CSCI from ICSCI, with a combined classification model achieving an area under the curve of 0.7980. Our findings indicated that CSCI and ICSCI are associated with distinct patterns of cortical reorganization in regions related to sensory processing and affective-cognitive integration. These results highlight the diagnostic potential of multidimensional cortical morphometry and support its relevance in guiding individualized, neuromodulation-based rehabilitation strategies in pediatric SCI.

Background/Objectives: Posterior fossa tumors (PFTs) often require radiotherapy which may damage both cortical and subcortical brain tissue. We examined voxel-based and region-based gray matter volume (GMV) alterations and explored their relation to cognitive functioning. Methods: Using T1-weighted MR imaging, intelligence scores from the Wechsler Adult Intelligence Scale-IV (WAIS-IV), and domain scores for language, learning, and memory, complex attention and cognitive flexibility were investigated in 18 of 21 assessed PFT survivors and 21 matched controls. GMV was quantified with voxel-based and region-based volumetry, compared among groups (controls versus survivors, irradiated versus non-irradiated survivors), and correlated with cognitive performance. Results: Survivors showed reduced GMV in two voxel-based clusters, located in the left occipital fusiform area and the left pallidum. Region-based analyses showed lower GMV in survivors located in subcortical areas, while higher GMV was observed in the left inferior temporal region. Survivors who received craniospinal radiation exhibited reductions in GMV in bilateral thalami, right ventral diencephalon, and central corpus callosum, and higher GMV in the bilateral middle temporal regions. Compared to controls, survivors scored lower for all cognitive domains, except for complex attention and cognitive flexibility. Amongst survivors, the GMV of the bilateral thalami and right ventral diencephalon correlated positively with working memory. Conclusions: Overall, PFT survivors demonstrated both alterations in GMV and cognitive functioning, with the most pronounced GMV deviations found in those treated with craniospinal radiation. Reduced GMV was associated with poorer cognitive performance.

Functional near-infrared spectroscopy (fNIRS) has the potential for evaluating language and conversational interaction in an ecologically valid way given that participants can be seated and interacting with a conversational partner. Aphasia, an acquired language disorder, impacts language abilities, including conversational interaction. Understanding of cortical activity in people with aphasia for conversational tasks could provide an ecologically valid index of brain function and recovery patterns in this population. This study provides pilot data in the use of fNIRS to evaluate language production for conversational responses in young (adult) neurotypical individuals, adults with post-stroke aphasia, and age-matched (i.e., older) neurotypical adults. Experiment 1 evaluated cortical activity for conversational responses versus sentence repetition in a computer-based conversational question task. Experiment 1 results showed differentiation between experimental conditions (with greater fronto-temporoparietal cortical activity for question answering vs. repetition) in young healthy individuals that was not seen in the people with aphasia and age-matched individuals. Experiment 2 evaluated cortical activity for conversational responses in a structured conversational question task with a live interlocutor versus sentence repetition. Experiment 2 results showed lower cortical activity across regions of interest in the age-matched group and greater cortical activity for question answering versus repetition in bilateral temporal and left parietal regions of interest in the people with aphasia. This study provides preliminary evidence for the potential of fNIRS to characterize cortical activity after stroke for functional language tasks.

