A global optimisation method for robust affine registration of brain images

Automated neuroradiological support systems for multiple cerebrovascular disease markers - A systematic review and meta-analysis

Cerebrovascular diseases (CVD) can lead to stroke and dementia. Stroke is the second leading cause of death world wide and dementia incidence is increasing by the year. There are several markers of CVD that are visible on brain imaging, including: white matter hyperintensities (WMH), acute and chronic ischaemic stroke lesions (ISL), lacunes, enlarged perivascular spaces (PVS), acute and chronic haemorrhagic lesions, and cerebral microbleeds (CMB). Brain atrophy also occurs in CVD. These markers are important for patient management and intervention, since they indicate elevated risk of future stroke and dementia. We systematically reviewed automated systems designed to support radiologists reporting on these CVD imaging findings. We considered commercially available software and research publications which identify at least two CVD markers. In total, we included 29 commercial products and 13 research publications. Two distinct types of commercial support system were available: those which identify acute stroke lesions (haemorrhagic and ischaemic) from computed tomography (CT) scans, mainly for the purpose of patient triage; and those which measure WMH and atrophy regionally and longitudinally. In research, WMH and ISL were the markers most frequently analysed together, from magnetic resonance imaging (MRI) scans; lacunes and PVS were each targeted only twice and CMB only once. For stroke, commercially available systems largely support the emergency setting, whilst research systems consider also follow-up and routine scans. The systems to quantify WMH and atrophy are focused on neurodegenerative disease support, where these CVD markers are also of significance. There are currently no openly validated systems, commercially, or in research, performing a comprehensive joint analysis of all CVD markers (WMH, ISL, lacunes, PVS, haemorrhagic lesions, CMB, and atrophy).

Imaging the structural connectome with hybrid MRI-microscopy tractography

Mapping how neurons are structurally wired into whole-brain networks can be challenging, particularly in larger brains where 3D microscopy is not available. Multi-modal datasets combining MRI and microscopy provide a solution, where high resolution but 2D microscopy can be complemented by whole-brain but lowresolution MRI. However, there lacks unified approaches to integrate and jointly analyse these multi-modal data in an insightful way. To address this gap, we introduce a data-fusion method for hybrid MRI-microscopy fibre orientation and connectome reconstruction. Specifically, we complement precise "in-plane" orientations from microscopy with "through-plane" information from MRI to construct 3D hybrid fibre orientations at resolutions far exceeding that of MRI whilst preserving microscopy's myelin specificity, resulting in superior fibre tracking. Our method is openly available, can be deployed on standard 2D microscopy, including different microscopy contrasts, and is species agnostic, facilitating neuroanatomical investigation in both animal models and human brains.

Deciphering white matter microstructural alterations in catatonia according to ICD-11: replication and machine learning analysis

Catatonia is a severe psychomotor disorder characterized by motor, affective and cognitive-behavioral abnormalities. Although previous magnetic resonance imaging (MRI) studies suggested white matter (WM) dysconnectivity in the pathogenesis of catatonia, it is unclear whether microstructural alterations of WM tracts connecting psychomotor regions might contribute to a better classification of catatonia patients. Here, diffusion-weighted MRI data were collected from two independent cohorts (whiteCAT/replication cohort) of patients with (n = 45/n = 13) and without (n = 56/n = 26) catatonia according to ICD-11 criteria. Catatonia severity was examined using the Northoff (NCRS) and Bush-Francis (BFCRS) Catatonia Rating Scales. We used tract-based spatial statistics (TBSS), tractometry (TractSeg) and machine-learning (ML) to classify catatonia patients from tractometry values as well as tractomics features generated by the newly developed tool RadTract. Catatonia patients showed fractional anisotropy (FA) alterations measured via TractSeg in different corpus callosum segments (CC_1, CC_3, CC_4, CC_5 and CC_6) compared to non-catatonia patients across both cohorts. Our classification results indicated a higher level of performance when trained on tractomics as opposed to traditional tractometry values. Moreover, in the CC_6, we successfully trained two classifiers using the tractomics features identified in the whiteCAT data. These classifiers were applied separately to the whiteCAT and replication cohorts, demonstrating comparable performance with Area Under the Receiver Operating Characteristics (AUROC) values of 0.79 for the whiteCAT cohort and 0.76 for the replication cohort. In contrast, training on FA tractometry resulted in lower AUROC values of 0.66 for the whiteCAT cohort and 0.51 for the replication cohort. In conclusion, these findings underscore the significance of CC WM microstructural alterations in the pathophysiology of catatonia. The successful use of an ML based classification model to identify catatonia patients has the potential to improve diagnostic precision.

Early life adversity is associated with greater similarity in neural representations of ambiguous and threatening stimuli

Exposure to early life adversity (ELA) is hypothesized to sensitize threat-responsive neural circuitry. This may lead individuals to overestimate threat in the face of ambiguity, a cognitive-behavioral phenotype linked to poor mental health. The tendency to process ambiguity as threatening may stem from difficulty distinguishing between ambiguous and threatening stimuli. However, it is unknown how exposure to ELA relates to neural representations of ambiguous and threatening stimuli, or how processing of ambiguity following ELA relates to psychosocial functioning. The current fMRI study examined multivariate representations of threatening and ambiguous social cues in 41 emerging adults (aged 18 to 19 years). Using representational similarity analysis, we assessed neural representations of ambiguous and threatening images within affective neural circuitry and tested whether similarity in these representations varied by ELA exposure. Greater exposure to ELA was associated with greater similarity in neural representations of ambiguous and threatening images. Moreover, individual differences in processing ambiguity related to global functioning, an association that varied as a function of ELA. By evidencing reduced neural differentiation between ambiguous and threatening cues in ELA-exposed emerging adults and linking behavioral responses to ambiguity to psychosocial wellbeing, these findings have important implications for future intervention work in at-risk, ELA-exposed populations.

Functional divisions of the left anterior and posterior temporoparietal junction for phonological and semantic processing in Chinese character reading

Previous studies have shown that the left temporoparietal junction (TPJ) plays a critical role in word reading. Nevertheless, there is still controversy surrounding the phonological and semantic functions of the left TPJ. The parietal unified connectivity-biased computation (PUCC) model posits that the function of the left TPJ depends on both the neurocomputation of this local area and its long-range connectivity. To clarify the specific roles of different TPJ subregions in phonological and semantic processing of Chinese characters, the present study used connectivity-based clustering to identify seven subdivisions within the left TPJ, and conducted comprehensive analyses including functional and structural connectivity, univariate and multivariate analyses (i.e., representational similarity analysis, RSA) on multimodal imaging data (task-state fMRI, resting-state fMRI, and diffusion-weighted imaging [DWI]). Functional and structural connectivity analyses revealed that the left anterior TPJ had stronger connections with the phonological network, while the left posterior TPJ had stronger connections with the semantic network. RSA revealed that the left anterior and posterior TPJ represented phonological and semantic information of Chinese characters, respectively. More importantly, the phonological and semantic representations of the left TPJ were respectively correlated with its functional connectivity to the phonological and semantic networks. Altogether, our results provide a more elaborate perspective on the functional dissociation of the left anterior and posterior TPJ in phonological and semantic processing of Chinese characters, and support the PUCC model.

Intersection-based slice motion estimation for fetal brain imaging

Fetal MRI offers a broad spectrum of applications, including the investigation of fetal brain development and facilitation of early diagnosis. However, image quality is often compromised by motion artifacts arising from both maternal and fetal movement. To mitigate these artifacts, fetal MRI typically employs ultrafast acquisition sequences. This results in the acquisition of three (or more) orthogonal stacks along different spatial axes. Nonetheless, inter-slice motion can still occur. If left uncorrected, such motion can introduce artifacts in the reconstructed 3D volume. Existing motion-correction approaches often rely on a two-step iterative process involving registration followed by reconstruction. They tend to detect and remove a large number of misaligned slices, resulting in poor reconstruction quality. This paper proposes a novel reconstruction-independent method for motion correction. Our approach benefits from the intersection of orthogonal slices and estimates motion for each slice by minimizing the difference between the intensity profiles along their intersections. To address potential misalignments, we present an innovative machine learning-based classifier for identifying misaligned slices. The parameters of these slices are then corrected using a multistart optimization approach. Quantitative evaluation on simulated datasets demonstrates very low registration errors. Qualitative analysis on real data further highlights the effectiveness of our approach compared to state-of-the-art methods.

Emo-FilM: A multimodal dataset for affective neuroscience using naturalistic stimuli

The Emo-FilM dataset stands for Emotion research using Films and fMRI in healthy participants. This dataset includes emotion annotations by 44 raters for 14 short films with a combined duration of over 2½ hours and recordings of respiration, heart rate, and functional magnetic resonance imaging (fMRI) from a sample of 30 individuals watching the same films. 50 items were annotated including discrete emotions and emotion components from the domains of appraisal, motivation, motor expression, physiological response, and feeling. The ratings had a mean inter-rater agreement of 0.38. The fMRI data acquired at 3 Tesla is includes high-resolution structural and resting state fMRI for each participant. Physiological recordings included heart rate, respiration, and electrodermal activity. This dataset is designed, but not limited, to studying the dynamic neural processes involved in emotion experience. It has a high temporal resolution of annotations, and includes validations of annotations by the fMRI sample. The Emo-FilM dataset is a treasure trove for researching emotion in response to naturalistic stimulation in a multimodal framework.

