Thresholding of statistical maps in functional neuroimaging using the false discovery rate

Disrupted default mode network connectivity and its role in negative symptoms of schizophrenia

Schizophrenia is a complex mental disorder characterised by positive symptoms, negative symptoms, and cognitive deficits, with recent studies suggesting that disruptions in the default mode network (DMN) may underlie many of these symptoms. In this study, we used graph theory analysis of resting-state functional magnetic resonance imaging data to investigate differences in the topological organisation and functional connectivity of the DMN in patients with schizophrenia, using two independent datasets of patients and healthy controls. The findings revealed significant group differences in the DMN of patients with schizophrenia, particularly within the core-medial temporal lobe (MTL) subsystem, characterised by lower shortest path length, clustering coefficient, and small-worldness, indicating less efficient network organisation. Weaker functional connectivity in the core-MTL subsystem was correlated with higher avolition-apathy scores, highlighting the role of DMN connectivity patterns in negative symptoms. These results, validated across two independent datasets, emphasise the robust and generalisable association between schizophrenia and DMN network features, less efficient topological properties, and weaker functional connectivity. This underscores the importance of targeting DMN connectivity to alleviate negative symptoms, improve clinical outcomes, and potentially serve as a biomarker for monitoring symptom severity and guiding treatment.

Differential neural decoding of alarm and avoidance information from vocal alarm calls in humans

Many animals and humans use scream calls to signal imminent threats, which typically evoke alarm and escape responses in recipients. Compared to animals, human scream calls are more diversified with varying levels of alarm signaling. Certain low-alarm human screams thus might not elicit full neural alarm cascades and threat avoidance actions. Here we investigated the neural circuits for decoding alarm and avoid-approach information from positive and negative scream calls in humans. Alarm and avoid-approach decisions showed minimal neural overlap, with alarm decisions recruiting neural cascades of sensory-affective decoding for action preparation, whereas avoid-approach judgments recruited neural systems for spatio-affective decoding for social decision-making. Furthermore, decision patterns revealed both an alarm quotient and an avoid quotient for risk arbitration, which linked the likelihood of an urgent response (alarm, avoid) to a slowing of choosing a potential safe option in response to scream calls. While the avoid quotient positively predicted neural activity in a broad cortico-limbic network, the alarm quotient predicted neural suppression with increasing alarm levels, especially in the amygdala as part of a presumed limbic alarm system. This points to a critical involvement of the amygdala at neural levels of choice arbitrations rather than in threat evaluations signaled by screams.

Low intensity gamma-frequency TMS safely modulates gamma oscillations in probable mild Alzheimer's dementia: a randomized 2 × 2 crossover pilot study

Introduction

AD is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. While traditional treatments targeting beta-amyloid accumulation have shown limited success, there is a pressing need for novel therapeutic approaches. Recent studies have highlighted the role of disrupted gamma oscillations in AD pathology, leading to the exploration of gamma neuromodulation as a potential therapeutic strategy to modify disease progression in individuals with AD dementia. This pilot clinical trial aimed to investigate the electrophysiological effects of low intensity gamma transcranial magnetic stimulation (gTMS) on gamma oscillations in patients with a diagnosis of probable mild AD dementia.

Methods

Employing a randomized, double-blind, sham-controlled, 2 × 2 crossover design, participants underwent a single session of both real low intensity gTMS and sham stimulation. EEG recordings and cognitive assessments were conducted before and after stimulation to assess changes in brain activity and their impact on episodic memory.

Results

We observed statistically significant changes in EEG activity (n = 14), indicating transient modulation of gamma oscillations immediately after low intensity gTMS. There was no significant improvement in cognition compared to baseline scores, but we evidenced a positive correlation between electrophysiological changes and cognitive outcome. Importantly, the intervention was well-tolerated, with no significant adverse effects reported.

Discussion

Low intensity gTMS has shown the capability to induce significant changes in brain activity, particularly in gamma oscillations. These findings suggest that low intensity gTMS holds promise as a safe and non-invasive therapeutic approach, challenging the conventional belief that high intensity magnetic pulses are necessary for effective brain modulation. To corroborate these initial findings, further research with extended intervention durations and larger, well-defined cohorts of patients with mild AD dementia is essential. This will validate the potential benefits of low intensity gTMS on cognitive performance in this population.

Clinical trial registration

https://clinicaltrials.gov/study/NCT05784298?term=NCT05784298&rank=1, NCT05784298.

Childhood abuse and neglect are differentially related to perceived discrimination and structural change in empathy-related circuitry

Behavioral studies indicate that adverse childhood experiences (ACE) are associated with altered empathic responding, but the neural mechanisms underlying this relationship remain unclear. Given the significance of empathy in contexts marred by historical conflict and systemic inequality, work on these mechanisms is particularly important in such contexts. The current study extends previous work by (1) examining associations of different dimensions of ACE with volumetric change in empathy-related circuitry, (2) distinguishing between trait and state empathy, and (3) including perceived discrimination as an additional psychosocial stressor. Thirty-nine healthy South African adults from the general population (Mage = 40.6 years) underwent 3 T MRI. FreeSurfer v6.0 was used to extract predefined volumes subserving empathy. Results showed that childhood abuse and perceived discrimination were associated with reduced state empathic concern, whereas childhood neglect was associated with reduced trait cognitive empathy. Childhood abuse was furthermore associated with volumetric increases in frontolimbic (hippocampus, anterior cingulate cortex (ACC)) and neocortical (superior frontal and temporal) regions subserving affective and cognitive empathy, and uniquely mediated the relationship between ACC volume and perceived discrimination. The association of ACE with altered empathic responding may thus be underpinned by specific circuitry reflective of adversity type, with childhood abuse contributing to heightened responsivity to socioemotional cues.

Perinatal SSRI exposure impacts innate fear circuit activation and behavior in mice and humans

Before assuming its role in the mature brain, serotonin modulates early brain development across phylogenetically diverse species. In mice and humans, early-life SSRI exposure alters the offspring's brain structure and is associated with anxiety and depression-related behaviors beginning in puberty. However, the impact of early-life SSRI exposure on brain circuit function is unknown. To address this question, we examined how developmental SSRI exposure changes fear-related brain activation and behavior in mice and humans. SSRI-exposed mice showed increased defense responses to a predator odor, and stronger fMRI amygdala and extended fear-circuit activation. Likewise, adolescents exposed to SSRIs in utero exhibited higher anxiety and depression symptoms than unexposed adolescents and also had greater activation of the amygdala and other limbic structures when processing fearful faces. These findings demonstrate that increases in anxiety and fear-related behaviors as well as brain circuit activation following developmental SSRI exposure are conserved between mice and humans. These findings have potential implications for the clinical use of SSRIs during human pregnancy and for designing interventions that protect fetal brain development.

Dose-dependent changes in global brain activity and functional connectivity following exposure to psilocybin: a BOLD MRI study in awake rats

Psilocybin is a hallucinogen with complex neurobiological and behavioral effects. This is the first study to use MRI to follow functional changes in brain activity in response to different doses of psilocybin in fully awake, drug naive rats. We hypothesized that psilocybin would show a dose-dependent increase in activity in the prefrontal cortex and thalamus, while decreasing hippocampal activity. Female and male rats were given IP injections of vehicle or psilocybin in doses of 0.03 mg/kg, 0.3 mg/kg, and 3.0 mg/kg while fully awake during the imaging session. These levels were validated by measuring psilocybin and its metabolite, psilocin. Changes in BOLD signal were recorded over a 20 min window. Data for resting state functional connectivity were collected approximately 35 min post injection. All data were registered to rat 3D MRI atlas with 169 brain areas providing site-specific changes in global brain activity and changes in functional connectivity. Treatment with psilocybin resulted in a significant dose-dependent increase in positive BOLD signal. The areas most affected by the acute presentation of psilocybin were the somatosensory cortex, basal ganglia and thalamus. Males and females showed different sensitivity to psilocybin dose, with females exhibiting greater activation than males at 0.3 mg/kg, especially in thalamic and basal ganglia regions. There was a significant dose-dependent global increase in functional connectivity, highlighted by hyperconnectivity to the cerebellum. Brain areas hypothesized to be involved in loss of sensory filtering and organization of sensory motor stimuli, such as the cortico-striato-thalamo-cortical circuit and the claustrum, showed increased activation at higher doses of psilocybin. Indeed, the general neuroanatomical circuitry associated with the psychedelic experience was affected but the direction of the BOLD signal and pattern of activity between neural networks was inconsistent with the human literature.

Social Buffering of Posttraumatic Stress Disorder: Longitudinal Effects and Neural Mediators

BACKGROUND

Posttraumatic stress disorder (PTSD) is a well-characterized psychiatric disorder that features changes in mood and arousal following traumatic events. Previous animal and human studies of social support during the peritraumatic window have demonstrated a buffering effect with regard to acute biological and psychological stress symptoms. Fewer studies have explored the magnitude of and mechanism through which early posttrauma social support can reduce longitudinal PTSD severity.

