BACKGROUND:Post-COVID condition (PCCo) affects 5% to 10% of individuals following SARS-CoV-2 infection, with cognitive disturbances being a major feature. Central hypotheses regarding its pathophysiology include disturbed cell energy metabolism and oxidative stress pointing to mitochondrial dysfunction. However, brain energy metabolism remains unexplored. METHODS:We investigated cerebral high-energy phosphate metabolism in 27 patients with PCCo and 23 fully recovered control participants using whole-brain 31P-magnetic resonance spectroscopic imaging at 3T. Adenosine triphosphate/phosphocreatine (ATP/PCr) ratios were quantified throughout the brain and analyzed with voxel-based and regional statistics including correlations with neuropsychological performance (Montreal Cognitive Assessment and Trail Making Test Part B). Statistical analysis used voxelwise comparisons with age as covariate, followed by region-of-interest analysis of cingulate cortex subdivisions. RESULTS:Patients with PCCo showed a significant cluster of reduced ATP/PCr ratios centered on the cingulate cortex. Regional analysis revealed consistent reductions across the anterior cingulate cortex (ACC), midcingulate cortex (MCC), and posterior cingulate cortex. Lower ATP/PCr ratios in the ACC specifically correlated with poorer cognitive performance. Exploratory analyses revealed a trend toward higher intracellular pH in the MCC, with significant negative correlation between pH and ATP/PCr observed only in patients, suggesting disease-specific alterations in pH regulation and bioenergetic homeostasis. Subgroup analysis showed similar metabolic alterations in patients with PCCo who met criteria for myalgic encephalomyelitis/chronic fatigue syndrome. CONCLUSIONS:Our study provides the first in vivo evidence of impaired brain energy metabolism in PCCo, with anterior cingulate dysfunction directly linked to cognitive impairment. The observed pH-ATP/PCr relationship suggests broader disruption of cellular bioenergetic regulation. These findings support mitochondrial dysfunction as a key pathophysiological mechanism and may inform targeted therapeutic strategies.

Combining Magnetic Resonance Images (MRI) from different sources is an increasingly common practice that holds high scientific value. Differences in acquisition parameters and participant characteristics can lead to variations in image quality, highlighting the importance of ensuring these variations do not result in biased statistical outcomes. Here, we investigated contributions of both technical and participant-related factors to MRI quality. We examined how technical factors (scanner hardware, software, and acquisition protocols) affect the Image Quality Rating (IQR) of anatomical MRI. We also evaluated the stability of IQR over time, examined the effects of defacing on image quality, and investigated how participant characteristics (age, sex, and mental health) influence IQR. We collected 2779 T1-weighted volumes, acquired at two different scanner sites (both Siemens 3 Tesla), using two coil array designs (64-channel and 32-channel array), and four scanner software versions (VB17, VB15, VE11, XA30), five acquisition protocols, including two different spatial resolutions (1 mm, 0.8 mm isotropic). Data were collected from 910 healthy controls (HC) (499 women, mean age 27.55 ± 11.27) and from 563 individuals (321 women, mean age 36.42 ± 12.93) with various clinical conditions (125 Major Depressive Disorder [MDD], 43 Autism Spectrum Disorder [AUT], 81 Alcohol Use Disorder [AUD], 104 Schizophrenia [SZ], 70 Chronic Pain [CP], 41 Bipolar Disorder [BD], and 100 with unspecified disease [NHC]). Structural images were preprocessed and analyzed using the quality control pipelines of the Computational Anatomy Toolbox (CAT12, https://neuro-jena.github.io/cat12-help/), which provide an image quality rating (IQR) index for each image, with higher IQR indicating a lower image quality. There was no significant effect of scanner site or coil design on IQR. We found a significant effect of scanner software, with lower image quality for VB17 compared with VB15. There was a significant effect of acquisition protocols (i.e., IQR with protocol "T1_1mm_extended" was higher than with others protocols), and image spatial resolution had a significant impact on IQR, with higher IQR values for 1 mm compared to 0.8 mm. Within participants, IQR was stable across sessions, showing minimal day-to-day variability. Defacing had no significant impact on IQR. Regarding participant characteristics, we observed a significant interaction between sex and age: IQR increased with age in men but not in women. Additionally, participants with SZ had a significant higher IQR compared to HC and MDD. This study provides a comprehensive assessment of the influence of technical and participant-related factors on MRI quality. The findings also support IQR as a robust indicator of image quality and emphasize the importance of integrating image quality metrics, both in multicentric studies and within individual research centers. Incorporating IQR as a quality metric would help minimize biases from image quality variations, enabling a more accurate assessment of underlying structural differences and leading to more reliable findings.

