Viscoelasticity of striatal brain areas reflects variations in body mass index of lean to overweight male adults

Although a variety of MRI studies investigated the link between body mass index (BMI) and parameters of neural gray matter (GM), the technique applied in most of these studies, voxel-based morphometry (VBM), focusses on the regional GM volume, a macroscopic tissue property. Thus, the studies were not able to exploit the BMI-related information contained in the GM microstructure although PET studies suggest that these factors are important. Here, we used cerebral MR Elastography (MRE) to characterize features of tissue microstructure by evaluating the propagation of shear waves applied to the skull and to assess local tissue viscoelasticity to test the link between this parameter and BMI in 22 lean to overweight males. Unlike the majority of existing MRE studies investigating neural viscoelasticity signals averaged across large brain regions, we used the viscoelasticity of individual voxels for our experiment. Our technique revealed a negative link between BMI and viscoelasticity of two areas of the striatal reward system, i.e., right putamen (t?=??8.2; p_{FWE-corrected}?=?0.005) and left globus pallidus (t?=??7.1; p_FWE?=?0.037) which was independent of GM volume at these coordinates. Finally, comparison of BMI models based on individual voxels vs. on signals averaged across brain atlas regions demonstrates that voxel-based models explain a significantly higher proportion of variance. Consequently, our findings show that cerebral MRE is suitable to identify medically relevant microstructural tissue properties. Using a voxel-wise analysis approach, we were able to utilize the high spatial resolution of MRE for mapping BMI-related information in the brain.

     

The effect of amyloid β on cognitive decline is modulated by neural integrity in cognitively normal elderly

ObjectiveAlzheimer's disease (AD) pathology of amyloid β (Aβ) accumulation and neurodegeneration may be relevant to preclinical cognitive decline. The objective of this study was to relate AD-sensitive biomarkers of Aβ and neurodegeneration and their interaction to longitudinal cognitive change in cognitively normal elderly.MethodsThirty-eight older people completed at least three consecutive neuropsychological examinations. Using positron emission tomography (PET), Aβ plaque burden was measured with [¹¹C]Pittsburgh compound B (PiB). PiB retention was dichotomized into a positive (n = 13) and negative (n = 25) PiB status. Neurodegenerative biomarkers were extracted within AD-vulnerable regions of interest (ROIs)—namely, the hippocampus and temporoparietal cortical areas. Within each ROI, metabolism was quantified with [¹⁸F] fluorodeoxyglucose (FDG) PET, and the gray matter structure was evaluated using volume (hippocampus) or thickness (cortical regions). ROI-specific functional and structural biomarkers were combined further into cross-modality neurodegenerative composite measures. Using hierarchical regression models, PiB and the neurodegenerative biomarkers were related to cognitive trajectories.ResultsPiB positivity was associated with memory and nonmemory worsening. The neurodegenerative biomarkers modified these relationships. Longitudinal cognitive decline was accelerated in those individuals who exhibited both PiB positivity and lower neurodegenerative biomarker scores, although the two measures appeared to be independent. PiB retention interacted predominantly with the cortical neurodegenerative composite for nonmemory change. Memory decline was best explained by the interaction between PiB and the hippocampal neurodegenerative composite, suggesting regional specificity of the neurodegenerative modulations.ConclusionsOur findings indicate that cognitive trajectories deteriorate at a faster rate in cognitively normal individuals expressing Aβ burden and neurodegeneration within specific AD-sensitive regions.     

Neurobiological origin of spurious brain morphological changes: A quantitative MRI study

The high gray‐white matter contrast and spatial resolution provided by T1‐weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1‐weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community. We acquired quantitative maps of the MRI parameters that determine signal intensities in T1‐weighted images (R₁ (=1/T1), R₂*, and PD) in a large cohort of healthy subjects (n = 120, aged 18–87 years). Synthetic T1‐weighted images were calculated from these quantitative maps and used to extract morphometry features—gray matter volume and cortical thickness. We observed significant variations in morphometry measures obtained from synthetic images derived from different subsets of MRI parameters. We also detected a modulation of these variations by age. Our findings highlight the impact of microstructural properties of brain tissue—myelination, iron, and water content—on automated measures of brain morphology and show that microstructural tissue changes might lead to the detection of spurious morphological changes in computational anatomy studies. They motivate a review of previous morphological results obtained from standard anatomical MRI images and highlight the value of quantitative MRI data for the inference of microscopic tissue changes in the healthy and diseased brain. Hum Brain Mapp 37:1801–1815, 2016. © 2016 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.     