METHODS

In this study, we investigated the beneficial impact of social support on longitudinal PTSD symptoms and probed brain regions sensitive to this buffering phenomenon, such as the amygdala and ventromedial prefrontal cortex. In the multisite AURORA study, 315 participants reported PTSD symptoms (PTSD Checklist for DSM-5) and perceived emotional support (Patient-Reported Outcomes Measurement Information System) at 2 weeks, 8 weeks, 3 months, and 6 months post emergency department visit. Additionally, neuroimaging data were collected at 2 weeks posttrauma.

RESULTS

We hypothesized that early posttrauma social support would be linked with greater fractional anisotropic values in white matter tracts that have known connectivity between the amygdala and prefrontal cortex and would predict reduced neural reactivity to social threat cues in the amygdala. Interestingly, while we observed greater fractional anisotropy in the bilateral cingulum and bilateral uncinate fasciculus as a function of early posttrauma emotional support, we also identified greater threat reactivity in the precuneus/posterior cingulate, a component of the default mode network.

CONCLUSIONS

Our findings suggest that the neurocircuitry underlying the response to social threat cues is facilitated through broader pathways that involve the posterior hub of the default mode network.

Structural brain alterations and clinical associations in individuals with chronic nonspecific neck pain

BACKGROUND

Chronic pain is associated with changes in brain structures. However, the specific morphological changes in chronic nonspecific neck pain (CNSNP) are still unclear.

OBJECTIVES

To investigate altered brain morphology in patients with CNSNP and its relationships with clinical characteristics of neck pain.

DESIGN

Cross-sectional study.

METHODS

Thirty CNSNP and 30 controls underwent T1-weighted structural MRI to assess whole-brain vertex-wise cortical thickness and gray matter volume. Between-group differences were determined using cluster-wise correction for multiple comparisons and analyses of global structure and pain-related regions of interest (ROIs). Pain outcomes were neck pain duration, intensity, disability and pressure pain thresholds (PPTs) over the cervical spine.

RESULTS

Overall, the cluster-wise analysis revealed increased cortical thickness and decreased gray matter volume in several brain regions such as the precuneus, supramarginal gyrus and parietal cortex in the neck pain group (CWP<0.05). The global analysis showed that the neck pain group had increased total thickness and decreased total volume (p < 0.05). The ROI analysis showed that the neck pain group exhibited increased thickness in the primary somatosensory cortex (S1), anterior cingulate cortex (ACC) and precuneus and decreased volume in the prefrontal cortex (PFC), S1, ACC and insula compared to controls (adjusted p-values<0.05). Reduced insula volume correlated with greater neck disability (r = -0.53, adjusted p-value<0.01). Increased PPTs correlated with greater S1 and precuneus thickness (r = 0.46-0.48, adjusted p-values<0.05) and S1 volume (r = 0.53-0.58, adjusted p-values<0.05).

CONCLUSION

Patients with CNSNP exhibited increased cortical thickness and decreased gray matter volume in brain regions involved in pain processing and emotional and cognitive responses.

Influence of chronic pain on regional brain volume reduction in a general older Japanese population: a longitudinal imaging analysis from the Hisayama Study

Longitudinal analyses of the influence of chronic pain on pain-related regional brain volumes in general populations are warranted. This prospective cohort study investigated the association between the presence of chronic pain at baseline and the subsequent changes in pain-related regional brain volumes among Japanese community-dwelling older residents. Participants aged 65 years or older who underwent brain magnetic resonance imaging (MRI) scans in both 2012 and 2017 were included. According to the presence or absence of chronic pain (defined as pain lasting for longer than 3 months) in 2012, participants were categorized into a 'chronic pain' group and 'no chronic pain' group. Region-of-interest analyses for the ventrolateral prefrontal cortex, dorsolateral prefrontal cortex, orbitofrontal cortex, postcentral gyrus, insular cortex, thalamus, anterior cingulate cortex, posterior cingulate cortex, amygdala and hippocampus were performed using FreeSurfer software. Whole-brain analysis was conducted by voxel-based morphometry. Rates of change in regional brain volume at 5 years after baseline were estimated using analysis of covariance. Among the 766 participants included in the FreeSurfer analysis, 444 (58%) were female and 287 (37%) were categorized into the chronic pain group. The results of FreeSurfer analysis showed that the chronic pain group had significantly greater decreases in regional volume in the postcentral gyrus (-2.187% in the chronic pain group versus -1.681% in the no chronic pain group, P = 0.01), thalamus (-4.400% versus -3.897%, P = 0.006), anterior cingulate cortex (-2.507% versus -1.941%, P = 0.004) and amygdala (-4.739% versus -4.022%, P = 0.03) compared to the no chronic pain group after adjusting for age, sex, education attainment, marital status, hypertension, diabetes, serum total cholesterol level, body mass index, current smoking, current drinking, regular exercise, cerebrovascular lesions on MRI, activities in daily living disability and depressive symptoms. Among the 730 participants included in the voxel-based morphometry analysis, 433 (59%) were female and 272 (37%) were categorized into the chronic pain group. The voxel-based morphometry analysis showed that the chronic pain group had a significantly greater regional volume decrease in the right anterior insula than the no chronic pain group. Our findings suggest that the presence of chronic pain at baseline is associated with a significantly greater decrease in the volume of pain-related brain regions at 5 years after baseline in community-dwelling older Japanese.

Effects of multisensory simultaneity judgment training on the comprehension and cortical processing of speech in noise: a randomized controlled trial

Understanding speech in noise can be facilitated by integrating auditory and visual speech cues. Audiovisual temporal acuity, which can be indexed by the temporal binding window (TBW), is critical for this process and can be enhanced through simultaneity judgment training. We hypothesized that multisensory training would narrow the TBW and improve speech understanding in noise. Participants were randomized to receive either training and testing (n = 15) or testing-only (n = 15) over three days. Trained participants demonstrated significant narrowing in their mean TBW size (403ms to 345ms; p = 0.030), whereas control participants did not (409ms to 474ms; p = 0.061). Although there were no group-level changes in word recognition scores, trained participants with larger TBW decreases exhibited larger improvements in auditory word recognition in noise (R2 = 0.291; p = 0.038). Individual differences in responses to training were found to be related to differences in cortical speech processing using functional near-infrared spectroscopy. Low audiovisual-evoked activity in the left middle temporal gyrus (R2 = 0.87; p = 0.006), left angular and superior temporal gyrus (R2 = 0.85; p = 0.006), and visual cortices (R2 = 0.74; p = 0.041) was associated with larger improvements in auditory word recognition after training. Multisensory training transfers benefits to speech comprehension in noise, and this effect may be mediated by upregulating activity in multisensory cortical networks for individuals with low baseline activity.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease

Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16); logopenic variant Primary Progressive Aphasia (n = 15); and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent MRI, tau PET and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, P < 0.001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = 0.30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = 0.10), tau in other functional networks (R2 = 0.11-0.26) and the magnitude of cortical atrophy (R2 = 0.20) and amyloid burden (R2 = 0.09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients 1 year later. This simple measure could aid the development of a personalized prognostic, monitoring and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

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.

Influence of individual's age on the characteristics of brain effective connectivity

Given the increasing number of older adults in society, there is a growing need for studies on changes in the aging brain. The aim of this research is to investigate the effective connectivity of different age groups using resting-state functional magnetic resonance imaging (fMRI) and graph theory. By examining connectivity in different age groups, a better understanding of age-related changes can be achieved. Lifespan pilot data from the Human Connectome Project (HCP) were used to examine dynamic effective connectivity (dEC) changes across different age groups. The Granger causality method with time windowing was employed to calculate dEC. After extracting graph measures, statistical analyses were performed to compare the age groups. Support vector machine and decision tree classifiers were used to classify the different age groups based on the extracted graph measures. Based on the obtained results, it can be concluded that there are significant differences in the effective connectivity among the three age groups. Statistical analyses revealed disassortativity. The global efficiency exhibited a decreasing trend, and the transitivity measure showed an increasing trend with the advancing age. The decision tree classifier showed an accuracy of 86.67 % with Kruskal-Wallis selected features. This study demonstrates that changes in effective connectivity across different age brackets can serve as a tool for better understanding brain function during the aging process.

The expression of insulin signaling and N-methyl-D-aspartate receptor genes in areas of gray matter atrophy is associated with cognitive function in type 2 diabetes

Type 2 diabetes (T2DM) is associated with brain abnormalities and cognitive dysfunction, including increased risk for Alzheimer's disease. However, the mechanisms of T2DM-related dementia remain poorly understood. We obtained retrospective data from the Mayo Clinic Study of Aging for 271 individuals with T2DM and 542 demographically matched non-diabetic controls (age 51-89, 62% male). We identified regions of significant gray matter atrophy in the T2DM group and then determined which genes were significantly expressed in these brain regions using imaging transcriptomics. We selected 15 candidate genes involved in insulin signaling, lipid metabolism, amyloid processing, N-methyl-D-aspartate-mediated neurotransmission, and calcium signaling. The T2DM group demonstrated significant gray matter atrophy in regions of the default mode, frontal-parietal, and sensorimotor networks (p < 0.05 cluster threshold corrected for false discovery rate, FDR). IRS1, AKT1, PPARG, PRKAG2, and GRIN2B genes were significantly expressed in these same regions (R2 > 0.10, p < 0.03, FDR corrected). Bayesian network analysis indicated significant directional paths among all 5 genes as well as the Clinical Dementia Rating score. Directional paths among genes were significantly altered in the T2DM group (Structural Hamming Distance = 12, p = 0.004), with PPARG expression becoming more important in the context of T2DM-related pathophysiology. Alterations of brain transcriptome patterns occurred in the absence of significant cognitive deficit or amyloid accumulation, potentially representing an early biomarker of T2DM-related dementia.