The midbrain dopamine system contributes to important neural functions in the basal ganglia, and is involved in aspects of pathological processes in schizophrenia. In preclinical and clinical studies, pharmacological blockade or stimulation of brain dopamine receptors alters cerebral perfusion, which is a surrogate marker of metabolic activity. However, there is scant documentation of this neurofunctional coupling in relation to individual differences in the dopamine system of healthy humans. We therefore tested the hypothesis that baseline dopamine D2/3 receptor availability predicts individual blood flow responses to challenge with a dopamine agonist.We used [18F]fallypride positron emission tomography (PET) imaging to quantify dopamine D2/3 receptor availability as binding potential (BPND) in nine healthy subjects. Using simultaneous perfusion-weighted functional magnetic resonance imaging (fMRI), we measured perfusion at baseline and after challenge with the dopamine agonist apomorphine.Results of this multimodal imaging study revealed a strong negative association between baseline D2/3 dopamine receptor availability and apomorphine-induced perfusion changes in the human basal ganglia. There was considerable intra-individual variation in the neurovascular response to the apomorphine challenge, which may call for further investigation of the dopaminergic regulation of cerebral perfusion in patients with schizophrenia.This study describes a novel paradigm for assessing dopamine sensitivity, facilitating an exploration of the dopamine supersensitivity hypothesis.

Continuous real-time functional magnetic resonance imaging (fMRI) neurofeedback is gaining increasing scientific attention in clinical neuroscience and may benefit from the short repetition times of modern multiband echoplanar imaging sequences. However, minimizing feedback delay can result in technical challenges. Here, we report a technical problem we experienced during continuous fMRI neurofeedback with multiband echoplanar imaging and short repetition times. We identify the possible origins of this problem, describe our current interim solution and provide openly available workflows and code to other researchers in case they wish to use a similar approach.

•EEG-assessed pre-target activity predicts speech-in-noise recognition.•α activity in left temporal areas predicts speech recognition probability.•Enhanced α power increases recognition probability of less heavily masked targets.•Enhanced α power decreases recognition probability of more heavily masked targets.

Speech elicits brain activity time-locked to its amplitude envelope. The resulting speech-brain synchrony (SBS) is thought to be crucial to speech parsing and comprehension. It has been shown that higher speech-brain coherence is associated with increased speech intelligibility. However, studies depending on the experimental manipulation of speech stimuli do not allow conclusion about the causality of the observed tracking. Here, we investigate whether individual differences in the intrinsic propensity to track the speech envelope when listening to speech-in-quiet is predictive of individual differences in speech-recognition-in-noise, in an independent task. We evaluated the cerebral tracking of speech in source-localized magnetoencephalography, at timescales corresponding to the phrases, words, syllables and phonemes. We found that individual differences in syllabic tracking in right superior temporal gyrus and in left middle temporal gyrus (MTG) were positively associated with recognition accuracy in an independent words-in-noise task. Furthermore, directed connectivity analysis showed that this relationship is partially mediated by top-down connectivity from premotor cortex-associated with speech processing and active sensing in the auditory domain-to left MTG. Thus, the extent of SBS-even during clear speech-reflects an active mechanism of the speech processing system that may confer resilience to noise.