IntroductionUnderstanding how emotions are encoded at the neural level remains a central challenge in human neuroscience. Facial expressions are among the most powerful and frequently used stimuli to study emotion processing. Face perception itself is a complex function supported by a core network—including bilateral occipito-fusiform and superior temporal regions—and an extended network involving anterior structures such as the bilateral amygdalae. However, previous findings on how emotional content modulates these networks have been inconsistent.MethodsTo disentangle perceptual and affective components of face emotion processing, we combined high-frequency pupillometry with functional magnetic resonance imaging (fMRI). Pupillary dilation serves as a sensitive index of two distinct processes: perceptual load, reflecting the informational complexity of a face, and arousal, indicating its immediate sensory impact. In our study, 25 participants (13 female) viewed faces expressing anger, fear, happiness, or neutrality as well as luminance-matched houses serving as control stimuli. A one-back task unrelated to emotion masked the true experimental purpose.ResultsRelative to houses, faces elicited stronger pupillary dilations as well as enhanced blood-oxygen-level-dependent (BOLD) activity in bilateral occipital and fusiform cortices as well as in both amygdalae. Among facial expressions, angry faces evoked the largest pupillary dilations, while fearful faces elicited the strongest neural responses within a right-lateralized network centered on the superior temporal sulcus (rSTS). Across all faces>houses (conjunction minimum-statistic inference), pupil size correlated positively with BOLD activity in the right fusiform gyrus (rFFG), left inferior occipital gyrus (lIOG), bilateral calcarine cortex, and bilateral lingual gyrus.DiscussionThese findings indicate that emotional faces impose a higher perceptual load than matched control stimuli, engaging a distributed network spanning early visual and attention-related areas. In conclusion, our results suggest that emotional quality is specified early in the perceptual process, with divergent pupillary and neural signatures separating arousal-driven threat responses (anger) from socially complex alarm cues (fear).

BackgroundSubjective cognitive decline (SCD) is one of the earliest noticeable symptoms of AD and is defined as having self‐perceived worsening of cognition without exhibiting objective impairments on standardized clinical cognitive tests (PMID: 31958406). Since not all individuals with SCD will convert into MCI or AD, it is important to accurately characterize and model the subtle changes in SCD brains that may be predictive of future trajectory towards AD.MethodLongitudinal MRI data and AD Assessment Scale (ADAS‐Cog) scores from 70 subjects with SCD and 100 healthy controls (HC) were acquired from the ADNI 2 and 3 database. Standard resting‐state fMRI pre‐processing and calculations of 3D regional homogeneity (ReHo) based on 27 neighboring voxels was performed using Data Processing & Analysis for Brain Imaging (DPABI) while site effects were minimized via CovBat harmonization (PMID: 37086875). Within a gray matter mask, two sample t‐tests were performed between the HC and SCD groups' ReHo maps using FSL's randomization procedure with 5000 permutations where age, sex, head motion, and voxel‐wise GM volume were included as covariates. Significance levels were adjusted for multiple comparisons using threshold‐free cluster enhancement correction. An ordinary least squares regression (OLS) model was developed for predicting future ADAS‐Cog scores based on baseline (year 0) clinical scores and ReHo values.ResultAt baseline compared to HC, SCD revealed significant ReHo decreases in the frontal and occipital regions along with significant increases in the temporal regions (Table 1). Correlation maps of SCD ReHo and ADAS‐Cog scores indicated negative correlations in the bilateral insula and temporal regions along with positive correlations in the medial parietal regions (Figure 1). The OLS model developed from these features and baseline clinical scores was able to predict ADAS‐Cog scores at year 4 with a goodness‐of‐fit (r2) of 0.72 among a randomized 50:50 training and test set. Independently, the model's r2 based on baseline clinical scores alone was 0.64.ConclusionReHo reflects neural synchronization within localized regions, providing insights into brain network coherence. Individuals with SCD exhibit significantly different resting‐state ReHo features compared to HCs. With predictive modeling, these ReHo features can help augment the long‐term projection of early AD trajectories.