White matter integrity and verbal memory following a first episode of psychosis: A longitudinal study

Psychotic disorders are heterogeneous disorders for which there is evidence of structural and functional brain abnormalities. The role of white matter integrity, often measured via Fractional Anisotropy (FA), has played a controversial role in individuals with a first episode of psychosis (FEP). Similarly, some FEP studies have observed that higher FA is associated with better verbal memory, but others failed to find such an association. Studying the early stages of psychosis represents a promising avenue to overcome previous confounding factors and characterize the disease in its early clinical stages. Eighty individuals with a FEP were recruited from a specialized early intervention program for psychosis alongside 55 non-clinical controls from the community matched for age and sex. Both groups were followed and scanned 4 times: at baseline (within 3 months after program entry), 6 months, 12 months, and 18 months. Tract-Based Spatial Statistics (TBSS) were used on 3.0 Tesla diffusion-weighted images to extract fractional anisotropy values for white matter regions of interest in accordance with the John Hopkins University white-matter tractography atlas. The analysis revealed no significant main effect of group or time, and no significant associations between FA and verbal memory. Overall, differences in FA are small early in the course of illness and longer follow-up periods may be required to identify possible changes during a critical intervention window.

Enhanced neural speech tracking through noise indicates stochastic resonance in humans

Neural activity in auditory cortex tracks the amplitude-onset envelope of continuous speech, but recent work counterintuitively suggests that neural tracking increases when speech is masked by background noise, despite reduced speech intelligibility. Noise-related amplification could indicate that stochastic resonance - the response facilitation through noise - supports neural speech tracking, but a comprehensive account is lacking. In five human electroencephalography experiments, the current study demonstrates a generalized enhancement of neural speech tracking due to minimal background noise. Results show that (1) neural speech tracking is enhanced for speech masked by background noise at very high signal-to-noise ratios (~30 dB SNR) where speech is highly intelligible; (2) this enhancement is independent of attention; (3) it generalizes across different stationary background maskers, but is strongest for 12-talker babble; and (4) it is present for headphone and free-field listening, suggesting that the neural-tracking enhancement generalizes to real-life listening. The work paints a clear picture that minimal background noise enhances the neural representation of the speech onset-envelope, suggesting that stochastic resonance contributes to neural speech tracking. The work further highlights non-linearities of neural tracking induced by background noise that make its use as a biological marker for speech processing challenging.

Connectivity profile and function of uniquely human cortical areas

Determining the brain specializations unique to humans requires directly comparative anatomical information from other primates, especially our closest relatives. Human (Homo sapiens) (m/f), chimpanzee (Pan troglodytes) (f), and rhesus macaque (Macaca mulatta) (m/f) white matter atlases were used to create connectivity blueprints, i.e., descriptions of the cortical grey matter in terms of the connectivity with homologous white matter tracts. This allowed a quantitative comparative of cortical organization across the species. We identified human-unique connectivity profiles concentrated in temporal and parietal cortices, and hominid-unique organization in prefrontal cortex. Functional decoding revealed human-unique hotspots correlated with language processing and social cognition. Overall, our results counter models that assign primacy to prefrontal cortex for human uniqueness.Significance statement Understanding what makes the human brain unique requires direct comparisons with other primates, particularly our closest relatives. Using connectivity blueprints, we compared to cortical organization of the human to that of the macaque and, for the first time, the chimpanzee. This approach revealed human-specific connectivity patterns in the temporal and parietal lobes, regions linked to language and social cognition. These findings challenge traditional views that prioritize the prefrontal cortex in defining human cognitive uniqueness, emphasizing instead the importance of temporal and parietal cortical evolution in shaping our species' abilities.

Distinct brain activity patterns associated with traditional Chinese medicine syndromes: a task-fMRI study of mild cognitive impairment

Background

Abnormalities in brain activity patterns during episodic memory tasks have been inconsistently reported in amnestic mild cognitive impairment (aMCI) patients using functional magnetic resonance imaging (fMRI). This study applied traditional Chinese medicine (TCM) syndrome differentiation to categorize aMCI patients into distinct subgroups, aiming to clarify the neural mechanisms underlying their cognitive profiles.

Methods

Participants included aMCI patients categorized into the turbid phlegm clouding the orifices (PCO) or spleen-kidney deficiency (SKD) syndrome subgroups, alongside cognitively normal controls (NC) matched for age and gender. Neuropsychological assessments were performed, and fMRI scans were acquired during an episodic memory task involving the recognition of new and old vocabulary. Brain activity across different stages of episodic memory was analyzed using SPM12 and DPABI 7.0 software.

Results

A total of 57 aMCI patients (34 with SKD and 23 with PCO) and 54 healthy controls were involved in the final task-based fMRI analysis. Compared with the NC group, the PCO group exhibited increased brain activation during both encoding and retrieval phases, primarily involving the prefrontal cortex and occipital lobe. Compared with the SKD group, the PCO group demonstrated the elevated activation in the right central sulcus and right insula during the encoding phase. Correlation analysis indicated a specific association between PCO symptom scores and insula activation. No statistically significant differences were found between the SKD and NC groups.

Conclusion

Distinct patterns of fMRI brain activity found in aMCI patients with PCO and SKD syndromes during episodic memory tasks suggest differing neural mechanisms that may contribute to the clinical heterogeneity of aMCI.

Motor preparation tracks decision boundary crossing rather than accumulated evidence in temporal decision-making

Interval timing, the ability of animals to estimate the passage of time, is thought to involve diverse neural processes rather than a single central "clock" (Paton & Buonomano, 2018). Each of the different processes engaged in interval timing follows a different dynamic path, according to its specific function. For example, attention tracks anticipated events, such as offsets of intervals (Rohenkohl & Nobre, 2011), while motor processes control the timing of the behavioral output (De Lafuente et al., 2024). However, which processes are involved and how they are orchestrated over time to produce a temporal decision remains unknown. Here, we study motor preparation in the temporal bisection task, in which Human (Female and male) participants categorized intervals as "long" or "short". In contrast to typical perceptual decisions, where motor plans for all response alternatives are prepared simultaneously (Shadlen & Kiani, 2013), we find that temporal bisection decisions develop sequentially. While preparation for "long" responses was already underway before interval offset, no preparation was found for "short" responses. Furthermore, within intervals categorized as "long", motor preparation was stronger at interval offset for faster responses. Our findings support the two-stage model of temporal decisions, where "long" decisions are considered during the interval itself, while "short" decisions are only considered after the interval is over. Viewed from a wider perspective, our study offers methods to study the neural mechanisms of temporal decisions, by studying the multiple processes that produce them.Significance Statement Interval timing is thought to rely on multiple neural processes, yet little is known about which processes are involved, and how they are organized in time. We recorded the EEG of Human participants while they performed a simple temporal decision task, and focused on mu-beta activity, a signature of motor preparation. In typical non-temporal perceptual decisions, mu-beta activity reflects the accumulation of evidence. We find that in temporal decision-making, mu-beta reflects the commitment of the decision instead. This distinction stems from the uniqueness of temporal decisions, in which alternatives are considered sequentially rather than simultaneously. Studying temporal decisions as the dynamic orchestration of multiple neural processes offers a new approach to study the neural mechanisms underlying the perception of time.

Transcallosal white matter and cortical gray matter variations in autistic adults aged 30-73 years

BACKGROUND

Autism spectrum disorder (ASD) is a lifelong condition that profoundly impacts health, independence, and quality of life. However, research on brain aging in autistic adults is limited, and microstructural variations in white and gray matter remain poorly understood. To address this critical gap, we assessed novel diffusion MRI (dMRI) biomarkers, free water, and free water corrected fractional anisotropy (fwcFA), and mean diffusivity (fwcMD) across 32 transcallosal tracts and their corresponding homotopic grey matter origin/endpoint regions of interest (ROIs) in middle and old aged autistic adults.

METHODS

Forty-three autistic adults aged 30-73 and 43 age-, sex-, and IQ-matched neurotypical controls underwent dMRI scans. We examined free water, fwcFA, fwcMD differences between the two groups and age-related pattern of each dMRI metric across the whole brain for each group. The relationships between clinical measures of ASD and free water in regions that significantly differentiated autistic adults from neurotypical controls were also explored. In supplementary analyses, we also assessed free water uncorrected FA and MD using conventional single tensor modeling.

