Prefrontal–hippocampal interactions for spatial navigation

The Multimodal MRI Features of Deteriorative MCI Patients-A 2-Year Follow-up Study

BACKGROUND

To explore the magnetic resonance imaging (MRI) features of the 2-year follow-up patients with deteriorative mild cognitive impairment (MCI).

METHODS

A number of 105 MCI-afflicted patients underwent multimodal MRI sequences in 2019 and 2021, respectively. The brain image was segmented into 116 regions, and the apparent diffusion coefficient (ADC) value, fractional anisotropy (FA) value, and cerebral blood flow (CBF) value of each brain region were extracted by the deep learning algorithm. They were divided into the deteriorative MCI group and the non-deteriorative MCI group according to the cognitive function 2 years later.

RESULTS

With the FA values analyzed, we found the characteristics in nine brain regions as follows: In both 2019 and 2021, the FA value was significantly lower in the deterioration group (DG) than in the non-deterioration group (NDG) (P < 0.001). In the DG, the FA value was significantly lower in 2021 than in 2019 (P < 0.001), while in the NDG, no significant difference was found in the FA value between 2019 and 2021 (P > 0.05). In terms of the ADC value, we found the characteristics in middle frontal gyrus-orbital part region as follows: In both 2019 and 2021, the ADC value was significantly higher in the DG than in the NDG (P < 0.001). In the DG, the ADC value was significantly higher in 2021 than in 2019 (P < 0.001).

CONCLUSIONS

The decrease of the FA value in nine brain regions and the increase of the ADC value in one brain region could be the warning characteristics of the deterioration of MCI.

Sub-Chronic 30 mg/kg Iron Treatment Induces Spatial Cognition Impairment and Brain Oxidative Stress in Wistar Rats

Iron overload has been shown to have deleterious effects in the brain through the formation of reactive oxygen species, which ultimately may contribute to neurodegenerative disorders. Accordingly, rodent studies have indicated that systemic administration of iron produces excess iron in the brain and results in behavioral and cognitive deficits. To what extent cognitive abilities are affected and which neurobiological mechanisms underlie those deficits remain to be more fully characterized. In the present study, we looked at the effects of a 30 mg/kg iron sub-chronic treatment on cognitive abilities in two hippocampal-dependent spatial tasks (place navigation, spatial/non-spatial object recognition), in relation with iron content and oxidative stress biomarkers (MDA, SOD, CAT) in the cerebellum, hippocampus, prefrontal cortex and striatum, four brain areas known to be involved in the processing of spatial information. Iron-treated rats were impaired in acquisition and retention of the platform location in the navigation task and in the spatial/non-spatial object recognition task. Iron content and MDA were found to be increased in the four brain regions of interest, but activity of the antioxidant enzymes was not modified. The results indicate that the ability of rats to process spatial information whether in place navigation or spontaneous object spatial/non-spatial recognition is disrupted following a 30 mg/kg sub-chronic treatment. The deficits are hypothesized to result from iron excess-induced oxidative stress in the network of brain areas involved in the processing of spatial information.

Neural signatures of opioid-induced risk-taking behavior in the prelimbic prefrontal cortex

Opioid use disorder occurs alongside impaired risk-related decision-making, but the underlying neural correlates are unclear. We developed an approach-avoidance conflict task using a modified conditioned place preference procedure to study neural signals of risky opioid seeking in the prefrontal cortex, a region implicated in executive decision-making. Following morphine conditioned place preference, rats underwent a conflict test in which fear-inducing cat odor was introduced in the previously drug-paired side of the apparatus. While the saline-exposed control group avoided cat odor, the morphine group included two subsets of rats that either maintained a preference for the paired side despite the presence of cat odor (Risk-Takers) or exhibited increased avoidance (Risk-Avoiders), as revealed by K-means clustering. Single-unit recordings from the prelimbic cortex (PL) demonstrated decreased neuronal activity upon acute morphine exposure in both Risk-Takers and Risk-Avoiders, but this firing rate suppression was absent after repeated morphine administration. Risk-Avoiders also displayed distinct post-morphine excitation in PL which persisted across conditioning. During the preference test, subpopulations of PL neurons in all groups were either excited or inhibited when rats entered the paired side. Interestingly, the inhibition in PL activity was lost during the subsequent conflict test in both saline and Risk-Avoider groups, but persisted in Risk-Takers. Additionally, Risk-Takers showed an increase in the proportion of PL neurons displaying location-specific firing in the drug-paired side from the preference to the conflict test. Together, our results suggest that persistent PL inhibitory signaling in the drug-associated context during motivational conflict may underlie increased risk-taking behavior following opioid exposure.