Toward a cumulative science of functional integration: A meta‐analysis of psychophysiological interactions

Much of the work in cognitive neuroscience is shifting from a focus on single brain regions to a focus on the connectivity between multiple brain regions. These inter‐regional connectivity patterns contribute to a wide range of behaviors and are studied with models of functional integration. The rapid expansion of the literature on functional integration offers an opportunity to scrutinize the consistency and specificity of one of the most popular approaches for quantifying connectivity: psychophysiological interaction (PPI) analysis. We performed coordinate‐based meta‐analyses on 284 PPI studies, which allowed us to test (a) whether those studies consistently converge on similar target regions and (b) whether the identified target regions are specific to the chosen seed region and psychological context. Our analyses revealed two key results. First, we found that different types of PPI studies—e.g., those using seeds such as amygdala and dorsolateral prefrontal cortex (DLPFC) and contexts such as emotion and cognitive control, respectively—each consistently converge on similar target regions, thus supporting the reliability of PPI as a tool for studying functional integration. Second, we also found target regions that were specific to the chosen seed region and psychological context, indicating distinct patterns of brain connectivity. For example, the DLPFC seed reliably contributed to a posterior cingulate cortex target during cognitive control but contributed to an amygdala target in other contexts. Our results point to the robustness of PPI while highlighting common and distinct patterns of functional integration, potentially advancing models of brain connectivity. Hum Brain Mapp 37:2904–2917, 2016. © 2016 Wiley Periodicals, Inc .     

Microscopic magnetic resonance elastography of traumatic brain injury model

Traumatic brain injury (TBI) is a major cause of death and disability for which there is no cure. One of the issues inhibiting clinical trial success is the lack of targeting specific patient populations due to inconsistencies between clinical diagnostic tools and underlying pathophysiology. The development of reliable, noninvasive markers of TBI severity and injury mechanisms may better identify these populations, thereby improving clinical trial design. Magnetic resonance elastography (MRE), by assessing tissue mechanical properties, can potentially provide such marker. MRE synchronizes mechanical excitations with a phase contrast imaging pulse sequence to noninvasively register shear wave propagation, from which local values of tissue viscoelastic properties can be deduced. The working hypothesis of this study is that TBI involves a compression of brain tissue large enough to bring the material out of its elastic range, sufficiently altering mechanical properties to generate contrast on MRE measurements. To test this hypothesis, we combined microscopic MRE with brain tissue collected from adult male rats subjected to a controlled cortical impact injury. Measurements were made in different regions of interest (somatosensory cortex, hippocampus, and thalamus), and at different time points following the injury (immediate, 24 h, 7 days, 28 days). Values of stiffness in the somatosensory cortex were found to be 23-32% lower in the injured hemisphere than in the healthy one, when no significant difference was observed in the case of sham brains. A preliminary in vivo experiment is also presented, as well as alternatives to improve the faithfulness of stiffness recovery.     

Extracellular matrix protein expression is brain region dependent

In the brain, extracellular matrix (ECM) components form networks that contribute to structural and functional diversity. Maladaptive remodeling of ECM networks has been reported in neurodegenerative and psychiatric disorders, suggesting that the brain microenvironment is a dynamic structure. A lack of quantitative information about ECM distribution in the brain hinders an understanding of region‐specific ECM functions and the role of ECM in health and disease. We hypothesized that each ECM protein as well as specific ECM structures, such as perineuronal nets (PNNs) and interstitial matrix, are differentially distributed throughout the brain, contributing to the unique structure and function in the various regions of the brain. To test our hypothesis, we quantitatively analyzed the distribution, colocalization, and protein expression of aggrecan, brevican, and tenascin‐R throughout the rat brain utilizing immunohistochemistry and mass spectrometry analysis and assessed the effect of aggrecan, brevican, and/or tenascin‐R on neurite outgrowth in vitro. We focused on aggrecan, brevican, and tenascin‐R as they are especially expressed in the mature brain, and have established roles in brain development, plasticity, and neurite outgrowth. The results revealed a differentiated distribution of all three proteins throughout the brain and indicated that their presence significantly reduces neurite outgrowth in a 3D in vitro environment. These results underline the importance of a unique and complex ECM distribution for brain physiology and suggest that encoding the distribution of distinct ECM proteins throughout the brain will aid in understanding their function in physiology and in turn assist in identifying their role in disease. J. Comp. Neurol. 524:1309–1336, 2016. © 2016 Wiley Periodicals, Inc.     

