fMRI Research Articles

Challenges in the measurement and interpretation of dynamic functional connectivity

Abstract In functional MRI (fMRI), dynamic functional connectivity (dFC) typically refers to fluctuations in measured functional connectivity on a time scale of seconds. This perspective piece focuses on challenges in the measurement and interpretation of functional connectivity dynamics. Sampling error, physiological artifacts, arousal level, and task state all contribute to variability in observed functional connectivity. In our view, the central challenge in the interpretation of functional connectivity dynamics is distinguishing between these sources of variability. We believe that applications of functional connectivity dynamics to track spontaneous cognition or as a biomarker of neuropsychiatric conditions must contend with these statistical issues as well as interpretative complications. In this perspective, we include a systematic survey of the recent literature, in which sliding window analysis remains the dominant methodology (79%). We identify limitations with this approach and discuss strategies for improving the analysis and interpretation of sliding window dFC by considering the time scale of measurement and appropriate experimental controls. We also highlight avenues of investigation that could help the field to move forward.

Trajectories of human brain functional connectome maturation across the birth transition.

Understanding the sequence and timing of brain functional network development at the beginning of human life is critically important from both normative and clinical perspectives. Yet, we presently lack rigorous examination of the longitudinal emergence of human brain functional networks over the birth transition. Leveraging a large, longitudinal perinatal functional magnetic resonance imaging (fMRI) data set, this study models developmental trajectories of brain functional networks spanning 25 to 55 weeks of post-conceptual gestational age (GA). The final sample includes 126 fetal scans (GA = 31.36 ± 3.83 weeks) and 58 infant scans (GA = 48.17 ± 3.73 weeks) from 140 unique subjects. In this study, we document the developmental changes of resting-state functional connectivity (RSFC) over the birth transition, evident at both network and graph levels. We observe that growth patterns are regionally specific, with some areas showing minimal RSFC changes, while others exhibit a dramatic increase at birth. Examples with birth-triggered dramatic change include RSFC within the subcortical network, within the superior frontal network, within the occipital-cerebellum joint network, as well as the cross-hemisphere RSFC between the bilateral sensorimotor networks and between the bilateral temporal network. Our graph analysis further emphasized the subcortical network as the only region of the brain exhibiting a significant increase in local efficiency around birth, while a concomitant gradual increase was found in global efficiency in sensorimotor and parietal-frontal regions throughout the fetal to neonatal period. This work unveils fundamental aspects of early brain development and lays the foundation for future work on the influence of environmental factors on this process.

Resting-state functional magnetic resonance imaging and support vector machines for the diagnosis of major depressive disorder in adolescents

BACKGROUND Research has found that the amygdala plays a significant role in underlying pathology of major depressive disorder (MDD). However, few studies have explored machine learning-assisted diagnostic biomarkers based on amygdala functional connectivity (FC). AIM To investigate the analysis of neuroimaging biomarkers as a streamlined approach for the diagnosis of MDD in adolescents. METHODS Forty-four adolescents diagnosed with MDD and 43 healthy controls were enrolled in the study. Using resting-state functional magnetic resonance imaging, the FC was compared between the adolescents with MDD and the healthy controls, with the bilateral amygdala serving as the seed point, followed by statistical analysis of the results. The support vector machine (SVM) method was then applied to classify functional connections in various brain regions and to evaluate the neurophysiological characteristics associated with MDD. RESULTS Compared to the controls and using the bilateral amygdala as the region of interest, patients with MDD showed significantly lower FC values in the left inferior temporal gyrus, bilateral calcarine, right lingual gyrus, and left superior occipital gyrus. However, there was an increase in the FC value in Vermis-10. The SVM analysis revealed that the reduction in the FC value in the right lingual gyrus could effectively differentiate patients with MDD from healthy controls, achieving a diagnostic accuracy of 83.91%, sensitivity of 79.55%, specificity of 88.37%, and an area under the curve of 67.65%. CONCLUSION The results showed that an abnormal FC value in the right lingual gyrus was effective as a neuroimaging biomarker to distinguish patients with MDD from healthy controls.

