Structural brain connectivity predicts early acute pain after mild traumatic brain injury.

ABSTRACT: Mild traumatic brain injury (mTBI), is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute postinjury pain is important because it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 157 patients with mTBI, following a motorized vehicle collision. We extracted white matter structural connectivity networks and used a machine learning approach to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamiccortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in 2 independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6 months after the collision still predicted mTBI pain at that timepoint (n = 36). These white matter connections were associated with 2 nociceptive psychophysical outcomes tested at a remote body site-namely, conditioned pain modulation and magnitude of suprathreshold pain-and with pain sensitivity questionnaire scores. Our findings demonstrate a stable white matter network, the properties of which determine an important amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

Brain Connectivity Predicts Chronic Pain in Acute Mild Traumatic Brain Injury.

OBJECTIVES: Previous studies have established the role of the cortico-mesolimbic and descending pain modulation systems in chronic pain prediction. Mild traumatic brain injury (mTBI) is an acute pain model where chronic pain is prevalent and complicated for prediction. In this study, we set out to study whether functional connectivity (FC) of the nucleus accumbens (NAc) and the periaqueductal gray matter (PAG) is predictive of pain chronification in early-acute mTBI. METHODS: To estimate FC, resting-state functional magnetic resonance imaging (fMRI) of 105 participants with mTBI following a motor vehicle collision was acquired within 72 hours post-accident. Participants were classified according to pain ratings provided at 12-months post-collision into chronic pain (head/neck pain ≥30/100, n = 44) and recovery (n = 61) groups, and their FC maps were compared. RESULTS: The chronic pain group exhibited reduced negative FC between NAc and a region within the primary motor cortex corresponding with the expected representation of the area of injury. A complementary pattern was also demonstrated between PAG and the primary somatosensory cortex. PAG and NAc also shared increased FC to the rostral anterior cingulate cortex (rACC) within the recovery group. Brain connectivity further shows high classification accuracy (area under the curve [AUC] = .86) for future chronic pain, when combined with an acute pain intensity report. INTERPRETATION: FC features obtained shortly after mTBI predict its transition to long-term chronic pain, and may reflect an underlying interaction of injury-related primary sensorimotor cortical areas with the mesolimbic and pain modulation systems. Our findings indicate a potential predictive biomarker and highlight targets for future early preventive interventions. ANN NEUROL 2022;92:819-833.

The default network is causally linked to creative thinking.

Creative thinking represents a major evolutionary mechanism that greatly contributed to the rapid advancement of the human species. The ability to produce novel and useful ideas, or original thinking, is thought to correlate well with unexpected, synchronous activation of several large-scale, dispersed cortical networks, such as the default network (DN). Despite a vast amount of correlative evidence, a causal link between default network and creativity has yet to be demonstrated. Surgeries for resection of brain tumors that lie in proximity to speech related areas are performed while the patient is awake to map the exposed cortical surface for language functions. Such operations provide a unique opportunity to explore human behavior while disrupting a focal cortical area via focal electrical stimulation. We used a novel paradigm of individualized direct cortical stimulation to examine the association between creative thinking and the DN. Preoperative resting-state fMRI was used to map the DN in individual patients. A cortical area identified as a DN node (study) or outside the DN (controls) was stimulated while the participants performed an alternate-uses-task (AUT). This task measures divergent thinking through the number and originality of different uses provided for an everyday object. Baseline AUT performance in the operating room was positively correlated with DN integrity. Direct cortical stimulation at the DN node resulted in decreased ability to produce alternate uses, but not in the originality of uses produced. Stimulation in areas that when used as network seed regions produced a network similar to the canonical DN was associated with reduction of creative fluency. Stimulation of areas that did not produce a default-like network (controls) did not alter creative thinking. This is the first study to causally link the DN and creative thinking.

Leveraging genetic diversity in mice to inform individual differences in brain microstructure and memory.