Prefrontal and lateral entorhinal neurons co-dependently learn item-outcome rules

The ability to learn novel items depends on brain functions that store information about items classified by their associated meanings and outcomes1-4, but the underlying neural circuit mechanisms of this process remain poorly understood. Here we show that deep layers of the lateral entorhinal cortex (LEC) contain two groups of 'item-outcome neurons': one developing activity for rewarded items during learning, and another for punished items. As mice learned an olfactory item-outcome association, we found that the neuronal population of LEC layers 5/6 (LECL5/6) formed an internal map of pre-learned and novel items, classified into dichotomic rewarded versus punished groups. Neurons in the medial prefrontal cortex (mPFC), which form a bidirectional loop circuit with LECL5/6, developed an equivalent item-outcome rule map during learning. When LECL5/6 neurons were optogenetically inhibited, tangled mPFC representations of novel items failed to split into rewarded versus punished groups, impairing new learning by mice. Conversely, when mPFC neurons were inhibited, LECL5/6 representations of individual items were held completely separate, disrupting both learning and retrieval of associations. These results suggest that LECL5/6 neurons and mPFC neurons co-dependently encode item memory as a map of associated outcome rules.

Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity

Objective. Therapeutic brain stimulation is conventionally delivered using constant-frequency stimulation pulses. Several recent clinical studies have explored how unconventional and irregular temporal stimulation patterns could enable better therapy. However, it is challenging to understand which irregular patterns are most effective for different therapeutic applications given the massively high-dimensional parameter space.Approach. Here we applied many irregular stimulation patterns in a single neural circuit to demonstrate how they can enable new dimensions of neural control compared to conventional stimulation, to guide future exploration of novel stimulation patterns in translational settings. We optogenetically excited the septohippocampal circuit with constant-frequency, nested pulse, sinusoidal, and randomized stimulation waveforms, systematically varying their amplitude and frequency parameters.Main results.We first found equal entrainment of hippocampal oscillations: all waveforms provided similar gamma-power increase, whereas no parameters increased theta-band power above baseline (despite the mechanistic role of the medial septum in driving hippocampal theta oscillations). We then compared each of the effects of each waveform on high-dimensional multi-band activity states using dimensionality reduction methods. Strikingly, we found that conventional stimulation drove predominantly 'artificial' (different from behavioral activity) effects, whereas all irregular waveforms induced activity patterns that more closely resembled behavioral activity.Significance. Our findings suggest that irregular stimulation patterns are not useful when the desired mechanism is to suppress or enhance a single frequency band. However, novel stimulation patterns may provide the greatest benefit for neural control applications where entraining a particular mixture of bands (e.g. if they are associated with different symptoms) or behaviorally-relevant activity is desired.

Large-scale coupling of prefrontal activity patterns as a mechanism for cognitive control in health and disease: evidence from rodent models

Cognitive control of behavior is crucial for well-being, as allows subject to adapt to changing environments in a goal-directed way. Changes in cognitive control of behavior is observed during cognitive decline in elderly and in pathological mental conditions. Therefore, the recovery of cognitive control may provide a reliable preventive and therapeutic strategy. However, its neural basis is not completely understood. Cognitive control is supported by the prefrontal cortex, structure that integrates relevant information for the appropriate organization of behavior. At neurophysiological level, it is suggested that cognitive control is supported by local and large-scale synchronization of oscillatory activity patterns and neural spiking activity between the prefrontal cortex and distributed neural networks. In this review, we focus mainly on rodent models approaching the neuronal origin of these prefrontal patterns, and the cognitive and behavioral relevance of its coordination with distributed brain systems. We also examine the relationship between cognitive control and neural activity patterns in the prefrontal cortex, and its role in normal cognitive decline and pathological mental conditions. Finally, based on these body of evidence, we propose a common mechanism that may underlie the impaired cognitive control of behavior.

