Low-frequency Blood Oxygen Level-dependent Fluctuations Research Articles

Effects of single- and multiple-dose oxytocin treatment on amygdala low-frequency BOLD fluctuations and BOLD spectral dynamics in autism

Prior neuroimaging clinical trials investigating the neural effects of intranasal administration of the neuropeptide oxytocin demonstrated a key role of the amygdala in oxytocin’s neuromodulatory effects. These studies mostly demonstrated the acute effects of single-dose administrations, examining task-dependent effects of oxytocin on brain activity elicited during explicit experimental tasks or stimuli presentations. The increased consideration of oxytocin as a potential ameliorating treatment in autism spectrum disorder (ASD) requires a better understanding of how multiple-dose oxytocin administration affects intrinsic, task-free, amygdala function. In this double-blind, randomized, placebo-controlled trial with between-subject design, 38 adult men with ASD underwent resting-state fMRI scanning before and after oxytocin or placebo treatment. Effects were assessed either after a single-dose administration, consisting of 24 international units, or after multiple-dose treatment, consisting of 4 weeks of once-daily nasal spray administrations. Compared to placebo, oxytocin induced a decrease in intrinsic resting-state BOLD signal amplitudes of the bilateral amygdala (fractional amplitudes of low-frequency fluctuations) and modulated cross-frequency interactions between adjacent BOLD frequency components. The right amygdala showed a pattern of reduced cross-frequency harmonicity, while the left amygdala showed a relative increase in harmonic cross-frequency interactions after oxytocin treatment. Notably, the direction and magnitude of BOLD spectral changes induced after a single-dose were qualitatively similar to treatment effects induced after multiple-dose treatment. Furthermore, the identified spectral changes in amygdalar BOLD amplitude and cross-frequency harmonicity were associated with improved feelings of tension, reflecting oxytocin’s anxiolytic, stress-reducing neuromodulatory role. The observed effects of oxytocin on amygdalar BOLD spectral characteristics and associated behaviors contribute to a deeper mechanistic understanding of the intrinsic, task-free neuromodulatory dynamics that underlie single- and multiple-dose oxytocin treatment in ASD. European Clinical Trial Registry (Eudract 2014-000586-45).

Intrinsic functional connectivity during continuous maintenance and suppression of emotion in bipolar disorder.

Resting-state connectivity studies, which examine unconstrained low frequency BOLD fluctuations, have reported inconsistent abnormalities in bipolar disorder (BP). In this study, we investigated intrinsic brain connectivity under the constraints of a Continuous Emotion Regulation Task (CERT) in BP patients in depressed (BPD) and manic (BPM) states, along with healthy control participants. Medication-free participants, with either a diagnosis of BP (BPD = 27, BPM = 30) or healthy controls (N = 33) were included. We collected 2 fMRI scans using the CERT paradigm, in which participants continuously watched negative pictures and either maintained emotions (MAINTAIN) or suppressed emotion using reappraisal techniques (SUPPRESS). Network-based statistic and graph theory analyses were examined for (i) the main effect of condition (within-group) and (ii) group and condition interactions. In healthy participants, MAINTAIN largely involved occipital and parietal cortices (p < .001), whereas SUPPRESS also recruited the frontal and cingulate cortices (p = .023). The interaction between group (BPD vs. BPM) and condition revealed a network involving the inferior frontal lobe which was stronger during MAINTAIN for BPD and during SUPPRESS for BPM (p = .037). Graph theory properties (i.e., clustering coefficient) for key nodes also evidenced significant group by condition interactions. We observed BP-related changes in network properties involved in normal and abnormal emotion regulation, which provide insights into the neural bases for affective disturbances in BP.

Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise

Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise

Low consistency of four brain connectivity measures derived from intracranial electrode measurements.

Measures of brain connectivity are currently subject to intense scientific and clinical interest. Multiple measures are available, each with advantages and disadvantages. Here, we study epilepsy patients with intracranial electrodes, and compare four different measures of connectivity. Perhaps the most direct measure derives from intracranial electrodes; however, this is invasive and spatial coverage is incomplete. These electrodes can be actively stimulated to trigger electrophysical responses to provide the first measure of connectivity. A second measure is the recent development of simultaneous BOLD fMRI and intracranial electrode stimulation. The resulting BOLD maps form a measure of effective connectivity. A third measure uses low frequency BOLD fluctuations measured by MRI, with functional connectivity defined as the temporal correlation coefficient between their BOLD waveforms. A fourth measure is structural, derived from diffusion MRI, with connectivity defined as an integrated diffusivity measure along a connecting pathway. This method addresses the difficult requirement to measure connectivity between any two points in the brain, reflecting the relatively arbitrary location of the surgical placement of intracranial electrodes. Using a group of eight epilepsy patients with intracranial electrodes, the connectivity from one method is compared to another method using all paired data points that are in common, yielding an overall correlation coefficient. This method is performed for all six paired-comparisons between the four methods. While these show statistically significant correlations, the magnitudes of the correlation are relatively modest (r2 between 0.20 and 0.001). In summary, there are many pairs of points in the brain that correlate well using one measure yet correlate poorly using another measure. These experimental findings present a complicated picture regarding the measure or meaning of brain connectivity.