Association between olfaction and higher cortical functions in Alzheimer’s disease,mild cognitive impairment,and healthy older adults

Introduction: Neural regions important for smell are proximal and closely connected to cortical areas that have been strongly implicated in higher order functions of value-based decision making and emotional memory. The integrity of these neural regions are affected in aging and neurodegenerative conditions. Two specific predictions follow from these neuroanatomical arrangements—namely, that olfaction would be associated with value-based decision making and with emotional memory. Method: To test these predictions, we measured these different capacities in participants with presumed varying degrees of integrity of the relevant brain structures: specifically, 13 patients with Alzheimer’s disease, 8 patients with mild cognitive impairment, and 20 healthy older adults. The participants completed detailed tests of olfaction, value-based decision making, emotional memory, and general cognitive ability. Results: Olfactory functioning was significantly associated with emotional and nonemotional memory. The association was especially strong and consistent for memory recall with olfaction, explaining as much as 10% additional variance over and above general cognition. Olfactory functioning was not strongly or consistently associated with decision making over and above general cognition. Conclusion: Olfaction is a strong predictor of memory recall. These findings may contribute to a better understanding of olfaction and specific cognitive domains known to be affected by aging and implicated in neurodegenerative disease.     

Dynamic functional connectivity shapes individual differences in associative learning

Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time‐dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning‐related performance change are supported by differences in cognitive ability and time‐sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911–3928, 2016. © 2016 Wiley Periodicals, Inc.     

Functional connectivity at rest is sensitive to individual differences in executive function: A network analysis

Graph theory provides a means to understand the nature of network characteristics and connectivity between specific brain regions. Here it was used to investigate whether the network characteristics of the brain at rest are associated with three dimensions thought to underlie individual differences in executive function (EF)—common EF, shifting‐specific EF, and updating‐specific EF (Miyake and Friedman [2012]). To do so, both an a priori analysis focused mainly on select frontoparietal regions previously linked to individual differences in EF as well as a whole‐brain analysis were performed. The findings indicated that individual differences in each of the three dimensions of EF were associated with specific patterns of resting‐state connectivity both in a priori and other brain regions. More specifically, higher common EF was associated with greater integrative (i.e., more hublike) connectivity of cuneus and supplementary motor area but less integrative function of lateral frontal nodes and left temporal lobe nodes. Higher shifting‐specific EF was associated with more hublike motor‐related nodes and cingulo‐opercular nodes. Higher updating‐specific EF was associated with less hublike lateral and medial frontoparietal nodes. In general, these results suggested that higher ability in each of these three dimensions of EF was not solely characterized by the connectivity characteristics of frontoparietal regions. The pattern was complicated in that higher EF was associated with the connectivity profile of nodes outside of the traditional frontoparietal network, as well as with less hublike or centrality characteristics of some nodes within the frontoparietal network. Hum Brain Mapp 37:2959–2975, 2016. © 2016 Wiley Periodicals, Inc.     

Cortical thickness change in autism during early childhood

Structural magnetic resonance imaging (MRI) scans at high spatial resolution can detect potential foci of early brain dysmaturation in children with autism spectrum disorders (ASD). In addition, comparison between MRI and behavior measures over time can identify patterns of brain change accompanying specific outcomes. We report structural MRI data from two time points for a total of 84 scans in children with ASD and 30 scans in typical controls (mean age time one = 4.1 years, mean age at time two = 6.6 years). Surface‐based cortical morphometry and linear mixed effects models were used to link changes in cortical anatomy to both diagnostic status and individual differences in changes in language and autism severity. Compared with controls, children with ASD showed accelerated gray matter volume gain with age, which was driven by a lack of typical age‐related cortical thickness (CT) decrease within 10 cortical regions involved in language, social cognition, and behavioral control. Greater expressive communication gains with age in children with ASD were associated with greater CT gains in a set of right hemisphere homologues to dominant language cortices, potentially identifying a compensatory system for closer translational study. Hum Brain Mapp 37:2616–2629, 2016. © 2016 Wiley Periodicals, Inc .     