Theta Oscillations Support Prefrontal-hippocampal Interactions in Sequential Working Memory

The prefrontal cortex and hippocampus may support sequential working memory beyond episodic memory and spatial navigation. This stereoelectroencephalography (SEEG) study investigated how the dorsolateral prefrontal cortex (DLPFC) interacts with the hippocampus in the online processing of sequential information. Twenty patients with epilepsy (eight women, age 27.6 ± 8.2 years) completed a line ordering task with SEEG recordings over the DLPFC and the hippocampus. Participants showed longer thinking times and more recall errors when asked to arrange random lines clockwise (random trials) than to maintain ordered lines (ordered trials) before recalling the orientation of a particular line. First, the ordering-related increase in thinking time and recall error was associated with a transient theta power increase in the hippocampus and a sustained theta power increase in the DLPFC (3-10 Hz). In particular, the hippocampal theta power increase correlated with the memory precision of line orientation. Second, theta phase coherences between the DLPFC and hippocampus were enhanced for ordering, especially for more precisely memorized lines. Third, the theta band DLPFC → hippocampus influence was selectively enhanced for ordering, especially for more precisely memorized lines. This study suggests that theta oscillations may support DLPFC-hippocampal interactions in the online processing of sequential information.

Dopamine differentially modulates medial temporal lobe activity and behavior during spatial navigation in young and older adults

Aging is associated with changes in spatial navigation behavior. In addition to an overall performance decline, older adults tend to rely more on proximal location cue information than on environmental boundary information during spatial navigation compared to young adults. The fact that older adults are more susceptible to errors during spatial navigation might be partly attributed to deficient dopaminergic modulation of hippocampal and striatal functioning. Hence, elevating dopamine levels might differentially modulate spatial navigation and memory performance in young and older adults. In this work, we administered levodopa (L-DOPA) in a double-blind within-subject, placebo-controlled design and recorded functional neuroimaging while young and older adults performed a 3D spatial navigation task in which boundary geometry or the position of a location cue were systematically manipulated. An age by intervention interaction on the neural level revealed an upregulation of brain responses in older adults and a downregulation of responses in young adults within the medial temporal lobe (including hippocampus and parahippocampus) and brainstem, during memory retrieval. Behaviorally, L-DOPA had no effect on older adults' overall memory performance; however, older adults whose spatial memory improved under L-DOPA also showed a shift towards more boundary processing under L-DOPA. In young adults, L-DOPA induced a decline in spatial memory performance in task-naïve participants. These results are consistent with the inverted-U-shaped hypothesis of dopamine signaling and cognitive function and suggest that increasing dopamine availability improves hippocampus-dependent place learning in some older adults.

Reaching the Goal: Superior Navigators in Late Adulthood Provide a Novel Perspective into Successful Cognitive Aging

Normal aging is typically associated with declines in navigation and spatial memory abilities. However, increased interindividual variability in performance across various navigation/spatial memory tasks is also evident with advancing age. In this review paper, we shed the spotlight on those older individuals who exhibit exceptional, sometimes even youth-like navigational/spatial memory abilities. Importantly, we (1) showcase observations from existing studies that demonstrate superior navigation/spatial memory performance in late adulthood, (2) explore possible cognitive correlates and neurophysiological mechanisms underlying these preserved spatial abilities, and (3) discuss the potential link between the superior navigators in late adulthood and SuperAgers (older adults with superior episodic memory). In the closing section, given the lack of studies that directly focus on this subpopulation, we highlight several important directions that future studies could look into to better understand the cognitive characteristics of older superior navigators and the factors enabling such successful cognitive aging.

A fuzzy-oscillatory model of medial prefrontal cortex control function in spatial memory retrieval in human navigation function

Navigation can be broadly defined as the process of moving from an origin to a destination through path-planning. Previous research has shown that navigation is mainly related to the function of the medial temporal lobe (MTL), including the hippocampus (HPC), and medial prefrontal cortex (mPFC), which controls retrieval of the spatial memories from this region. In this study, we suggested a cognitive and computational model of human navigation with a focus on mutual interactions between the hippocampus (HPC) and the mPFC using the concept of synchrony. The Van-der-pol oscillator was used to model the synchronous process of receiving and processing “what stream” information. A fuzzy lookup table system was applied for modeling the controlling function of the mPFC in retrieving spatial information from the HPC. The effect of attention level was also included and simulated. The performance of the model was evaluated using information reported in previous experimental research. Due to the inherent stability of the proposed fuzzy-oscillatory model, it is less sensitive to the exact values of the initial conditions, and therefore, it is shown that it is consistent with the actual human performance in real environments. Analyzing the proposed cognitive and fuzzy-oscillatory computational model demonstrates that the model is able to reproduce certain cognitive and functional disturbances in navigation in related diseases such as Alzheimer’s disease (AD). We have shown that an increase in the bifurcation parameter of the Van-der-pol equation represents an increase in the low-frequency spectral power density and a decrease in the high-frequency spectral power as occurs in AD due to an increase in the amyloid plaques in the brain. These changes in the frequency characteristics of neuronal activity, in turn, lead to impaired recall and retrieval of landmarks information and learned routes upon encountering them. As a result, and because of the wrong frequency code being transmitted, the relevant set of rules in the mPFC is not activated, or another unrelated set will be activated, which leads to forgetfulness and erroneous decisions in routing and eventually losing the route in Alzheimer’s patients.