Precision non-invasive brain stimulation: anin silicopipeline for personalized control of brain dynamics

Objective.Non-invasive brain stimulation (NIBS) offers therapeutic benefits for various brain disorders. Personalization may enhance these benefits by optimizing stimulation parameters for individual subjects.Approach.We present a computational pipeline for simulating and assessing the effects of NIBS using personalized, large-scale brain network activity models. Using structural MRI and diffusion-weighted imaging data, the pipeline leverages a convolutional neural network-based segmentation algorithm to generate subject-specific head models with up to 40 tissue types and personalized dielectric properties. We integrate electromagnetic simulations of NIBS exposure with whole-brain network models to predict NIBS-dependent perturbations in brain dynamics, simulate the resulting EEG traces, and quantify metrics of brain dynamics.Main results.The pipeline is implemented on o2S2PARC, an open, cloud-based infrastructure designed for collaborative and reproducible computational life science. Furthermore, a dedicated planning tool provides guidance for optimizing electrode placements for transcranial temporal interference stimulation. In two proof-of-concept applications, we demonstrate that: (i) transcranial alternating current stimulation produces expected shifts in the EEG spectral response, and (ii) simulated baseline network activity exhibits physiologically plausible fluctuations in inter-hemispheric synchronization.Significance.This pipeline facilitates a shift from exposure-based to response-driven optimization of NIBS, supporting new stimulation paradigms that steer brain dynamics towards desired activity patterns in a controlled manner.

The relationships of resting-state brain entropy (BEN), ovarian hormones and behavioral inhibition and activation systems (BIS/BAS)

Brain entropy (BEN) quantifies irregularity, disorder and uncertainty of brain activity. Recent studies have linked BEN, derived from resting-state functional magnetic resonance imaging (rs-fMRI), to cognition, task activation, neuromodulation, and pharmacological interventions. However, it remains unknown whether BEN can reflect the effects of hormonal fluctuations. Furthermore, ovarian hormones are known to modulate behavioral traits, such as inhibitory control and impulsivity, as measured by the Behavioral Inhibition and Activation Systems (BIS/BAS). In this study, we investigated how ovarian hormones influence BEN and BIS/BAS in young adult women. The forty-four participants (mean age = 22.61 ± 2.14 years) were obtained from OpenNeuro in the study. Ovarian hormones including estradiol (E2), progesterone (PROG) and BIS/BAS were acquired before scanning. The voxel-wise BEN maps were calculated from the preprocessed rs-fMRI images. Pearson's correlation and mediation analyses were used to assess the relationships between BEN and ovarian hormones as well as BIS/BAS. Our results revealed a negative correlation between BEN and PROG in frontoparietal network (FPN), including the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC), as well as in the limbic network, encompassing the amygdala, hippocampus, and parahippocampal cortex. In contrast, BEN showed a positive correlation with impulsivity traits measured by the BAS-drive subscale of BAS in the left DLPFC. Additionally, PROG was negatively correlated with impulsivity traits measured by BAS-drive. Results from mediation analysis demonstrated that PROG reduces impulsivity, as measured by BAS-drive, by decreasing BEN in the left DLPFC and subsequently increasing functional connectivity (FC) within this region. These findings provide the first evidence that BEN reflects the influence of PROG on brain function and behavior. Furthermore, they elucidate the neural mechanisms through which PROG modulates impulsivity traits measured by BAS-drive: PROG enhances the temporal coherence (decreased entropy) of neural activity in the left DLPFC, which in turn increases temporal synchronization (increased FC) within this region during resting-state, and then enhances executive control functions, thereby negatively regulating impulsivity. These findings provide new insights into our understanding of the effects of ovarian hormones on the brain and behavior in women.

Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans

Cortical stimulation with single pulses is a common technique in clinical practice and research. However, we still do not understand the extent to which it engages subcortical circuits that may contribute to the associated evoked potentials (EPs). Here we show that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the state of the targeted cortico-thalamic network. We then optogenetically dissect the underlying circuit in mice, demonstrating that the EPs late component is caused by a thalamic hyperpolarization and rebound. The magnitude of this late component correlates with bursting frequency and synchronicity of thalamic neurons, modulated by the subject's behavioral state. A simulation of the thalamo-cortical circuit highlights that both intrinsic thalamic currents as well as cortical and thalamic GABAergic neurons contribute to this response profile. We conclude that single pulse cortical stimulation engages cortico-thalamo-cortical circuits largely preserved across different species and stimulation modalities.

Relationships between brain activity, tryptophan-related gut metabolites, and autism symptomatology

While it has been suggested that alterations in the composition of gut microbial metabolites may play a causative role in the pathophysiology of autism spectrum disorder (ASD), it is not known how gut microbial metabolites are associated with ASD-specific brain alterations. In this cross-sectional, case-control observational study, (i) fecal metabolomics, (ii) task-based functional magnetic resonance imaging (fMRI), and (iii) behavioral assessments were obtained from 43 ASD and 41 neurotypical (NT) children, aged 8-17. The fMRI tasks used socio-emotional and sensory paradigms that commonly reveal strong evoked brain differences in ASD participants. Our results show that fecal levels of specific tryptophan-related metabolites, including kynurenate, were significantly lower in ASD compared to NT, and were associated with: 1) alterations in insular and cingulate cortical activity previously implicated in ASD; and 2) ASD severity and symptoms (e.g., ADOS scores, disgust propensity, and sensory sensitivities). Moreover, activity in the mid-insula and mid-cingulate significantly mediated relationships between the microbial tryptophan metabolites (indolelactate and tryptophan betaine) and ASD severity and disgust sensitivity. Thus, we identify associations between gut microbial tryptophan metabolites, ASD symptoms, and brain activity in humans, particularly in brain regions associated with interoceptive processing.

Sequential patterning of dynamic brain states distinguish Parkinson's disease patients with mild cognitive impairments

Parkinson's disease (PD) is a neurodegenerative disease which presents clinically with progressive impairments in motoric and cognitive functioning. Pathophysiologic mechanisms underlying these impairments are believed to be attributable to a breakdown in the spatiotemporal coordination of functional neural networks across multiple cortical and subcortical regions. The current investigation used resting state, functional magnetic resonance imaging (rs-fMRI) to determine whether the temporal characteristics or sequential patterning of dynamic functional network connectivity (dFNC) states could accurately distinguish among people with PD who had normal cognition (PD-NC, n = 18), those with PD who had mild cognitive impairment (PD-MCI, n = 15), and older-aged healthy control (HC, n = 22) individuals. Results indicated that the proportion of time during the rs-fMRI scan that was spent in each of three identified dFNC states (dwell time) differed among these three groups. Individuals in the PD-MCI group spent significantly more time in a dFNC state characterized by low functional network connectivity, relative to participants in both the PD-NC (p = 0.0226) and HC (p = 0.0027) cohorts and tend to spend less time in a state characterized by anti-correlated thalamo-cortical connectivity, relative to both the PD-NC (p = 0.016) and HC (p = 0.0562) groups. A machine-learning method using sequential pattern mining was also found to distinguish among the groups with moderate accuracies ranging from 0.53 to 0.80, revealing distinct sequential patterns in the temporal ordering of dFNC states. These findings underscore the potential of dFNC and sequential pattern mining as relevant methods for further exploration of the pathophysiologic underpinnings of cognitive impairment among people living with PD.

Oxygen extraction fraction changes in ischemic tissue from 24-72 hours to 12 months after successful reperfusion

Oxygen Extraction Fraction (OEF) is a critical measure of a tissue's metabolic state post-ischemic stroke. This study investigated OEF changes in stroke-affected tissue compared to healthy tissue, post-reperfusion. OEF maps generated from gradient echo MRI images of 87 ischemic stroke patients at three time points after successful Endovascular Thrombectomy (EVT) were analysed in a prospective longitudinal multicentre study. Regions of interest (ROIs) delineating the infarct areas and corresponding mirror regions were drawn. The MR-derived OEF index values were obtained from the ROIs and compared using Wilcoxon signed rank tests. The cross-sectional comparison of OEF index values revealed lower values in the infarct areas than the corresponding contralateral areas at all three time points after successful EVT, presented as median (interquartile range) [24-72 hours: 20.84 (17.56-26.82)% vs 27.56 (23.22-31.87)%; 3 months: 27.37 (23.28-30.35)% vs 32.55 (28.00-35.81)%; 12 months: 24.38 (22.35-29.77)% vs 29.39 (25.86-34.04)%, p < 0.001 for all three time points]. Longitudinally, relative OEF index values increased gradually over time [24-72 hours: 0.81 (0.67-0.87); 3 months: 0.86 (0.79-0.95); 12 months: 0.88 (0.75-0.95)]. The findings revealed that following successful EVT, OEF in infarct tissue improves over time, indicating potential tissue recovery.Trial registration name and URL: Post-Reperfusion Pathophysiology in Acute Ischemic Stroke https://trialsearch.who.int/Trial2.aspx?TrialID=ACTRN12624000629538.