Intrinsic network activity in tinnitus investigated using functional MRI

Tinnitus is an increasingly common disorder in which patients experience phantom auditory sensations, usually ringing or buzzing in the ear. Tinnitus pathophysiology has been repeatedly shown to involve both auditory and non‐auditory brain structures, making network‐level studies of tinnitus critical. In this magnetic resonance imaging (MRI) study, two resting‐state functional connectivity (RSFC) approaches were used to better understand functional network disturbances in tinnitus. First, we demonstrated tinnitus‐related reductions in RSFC between specific brain regions and resting‐state networks (RSNs), defined by independent components analysis (ICA) and chosen for their overlap with structures known to be affected in tinnitus. Then, we restricted ICA to data from tinnitus patients, and identified one RSN not apparent in control data. This tinnitus RSN included auditory–sensory regions like inferior colliculus and medial Heschl's gyrus, as well as classically non‐auditory regions like the mediodorsal nucleus of the thalamus, striatum, lateral prefrontal, and orbitofrontal cortex. Notably, patients' reported tinnitus loudness was positively correlated with RSFC between the mediodorsal nucleus and the tinnitus RSN, indicating that this network may underlie the auditory–sensory experience of tinnitus. These data support the idea that tinnitus involves network dysfunction, and further stress the importance of communication between auditory–sensory and fronto‐striatal circuits in tinnitus pathophysiology. Hum Brain Mapp 37:2717–2735, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc .     

The effects of dexamphetamine on the resting‐state electroencephalogram and functional connectivity

The catecholamines—dopamine and noradrenaline—play important roles in directing and guiding behavior. Disorders of these systems, particularly within the dopamine system, are associated with several severe and chronically disabling psychiatric and neurological disorders. We used the recently published group independent components analysis (ICA) procedure outlined by Chen et al. (2013) to present the first pharmaco‐EEG ICA analysis of the resting ‐ state EEG in healthy participants administered 0.45 mg/kg dexamphetamine. Twenty‐eight healthy participants between 18 and 41 were recruited. Bayesian nested‐domain models that explicitly account for spatial and functional relationships were used to contrast placebo and dexamphetamine on component spectral power and several connectivity metrics. Dexamphetamine led to reductions across delta, theta, and alpha spectral power bands that were predominantly localized to Frontal and Central regions. Beta 1 and beta 2 power were reduced by dexamphetamine at Frontal ICs, while beta 2 and gamma power was enhanced by dexamphetamine in posterior regions, including the parietal, occipital‐temporal, and occipital regions. Power–power coupling under dexamphetamine was similar for both states, resembling the eyes open condition under placebo. However, orthogonalized measures of power coupling and phase coupling did not show the same effect of dexamphetamine as power‐power coupling. We discuss the alterations of low‐ and high ‐ frequency EEG power in response to dexamphetamine within the context of disorders of dopamine regulation, in particular schizophrenia, as well as in the context of a recently hypothesized association between low ‐ frequency power and aspects of anhedonia. Hum Brain Mapp 37:570–588, 2016. © 2015 Wiley Periodicals, Inc.     

Age‐related cognitive decline coincides with accelerated volume loss of the dorsal but not ventral hippocampus in mice

