Automatically parcellating the human cerebral cortex

Determining the atlas correspondence of Desikan-Killiany-Tourville and Glasser MMP1 atlases across magnetic field strengths

BACKGROUND

Over sixty-six brain atlases exist to parcellate the brain based on cytoarchitecture, function, and connectivity. Because atlas choice depends on individual study goals and hypotheses, variability in findings contributes to challenges in replication, validation, and reconciling the results across studies. Our goal was to measure the intersection of three commonly used atlases and create a tool to find regional correspondence between the atlases.

NEW METHOD

This study used three independent samples of anatomical MRI data acquired with different B0 magnetic field strengths: 1.5 Tesla (T), 3 T, and 7 T. The Desikan-Killiany- Tourville (DKT) and Glasser atlases were used to parcellate the brain. Coefficient-of- variation of regional volumes was measured to evaluate regional variability across subjects in each atlas. DKT and Glasser parcellation correspondence was calculated to answer the shared question of what Glasser regions intersect with a DKT region and vice versa and to investigate consistency of the parcellations in relation to each other across a variety of individuals and image resolutions.

RESULTS

We found that regional correspondence was consistent across field strengths for the DKT and Glasser parcellations despite showing population variability in volume, age, and sex, and was validated in the Schaefer400 atlas. Parcellation intersection data along with sample code to calculate specific regional correspondence is available.

COMPARISON WITH EXISTING METHODS

Prior studies have attempted to reconcile multiple atlases, but did not compare voxel- by-voxel on real data.

CONCLUSION

This analysis created a tool for researchers and can aid in comparisons with differing atlas choice and variable field strengths.

A road map to manual segmentation of cerebral structures

Manual segmentation is an essential tool in the researcher's technical arsenal. It is a frequent practice necessary for image analysis in many protocols, especially in neuroimaging and comparative brain anatomy. In the framework of emergence of studies focusing on alternative animal models, manual segmentation procedures play a critical role. Nevertheless, this critical task is often assigned to students, a process that, unfortunately, tends to be time-consuming and repetitive. Well-conducted and well-described segmentation procedures can potentially guide novice and even expert operators and enhance research works' internal and external validity, making it possible to harmonize studies and facilitate data sharing. Furthermore, recent advances in neuroimaging, such as ex vivo imaging or ultra-high-field MRI, enable new acquisition modalities and the identification of minute structures that are barely visible with typical approaches. In this context of increasingly detailed and multimodal brain studies, reflecting on methodology is relevant and necessary. Because it is crucial to implement good practices in manual segmentation per se but also in the description of the segmentation procedures in research papers, we propose a general roadmap for optimizing the technique, its process and the reporting of manual segmentation. For each of them, the relevant elements of the literature have been collected and cited. The article is accompanied by a checklist that the reader can use to verify that the critical steps are being followed.

Cortical volume alterations in the limbic network in adolescents with high reactive aggression

Previous studies show aggression-related structural alterations in frontal and limbic brain regions. Most studies have focused on overall aggression, instead of its subtypes, and on specific regions instead of networks. This study aims to identify both brain networks and regions that are associated with reactive and proactive subtypes of aggression. Structural MRI data were collected from 340 adolescents (125 F/215 M) with a mean age of 16.29 (SD = 1.20). Aggression symptomology was indexed via the Reactive Proactive Aggression Questionnaire (RPQ). Freesurfer was used to estimate Cortical Volume (CV) from seven networks and regions within specific networks associated with aggression. Two multivariate analyses of covariance (MANCOVAs) were conducted on groups for low versus higher reactive and proactive RPQ scores. Our reactive aggression MANCOVA showed a main effect in CV [F(14,321) = 1.935, p = 0.022,ηp2 = 0.078] across all the 7-Networks. Unpacking this main effect revealed significant volumetric differences in the right Limbic Network (LN) (p = 0.029) and the Temporal Pole (p = 0.011), where adolescents in the higher reactive aggression group showed higher cortical volumes. Such findings are consistent with region/voxel-specific analyses that have associated atypical structure within the LN and reactive aggression. Moreover, the temporal pole is highly interconnected with regions important in the regulation and initiation of reactive aggression.

Dependence of brain-tissue R2 on MRI field strength

PURPOSE

To quantify T2 relaxation in the brain at 3 T and 7 T to study its field dependence and correlation with iron content, and to investigate whether iron can be separated from other sources of T2 relaxation based on this field dependence.

METHODS

Nine subjects were scanned at both field strengths with the same acquisition technique, which used multiple gradient-echo sampling of a spin echo. This allowed for separation of T2 relaxation from static dephasing by B0 field inhomogeneities and the effects of radiofrequency refocusing imperfections. The average relaxation rates (R2 = 1/T2) in multiple regions of interest in the brain were fitted with a model linear in B0 and correlated with literature iron values.

RESULTS

The relationship between the R2 values at the two field strengths appeared to be linear over all regions of interest. The R2 values (in s-1) in the regions of interest for which both an iron and a lipid mass fraction have been documented in the literature were fitted asR 2 = 9 + 0.9 + 2 · 10 4 [ Fe ] + 5.7 [ lipid ] · B 0 $$ {\mathrm{R}}_2=9+\left(0.9+2\cdotp {10}^4\left[\mathrm{Fe}\right]+5.7\left[\mathrm{lipid}\right]\right)\cdotp {\mathrm{B}}_0 $$ , where[ Fe ] $$ \left[\mathrm{Fe}\right] $$ and[ lipid ] $$ \left[\mathrm{lipid}\right] $$ indicate the putative mass fractions of iron and lipid.

CONCLUSION

The R2 relaxation rate is well described by a constant plus a term linear in B0, with both iron and lipid content contributing to the slope. This indicates that the contributions of lipid and iron to R2 cannot be separated based solely on the field dependence of R2 in the field range of 3-7 T.

Late-onset GM2 gangliosidosis: magnetic resonance imaging, diffusion tensor imaging, and correlational fiber tractography differentiate Tay-Sachs and Sandhoff diseases

GM2 gangliosidosis is lysosomal storage disorder caused by deficiency of the heterodimeric enzyme β-hexosaminidase A. Tay-Sachs disease is caused by variants in HEXA encoding the α-subunit and Sandhoff disease is caused by variants in HEXB encoding the β-subunit. Due to shared clinical and biochemical findings, the two have been considered indistinguishable. We applied T1-weighted volumetric analysis, diffusion tensor imaging (DTI), and correlational fiber tractography to assess phenotypic differences in these two diseases. 51 T1-weighted and 40 DTI scans from 19 Late-Onset GM2 patients with either late-onset Sandhoff disease (LOSD), or late-onset Tay-Sachs (LOTS) were included and compared to 1033 neurotypical control volumetric MRI scans. LOTS patients had significantly smaller cerebellum volume compared to neurotypical controls (p < 0.0001) and LOSD patients (p < 0.0001). There was no statistical difference for the volume of any structure between LOSD and neurotypical controls. DTI analysis showed LOTS patients had higher mean diffusivity (MD) in the left cerebellum (p = 0.003703), right cerebellum (p = 0.003435), superior cerebellar peduncle (p = 0.007332), and vermis (p = 0.01007) compared to LOSD. LOTS patients had lower fractional anisotropy (FA) in the left cerebellum (p = 0.005537), right cerebellum (p = 0.01905), SCP (p = 0.02844), and vermis (p = 0.02469) when compared to LOSD. Correlational fiber tractography identified fiber tracts in cerebellar pathways with higher FA and lower MD in LOSD patients compared to LOTS patients. Our study shows neurobiologic differences between these two related disorders. To our knowledge, this is the first study using correlational tractography in a lysosomal storage disorder. This result indicates a greater burden of cerebellar pathology in LOTS patients compared with LOSD patients.

Neuroimaging Correlates of Traumatic Brain Injury in an Older Community-Dwelling Population: The Atherosclerosis Risk in Communities Study

BACKGROUND AND OBJECTIVES

Neuroimaging correlates of remote traumatic brain injury (TBI) are not well understood. Our objective was to examine associations of TBI with brain MRI markers of degeneration and vascular disease.

METHODS

We performed a cross-sectional analysis using data from a subset of participants who underwent a 3T brain MRI during the fifth Atherosclerosis Risk in Communities Study visit in 2011-2013. Prior TBI and age at first TBI (<18 years, 18-65 years, >65 years) was defined using self-report and International Classification of Diseases, Ninth Edition code data. We examined the following brain MRI metrics: presence of infarcts and microhemorrhages, white matter hyperintensity (WMH) volume, and the distribution of the number of regions of interest (ROIs) below a z-score cut-point of -1.5 for volumetrics, cortical thickness, and fractional anisotropy (FA) and above +1.5 for mean diffusivity (MD).

RESULTS

A total of 1,642 participants were included (mean age 76.8 ± 5.32 years, 61.0% female, 28.3% self-reported Black race, and 25.5% with a history of TBI [median time between first TBI and MRI: 38.2 years]). There was no evidence of differences in vascular imaging findings by overall TBI status, but individuals who sustained their first TBI at age <18 years had higher WMH volume (adjusted β = 0.22 mm3, 95% CI 0.00-0.43) and individuals who sustained their first TBI at age >65 years were more likely to have subcortical microhemorrhages (adjusted OR 1.69, 95% CI 1.03-2.75) compared with individuals without TBI. Compared with individuals without TBI, individuals with a history of TBI had a greater number of ROIs beyond the z-score cut-point for all metrics (smaller volumes, lower cortical thickness, lower FA, and higher MD). These findings were consistent among participants with first TBI sustained at age >65 years old, whereas participants with first TBI sustained at age <18 years old had a greater number of regions beyond the z-score cut-point only for FA and MD.

DISCUSSION

In this community-dwelling cohort of older adults, TBI was associated with smaller brain volumes, lower cortical thickness, lower FA, and higher MD. Further work is needed in the chronic postinjury period to elucidate the mechanisms underlying the observed structural changes after TBI.