A Brain-Inspired Model of Hippocampal Spatial Cognition Based on a Memory-Replay Mechanism

Since the hippocampus plays an important role in memory and spatial cognition, the study of spatial computation models inspired by the hippocampus has attracted much attention. This study relies mainly on reward signals for learning environments and planning paths. As reward signals in a complex or large-scale environment attenuate sharply, the spatial cognition and path planning performance of such models will decrease clearly as a result. Aiming to solve this problem, we present a brain-inspired mechanism, a Memory-Replay Mechanism, that is inspired by the reactivation function of place cells in the hippocampus. We classify the path memory according to the reward information and find the overlapping place cells in different categories of path memory to segment and reconstruct the memory to form a “virtual path”, replaying the memory by associating the reward information. We conducted a series of navigation experiments in a simple environment called a Morris water maze (MWM) and in a complex environment, and we compared our model with a reinforcement learning model and other brain-inspired models. The experimental results show that under the same conditions, our model has a higher rate of environmental exploration and more stable signal transmission, and the average reward obtained under stable conditions was 14.12% higher than RL with random-experience replay. Our model also shows good performance in complex maze environments where signals are easily attenuated. Moreover, the performance of our model at bifurcations is consistent with neurophysiological studies.

Tonic excitation of nucleus reuniens decreases prefrontal-hippocampal coordination during slow-wave states

The nucleus reuniens of the thalamus (RE) is an important node between the medial prefrontal cortex (mPFC) and the hippocampus (HPC). Previously, we have shown that its mode of activity and its influence in mPFC-HPC communication is dependent upon brain state. During slow-wave states, RE units are closely and rhythmically coupled to the ongoing mPFC-slow oscillation (SO), while during activated (theta) states, RE neurons fire in an arrhythmic and tonically active manner. Inactivating the RE selectively impoverishes coordination of the SO between mPFC and HPC and interestingly, both mPFC and RE stimulation during the SO cause larger responses in the HPC than during theta. It is unclear if the activity patterns within the RE across states may play a role in both phenomena. Here, we optogenetically excited RE neurons in a tonic fashion to assess the impact on mPFC-HPC coupling. This stimulation decreased the influence of mPFC stimulation in the HPC during SO states, in a manner similar to what is observed across state changes into theta. Importantly, this type of stimulation had no effect on evoked responses during theta. Perhaps more interestingly, tonic optogenetic excitation of the RE also decreased mPFC-HPC SO coherence. Thus, it may not be the integrity of the RE per se that is responsible for efficient communication between mPFC and HPC, but rather the particular state in which RE neurons find themselves. Our results have direct implications for how distant brain regions can communicate most effectively, an issue that is ultimately important for activity-dependent processes occurring during slow-wave sleep-dependent memory consolidation.

Lower functional hippocampal connectivity in healthy adults is jointly associated with higher levels of leptin and insulin resistance

BACKGROUND

Metabolic dysregulation is currently considered a major risk factor for hippocampal pathology. The aim of the present study was to characterize the influence of key metabolic drivers on functional connectivity of the hippocampus in healthy adults.

METHODS

Insulin resistance was directly quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test and fasting levels of insulin, glucose, leptin, and cortisol, and measurements of body mass index and waist circumference were obtained in a sample of healthy cognitively intact adults (n = 104). Resting-state neuroimaging data were also acquired for the quantification of hippocampal functional cohesiveness and integration with the major resting-state networks (RSNs). Data-driven analysis using unsupervised machine learning (k-means clustering) was then employed to identify clusters of individuals based on their metabolic and functional connectivity profiles.

RESULTS

K-means clustering identified two clusters of increasing metabolic deviance evidenced by cluster differences in the plasma levels of leptin (40.36 (29.97) vs. 27.59 (25.58) μg/L) and the degree of insulin resistance (SSPG concentration: 161.63 (65.27) vs. 125.72 (66.81) mg/dL). Individuals in the cluster with higher metabolic deviance showed lower functional cohesiveness within each hippocampus and lower integration of posterior and anterior components of the left and right hippocampus with the major RSNs. The two clusters did not differ in general intellectual ability or episodic memory.