Even in the absence of neurodegenerative diseases, progressing age often coincides with cognitive decline and morphological changes. However, longitudinal studies that directly link these two processes are missing. In this proof‐of‐concept study we therefore performed repeated within‐subject testing of healthy male R26R mice in a spatial learning task in combination with manganese‐enhanced volumetric MRI analyses at the ages of 8, 16, and 24 months. We grouped the mice into good and poor performers (n = 6, each), based on their spatial learning abilities at the age of 24 months. Using this stratification, we failed to detect a priori volume differences, but observed a significant decrease in total hippocampal volume over time for both groups. Interestingly, this volume decrease was specific for the dorsal hippocampus and significantly accelerated in poor performers between 16 and 24 months of age. This is the first time that individual changes in hippocampal volume were traced alongside cognitive performance within the same subjects over 1½ years. Our study points to a causal link between volume loss of the dorsal hippocampus and cognitive impairments. In addition, it suggests accelerated degenerative processes rather than a priori volume differences as determining trajectories of age‐related cognitive decline. Despite the relatively small sample sizes, the strong behavioral and moderate morphological alterations demonstrate the general feasibility of longitudinal studies of age‐related decline in cognition and hippocampus integrity. © 2016 Wiley Periodicals, Inc.     

High‐order resting‐state functional connectivity network for MCI classification

Brain functional connectivity (FC) network, estimated with resting‐state functional magnetic resonance imaging (RS‐fMRI) technique, has emerged as a promising approach for accurate diagnosis of neurodegenerative diseases. However, the conventional FC network is essentially low‐order in the sense that only the correlations among brain regions (in terms of RS‐fMRI time series) are taken into account. The features derived from this type of brain network may fail to serve as an effective disease biomarker. To overcome this drawback, we propose extraction of novel high‐order FC correlations that characterize how the low‐order correlations between different pairs of brain regions interact with each other. Specifically, for each brain region, a sliding window approach is first performed over the entire RS‐fMRI time series to generate multiple short overlapping segments. For each segment, a low‐order FC network is constructed, measuring the short‐term correlation between brain regions. These low‐order networks (obtained from all segments) describe the dynamics of short‐term FC along the time, thus also forming the correlation time series for every pair of brain regions. To overcome the curse of dimensionality, we further group the correlation time series into a small number of different clusters according to their intrinsic common patterns. Then, the correlation between the respective mean correlation time series of different clusters is calculated to represent the high‐order correlation among different pairs of brain regions. Finally, we design a pattern classifier, by combining features of both low‐order and high‐order FC networks. Experimental results verify the effectiveness of the high‐order FC network on disease diagnosis. Hum Brain Mapp 37:3282–3296, 2016. © 2016 Wiley Periodicals, Inc.     

Global and regional alterations of hippocampal anatomy in long‐term meditation practitioners

Studies linking meditation and brain structure are still relatively sparse, but the hippocampus is consistently implicated as one of the structures altered in meditation practitioners. To explore hippocampal features in the framework of meditation, we analyzed high‐resolution structural magnetic resonance imaging data from 30 long‐term meditators and 30 controls, closely matched for sex, age, and handedness. Hippocampal formations were manually traced following established protocols. In addition to calculating left and right hippocampal volumes (global measures), regional variations in surface morphology were determined by measuring radial distances from the hippocampal core to spatially matched surface points (local measures). Left and right hippocampal volumes were larger in meditators than in controls, significantly so for the left hippocampus. The presence and direction of this global effect was confirmed locally by mapping the exact spatial locations of the group differences. Altogether, radial distances were larger in meditators compared to controls, with up to 15% difference. These local effects were observed in several hippocampal regions in the left and right hemisphere though achieved significance primarily in the left hippocampal head. Larger hippocampal dimensions in long‐term meditators may constitute part of the underlying neurological substrate for cognitive skills, mental capacities, and/or personal traits associated with the practice of meditation. Alternatively, given that meditation positively affects autonomic regulation and immune activity, altered hippocampal dimensions may be one result of meditation‐induced stress reduction. However, given the cross‐sectional design, the lack of individual stress measures, and the limited resolution of brain data, the exact underlying neuronal mechanisms remain to be established. Hum Brain Mapp 34:3369–3375, 2013. © 2012 Wiley Periodicals, Inc.     