RESULTS

Autistic adults exhibited significantly elevated free water in seven frontal transcallosal tracts compared to controls. In controls, age-related increases in free water and decreases in fwcFA were observed across most transcallosal tracts. However, these age-associated patterns were entirely absent in autistic adults. In gray matter, autistic adults showed elevated free water in the calcarine cortices and lower fwcMD in the dorsal premotor cortices compared to controls. Lastly, age-related increases in free water were found across all white matter and gray matter ROIs in neurotypical controls, whereas no age-related associations were detected in any dMRI metrics for autistic adults.

LIMITATIONS

We only recruited cognitively capable autistic adults, which limits the generalizability of our findings across the full autism spectrum. The cross-sectional design precludes inferences about microstructural changes over time in middle and old aged autistic adults.

CONCLUSIONS

Our findings revealed increased free water load in frontal white matter in autistic adults and identified distinct age-associated microstructural variations between the two groups. These findings highlight more heterogeneous brain aging profiles in autistic adults. Our study also demonstrated the importance of quantifying free water in dMRI studies of ASD.

Accentuation Affects the Planning Scope and Focus-Accentuation Consistency Modulates Sentence Production: Evidence From Eye Movements

PURPOSE

Previous studies have shown that the planning scope of sentence production is flexible and influenced by a range of linguistic and extralinguistic factors. However, one important aspect that remains underexplored is the role of prosody, a key component of language, in shaping the planning scope. While it has been established that both conceptual and grammatical information influence sentence production and conceptual information is closely linked with prosodic cues, it remains unclear whether and how prosody, particularly accentuation, affects the planning process. Additionally, there is limited understanding of how conceptual (focus) and prosodic (accentuation) information interact to influence sentence production. Therefore, this study aims to investigate whether prosody (specifically, sentence accentuation) influences the planning scope and how the interaction between conceptual focus and prosodic accentuation jointly shapes sentence production.

METHOD

Question-answer pairs were used to create focus, and a red dot was added in scenarios as a cue for accentuation. Participants were asked to complete a picture description task and accent the entity with a red dot. We manipulated the accentuation position (initial vs. medial) and focus-accentuation consistency (consistent vs. inconsistent).

RESULTS

Speech latencies with initial accentuation were shorter than with medial accentuation. Eye-tracking data indicated that speakers preferred to fixate on accented pictures before articulation in initial accentuation, whereas in medial accentuation, speakers first preferred to fixate on deaccented pictures before shifting to accented ones. Both speech and first fixation latencies on accented pictures were shorter in the consistent condition. In the initial accentuation, accented-deaccented advantage scores were higher in the consistent condition from scenario onset to speech onset, while in the medial accentuation, this difference emerged after 220 ms. In addition, a focus inconsistent with the accentuation position slightly increases the acoustic prominence of deaccented information.

CONCLUSIONS

Accentuation positions affect planning scope, with a larger scope for medial accentuation. Additionally, the consistency between focus and accentuation influences sentence production, broadly affecting the processing of accented information and impacting external acoustic prominence. This influence on accented information processing occurs during the conceptualization and linguistic encoding phases, with processing starting more quickly and taking priority when focus and accentuation are consistent. This study provides a more comprehensive understanding of how various linguistic components interact to shape sentence production.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.28306436.

Resting-State Electroencephalographic Signatures Predict Treatment Efficacy of tACS for Refractory Auditory Hallucinations in Schizophrenic Patients

Transcranial alternating current stimulation (tACS) has been reported to treat refractory auditory hallucinations in schizophrenia. Despite diligent efforts, it is imperative to underscore that tACS does not uniformly demonstrate efficacy across all patients as with all treatments currently employed in clinical practice. The study aims to find biomarkers predicting individual responses to tACS, guiding treatment decisions, and preventing healthcare resource wastage. We divided 17 schizophrenic patients with refractory auditory hallucinations into responsive(RE) and non-responsive(NR) groups based on their auditory hallucination symptom reduction rates after one month of tACS treatment. The pre-treatment resting-state electroencephalogram(rsEEG) was recorded and then computed absolute power spectral density (PSD), Hjorth parameters (HPs, Hjorth activity (HA), Hjorth mobility (HM), and Hjorth complexity (HC) included) from different frequency bands to portray the brain oscillations. The results demonstrated that statistically significant differences localized within the high gamma frequency bands of the right brain hemisphere. Immediately, we input the significant dissociable features into popular machine learning algorithms, the Cascade Forward Neural Network achieved the best recognition accuracy of 93.87%. These findings preliminarily imply that high gamma oscillations in the right brain hemisphere may be the main influencing factor leading to different responses to tACS treatment, and incorporating rsEEG signatures could improve personalized decisions for integrating tACS in clinical treatment.

Structural Cerebellar and Lateral Frontoparietal Networks are altered in CUD: An SBM Analysis

Repetitive drug use results in enduring structural and functional changes in the brain. Addiction research has consistently revealed significant modifications in key brain networks related to reward, habit, salience, executive function, memory and self-regulation. Techniques like Voxel-based Morphometry have highlighted large-scale structural differences in grey matter across distinct groups. Source-based Morphometry (SBM) takes this a step further by incorporating the Independent Component Analysis to detect shared patterns of grey matter variation, all without requiring prior selection of regions of interest. However, SBM has yet to be employed in the study of structural alteration patterns related to cocaine addiction. Therefore, we performed this analysis to explore alterations in structural covariance specific to cocaine addiction. Our study involved 40 individuals diagnosed with Cocaine Use Disorder (CUD) and 40 matched healthy controls. Participants with CUD completed clinical questionnaires assessing the severity of their dependence and other relevant clinical variables. Following the adjustment for age-related effects, we observed notable disparities between groups in two structural independent components, which we identified as the structural cerebellar network and the structural lateral frontoparietal network, which display opposing trends. Specifically, the individuals with CUD exhibited a heightened contribution to the cerebellar network but simultaneously demonstrated a reduced contribution to the lateral frontoparietal network compared to the healthy controls. These findings unveil distinctive covariance patterns of neuroregulation linked with cocaine addiction, which indicates an interruption in the typical structural development in an affected lateral frontoparietal network, while suggesting an extended pattern of neuroregulation within the cerebellar network in individuals with CUD.

Phenome-wide associations of sleep characteristics in the Human Phenotype Project

Sleep tests commonly diagnose sleep disorders, but the diverse sleep-related biomarkers recorded by such tests can also provide broader health insights. In this study, we leveraged the uniquely comprehensive data from the Human Phenotype Project cohort, which includes 448 sleep characteristics collected from 16,812 nights of home sleep apnea test monitoring in 6,366 adults (3,043 male and 3,323 female participants), to study associations between sleep traits and body characteristics across 16 body systems. In this analysis, which identified thousands of significant associations, visceral adipose tissue (VAT) was the body characteristic that was most strongly correlated with the peripheral apnea-hypopnea index, as adjusted by sex, age and body mass index (BMI). Moreover, using sleep characteristics, we could predict over 15% of body characteristics, spanning 15 of the 16 body systems, in a held-out set of individuals. Notably, sleep characteristics contributed more to the prediction of certain insulin resistance, blood lipids (such as triglycerides) and cardiovascular measurements than to the characteristics of other body systems. This contribution was independent of VAT, as sleep characteristics outperformed age, BMI and VAT as predictors for these measurements in both male and female participants. Gut microbiome-related pathways and diet (especially for female participants) were notably predictive of clinical obstructive sleep apnea symptoms, particularly sleepiness, surpassing the prediction power of age, BMI and VAT on these symptoms. Together, lifestyle factors contributed to the prediction of over 50% of the sleep characteristics. This work lays the groundwork for exploring the associations of sleep traits with body characteristics and developing predictive models based on sleep monitoring.

Dynamic subtalar joint space measurement analysis following tibiotalar arthrodesis and total ankle replacement

BACKGROUND

Tibiotalar arthrodesis and total ankle replacement are current standards for treating end-stage ankle osteoarthritis. Our clinical understanding of biomechanical causes and risk factors for subtalar secondary osteoarthritis development following surgical treatment is limited. The objective of this retrospective study was to investigate subchondral bone morphometric differences of individuals treated with a tibiotalar arthrodesis or ankle arthroplasty that may influence subtalar joint measurements during overground walking; results were compared between surgical groups, their unaffected limb, and asymptomatic controls.

METHODS

Previously collected kinematics were used to measure and compare subtalar joint space and congruence throughout the dynamic activity utilizing a correspondence-based joint measurement analysis. A morphometric analysis evaluated subchondral bone differences of the calcaneus subtalar joint between groups.

FINDINGS

The affected subtalar joint of arthrodesis participants showed increased joint space distance in the medial facet during early stance that was related to kinematic differences compared to controls and their contralateral untreated limbs. Our morphometric analyses demonstrated subchondral bone asymmetries in both surgical groups compared to their contralateral untreated limbs.

INTERPRETATION

Previously reported kinematic differences between treated and untreated limbs in arthrodesis participants may translate to the variations in joint space and morphology observed in this study. Our earlier findings within the arthroplasty group indicated no significant kinematic differences between treated and untreated limbs, and the current study showed minimal significant differences in joint space distances. Collectively, this suggests that arthroplasty joint space and subchondral bone shapes are not as strongly influenced by functional asymmetries as those in the arthrodesis group.