Altered Neural Processing of Interoception in Patients With Functional Neurological Disorder: A Task-Based fMRI Study.

Research suggests that disrupted interoception contributes to the development and maintenance of functional neurological disorder (FND); however, no functional neuroimaging studies have examined the processing of interoceptive signals in patients with FND. The authors examined univariate and multivariate functional MRI neural responses of 38 patients with mixed FND and 38 healthy control individuals (HCs) during a task exploring goal-directed attention to cardiac interoception-versus-control (exteroception or rest) conditions. The relationships between interoception-related neural responses, heartbeat-counting accuracy, and interoceptive trait prediction error (ITPE) were also investigated for FND patients. When attention was directed to heartbeat signals versus exteroception or rest tasks, FND patients showed decreased neural activations (and reduced coactivations) in the right anterior insula and bilateral dorsal anterior cingulate cortices (among other areas), compared with HCs. For FND patients, heartbeat-counting accuracy was positively correlated with right anterior insula and ventromedial prefrontal activations during interoception versus rest. Cardiac interoceptive accuracy was also correlated with bilateral dorsal anterior cingulate activations in the interoception-versus-exteroception contrast, and neural activations were correlated with ITPE scores, showing inverse relationships to those observed for heartbeat-counting accuracy. This study identified state and trait interoceptive disruptions in FND patients. Convergent between- and within-group findings contextualize the pathophysiological role of cingulo-insular (salience network) areas across the spectrum of functional seizures and functional movement disorder. These findings provide a starting point for the future development of comprehensive neurophysiological assessments of interoception for FND patients, features that also warrant research as potential prognostic and monitoring biomarkers.

Comparative effects of topiramate and naltrexone on neural activity during anticipatory anxiety in individuals with alcohol use disorder.

Topiramate has been found to be effective in reducing alcohol use and may also attenuate anxiety severity in patients with alcohol use disorder (AUD). This study compared the neural response of treatment-seeking patients with AUD on either topiramate or naltrexone during an anticipatory anxiety task. Participants were 42 patients with AUD who were randomized to receive either topiramate (n =23; titrated dose up to 200mg/day) or naltrexone (n = 19; 50mg/day) for 12-weeks as part of a larger randomized controlled trial. Following 6weeks of treatment, participants completed an anticipatory anxiety task during a functional magnetic resonance imaging (fMRI) session. The task presented a series of high-threat and low-threat stimuli followed by an unpleasant or pleasant image, respectively. Primary whole-brain analyses revealed no significant differences in neural activation between the topiramate and naltrexone groups. Deactivation for safe cues relative to threat cues was observed within the precuneus, inferior parietal lobule and the cingulate gyrus. In the precentral and middle frontal gyri, threat cues elicited greater activation. Exploratory analyses revealed an effect of change in anxiety from baseline to week 6, with a greater reduction associated with a reduced response to threat cues relative to safe cues in the cuneus and lingual gyrus. The current study is the first to examine and compare neural activation during anticipatory anxiety in treatment-seeking individuals on topiramate and naltrexone. This preliminary research contributes to our understanding of the therapeutic mechanisms of these alcohol pharmacotherapies.

Multimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer’s disease continuum

Abstract Amyloid-β (Aβ) plaques in conjunction with hyperphosphorylated tau proteins in the form of neurofibrillary tangles are the two neuropathological hallmarks of Alzheimer’s disease. It is well-known that the identification of individuals with Aβ positivity could enable early diagnosis. In this work, we aim at capturing the Aβ positivity status in an unbalanced cohort enclosing subjects at different disease stages, exploiting the underlying structural and connectivity disease-induced modulations as revealed by structural, functional, and diffusion MRI. Of note, due to the unbalanced cohort, the outcomes may be guided by those factors rather than amyloid accumulation. The partial views provided by each modality are integrated in the model, allowing to take full advantage of their complementarity in encoding the effects of the Aβ accumulation, leading to an accuracy of 0.762 ± 0.04. The specificity of the information brought by each modality is assessed by post hoc explainability analysis (guided backpropagation), highlighting the underlying structural and functional changes. Noteworthy, well-established biomarker key regions related to Aβ deposition could be identified by all modalities, including the hippocampus, thalamus, precuneus, and cingulate gyrus, witnessing in favor of the reliability of the method as well as its potential in shedding light on modality-specific possibly unknown Aβ deposition signatures.

APPLICATION OF THE ITEM RESPONSE THEORY IN IMAGE PROCESSING

The Item Response Theory (IRT) was applied to image processing where the item's difficulty parameter was used to reconstruct a region of interest in an image contaminated with noise. Shannon's entropy was used for the dichotomization of the image pixels. To demonstrate the efficiency of the proposed method, it was used on simulated data that can be related to functional magnetic resonance imaging (fMRI). The results on simulated data showed that IRT achieved a high percentage of accuracy in identifying the region of interest in the image and that, on average, the estimation converges to the true region of interest, thus proving to be a promising method for the analysis of such data.

In vivo assessment of pediatric kidney function using multi-parametric and multi-nuclear functional magnetic resonance imaging: challenges, perspectives, and clinical applications

AbstractThe conventional methods for assessing kidney function, such as glomerular filtration rate and microalbuminuria, provide only partial insight into kidney function. Multi-parametric and multi-nuclear functional resonance magnetic imaging (MRI) techniques are innovative approaches to unraveling kidney physiology. Multi-parametric MRI includes various sequences to evaluate kidney perfusion, tissue oxygenation, and microstructure characterization, including fibrosis—a key pathological event in acute and chronic kidney disease and in transplant patients—without the need for invasive kidney biopsy. Multi-nuclear MRI detects nuclei other than protons. 23Na MRI enables visualization of the corticomedullary gradient and assessment of tissue sodium storage, which can be particularly relevant for personalized medicine in salt-wasting tubular disorders. Meanwhile, 31P-MRS measures intracellular phosphate and ATP variations, providing insights into oxidative metabolism in the muscle during exercise and recovery. This technique can be useful for detecting subclinical ischemia in chronic kidney disease and in tubulopathies with kidney phosphate wasting. These techniques are non-invasive and do not involve radiation exposure, making them especially suitable for longitudinal and serial assessments. They enable in vivo evaluation of kidney function on a whole-organ basis within a short acquisition time and with the ability to distinguish between medullary and cortical compartments. Therefore, they offer considerable potential for pediatric patients. In this review, we provide a brief overview of the main imaging techniques, summarize available literature data on both adult and pediatric populations, and examine the perspectives and challenges associated with multi-parametric and multi-nuclear MRI. Graphical Abstract

Neural correlates associated with a family history of alcohol use disorder: A narrative review of recent findings