Synchronous Theta Networks Characterize Successful Memory Retrieval

Memory retrieval activates regions across the brain, including not only the hippocampus and medial temporal lobe (MTL), but also frontal, parietal, and lateral temporal cortical regions. What remains unclear, however, is how these regions communicate to organize retrieval-specific processing. Here, we elucidate the role of theta (3-8 Hz) synchronization, broadly implicated in memory function, during the spontaneous retrieval of episodic memories. Analyzing a dataset of 382 neurosurgical patients (213 males, 168 females, and 1 unknown) implanted with intracranial electrodes who completed a free-recall task, we find that synchronous networks of theta phase synchrony span the brain in the moments before spontaneous recall, in comparison to periods of deliberation and incorrect recalls. Hubs of the retrieval network, which systematically synchronize with other regions, appear throughout the prefrontal cortex and lateral and medial temporal lobes, as well as other areas. Theta synchrony increases appear more prominently for slow (3 Hz) theta than for fast (8 Hz) theta in the recall-deliberation contrast, but not in the encoding or recall-intrusion contrasts, and theta power and synchrony correlate positively throughout the theta band. These results implicate diffuse brain-wide synchronization of theta rhythms, especially slow theta, in episodic memory retrieval.

Unsupervised identification of internal perceptual states influencing psychomotor performance

When humans perform repetitive tasks over long periods, their performance is not constant. People drift in and out of states that might be loosely categorised as engagement, disengagement or 'flow' and these states will be reflected in aspects of their performance (for example, reaction time, accuracy, criteria shifts and potentially longer-term strategy). Until recently it has been challenging to relate these behavioural states to the underlying neural mechanisms that generate them. Here, we acquired magnetoencephalograpy recordings and contemporaneous, dense behavioural data from participants performing an engaging task (Tetris) that required rapid, strategic behavioural responses over the period of an entire game. We asked whether it was possible to infer the presence of distinct behavioural states from the behavioural data and, if so, whether these states would have distinct neural correlates. We used hidden Markov Modelling to segment the behavioural time series into states with unique behavioural signatures, finding that we could identify three distinct and robust behavioural states. We then computed occipital alpha power across each state. These within-participant differences in alpha power were statistically significant, suggesting that individuals shift between behaviourally and neurally distinct states during complex performance, and that visuo-spatial attention change across these states.

Flexible nonlinear modeling reveals age-related differences in resting-state functional brain connectivity in autistic males from childhood to mid-adulthood

BACKGROUND

Divergent age-related functional brain connectivity in autism spectrum disorder (ASD) has been observed using resting-state fMRI, although the specific findings are inconsistent across studies. Common statistical regression approaches that fit identical models across functional brain networks may contribute to these inconsistencies. Relationships among functional networks have been reported to follow unique nonlinear developmental trajectories, suggesting the need for flexible modeling. Here we apply generalized additive models (GAMs) to flexibly adapt to distinct network trajectories and simultaneously describe divergent age-related changes from childhood into mid-adulthood in ASD.

METHODS

1107 males, aged 5-40, from the ABIDE I & II cross-sectional datasets were analyzed. Functional connectivity was extracted using a network-based template. Connectivity values were harmonized using COMBAT-GAM. Connectivity-age relationships were assessed with thin-plate spline GAMs. Post-hoc analyses defined the age-ranges of divergent aging in ASD.

RESULTS

Typically developing (TD) and ASD groups shared 15 brain connections that significantly changed with age (FDR-corrected p < 0.05). Network connectivity exhibited diverse nonlinear age-related trajectories across the functional connectome. Comparing ASD and TD groups, default mode to central executive between-network connectivity followed similar nonlinear paths with no group differences. Contrarily, the ASD group had chronic hypoconnectivity throughout default mode-ventral attentional (salience) and default mode-somatomotor aging trajectories. Within-network somatomotor connectivity was similar between groups in childhood but diverged in adolescence with the ASD group showing decreased within-network connectivity. Network connectivity between the somatomotor network and various other functional networks had fully disrupted age-related pathways in ASD compared to TD, displaying significantly different model curvatures and fits.

LIMITATIONS

The present analysis includes only male participants and has a restricted age range, limiting analysis of early development and later life aging, years 40 and beyond. Additionally, our analysis is limited to large-scale network cortical functional parcellation. To parse more specificity of brain region connectivity, a fine-grained functional parcellation including subcortical areas may be warranted.

CONCLUSION

Flexible non-linear modeling minimizes statistical assumptions and allows diagnosis-related brain connections to follow independent data-driven age-related pathways. Using GAMs, we describe complex age-related pathways throughout the human connectome and observe distinct periods of divergence in autism.

Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex

BACKGROUND

Depression impacts nearly 3% of the global adult population. Symptomatology is likely related to regions encompassing frontoparietal, somatosensory, and salience networks. Questions regarding deep brain nuclei (DBN), including the substantia nigra (STN), subthalamic nucleus (STN), and red nucleus (RN) remain unanswered.

METHODS

Using an existing structural neuroimaging dataset including 86 individuals (Baranger et al., 2021; nDEP = 39), frequentist and Bayesian logistic regressions assessed whether DBN volumes predict diagnosis, then structural covariance analyses in FreeSurfer tested diagnostic differences in deep brain volume and cortical morphometry covariance. Exploratory correlations tested relationships between implicated cortical regions and Hamilton Depression Rating Scale (HAM-D) scores.

RESULTS

Group differences emerged in deep brain/cortical covariance. Right RN volume covaried with left parietal operculum volume and central sulcus thickness, while left RN and right STN volumes covaried with right occipital pole volume. Positive relationships were observed within the unaffected group and negative relationships among those with depression. These cortical areas did not correlate with HAM-D scores. Simple DBN volumes did not predict diagnostic group.

CONCLUSION

Structural codependence between DBN and cortical regions may be important in depression, potentially for sensorimotor features. Future work should focus on causal mechanisms of DBN involvement with sensory integration.

Natural language processing models reveal neural dynamics of human conversation

Through conversation, humans engage in a complex process of alternating speech production and comprehension to communicate. The neural mechanisms that underlie these complementary processes through which information is precisely conveyed by language, however, remain poorly understood. Here, we used pre-trained deep learning natural language processing models in combination with intracranial neuronal recordings to discover neural signals that reliably reflected speech production, comprehension, and their transitions during natural conversation between individuals. Our findings indicate that the neural activities that reflected speech production and comprehension were broadly distributed throughout frontotemporal areas across multiple frequency bands. We also find that these activities were specific to the words and sentences being conveyed and that they were dependent on the word's specific context and order. Finally, we demonstrate that these neural patterns partially overlapped during language production and comprehension and that listener-speaker transitions were associated with specific, time-aligned changes in neural activity. Collectively, our findings reveal a dynamical organization of neural activities that subserve language production and comprehension during natural conversation and harness the use of deep learning models in understanding the neural mechanisms underlying human language.

Limbic system abnormalities in episodic cluster headache: a 7T MRI multimodal study

BACKGROUND

Although the limbic system has long been thought to be involved in the pathophysiology of cluster headache, inconsistencies in imaging studies of episodic cluster headache (eCH) patients and limited understanding of the specific regions within the limbic system have prevented a full explanation of its involvement in the disease. Therefore, we performed multimodal imaging analysis using 7 T MRI with the aim of exploring structural-functional abnormalities in subregions of the limbic system and their relationship with clinical features.

METHODS

In this cross-sectional study, we employed 7T MRI to investigate structural (volumetric) and functional (fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo)) alterations in limbic subregions (hypothalamus, thalamus, amygdala, hippocampus) among 69 in-bout but outside the attacks eCH patients and 63 healthy controls (HCs). Automated volumetry and resting-state functional MRI analyses were performed after adjusting for age, Generalized Anxiety Disorder scale, sex (and intracranial volume when evaluating volumetric measures). Then functional-structural coupling indices were computed to assess network-level relationships.

RESULTS

In eCH patients, volumes in right anterior inferior and right posterior of hypothalamus, left molecular_layer_hippocampal-head, left lateral-nucleus and left Central-nucleus on the headache side, as well as left tuberal inferior and left tuberal superior of hypothalamus, and right parasubiculum on the contralateral side were significantly altered compared with HCs (P < 0.05). Additionally, the volume of the right anterior inferior was positively correlated with the duration of last headache episode. After false discovery rate correction, widespread alterations in fALFF and ReHo values were observed among hypothalamic, thalamic, hippocampal, and amygdalar subregions, some of which correlated with clinical measures. Furthermore, the structure-function coupling indices in the right anterior inferior and the left lateral geniculate nucleus on the headache side differed significantly between eCH patients and HCs.

CONCLUSIONS

Our findings demonstrate that in-bout but outside the attacks eCH patients present anatomical and functional maladaptation of the limbic system. Moreover, the observed dissociation between localized abnormalities and largely preserved network coupling-except in the hypothalamus and thalamus-suggests that these two regions may be particularly susceptible to eCH-related dysfunction, while broader brain networks retain compensatory capacity in pathological states. These findings refine potential neuromodulation targets and highlight the value of ultrahigh-field imaging in eCH research.