TaiChi-MSS protocol: enhancing cognitive and brain function in MCI patients through Tai Chi exercise combined with multisensory stimulation

Background

The aging population in China is confronted with considerable challenges, with 14.71% of elderly individuals affected by mild cognitive impairment (MCI). The practice of Tai Chi has been demonstrated to enhance cognitive function, while sensory stimulation has been shown to facilitate neural activity. Nevertheless, the combined impact of Tai Chi and sensory stimulation on cognitive, sensory functions, and brain activation in older adults with MCI remains uncertain. This study aims to ascertain whether the integration of Tai Chi with sensory stimulation can facilitate more efficacious interventions for these outcomes.

Methods and analysis

The TaiChi-MSS (Tai Chi and Multisensory Stimulation for Cognitive Function) study is a multi-center, randomized controlled trial (RCT) conducted in Suzhou and Shanghai, enrolling 88 participants aged 60 years or older with MCI. Participants will be randomly assigned to one of four groups: Tai Chi, multisensory stimulation, Tai Chi combined with multisensory stimulation or control. The intervention will last 6 months, with follow-up assessments at 3, 6, and 9 months. Primary outcomes include cognitive and sensory assessments, assessed using the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), domain-specific cognitive tests, Pure Tone Audiometry (PTA), and Sniffin' Sticks Odor Identification Test. Secondary outcomes involve brain activation, measured through functional Magnetic Resonance Imaging (fMRI) scans. fMRI will be used to assess brain structure and connectivity changes, focusing on neuroplasticity. Data will be analyzed using mixed-effects models. The False Discovery Rate (FDR) will be the correction method for multiple comparisons to control for the expected proportion of false positives.

Ethics and dissemination

This study was approved by the ethics committee of Shanghai University of Sport (No. 102772023RT200). The results of this study will be disseminated in peer-reviewed journals and presented at academic conferences.

Brain connectivity for constructing new face representations in typical adults versus a prosopagnosic patient

Will our brains get to know a new face better if we look at its external features first? Here we offer neurophysiological evidence of the relevance of external versus internal facial features for constructing new face representations, by contrasting successful face processing with a prototypical case of face agnosia. A woman with acquired prosopagnosia (E.C.) and 14 age-matched typical participants (7 women) were exposed to a face-feature matching task. External (E), internal (I) features, and whole target faces of unknown individuals (from an IdentiKit gallery) were displayed according to two different sequences: E →I→whole faces, or I→E→whole faces. Then, we studied the induced EEG activity using 'isolated effective coherence' to analyse the intracortical causal information flow among face-sensitive nodes. Initial presentation of external features (E before I), when compared to internal ones, triggered connections encompassing extensively the right-hemisphere face processing pathway [from posterior visual cortices for initial structural analysis, towards both intermediate (occipitotemporal) and high-level (prefrontal) relay stations], in which face-identity is thought to emerge progressively. Also, whereas exposure to internal features as second stimulus seemed to demand some sort of basic visual processing, external features triggered again more widespread and integrative connections. Connections for whole faces closing the E-I sequence resembled those for external features initiating the same sequence. Meanwhile, the predominant connections for whole faces completing the I-E sequence were more restricted to specific brain areas, with relevant prefrontal activity and a few connected nodes in right posterior regions, suggesting high attentional load plus initial and intermediate processing of face identity. Interestingly, the pattern of connections that distinguished typical participants from E.C. in the I-E sequence was the recruitment of left posterior visual regions, presumably underlying analytical subroutines for structural encoding of facial stimuli. These findings support that initial exposure to external features, followed by internal ones, provides the best visual cue to acquire new face configurations. Nevertheless, in case of face agnosia after right posterior damage, relying preferentially on internal features and left hemisphere specialized subroutines might be an alternative for cognitive training.

Structural connectome construction using constrained spherical deconvolution in multi-shell diffusion-weighted magnetic resonance imaging

Connectional neuroanatomical maps can be generated in vivo by using diffusion-weighted magnetic resonance imaging (dMRI) data, and their representation as structural connectome (SC) atlases adopts network-based brain analysis methods. We explain the generation of high-quality SCs of brain connectivity by using recent advances for reconstructing long-range white matter connections such as local fiber orientation estimation on multi-shell dMRI data with constrained spherical deconvolution, which yields both increased sensitivity to detecting crossing fibers compared with competing methods and the ability to separate signal contributions from different macroscopic tissues, and improvements to streamline tractography such as anatomically constrained tractography and spherical-deconvolution informed filtering of tractograms, which have increased the biological accuracy of SC creation. Here, we provide step-by-step instructions to creating SCs by using these methods. In addition, intermediate steps of our procedure can be adapted for related analyses, including region of interest-based tractography and quantification of local white matter properties. The associated software MRtrix3 implements the relevant tools for easy application of the protocol, with specific processing tasks deferred to components of the FSL software. The protocol is suitable for users with expertise in dMRI and neuroscience and requires between 2 h and 13 h to complete, depending on the available computational system.

Comparison of resting-state brain activity between insomnia and generalized anxiety disorder: A coordinate-based meta-analysis

Patients with insomnia disorder (ID) usually experience a greater burden of comorbid anxiety symptoms. However, the neural mechanism under the mutual relationship between ID and anxiety remains largely unclear. The meta-analysis aimed to explore the concordance and distinction of regional brain functional activity in patients with ID and those with generalized anxiety disorder (GAD) using coordinate-based activation likelihood estimation approach. Studies using resting-state regional homogeneity, amplitude of low-frequency fluctuations (ALFF), or fractional ALFF in patients with ID or GAD were included by searching multiple databases up to May 24, 2024. Using meta-analytic approach, 21 studies of ID vs. healthy controls (HC) and 16 studies of GAD vs. HC were included to illuminate the common and distinct patterns between the two disorders. Results showed that ID and GAD shared increased brain activities in the left posterior cingulate cortex and left precuneus, as well as decreased brain activity in the left medial prefrontal cortex. Additionally, compared with ID, GAD showed greater increased activities in the left superior frontal gyrus. Our study reveals both common and different activation patterns between ID and GAD, which may provide novel insights for understanding the neural basis of the two disorders and enlighten the possibility of the development of more targeted treatment strategies for ID and GAD.

Dissociable spatial topography of cortical atrophy in early-onset and late-onset Alzheimer's disease: A head-to-head comparison of the LEADS and ADNI cohorts

INTRODUCTION

Early-onset and late-onset Alzheimer's disease (EOAD and LOAD, respectively) have distinct clinical manifestations, with prior work based on small samples suggesting unique patterns of neurodegeneration. The current study performed a head-to-head comparison of cortical atrophy in EOAD and LOAD, using two large and well-characterized cohorts (LEADS and ADNI).

METHODS

We analyzed brain structural magnetic resonance imaging (MRI) data acquired from 377 sporadic EOAD patients and 317 sporadicLOAD patients who were amyloid positive and had mild cognitive impairment (MCI) or mild dementia (i.e., early-stage AD), along with cognitively unimpaired participants.

RESULTS

After controlling for the level of cognitive impairment, we found a double dissociation between AD clinical phenotype and localization/magnitude of atrophy, characterized by predominant neocortical involvement in EOAD and more focal anterior medial temporal involvement in LOAD.

DISCUSSION

Our findings point to the clinical utility of MRI-based biomarkers of atrophy in differentiating between EOAD and LOAD, which may be useful for diagnosis, prognostication, and treatment.

HIGHLIGHTS

Early-onset Alzheimer's disease (EOAD) and late-onset AD (LOAD) patients showed distinct and overlapping cortical atrophy patterns. EOAD patients showed prominent atrophy in widespread neocortical regions. LOAD patients showed prominent atrophy in the anterior medial temporal lobe. Regional atrophy was correlated with the severity of global cognitive impairment. Results were comparable when the sample was stratified for mild cognitive impairment (MCI) and dementia.

MRI-based morphometric structural changes correlate with histopathology in experimental autoimmune encephalomyelitis

BACKGROUND AND OBJECTIVES

Magnetic resonance imaging (MRI) and neurohistopathology are important correlates for evaluation of disease progression in multiple sclerosis (MS). Here we used experimental autoimmune encephalomyelitis (EAE) as an animal model of MS to determine the correlation between clinical EAE severity, MRI and histopathological parameters.

METHODS

N = 11 female C57BL/6J mice were immunized with human myelin oligodendrocyte glycoprotein 1-125, while N = 9 remained non-immunized. Mice were scanned longitudinally over a period of 13 weeks using a 11.7 Tesla (T) Bruker BioSpec® preclinical MRI instrument, and regional volume changes of the lumbar spinal cord were analyzed using Voxel-Guided Morphometry (VGM). Following the final in vivo T1-weighted MRI scan, the lumbar spinal cord of each mouse was subjected to an ex vivo MRI scan using T1-, T2*- and diffusion tensor imaging (DTI)-weighted sequences. Tissue sections were then stained for immune cell infiltration, demyelination, astrogliosis, and axonal damage using hematoxylin-eosin staining and immunohistochemistry.