In human Alzheimer's disease (AD) patients and AD mouse models, both differential pre-disease brain features and differential disease-associated memory decline are observed, suggesting that certain neurological features may protect against AD-related cognitive decline. The combination of these features is known as brain reserve, and understanding the genetic underpinnings of brain reserve may advance AD treatment in genetically diverse human populations. One potential source of brain reserve is brain microstructure, which is genetically influenced and can be measured with diffusion MRI (dMRI). To investigate variation of dMRI metrics in pre-disease-onset, genetically diverse AD mouse models, we utilized a population of genetically distinct AD mice produced by crossing the 5XFAD transgenic mouse model of AD to 3 inbred strains (C57BL/6J, DBA/2J, FVB/NJ) and two wild-derived strains (CAST/EiJ, WSB/EiJ). At 3 months of age, these mice underwent diffusion magnetic resonance imaging (dMRI) to probe neural microanatomy in 83 regions of interest (ROIs). At 5 months of age, these mice underwent contextual fear conditioning (CFC). Strain had a significant effect on dMRI measures in most ROIs tested, while far fewer effects of sex, sex*strain interactions, or strain*sex*5XFAD genotype interactions were observed. A main effect of 5XFAD genotype was observed in only 1 ROI, suggesting that the 5XFAD transgene does not strongly disrupt neural development or microstructure of mice in early adulthood. Strain also explained the most variance in mouse baseline motor activity and long-term fear memory. Additionally, significant effects of sex and strain*sex interaction were observed on baseline motor activity, and significant strain*sex and sex*5XFAD genotype interactions were observed on long-term memory. We are the first to study the genetic influences of brain microanatomy in genetically diverse AD mice. Thus, we demonstrated that strain is the primary factor influencing brain microstructure in young adult AD mice and that neural development and early adult microstructure are not strongly altered by the 5XFAD transgene. We also demonstrated that strain, sex, and 5XFAD genotype interact to influence memory in genetically diverse adult mice. Our results support the usefulness of the 5XFAD mouse model and convey strong relationships between natural genetic variation, brain microstructure, and memory.

Structural and functional brain-wide alterations in A350V Iqsec2 mutant mice displaying autistic-like behavior.

IQSEC2 is an X-linked gene that is associated with autism spectrum disorder (ASD), intellectual disability, and epilepsy. IQSEC2 is a postsynaptic density protein, localized on excitatory synapses as part of the NMDA receptor complex and is suggested to play a role in AMPA receptor trafficking and mediation of long-term depression. Here, we present brain-wide structural volumetric and functional connectivity characterization in a novel mouse model with a missense mutation in the IQ domain of IQSEC2 (A350V). Using high-resolution structural and functional MRI, we show that animals with the A350V mutation display increased whole-brain volume which was further found to be specific to the cerebral cortex and hippocampus. Moreover, using a data-driven approach we identify putative alterations in structure-function relations of the frontal, auditory, and visual networks in A350V mice. Examination of these alterations revealed an increase in functional connectivity between the anterior cingulate cortex and the dorsomedial striatum. We also show that corticostriatal functional connectivity is correlated with individual variability in social behavior only in A350V mice, as assessed using the three-chamber social preference test. Our results at the systems-level bridge the impact of previously reported changes in AMPA receptor trafficking to network-level disruption and impaired social behavior. Further, the A350V mouse model recapitulates similarly reported brain-wide changes in other ASD mouse models, with substantially different cellular-level pathologies that nonetheless result in similar brain-wide alterations, suggesting that novel therapeutic approaches in ASD that result in systems-level rescue will be relevant to IQSEC2 mutations.

Individual variability in functional connectivity architecture of the mouse brain.

In recent years precision fMRI has emerged in human brain research, demonstrating characterization of individual differences in brain organization. However, mechanistic investigations to the sources of individual variability are limited in humans and thus require animal models. Here, we used resting-state fMRI in awake mice to quantify the contribution of individual variation to the functional architecture of the mouse cortex. We found that the mouse connectome is also characterized by stable individual features that support connectivity-based identification. Unlike in humans, we found that individual variation is homogeneously distributed in sensory and association networks. Finally, connectome-based predictive modeling of motor behavior in the rotarod task revealed that individual variation in functional connectivity explained behavioral variability. Collectively, these results establish the feasibility of precision fMRI in mice and lay the foundation for future mechanistic investigations of individual brain organization and pre-clinical studies of brain disorders in the context of personalized medicine.

Brain-wide structural and functional disruption in mice with oligodendrocyte-specific Nf1 deletion is rescued by inhibition of nitric oxide synthase.