Modulating limbic circuits in temporal lobe epilepsy: impacts on seizures, memory, mood and sleep

Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures that often originate within limbic networks involving amygdala and hippocampus. The limbic network is involved in crucial physiologic functions involving memory, emotion and sleep. Temporal lobe epilepsy is frequently drug-resistant, and people often experience comorbidities related to memory, mood and sleep. Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is an established therapy for temporal lobe epilepsy. However, the optimal stimulation parameters and their impact on memory, mood and sleep comorbidities remain unclear. We used an investigational brain sensing-stimulation implanted device to accurately track seizures, interictal epileptiform spikes (IES), and memory, mood and sleep comorbidities in five ambulatory subjects. Wireless streaming of limbic network local field potentials (LFPs) and subject behaviour were captured on a mobile device integrated with a cloud environment. Automated algorithms applied to the continuous LFPs were used to accurately cataloged seizures, IES and sleep-wake brain state. Memory and mood assessments were remotely administered to densely sample cognitive and behavioural response during ANT-DBS in ambulatory subjects living in their natural home environment. We evaluated the effect of continuous low-frequency and duty cycle high-frequency ANT-DBS on epileptiform activity and memory, mood and sleep comorbidities. Both low-frequency and high-frequency ANT-DBS paradigms reduced seizures. However, continuous low-frequency ANT-DBS showed greater reductions in IES, electrographic seizures and better sleep and memory outcomes. These results highlight the potential of synchronized brain sensing and dense behavioural tracking during ANT-DBS for optimizing neuromodulation therapy. While studies with larger patient numbers are needed to validate the benefits of low-frequency ANT-DBS, these findings are potentially translatable to individuals currently implanted with ANT-DBS systems.

A Case for Automated Segmentation of MRI Data in Neurodegenerative Diseases: Type II GM1 Gangliosidosis

BACKGROUND

Volumetric analysis and segmentation of magnetic resonance imaging (MRI) data is an important tool for evaluating neurological disease progression and neurodevelopment. Fully automated segmentation pipelines offer faster and more reproducible results. However, since these analysis pipelines were trained on or run based on atlases consisting of neurotypical controls, it is important to evaluate how accurate these methods are for neurodegenerative diseases. In this study, we compared five fully automated segmentation pipelines, including FSL, Freesurfer, volBrain, SPM12, and SimNIBS, with a manual segmentation process in GM1 gangliosidosis patients and neurotypical controls.

METHODS

We analyzed 45 MRI scans from 16 juvenile GM1 gangliosidosis patients, 11 MRI scans from 8 late-infantile GM1 gangliosidosis patients, and 19 MRI scans from 11 neurotypical controls. We compared the results for seven brain structures, including volumes of the total brain, bilateral thalamus, ventricles, bilateral caudate nucleus, bilateral lentiform nucleus, corpus callosum, and cerebellum.

RESULTS

We found volBrain's vol2Brain pipeline to have the strongest correlations with the manual segmentation process for the whole brain, ventricles, and thalamus. We also found Freesurfer's recon-all pipeline to have the strongest correlations with the manual segmentation process for the caudate nucleus. For the cerebellum, we found a combination of volBrain's vol2Brain and SimNIBS' headreco to have the strongest correlations, depending on the cohort. For the lentiform nucleus, we found a combination of recon-all and FSL's FIRST to give the strongest correlations, depending on the cohort. Lastly, we found segmentation of the corpus callosum to be highly variable.

CONCLUSIONS

Previous studies have considered automated segmentation techniques to be unreliable, particularly in neurodegenerative diseases. However, in our study, we produced results comparable to those obtained with a manual segmentation process. While manual segmentation processes conducted by neuroradiologists remain the gold standard, we present evidence to the capabilities and advantages of using an automated process that includes the ability to segment white matter throughout the brain or analyze large datasets, which pose feasibility issues to fully manual processes. Future investigations should consider the use of artificial intelligence-based segmentation pipelines to determine their accuracy in GM1 gangliosidosis, lysosomal storage disorders, and other neurodegenerative diseases.

Does Midbrain Atrophy Distinguish Progressive Supranuclear Palsy from Frontotemporal Dementia?

BACKGROUND

The diagnostic value of midbrain atrophy for distinguishing behavioral variant frontotemporal dementia (bvFTD) from progressive supranuclear palsy (PSP) is unclear.

OBJECTIVE

To investigate whether measures of midbrain atrophy differentiate PSP from bvFTD.

METHODS

We included four groups: healthy controls (n = 19), PSP-Richardson syndrome (n = 20), bvFTD (n = 19) and Parkinson's disease (PD; n = 12). The following quantitative and qualitative measures were calculated: Hummingbird sign rating scale [HBS-RS], global midbrain atrophy [GMA], midbrain area, midbrain/pons ratio, the Magnetic Resonance Parkinsonism Index (MRPI), the MRPI 2.0 and brainstem volume.

RESULTS

Compared to controls, PSP and bvFTD had lower values of midbrain area, HBS-RS and GMA, and higher MRPI and MRPI 2.0. HBS-RS, GMA, midbrain/pons ratio, midbrain area, MRPI, MRPI 2.0 and brainstem volume distinguished PSP from bvFTD with 73%, 67%, 75%, 83%, 71%, 69% and 82% accuracies, respectively.

CONCLUSIONS

Both quantitative and qualitative measures of midbrain atrophy provided modest accuracy in distinguishing PSP from bvFTD.

Measuring the associations between brain morphometry and polygenic risk scores for substance use disorders in drug-naive adolescents

Substance use has been associated with differences in adult brain morphology; however, it is unclear whether these differences precede or are a result of substance use substance use. We investigated the impact of polygenic risk scores (PRSs) for cannabis use disorder (CUD) and general substance use and substance use disorder liability (SU/SUD) on brain morphology in drug-naïve adolescents. Baseline data were used from 1,874 European-descent participants (ages 9-11) comprising 222, 328 and 387 pairs of MZ twins, DZ twins, and Non-Twin Siblings, respectively, in the Adolescent Brain Cognitive Development Study. We fitted multivariate twin models to estimate the putative effects of CUD, SU/SUD, and brain region-specific PRSs. These models assessed their influence on six subcortical and two cortical phenotypes. PRS for CUD and SU/SUD were created based on GWAS conducted by Johnson et al. (2020) and Hatoum et al. (2023), respectively. When decomposing variance in each brain region of interest (ROI), we used the corresponding ROI-specific PRS. Brain morphometry in drug-naive subjects was unrelated to CUD PRS. The variance explained in each ROI by its corresponding PRS ranged from 0.8-4.4%. The SU/SUD PRS showed marginally significant effects (0.2-0.4%) on cortical surface area and nucleus accumbens volume, but overall effect sizes were small. Our findings indicate that differences in brain morphometry among baseline drug-naive individuals are not associated with the genetic risk for CUD but show a weak association with general addiction and substance use risk (SU/SUD), particularly in nucleus accumbens volume and total cortical surface area.

Cardiac dysfunction is associated with indices of brain atrophy and cognitive impairment in heart failure with reduced ejection fraction

Cardiac dysfunction in heart failure with reduced ejection fraction (HFrEF) may contribute to brain atrophy and cognitive decline beyond that which is typical of healthy aging. This study tested the hypothesis that HFrEF would be associated with regionally unique brain remodeling and impaired cognitive performance independent of age. Furthermore, that cardiac index and clinical markers of HFrEF severity would predict brain remodeling and cognition with age and HFrEF, respectively. Cardiac function and brain morphology were assessed using magnetic resonance imaging in young healthy adults (24 ± 6 yr), older healthy adults (60 ± 6 yr), and patients living with HFrEF (59 ± 6 yr). The Montreal Cognitive Assessment was administered to assess cognition. Gray matter volume (GMV) (young: 492 ± 24, old: 456 ± 24, HFrEF: 433 ± 32 cm3, P ≤ 0.05) and cortical thickness (young: 2.44 ± 0.07, old: 2.33 ± 0.08, HFrEF: 2.22 ± 0.10 mm, P < 0.01) were lower with age and lowered further with HFrEF. Regional analysis revealed a unique pattern of atrophy with HFrEF. Whereas age had little effect on cortical curvature (P = 0.60), it was greater in HFrEF (young: 0.127 ± 0.003, old: 0.128 ± 0.003, HFrEF: 0.136 ± 0.005 mm-1, P < 0.01). Cardiac index was the best correlate of brain atrophy and cognitive performance with age (R = 0.33-0.47; P < 0.05). However, EF and end systolic volume index were better correlates of brain atrophy and cognitive performance in HFrEF (R = -0.50-0.49; P ≤ 0.05). These data indicate that lower GMV and cortical thickness in HFrEF are not merely an acceleration of age-related declines but reflect a unique pattern of brain atrophy and remodeling. In addition, classic markers of HF severity may be better predictors of pathological brain remodeling than reduced cardiac index.NEW & NOTEWORTHY Lower gray matter volume, and cortical thinning in heart failure are regionally dependent, and independent of age. Patients living with heart failure had higher cortical curvature, but older adults did not. Lower gray matter volume, cortical thinning, and cognitive impairment were associated with markers of cardiac dysfunction, with ejection fraction, and end systolic volume index being better predictors among the older and heart failure cohort than cardiac index.

Maintaining Brain Health: The Impact of Physical Activity and Fitness on the Aging Brain-A UK Biobank Study

The growing prevalence of physical and neurological disorders linked to aging poses significant challenges for society. Many of these disorders are closely linked to changes in brain structure and function, highlighting the importance of identifying protective factors that can preserve brain structure in later life and mitigate age-related decline. Physical activity (PA) is consistently linked to physical health and was found to mitigate age-related disorders. However, its effects on markers of brain aging remain inconclusive, partly due to reliance on underpowered studies and self-reported data. We investigated the effects of accelerometer-measured PA and physical fitness on BrainAGE, a machine-learning-derived marker of brain aging, in a large UK Biobank cohort. Using cortical and subcortical neuroimaging-derived features, a BrainAGE model was trained on 21,442 participants (mean absolute error: 3.75 years) and applied to predict BrainAGE for an independent sample of 10,874 participants. Accelerometer-measured moderate-intensity PA, but not self-reported PA, was associated with decelerated brain aging, indicated by a negative BrainAGE. Further, higher hand grip strength, along with lower body mass index (BMI), diastolic blood pressure (DBP), and resting heart rate, was linked to decelerated aging. These fitness measures impacted BrainAGE independently of PA. Additionally, fitness partially accounted for the relationship between PA and BrainAGE. Specifically, BMI, DBP, and resting heart rate showed a significant mediating effect, while grip strength did not. These findings highlight the interplay between PA and fitness in maintaining brain health and provide valuable insights for neuroscience and preventive health measures.