Dynamic categorization rules alter representations in human visual cortex

Everyday tasks often require stimuli to be categorized dynamically, such that an identical object can elicit different responses based on the current decision rule. Traditionally, sensory regions have been viewed as separate from such context-dependent processing, functioning primarily to process incoming inputs. However, an alternative view suggests sensory regions also integrate inputs with current task goals, facilitating more efficient information relay to higher-level areas. Here we test this by asking human participants to visually categorize novel shape stimuli based on different decision boundaries. Using fMRI and multivariate analyses of retinotopically-defined visual areas, we show that cortical shape representations become more distinct across relevant decision boundaries in a context-dependent manner, with the largest changes in discriminability observed for stimuli near the decision boundary. Importantly, these modulations are associated with improved task performance. These findings demonstrate that visual cortex representations are adaptively modulated to support dynamic behavior.

A vectorial code for semantics in human hippocampus

As we listen to speech, our brains actively compute the meanings of individual words. Inspired by the success of large language models (LLMs), we hypothesized that the brain employs vectorial coding principles, such that meaning is reflected in distributed activity of single neurons. We recorded responses of hundreds of neurons in the human hippocampus, which has a well-established role in semantic coding, while participants listened to narrative speech. We find encoding of contextual word meaning in the simultaneous activity of neurons whose individual selectivities span multiple unrelated semantic categories. Like embedding vectors in semantic models, distance between neural population responses correlates with semantic distance; however, this effect was only observed in contextual embedding models (like BERT) and was reversed in non-contextual embedding models (like Word2Vec), suggesting that the semantic distance effect depends critically on contextualization. Moreover, for the subset of highly semantically similar words, even contextual embedders showed an inverse correlation between semantic and neural distances; we attribute this pattern to the noise-mitigating benefits of contrastive coding. Finally, in further support for the critical role of context, we find that neural response variance increases with lexical polysemy. Ultimately, these results support the hypothesis that semantic coding in the hippocampus follows vectorial principles.

Primate thalamic nuclei select abstract rules and shape prefrontal dynamics

Flexible behavior depends on abstract rules to generalize beyond specific instances and outcome monitoring to adjust actions. Cortical circuits are posited to read out rules from high-dimensional representations of task-relevant variables in prefrontal cortex (PFC). We instead hypothesized that converging inputs from PFC, directly or via basal ganglia (BGs), enable the thalamus to select rules. We measured activity across PFC and connected thalamic nuclei of monkeys applying rules. Abstract rule information first appeared in ventroanterior thalamus (VA)-the main thalamic hub between BG and PFC. Mediodorsal thalamus (MD) also represented rule information before PFC, persisting to help maintain activation of relevant PFC cell ensembles. MD, a major recipient of midbrain dopamine input, was the first to represent information about behavioral outcomes. A PFC-BG-thalamus model reproduced key findings, and thalamic-lesion modeling disrupted PFC rule representations. This suggests that the thalamus selects high-level cognitive information from PFC and monitors behavioral outcomes of these selections.

The intrinsic functional connectivity patterns of the phonological and semantic networks in word reading

Previous studies have revealed that phonological and semantic processing recruit separate brain networks. However, the intrinsic functional connectivity patterns of the phonological and semantic networks remain unclear. To address this issue, the present study explored the static and dynamic functional connectivity patterns of phonological and semantic networks during the resting state. The static functional connectivity pattern of the two networks was examined by adopting a voxel-based global brain connectivity (GBC) method. In this analysis, we estimated the within-network connectivity (WNC), between-network connectivity between phonological and semantic networks (BNC_PS), and between-network connectivity of the two language networks (i.e., phonological and semantic networks) with the non-language network (BNC_N). The results showed that both phonological and semantic networks exhibited stronger intra-network connectivity (i.e., WNC) than inter-network connectivity (i.e., BNC_PS and BNC_N), indicating that both networks are relatively encapsulated. For dynamic functional connectivity, three distinct dynamic functional states were identified. Specifically, State 1 showed an overall positive connectivity pattern. State 2 exhibited an overall weak connectivity pattern. State 3 showed positive intra-network connectivity and negative inter-network connectivity. These results suggested that phonological and semantic networks exhibited a flexible integration and segregation pattern over time. Taken together, our results revealed that the phonological and semantic networks showed an intra-network integration and inter-network segregation pattern. These findings deepen our understanding of the intrinsic functional connectivity patterns of language networks.

The effects of intermittent theta burst stimulation (iTBS) on resting-state brain entropy (BEN)

Intermittent theta burst stimulation (iTBS), a novel protocol within repetitive transcranial magnetic stimulation (rTMS), has shown superior therapeutic effects for depression compared to conventional high-frequency rTMS (HF-rTMS). However, the neural mechanisms underlying iTBS remain poorly understood. Brain entropy (BEN), a measure of the irregularity of brain activity, has recently emerged as a promising marker for regional brain function and has demonstrated sensitivity to depression and HF-rTMS. Given its potential, BEN may help elucidate the mechanisms of iTBS. In this study, we computed BEN using resting-state fMRI data from sixteen healthy participants obtained from OpenNeuro. Participants underwent iTBS over the left dorsolateral prefrontal cortex (L-DLPFC) at two different intensities (90 ​% and 120 ​% of resting motor threshold (rMT)) on separate days. We used a 2 ​× ​2 repeated measures analysis of variance (ANOVA) to analyze the interaction between iTBS stimulation intensity and the pre- vs. post-stimulation effects on BEN and paired sample t-tests to examine the specific BEN effects of iTBS at different intensities. Additionally, spatial correlation analysis was conducted to determine whether iTBS altered the baseline coupling between BEN and neurotransmitter receptors/transporters, to investigate potential neurotransmitter changes induced by iTBS. Our results indicate that subthreshold iTBS (90 ​% rMT) reduced striatal BEN, while suprathreshold iTBS (120 ​% rMT) increased it. Subthreshold iTBS led to changes in the baseline coupling between BEN and several neurotransmitter receptor/transporter maps, primarily involving serotonin (5-HT), cannabinoid (CB), acetylcholine (ACh), and glutamate (Glu). Our findings suggest that BEN is sensitive to the effects of iTBS, with different stimulation intensities having distinct effects on neural activity. Notably, subthreshold iTBS may offer more effective stimulation. This research highlights the crucial role of stimulation intensity in modulating brain activity and lays the groundwork for future clinical studies focused on optimizing therapeutic outcomes through precise stimulation intensity.

Romer-EPTI: Rotating-view motion-robust super-resolution EPTI for SNR-efficient distortion-free in-vivo mesoscale diffusion MRI and microstructure imaging

PURPOSE

To overcome the major challenges in diffusion MRI (dMRI) acquisition, including limited SNR, distortion/blurring, and susceptibility to motion artifacts.

THEORY AND METHODS

A novel Romer-EPTI technique is developed to achieve SNR-efficient acquisition while providing distortion-free imaging, minimal spatial blurring, high motion robustness, and simultaneous multi-TE imaging. It introduces a ROtating-view Motion-robust supEr-Resolution technique (Romer) combined with a distortion/blurring-free Echo Planar Time-resolved Imaging (EPTI) readout. Romer enhances SNR through simultaneous multi-thick-slice acquisition with rotating-view encoding, while providing high motion-robustness via a high-fidelity, motion-aware super-resolution reconstruction. Instead of EPI, the in-plane encoding is performed using EPTI readout to prevent geometric distortion, T2/T2*-blurring, and importantly, dynamic distortions that could introduce additional blurring/artifacts after super-resolution reconstruction due to combining volumes with inconsistent geometries. This further improves effective spatial resolution and motion robustness. Additional developments include strategies to address slab-boundary artifacts, achieve minimized TE and optimized readout for additional SNR gain, and increase robustness to strong phase variations at high b-values.

RESULTS

Using Romer-EPTI, we demonstrated distortion-free whole-brain mesoscale in-vivo dMRI at both 3T (500-μm isotropic [iso] resolution) and 7T (485-μm iso resolution) for the first time. Motion experiments demonstrated the technique's motion robustness and its ability to obtain high-resolution diffusion images in the presence of subject motion. Romer-EPTI also demonstrated high SNR gain and robustness in high b-value (b = 5000 s/mm2) and time-dependent dMRI.

CONCLUSION

The high SNR efficiency, improved image quality, and motion robustness of Romer-EPTI make it a highly efficient acquisition for high-resolution dMRI and microstructure imaging.

Long-chain omega-3 polyunsaturated fatty acids are associated with brain connectivity and mood in young adults with subthreshold depression: A preliminary study

BACKGROUND

The long-chain omega-3 polyunsaturated fatty acids (PUFAs) docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) have beneficial effects in depression, and these effects may be mediated via changes in functional brain connectivity. However, little is known about these effects in those with subthreshold depression.

METHODS

15 Participants aged 18-29 years with Patient Health Questionnaire-8 (PHQ-8) scores ≥ 4 and Generalised Anxiety Disorder Assessment-7 (GAD-7) scores ≥ 5, underwent resting-state functional magnetic resonance imaging. Whole-brain, seed-based connectivity analyses were performed using bilateral orbitofrontal cortex (OFC) and amygdala seeds. Omega-3 and -6 PUFA status was assessed from dried bloodspot analysis of %DHA, %EPA, Omega-3 Index (calculated as the sum of DHA plus EPA expressed as a percentage of the total measured fatty acids and a correction applied as dried blood spot samples were used instead of erythrocytes) and ratio of the omega-6 PUFA arachidonic acid (ARA) to EPA (ARA/EPA).