Neurofibromin gene (NF1) mutation causes neurofibromatosis type 1 (NF1), a disorder in which brain white matter deficits identified by neuroimaging are common, yet of unknown cellular etiology. In mice, Nf1 loss in adult oligodendrocytes causes myelin decompaction and increases oligodendrocyte nitric oxide (NO) levels. Nitric oxide synthase (NOS) inhibitors rescue this pathology. Whether oligodendrocyte pathology is sufficient to affect brain-wide structure and account for NF1 imaging findings is unknown. Here we show that Nf1 gene inactivation in adult oligodendrocytes (Plp-Nf1fl/+ mice) results in a motor coordination deficit. Magnetic resonance imaging in awake mice showed that fractional anisotropy is reduced in Plp-Nf1fl/+ corpus callosum and that interhemispheric functional connectivity in the motor cortex is also reduced, consistent with disrupted myelin integrity. Furthermore, NOS-specific inhibition rescued both measures. These results suggest that oligodendrocyte defects account for aspects of brain dysfunction in NF1 that can be identified by neuroimaging and ameliorated by NOS inhibition.

Tremor Relief and Structural Integrity after MRI-guided Focused US Thalamotomy in Tremor Disorders.

Background MRI-guided focused US thalamotomy of ventral intermediate nucleus of the thalamus is a treatment for tremor disorders. Purpose To evaluate white matter integrity before and after thalamotomy and its correlation with clinical outcome. Materials and Methods Participants with essential tremor (ET) or Parkinson disease (PD) undergoing thalamotomy were prospectively recruited between March 2016 and October 2018. Tremor and quality of life were assessed before, 1 month after, and 6 months after thalamotomy. Participants underwent T1-weighted, T2-weighted fluid-attenuated image recovery, and diffusion-tensor MRI before and 1 day, 7-10 days, 1-3 months, and 6 months or longer after treatment. Diffusivity and fiber tractography measures were calculated. Repeated measures analysis of variance with post hoc paired t test and Skillings-Mack test with post hoc Wilcoxon signed-rank test were used for normally and nonnormally distributed data, respectively, and Bonferroni method corrected for multiple comparisons. Results Twenty-two study participants with ET (mean age, 72 years ± 6 [standard deviation]; 14 men), 17 participants with PD (mean age, 65 years ± 8; 13 men), and a replication set of 17 participants with ET (mean age, 73 years ± 6; 10 men) were evaluated. Long-term damage was found in the ablated core (mean fractional anisotropy [FA] at baseline, 0.41 ± 0.10, and at ≥6 months, 0.23 ± 0.09; P < .001) and thalamus to red nucleus tract (mean number of tracts at baseline, 1663, and at ≥6 months, 1070; P = .003). Negative correlation was observed between motor thalamus FA 1 day after ablation and tremor improvement (ET: R = -0.52 [P = .03]; PD: R = -0.61 [P = .003]). Better tremor relief in ET was associated with lower fractional anisotropy before treatment (R = -0.5; P = .02). Conclusion MRI-guided focused US thalamotomy resulted in short- and long-term white-matter changes. Diffusion-tensor imaging provided evidence for long-term damage in the ablation core and in the thalamus and red nucleus tract, and a correlation between preablation fractional anisotropy in the motor thalamus and clinical outcome. © RSNA, 2020 Online supplemental material is available for this article.

Individual structural features constrain the mouse functional connectome.

Whole brain dynamics intuitively depend upon the internal wiring of the brain; but to which extent the individual structural connectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure-function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine.

Autism-associated Nf1 deficiency disrupts corticocortical and corticostriatal functional connectivity in human and mouse.

Children with the autosomal dominant single gene disorder, neurofibromatosis type 1 (NF1), display multiple structural and functional changes in the central nervous system, resulting in neuropsychological cognitive abnormalities. Here we assessed the pathological functional organization that may underlie the behavioral impairments in NF1 using resting-state functional connectivity MRI. Coherent spontaneous fluctuations in the fMRI signal across the entire brain were used to interrogate the pattern of functional organization of corticocortical and corticostriatal networks in both NF1 pediatric patients and mice with a heterozygous mutation in the Nf1 gene (Nf1+/-). Children with NF1 demonstrated abnormal organization of cortical association networks and altered posterior-anterior functional connectivity in the default network. Examining the contribution of the striatum revealed that corticostriatal functional connectivity was altered. NF1 children demonstrated reduced functional connectivity between striatum and the frontoparietal network and increased striatal functional connectivity with the limbic network. Awake passive mouse functional connectivity MRI in Nf1+/- mice similarly revealed reduced posterior-anterior connectivity along the cingulate cortex as well as disrupted corticostriatal connectivity. The striatum of Nf1+/- mice showed increased functional connectivity to somatomotor and frontal cortices and decreased functional connectivity to the auditory cortex. Collectively, these results demonstrate similar alterations across species, suggesting that NF1 pathogenesis is linked to striatal dysfunction and disrupted corticocortical connectivity in the default network.