AbstractA family history of alcohol use disorder (AUD) is associated with a significantly increased risk of developing AUD in one's lifetime. The previously reviewed literature suggests there are structural and functional neurobiological markers associated with familial AUD, but to our knowledge, no recent review has synthesized the latest findings across neuroimaging studies in this at‐risk population. For this narrative review, we conducted keyword searches in electronic databases to find cross‐sectional and longitudinal studies (2015‐present) that used magnetic resonance imaging (MRI), diffusion tensor imaging, task‐based functional MRI (fMRI), and/or resting state functional connectivity MRI. These studies were used to identify gray matter, white matter, and brain activity markers of risk and resilience in family history positive (FHP) individuals with a family history of AUD. FHP individuals have greater early adolescent thinning of executive functioning (frontal lobe) regions; however, some studies have reported null effects or greater gray matter volume and thickness relative to family history negative (FHN) peers without familial AUD. FHP individuals also have white matter microstructure alterations, such as reduced integrity of fronto‐striatal pathways. Recent fMRI studies have found greater inhibitory control activity in FHP individuals, while reward‐related findings are mixed. A growing interest in identifying intrinsic connectivity differences between FHP and FHN individuals has emerged in recent years. Familial AUD is related to both structural and functional brain alterations. Research should continue to focus on (1) longitudinal analyses with larger samples, (2) assessment of personal substance use and prenatal exposure to alcohol, (3) the effects of comorbid familial psychopathology, (4) examination of sex‐specific markers of risk and resilience, (5) neural predictors of alcohol use initiation, and (6) brain–behavior relationships. These efforts would aid the design of neurobiologically informed prevention and intervention efforts focused on this at‐risk population.

Magnetic resonance imaging characterization of an α‐synuclein model of Parkinson's disease

AbstractParkinson's disease (PD) is primarily characterized by three histological hallmarks: dopaminergic neuronal degeneration, α‐synuclein accumulation and iron deposition. Over the last years, neuroimaging, particularly magnetic resonance imaging (MRI) has provided invaluable insights into the mechanisms underlying the disease. However, no imaging method has yet been able to translate α‐synuclein protein accumulation and spreading. Amongst the animal models mimicking the disease, the α‐synuclein rat, generated through the injection of human α‐synuclein, has been characterized in terms of behavioural and histological aspects but not thoroughly explored in MRI. The aim of this study is, therefore, to identify the radiological signature from several MRI sequences, while controlling for histological and behavioural characteristics. Rats were assessed for motor and cognitive functions over a 4‐month period. During this time, three MRI sessions, including both morphological and functional sequences, were conducted. Histological studies evaluated the three main hallmarks of PD. The progressive dopaminergic neurodegeneration and the spread of human α‐synuclein corresponded to the level of sensorimotor, attentional and learning deficits observed in this PD model. MRI analyses showed progressive structural abnormalities in the midbrain, diencephalon and several cortical structures, as well as a pattern of hyperconnectivity in the basal ganglia and cortical networks. The regions affected in imaging demonstrated the highest load of human α‐synuclein. This model's structural and functional MRI changes could serve as indirect indicators of α‐synuclein accumulation and its association with impaired non‐motor functions.

Progressive Bulbar Palsy Care: Exploring the Potential of Functional MRI for Early Detection

Progressive bulbar palsy (PBP) is a neurodegenerative disorder impacting motor neurons involved in speech, swallowing, and breathing. Early diagnosis is challenging due to limited diagnostic tools. Functional MRI (fMRI) holds promise for detecting early biomarkers and tracking disease progression, potentially improving clinical management. This study aims to explore the utility of fMRI in developing imaging biomarkers for the early detection, prognostication, and monitoring of PBP. By addressing existing gaps in the literature, the research seeks to demonstrate how fMRI can enhance diagnostic accuracy, provide predictive insights into disease progression, and improve patient outcomes. A systematic literature review was conducted using databases such as Google Scholar. The search focused on articles published from 2018 onwards, using keywords related to PBP and fMRI. Inclusion criteria included peer-reviewed studies involving human subjects relevant to the use of fMRI in PBP. Exclusion criteria excluded non-peer-reviewed articles, non-English publications, and studies not specifically addressing fMRI in PBP. Data synthesis involved both qualitative and quantitative analyses of identified biomarkers, diagnostic accuracy, and prognostic value. The review identified several fMRI biomarkers that show potential for early detection and monitoring of PBP. These biomarkers, derived from functional and structural changes in corticobulbar pathways, offer enhanced sensitivity compared to traditional diagnostic methods. Predictive models based on fMRI metrics can forecast disease progression, aiding in personalized treatment planning. The study concludes that integrating fMRI into clinical practice could lead to earlier interventions, more accurate prognostic assessments, and improved management of PBP, ultimately enhancing patient quality of life and outcomes.