RESULTS

PHQ-8 scores indicated subthreshold depression (mean = 10.0; SD = 4.2) and were negatively associated with DHA levels and Omega-3 Index. Significant negative associations were also identified between connectivity of the OFC with the angular gyrus and DHA and Omega-3 Index, while weaker connectivity of these regions was associated with lower PHQ-8 and GAD-7 scores. DHA and Omega-3 Index values were significantly associated with greater connectivity of the amygdala with the posterior cingulate cortex, which was also associated with lower PHQ-8 scores.

CONCLUSIONS

Higher omega-3 PUFA status in young adults with moderate, but mean subthreshold depression was associated with lower depression rating scores and altered functional connectivity of brain regions shown to play a role in the neurobiology of depression.

The Neural Oscillatory Basis of Perspective-Taking in Autistic and Non-Autistic Adolescents Using Magnetoencephalography

Taking another's perspective is a high-level mental skill underlying many aspects of social cognition. Perspective-taking is usually an embodied egocentric process whereby people mentally rotate themselves away from their physical location into the other's orientation. This is accompanied by increased theta-band (3-7 Hz) brain oscillations within a widespread fronto-parietal cortical network including the temporoparietal junction. Individuals with autism spectrum conditions (ASC) have been reported to experience challenges with high-level perspective-taking, particularly when adopting embodied strategies. To investigate the potential neurophysiological basis of these autism-related individual differences, we used magnetoencephalography in combination with a well-replicated perspective-taking paradigm in a group of 18 autistic and 17 age-matched non-autistic adolescents. Findings revealed that increasing the angle between self and other perspective resulted in prolonged reaction times for the autistic group during perspective-taking. This was accompanied by reduced theta power across a wide network of regions typically active during social cognitive tasks. On the other hand, the autistic group showed greater alpha power decreases in visual cortex compared with the non-autistic group across all perspective-taking conditions. These divergent theta and alpha power effects, coupled with steeper response time slopes, suggest that autistic individuals may rely more on alternative cognitive strategies, such as mental object rotation, rather than an egocentric embodied approach. Finally, no group differences were found when participants were asked to track, rather than take, another's viewpoint, suggesting that autism-related individual differences are specific to high-level perspective-taking.

M2OCNN: Many-to-One Collaboration Neural Networks for simultaneously multi-modal medical image synthesis and fusion

BACKGROUND AND OBJECTIVE

Acquiring comprehensive information from multi-modal medical images remains a challenge in clinical diagnostics and treatment, due to complex inter-modal dependencies and missing modalities. While cross-modal medical image synthesis (CMIS) and multi-modal medical image fusion (MMIF) address certain issues, existing methods typically treat these as separate tasks, lacking a unified framework that can generate both synthesized and fused images in the presence of missing modalities.

METHODS

In this paper, we propose the Many-to-One Collaboration Neural Network (M2OCNN), a unified model designed to simultaneously address CMIS and MMIF. Unlike traditional approaches, M2OCNN treats fusion as a specific form of synthesis and provides a comprehensive solution even when modalities are missing. The network consists of three modules: the Parallel Untangling Hybrid Network, Comprehensive Feature Router, and Series Omni-modal Hybrid Network. Additionally, we introduce a mixed-resolution attention mechanism and two transformer variants, Coarsormer and ReCoarsormer, to suppress high-frequency interference and enhance model performance. M2OCNN outperformed state-of-the-art methods on three multi-modal medical imaging datasets, achieving an average PSNR improvement of 2.4 dB in synthesis tasks and producing high-quality fusion images despite missing modalities. The source code is available at https://github.com/zjno108/M2OCNN.

CONCLUSION

M2OCNN offers a novel solution by unifying CMIS and MMIF tasks in a single framework, enabling the generation of both synthesized and fused images from a single modality. This approach sets a new direction for research in multi-modal medical imaging, with implications for improving clinical diagnosis and treatment.

Experimentally induced colitis impacts myelin development and home-cage behavior in young pigs regardless of supplementation with oral gamma-cyclodextrin-encapsulated tributyrin

Introduction

Colitis, a chronic intestinal disorder that causes inflammation of the colonic mucosa, has been linked with structural brain abnormalities. To combat intestinal inflammation, researchers have investigated how nutritional supplementation, such as butyric acid, may ameliorate untoward effects. By encapsulating and using conjugates of butyrate, such as butyrate glycerides (i.e., tributyrin), slower release to the lower portions of the gastrointestinal tract can be achieved. Additionally, butyrate supplementation has been linked with supporting brain function and regulating integrity.

Methods

In the present study, a total of 24 intact male pigs were artificially reared and randomly assigned to 1 of 3 treatment conditions: (1) a control milk replacer (CON), (2) control plus oral dextran sodium sulfate (DSS) to induce colitis, or (3) control supplemented with 9.0 mM of gamma-cyclodextrin encapsulated tributyrin (TBCD) plus oral DSS (TBCD+DSS). Pigs were orally administered DSS treatments daily from postnatal day (PND) 14-18. Continuous video recording began on PND 3 and ceased on PND 27 or 28, with videos processed and analyzed for home-cage tracking behavior. On PND 26 or 27, pigs underwent neuroimaging procedures to assess overall brain anatomy (MPRAGE), microstructure (DTI), and myelin (MWF).

Results and discussion

Home-cage spatial preference was not altered prior to DSS dosing or during the overall study period. However, TBCD+DSS pigs spent less (p < 0.05) time within quadrant 4 when compared with CON pigs. Across almost all 29 brain regions assessed, absolute volumes were observed to be smaller in the TBCD+DSS group compared with CON and DSS groups. However, once individual volumes were assessed relative to the whole brain, most treatment effects dissipated other than for gray matter volume (p = 0.041). Diffusivity was found to be altered in several regions across treatment groups, thereby indicating differences in fiber organization. In areas like the hippocampus and thalamus, when fractional anisotropy (FA) values were highest for a given treatment, in the other diffusion metrics (mean, radial, axial diffusivity) values were lowest for that same treatment, indicating more organized cellular structure. Several other diffusion trends and differences were observed across various regions. Lastly, myelin water fraction (MWF) values were lowest in DSS-treated groups compared with CON (p < 0.05) for the whole brain and left/right cortices.

Conclusion

Overall, fiber organization and myelination were observed to be altered by experimentally induced colitis and contrary to expectations, tributyrin supplementation did not ameliorate these effects. Future work is warranted to investigate other protective nutritional mechanisms for colitis.

Neural dynamics of semantic control underlying generative storytelling

Storytelling has been pivotal for the transmission of knowledge across human history, yet the role of semantic control and its associated neural dynamics has been poorly investigated. Here, human participants generated stories that were either appropriate (ordinary), novel (random), or balanced (creative), while recording functional magnetic resonance imaging (fMRI). Deep language models confirmed participants adherence to task instructions. At the neural level, linguistic and visual areas exhibited neural synchrony across participants regardless of the semantic control level, with parietal and frontal regions being more synchronized during random ideation. Importantly, creative stories were differentiated by a multivariate pattern of neural activity in frontal and fronto-temporo-parietal cortices compared to ordinary and random stories. Crucially, similar brain regions were also encoding the features that distinguished the stories. Moreover, we found specific spatial frequency patterns underlying the modulation of semantic control during story generation, while functional coupling in default, salience, and control networks differentiated creative stories with their controls. Remarkably, the temporal irreversibility between visual and high-level areas was higher during creative ideation, suggesting the enhanced hierarchical structure of causal interactions as a neural signature of creative storytelling. Together, our findings highlight the neural mechanisms underlying the regulation of semantic exploration during narrative ideation.

Changes in cerebrovascular reactivity within functional networks in older adults with long-COVID

Introduction

Cognitive symptoms are reported in the vast majority of individuals with long-COVID and there is growing support to suggest neurovascular mechanisms may play a role. Older adults are at increased risk for developing complications associated with COVID-19, including heightened risk for cognitive decline. Cerebrovascular Reactivity (CVR), a marker of neurovascular health, has been linked to age related cognitive decline and may play a role in long-COVID, however, this has not yet been explored.

Methods

The present study examined group differences in CVR in 31 older adults with long-COVID compared to 31 cognitively unimpaired older adults without long-COVID symptoms. Follow up analyses were conducted to examine how CVR was associated with both subjective cognitive symptoms and neuropsychological (NP) test performance. A subject-specific approach, Distribution-Corrected Z-scores (DisCo-Z), was used.

Results

Analyses revealed the long-COVID group demonstrated significantly greater incidence of extreme CVR clusters within the brain (>100 voxels) and within functional networks thought to drive attention and executive function. Extreme positive CVR clusters were positively associated with greater number of subjective cognitive symptoms and negatively correlated with NP performance.

Discussion

These findings are among the first to provide a link between cognitive functioning in long-COVID and neurovascular changes relevant for aging and mechanistic studies of long-COVID.

Temporal Apparent Diffusion Coefficient Changes During Chemoradiation: An Imaging Biomarker for Tumor Response Monitoring and Spatial Recurrence Prediction in Glioblastoma

PURPOSE

Apparent diffusion coefficient (ADC) from diffusion-weighted imaging has been shown to detect early treatment response in glioblastoma. This prospective observational serial imaging study aimed to compare ADC changes in gross tumor volume (GTV) regions that developed recurrence versus those that remained recurrence-free.