A functional parcellation of the whole brain in high-functioning individuals with autism spectrum disorder reveals atypical patterns of network organization

Researchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy high-functioning individuals with ASD and a group of seventy typically developing (TD) individuals. The rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates internal consistency and repeatability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ. We compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: (1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, (2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and (3) subcortical structures and the hippocampus are atypically integrated with the neocortex. These results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.

Ultrafast fMRI reveals serial queuing of information processing during multitasking in the human brain

The human brain is heralded for its massive parallel processing capacity, yet influential cognitive models suggest that there is a central bottleneck of information processing distinct from perceptual and motor stages that limits our ability to carry out two cognitively demanding tasks at once, resulting in the serial queuing of task information processing. Here we used ultrafast (199 ms TR), high-field (7T) fMRI with multivariate analyses to distinguish brain activity between two arbitrary sensorimotor response selection tasks when the tasks were temporally overlapping. We observed serial processing of task-specific activity in the fronto-parietal multiple-demand (MD) network, while processing in earlier sensory stages unfolded largely in parallel. Moreover, the MD network combined with modality-specific motor areas to define the functional characteristic of the central bottleneck at the stage of response selection. These results provide direct neural evidence for serial queuing of information processing and pinpoint the neural substrates undergirding the central bottleneck.

Opioidergic pain relief in humans is mediated by beta and high-gamma modulation in limbic regions

The nature of the neurophysiological effects of opioids, especially those responsible for their analgesic properties, are unknown, hindering efforts to develop non-addictive alternatives. Fentanyl and hydromorphone were administered to patients experiencing semi-chronic, clinically-relevant pain after surgical implantation of electrodes for the localization of seizure onset. Opioids suppressed beta oscillations in lateral amygdala, ventral and dorsolateral prefrontal cortices, and increased beta in medial amygdala and hippocampus. Opioids also suppressed high gamma oscillations in insula and lateral amygdala, and increased high gamma in cingulate cortex and hippocampus. The amplitude of these beta effects in the ventral prefrontal cortex, medial amygdala and hippocampus, and of gamma effects in the insula, were positively correlated with the magnitude of pain relief in response to a constant dose. These findings identify electrophysiological events in a network of limbic structures that may participate in opioidergic pain relief through nociceptive gating and a decreased concerned fixation on pain, providing insights into the neural basis of pain relief and suggesting possible biomarkers for developing non-addictive opioid alternatives.

Systematic bias in surface area asymmetry measurements from automatic cortical parcellations

Anatomical asymmetry is a hallmark of the human brain and may reflect hemispheric differences in its functional organization. Widely used software like FreeSurfer can automate neuroanatomical measurements and facilitate studies of hemispheric asymmetry. However, patterns of surface area lateralization measured using FreeSurfer are curiously consistent across diverse samples. Here, we demonstrate systematic biases in these measurements obtained from the default processing pipeline. We compared surface area asymmetry measured from reconstructions of original brains vs. the same scans after flipping their left-right orientation. The default pipeline returned implausible asymmetry patterns between the original and flipped brains: Many structures were always left- or right-lateralized. Notably, these biases occur prominently in key speech and language regions. In contrast, manual labeling and curvature-based parcellations of key structures both yielded the expected reversals of left/right lateralization in flipped brains. We determined that these biases result from discrepancies in how regional labels are defined in the left vs. right hemisphere in the default cortical parcellation atlases. These biases are carried into individual parcellations because the FreeSurfer parcellation algorithm prioritizes vertex correspondence to the template atlas relative to individual neuroanatomical variation. We further demonstrate several straightforward, bias-free approaches to measuring surface area asymmetry, including using symmetric registration templates and parcellation atlases, vertex-wise analyses, and within-subject curvature-based parcellations. These results highlight theoretical concerns about using only the default processing stream to make inferences about population-level brain asymmetry and underscore the need for validating bias-free neuroanatomical measurements, particularly when studying regions where structural lateralization may underlie functional lateralization.

Auditory cortex anatomy reflects multilingual phonological experience

This study examines whether auditory cortex anatomy reflects multilingual experience, specifically individuals' phonological repertoire. Using data from over 200 participants exposed to 1-7 languages across 36 languages, we analyzed the role of language experience and typological distances between languages they spoke in shaping neural signatures of multilingualism. Our findings reveal a negative relationship between the thickness of the left and right second transverse temporal gyrus (TTG) and participants' degree of multilingualism. Models incorporating phoneme-level information in the language experience index explained the most variance in TTG thickness, suggesting that a more extensive and more phonologically diverse language experience is associated with thinner cortices in the second TTG. This pattern, consistent across two datasets, supports the idea of experience-driven pruning and neural efficiency. Our findings indicate that experience with typologically distant languages appear to impact the brain differently than those with similar languages. Moreover, they suggest that early auditory regions seem to represent phoneme-level cross-linguistic information, contrary to the most established models of language processing in the brain, which suggest that phonological processing happens in more lateral posterior superior temporal gyrus (STG) and superior temporal sulcus (STS).

Scale-dependent brain age with higher-order statistics from structural magnetic resonance imaging

Inferring chronological age from magnetic resonance imaging (MRI) brain data has become a valuable tool for the early detection of neurodegenerative diseases. We present a method inspired by cosmological techniques for analyzing galaxy surveys, utilizing higher-order summary statistics with multivariate two- and three-point analyses in 3D Fourier space. This method identifies outliers while offering physiological interpretability, allowing the detection of scales where brain anatomy differs across age groups and providing insights into brain aging processes. Similarly to the evolution of cosmic structures, the brain structure also evolves naturally but displays contrasting behaviors at different scales. On larger scales, structure loss occurs with age, possibly due to ventricular expansion, while smaller scales show increased structure, likely related to decreased cortical thickness and gray/white matter volume. Using MRI data from the OASIS-3 database for the complete sample of 864 sessions (reduced sample: 827 sessions), our method predicts chronological age with a Mean Absolute Error (MAE) of 3.8 years (~3.6 years) for individuals aged ~40-100 (50-85), while providing information as a function of scale. A neural density posterior estimation shows that the 1- σ uncertainty for each individual varies between ~3 and 7 years, suggesting that, beyond sample variance, complex genetic or lifestyle-related factors may influence brain aging. Applying this method to an independent database, Cam-CAN, validates our analysis, yielding a MAE of ~3.4 for the age range from 18 to 88 years. This work demonstrates the utility of interdisciplinary research, bridging cosmological methods and neuroscience.

Protocol to perform offline ECoG brain-to-text decoding for natural tonal sentences

Here, we present a protocol to decode Mandarin sentences from invasive neural recordings using a brain-to-text framework. We describe steps for preparing materials, including designing the sentence corpus and setting up electrocorticography (ECoG) recording systems. We then detail procedures for decoding, such as data preprocessing, selection of speech-responsive electrodes, speech detection, syllable and tone decoding, and language modeling. We also outline performance evaluation metrics. For complete details on the use and execution of this protocol, please refer to Zhang et al.1.

Morphometric Measurement of Mean Cortical Curvature: Analysis of Alterations in Cognitive Impairment

Background and Objectives: Cognitive impairment, including mild cognitive impairment (MCI) and Alzheimer's disease (AD), is a growing public health concern. Early detection and an understanding of structural changes are crucial for accurate diagnosis and timely intervention. Cortical curvature, a morphometric measure derived from structural magnetic resonance imaging (MRI), has emerged as a potential biomarker for neurodegenerative processes. This study investigates the relationship between mean cortical curvature and cognitive impairment. Materials and Methods: A cross-sectional study was conducted with 58 participants, categorized into, first, cognitively impaired (CI) and non-cognitively impaired (NC) groups and, second, a normal cognitive group (NC), a mild cognitive performance group (MPG), and a low cognitive performance group (LPG) based on the Montreal Cognitive Assessment (MoCA) score. MRI data were acquired using a 3.0 Tesla scanner, and cortical reconstruction was performed using FreeSurfer 7.2.0. Mean cortical curvature values were extracted for 34 brain regions per hemisphere. Results: Significant differences in mean cortical curvature were found between the CI and NC groups. In the right hemisphere, statistically significant changes in mean curvature were observed in the isthmus cingulate (U = 188.5, p = 0.006), lingual (U = 202.5, p = 0.013), pars orbitalis (U = 221.5, p = 0.031), and posterior cingulate regions (U = 224.5, p = 0.035). In the left hemisphere, significant differences were detected in the cuneus (U = 226.5, p = 0.038) and posterior cingulate (U = 231.5, p = 0.046) regions. Analysis across three cognitive performance groups (NC, MPG, and LPG) showed significant curvature differences in the right isthmus cingulate (H(2) = 7.492, p = 0.024) and lingual regions (H(2) = 6.250, p = 0.044). Conclusions: Decreased mean cortical curvature in brain regions associated with cognitive function could be indicative of cognitive impairment and may reflect early neurodegenerative changes. These results highlight cortical curvature as a potential structural sign for cognitive impairment, showing the need for further investigation in longitudinal studies.

Validation of the Patient-Determined Disease Steps in ambulatory older adults with multiple sclerosis

INTRODUCTION

Multiple sclerosis (MS) is increasingly prevalent among older adults, and this results in the cumulative effects of aging and MS on mobility disability. The Patient-Determined Disease Steps (PDDS) is a patient-reported outcome measure of mobility disability in adults with MS, but its validity has not been established in older adults. This study validated the PDDS in older adults with MS by examining correlations with conceptually-relevant objective and subjective measures, including neuroimaging markers.