RESULTS

While in vivo MRI VGM detected an overall increase in volume over time, no differences were observed between EAE animals and controls. Ex vivo MRI showed a generalized atrophy of the spinal cord, which was pronounced in the anterolateral tract. The most striking correlation was observed between EAE score, white matter atrophy in ex vivo T1-weighted scans and histological parameters.

DISCUSSION

The data demonstrate that ex vivo MRI is a valuable tool to assess white matter atrophy in EAE, which was shown to be directly linked to the severity of EAE and spinal cord histopathology.

Linear incrementality in focus and accentuation processing during sentence production: evidence from eye movements

Introduction

While considerable research in language production has focused on incremental processing during conceptual and grammatical encoding, prosodic encoding remains less investigated. This study examines whether focus and accentuation processing in speech production follows linear or hierarchical incrementality.

Methods

We employed visual world eye-tracking to investigate how focus and accentuation are processed during sentence production. Participants were asked to complete a scenario description task where they were prompted to use a predetermined sentence structure to accurately convey the scenario, thereby spontaneously accentuate the corresponding entity. We manipulated the positions of focus with accentuation (initial vs. medial) by changing the scenarios. The initial and medial positions correspond to the first and second nouns in sentences like "N1 is above N2, not N3."

Results

Our findings revealed that speech latencies were significantly shorter in the sentences with initial focus accentuation than those with medial focus accentuation. Furthermore, eye-tracking data demonstrated that speakers quickly displayed a preference for fixating on initial information after scenarios onset. Crucially, the time-course analysis revealed that the onset of the initial focus accentuation effect (around 460 ms) preceded that of the medial focus accentuation effect (around 920 ms).

Discussion

These results support that focus and accentuation processing during speech production prior to articulation follows linear incrementality rather than hierarchical incrementality.

Patients with dementia with Lewy bodies display a signature alteration of their cognitive connectome

Cognition plays a central role in the diagnosis and characterization of dementia with Lewy bodies (DLB). However, the complex associations among cognitive deficits in different domains in DLB are largely unknown. To characterize these associations, we investigated and compared the cognitive connectome of DLB patients, healthy controls (HC), and Alzheimer's disease patients (AD). We obtained data from the National Alzheimer's Coordinating Center. We built cognitive connectomes for DLB (n = 104), HC (n = 3703), and AD (n = 1985) using correlations among 24 cognitive measures mapping multiple cognitive domains. Connectomes were compared using global and nodal graph measures of centrality, integration, and segregation. For global measures, DLB showed a higher global efficiency (integration) and lower transitivity (segregation) than HC and AD. For nodal measures, DLB showed higher global efficiency in most measures, higher participation (centrality) in free-recall memory, processing speed/attention, and executive measures, and lower local efficiency (segregation) than HC. Compared with AD, DLB showed lower nodal strength and local efficiency, especially in memory consolidation. The cognitive connectome of DLB shows a loss of segregation, leading to a loss of cognitive specialization. This study provides the data to advance the understanding of cognitive impairment and clinical phenotype in DLB, with implications for differential diagnosis.

Host genetics maps to behaviour and brain structure in developmental mice

Gene-environment interactions in the postnatal period have a long-term impact on neurodevelopment. To effectively assess neurodevelopment in the mouse, we developed a behavioural pipeline that incorporates several validated behavioural tests to measure translationally relevant milestones of behaviour in mice. The behavioral phenotype of 1060 wild type and genetically-modified mice was examined followed by structural brain imaging at 4 weeks of age. The influence of genetics, sex, and early life stress on behaviour and neuroanatomy was determined using traditional statistical and machine learning methods. Analytical results demonstrated that neuroanatomical diversity was primarily associated with genotype whereas behavioural phenotypic diversity was observed to be more susceptible to gene-environment variation. We describe a standardized mouse phenotyping pipeline, termed the Developmental Behavioural Milestones (DBM) Pipeline released alongside the 1000 Mouse Developmental Behavioural Milestones (1000 Mouse DBM) database to institute a novel framework for reproducible interventional neuroscience research.

Exploring the links among brain iron accumulation, cognitive performance, and dietary intake in older adults: A longitudinal MRI study

This study evaluated longitudinal brain iron accumulation in older adults, its association with cognition, and the role of specific nutrients in mitigating iron accumulation. MRI-based, quantitative susceptibility mapping estimates of brain iron concentration were acquired from seventy-two healthy older adults (47 women, ages 60-86) at a baseline timepoint (TP1) and a follow-up timepoint (TP2) 2.5-3.0 years later. Dietary intake was evaluated at baseline using a validated questionnaire. Cognitive performance was assessed at TP2 using the uniform data set (Version 3) neuropsychological tests of episodic memory (MEM) and executive function (EF). Voxel-wise, linear mixed-effects models, adjusted for longitudinal gray matter volume alterations, age, and several non-dietary lifestyle factors revealed brain iron accumulation in multiple subcortical and cortical brain regions, which was negatively associated with both MEM and EF performance at T2. However, consumption of specific dietary nutrients at TP1 was associated with reduced brain iron accumulation. Our study provides a map of brain regions showing iron accumulation in older adults over a short 2.5-year follow-up and indicates that certain dietary nutrients may slow brain iron accumulation.

Directed connectivity in theta networks supports action-effect integration

The ability to plan and carry out goal-directed behavior presupposes knowledge about the contingencies between movements and their effects. Ideomotor accounts of action control assume that agents integrate action-effect contingencies by creating action-effect bindings, which associate movement patterns with their sensory consequences. However, the neurophysiological underpinnings of action-effect binding are not yet well understood. Given that theta band activity has been linked to information integration, we thus studied action-effect integration in an electrophysiological study with N = 31 healthy individuals with a strong focus on theta band activity. We examined how information between functional neuroanatomical structures is exchanged to enable action planning. We show that theta band activity in a network encompassing the insular cortex (IC), the anterior temporal lobe (ATL), and the inferior frontal cortex (IFC) supports the establishment of action-effect bindings. All regions revealed bi-directional effective connectivities, indicating information transfer between these regions. The IC and ATL create a loop for information integration and the conceptual abstraction of it. The involvement of anterior regions of the IFC, particularly during the acquisition phase of the action-effect, likely reflects episodic control mechanisms in which a past event defines a "template" of what action-effect is to be expected. Taken together, the current findings connect well with major cognitive concepts. Our study suggests a functional relevance of theta band activity in an IC-ATL-IFC network, which in turn implies that basic ideomotor action-effect integration is implemented through theta band activity and effective connectivities between temporo-frontal structures.

The ghost of selective inference in spatiotemporal trend analysis

In spatiotemporal trend analysis, selective inference occurs when researchers are only interested in significant trends based on a fixed threshold (α, often 0.05), without considering the total number of statistical tests performed. Using simultaneous inference in gridded data involves thousands of trend tests, one for each pixel, leading to multiple testing or multiplicity problems. Multiplicity increases the chance of false discoveries in an unknown way unless the p-values of all tests performed are appropriately considered and adjusted. This discussion paper provides a selective and non-exhaustive review of the problems of multiplicity and selective inference. We discuss some appropriate methods to cope with the inflation of spurious results and comment on some examples based on gridded data in the context of research on spatiotemporal trend analysis. In addition, we suggest some good practices in transparency to facilitate the replicability of studies. The effects of uncorrected multiplicity and selective interference can be likened to a ghostly layer over the data, projecting illusions of significance that vanish with rigorous correction methods, revealing the true statistical skeleton of the results. The basis for addressing these problems is to assume that, although it may sometimes seem counterintuitive, the reality of what we perceive as statistically significant (i.e., p-values <0.05) also depends on the number (and value) of what we perceive as non-significant (i.e., p-values ≥0.05). Indeed, in a multiplicity context, one cannot correctly decide what is statistically significant until the whole story is known. Uncorrected selective inference precisely involves ignoring part of the story.

Decoding Salience: A Functional Magnetic Resonance Imaging Investigation of Reward and Contextual Unexpectedness in Memory Encoding and Retrieval

The present study investigated the neuromodulatory substrates of salience processing and its impact on memory encoding and behaviour, with a specific focus on two distinct types of salience: reward and contextual unexpectedness. 46 Participants performed a novel task paradigm modulating these two aspects independently and allowing for investigating their distinct and interactive effects on memory encoding while undergoing high-resolution fMRI. By using advanced image processing techniques tailored to examine midbrain and brainstem nuclei with high precision, our study additionally aimed to elucidate differential activation patterns in subcortical nuclei in response to reward-associated and contextually unexpected stimuli, including distinct pathways involving in particular dopaminergic modulation. We observed a differential involvement of the ventral striatum, substantia nigra (SN) and caudate nucleus, as well as a functional specialisation within the subregions of the cingulate cortex for the two salience types. Moreover, distinct subregions within the SN in processing salience could be identified. Dorsal areas preferentially processed salience related to stimulus processing (of both reward and contextual unexpectedness), and ventral areas were involved in salience-related memory encoding (for contextual unexpectedness only). These functional specialisations within SN are in line with different projection patterns of dorsal and ventral SN to brain areas supporting attention and memory, respectively. By disentangling stimulus processing and memory encoding related to two salience types, we hope to further consolidate our understanding of neuromodulatory structures' differential as well as interactive roles in modulating behavioural responses to salient events.