METHODS AND MATERIALS

Patients with glioblastoma underwent diffusion-weighted imaging at radiation planning (baseline, fraction 0), fraction 10, fraction 20, and 1 month after completing a 6-week course of chemoradiation. Recurrence was contoured at the earliest magnetic resonance imaging showing progression. The intersection of the GTV and recurrence was labeled resistant-GTV, whereas nonintersecting GTV was labeled sensitive-GTV. ADC values and percentage changes from fraction 0 were compared between these regions.

RESULTS

Eighty patients were analyzed. Median absolute ADC values for resistant (0.94 μm2/ms; IQR, 0.84-1.08) and sensitive-GTV (0.93 μm2/ms; IQR, 0.87-1.13) were similar at baseline (P = .193), but statistically significant differences were observed from the start of radiation therapy. Median ADC changes from baseline for resistant- and sensitive-GTV were +2.5% versus +15.1% at fraction 10 (P < .001), +8.1% versus +23.1% at fraction 20 (P < .001), and +21.2% versus +36.4% at 1 month after completing a 6-week course of chemoradiation (P <.001), respectively. Smaller ADC changes at fraction 10 (odds ratio, 0.95; P = .005) and fraction 20 (odds ratio, 0.95; P = .010) were independent predictors of increased risk of GTV failure, adjusting for O6-methylguanine DNA methyltransferase promoter methylation and extent of surgical resection.

CONCLUSIONS

Temporal ADC changes are promising imaging biomarkers for treatment response and spatial recurrence prediction and may provide a target for magnetic resonance imaging-guided biologically adapted radiation clinical trials.

The relation between cerebral small vessel function and white matter microstructure in monogenic and sporadic small vessel disease - the ZOOM@SVDs study

In cerebral small vessel disease (cSVD), vascular dysfunction has been associated with cSVD-lesions across the brain. Here we further explore the relation between vascular dysfunction and cSVD-related brain injury. We tested two hypotheses: (1) that complementary measures of abnormal small vessel function relate to decreased white matter integrity, and (2) that local variance in vascular dysfunction relates to local variance in white matter integrity within individual patients. We included 23 patients with monogenic cSVD (i.e. CADASIL) and 46 patients with sporadic cSVD. With whole-brain analyses, we tested if small vessel flow velocity and reactivity measures from 7T-MRI were associated with global peak-width-of-skeletonized-mean-diffusivity (PSMD). We also tested voxel-wise correlations between reactivity to hypercapnia and mean diffusivity (MD) in white matter. Whole-brain analyses showed a negative association between blood flow velocity and PSMD for the perforating arteries in the centrum semiovale in CADASIL (p = 0.04) and in the basal ganglia in sporadic cSVD (p = 0.002). Global white matter reactivity to hypercapnia was not associated with PSMD. Within patients, both in CADASIL and sporadic cSVD, we observed significant voxel-wise negative correlations for endothelial-independent vascular reactivity and MD in the white matter. These findings confirm our hypothesis that small vessel dysfunction in patients with cSVD is associated with microstructural white matter alterations, also at voxel level. The latter may reflect a direct relationship between local small vessel dysfunction and tissue injury.

Imaging Microstructural Parameters of Breast Tumor in Patient Using Time-Dependent Diffusion: A Feasibility Study

Objectives: To explore the feasibility of time-dependent diffusion in clinical applications of breast MRI, as well as the capacity of quantitative microstructural mapping for characterizing the cellular properties in malignant and benign breast tumors. Methods: 38 patients with 45 lesions were enrolled. Diffusion MRI acquisition was conducted with a combination of pulsed gradient spin-echo sequences (PGSE) and oscillating gradient spin-echo (OGSE) on a 3T MRI scanner. The microstructural parameters including cellularity extracellular diffusivity (Dex), mean cell size, intracellular volume fraction (νin), and the apparent diffusion coefficient (ADC) values were calculated. Each parameter was compared using the unpaired t-test between malignant and benign tumors. The area under the receiver operating characteristic curve (AUC) values was used to evaluate the diagnostic performance of different indices. Results: The mean diameter, Dex, ADC0Hz, ADC25Hz, and ADC50Hz were significantly lower in the malignant group than in the benign group (p < 0.001), while νin and cellularity were significantly higher in the malignant group (p < 0.001). All the microstructural parameters and time-dependent ADC values achieved high accuracy in differentiating between malignant and benign tumors of the breast. For microstructural parameters, the AUC of the cellularity was greater than others (AUC = 0.936). In an immunohistochemical subgroup comparison, the PR-positive group had significantly lower νin and cellularity, and significantly elevated Dex and ADC0Hz compared to the negative groups (p < 0.05). When combining diffusion parameters (cellularity, diameter, and ADC25Hz), the highest diagnostic performance was obtained with an AUC of 0.969. Conclusions: DWI with a short diffusion time is capable of providing additional microstructural parameters in differentiating between benign and malignant breast tumors. The time-dependent diffusion MRI parameters have the potential to serve as a non-invasive tool to probe the differences in the internal structures of breast lesions.

Functional Activation following Transcranial Magnetic Stimulation in Neurotypical Adult Readers

BACKGROUND

Transcranial magnetic stimulation (TMS) is considered a promising technique to noninvasively modulate cortical excitability and enhance cognitive functions. Despite the growing interest in using TMS to facilitate reading performance in learning disabilities, the immediate TMS-induced effects on brain activity during reading and language tasks in adults with typically developed reading skills remain to be further investigated. In the current study, we explored how a single offline session of intermittent theta burst stimulation (iTBS) delivered to core left-hemisphere nodes of the dorsal and ventral reading network changes brain activity during a spoken and written reading task.

METHODS

A total of 25 adults with typically developed reading skills participated in a sandwich design TMS-functional magnetic resonance imaging (fMRI) study, which was comprised of a baseline fMRI picture-word identification task that involved matching written or spoken words to picture cues, a single transcranial magnetic stimulation (TMS) session to either the left supramarginal gyrus (SMG) or the left middle temporal gyrus (MTG), followed by a post-stimulation fMRI session. A whole-brain analysis based on the general lineal model (GLM) was used to identify overall activated regions during the processing of spoken and written words. To identify differences between pre-and post-stimulation fMRI sessions, a paired sample t-test was conducted for each group separately (SMG and MTG groups).

RESULTS

Significant differences were found between pre-and post-stimulation fMRI sessions, with higher functional activation (post > pre) for spoken words only following SMG stimulation, and for both spoken and written words following MTG stimulation, in regions associated with the reading network and additional cognitive and executive control regions.

CONCLUSIONS

Our results showed how a single-offline TMS session can modulate brain activity at ~20 minutes post-stimulation during spoken and written word processing. The selective contribution of the SMG stimulation for auditory (spoken) word processing provides further evidence of the distinct role of the dorsal and ventral streams within the reading network. These findings could contribute to the development of neuromodulatory interventions for individuals with reading and language impairments.

CLINICAL TRIAL REGISTRATION

No: NCT04041960. Registered 29 July, 2019, https://clinicaltrials.gov/study/NCT04041960?cond=NCT04041960&rank=1 .

Neural Patterns of Social Pain in the Brain-Wide Representations Across Social Contexts

Empathy can be elicited by physiological pain, as well as in social contexts. Although physiological and different social contexts induce a strong subjective experience of empathy, the general and context-specific neural representations remain elusive. Here, it is combined fMRI with multivariate pattern analysis (MVPA) to establish neurofunctional models for social pain triggered by observing social exclusion and separation naturistic stimuli. The findings revealed that both social contexts engaged the empathy and social function networks. Notably, the intensity of pain empathy elicited by these two social stimuli does not significantly differentiate the neural representations of social exclusion and separation, suggesting context-specific neural representations underlying these experiences. Furthermore, this study established a model that traces the progression from physiological pain to social pain empathy. In conclusion, this study revealed the neural pathological foundations and interconnectedness of empathy induced by social and physiological stimuli and provide robust neuromarkers to precisely evaluate empathy across physiological and social domains.

Association of microstructural lesions of the corpus callosum with cognitive impairment in patients with high grade glioma

PURPOSE

Glioblastoma is one of the most common malignant brain tumors. To ensure a treatment that does not only lengthen survival, but also improves preservation of neurocognitive functions, reliable methods to measure changes in neurocognitive abilities at an early stage are necessary. The most direct way to objectify neurocognitive properties is neuropsychological testing. Neurocognitive decline is often based on lesions of the connectome. We take the corpus callosum (CC) as a reliable structure to identify decline of white matter (WM) integrity. We hypothesized a relation between compromised structural integrity in specific regions of the CC and neurocognitive deficits in glioma patients.

METHODS

We included 28 patients with high-grade glioma who underwent a neuropsychological test battery and MRI with Diffusion tensor imaging (DTI) preoperatively. MRI data was processed using the software fsl, Oxford. Neuropsychological parameters were correlated with the fractional anisotropy (FA) in three parts of the CC.

RESULTS

Preoperatively, most of the neuropsychological parameters correlated significantly with FA of at least one of the CC volumes. Higher FA-values were associated with better focus, memory, speed and speech fluency. Different tests examined the same neuropsychological parameter and then correlated with the same region of the CC.

CONCLUSIONS

We consider the FA of the CC for an adequate parameter to examine the influence of distant lesions on neurocognitive abilities.