METHODS

The sample included older adults with MS (N = 87, mean age = 64.67 ± 4.24yrs, percent female = 65.5). Primary outcome measures for validation included the Timed 25-foot Walk (T25FW), Short Physical Performance Battery (SPPB), University of Alabama at Birmingham Life-Space-Assessment scale (UAB-LSA), Nine-Hole Peg Test (9HPT), oral Symbol-Digit Modalities Test (Oral SDMT), and Fatigue Severity Scale (FSS). Structural measures of brain integrity, evaluated via 3T MRI, included grey matter volumes (thalamus, caudate, putamen, globus pallidus, hippocampus), and total white matter lesion load (WMLL). Spearman correlations were used for analyses based on non-normality of the data.

RESULTS

Higher PDDS scores were significantly correlated with slower walking speed (T25FW time: ρ= 0.664, p < .001), worse lower extremity functioning (SPPB: ρ= -0.540, p < .001), poor fine motor dexterity (9HPT time) bilaterally (dominant hand: ρ= 0.367, p < .001; non-dominant hand: ρ= 0.263, p= .014), worse fatigue (FSS: ρ= 0.383, p < .001), and lower community mobility (UAB-LSA: ρ= -0.586, p < .001). Higher PDDS scores were also associated with lower grey matter volume in the caudate (ρ= -0.218, p= .042), putamen (ρ= -0.226, p= .036), and hippocampus (ρ= -0.213, p= .047). There were no significant correlations with WMLL, Oral SDMT, or socio-demographic covariates.

CONCLUSION

The PDDS is a valid self-report measure of MS-related disability in ambulatory older adults with MS.

Retrospective assessment of clinical global impression of severity and change in GM1 gangliosidosis: a tool to score natural history data in rare disease cohorts

BACKGROUND

Clinical trials for rare diseases pose unique challenges warranting alternative approaches in demonstrating treatment efficacy. Such trials face challenges including small patient populations, variable onset of symptoms and rate of disease progression, and ethical considerations, particularly in neurodegenerative diseases. In this study, we present the retrospective clinical global impression (RCGI) severity and change (RCGI-S/C) scale on 27 patients with GM1 gangliosidosis, a post hoc clinician-rated outcome measure to evaluate natural history study participants as historical controls for comparisons with treated patients in a clinical trial.

METHODS

We conducted a systematic chart review of 27 GM1 gangliosidosis natural history participants across 95 total visits. RCGI-S was assessed at the first visit and rated 1 (normal) to 7 (among the most extremely ill). Each subsequent follow-up was rated on the RCGI-C scale from 1 (very much improved) to 7 (very much worse). We demonstrate scoring guidelines of both scales with examples and justifications for this pilot in GM1 gangliosidosis natural history participants. The convergent validity of the RCGI scales was explored through correlations with magnetic resonance imaging (MRI) and the Vineland Adaptive Behavioral Scales.

RESULTS

We found strong association between the RCGI-S scores with gray matter volume (r(14) = -0.81; 95% CI [-0.93, -0.51], p < 0.001), and RCGI-C scores significantly correlated with increases in ventricular volume (χ2(1) = 18.6, p < 0.001). Baseline RCGI-S scores also strongly correlated with Vineland adaptive behavioral composite scores taken at the same visit (r(14) = -0.72; 95% CI [-0.93, -0.17], p = 0.02).

CONCLUSION

RCGI-S/C scales, which use the clinical evaluation to assess the severity of disease of each patient visit over time, were consolidated into a single quantitative metric in this study. Longitudinal RCGI-C scores allowed us to quantify disease progression in our late-infantile and juvenile GM1 patients. We suggest that the retrospective CGI may be an important tool in evaluating historical data for comparison with changes in disease progression/mitigation following therapeutic interventions.

Semiology of seizures with temporo-polar or "medio-lateral" temporal origin: A systematic review

A systematic review using PRISMA criteria was used to review the literature regarding the specific semiology of seizure arising (a) from the temporal pole or (b) from both medial and lateral temporal cortex. Evidence was analyzed with regard to information provided by intracranial EEG recordings and surgical outcomes, and an estimation of validity of reported signs and symptoms was performed. Semiology of seizures originating from the temporal pole was mostly related to diverse patterns of ictal spread rather than to the localization of seizure origin and comprised a wide variety of early signs and symptoms. Seizures with rapid involvement of temporo-medial and temporo-lateral cortex were intermediate in semiology between medial and lateral onset seizures and may have more frequently early automatisms and early vocalization than seizures arising from temporo-medial or temporo-lateral cortex only. Results of this review are discussed as to limiting factors of origin-based analyses for the understanding of seizure semiology.

Shaping the structural dynamics of motor learning through cueing during sleep

Enhancing the retention of recent memory traces through sleep reactivation is possible via Targeted memory reactivation (TMR), involving cueing learned material during posttraining sleep. Evidence indicates detectable short-term microstructural changes in the brain within an hour after motor sequence learning, and posttraining sleep is believed to contribute to the consolidation of these motor memories, potentially leading to enduring microstructural changes. In this study, we explored how TMR during posttraining sleep affects performance gains and delayed microstructural remodeling, using both standard diffusion tensor imaging and advanced neurite orientation dispersion and density imaging. Sixty healthy young adults participated in a 5 days protocol, undergoing five diffusion-weighted imaging sessions, pre- and post-two motor sequence training sessions, and after a posttraining night of either regular sleep (RS) or TMR. Results demonstrated rapid skill acquisition on day 1, followed by performance stabilization on day 2, and improvement on day 5, in both RS and TMR groups. (Re)training induced widespread microstructural changes in motor-related areas, initially involving the hippocampus, followed by a delayed engagement of the caudate nucleus. Mean Diffusivity changes were accompanied by increased neurite density index in the putamen, suggesting increased neurite density, while free water fraction reduction indicated glial reorganization. TMR-related structural differences emerged in the dorsolateral prefrontal cortex on day 2 and the right cuneus on day 5, suggesting unique sleep TMR-related neural reorganization patterns. Persistence of practice-related structural changes, although moderated over time, suggests a lasting neural network reorganization, partially mediated by sleep TMR.

Healthy dietary intake diminishes the effect of cerebral small vessel disease on cognitive performance in older adults

Introduction

We evaluated whether regular dietary intake of nutrients commonly found in fish, unsaturated oils, and nuts would moderate the associations between neuroimaging biomarkers of cerebral small vessel disease (cSVD) and cognitive function in older adults.

Methods

Dietary information, Montreal Cognitive Assessment (MoCA) scores, and magnetic resonance imaging (MRI) scans were collected from 71 older adults without dementia (60-86 years). MRI biomarkers of cSVD were calculated for each participant. Multivariate linear regression models were computed using dietary intake as the moderating variable. Covariates included age, sex, and estimated intracranial volume.

Results

Dietary intake moderated the association between several cSVD biomarkers and MoCA scores such that the expected negative association between cSVD biomarkers and cognition was seen at low levels of healthy dietary intake, but not at medium or high levels. A dietary intake by age moderation was not observed.

Discussion

Our findings indicate that healthy dietary intake may confer cognitive reserve against cSVD in older adults.

Multimodal Adaptations to Expiratory Musculature-Targeted Resistance Training: A Preliminary Study in Healthy Young Adults

PURPOSE

Exercise-induced adaptations, including neuroplasticity, are well studied for physical exercise that targets skeletal muscles. However, little is known about the neuroplastic potential of targeted speech and swallowing exercises. The current study aimed to gather preliminary data on molecular and functional changes associated with the neuroplastic effects of 4-week expiratory musculature-targeted resistance training in healthy young adults.

METHOD

Five healthy young adult men aged between 19 and 35 years, M (SD) = 28.8 (2.68) years, underwent 4 weeks of expiratory muscle strength training (EMST). We measured changes in maximum expiratory pressure (MEP), serum brain-derived neurotrophic factor (BDNF), and insulin-like growth factor 1 (IGF-1) levels at baseline and posttraining conditions. Furthermore, functional and structural magnetic resonance images were obtained to investigate the neuroplastic effects of EMST. We analyzed the effects of training using a linear mixed model for each outcome, with fixed effects for baseline and posttraining.

RESULTS

MEP and serum BDNF levels significantly increased posttraining. However, this effect was not observed for IGF-1. A significant increase in functional activation in eight regions was also observed posttraining. However, we did not observe significant changes in the white matter microstructure.

CONCLUSIONS

Preliminary data from our study suggest targeted resistance training of expiratory muscles results in molecular and neuroplastic adaptations similar to exercise that targets skeletal muscles. Additionally, these results suggest that EMST could be a potential intervention to modulate (or prime) neurotrophic signaling pathways linked to functional strength gains and neuroplasticity.

[18F]MK-6240 Radioligand Delivery Indices as Surrogates of Cerebral Perfusion: Bias and Correlation Against [15O]Water

[18F]MK-6240 PET (where MK-6240 is 6-(fluoro)-3-(1H-pyrrolo[2,3-c]pyridin-1-yl)isoquinolin-5-amine) is used to assess in vivo tau deposition across the Alzheimer disease (AD) spectrum. We aimed to quantify the associations and bias of early-frame [18F]MK-6240 PET as surrogates for cerebral perfusion against gold standard [15O]water PET and the potential impact of cerebral perfusion on [18F]MK-6240 tau quantification across aging and the AD spectrum. Methods: Fourteen cognitively normal (CN, 4 young CN and 10 old CN) and 3 AD participants underwent dynamic [18F]MK-6240 PET, with 9 undergoing arterial sampling. A subset (n = 11) underwent [15O]water PET. [18F]MK-6240 perfusion indices were estimated as radiotracer delivery indices K 1 (using 2-tissue-compartment models), and relative perfusion indices were estimated as R1 (using compartmental and reference tissue models, cerebellar gray matter reference region) and early-frame SUV ratio (0-3 min). [15O]water K 1 and R1 were estimated using 1-tissue-compartment models). [18F]MK-6240 tau burden was estimated using distribution volume ratio and SUV ratio at 90-110 min. Spearman correlations, linear mixed-effect models, and Bland-Altman analyses examined relationships between [18F]MK-6240 perfusion indices against [15O]water and between estimates of perfusion and tau burden in tau-relevant regions. The impact of partial-volume correction was examined. Results: Significant correlations were observed between [18F]MK-6240 K 1 and [15O]water K 1 (ρ = 0.57); However, [18F]MK-6240 K 1 underestimated [15O]water K 1 by up to 50%, with a strong negative proportional bias. Significant correlations were observed between [18F]MK-6240 relative perfusion and [15O]water R1 (ρ > 0.84), with minimal bias. In 2 AD participants, significant correlations were observed between perfusion and [18F]MK-6240 retention. Applying partial-volume correction did not significantly impact the correlations or improve the underestimations in [18F]MK-6240 K 1 Conclusion: Using head-to-head [18F]MK-6240 and [15O]water data, we showed that [18F]MK-6240 exhibited a relatively low extraction fraction, leading to underestimation of cerebral perfusion. Our results provide further support for [18F]MK-6240 R1 as a reliable estimate of relative cerebral perfusion, with strong associations and minimal bias compared with [15O]water. In addition, lower perfusion may be associated with higher [18F]MK-6240 retention in tau-relevant regions in AD. These findings further support the use of dynamic [18F]MK-6240 in dual-imaging assessments of tau burden and vascular health.