Resting BOLD fluctuations in the primary somatosensory cortex correlate with tactile acuity

Sensory perception, including 2-point discrimination (2ptD), is tightly linked to cortical processing of tactile stimuli in primary somatosensory cortices. While the role of cortical activity in response to a tactile stimulus has been widely investigated, the role of baseline cortical activity is largely unknown. Using resting state fMRI we investigated the relationship between local BOLD fluctuations in the primary somatosensory cortex (the representational field of the hand) and 2ptD of the corresponding index finger (right and left). Cortical activity was measured using fractional amplitudes of the low frequency BOLD fluctuations (fALFF) and synchronicity using regional homogeneity (ReHo) of the S1 hand region during rest. 2ptD correlated with higher ReHo values in the representational areas of the contralateral S1 cortex (left hand: p = .028; right hand: p = .049). 2ptD additionally correlated with higher fALFF in the representational area of the left hand (p = .007) and showed a trend for a significant correlation in the representational area of the right hand (p = .051). Thus, higher BOLD amplitudes and synchronicity at rest, as measures of cortical activity and synchronicity, respectively, are related to better tactile discrimination abilities of the contralateral hand. Our findings extend the relationship seen between spontaneous BOLD fluctuations and sensory perception.

Resting state functional connectivity in the human spinal cord.

Functional magnetic resonance imaging using blood oxygenation level dependent (BOLD) contrast is well established as one of the most powerful methods for mapping human brain function. Numerous studies have measured how low-frequency BOLD signal fluctuations from the brain are correlated between voxels in a resting state, and have exploited these signals to infer functional connectivity within specific neural circuits. However, to date there have been no previous substantiated reports of resting state correlations in the spinal cord. In a cohort of healthy volunteers, we observed robust functional connectivity between left and right ventral (motor) horns, and between left and right dorsal (sensory) horns. Our results demonstrate that low-frequency BOLD fluctuations are inherent in the spinal cord as well as the brain, and by analogy to cortical circuits, we hypothesize that these correlations may offer insight into the execution and maintenance of sensory and motor functions both locally and within the cerebrum.DOI: http://dx.doi.org/10.7554/eLife.02812.001.

Anti-Correlated Cortical Networks of Intrinsic Connectivity in the Rat Brain

In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD fluctuations.

The brain remains electrically and metabolically active during resting conditions. The low-frequency oscillations (LFO) of the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI) coherent across distributed brain regions are known to exhibit features of this activity. However, these intrinsic oscillations may undergo dynamic changes in time scales of seconds to minutes during resting conditions. Here, using wavelet-transform based time-frequency analysis techniques, we investigated the dynamic nature of default-mode networks from intrinsic BOLD signals recorded from participants maintaining visual fixation during resting conditions. We focused on the default-mode network consisting of the posterior cingulate cortex (PCC), the medial prefrontal cortex (mPFC), left middle temporal cortex (LMTC) and left angular gyrus (LAG). The analysis of the spectral power and causal flow patterns revealed that the intrinsic LFO undergo significant dynamic changes over time. Dividing the frequency interval 0 to 0.25 Hz of LFO into four intervals slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz) and slow-2 (0.198–0.25 Hz), we further observed significant positive linear relationships of slow-4 in-out flow of network activity with slow-5 node activity, and slow-3 in-out flow of network activity with slow-4 node activity. The network activity associated with respiratory related frequency (slow-2) was found to have no relationship with the node activity in any of the frequency intervals. We found that the net causal flow towards a node in slow-3 band was correlated with the number of fibers, obtained from diffusion tensor imaging (DTI) data, from the other nodes connecting to that node. These findings imply that so-called resting state is not ‘entirely’ at rest, the higher frequency network activity flow can predict the lower frequency node activity, and the network activity flow can reflect underlying structural connectivity.