Mild traumatic brain injury increases cortical iron: evidence from individual susceptibility mapping

Quantitative susceptibility mapping has been applied to map brain iron distribution after mild traumatic brain injury to understand properties of neural tissue which may be related to cellular dyshomeostasis. However, this is a heterogeneous injury associated with microstructural brain changes, and 'traditional' group-wise statistical approaches may lead to a loss of clinically relevant information, as subtle alterations at the individual level can be obscured by averages and confounded by within-group variability. More precise and individualized approaches are needed to characterize mild traumatic brain injury better and elucidate potential cellular mechanisms to improve intervention and rehabilitation. To address this issue, we use quantitative MRI to build individualized profiles of regional positive (iron-related) magnetic susceptibility across 34 bilateral cortical ROIs following mild traumatic brain injury. Healthy population templates were constructed for each cortical area using standardized Z-scores derived from 25 age-matched male controls aged between 16 and 32 years (M = 21.10, SD = 4.35), serving as a reference against which Z-scores of 35 males with acute (<14 days) sports-related mild traumatic brain injury were compared [M = 21.60 years (range: 16-33), SD = 4.98]. Secondary analyses sensitive to cortical depth and curvature were also generated to approximate the location of iron accumulation in the cortical laminae and the effect of gyrification. Primary analyses indicated that approximately one-third (11/35; 31%) of injured participants exhibited elevated positive susceptibility indicative of abnormal iron profiles relative to the healthy population, a finding that was mainly concentrated in regions within the temporal lobe. Injury severity was significantly higher (P = 0.02) for these participants than their iron-normal counterparts, suggesting a link between injury severity, symptom burden, and elevated cortical iron. Secondary exploratory analyses of cortical depth and curvature profiles revealed abnormal iron accumulation in 83% (29/35) of mild traumatic brain injury participants, enabling better localization of injury-related changes in iron content to specific loci within each region and identifying effects that may be more subtle and lost in region-wise averaging. Our findings suggest that individualized approaches can further elucidate the clinical relevance of iron in mild head injury. Differences in injury severity between iron-normal and iron-abnormal mild traumatic brain injury participants identified in our primary analysis highlight not only why precise investigation is required to understand the link between objective changes in the brain and subjective symptomatology, but also identify iron as a candidate biomarker for tissue pathology after mild traumatic brain injury.

Altered thalamotemporal structural connectivity is associated with autistic traits in children with ASD

BACKGROUND

Thalamocortical functional and structural connectivity alterations may contribute to clinical phenotype of Autism Spectrum Disorder (ASD). As previous studies focused mainly on thalamofrontal connections in ASD, we comprehensively investigated the thalamic functional networks and white matter pathways projecting also to temporal, parietal, occipital lobes and their associations with core and co-occurring conditions of this population.

METHODS

A total of 38 children (19 with ASD) underwent magnetic resonance imaging and behavioral assessment. Functional and structural scans were processed to analyze between-group thalamic connectivity differences and their relationships to measurements of autistic traits and language abilities.

RESULTS

No functional differences were found between groups across 20 networks in each hemisphere. However, we showed that the diffusion properties of thalamocortical pathways projecting to the right and left temporal lobes were disrupted in children with ASD. Additionally, there was a significant association between diffusion differences of thalamotemporal tracts and severity of autistic traits.

CONCLUSIONS

Our findings on altered thalamotemporal structural but not functional connectivity contribute to the understanding of white matter organization of thalamocortical pathways in children with ASD.

Semantic language decoding across participants and stimulus modalities

Brain decoders that reconstruct language from semantic representations have the potential to improve communication for people with impaired language production. However, training a semantic decoder for a participant currently requires many hours of brain responses to linguistic stimuli, and people with impaired language production often also have impaired language comprehension. In this study, we tested whether language can be decoded from a goal participant without using any linguistic training data from that participant. We trained semantic decoders on brain responses from separate reference participants and then used functional alignment to transfer the decoders to the goal participant. Cross-participant decoder predictions were semantically related to the stimulus words, even when functional alignment was performed using movies with no linguistic content. To assess how much semantic representations are shared between language and vision, we compared functional alignment accuracy using story and movie stimuli and found that performance was comparable in most cortical regions. Finally, we tested whether cross-participant decoders could be robust to lesions by excluding brain regions from the goal participant prior to functional alignment and found that cross-participant decoders do not depend on data from any single brain region. These results demonstrate that cross-participant decoding can reduce the amount of linguistic training data required from a goal participant and potentially enable language decoding from participants who struggle with both language production and language comprehension.

A role for the insula in establishing social dominance: structural and functional MRI studies in nonhuman primates

Awareness of one's position in the social hierarchy is essential for survival. Conversely, poor social cognition is associated with several neuropsychiatric diseases. Although brain regions that mediate understanding of the social hierarchy are poorly understood, recent evidence implicates the insula. Magnetic resonance imaging (MRI) scans were acquired in twelve individually housed male cynomolgus monkeys to determine whether structural and functional characteristics of the insular cortex predicted the social rank that monkeys would attain once they formed stable social hierarchies. Structural MRI revealed that left insular volume was significantly larger in monkeys that would become dominant vs. subordinate. No differences were observed in other areas including amygdala, caudate nucleus, or prefrontal cortex. Volumetric differences were localized to dorsal anterior regions of both left and right insulae. Functional MRI revealed that global correlation, a measure of connectedness to the rest of the brain, was significantly lower in the left insula of monkeys who would become dominant vs. subordinate. Moreover, the fractional amplitude of low-frequency fluctuations, a reflection of spontaneous brain activity, trended lower in bilateral insula in the future dominant monkeys. This prospective study provides evidence for a role of the insula in the establishment and maintenance of social dominance relationships.

Characterizing positive and negative quantitative susceptibility values in the cortex following mild traumatic brain injury: a depth- and curvature-based study

Evidence has linked head trauma to increased risk factors for neuropathology, including mechanical deformation of the sulcal fundus and, later, perivascular accumulation of hyperphosphorylated tau adjacent to these spaces related to chronic traumatic encephalopathy. However, little is known about microstructural abnormalities and cellular dyshomeostasis in acute mild traumatic brain injury in humans, particularly in the cortex. To address this gap, we designed the first architectonically motivated quantitative susceptibility mapping study to assess regional patterns of net positive (iron-related) and net negative (myelin-, calcium-, and protein-related) magnetic susceptibility across 34 cortical regions of interest following mild traumatic brain injury. Bilateral, between-group analyses sensitive to cortical depth and curvature were conducted between 25 males with acute (<14 d) sports-related mild traumatic brain injury and 25 age-matched male controls. Results suggest a trauma-induced increase in net positive susceptibility focal to superficial, perivascular-adjacent spaces in the parahippocampal sulcus. Decreases in net negative susceptibility values in distinct voxel populations within the same region indicate a potential dual pathology of neural substrates. These mild traumatic brain injury-related patterns were distinct from age-related processes revealed by correlation analyses. Our findings suggest depth- and curvature-specific deposition of biological substrates in cortical tissue convergent with features of misfolded proteins in trauma-related neurodegeneration.

Motor somatotopy impacts imagery strategy success in human intracortical brain-computer interfaces

Objective:The notion of a somatotopically organized motor cortex, with movements of different body parts being controlled by spatially distinct areas of cortex, is well known. However, recent studies have challenged this notion and suggested a more distributed representation of movement control. This shift in perspective has significant implications, particularly when considering the implantation location of electrode arrays for intracortical brain-computer interfaces (iBCIs). We sought to evaluate whether the location of neural recordings from the precentral gyrus, and thus the underlying somatotopy, has any impact on the imagery strategies that can enable successful iBCI control.Approach:Three individuals with a spinal cord injury were enrolled in an ongoing clinical trial of an iBCI. Participants had two intracortical microelectrode arrays implanted in the arm and/or hand areas of the precentral gyrus based on presurgical functional imaging. Neural data were recorded while participants attempted to perform movements of the hand, wrist, elbow, and shoulder.Main results:We found that electrode arrays that were located more medially recorded significantly more activity during attempted proximal arm movements (elbow, shoulder) than did lateral arrays, which captured more activity related to attempted distal arm movements (hand, wrist). We also evaluated the relative contribution from the two arrays implanted in each participant to decoding accuracy during calibration of an iBCI decoder for translation and grasping tasks. For both task types, imagery strategy (e.g. reaching vs wrist movements) had a significant impact on the relative contributions of each array to decoding. Overall, we found some evidence of broad tuning to arm and hand movements; however, there was a clear bias in the amount of information accessible about each movement type in spatially distinct areas of cortex.Significance:These results demonstrate that classical concepts of somatotopy can have real consequences for iBCI use, and highlight the importance of considering somatotopy when planning iBCI implantation.

Accuracy and Longitudinal Consistency of PET/MR Attenuation Correction in Amyloid PET Imaging amid Software and Hardware Upgrades

BACKGROUND AND PURPOSE

Integrated PET/MR allows the simultaneous acquisition of PET biomarkers and structural and functional MRI to study Alzheimer disease (AD). Attenuation correction (AC), crucial for PET quantification, can be performed by using a deep learning approach, DL-Dixon, based on standard Dixon images. Longitudinal amyloid PET imaging, which provides important information about disease progression or treatment responses in AD, is usually acquired over several years. Hardware and software upgrades often occur during a multiple-year study period, resulting in data variability. This study aims to harmonize PET/MR DL-Dixon AC amid software and head coil updates and evaluate its accuracy and longitudinal consistency.