Changes in Negative Emotions Across Five Weeks of HRV Biofeedback Intervention were Mediated by Changes in Resting Heart Rate Variability

Resting heart rate variability (HRV) is typically higher in those with better emotional well-being. In the current study, we examined whether changes in resting HRV mediated changes in negative emotions during a 7-week clinical trial of HRV biofeedback. Younger and older adults were randomly assigned to one of two daily biofeedback practices for 5 weeks: (1) engage in slow-paced breathing to increase the amplitude of oscillations in heart rate at their breathing frequency (Osc+); or (2) engage in self-selected strategies to decrease heart rate oscillations (Osc-). We assessed negative emotion using the State Anxiety Inventory (SAI) and Profile of Mood States (POMS). Resting HRV at pre-intervention was significantly higher among those with lower negative emotion scores. Those participants showing greater increases in resting HRV showed greater decreases in negative emotion. In a mediation model with all participants, resting HRV changes significantly mediated the relationship between training performance (i.e., heart rate oscillation during practice sessions) and changes in negative emotion. However, additional analyses revealed this mediation effect was significantly moderated by condition and was only significant in the Osc+ condition. Thus, resting HRV changes mediated how biofeedback to increase amplitude of heart rate oscillations reduced negative emotion.

Patterns of cortical thickness in MCI patients with and without semantic impairment

BACKGROUND

About half of MCI patients experience semantic deficits, which may predict progression to Alzheimer's disease (AD). The neural basis of these deficits in MCI is not well understood. This study aimed to examine the relationship between semantic memory performance and cortical thickness in MCI patients.

METHODS

Using FreeSurfer, T1-weighted MRI scans were analyzed from MCI patients with (MCIsem+) and without (MCIsem-) semantic deficits. Correlation analyses across all participants, including healthy controls, examined the link between semantic memory and cortical thickness, controlling for age and education. Group comparisons of cortical thickness were also conducted between MCIsem+ and MCIsem- groups.

RESULTS

Significant correlations emerged between semantic memory performance and cortical thickness in the left medial temporal lobe, right temporal pole, and bilateral frontal regions-areas involved in central semantic and executive processes. Additionally, MCIsem + patients showed reduced cortical thickness in frontal, parietal, and occipital areas compared to MCIsem- patients.

CONCLUSION

Semantic memory performance in MCI patients is associated with structural differences in regions supporting both central and executive aspects of semantic processing. Given that MCIsem + patients may face higher risk of AD progression, longitudinal studies should investigate these cortical markers' predictive value.

Neural connectivity underlying core language functions

INTRODUCTION

Although many white matter tracts underlying language functions have been identified, even in aggregate they do not provide a sufficiently detailed and expansive picture to enable us to fully understand the computational processes that might underly language production and comprehension. We employed diffusion tensor tractography (DTT) with a tensor distribution model to more extensively explore the white matter tracts supporting core language functions. Our study was guided by hypotheses stemming largely from the aphasia literature.

METHODS

We employed high angular resolution diffusion imaging (HARDI) with a dual region of interest tractography approach. Our diffusion tensor distribution model uses a mixture of Wishart distributions to estimate the water molecule displacement probability functions on a voxel-by-voxel basis and to model crossing/branching fibers using a multicompartmental approach.

RESULTS

We replicated the results of previously published studies of tracts underlying language function. Our study also yielded a number of novel findings: 1) extensive connectivity between Broca's region and the entirety of the middle and superior frontal gyri; 2) extensive interconnectivity between the four subcomponents of Broca's region, pars orbitalis, pars triangularis, pars opercularis, and the inferior precentral gyrus; 3) connectivity between the mid-superior temporal gyrus and the transverse gyrus; 4) connectivity between the mid-superior temporal gyrus, the transverse gyrus, and the planum temporale and the inferior and middle temporal gyri; and 5) connectivity between mid- and anterior superior temporal gyrus and all components of Broca's region.

DISCUSSION

These results, which replicate the results of prior DTT studies, also considerably extend them and thereby provide a fuller picture of the structural basis of language function and the basis for a novel model of the neural network architecture of language function. This new model is entirely consistent with discoveries from the aphasia literature and with parallel distributed processing conceptualizations of language function.

Associations between structural brain changes and blood neurofilament light chain protein in treatment-resistant schizophrenia

OBJECTIVE

Around 30% of people with schizophrenia are refractory to antipsychotic treatment (treatment-resistant schizophrenia). Abnormal structural neuroimaging findings, in particular volume and thickness reductions, are often described in schizophrenia. Novel biomarkers of active brain pathology such as neurofilament light chain protein are now expected to improve current understanding of psychiatric disorders, including schizophrenia. This study explored whether treatment-resistant schizophrenia individuals exhibit different associations between plasma neurofilament light chain protein levels and regional cortical thickness reductions compared with controls.

METHODS

Plasma neurofilament light chain protein levels were measured, and T1-weighted magnetic resonance imaging sequences were obtained and processed via FreeSurfer for each participant. General linear models adjusting for age and body mass index were estimated to determine whether the interaction between diagnostic group and plasma neurofilament light chain protein level predicted lower cortical thickness across frontotemporal structures and the insula.

RESULTS

A total of 79 participants were included: 37 treatment-resistant schizophrenia and 42 healthy controls. Significant (false discovery rate-corrected) cortical thinning of the left (p = 0.005, η2p = 0.100) and right (p = 0.002, η2p = 0.149) insula, and left inferior temporal gyrus (p < 0.001, η2p = 0.143) was associated with higher levels of plasma neurofilament light chain protein in treatment-resistant schizophrenia, but not in healthy controls.

CONCLUSIONS

The association between regional thickness reduction of the bilateral insula and left inferior temporal gyrus with plasma neurofilament light chain protein may reflect a neuroprogressive component to schizophrenia, which is not observed in the normal population.

Assessment of the impact of reconstitution therapies-cladribine tablets and alemtuzumab-on the atrophy progression among patients with relapse-remitting multiple sclerosis

Introduction

Immune reconstitution therapies (IRT) are highly effective therapies for multiple sclerosis (MS). Among IRT, we can distinguish partially selective therapies such as cladribine in tablets (CLAD) and non-selective therapies, which include alemtuzumab (ALEM). Today, it is known that these therapies are effective in controlling the relapse activity of the disease and the progression of clinical disability, which has been proven both in clinical trials and in real world evidence (RWE). However, there is a lack of data assessing the effect of IRT on the neurodegenerative process, which is intensified in patients with MS. The aim of the study was to assess the effect of IRT treatment on the degree and pattern of brain atrophy in patients with MS during 3 years of observation.

Methods

Patients with relapsing-remitting MS (RRMS) treated with CLAD and ALEM were retrospectively recruited for the study. Demographic, clinical, and magnetic resonance imaging (MRI) data were collected at 4 time points: before the treatment and one, two, and three years after the treatment. MRI examinations were analyzed volumetrically using Freesurfer software. Global and regional changes in atrophy were assessed by calculating percentage changes in volume between time points. Results of drug groups were compared with each other.

Results

After 3 years of follow-up, statistically significant differences between groups were observed in hippocampus [p < 0.01] and amygdala volume changes [p < 0.01]. Ventral diencephalon atrophy was noted in both groups. On the other hand, in both groups, no significant atrophy of white and grey matter was noted. In addition, an increase in the thalamus volume was observed.

Discussion

In the studied groups, IRT therapies were shown to slow down the atrophy process in MS patients to a similar extent. These therapies may play a neuroprotective role by increasing the volume of the thalamus and hippocampus. The study was limited by the small number of both groups. Therefore, further studies are needed to fully assess the effect of reconstitution therapies on neurodegenerative processes in patients with RRMS.

The aging human brain exhibits reduced cerebrospinal fluid flow during sleep due to both neural and vascular factors

Aging reduces the quality and quantity of sleep, and greater sleep loss over the lifespan is predictive of neurodegeneration and cognitive decline. One mechanism by which sleep loss could contribute to impaired brain health is through disruption of cerebrospinal fluid (CSF) circulation. CSF is the primary waste transport system of the brain, and in young adults, CSF waves are largest during NREM sleep. However, whether sleep-dependent brain fluid physiology changes in aging is not known, due to the technical challenges of performing neuroimaging studies during sleep. We collected simultaneous fast fMRI and EEG data to measure large-scale CSF flow in healthy young and older adults and tested whether there were age-related changes to CSF dynamics during nighttime sleep. We found that sleep-dependent CSF flow was reduced in older adults, and this reduction was linked to impaired frontal EEG delta power and global hemodynamic oscillations during sleep. To identify mechanisms underlying reduced CSF flow, we used sensory and vasoactive stimuli to drive CSF flow in daytime task experiments, and found that both neural and cerebrovascular physiological changes contributed to the disruption of CSF flow during sleep. Finally, we found that this reduction in CSF flow was associated with gray matter atrophy in aging. Together, these results demonstrate that the aging human brain has reduced CSF flow during sleep, and identifies underlying neurovascular mechanisms that contribute to this age-related decline, suggesting targets for future interventions.