Using cluster-based permutation tests to estimate MEG/EEG onsets: How bad is it?

Localising effects in space, time and other dimensions is a fundamental goal of magneto- and electroencephalography (EEG) research. A popular exploratory approach applies mass-univariate statistics followed by cluster-sum inferences, an effective way to correct for multiple comparisons while preserving high statistical power by pooling together neighbouring effects. Yet, these cluster-based methods have an important limitation: each cluster is associated with a unique p-value, such that there is no error control at individual timepoints, and one must be cautious about interpreting when and where effects start and end. Sassenhagen and Draschkow (2019) provided an important reminder of this limitation. They also reported results from a simulation, suggesting that onsets estimated from EEG data are both positively biased and very variable. However, the simulation lacked comparisons to other methods. Here, I report such comparisons in a new simulation, replicating the positive bias of the cluster-sum method, but also demonstrating that it performs relatively well, in terms of bias and variability, compared to other methods that provide pointwise p-values: two methods that control the false discovery rate and two methods that control the familywise error rate (cluster-depth and maximum statistic methods). I also present several strategies to reduce estimation bias, including group calibration, group comparison and using binary segmentation, a simple change point detection algorithm that outperformed mass-univariate methods in simulations. Finally, I demonstrate how to generate onset hierarchical bootstrap confidence intervals that integrate variability over trials and participants, a substantial improvement over standard group approaches that ignore measurement uncertainty.

Sex- and brain region-specific alterations in brain volume in germ-free mice

Several lines of evidence demonstrate that microbiota influence brain development. Using high-resolution ex vivo magnetic resonance imaging (MRI), this study examined the impact of microbiota status on brain volume and revealed microbiota-related differences that were sex and brain region dependent. Cortical and hippocampal regions demonstrate increased sensitivity to microbiota status during the first 5 weeks of postnatal life, effects that were greater in male germ-free mice. Conventionalization of germ-free mice at puberty did not normalize brain volume changes. These data add to the existing literature and highlight the need to focus more attention on early-life microbiota-brain axis mechanisms in order to understand the regulatory role of the microbiome in brain development.

Static and Dynamic Dysconnectivity in Early Psychosis: Relationship With Symptom Dimensions

BACKGROUND AND HYPOTHESIS

Altered functional connectivity (FC) has been frequently reported in psychosis. Studying FC and its time-varying patterns in early-stage psychosis allows the investigation of the neural mechanisms of this disorder without the confounding effects of drug treatment or illness-related factors.

STUDY DESIGN

We employed resting-state functional magnetic resonance imaging (rs-fMRI) to explore FC in individuals with early psychosis (EP), who also underwent clinical and neuropsychological assessments. 96 EP and 56 demographically matched healthy controls (HC) from the Human Connectome Project for Early Psychosis database were included. Multivariate analyses using spatial group independent component analysis were used to compute static FC and dynamic functional network connectivity (dFNC). Partial correlations between FC measures and clinical and cognitive variables were performed to test brain-behavior associations.

STUDY RESULTS

Compared to HC, EP showed higher static FC in the striatum and temporal, frontal, and parietal cortex, as well as lower FC in the frontal, parietal, and occipital gyrus. We found a negative correlation in EP between cognitive function and FC in the right striatum FC (pFWE = 0.009). All dFNC parameters, including dynamism and fluidity measures, were altered in EP, and positive symptoms were negatively correlated with the meta-state changes and the total distance (pFWE = 0.040 and pFWE = 0.049).

CONCLUSIONS

Our findings support the view that psychosis is characterized from the early stages by complex alterations in intrinsic static and dynamic FC, that may ultimately result in positive symptoms and cognitive deficits.

Pain can't be carved at the joints: defining function-based pain profiles and their relevance to chronic disease management in healthcare delivery design

BACKGROUND

Pain is a complex problem that is triaged, diagnosed, treated, and billed based on which body part is painful, almost without exception. While the "body part framework" guides the organization and treatment of individual patients' pain conditions, it remains unclear how to best conceptualize, study, and treat pain conditions at the population level. Here, we investigate (1) how the body part framework agrees with population-level, biologically derived pain profiles; (2) how do data-derived pain profiles interface with other symptom domains from a whole-body perspective; and (3) whether biologically derived pain profiles capture clinically salient differences in medical history.

METHODS

To understand how pain conditions might be best organized, we applied a carefully designed a multi-variate pattern-learning approach to a subset of the UK Biobank (n = 34,337), the largest publicly available set of real-world pain experience data to define common population-level profiles. We performed a series of post hoc analyses to validate that each pain profile reflects real-world, clinically relevant differences in patient function by probing associations of each profile across 137 medication categories, 1425 clinician-assigned ICD codes, and 757 expert-curated phenotypes.

RESULTS

We report four unique, biologically based pain profiles that cut across medical specialties: pain interference, depression, medical pain, and anxiety, each representing different facets of functional impairment. Importantly, these profiles do not specifically align with variables believed to be important to the standard pain evaluation, namely painful body part, pain intensity, sex, or BMI. Correlations with individual-level clinical histories reveal that our pain profiles are largely associated with clinical variables and treatments of modifiable, chronic diseases, rather than with specific body parts. Across profiles, notable differences include opioids being associated only with the pain interference profile, while antidepressants linked to the three complimentary profiles. We further provide evidence that our pain profiles offer valuable, additional insights into patients' wellbeing that are not captured by the body-part framework and make recommendations for how our pain profiles might sculpt the future design of healthcare delivery systems.

CONCLUSION

Overall, we provide evidence for a shift in pain medicine delivery systems from the conventional, body-part-based approach to one anchored in the pain experience and holistic profiles of patient function. This transition facilitates a more comprehensive management of chronic diseases, wherein pain treatment is integrated into broader health strategies. By focusing on holistic patient profiles, our approach not only addresses pain symptoms but also supports the management of underlying chronic conditions, thereby enhancing patient outcomes and improving quality of life. This model advocates for a seamless integration of pain management within the continuum of care for chronic diseases, emphasizing the importance of understanding and treating the interdependencies between chronic conditions and pain.

In perspective of specific symptoms of major depressive disorder: Functional connectivity analysis of electroencephalography and potential biomarkers of treatment response

BACKGROUND

The symptom variability in major depressive disorder (MDD) complicates treatment assessment, necessitating a thorough understanding of MDD symptoms and potential biomarkers.

METHODS

In this prospective study, we enrolled 54 MDD patients and 39 controls. Over the course of weeks 1, 2, and 4 participants underwent evaluations, with electroencephalograms (EEG) recorded at baseline and week 1. Our investigation considered five previously identified syndromal factors derived from the 17-item Hamilton Depression Rating Scale (17-item HAMD) for assessing depression: core, insomnia, somatic anxiety, psychomotor-insight, and anorexia. We assessed treatment response and EEG characteristics across all syndromal factors and total scores, all of which are based on the 17-item HAMD. To analyze the topology of brain networks, we employed functional connectivity (FC) and a graph theory-based method across various frequency bands.

RESULTS

The healthy control group had notably higher values in delta band EEG FC compared to the MDD patient group. Similar distinctions were observed between the responder and non-responder patient groups. Further exploration of baseline FC values across distinct syndromal factors revealed significant variations among the core, psychomotor-insight, and anorexia subgroups when using a specific graph theory-based approach, focusing on global efficiency and average clustering coefficient.

LIMITATIONS

Different antidepressants were included in this study. Therefore, the results should be interpreted with caution.

CONCLUSIONS

Our findings suggest that delta band EEG FC holds promise as a valuable predictor of antidepressant efficacy. It demonstrates an ability to adapt to individual variations in depressive symptomatology, offering insights into personalized treatment for patients with depression.

Prediction of Post Traumatic Epilepsy Using MR-Based Imaging Markers

Post-traumatic epilepsy (PTE) is a debilitating neurological disorder that develops after traumatic brain injury (TBI). Despite the high prevalence of PTE, current methods for predicting its occurrence remain limited. In this study, we aimed to identify imaging-based markers for the prediction of PTE using machine learning. Specifically, we examined three imaging features: Lesion volumes, resting-state fMRI-based measures of functional connectivity, and amplitude of low-frequency fluctuation (ALFF). We employed three machine-learning methods, namely, kernel support vector machine (KSVM), random forest, and an artificial neural network (NN), to develop predictive models. Our results showed that the KSVM classifier, with all three feature types as input, achieved the best prediction accuracy of 0.78 AUC (area under the receiver operating characteristic (ROC) curve) using nested cross-validation. Furthermore, we performed voxel-wise and lobe-wise group difference analyses to investigate the specific brain regions and features that the model found to be most helpful in distinguishing PTE from non-PTE populations. Our statistical analysis uncovered significant differences in bilateral temporal lobes and cerebellum between PTE and non-PTE groups. Overall, our findings demonstrate the complementary prognostic value of MR-based markers in PTE prediction and provide new insights into the underlying structural and functional alterations associated with PTE.