Atherosclerosis of the Circle of Willis (ACW) is a common comorbidity in Alzheimer's disease (AD). Therefore, in the era of disease-modifying treatments understanding how ACW may influence cortical neurodegeneration driven by AD neuropathological processes is valuable. By investigating the impact of ACW on cortical microstructural changes, we aim to identify potential cortical patterns to improve diagnostic precision, offering better-targeted therapeutic approaches for individuals with combined vascular and neurodegenerative pathologies. Structural and diffusion ante mortem MRI scans of 58 participants with intermediate or severe Alzheimer's disease neuropathologic change (ADNC) were obtained from the National Alzheimer's Coordinating Center (NACC). Participants were grouped by ACW severity (37 with none/mild and 21 moderate/severe) (Table 1). Macrostructural MRI metrics (cortical volume and cortical thickness) and three minicolumn-related diffusivity metrics were extracted: the angle between the radial minicolumnar direction and the principal diffusion direction (AngleR); the principal diffusion component parallel with the minicolumns (ParlPD), and the diffusion components perpendicular to the minicolumns (PerpPD+) (Torso et al. 2022, PMID:36281682). The groups were compared to investigate potential differences in clinical, demographic vascular risk factors and whole-brain MRI macrostructural data. Regional differences in macrostructural (Cortical volume and cortical thickness) and diffusion metrics were analyzed using a linear model, adjusted for the interval between the MRI scan and autopsy dates, acquisition protocol, age, and sex. The results were corrected for multiple comparisons using the false discovery rate (pFDR < 0.05). Regional analysis revealed that participants with higher ACW severity exhibited a significant lower ParlPD values in the bilateral temporal and occipital regions (Figure 1), as well as significantly lower PerpPD+ values in the left occipital regions. No differences were found in demographic, clinical, vascular risk factor and whole-brain MRI macrostructural data when comparing the two groups. These findings highlight the potential of cortical diffusivity in detecting distinct patterns of microstructural changes in individuals with the same ADNC severity but varying levels of ACW severity. This underscores the utility of cortical diffusivity for patient stratification in clinical practice and trials.

BackgroundPlasma ptau217 has recently emerged as a reliable biomarker for early Alzheimer's disease (AD) pathology. Additionally, previous works have suggested that indices of cortical mean diffusivity (MD) derived from diffusion‐weighted imaging are thought to reflect early microstructural changes preceding detectable structural atrophy in neurodegenerative diseases. While ptau217 has been shown to correlate with cortical atrophy in cognitively normal individuals, its relationship with cortical MD remains unstudied.Methods1029 cognitively unimpaired (CU) elderly participants (mean age: 74.9, range: 69‐87; 65% female) with 3T MRI and plasma ptau217 measures were selected for baseline cross‐sectional analyses from the Vallecas Project cohort, a single‐centre 12‐year longitudinal study with annual follow‐ups. Plasma ptau217 levels were measured on the fully automated LUMIPULSE platform, and individuals were classified as either ptau217+ (n = 174, mean age: 76.0) or ptau217‐ (n = 855, mean age: 74.7) based on a pre‐established threshold of 0.247 pg/mL. Diffusion‐weighted images were preprocessed using an in‐house pipeline to correct for eddy currents and image distortions due to magnetic field inhomogeneity, and diffusion tensors were fitted using FSL. A normalised grey matter image was used to mask normalised MD images to obtain cortical grey matter MD maps, which were subsequently analysed in a voxel‐wise GLM using SPM12, controlling for age and sex.ResultsAt baseline, there was no difference between groups in sex distribution, although individuals with elevated ptau217 levels were significantly older (p = 0.0001). After controlling for sex and age, the ptau217+ group showed significantly higher cortical MD in bilateral medial temporal (amygdala and hippocampus) and insular regions (insular and opercular cortices) compared to ptau217‐ (p <0.05, FDR‐corrected; Figure 1).ConclusionsIn our study of a large‐scale, well‐characterised cognitively unimpaired population with available diffusion weighted imaging, changes in cortical MD can already be observed in those with elevated plasma ptau217 in regions commonly associated with AD neuropathology. Further analysis on longitudinal MD changes in the same cohort are ongoing.