Polygenic scores for autism are associated with reduced neurite density in adults and children from the general population

Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.

Persistent impact of antenatal maternal anaemia on child brain structure at 6-7 years of age: a South African child health study

BACKGROUND

This study aimed to determine whether associations of antenatal maternal anaemia with smaller corpus callosum, caudate nucleus, and putamen volumes previously described in children at age 2-3 years persisted to age 6-7 years in the Drakenstein Child Health Study (DCHS).

METHODS

This neuroimaging sub-study was nested within the DCHS, a South African population-based birth cohort. Pregnant women were enrolled (2012-2015) and mother-child dyads were followed prospectively. A sub-group of children had magnetic resonance imaging at 6-7 years of age (2018-2022). Mothers had haemoglobin measurements during pregnancy and a proportion of children were tested postnatally. Maternal anaemia (haemoglobin < 11 g/dL) and child anaemia were classified using WHO and local guidelines. Linear modeling was used to investigate associations between antenatal maternal anaemia status, maternal haemoglobin concentrations, and regional child brain volumes. Models included potential confounders and were conducted with and without child anaemia to assess the relative roles of antenatal versus postnatal anaemia.

RESULTS

Overall, 157 children (Mean [SD] age of 75.54 [4.77] months; 84 [53.50%] male) were born to mothers with antenatal haemoglobin data. The prevalence of maternal anaemia during pregnancy was 31.85% (50/157). In adjusted models, maternal anaemia status was associated with smaller volumes of the total corpus callosum (adjusted percentage difference, - 6.77%; p = 0.003), left caudate nucleus (adjusted percentage difference, - 5.98%, p = 0.005), and right caudate nucleus (adjusted percentage difference, - 6.12%; p = 0.003). Continuous maternal haemoglobin was positively associated with total corpus callosum (β = 0.239 [CI 0.10 to 0.38]; p < 0.001) and caudate nucleus (β = 0.165 [CI 0.02 to 0.31]; p = 0.027) volumes. In a sub-group (n = 89) with child haemoglobin data (Mean [SD] age of 76.06 [4.84]), the prevalence of antenatal maternal anaemia and postnatal child anaemia was 38.20% (34/89) and 47.19% (42/89), respectively. There was no association between maternal and child anaemia (χ2 = 0.799; p = 0.372), and child anaemia did not contribute to regional brain volume differences associated with maternal anaemia.

CONCLUSIONS

Associations between maternal anaemia and regional child brain volumes previously reported at 2-3 years of age were consistent and persisted to 6-7 years of age. Findings support the importance of optimising antenatal maternal health and reinforce these brain regions as a future research focus.

Distinctive autophagy/mitophagy biomarker profiles in frontotemporal lobar degeneration and Alzheimer's disease

Maintaining cellular homeostasis by removing damaged and senescent mitochondria, a process termed mitophagy, is crucial in preventing Alzheimer's disease (AD) and represents a promising therapeutic target. Our previous research revealed altered mitophagy biomarkers, such as increased CSF and serum PINK1 and serum BNIP3L and decreased serum TFEB levels, indicating impaired autophagy-lysosomal degradation in the AD continuum. However, the role of autophagy/mitophagy in frontotemporal lobar degeneration (FTLD) remains unclear. This study investigated the biomarkers of autophagy/mitophagy and lysosomal biogenesis (PINK1, ULK1, BNIP3L, and TFEB) in biofluids (CSF and serum) from 308 biomarker-defined individuals across the FTLD continuum (FTLD-dementia, n = 29; FTLD-MCI, n = 33) and compared them with those across the AD continuum (MCI-AD, n = 100; AD-dementia, n = 100) and cognitively unimpaired (CU) controls (n = 46) recruited from Czech Brain Aging Study. Additionally, we compared the mitophagy biomarkers across different FTLD clinical subtypes (frontal, semantic and nonfluent variant) with CU, and explored the association between mitophagy biomarkers and clinical phenotypes of FTLD (biomarkers of tau, biomarkers of neurodegeneration, cognition and ATN profile).Our findings indicated a significantly lower CSF PINK1 and ULK1 levels in FTLD compared to AD, with FTLD dementia showing particularly low CSF PINK1 levels compared to AD-dementia. Conversely, CSF ULK1 levels were higher in FTLD-MCI compared to AD-dementia. Serum analyses revealed lower PINK1 and higher TFEB levels in FTLD dementia compared to AD dementia. This study provides compelling evidence of distinct alterations in autophagy/mitophagy biomarkers between FTLD and AD, indicating that these neurodegenerative diseases may affect the cellular waste disposal system through different pathways. This is the first study to explore mitophagy biomarkers in human CSF and serum in FTLD, opening avenues for further research and potential clinical applications.

A Case for Automated Segmentation of MRI Data in Milder Neurodegenerative Diseases

Background

Volumetric analysis and segmentation of magnetic resonance imaging (MRI) data is an important tool for evaluating neurological disease progression and neurodevelopment. Fully automated segmentation pipelines offer faster and more reproducible results. However, since these analysis pipelines were trained on or run based on atlases consisting of neurotypical controls, it is important to evaluate how accurate these methods are for neurodegenerative diseases. In this study, we compared 5 fully automated segmentation pipelines including FSL, Freesurfer, volBrain, SPM12, and SimNIBS with a manual segmentation process in GM1 gangliosidosis patients and neurotypical controls.

Methods

We analyzed 45 MRI scans from 16 juvenile GM1 gangliosidosis patients, 11 MRI scans from 8 late-infantile GM1 gangliosidosis patients, and 19 MRI scans from 11 neurotypical controls. We compared results for 7 brain structures including volumes of the total brain, bilateral thalamus, ventricles, bilateral caudate nucleus, bilateral lentiform nucleus, corpus callosum, and cerebellum.

Results

We found volBrain's vol2Brain pipeline to have the strongest correlations with the manual segmentation process for the whole brain, ventricles, and thalamus. We also found Freesurfer's recon-all pipeline to have the strongest correlations with the manual segmentation process for the caudate nucleus. For the cerebellum, we found a combination of volBrain's vol2Brain and SimNIBS' headreco to have the strongest correlations depending on the cohort. For the lentiform nucleus, we found a combination of recon-all and FSL's FIRST to give the strongest correlations depending on the cohort. Lastly, we found segmentation of the corpus callosum to be highly variable.

Conclusion

Previous studies have considered automated segmentation techniques to be unreliable, particularly in neurodegenerative diseases. However, in our study we produced results comparable to those obtained with a manual segmentation process. While manual segmentation processes conducted by neuroradiologists remain the gold standard, we present evidence to the capabilities and advantages of using an automated process including the ability to segment white matter throughout the brain or analyze large datasets, which pose feasibility issues to fully manual processes. Future investigations should consider the use of artificial intelligence-based segmentation pipelines to determine their accuracy in GM1 gangliosidosis, lysosomal storage disorders, and other neurodegenerative diseases.

Cognitive and brain health in juvenile myoclonic epilepsy: Role of social determinants of health

OBJECTIVE

Juvenile myoclonic epilepsy (JME) is a prevalent genetic generalized epilepsy with linked abnormalities in cognition, behavior, and brain structure. Well recognized is the potential for advancing understanding of the epigenetic contributions to the neurobehavioral complications of JME, but to date there has been no examination of the role of socioeconomic disadvantage in regard to the cognitive and brain health of JME, which is the focus of this investigation.

METHODS

Seventy-seven patients with JME and 44 unrelated controls underwent neuropsychological assessment, structural neuroimaging, and clinical interview to delineate epilepsy history and aspects of family status. The Area Deprivation Index characterized the presence and degree of neighborhood disadvantage, which was examined in relation to cognitive factor scores underlying a comprehensive neuropsychological test battery, academic metrics, integrity of brain structure, and family characteristics.

RESULTS

JME participants resided in neighborhoods associated with significantly more socioeconomic disadvantage, which was associated with significantly poorer performance across all three cognitive factor scores and reading fluency. JME was associated with significant reduction of total subcortical gray matter (GM) but not total cortical gray or white matter volumes. Among controls, participants residing in more advantaged areas exhibited increased volumes of total subcortical GM and diverse subcortical structures as well as areas of increased cortical thickness and volume in frontal/prefrontal regions, findings that were compromised or not evident in JME, raising the possibility of disease-related attenuation of socioeconomic advantage.

SIGNIFICANCE

Socioeconomic disadvantage in JME is associated with adverse effects on cognitive and academic status, whereas socioeconomic advantage in controls is associated with increased brain volumes and thickness, markers of brain health that were largely attenuated or absent in JME. The associations detected here argue for the need to better integrate the social determinants of health with genetic and epigenetic factors in advancing understanding of cognitive and brain health in JME.

The value of hippocampal sub-region imaging features for the diagnosis and severity grading of ASD in children

BACKGROUND

Hippocampal structural changes in Autism Spectrum Disorder (ASD) are inconsistent. This study investigates hippocampal subregion changes in ASD patients to reveal intrinsic hippocampal anomalies.

METHODS

A retrospective study from Hainan Children's Hospital database (2020-2023) included ASD patients and matched controls. We classified ASD participants based on severity, dividing all subjects into four groups: normal, mild, moderate, and severe. High-resolution T1-weighted MRI images were analyzed for hippocampal subregion segmentation and volume calculations using Freesurfer. Texture features were extracted via the Gray-Level Co-occurrence Matrix. The Receiver Operating Characteristic curve was used to evaluate seven random forest predictive models constructed from volume, subregion, and texture features, as well as their combinations following feature selection.