Application of multiline two-photon microscopy to functional in vivo imaging

High spatial resolution and low risks of photodamage make two-photon laser-scanning microscopy (TPLSM) the method of choice for biological imaging. However, the study of functional dynamics such as neuronal calcium regulation often also requires a high temporal resolution. Hitherto, acquisition speed is usually increased by line scanning, which restricts spatial resolution to structures along a single axis. To overcome this gap between high spatial and high temporal resolution we performed TPLSM with a beam multiplexer to generate multiple laser foci inside the sample. By detecting the fluorescence emitted from these laser foci with an electron-multiplying camera, it was possible to perform multiple simultaneous linescans. In addition to multiline scanning, the array of up to 64 laser beams could also be used in x-y scan mode to collect entire images at high frame rates. To evaluate the applicability of multiline TPLSM to functional in vivo imaging, calcium signals were monitored in visual motion-sensitive neurons in the brain of flies. The capacity of our method to simultaneously acquire signals at different cellular locations is exemplified by measurements at branched neurites and 'spine'-like structures. Calcium dynamics depended on branch size, but 'spines' did not systematically differ from their 'parent neurites'. The spatial resolution of our setup was critically evaluated by comparing it to confocal microscopy and the negative effect of scattering of emission light during image detection was assessed directly by running the setup in both imaging and point-scanning mode.     

Structure Mapping for Social Learning

Analogical reasoning is a foundational tool for human learning, allowing learners to recognize relational structures in new events and domains. Here I sketch some grounds for understanding and applying analogical reasoning in social learning. The social world is fundamentally characterized by relations between people, with common relational structures—such as kinships and social hierarchies—forming social units that dictate social behaviors. Just as young learners use analogical reasoning for learning relational structures in other domains—spatial relations, verbs, relational categories—analogical reasoning ought to be a useful cognitive tool for acquiring social relations and structures.     

Meta‐analysis of psychophysiological interactions: Revisiting cluster‐level thresholding and sample sizes

Within the neuroimaging community, coordinate based meta‐analyses (CBMAs) are essential for aggregating findings across studies and testing whether those studies report similar anatomical locations. This approach has been predominantly applied to studies that focus on whether activation of a brain region is associated with a given psychological process. In a recent paper, we used CBMA to examine a distinct set of studies—that is, those focusing on whether connectivity between brain regions is modulated by a given psychological process (Smith et al. [2016]: Hum Brain Mapp 37:2904–2917). Specifically, we reviewed 284 studies examining brain connectivity with psychophysiological interactions (PPI). Our meta‐analytic results indicated that PPI yields connectivity patterns that are consistent across studies and that can be specific for a given psychological process and seed region. After publication of our findings, we learned that the analysis software we used to conduct our CBMAs (GingerALE v2.3.3) contained an implementation error that led to results that were more liberal than intended. Here, we comment on the impact of this implementation error on the results of our paper, new recommendations for sample sizes in CBMAs, and the importance of communication between software users and developers. We show that our key claims are supported in a reanalysis and that our results are robust to new guidelines on sample sizes. Hum Brain Mapp 38:588–591, 2017. © 2016 Wiley Periodicals, Inc.     

Hippocampal and prefrontal contributions to memory retrieval: Examination of immediate early gene,NMDA receptor and environmental interactions

Animals can use a range of strategies to recall important locations. These include simple stimulus–response strategies and more complex spatial (place) strategies, which are thought to have distinct neural substrates. The hippocampus—and NMDA receptor activation therein—is considered to be crucial for spatial, but not response strategies. The medial prefrontal cortex has also been implicated in memory retrieval; however, evidence concerning its specific role is equivocal. Both hippocampal and prefrontal regions have been associated with flexible behavioural responding (e.g. when task demands change). Here, we investigated the use of spatial and non‐spatial strategies in the Morris water maze and their associated brain areas in rats using immediate early gene (IEG) imaging of Zif268 and c‐Fos. Specifically, we charted the involvement of hippocampal and prefrontal subregions during retrieval of spatial and non‐spatial memories. Behavioural flexibility was also examined using intact and partial cue configurations during recall. Results indicated that regions of both the hippocampus (area CA3) and prefrontal cortex (anterior cingulate cortex) were preferentially engaged in spatial memory recall compared to response learning. In addition, both spatial and non‐spatial memories were dependent on NMDA receptor activation. MK801 impaired recall performance across all groups and reduced IEG activation across hippocampal and prefrontal regions. Finally, IEG results revealed divergent patterns of Zif268 and c‐Fos activity and support the suggestion that Zif268 plays a functional role in the recall of long‐term memories.