Abnormal cerebral blood flow in children with developmental stuttering

BACKGROUND

Stuttering affects approximately 5% of children; however, its neurological basis remains unclear. Identifying imaging biomarkers could aid in early detection. Accordingly, we investigated resting-state cerebral blood flow (CBF) in children with developmental stuttering.

METHODS

Pulsed arterial spin labelling magnetic resonance imaging was utilised to quantify CBF in 35 children with developmental stuttering and 27 healthy controls. We compared normalised CBF between the two groups and evaluated the correlation between abnormal CBF and clinical indicators.

RESULTS

Compared with healthy controls, the stuttering group exhibited decreased normalised CBF in the cerebellum lobule VI bilaterally, right cuneus, and left superior occipital gyrus and increased CBF in the right medial superior frontal gyrus, left rectus, and left dorsolateral superior frontal gyrus. Additionally, normalised CBF in the left cerebellum lobule VI and left superior occipital gyrus was positively correlated with stuttering severity.

CONCLUSIONS

Children who stutter display decreased normalised CBF primarily in the cerebellum and occipital gyrus, with increased normalised CBF in the frontal gyrus. Additionally, the abnormal CBF in the left cerebellum lobule VI and left superior occipital gyrus was associated with more severe symptoms, suggesting that decreased CBF in these areas may serve as a novel neuroimaging clue for stuttering.

IMPACT

Stuttering occurs in 5% of children and often extends into adulthood, which may negatively affect quality of life. Early detection and treatment are essential. We used pulsed arterial spin labelling magnetic resonance imaging to visualise the resting-state cerebral blood flow (CBF) in children who stutter and healthy children. Normalised CBF was decreased in stutterers in the cerebellum and occipital gyrus and increased in the frontal gyrus. Stuttering severity was linked to abnormal normalised CBF in the left cerebellum lobule VI and left superior occipital gyrus, suggesting that CBF may serve as a novel neuroimaging clue for stuttering.

Brain volume and microglial density changes are correlated in a juvenile mouse model of cranial radiation and CSF1R inhibitor treatment

Microglia have been shown to proliferate and become activated following cranial radiotherapy (CRT), resulting in a chronic inflammatory response. We investigated the role of microglia in contributing to widespread volume losses observed in the brain following CRT in juvenile mice. To manipulate microglia, we used low-dose treatment with a highly selective CSF1R inhibitor called PLX5622 (PLX). We hypothesized that alteration of the post-CRT microglia population would lead to changes in brain development outcomes, as evaluated by structural MRI. Wild-type C57BL/6J mice were provided with daily intraperitoneal injections of PLX (25 mg/kg) or vehicle from postnatal day (P)14 to P19. Mice also received whole-brain irradiation (7 Gy) or sham irradiation (0 Gy) at 16 days of age. In one cohort of mice, immunohistochemical assessment in tissue sections was conducted to assess the impact of the selected PLX and CRT doses as well as their combination. In a separate cohort, mice were imaged using MRI at P14 (pretreatment), P19, P23, P42 and P63 in order to assess induced volume changes, which were measured based on structures from a predefined atlas. We observed that PLX and radiation treatments led to sex-specific changes in the microglial cell population. Across treatment groups, MRI-detected anatomical volumes at P19 and P63 were associated with microglia and proliferating microglia densities, respectively. Overall, our study demonstrates that low-dose PLX treatment produces a sex-dependent response in juvenile mice, that manipulation of microglia alters CRT-induced volume changes and that microglia density and MRI-derived volume changes are correlated in this model.

A Multivariate and Network Analysis Uncovers a Long-Term Influence of Exclusive Breastfeeding on the Development of Brain Morphology and Structural Connectivity

Exclusive breastfeeding (eBF) in infancy appears to offer a developmental advantage for children's brains compared to formula-fed counterparts. Existing research has predominantly focused on global brain measures (i.e., total white/grey matter volumes) or on limited sets of specific brain regions, in selected age groups, leaving uncertainties about the impact of eBF on the overall structural connectomes. In this cross-sectional study encompassing participants from childhood to adulthood, partial least squares correlations (PLSC) were employed to assess white and grey matter volumes. Furthermore, a network analytic approach was used to estimate the structural connectome based on cortical thickness data. The results revealed that eBF duration correlated with increased white matter volumes in children and with the volume of the medial orbital gyrus in adults. Structural connectome analyses demonstrated heightened anatomical connectivity in eBF children, evidenced by enhanced network density and local/global efficiency, along with increased node degree and local efficiency in frontal and temporal lobes. Similarly, eBF in adults was associated to an improved node connectivity in the frontal lobe. These findings imply a lasting impact of eBF on brain morphometry and structural connectivity. Childhood benefits include heightened white matter development, while in adulthood, eBF may contribute to reduced neural loss associated with aging and enhanced connectivity, particularly in frontal regions.

Harnessing slow event-related fMRI to investigate trial-level brain-behavior relationships during object identification

Understanding brain-behavior relationships is the core goal of cognitive neuroscience. However, these relationships-especially those related to complex cognitive and psychopathological behaviors-have recently been shown to suffer from very small effect sizes (0.1 or less), requiring potentially thousands of participants to yield robust findings. Here, we focus on a much more optimistic case utilizing task-based fMRI and a multi-echo acquisition with trial-level brain-behavior associations measured within participant. In a visual object identification task for which the behavioral measure is response time (RT), we show that while trial-level associations between BOLD and RT can similarly suffer from weak effect sizes, converting these associations to their corresponding group-level effects can yield robust peak effect sizes (Cohen's d = 1.0 or larger). Multi-echo denoising (Multi-Echo ICA or ME-ICA) yields larger effects than optimally combined multi-echo with no denoising, which is in turn an improvement over standard single-echo acquisition. While estimating these brain-behavior relationships benefits from the inclusion of a large number of trials per participant, even a modest number of trials (20-30 or more) yields robust group-level effect sizes, with replicable effects obtainable with relatively standard sample sizes (N = 20-30 participants per sample).

Cortical Generators and Connections Underlying Phoneme Perception: A Mismatch Negativity and P300 Investigation

The cortical generators of the pure tone MMN and P300 have been thoroughly studied. Their nature and interaction with respect to phoneme perception, however, is poorly understood. Accordingly, the cortical sources and functional connections that underlie the MMN and P300 in relation to passive and active speech sound perception were identified. An inattentive and attentive phonemic oddball paradigm, eliciting a MMN and P300 respectively, were administered in 60 healthy adults during simultaneous high-density EEG recording. For both the MMN and P300, eLORETA source reconstruction was performed. The maximal cross-correlation was calculated between ROI-pairs to investigate inter-regional functional connectivity specific to passive and active deviant processing. MMN activation clusters were identified in the temporal (insula, superior temporal gyrus and temporal pole), frontal (rostral middle frontal and pars opercularis) and parietal (postcentral and supramarginal gyrus) cortex. Passive discrimination of deviant phonemes was aided by a network connecting right temporoparietal cortices to left frontal areas. For the P300, clusters with significantly higher activity were found in the frontal (caudal middle frontal and precentral), parietal (precuneus) and cingulate (posterior and isthmus) cortex. Significant intra- and interhemispheric connections between parietal, cingulate and occipital regions constituted the network governing active phonemic target detection. A predominantly bilateral network was found to underly both the MMN and P300. While passive phoneme discrimination is aided by a fronto-temporo-parietal network, active categorization calls on a network entailing fronto-parieto-cingulate cortices. Neural processing of phonemic contrasts, as reflected by the MMN and P300, does not appear to show pronounced lateralization to the language-dominant hemisphere.

Bayesian merged utilization of GRAPPA and SENSE (BMUGS) for in-plane accelerated reconstruction increases fMRI detection power

In fMRI, capturing brain activity during a task is dependent on how quickly the k-space arrays for each volume image are obtained. Acquiring the full k-space arrays can take a considerable amount of time. Under-sampling k-space reduces the acquisition time, but results in aliased, or "folded," images after applying the inverse Fourier transform (IFT). GeneRalized Autocalibrating Partial Parallel Acquisition (GRAPPA) and SENSitivity Encoding (SENSE) are parallel imaging techniques that yield reconstructed images from subsampled arrays of k-space. With GRAPPA operating in the spatial frequency domain and SENSE in image space, these techniques have been separate but can be merged to reconstruct the subsampled k-space arrays more accurately. Here, we propose a Bayesian approach to this merged model where prior distributions for the unknown parameters are assessed from a priori k-space arrays. The prior information is utilized to estimate the missing spatial frequency values, unalias the voxel values from the posterior distribution, and reconstruct into full field-of-view images. Our Bayesian technique successfully reconstructed simulated and experimental fMRI time series with no aliasing artifacts while decreasing temporal variation and increasing task detection power.