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

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

Functional connectivity changes in two cortico-hippocampal networks of Alzheimer's disease continuum and their correlations with cognition: A SILCODE study.

The anterior-temporal (AT) and posterior-medial (PM) networks have been proposed to play pivotal roles in the memory processing associated with Alzheimer's disease (AD). Nevertheless, these two networks' intrinsic functional coupling characteristics are still vague in different AD stages. To explore the functional connectivity (FC) alterations within and across the AT&PM networks in patients with dementia of the Alzheimer's type (DAT), mild cognitive impairment (MCI), subjective cognitive decline (SCD), and normal controls (NC). A total of 368 participants over 50 years old from the SILCODE study were recruited, including 99 NC, 134 SCD, 67 MCI, and 68 DAT patients. All the participants underwent a resting-state functional magnetic resonance imaging scan and a battery of neuropsychological tests. The 56 regions-of-interest of the AT&PM networks were defined broadly following existing literature. The FCs were calculated using DPABINet and compared among these four groups. Correlation analyses were performed on FCs and cognitive tests. Analysis of variance of all four groups showed significant alteration, mainly in the PM networks. Compared to NC, globally decreased FCs regarding AT&PM networks were observed in DAT and MCI patients, while globally increased FCs regarding AT&PM networks were observed in SCD. The decreased FCs in DAT were significantly correlated with the neuropsychological test on the memory domain. The FC alteration showed different patterns across the AD continuum, especially in individuals with SCD. The elevated FCs in the AT&PM networks of SCD may implicate certain compensating processes in the early stage of AD.

Forecasting fMRI images from video sequences: linear model analysis.

Over the past few decades, a variety of significant scientific breakthroughs have been achieved in the fields of brain encoding and decoding using the functional magnetic resonance imaging (fMRI). Many studies have been conducted on the topic of human brain reaction to visual stimuli. However, the relationship between fMRI images and video sequences viewed by humans remains complex and is often studied using large transformer models. In this paper, we investigate the correlation between videos presented to participants during an experiment and the resulting fMRI images. To achieve this, we propose a method for creating a linear model that predicts changes in fMRI signals based on video sequence images. A linear model is constructed for each individual voxel in the fMRI image, assuming that the image sequence follows a Markov property. Through the comprehensive qualitative experiments, we demonstrate the relationship between the two time series. We hope that our findings contribute to a deeper understanding of the human brain's reaction to external stimuli and provide a basis for future research in this area.

Altered parasympathetic outflow and central sensitization response to continuous pain in cyclic vomiting syndrome: a functional magnetic resonance imaging study.

Cyclic vomiting syndrome (CVS) is a disorder of brain-gut interaction characterized by recurrent episodes of nausea and vomiting interspersed with asymptomatic periods and associated with autonomic nervous system dysfunction. We examined the dysautonomic response to noxious stimuli seen in CVS patients using our previously validated approach to integrate peripheral autonomic outflow metrics, temporal summation of pain, and brain fMRI. BOLD fMRI and ECG were acquired from CVS patients and healthy adults during a rest condition and a sustained cuff pressure pain stimulus at the leg. After the latter scan, participants rated pain for the full 6-minute pain stimulus as well as first, middle, and last two-minutes to calculate temporal summation. During sustained pain, patients (n=13) exhibited greater reduction in heart rate variability within the high-frequency range (HF-HRV) and reduced anticorrelation between HF-HRV and fMRI signal in the anterior insula, pregenual anterior cingulate cortex, and ventrolateral and dorsolateral prefrontal cortex relative to healthy adults (n=13). Compared to healthy adults (n=14), patients (n=14) exhibited increasing pain intensity over the course of sustained cuff pressure. Seed-based functional connectivity analysis revealed for healthy adults (n=13), pain sensitization correlated with pain-induced increases in connectivity between primary somatosensory cortex and regions of interest in both left anterior insula/posterior orbitofrontal cortex and right pre-supplementary motor area, while this correlation was disrupted in CVS (n=10). Our results support altered central coding of nociceptive stimuli and autonomic responsivity of CVS patients in key brain regions implicated in autonomic control and interoception.