Complexity of low‐frequency blood oxygen level‐dependent fluctuations covaries with local connectivity

Very low-frequency blood oxygen level-dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generating such fluctuations are poorly understood. Using publicly available data from 1,019 subjects of age 7-30, we show that BOLD fluctuations exhibit temporal complexity that is linearly related to local connectivity (regional homogeneity), consistently and significantly covarying across subjects and across gray matter regions. This relationship persisted independently of covariance with gray matter density or standard deviation of BOLD signal. During late neurodevelopment, BOLD fluctuations were unchanged with age in association cortex while becoming more random throughout the rest of the brain. These data suggest that local interconnectivity may play a key role in establishing the complexity of low-frequency BOLD fluctuations underlying functional magnetic resonance imaging connectivity. Stable low-frequency power dynamics may emerge through segmentation and integration of connectivity during development of distributed large-scale brain networks.

Disrupted Functional Connectivity of the Pain Network in Fibromyalgia

To investigate the impact of chronic pain on brain dynamics at rest. Functional connectivity was examined in patients with fibromyalgia (FM) (n = 9) and healthy controls (n = 11) by calculating partial correlations between low-frequency blood oxygen level-dependent fluctuations extracted from 15 brain regions. Patients with FM had more positive and negative correlations within the pain network than healthy controls. Patients with FM displayed enhanced functional connectivity of the anterior cingulate cortex (ACC) with the insula (INS) and basal ganglia (p values between .01 and .05), the secondary somatosensory area with the caudate (CAU) (p = .012), the primary motor cortex with the supplementary motor area (p = .007), the globus pallidus with the amygdala and superior temporal sulcus (both p values < .05), and the medial prefrontal cortex with the posterior cingulate cortex (PCC) and CAU (both p values < .05). Functional connectivity of the ACC with the amygdala and periaqueductal gray (PAG) matter (p values between .001 and .05), the thalamus with the INS and PAG (both p values < .01), the INS with the putamen (p = .038), the PAG with the CAU (p = .038), the secondary somatosensory area with the motor cortex and PCC (both p values < .05), and the PCC with the superior temporal sulcus (p = .002) was also reduced in FM. In addition, significant negative correlations were observed between depression and PAG connectivity strength with the thalamus (r = -0.64, p = .003) and ACC (r = -0.60, p = .004). These findings demonstrate that patients with FM display a substantial imbalance of the connectivity within the pain network during rest, suggesting that chronic pain may also lead to changes in brain activity during internally generated thought processes such as occur at rest.

Functional Differentiation of Posterior Superior Temporal Sulcus in Autism: A Functional Connectivity Magnetic Resonance Imaging Study

Socio-communicative impairments are salient features of autism spectrum disorder (ASD). Abnormal development of posterior superior temporal sulcus (pSTS)--a key processing area for language, biological motion, and social context--could play a role in these deficits. Functional connectivity magnetic resonance imaging was used to examine the synchronization of low-frequency blood oxygen level-dependent fluctuations during continuous performance on a visual search task. Twenty-one children and adolescents with ASD and 26 typically developing individuals-matched on age and IQ-participated in the study. Three subregions of pSTS were delineated with a data-driven approach, and differentiation of pSTS was examined by comparing the connectivity of each subregion. In typically developing individuals, differentiation of networks was positively associated with age and anatomical maturation (cortical thinning in pSTS, greater white matter volume). In the ASD group, differentiation of pSTS connectivity was significantly reduced, and correlations with anatomical measures were weak or absent. Moreover, pSTS differentiation was inversely correlated with autism symptom severity. Atypical maturation of pSTS suggests altered trajectories for functional segregation and integration of networks in ASD, potentially related to impaired cognitive and sensorimotor development. Furthermore, our findings provide a novel explanation for atypically increased connectivity in ASD that has been observed in some functional connectivity magnetic resonance imaging studies.

Network anticorrelations, global regression, and phase‐shifted soft tissue correction

Synchronized low-frequency BOLD fluctuations are observed in dissociable large-scale, distributed networks with functional specialization. Two such networks, referred to as the task-positive network (TPN) and the task-negative network (TNN) because they tend to be active or inactive during cognitively demanding tasks, show reproducible anticorrelation of resting BOLD fluctuations after removal of the global brain signal. Because global signal regression mandates that anticorrelated regions to a given seed region must exist, it is unclear whether such anticorrelations are an artifact of global regression or an intrinsic property of neural activity. In this study, we demonstrate from simulated data that spurious anticorrelations are introduced during global regression for any two networks as a linear function of their size. Using actual resting state data, we also show that both the TPN and TNN become anticorrelated with the orbits when soft tissues are included in the global regression algorithm. Finally, we propose a technique using phase-shifted soft tissue regression (PSTCor) that allows improved correction of global physiological artifacts without global regression that shows improved anatomic specificity to global regression but does not show significant network anticorrelations. These results imply that observed anticorrelations between TNN and TPN may be largely or entirely artifactual in the resting state. These results also imply that differences in network anticorrelations attributed to pathophysiological or behavioral states may be due to differences in network size or recruitment rather than actual anticorrelations.