MATERIALS AND METHODS

Tri-modality PET/MR and CT images were obtained from 329 participants, with a subset of 38 undergoing tri-modality scans twice within approximately 3 years. Transfer learning was used to fine-tune DL-Dixon models on images from 2 scanner software versions (VB20P and VE11P) and 2 head coils (16-channel and 32-channel coils). The accuracy and longitudinal consistency of the DL-Dixon AC were evaluated. Power analyses were performed to estimate the sample size needed to detect various levels of longitudinal changes in the PET standardized uptake value ratio (SUVR).

RESULTS

The DL-Dixon method demonstrated high accuracy across all data, irrespective of scanner software versions and head coils. More than 95.6% of brain voxels showed less than 10% PET relative absolute error in all participants. The median [interquartile range] PET mean relative absolute error was 1.10% [0.93%, 1.26%], 1.24% [1.03%, 1.54%], 0.99% [0.86%, 1.13%] in the cortical summary region, and 1.04% [0.83%, 1.36%], 1.08% [0.84%, 1.34%], 1.05% [0.72%, 1.32%] in cerebellum by using the DL-Dixon models for the VB20P 16-channel coil, VE11P 16-channel coil, and VE11P 32-channel coil data, respectively. The within-subject coefficient of variation and intraclass correlation coefficient of PET SUVR in the cortical regions were comparable between the DL-Dixon and CT AC. Power analysis indicated that similar numbers of participants would be needed to detect the same level of PET changes by using DL-Dixon and CT AC.

CONCLUSIONS

DL-Dixon exhibited excellent accuracy and longitudinal consistency across the 2 software versions and head coils, demonstrating its robustness for longitudinal PET/MR neuroimaging studies in AD.

Functional brain connectivity in early adolescence after hypothermia-treated neonatal hypoxic-ischemic encephalopathy

BACKGROUND

Neonatal hypoxic-ischemic encephalopathy (HIE) injures the infant brain during the basic formation of the developing functional connectome. This study aimed to investigate long-term changes in the functional connectivity (FC) networks of the adolescent brain following neonatal HIE treated with therapeutic hypothermia (TH).

METHODS

This prospective, population-based cohort study included all infants (n = 66) with TH-treated neonatal HIE in Stockholm during 2007-2009 and a control group (n = 43) of children with normal neonatal course. Assessment with resting-state functional magnetic resonance imaging (fMRI) was performed at Karolinska Institutet, Stockholm at age 9-12 years.

RESULTS

fMRI data met quality criteria for 35 children in the HIE-cohort (mean [SD] age at MRI: 11.2 [0.74] years, 46% male) and 30 children in the control group (mean [SD] age at MRI: 10.1 [0.78] years, 53% male). Adverse outcome was present in 40% of children in the HIE-cohort. Non-parametric statistical analysis failed to detect any significant (p < 0.001) alterations of FC networks in the HIE-cohort, nor between children in the HIE-cohort with or without neurological symptoms.

CONCLUSION

Findings of persistent alterations in specific functional networks did not remain significant after correction for multiple comparisons in this cohort of adolescent children exposed to TH-treated neonatal HIE.

IMPACT

Neonatal hypoxic-ischemic encephalopathy (HIE) could not be associated with alterations in functional connectivity in this cohort of adolescent children. Findings of aberrant connectivity identified in two functional networks were no longer significant after correction for multiple comparisons. Larger, multi-center studies are needed to understand whether network abnormalities persist long term and are related to outcomes in neonatal HIE.

Effects of alcohol and cannabis co-use on salience network resting state functional connectivity in individuals who drink alcohol heavily

INTRODUCTION

The salience network may be linked to addiction. Evidence suggests less salience network resting state functional connectivity (rsFC) from heavy alcohol use, but higher rsFC within and between brain networks from regular cannabis use. Given the rise in alcohol-cannabis co-use, the present study sought to elucidate rsFC between regions within the salience network and regions across the whole brain in individuals who use no drugs regularly, those who use alcohol only heavily, and those who co-use alcohol-cannabis.

METHODS

This is a secondary analysis of three clinical laboratory studies. A total of sixty individuals were classified into one of three groups based on their drug use: control (n = 16), heavy alcohol use only (n = 27), and heavy alcohol and regular cannabis co-use (n = 17). All participants completed resting state fMRI scans. Seed regions from the salience network were used to examine group differences in rsFC.

RESULTS

Main effects of group on rsFC emerged between the anterior cingulate cortex, left and right anterior insula, and left supramarginal gyrus seeds and regions associated with motor, sensory, visual, and executive control functioning (all ps < 0.05). Post-hoc analyses revealed less rsFC between alcohol-only and co-use groups as compared to controls (all ps < 0.05), but no differences between alcohol-only and co-use groups (all ps > 0.05).

CONCLUSIONS

This preliminary study suggests that co-using alcohol-cannabis may not be associated with any additive or contrasting effects on rsFC compared to using alcohol alone. Thus, in individuals who co-use alcohol-cannabis, alcohol may drive neural alterations associated with inhibitory control and substance craving.

Functional connectivity-based compensation in the brains of non-demented older adults and the influence of lifestyle: A longitudinal 7-year study

INTRODUCTION

The aging brain is characterized by structural decline and functional connectivity changes towards dedifferentiation, leading to cognitive decline. To some degree, the brain can compensate for structural deterioration. In this study, we aim to answer two questions: Where can we detect longitudinal functional connectivity-based compensation in the brains of cognitively healthy older adults? Can lifestyle predict the strength of this functional compensation?

METHODS

Using longitudinal data from 228 cognitively healthy older adults, we analyzed five measurement points over 7 years. Network-based statistics and latent growth modeling were employed to examine changes in structural and functional connectivity, as well as potential functional compensation for declines in processing speed and memory. Random forest and linear regression were used to predict the amplitude of compensation based on demographic, biological, and lifestyle factors.

RESULTS

Both functional and structural connectivity showed increases and decreases over time, depending on the specific connection and measure. Increased functional connectivity of 27 connections was linked to smaller declines in cognition. Five of those connections showed simultaneous decreases in fractional anisotropy, indicating direct compensation. The degree of compensation depended on the type of compensation and the cognitive ability, with demographic, biological, and lifestyle factors explaining 3.4-8.9% of the variance.

CONCLUSIONS

There are widespread changes in structural and functional connectivity in older adults. Despite the trend of dedifferentiation in functional connectivity, we detected both direct and indirect compensatory subnetworks that mitigated the decline in cognitive performance. The degree of compensation was influenced by demographic, biological, and lifestyle factors.

Conventional and Advanced Magnetic Resonance Imaging Biomarkers of Multiple Sclerosis in the Brain

Multiple sclerosis (MS) is a heterogeneous disease, and each MS patient exhibits different clinical symptoms that are reflected in their magnetic resonance imaging (MRI) results. Each MS lesion should be interpreted carefully and evaluated in conjunction with a clinical examination. MRI plays a major role in evaluating how MS lesions are aggregated in the central nervous system and how they change over time. There are several conventional MRI biomarkers of MS that could be utilized to evaluate each MS phenotype. MRI is useful for clinical decisions, aiding in the determination of disease-modifying treatment or disease prognosis. Despite its higher sensitivity, MRI provides low specificity due to the heterogeneity of MS lesions. However, advanced MRI biomarkers show promise in terms of defining MS lesions, as each imaging biomarker correlates differently with the clinical scenario of each MS phenotype. The aim of this review is to summarise the current state of MRI biomarkers for MS in the brain and how they relate to neurological disabilities.

Early alterations of functional connectivity, regional brain volumes and astrocyte markers in the beta-sitosterol beta-d-glucoside (BSSG) rat model of parkinsonism

The β-sitosterol-β-ᴅ-glucoside (BSSG) rat model of experimental parkinsonism develops pathological behaviour and motor changes that progress over time. The purpose of this study was to identify early changes in structure and function of the brain of rats treated with BSSG using both structural and resting-state functional MRI. BSSG and non-BSSG rats were fed five days a week for sixteen weeks, then underwent in vivo MRI scans and an assessment of motor performance 2 and 8 weeks later (18 and week 24 from BSSG). Groups of rats were killed at weeks 19 and 25, then imaged again with MR ex vivo, and immunostained for tyrosine hydroxylase (TH). Since BSSG may interfere with cholesterol metabolism in astrocytes, we also studied potential target engagement and measured levels of astrocyte markers GFAP and S100b. At both studied timepoints, functional connectivity (FC) between brain areas with intermediate connectivity was decreased, but brain volumes increased in the BSSG-treated rats. At week 18/19, fine movements were normal, whereas TH and GFAP were decreased in the striatum, but not in the substantia nigra. At week 24/25, fine movements were impaired, and TH was decreased both in the striatum and the substantia nigra and S100b was increased in the substantia nigra. Astrogliosis may contribute to the increased brain volume found after BSSG exposure. Using the BSSG model of parkinsonism, the results demonstrate early functional and structural alterations in MRI imaging that occur before the appearance of detectable motor symptoms.

Single-shot echo planar time-resolved imaging for multi-echo functional MRI and distortion-free diffusion imaging

PURPOSE

To develop a single-shot SNR-efficient distortion-free multi-echo imaging technique for dynamic imaging applications.