BackgroundAtherosclerosis of the Circle of Willis (ACW) is a common comorbidity in Alzheimer’s disease (AD). Therefore, in the era of disease‐modifying treatments understanding how ACW may influence cortical neurodegeneration driven by AD neuropathological processes is valuable. By investigating the impact of ACW on cortical microstructural changes, we aim to identify potential cortical patterns to improve diagnostic precision, offering better‐targeted therapeutic approaches for individuals with combined vascular and neurodegenerative pathologies.MethodStructural and diffusion ante mortem MRI scans of 58 participants with intermediate or severe Alzheimer's disease neuropathologic change (ADNC) were obtained from the National Alzheimer's Coordinating Center (NACC). Participants were grouped by ACW severity (37 with none/mild and 21 moderate/severe) (Table 1).Macrostructural MRI metrics (cortical volume and cortical thickness) and three minicolumn‐related diffusivity metrics were extracted: the angle between the radial minicolumnar direction and the principal diffusion direction (AngleR); the principal diffusion component parallel with the minicolumns (ParlPD), and the diffusion components perpendicular to the minicolumns (PerpPD+) (Torso et al. 2022, PMID:36281682).The groups were compared to investigate potential differences in clinical, demographic vascular risk factors and whole‐brain MRI macrostructural data. Regional differences in macrostructural (Cortical volume and cortical thickness) and diffusion metrics were analyzed using a linear model, adjusted for the interval between the MRI scan and autopsy dates, acquisition protocol, age, and sex. The results were corrected for multiple comparisons using the false discovery rate (pFDR < 0.05).ResultRegional analysis revealed that participants with higher ACW severity exhibited a significant lower ParlPD values in the bilateral temporal and occipital regions (Figure 1), as well as significantly lower PerpPD+ values in the left occipital regions. No differences were found in demographic, clinical, vascular risk factor and whole‐brain MRI macrostructural data when comparing the two groups.ConclusionThese findings highlight the potential of cortical diffusivity in detecting distinct patterns of microstructural changes in individuals with the same ADNC severity but varying levels of ACW severity. This underscores the utility of cortical diffusivity for patient stratification in clinical practice and trials.

BackgroundPlasma ptau217 has recently emerged as a reliable biomarker for early Alzheimer’s disease (AD) pathology. Additionally, previous works have suggested that indices of cortical mean diffusivity (MD) derived from diffusion‐weighted imaging are thought to reflect early microstructural changes preceding detectable structural atrophy in neurodegenerative diseases. While ptau217 has been shown to correlate with cortical atrophy in cognitively normal individuals, its relationship with cortical MD remains unstudied.Methods1029 cognitively unimpaired (CU) elderly participants (mean age: 74.9, range: 69‐87; 65% female) with 3T MRI and plasma ptau217 measures were selected for baseline cross‐sectional analyses from the Vallecas Project cohort, a single‐centre 12‐year longitudinal study with annual follow‐ups. Plasma ptau217 levels were measured on the fully automated LUMIPULSE platform, and individuals were classified as either ptau217+ (n = 174, mean age: 76.0) or ptau217‐ (n = 855, mean age: 74.7) based on a pre‐established threshold of 0.247 pg/mL. Diffusion‐weighted images were preprocessed using an in‐house pipeline to correct for eddy currents and image distortions due to magnetic field inhomogeneity, and diffusion tensors were fitted using FSL. A normalised grey matter image was used to mask normalised MD images to obtain cortical grey matter MD maps, which were subsequently analysed in a voxel‐wise GLM using SPM12, controlling for age and sex.ResultsAt baseline, there was no difference between groups in sex distribution, although individuals with elevated ptau217 levels were significantly older (p = 0.0001). After controlling for sex and age, the ptau217+ group showed significantly higher cortical MD in bilateral medial temporal (amygdala and hippocampus) and insular regions (insular and opercular cortices) compared to ptau217‐ (p <0.05, FDR‐corrected; Figure 1).ConclusionsIn our study of a large‐scale, well‐characterised cognitively unimpaired population with available diffusion weighted imaging, changes in cortical MD can already be observed in those with elevated plasma ptau217 in regions commonly associated with AD neuropathology. Further analysis on longitudinal MD changes in the same cohort are ongoing.