A historical perspective on the evolution of resting-state functional connectivity with MRI

In this review article, I discuss initial and recent studies of the assessment of functional connectivity in the human brain using low-frequency BOLD fluctuations in the resting state. By putting the studies in their historical context, the goal is to give the reader an appreciation of the evolution of the field and the pivotal events and studies that have led to the widespread acceptance of the method as a neuroscience tool for investigating functional connectivity in the human brain.

Spatiotemporal dynamics of low frequency BOLD fluctuations in rats and humans

Most studies involving spontaneous fluctuations in the BOLD signal extract connectivity patterns that show relationships between brain areas that are maintained over the length of the scanning session. In this study, however, we examine the spatiotemporal dynamics of the BOLD fluctuations to identify common patterns of propagation within a scan. A novel pattern finding algorithm was developed for detecting repeated spatiotemporal patterns in BOLD fMRI data. The algorithm was applied to high temporal resolution T2*-weighted multislice images obtained from rats and humans in the absence of any task or stimulation. In rats, the primary pattern consisted of waves of high signal intensity, propagating in a lateral to medial direction across the cortex, replicating our previous findings (Majeed et al., 2009a). These waves were observed primarily in sensorimotor cortex, but also extended to visual and parietal association areas. A secondary pattern, confined to subcortical regions consisted of an initial increase and subsequent decrease in signal intensity in the caudate–putamen. In humans, the most common spatiotemporal pattern consisted of an alteration between activation of areas comprising the “default-mode” (e.g., posterior cingulate and anterior medial prefrontal cortices) and the “task-positive” (e.g., superior parietal and premotor cortices) networks. Signal propagation from focal starting points was also observed. The pattern finding algorithm was shown to be reasonably insensitive to the variation in user-defined parameters, and the results were consistent within and between subjects. This novel approach for probing the spontaneous network activity of the brain has implications for the interpretation of conventional functional connectivity studies, and may increase the amount of information that can be obtained from neuroimaging data.

Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity

The resting brain exhibits coherent patterns of spontaneous low-frequency BOLD fluctuations. These so-called resting-state functional connectivity (RSFC) networks are posited to reflect intrinsic representations of functional systems commonly implicated in cognitive function. Yet, the direct relationship between RSFC and the BOLD response induced by task performance remains unclear. Here we examine the relationship between a region's pattern of RSFC across participants and that same region's level of BOLD activation during an Eriksen Flanker task. To achieve this goal we employed a voxel-matched regression method, which assessed whether the magnitude of task-induced activity at each brain voxel could be predicted by measures of RSFC strength for the same voxel, across 26 healthy adults. We examined relationships between task-induced activation and RSFC strength for six different seed regions [Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle, M.E., 2005. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U. S. A. 102, 9673–9678.], as well as the “default mode” and “task-positive” resting-state networks in their entirety. Our results indicate that, for a number of brain regions, inter-individual differences in task-induced BOLD activity were predicted by one of two resting-state properties: (1) the region's positive connectivity strength with the task-positive network, or (2) its negative connectivity with the default mode network. Strikingly, most of the regions exhibiting a significant relationship between their RSFC properties and task-induced BOLD activity were located in transition zones between the default mode and task-positive networks. These results suggest that a common mechanism governs many brain regions' neural activity during rest and its neural activity during task performance.

Correlated Low-Frequency BOLD Fluctuations in the Resting Human Brain Are Modulated by Recent Experience in Category-Preferential Visual Regions

The resting brain is associated with significant intrinsic activity fluctuations, such as the correlated low-frequency (LF) blood oxygen level-dependent (BOLD) fluctuations measured by functional magnetic resonance imaging. Despite a recent expansion of studies investigating resting-state LF-BOLD correlations, their nature and function are poorly understood. A major constraint on LF-BOLD correlations appears to be stable properties of anatomic connectivity. There is also evidence that coupling can be modulated by recent or ongoing task performance, suggesting that certain components of correlated dynamics are malleable on short timescales. Here, we compared activity during extended periods of rest following performance of 2 distinct cognitive tasks using different categories of visual stimuli-faces and complex scenes. Prolonged exposure to these distinct categories of visual information caused frontal networks to couple differentially with posterior category-preferential visual regions during subsequent periods of rest. In addition, we report preliminary evidence suggesting that conditions exist in which the degree of modulation of LF-BOLD correlations predicts subsequent memory. The finding that resting-state LF-BOLD correlations are modulated by recent experience in functionally specific brain regions engaged during prior task performance clarifies their role as a dynamic phenomenon which may be involved in mnemonic processes.