Resting brain (rs) activity has been shown to be a reliable predictor of the level of foreign language (L2) proficiency younger adults can achieve in a given time-period. Since rs properties change over the lifespan, we investigated whether L2 attainment in older adults (aged 64–74 years) is also predicted by individual differences in rs activity, and to what extent rs activity itself changes as a function of L2 proficiency. To assess how neuronal assemblies communicate at specific frequencies to facilitate L2 development, we examined localized and global measures (Minimum Spanning Trees) of connectivity. Results showed that central organization within the beta band (~ 13–29.5 Hz) predicted measures of L2 complexity, fluency and accuracy, with the latter additionally predicted by a left-lateralized centro-parietal beta network. In contrast, reduced connectivity in a right-lateralized alpha (~ 7.5–12.5 Hz) network predicted development of L2 complexity. As accuracy improved, so did central organization in beta, whereas fluency improvements were reflected in localized changes within an interhemispheric beta network. Our findings highlight the importance of global and localized network efficiency and the role of beta oscillations for L2 learning and suggest plasticity even in the ageing brain. We interpret the findings against the background of networks identified in socio-cognitive processes.

Silencing of dopamine transporter (DAT), a main controlling factor of dopaminergic signaling, results in biochemical and behavioral features characteristic for neuropsychiatric diseases with presumed hyperdopaminergia including schizophrenia, attention deficit hyperactivity disorder (ADHD), bipolar disorder, and obsessive-compulsive disorder (OCD). Investigation of DAT silencing thus provides a transdiagnostic approach towards a systems-level understanding of common underlying pathways. Using a high-field multimodal imaging approach and a highly sensitive cryogenic coil, we integrated structural, functional and metabolic investigations in tandem with behavioral assessments on a newly developed preclinical rat model, comparing DAT homozygous knockout (DAT-KO, N = 14), heterozygous knockout (N = 8) and wild-type male rats (N = 14). We identified spatially distributed structural and functional brain alterations encompassing motor, limbic and associative loops that demonstrated strong behavioral relevance and were highly consistent across imaging modalities. DAT-KO rats manifested pronounced volume loss in the dorsal striatum, negatively correlating with cerebellar volume increase. These alterations were associated with hyperlocomotion, repetitive behavior and loss of efficient functional small-world organization. Further, prefrontal and midbrain regions manifested opposite changes in functional connectivity and local network topology. These prefrontal disturbances were corroborated by elevated myo-inositol levels and increased volume. To conclude, our imaging genetics approach provides multimodal evidence for prefrontal-midbrain decoupling and striato-cerebellar neuroplastic compensation as two key features of constitutive DAT blockade, proposing them as transdiagnostic mechanisms of hyperdopaminergia. Thus, our study connects developmental DAT blockade to systems-level brain changes, underlying impaired action inhibition control and resulting in motor hyperactivity and compulsive-like features relevant for ADHD, schizophrenia and OCD.

Dysfunctions of the thyroid hormone (TH) transporting monocarboxylate transporter MCT8 lead to a complex X-linked syndrome with abnormal serum TH concentrations and prominent neuropsychiatric symptoms (Allan-Herndon-Dudley syndrome, AHDS). The key features of AHDS are replicated in double knockout mice lacking MCT8 and organic anion transporting protein OATP1C1 (Mct8/Oatp1c1 DKO). In this study, we characterize impairments of brain structure and function in Mct8/Oatp1c1 DKO mice using multimodal magnetic resonance imaging (MRI) and assess the potential of the TH analogue 3,3′,5-triiodothyroacetic acid (TRIAC) to rescue this phenotype. Structural and functional MRI were performed in 11-weeks-old male Mct8/Oatp1c1 DKO mice (N = 10), wild type controls (N = 7) and Mct8/Oatp1c1 DKO mice (N = 13) that were injected with TRIAC (400 ng/g bw s.c.) daily during the first three postnatal weeks. Grey and white matter volume were broadly reduced in Mct8/Oatp1c1 DKO mice. TRIAC treatment could significantly improve white matter thinning but did not affect grey matter loss. Network-based statistic showed a wide-spread increase of functional connectivity, while graph analysis revealed an impairment of small-worldness and whole-brain segregation in Mct8/Oatp1c1 DKO mice. Both functional deficits could be substantially ameliorated by TRIAC treatment. Our study demonstrates prominent structural and functional brain alterations in Mct8/Oatp1c1 DKO mice that may underlie the psychomotor deficiencies in AHDS. Additionally, we provide preclinical evidence that early-life TRIAC treatment improves white matter loss and brain network dysfunctions associated with TH transporter deficiency.