BackgroundGood sleep quality is essential for both physiological and mental health. It helps in clearing TAU and beta‐amyloid aggregates and consolidating memory, key processes in delaying dementia. Poor sleep is linked to reduced cognitive flexibility in daily life, likely due to decreased brain complexity, reflecting a reduced range of adaptive spatiotemporal brain dynamics. This study introduces a novel approach using non‐linear EEG analysis focused on low conventional bands to classify sleep quality in individuals with mild cognitive impairment (MCI), based on brain complexity.MethodResting‐state EEG was collected from 22 participants with MCI aged 60+, grouped by sleep quality (Pittsburgh Sleep Quality Index): 11 MCI with good sleep, and 11 MCI with poor sleep (Table 1). EEG data (128 channels, 5‐minute recordings) were normalized and decomposed using the Discrete Wavelet Transform to reach delta (1–4 Hz) and theta (4–8 Hz) bands. Ten non‐linear complexity features, namely approximate entropy, correlation dimension, detrended fluctuation analysis, energy, Higuchi fractal dimension, Hurst exponent, Katz fractal dimension, Boltzmann Gibbs entropy, Lyapunov exponent and Shannon entropy, were extracted from 5 second segments. Statistical measures (mean, standard deviation, 95th percentile, variance, median, kurtosis) were computed from these time‐distribution features. These statistics were then used for training and testing a set of classic machine learning classifiers, employing leave‐one‐out cross‐validation (Figure 2).ResultsBrain complexity successfully classified sleep quality in MCI, achieving an accuracy and area under the curve (AUC) of 1 in channel D13 (delta subband) using Quadratic Discriminant Analysis (QDA), and an accuracy of 0.94 and an AUC of 0.95 in channel B17 (theta subband) using the Extra Trees Classifier (ETC) (Figure 3).ConclusionSpecific machine learning classifiers distinguish excellently sleep quality in MCI using spatiotemporal complexity features from slow EEG subbands. The most relevant channels for group discrimination were primarily located in bilateral temporal regions of the neocortex known to be among the first affected in amnestic MCI, as previously shown in neuroimaging studies. Future longitudinal studies could investigate whether changes in brain complexity within these slow‐frequency temporal regions, influenced by sleep quality, are associated with an earlier or faster onset of dementia.

Understanding the spatial distribution of gliomas in the brain and their molecular subtypes can aid in the diagnosis and development of targeted therapies. This study aims to create probabilistic radiologic maps of glioma locations using large MRI datasets and the most recent consensus brain tumour classification. Neuroimaging data from multiple databases were analysed. Patients included had MRI T1 images and validated tumour segmentations. Probabilistic tumour maps were generated whereby binary tumour masks were aligned to a standard brain template and aggregated to compute voxel-wise frequency maps of glioma occurrence detailing glioma volume, molecular subtype, age, sex and overall survival with tumour location. The study included 2164 patients with gliomas. Key findings include distinct spatial patterns associated with glioma size and molecular subtype: smaller tumours favoured the left temporal region, medium-sized tumours the medial frontoparietal and bilateral temporal regions and larger tumours the frontotemporoparietal regions, predominantly on the right. Isocitrate dehydrogenase (IDH)-wild-type tumours were more common in medial parietotemporal regions, while IDH-mutant tumours were preferentially found in frontotemporal regions. Younger patients had more frontal tumours, while older patients had higher parieto-occipital tumour burdens. Tumours in medial structures and parietal lobes were linked to lower survival, whereas right temporal tumours were associated with higher rates of survival. These findings likely correlate with IDH mutation status. Leveraging eight glioma databases, probabilistic tumour maps revealed significant relationships between brain regions, molecular subtypes and clinical outcomes. These findings could be used in clinical decision-making and offer insights into glioma pathogenesis and treatment of patients impacted by this disease.