Monitoring Bottlenose Dolphin (Tursiops truncatus) Welfare During a Functional Neuroimaging Study

The development of non-invasive methods to study brain structure and function has enabled a flowering of cognitive neuroscience in humans and nonhuman species. Herein, we describe the development of protocols for functional magnetic resonance imaging (fMRI) of a bottlenose dolphin (Tursiops truncatus), including protocols to monitor the health and welfare of the subject over the course of our five-year study. A Welfare Control Plan (WCP) was designed to monitor, enhance, and protect our subject’s welfare throughout the course of the study. The WCP was developed so our team of marine mammal veterinarians, trainers, and researchers could (1) identify study procedures that might negatively impact the individual’s welfare and propose measures to mitigate them, (2) define and implement protocols for monitoring the individual’s welfare throughout the study, and (3) determine the study’s temporary or final endpoints. Overall, behavioral, physiological, and health welfare indicators showed that the dolphin’s quality of life was not negatively impacted by participating in our functional neuroimaging study. Our study provides an example of how innovative, ambitious, and logistically complex animal studies can successfully be performed while protecting the welfare of participating animals through adequate planning, enough human and economic resources, and full human/institutional commitment to animal welfare.

Machine learning diagnosis of schizophrenia using structural and functional images of the brain

Abstract. This study aims to provide earlier, and faster schizophrenia diagnosis based on neurocognitive, structural, and behavioral measures using machine learning. This is because current ways of diagnosis, while accurate, delay patients ability to seek medical care before observable, lasting symptoms develop and are prone to error and discrimination. To provide diagnosis, we used Linear Support Vector Machine (linear SVM), Random Forest (RF), Multilayer Perceptron (MLP), and k-Nearest Neighbor (kNN), all trained with neurocognitive and behavioral measures combined with either structural or functional MRI data or both of 99 subjects from the OpenNeuro public dataset. 100 iterations of classification were run, and results showed a higher-than-average accuracy for all classifiers using all combinations of parameters, with a highest accuracy of 0.75 using linear SVM trained with behavioral and neurocognitive measures and fMRI data. We found correlations between structural changes in AAL3 brain regions and n-back working memory task performance, noting that the inferior parietal gyrus, right precuneus, supplementary motor area, and the central lateral thalamic nucleus have the highest feature importance. This means that future studies can select these features for further clinical examination or for machine learning diagnosis. We conclude that linear SVM provides the highest average diagnostic accuracy, and that fMRI data often leads to more accurate algorithmic decisions than sMRI data and thus should be weighed more in future studies.

Cortical areas for planning sequences before and during movement.

Production of rapid movement sequences relies on preparation before (pre-planning) and during (online planning) movement. Here, we compared these processes and asked whether they recruit different cortical areas. Human participants performed three single-finger and three multi-finger sequences in a delayed movement paradigm while undergoing 7T functional MRI. During preparation, primary motor (M1) and somatosensory (S1) areas showed pre-activation of the first movement, even without increases in overall activation. During production, the temporal summation of activity patterns corresponding to constituent fingers explained activity in these areas (M1 and S1). In contrast, the dorsal premotor cortex (PMd) and anterior superior parietal lobule (aSPL) showed substantial activation during the preparation (pre-planning) of multi-finger compared to single-finger sequences. These regions (PMd and aSPL) were also more active during production of multi-finger sequences, suggesting that pre- and online planning may recruit the same regions. However, we observed small but robust differences between the two contrasts, suggesting distinct contributions to pre- and online planning. Multivariate analysis revealed sequence-specific representations in both PMd and aSPL, which remained stable across both preparation and production phases. Our analyses show that these areas maintain a sequence-specific representation before and during sequence production, likely guiding the execution-related areas in the production of rapid movement sequences.Significance Statement Understanding how the brain orchestrates complex behavior remains a core challenge in human neuroscience. Here, we combine high-resolution neuroimaging and a carefully crafted design to study the neural control of rapid sequential finger movements, like typing or playing the piano. Advancing prior research, we show that the brain areas involved in planning these movements maintain those representations throughout the execution of the sequence. This representational stability across planning and execution suggests an intricate connection between these processes. Our results shed light on the nuanced contributions of different cortical areas to different aspects of coordinating skilled movement. This work is well placed to inform future research in animal models and the development of targeted interventions against movement disorders.