An IQSEC2 Mutation Associated With Intellectual Disability and Autism Results in Decreased Surface AMPA Receptors.

We have recently described an A350V mutation in IQSEC2 associated with intellectual disability, autism and epilepsy. We sought to understand the molecular pathophysiology of this mutation with the goal of developing targets for drug intervention. We demonstrate here that the A350V mutation results in interference with the binding of apocalmodulin to the IQ domain of IQSEC2. We further demonstrate that this mutation results in constitutive activation of the guanine nucleotide exchange factor (GEF) activity of IQSEC2 resulting in increased production of the active form of Arf6. In a CRISPR generated mouse model of the A350V IQSEC2 mutation, we demonstrate that the surface expression of GluA2 AMPA receptors in mouse hippocampal tissue was significantly reduced in A350V IQSEC2 mutant mice compared to wild type IQSEC2 mice and that there is a significant reduction in basal synaptic transmission in the hippocampus of A350V IQSEC2 mice compared to wild type IQSEC2 mice. Finally, the A350V IQSEC2 mice demonstrated increased activity, abnormal social behavior and learning as compared to wild type IQSEC2 mice. These findings suggest a model of how the A350V mutation in IQSEC2 may mediate disease with implications for targets for drug therapy. These studies provide a paradigm for a personalized approach to precision therapy for a disease that heretofore has no therapy.

Multi-Modal Nano Particle Labeling of Neurons.

The development of imaging methodologies for single cell measurements over extended timescales of up to weeks, in the intact animal, will depend on signal strength, stability, validity and specificity of labeling. Whereas light-microscopy can achieve these with genetically-encoded probes or dyes, this modality does not allow mesoscale imaging of entire intact tissues. Non-invasive imaging techniques, such as magnetic resonance imaging (MRI), outperform light microscopy in field of view and depth of imaging, but do not offer cellular resolution and specificity, suffer from low signal-to-noise ratio and, in some instances, low temporal resolution. In addition, the origins of the signals measured by MRI are either indirect to the process of interest or hard to validate. It is therefore highly warranted to find means to enhance MRI signals to allow increases in resolution and cellular-specificity. To this end, cell-selective bi-functional magneto-fluorescent contrast agents can provide an elegant solution. Fluorescence provides means for identification of labeled cells and particles location after MRI acquisition, and it can be used to facilitate the design of cell-selective labeling of defined targets. Here we briefly review recent available designs of magneto-fluorescent markers and elaborate on key differences between them with respect to durability and relevant cellular highlighting approaches. We further focus on the potential of intracellular labeling and basic functional sensing MRI, with assays that enable imaging cells at microscopic and mesoscopic scales. Finally, we illustrate the qualities and limitations of the available imaging markers and discuss prospects for in vivo neural imaging and large-scale brain mapping.

Multidimensional co-segmentation of longitudinal brain MRI ensembles in the presence of a neurodegenerative process.