Identifying the circuits responsible for cognition and understanding their embedded computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach, from behavioral modeling and fMRI in task-performing mice to cellular recordings, in order to disentangle local network contributions to olfactory reinforcement learning. At mesoscale, fMRI identifies a functional olfactory-striatal network interacting dynamically with higher-order cortices. While primary olfactory cortices respectively contribute only some value components, the downstream olfactory tubercle of the ventral striatum expresses comprehensively reward prediction, its dynamic updating, and prediction error components. In the tubercle, recordings reveal two underlying neuronal populations with non-redundant reward prediction coding schemes. One population collectively produces stabilized predictions as distributed activity across neurons; in the other, neurons encode value individually and dynamically integrate the recent history of uncertain outcomes. These findings validate a cross-scale approach to mechanistic investigations of higher cognitive functions in rodents.

SUMMARYThe unbiased identification of brain circuits responsible for behavior and their local cellular computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach from behavioral modeling and fMRI in task-performing mice to cellular network dynamics to identify how reward predictions are represented in the forebrain upon olfactory conditioning. fMRI identified functional segregation in reward prediction and error computations among olfactory cortices and subcortical circuits. Among them, the olfactory tubercle contributed both to dynamic reward predictions and prediction error. In this region, cellular recordings revealed two parallel neuronal populations for prediction coding. One population produced stabilized predictions as distributed stimulus-bound transient network activity; the other evolved during anticipatory waiting and fully reflected predicted value in single-units, dynamically integrating the recent cue-specific history of uncertain outcomes. Thus, the cross-scale approach revealed regional functional differentiation among the distributed forebrain circuits with a limbic hotspot for multiple non-redundant reward prediction coding.

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

22q11.2, 15q13.3, and 1q21.1 microdeletions attract considerable interest by conferring high risk for a range of neuropsychiatric disorders, including schizophrenia and autism. A fundamental open question is whether divergent or convergent neural mechanisms mediate this genetic pleiotropic association with the same behavioral phenotypes. We use a combination of rodent microdeletion models with high-field neuroimaging to perform a comparative whole-brain characterization of functional and structural mechanisms linked to high-risk states. Resting-state functional and structural magnetic resonance imaging data were acquired on mice carrying heterozygous microdeletions in 22q11.2 (N = 12), 15q13.3 (N = 11), and 1q21.1 (N = 11) loci. We performed network-based statistic, graph, and morphometric analyses. The three microdeletions did not share significant systems-level features. Instead, morphometric analyses revealed microcephaly in 1q21.1 and macrocephaly in 15q13.3 deletions, whereas cerebellar volume was specifically reduced in 22q11.2 deletion. In function, 22q11.2 deletion mice showed widespread cortical hypoconnectivity, accompanied by opposing hyperconnectivity in dopaminergic pathways, which was confirmed by graph analysis. 1q21.1 exhibited distinct changes in posterior midbrain morphology and function, especially in periaqueductal gray, whereas 15q13.3 demonstrated alterations in auditory/striatal system. The combination of cortical hypoconnectivity and dopaminergic hyperconnectivity and reduced cerebellum in 22q11.2 deletion mirrors key neurodevelopmental features of schizophrenia, whereas changes in midbrain and auditory/striatal morphology and topology in 1q21.1 and 15q13.3 rather indicate focal processes possibly linked to the emergence of abnormal salience perception and hallucinations. In addition to insights into pathophysiological processes in these microdeletions, our results establish the general point that microdeletions might increase risk for overlapping neuropsychiatric phenotypes through separable neural mechanisms.