RESULTS

The study included 114 ASD patients (98 boys, 2-8 years; 16 girls, 2-6 years; 17 mild, 57 moderate, 40 severe) and 111 healthy controls (HCs). No significant differences in volumes were found between ASD patients and HCs (adjusted P-value >0.05). The seven random forest models showed that single volume and texture features performed poorly for ASD classification; however, integrating various feature types improved AUC values. Further selection of texture, subregion, and volume features enhanced AUC performance across normal and varying severity categories, demonstrating the potential value of specific subregions and integrated features in ASD diagnosis.

CONCLUSION

Random forest models revealed that hippocampal volume, texture features, and subregion characteristics are crucial for diagnosing and assessing the severity of ASD. Integrating selected texture and subregion features optimized diagnostic efficacy, while combining texture, subregion, and volume features further improved severity grading effectiveness.

The Cortical Asymmetry Index for subtyping dementia patients

OBJECTIVES

Frontotemporal dementia (FTD) usually shows more asymmetric atrophy patterns than Alzheimer's disease (AD). We aim to quantify this asymmetry to differentiate FTD, AD, and FTD subtypes.

METHODS

We studied T1-MRI scans, including FTD (different phenotypes), AD, and healthy controls (CTR). We defined the Cortical Asymmetry Index (CAI) using measures based on a metric derived from information theory with the cortical thickness measures. Some participants had additional follow-up MRIs, cerebrospinal fluid (CSF), or plasma measures. We analysed differences at cross-sectional and longitudinal levels. We then clustered FTD and AD participants based on the CAI values and studied the patients' fluid biomarker characteristics within each cluster.

RESULTS

A total of 101 FTD patients (64  ±  8 years, 53 men), 230 AD patients (65  ±  10 years, 84 men), and 173 CTR (59  ±  15 years, 67 men) were studied. CAI differentiated FTD, AD, and CTR. It also distinguished the semantic variant primary progressive aphasia (svPPA) from the other FTD phenotypes. In FTD, the CAI increased over time. The cluster analysis identified two subgroups within FTD, characterised by different neurofilament-light (NfL) levels, and two subgroups within AD, with different plasma glial fibrillary acidic protein (GFAP) levels. In AD, CAI correlated with GFAP and Mini-Mental State Examination (MMSE); in FTD, the CAI was associated with NfL levels.

CONCLUSIONS

The proposed method quantifies asymmetries previously described visually. The CAI could define clinically and biologically meaningful disease subgroups in the differential diagnosis of AD and FTD and its subtypes. CAI could also be of interest in tracking disease progression in FTD.

KEY POINTS

Question There is a need to find quantitative metrics from MRI that can identify disease subgroups, and that could be useful for diagnosis and tracking. Findings We propose a Cortical Asymmetry Index that differentiates Alzheimer's disease (AD) from Frontotemporal dementia (FTD), distinguishes FTD subtypes, correlates with NFL and GFAP levels, and monitors FTD progression. Clinical relevance Our proposed index holds the potential to support clinical applications for diagnosis and disease tracking in AD and FTD, using a quantitative summary metric from MRI data. It also contributes to the understanding of these diseases.

Volume Changes in Brain Subfields of Patients with Alzheimer's Disease After Transcranial Ultrasound Stimulation

Background/Objectives: Alzheimer's disease (AD) is characterized by progressive brain atrophy marked by cognitive decline and memory loss, which significantly affect patients' quality of life. Transcranial ultrasound stimulation (TUS) is a potential physical treatment for AD patients. However, the specific brain regions stimulated by TUS and its therapeutic effects remain unclear. Methods: In this study, magnetic resonance imaging (MRI) and FreeSurfer segmentation were employed to assess alterations in the brain volume of AD patients after TUS. Results: Our findings revealed significant volume increases in the corpus callosum (CC) and lateral orbitofrontal cortex (lOFC) in the TUS group. Moreover, the volumetric changes in the CC were strongly correlated with improvements in the Mini-Mental State Examination score, which is a widely used measure of cognitive function of AD patients. Conclusions: TUS has the potential to alleviate disease progression and offers a non-invasive therapeutic approach to the improvement of cognitive function in AD patients.

Preserved Serotonin Transporter Availability in Parkinson Disease Measured with Either [11C]MADAM or [11C]DASB: A Study Including 2 Separate Cohorts of Nondepressed Patients

Serotonin transporter (SERT) availability was assessed using 2 tracers, [11C]N,N-dimethyl-2-(2-amino-4-cyanophenylthio)benzylamine ([11C]DASB) and [11C]N,N-dimethyl-2-(2-amino-4-fluoromethylphenylthio)benzylamine) ([11C]MADAM), in independent cohorts of patients and controls. This study aimed to independently confirm whether SERT remains intact in nondepressed individuals with early-stage Parkinson disease (PD), because the use of diverse methodologies could potentially yield disparate results. Methods: Seventeen PD patients (5 women and 12 men; age, 64 ± 7 y; Unified Parkinson's Disease Rating Scale motor score, 23 ± 5; Beck Depression Inventory score, 5 ± 4) and 20 age- and sex-matched healthy controls underwent [11C]MADAM PET at Karolinska Institutet. Fifteen PD patients (5 women and 10 men; age, 59 ± 9 y; Unified Parkinson's Disease Rating Scale motor score, 15 ± 7; Beck Depression Inventory score, 4 ± 4) and 8 controls were examined with [11C]DASB PET at the University of British Columbia. PET scans were performed at both institutions using a high-resolution research tomograph. A simplified reference tissue model and Logan graphical analysis were used to calculate the regional nondisplaceable binding potential (BPND), using the cerebellum as the reference. Parametric BPND images were generated using wavelet-aided parametric imaging. MRI-defined volumes of interest included cortical and subcortical regions, as well as brain stem nuclei. Results: There were no significant differences between controls and early-stage PD patients in either the [11C]DASB or the [11C]MADAM cohort, regardless of the analysis method. Group differences (Cohen d) in the [11C]DASB cohort ranged from 0.34 to 0.86 in brain stem nuclei, 0.09 to 0.61 in subcortical regions, and 0.28 to 0.70 in cortical regions. In the [11C]MADAM cohort, they ranged from 0.16 to 0.40, 0.19 to 0.55, and 0.32 to 0.61, respectively. Logan BPND highly correlated with simplified reference tissue model BPND for both tracers in each group (P < 0.001). Conclusion: SERT availability is relatively preserved in nondepressed patients with PD. This study suggests that serotonergic degeneration is not a major feature of the disease in nondepressed patients with nonadvanced disease.

Parallel hierarchical encoding of linguistic representations in the human auditory cortex and recurrent automatic speech recognition systems

The human brain's ability to transform acoustic speech signals into rich linguistic representations has inspired advancements in automatic speech recognition (ASR) systems. While ASR systems now achieve human-level performance under controlled conditions, prior research on their parallels with the brain has been limited by the use of biologically implausible models, narrow feature sets, and comparisons that primarily emphasize predictability of brain activity without fully exploring shared underlying representations. Additionally, studies comparing the brain to text-based language models overlook the acoustic stages of speech processing, an essential part in transforming sound to meaning. Leveraging high-resolution intracranial recordings and a recurrent ASR model, this study bridges these gaps by uncovering a striking correspondence in the hierarchical encoding of linguistic features, from low-level acoustic signals to high-level semantic processing. Specifically, we demonstrate that neural activity in distinct regions of the auditory cortex aligns with representations in corresponding layers of the ASR model and, crucially, that both systems encode similar features at each stage of processing-from acoustic to phonetic, lexical, and semantic information. These findings suggest that both systems, despite their distinct architectures, converge on similar strategies for language processing, providing insight in the optimal computational principles underlying linguistic representation and the shared constraints shaping human and artificial speech processing.

Characterizing the microstructural transition at the gray matter-white matter interface: Implementation and demonstration of age-associated differences

BACKGROUND

The cortical gray matter-white matter interface (GWI) is a natural transition zone where the composition of brain tissue abruptly changes and is a location for pathologic change in brain disorders. While diffusion magnetic resonance imaging (dMRI) is a reliable and well-established technique to characterize brain microstructure, the GWI is difficult to assess with dMRI due to partial volume effects and is normally excluded from such studies.

METHODS

In this study, we introduce an approach to characterize the dMRI microstructural profile across the GWI and to assess the sharpness of the microstructural transition from cortical gray matter (GM) to white matter (WM). This analysis includes cross-sectional data from a total of 146 participants (18-91 years; mean age: 52.4 (SD 21.4); 83 (57 %) female) enrolled in two normative lifespan cohorts at Albert Einstein College of Medicine from 2019 to 2023. We compute the aggregate GWI slope for each parameter, across each of 6 brain regions (cingulate, frontal, occipital, orbitofrontal, parietal, and temporal) for each participant. The association of GWI slope in each region with age was assessed using a linear model, with biological sex as a covariate.

RESULTS

We demonstrate this method captures an inherent change in fractional anisotropy (FA), axial diffusivity (AD), orientation dispersion index (ODI) and intracellular volume fraction (ICVF) across the GWI that is characterized by small variance. We identified statistically significant associations of FA slope with age in all regions (p < 0.002 for all analyses), with FA slope magnitude inversely associated with higher age. Similar statistically significant age-related associations were found for AD slope in cingulate, occipital, and temporal regions, for ODI slope in parietal and occipital regions, and for ICVF slope in frontal, orbitofrontal, parietal, and temporal regions.

CONCLUSION

The inverse association of slope magnitude with age indicates loss of the sharp GWI transition in aging, which is consistent with processes such as dendritic pruning, axonal degeneration, and inflammation. This method overcomes techniques issues related to interrogating the GWI. Beyond characterizing normal aging, it could be applied to explore pathological effects at this crucial, yet under-researched region.