MRI Segmentation of a pathological brain poses a significant challenge, as the available anatomical priors that provide top-down information to aid segmentation are inadequate in the presence of abnormalities. This problem is further complicated for longitudinal data capturing impaired brain development or neurodegenerative conditions, since the dynamic of brain atrophies has to be considered as well. For these cases, the absence of compatible annotated training examples renders the commonly used multi-atlas or machine-learning approaches impractical. We present a novel segmentation approach that accounts for the lack of labeled data via multi-region multi-subject co-segmentation (MMCoSeg) of longitudinal MRI sequences. The underlying, unknown anatomy is learned throughout an iterative process, in which the segmentation of a region is supported both by the segmentation of the neighboring regions, which share common boundaries, and by the segmentation of corresponding regions, in the other jointly segmented images. A 4D multi-region atlas that models the spatio-temporal deformations and can be adapted to different subjects undergoing similar degeneration processes is reconstructed concurrently. An inducible mouse model of p25 accumulation (the CK-p25 mouse) that displays key pathological hallmarks of Alzheimer disease (AD) is used as a gold-standard to test the proposed algorithm by providing a conditional control of rapid neurodegeneration. Applying the MMCoSeg to a cohort of CK-p25 mice and littermate controls yields promising segmentation results that demonstrate high compatibility with expertise manual annotations. An extensive comparative analysis with respect to current well-established, atlas-based segmentation methods highlights the advantage of the proposed approach, which provides accurate segmentation of longitudinal brain MRIs in pathological conditions, where only very few annotated examples are available.

Utah optrode array customization using stereotactic brain atlases and 3-D CAD modeling for optogenetic neocortical interrogation in small rodents and nonhuman primates.

As the optogenetic field expands, the need for precise targeting of neocortical circuits only grows more crucial. This work demonstrates a technique for using Solidworks® computer-aided design (CAD) and readily available stereotactic brain atlases to create a three-dimensional (3-D) model of the dorsal region of area visual cortex 4 (V4D) of the macaque monkey (Macaca fascicularis) visual cortex. The 3-D CAD model of the brain was used to customize an [Formula: see text] Utah optrode array (UOA) after it was determined that a high-density ([Formula: see text]) UOA caused extensive damage to marmoset (Callithrix jacchus) primary visual cortex as assessed by electrophysiological recording of spiking activity through a 1.5-mm-diameter through glass via. The [Formula: see text] UOA was customized for optrode length ([Formula: see text]), optrode width ([Formula: see text]), optrode pitch ([Formula: see text]), backplane thickness ([Formula: see text]), and overall form factor ([Formula: see text]). Two [Formula: see text] UOAs were inserted into layer VI of macaque V4D cortices with minimal damage as assessed in fixed tissue cytochrome oxidase staining in nonrecoverable surgeries. Additionally, two [Formula: see text] arrays were implanted in mice (Mus musculus) motor cortices, providing early evidence for long-term tolerability (over 6 months), and for the ability to integrate the UOA with a Holobundle light delivery system toward patterned optogenetic stimulation of cortical networks.

The Organization of Mouse and Human Cortico-Hippocampal Networks Estimated by Intrinsic Functional Connectivity.

While the hippocampal memory system has been relatively conserved across mammals, the cerebral cortex has undergone massive expansion. A central question in brain evolution is how cortical development affected the nature of cortical inputs to the hippocampus. To address this question, we compared cortico-hippocampal connectivity using intrinsic functional connectivity MRI (fcMRI) in awake mice and humans. We found that fcMRI recapitulates anatomical connectivity, demonstrating sensory mapping within the mouse parahippocampal region. Moreover, we identified a similar topographical modality-specific organization along the longitudinal axis of the mouse hippocampus, indicating that sensory information arriving at the hippocampus is only partly integrated. Finally, comparing cortico-hippocampal connectivity across species, we discovered preferential hippocampal connectivity of sensory cortical networks in mice compared with preferential connectivity of association cortical networks in humans. Supporting this observation in humans but not in mice, sensory and association cortical networks are connected to spatially distinct subregions within the parahippocampal region. Collectively, these findings indicate that sensory cortical networks are coupled to the mouse but not the human hippocampal memory system, suggesting that the emergence of expanded and new association areas in humans resulted in the rerouting of cortical information flow and dissociation of primary sensory cortices from the hippocampus.

Realistic Numerical and Analytical Modeling of Light Scattering in Brain Tissue for Optogenetic Applications(1,2,3).

In recent years, optogenetics has become a central tool in neuroscience research. Estimating the transmission of visible light through brain tissue is of crucial importance for controlling the activation levels of neurons in different depths, designing optical systems, and avoiding lesions from excessive power density. The Kubelka-Munk model and Monte Carlo simulations have previously been used to model light propagation through rodents' brain tissue, however, these prior attempts suffer from fundamental shortcomings. Here, we introduce and study two modified approaches for modeling the distributions of light emanating from a multimode fiber and scattering through tissue, using both realistic numerical Monte Carlo simulations and an analytical approach based on the beam-spread function approach. We demonstrate a good agreement of the new methods' predictions both with recently published data, and with new measurements in mouse brain cortical slices, where our results yield a new cortical scattering length estimate of ∼47 µm at λ = 473 nm, significantly shorter than ordinarily assumed in optogenetic applications.