Low-frequency BOLD fluctuations demonstrate altered thalamocortical connectivity in diabetic neuropathic pain

BackgroundIn this paper we explored thalamocortical functional connectivity in a group of eight patients suffering from peripheral neuropathic pain (diabetic pain), and compared it with that of a group of healthy subjects. We hypothesized that functional interconnections between the thalamus and cortex can be altered after years of ongoing chronic neuropathic pain.ResultsFunctional connectivity was studied through a resting state functional magnetic resonance imaging (fMRI) paradigm: temporal correlations between predefined regions of interest (primary somatosensory cortex, ventral posterior lateral thalamic nucleus, medial dorsal thalamic nucleus) and the rest of the brain were systematically investigated. The patient group showed decreased resting state functional connectivity between the thalamus and the cortex.ConclusionThis supports the idea that chronic pain can alter thalamocortical connections causing a disruption of thalamic feedback, and the view of chronic pain as a thalamocortical dysrhythmia.

Resting state corticolimbic connectivity abnormalities in unmedicated bipolar disorder and unipolar depression

This study for the first time investigated resting state corticolimbic connectivity abnormalities in unmedicated bipolar disorder (BD) and compared them with findings in healthy controls and unipolar major depressive disorder (MDD) patient groups. Resting state correlations of low frequency BOLD fluctuations (LFBF) in echoplanar functional magnetic resonance (fMRI) data were acquired from a priori defined regions of interests (ROIs) in the pregenual anterior cingulate cortex (pgACC), dorsomedial thalamus (DMTHAL), pallidostriatum (PST) and amygdala (AMYG), to investigate corticolimbic functional connectivity in unmedicated BD patients in comparison to healthy subjects and MDD patients. Data were acquired from 11 unmedicated BD patients [six manic (BDM) and five depressed (BDD)], and compared with data available from 15 unmedicated MDD and 15 healthy subjects. BD patients had significantly decreased pgACC connectivity to the left and right DMTHAL, similar to findings seen in MDD. Additionally, BD patients had decreased pgACC connectivity with the left and right AMYG as well as the left PST. An exploratory analysis revealed that both BDD and BDM patients had decreased connectivity between the pgACC and DMTHAL. The results of the study indicate a common finding of decreased corticolimbic functional connectivity in different types of mood disorders.

Caffeine reduces resting-state BOLD functional connectivity in the motor cortex

In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects ( N = 9). We found that caffeine significantly ( p < 0.05) reduced measures of resting-state BOLD connectivity in the motor cortex. Baseline cerebral blood flow and spectral energy in the low-frequency BOLD fluctuations were also significantly decreased by caffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

Resting-state functional connectivity in animal models: modulations by exsanguination.

We studied the spatiotemporal characteristics of the resting state low frequency fluctuations in functional MRI (fMRI), blood oxygenation level dependent (BOLD) signal in isoflurane-anesthetized rats. fMRI-BOLD measurements at 9.4 Telsa were made during normal and exsanguinated condition previously known to alter cerebral blood flow (CBF) fluctuations in anesthetized rats. fMRI signal time series were low-pass filtered and studied by spectral analysis. During normal conditions, baseline mean arterial pressure (MAP) was 110 +/- 10 mm Hg and low-frequency fluctuations in BOLD signal were observed in the frequency range of 0.01 - 0.125 Hz. Following blood withdrawal (exsanguination), MAP decreased to 68 +/- 7 mm Hg, resulting in an increase in the amplitude of the low-frequency fluctuations in BOLD signal time series and an increase in power at several frequencies between 0.01 and 0.125 Hz. Spatially, the BOLD fluctuations were confined to the cortex and thalamus spanning both hemispheres with sparse presence in the caudate putamen and hippocampus during both normal and exsanguinated states. Spatial distribution of the low frequency fluctuations in BOLD signal, from cross correlation analysis, indicates substantial inter-hemispheric synchrony similar to that observed in the conscious human brain. The behavior of the resting state BOLD signal fluctuations similar to CBF fluctuations during exsanguination indicates a myogenic dependence. Also, a high inter-hemispheric synchrony combined with different phase characteristics of the low frequency BOLD fluctuations particularly in the hippocampus relative to the cortex emphasizes distinct functional networks.