METHODS

Echo planar time-resolved imaging (EPTI) was first introduced as a multi-shot technique for distortion-free multi-echo imaging. This work aims to develop single-shot EPTI (ss-EPTI) to achieve improved robustness to motion/physiological noise, increased temporal resolution, and higher SNR efficiency. A new spatiotemporal encoding that enables reduced phase-encoding blips and minimized echo spacing under the single-shot regime was developed, which improves sampling efficiency and enhances spatiotemporal correlation in the k-TE space for improved reconstruction. A continuous readout with minimized deadtime was employed to optimize SNR efficiency. Moreover, k-TE partial Fourier and simultaneous multi-slice acquisition were integrated for further acceleration.

RESULTS

ss-EPTI provided distortion-free imaging with densely sampled multi-echo images at standard resolutions (e.g., ˜1.25 to 3 mm) in a single-shot. Improved SNR efficiency was observed in ss-EPTI due to improved motion/physiological-noise robustness and efficient continuous readout. Its ability to eliminate dynamic distortions-geometric changes across dynamics due to field changes induced by physiological variations or eddy currents-further improved the data's temporal stability. For multi-echo fMRI, ss-EPTI's multi-echo images recovered signal dropout in short-T 2 * $$ {\mathrm{T}}_2^{\ast } $$ regions and provided TE-dependent functional information to distinguish non-BOLD noise for further tSNR improvement. For diffusion MRI, it achieved shortened TEs for improved SNR and provided images free from both B0-induced and diffusion-encoding-dependent eddy-current-induced distortions with multi-TE diffusion metrics.

CONCLUSION

ss-EPTI provides SNR-efficient distortion-free multi-echo imaging with comparable temporal resolutions to ss-EPI, offering a new acquisition tool for dynamic imaging.

Differences in temporal profile of brain responses by pleasantness of somatosensory stimulation in autistic individuals

Purpose/Aim. Autistic individuals may show either hyper- or hypo- responsiveness to touch compared to non-autistic individuals. These behavioural responses depend on perceptual and evaluative mechanisms, which unfold sequentially and thus can be distinguished by exploring the timing of neural responses. In this study, we examined neural response timing to pleasant, unpleasant, and affectively neutral textures, to determine whether these perceptual versus evaluative subprocesses differ in autism and how each subprocess contributes to behavioural responses.Materials and Methods. Our sample included n = 13 autistic and n = 14 non-autistic adults who completed functional magnetic resonance imaging. We analysed early, intermediate, and late phases of the tactile response, derived from studies of noxious tactile stimulation, to three different textures.Results. The autistic group showed distinct differences from the non-autistic group to each of the textures, showing earlier, somatosensory differences in response to the pleasantly and unpleasantly rated textures and later, frontomotor differences in response to the neutrally rated texture. Further, reduced early phase response to the pleasant texture correlated with increased sensory seeking behaviour.Conclusions. While preliminary, these results suggest distinct patterns between autistic and non-autistic individuals in how the neural response to touch unfolds and its correspondence with the perceived pleasantness of tactile experience. The findings suggest perceptual differences in response to affectively charged textures and evaluative differences in response to neutral, ambiguous textures. These temporal properties may inform future studies of tactile processing in autism, lending a better understanding of how individuals differ in their sensory experiences across contexts.

Altered Neural Activation in First Episode Psychosis Patients With Comorbid Conduct Disorder: A Pilot Investigation

Objective

Most individuals with psychosis do not perpetrate violence. However, conduct disorder (CD) increases the risk of violence in psychotic conditions. Because it is currently unknown whether the neural correlates of first-episode psychosis (FEP) differ when CD is present, we used functional magnetic resonance imaging (fMRI) during a Go/No-Go impulsivity paradigm to investigate. Based on previous research, we hypothesized that activation differences between FEP and FEP+CD would be found in the prefrontal cortex, cingulate cortex, and inferior parietal lobule.

Method

We scanned 51 male participants: 17 FEP, 16 FEP+CD, and 18 healthy controls with an average age of 24.2 years (range, 17-34 years). Whole-brain images were analyzed via a general linear model, and first-level contrast images were created comparing successful No-Go > Go trials. Paired t tests were conducted at the group level and included confound regressors for age, IQ, antipsychotic dose, psychotic symptoms, and framewise displacement. A voxel-based Z-score threshold of Z > 3.1 (p < 0.001, uncorrected) and a cluster-level extent threshold of p <0.01, corrected, was considered significant.

Results

Successful response inhibition elicited hyperactivation in FEP+CD vs FEP in the cingulate gyrus; regions of the PFC, including right middle frontal gyrus (RMFG); bilateral inferior parietal lobule; temporal gyrus; and cerebellum (p values ranged from 1.11E-08 to 0.0031). There was no region in which activation was greater in FEP > FEP+CD.

Conclusion

These preliminary results tentatively suggest that brain regions subserving response inhibition may be altered when CD is comorbid with FEP.

Neural connectivity underlying core language functions

INTRODUCTION

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

METHODS

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

RESULTS

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

DISCUSSION

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

Parallel transmit hybrid pulse design for controlled on-resonance magnetization transfer in R1 mapping at 7T

PURPOSE

This work proposes a "hybrid" RF pulse design method for parallel transmit (pTx) systems to simultaneously control flip angle and root-mean-squaredB 1 + $$ {\mathrm{B}}_1^{+} $$ (B 1 rms $$ {B}_1^{\mathrm{rms}} $$ ). These pulses are generally only designed for flip angle, however, this can lead to uncontrolledB 1 rms $$ {B}_1^{\mathrm{rms}} $$ , which then leads to variable magnetization transfer (MT) effects. We demonstrate the hybrid design approach for quantitative imaging where both flip angle andB 1 rms $$ {B}_1^{\mathrm{rms}} $$ are important.

THEORY AND METHODS

A dual cost function optimization is performed containing the normalized mean squared errors of the flip angle andB 1 rms $$ {B}_1^{\mathrm{rms}} $$ distributions weighted by a parameterλ $$ \lambda $$ . Simulations were conducted to study the behavior of both properties when simultaneously optimizing them. In vivo experiments on a 7T MRI system with an 8-channel pTx head coil were carried out to study the effect of the hybrid design approach on variable flip angleR 1 $$ {\mathrm{R}}_1 $$ (= 1/T1) mapping.

RESULTS

Simulations showed that both flip angle andB 1 rms $$ {B}_1^{\mathrm{rms}} $$ can be homogenized simultaneously without detriment to either when compared to an individual optimization. By homogenizing flip angle andB 1 rms $$ {B}_1^{\mathrm{rms}} $$ ,R 1 $$ {\mathrm{R}}_1 $$ maps were more uniform (coefficient of variation 6.6% vs. 13.0%) compared to those acquired with pulses that only homogenized flip angle.

CONCLUSION

The proposed hybrid design homogenizes on-resonance MT effects while homogenizing the flip angle distribution, with only a small detriment in the latter compared to a pulse that just homogenizes flip angle. This improvedR 1 $$ {\mathrm{R}}_1 $$ mapping by controlling incidental MT effects, yielding more uniformR 1 $$ {\mathrm{R}}_1 $$ maps.

Comparing repeatability metrics for quantitative susceptibility mapping in the head and neck

OBJECTIVE

Quantitative susceptibility mapping (QSM) is a technique that has been demonstrated to be highly repeatable in the brain. As QSM is applied to other parts of the body, it is necessary to investigate metrics for quantifying repeatability, to enable optimization of repeatable QSM reconstruction pipelines beyond the brain.

MATERIALS AND METHODS

MRI data were acquired in the head and neck (HN) region in ten healthy volunteers, who underwent six acquisitions across two sessions. QSMs were reconstructed using six representative state-of-the-art techniques. Repeatability of the susceptibility values was compared using voxel-wise metrics (normalized root mean squared error and XSIM) and ROI-based metrics (within-subject and between-subject standard deviation, coefficient of variation (CV), intraclass correlation coefficient (ICC)).

RESULTS

Both within-subject and between-subject variations were smaller than the variation between QSM dipole inversion methods, in most ROIs. autoNDI produced the most repeatable susceptibility values, with ICC > 0.75 in three of six HN ROIs with an average ICC of 0.66 across all ROIs. Joint consideration of standard deviation and ICC offered the best metric of repeatability for comparisons between QSM methods, given typical distributions of positive and negative QSM values.

DISCUSSION

Repeatability of QSM in the HN region is highly dependent on the dipole inversion method chosen, but the most repeatable methods (autoNDI, QSMnet, TFI) are only moderately repeatable in most HN ROIs.

Primate thalamic nuclei select abstract rules and shape prefrontal dynamics

Flexible behavior depends on abstract rules to generalize beyond specific instances, and outcome monitoring to adjust actions. Cortical circuits are posited to read out rules from high-dimensional representations of task-relevant variables in prefrontal cortex (PFC). We instead hypothesized that converging inputs from PFC, directly or via basal ganglia (BG), enable thalamus to select rules. We measured activity across PFC and connected thalamic nuclei of monkeys applying rules. Abstract rule information first appeared in ventroanterior thalamus (VA) - the main thalamic hub between BG and PFC. Mediodorsal thalamus (MD) also represented rule information before PFC, persisting to help maintain activation of relevant PFC cell ensembles. MD, a major recipient of midbrain dopamine input, was first to represent information about behavioral outcomes. A PFC-BG-thalamus model reproduced key findings, and thalamic-lesion modeling disrupted PFC rule representations. This suggests that thalamus selects high-level cognitive information from PFC and monitors behavioral outcomes of these selections.