Early Age-Related Functional Connectivity Decline in High-Order Cognitive Networks.

As the world ages, it becomes urgent to unravel the mechanisms underlying brain aging and find ways of intervening with them. While for decades cognitive aging has been related to localized brain changes, growing attention is now being paid to alterations in distributed brain networks. Functional connectivity magnetic resonance imaging (fcMRI) has become a particularly useful tool to explore large-scale brain networks; yet, the temporal course of connectivity lifetime changes has not been established. Here, an extensive cross-sectional sample (21-85 years old, N = 887) from a public fcMRI database was used to characterize adult lifespan connectivity dynamics within and between seven brain networks: the default mode, salience, dorsal attention, fronto-parietal control, auditory, visual and motor networks. The entire cohort was divided into young (21-40 years, mean ± SD: 25.5 ± 4.8, n = 543); middle-aged (41-60 years, 50.6 ± 5.4, n = 238); and old (61 years and above, 69.0 ± 6.3, n = 106) subgroups. Correlation matrices as well as a mixed model analysis of covariance indicated that within high-order cognitive networks a considerable connectivity decline is already evident by middle adulthood. In contrast, a motor network shows increased connectivity in middle adulthood and a subsequent decline. Additionally, alterations in inter-network interactions are noticeable primarily in the transition between young and middle adulthood. These results provide evidence that aging-related neural changes start early in adult life.

Holographic fiber bundle system for patterned optogenetic activation of large-scale neuronal networks.

Optogenetic perturbation has become a fundamental tool in controlling activity in neurons. Used to control activity in cell cultures, slice preparations, anesthetized and awake behaving animals, optical control of cell-type specific activity enables the interrogation of complex systems. A remaining challenge in developing optical control tools is the ability to produce defined light patterns such that power-efficient, precise control of neuronal populations is obtained. Here, we describe a system for patterned stimulation that enables the generation of structured activity in neurons by transmitting optical patterns from computer-generated holograms through an optical fiber bundle. The system couples the optical system to versatile fiber bundle configurations, including coherent or incoherent bundles composed of hundreds of up to several meters long fibers. We describe the components of the system, a method for calibration, and a detailed power efficiency and spatial specificity quantification. Next, we use the system to precisely control single-cell activity as measured by extracellular electrophysiological recordings in ChR2-expressing cortical cell cultures. The described system complements recent descriptions of optical control systems, presenting a system suitable for high-resolution spatiotemporal optical control of wide-area neural networks in vitro and in vivo, yielding a tool for precise neural system interrogation.

Transfer of learning relates to intrinsic connectivity between hippocampus, ventromedial prefrontal cortex, and large-scale networks.

An important aspect of adaptive learning is the ability to flexibly use past experiences to guide new decisions. When facing a new decision, some people automatically leverage previously learned associations, while others do not. This variability in transfer of learning across individuals has been demonstrated repeatedly and has important implications for understanding adaptive behavior, yet the source of these individual differences remains poorly understood. In particular, it is unknown why such variability in transfer emerges even among homogeneous groups of young healthy participants who do not vary on other learning-related measures. Here we hypothesized that individual differences in the transfer of learning could be related to relatively stable differences in intrinsic brain connectivity, which could constrain how individuals learn. To test this, we obtained a behavioral measure of memory-based transfer outside of the scanner and on a separate day acquired resting-state functional MRI images in 42 participants. We then analyzed connectivity across independent component analysis-derived brain networks during rest, and tested whether intrinsic connectivity in learning-related networks was associated with transfer. We found that individual differences in transfer were related to intrinsic connectivity between the hippocampus and the ventromedial prefrontal cortex, and between these regions and large-scale functional brain networks. Together, the findings demonstrate a novel role for intrinsic brain dynamics in flexible learning-guided behavior, both within a set of functionally specific regions known to be important for learning, as well as between these regions and the default and frontoparietal networks, which are thought to serve more general cognitive functions.