As ketamine is increasingly used as an effective antidepressant with rapid action, sustaining its short-lived efficacy over a longer period of time using a schedule of repeated injections appears as an option. An open question is whether repeated and single administrations would affect convergent neurocircuits. We used a combination of one of the most robust animal models of depression with high-field neuroimaging to perform a whole-brain delineation of functional mechanisms underlying ketamine’s effects. Rats from two genetic strains, depressive-like and resilient, received seven treatments of 10 mg/kg S-ketamine (N = 14 depressive-like, N = 11 resilient) or placebo (N = 12 depressive-like, N = 10 resilient) and underwent resting-state functional magnetic resonance imaging. Using graph theoretical models of brain networks, we compared effects of repeated ketamine with those of single administration from a separate dataset of our previous study. Compared to single treatment, repeated ketamine evoked strain-specific brain network randomization, resembling characteristics of the depressive-like strain and patients. Several affected regions belonged to the auditory, visual, and motor circuitry, hinting at possible cumulative side effects. Finally, when compared to saline, repeated ketamine affected only a few local topological properties and had no effects on global properties. In combination with the lack of clear differences compared to placebo, our findings point toward an inefficacy of ketamine’s long-term administration on brain topology, making questionable the postulated effect of repeated administration and being consistent with the recently reported absence of repeated ketamine’s antidepressant efficacy in several placebo-controlled studies.

Even in response to apparently simple tasks such as hand moving, human brain activity shows remarkable inter-subject variability. Presumably, this variability reflects genuine behavioural or functional variability. Recently, spatial variability of resting-state features in fMRI - specifically connectivity - has been shown to explain (spatial) task-response variability. Such a link, however, is still missing for M/EEG data and its spectrally rich structure. At the same time, it has recently been shown that task responses in M/EEG can be well represented using transient spectral events bursting at fast time scales. Here, we show that individual differences in the spatio-spectral structure of M/EEG task responses, can, to a reasonable degree, be predicted from individual differences in transient spectral events identified at rest. In a MEG dataset of diverse task conditions (including motor responses, working memory and language comprehension tasks) and resting-state sessions for each subject (n = 89), we used Hidden-Markov-Modelling to identify transient spectral events as a feature set to learn the mapping of space-time-frequency content from rest to task. Resulting trial-averaged, subject-specific task-response predictions were then compared with the actual task responses in left-out subjects. All task conditions were predicted significantly above chance. Furthermore, we observed a systematic relationship between genetic similarity (e.g. unrelated subjects vs. twins) and predictability. These findings support the idea that subject-specific transient spectral events in resting-state neural activity are linked to, and predictive of, subject-specific trial-averaged task responses in a wide range of experimental conditions.

The resting brain exhibits spontaneous patterns of activity that reflect features of the underlying neural substrate. Examination of inter-areal coupling of resting state oscillatory activity has revealed that the brain’s resting activity is composed of functional networks, whose topographies differ depending upon oscillatory frequency, suggesting a role for carrier frequency as a means of creating multiplexed, or functionally segregated, communication channels between brain areas. Using canonical correlation analysis, we examined spectrally resolved resting-state connectivity patterns derived from MEG recordings to determine the relationship between connectivity intrinsic to different frequency channels and a battery of over a hundred behavioural and demographic indicators, in a group of 89 young healthy participants. We demonstrate that each of the classical frequency bands in the range 1-40Hz (delta, theta, alpha, beta and gamma) delineates a subnetwork that is behaviourally relevant, spatially distinct, and whose expression is either negatively or positively predictive of individual traits, with the strongest link in the alpha band being negative and networks oscillating at different frequencies, such as theta, beta and gamma carrying positive function.

The role of neuronal oscillations in the processing of speech has recently come to prominence. Since resting-state (RS) brain activity has been shown to predict both task-related brain activation and behavioural performance, we set out to establish whether inter-individual differences in spectrally-resolved RS-MEG power are associated with variations in words-in-noise recognition in a sample of 88 participants made available by the Human Connectome Project. Positive associations with resilience to noise were observed with power in the range 21 and 29 Hz in a number of areas along the left temporal gyrus and temporo-parietal association areas peaking in left posterior superior temporal gyrus (pSTG). Significant associations were also found in the right posterior superior temporal gyrus in the frequency range 30-40 Hz. We propose that individual differences in words-in-noise performance are related to baseline excitability levels of the neural substrates of phonological processing.