Monkeys engage in visual simulation to solve complex problems.

Visual simulation-i.e., using internal reconstructions of the world to experience potential future versions of events that are not currently happening-is among the most sophisticated capacities of the human mind. But is this ability in fact uniquely human? To answer this question, we tested monkeys on a series of experiments involving the "Planko" game, which we have previously used to evoke visual simulation in human participants. We found that monkeys were able to successfully play the game using a simulation strategy, predicting the trajectory of a ball through a field of planks while demonstrating a level of accuracy and behavioral signatures comparable with those of humans. Computational analyses further revealed that the monkeys' strategy while playing Planko aligned with a recurrent neural network (RNN) that approached the task using a spontaneously learned simulation strategy. Finally, we carried out awake functional magnetic resonance imaging while monkeys played Planko. We found activity in motion-sensitive regions of the monkey brain during hypothesized simulation periods, even without any perceived visual motion cues. This neural result closely mirrors previous findings from human research, suggesting a shared mechanism of visual simulation across species. Taken together, these findings challenge traditional views of animal cognition, proposing that nonhuman primates possess a complex cognitive landscape, capable of invoking imaginative and predictive mental experiences to solve complex everyday problems.

Application of functional magnetic resonance imaging to evaluate renal structure and function in type 2 cardiorenal syndrome

BackgroundThere is a lack of diagnostic non-invasive imaging technology for assessing the early structural and functional changes of the kidney in type 2 cardiorenal (CRS) patients. This study aims to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for clinical application in type 2 CRS patients, to provide imaging markers for the assessment of kidney damage.MethodsThis is a retrospective observational clinical study conducted in Nanjing, China. The clinical characteristics, including age, gender, medical history, laboratory results, and ultrasound and magnetic resonance imaging results were collected from the electronic medical record. Thirty-one patients with type 2 CRS, 20 patients with chronic heart failure (HF) and 20 healthy controls were enrolled and divided into type 2 CRS, HF and control groups. All the participants underwent magnetic resonance imaging (MRI) scanning. The apparent diffusion coefficient (ADC) value and IVIM-DWI parameters including true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were obtained. The correlation between estimated glomerular filtration rate (eGFR), renal size and imaging parameters was evaluated by Spearman correlation analysis.ResultsADC and D of the renal cortex in patients with type 2 CRS were lower than those in the healthy control group. ADC and f in the HF group were lower than those in the control group. D was positively correlated with the length (r = 0.3752, P = 0.0013) and transverse diameter (r = 0.3258, P = 0.0056) of the kidney. ADC (r = 0.2964, P = 0.0121) and D (r = 0.3051, P = 0.0097) were positively correlated with eGFR. Renal cortical ADC and D values could distinguish type 2 CRS patients from the healthy controls with area under the curve (AUC) of 0.723 and 0.706, respectively.ConclusionThe ADC and D values were not only correlated with renal function, but also had lower levels in type 2 CRS. The IVIM-DWI parameter D was also related to kidney size, but further research is needed to determine whether it can be used as a novel imaging marker for type 2 CRS.