The therapeutic effect of magnetic resonance-guided focused ultrasound is generally not available to patients with a low skull density ratio (SDR). In this study, we investigated factors associated with treatment success in low-SDR cases with essential tremor and tremor-dominant Parkinson disease, and predictors of maximum temperature rise, with particular regard to regional skull conditions. We retrospectively analyzed 171 consecutive cases. Descriptive statistics for the entire skull and averages across 10 regions were obtained for SDR, skull thickness, and ultrasound incident angle (IA; smaller = more vertical). We divided 1024 ultrasonic transducer elements into 10 regions predefined by ExAblate 4000. Successful treatment was defined as < half the preoperative symptom score at 6 months postoperatively. First, univariate analysis of cases with an SDR < 0.40 was conducted to explore candidates for skull conditions associated with successful treatment. Subsequently, for all cases, regardless of SDR, several multiple regression models were built to predict the maximum temperature rise, and their performance was compared. Twenty-six cases had an SDR < 0.40, and treatment was successful in 15. Of those with an SDR < 0.40, the IA of the parietal region on the sonication side and the SDR of the bilateral temporal region tended to be smaller in the successful treatment group (not statistically significant). The maximum temperature was more accurately predicted when the model included the IA of the parietal region on the sonication side (Akaike Information Criterion, 777 [from 757]). Furthermore, replacing SDR with SDR excluding the bilateral temporal region enhanced predictions (Akaike Information Criterion, 777 [from 767]). The parietal IA on the sonication side and bilateral temporal SDR were associated with treatment success in low-SDR patients, which enabled more accurate prediction of maximum temperature rise. This finding will help identify suitable candidates among those with low-SDR.

Memory functional MRI (fMRI) has been used to explore cognitive processing in people with refractory temporal lobe epilepsy (TLE) to predict memory decline after anterior temporal lobe resection (ATLR). Traditional studies employed univariate analysis (UVA), focusing on isolated voxel activity in mesial temporal regions. By contrast, multivariate pattern analysis (MVPA), examines distributed activity patterns , offering deeper insight into neural networks supporting cognitive functions. MVPA allows precise mapping of individual memory encoding strategies that may influence surgical planning. Individual MVPA maps may be useful in the planning of surgical resection and trajectories for less-invasive procedures like laser interstitial thermotherapy (LiTT) to avoid critical brain regions. These may mitigate against the cognitive consequences of epilepsy surgery. We used MVPA to examine face and word encoding differences in healthy individuals and in people with TLE due to hippocampal sclerosis (HS). In healthy controls, medial temporal regions bilaterally supported face and word encoding. Lateral temporal regions were lateralized-right for faces and left for words. The fusiform gyri were involved in both tasks across all participants. HS patients showed altered encoding patterns, with reduced classifier accuracy (CA) in medial and lateral temporal regions. For face encoding, both left HS (LHS) and right HS (RHS) groups showed bilateral CA reductions in the parahippocampal gyrus (PHG), with additional hippocampal CA reduction in LHS. For word encoding, RHS patients showed CA reductions in right medial and bilateral lateral temporal regions, while LHS patients had reductions only in the left superior temporal gyrus (STG). These results highlight the bilateral network involved in memory encoding and the value of individualized cognitive mapping to prevent surgery-associated memory decline.

Women show declines in verbal memory across the menopause transition that may persist into the postmenopause. The goal of the present study was to characterize the patterns of brain activity and hippocampal functional connectivity that support verbal memory performance in midlife postmenopausal women. The study sample included 171 midlife postmenopausal women from the MsBrain I study (mean age = 59.3 years, mean education= 15.7 years, 87.7% white). All participants were cognitively normal, native English speakers, not taking menopausal hormone therapy. Participants completed neuropsychological (California Verbal Learning Test [CVLT]) and neuroimaging assessments, including an fMRI task of verbal encoding and recognition. Findings indicated that during verbal encoding, greater activation of bilateral prefrontal and medial temporal regions, as well as the precuneus, cuneus, caudate, and cerebellar regions, was associated with better performance on CVLT measures, including learning, short- and long-delay recall, and semantic clustering. Functional connectivity from both hippocampi to primarily right prefrontal regions during verbal encoding associated with better CVLT performance. In-scanner word recognition accuracy was more strongly associated with activation of parietal and occipital regions, and with functional connectivity between the right hippocampus and bilateral parietal and temporal regions. Our findings characterize the patterns underlying verbal memory abilities in midlife postmenopausal women. The patterns identified here may act as a foundation for better interpreting the effects of hormonal changes and menopausal symptoms on cognition at midlife, and for identifying neural targets for pharmacological and lifestyle interventions aimed at sustaining women's memory function.