CONCLUSIONS

We identified two clusters of individuals differentiated by abnormalities in insulin resistance, leptin levels, and hippocampal connectivity, with one of the clusters showing greater deviance. These findings support the link between metabolic dysregulation and hippocampal function even in nonclinical samples.

Hippocampal volume reduction is associated with direct measure of insulin resistance in adults

Hippocampal integrity is highly susceptible to metabolic dysfunction, yet its mechanisms are not well defined. We studied 126 healthy individuals aged 23-61 years. Insulin resistance (IR) was quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test. Body mass index (BMI), adiposity, fasting insulin, glucose, leptin as well as structural neuroimaing with automatic hippocampal subfield segmentation were performed. Data analysis using unsupervised machine learning (k-means clustering) identified two subgroups reflecting a pattern of more pronounced hippocampal volume reduction being concurrently associated with greater adiposity and insulin resistance; the hippocampal volume reductions were uniform across subfields. Individuals in the most deviant subgroup were predominantly women (79 versus 42 %) with higher BMI [27.9 (2.5) versus 30.5 (4.6) kg/m²], IR (SSPG concentration, [156 (61) versus 123 (70) mg/dL] and leptinemia [21.7 (17.0) versus 44.5 (30.4) μg/L]. The use of person-based modeling in healthy individuals suggests that adiposity, insulin resistance and compromised structural hippocampal integrity behave as a composite phenotype; female sex emerged as risk factor for this phenotype.

Differential prioritization of intramaze cue and boundary information during spatial navigation across the human lifespan

Spatial learning can be based on intramaze cues and environmental boundaries. These processes are predominantly subserved by striatal- and hippocampal-dependent circuitries, respectively. Maturation and aging processes in these brain regions may affect lifespan differences in their contributions to spatial learning. We independently manipulated an intramaze cue or the environment's boundary in a navigation task in 27 younger children (6-8 years), 30 older children (10-13 years), 29 adolescents (15-17 years), 29 younger adults (20-35 years) and 26 older adults (65-80 years) to investigate lifespan age differences in the relative prioritization of either information. Whereas learning based on an intramaze cue showed earlier maturation during the progression from younger to later childhood and remained relatively stable across adulthood, maturation of boundary-based learning was more protracted towards peri-adolescence and showed strong aging-related decline. Furthermore, individual differences in prioritizing intramaze cue- over computationally more demanding boundary-based learning was positively associated with cognitive processing fluctuations and this association was partially mediated by spatial working memory capacity during adult, but not during child development. This evidence reveals different age gradients of two modes of spatial learning across the lifespan, which seem further influenced by individual differences in cognitive processing fluctuations and working memory, particularly during aging.

The Versatile Wayfinder: Prefrontal Contributions to Spatial Navigation

The prefrontal cortex (PFC) supports decision-making, goal tracking, and planning. Spatial navigation is a behavior that taxes these cognitive processes, yet the role of the PFC in models of navigation has been largely overlooked. In humans, activity in dorsolateral PFC (dlPFC) and ventrolateral PFC (vlPFC) during detours, reveal a role in inhibition and replanning. Dorsal anterior cingulate cortex (dACC) is implicated in planning and spontaneous internally-generated changes of route. Orbitofrontal cortex (OFC) integrates representations of the environment with the value of actions, providing a 'map' of possible decisions. In rodents, medial frontal areas interact with hippocampus during spatial decisions and switching between navigation strategies. In reviewing these advances, we provide a framework for how different prefrontal regions may contribute to different stages of navigation.

Basal Forebrain Atrophy Is Associated With Allocentric Navigation Deficits in Subjective Cognitive Decline

Individuals with subjective cognitive decline (SCD) are at higher risk of incipient Alzheimer's disease (AD). Spatial navigation (SN) impairments in AD dementia and mild cognitive impairment patients have been well-documented; however, studies investigating SN deficits in SCD subjects are still lacking. This study aimed to explore whether basal forebrain (BF) and entorhinal cortex (EC) atrophy contribute to spatial disorientation in the SCD stage. In total, 31 SCD subjects and 24 normal controls were enrolled and administered cognitive scales, a 2-dimensional computerized SN test, and structural magnetic resonance imaging (MRI) scanning. We computed the differences in navigation distance errors and volumes of BF subfields, EC, and hippocampus between the SCD and control groups. The correlations between MRI volumetry and navigation distance errors were also calculated. Compared with the controls, the SCD subjects performed worse in both egocentric and allocentric navigation. The SCD group showed volume reductions in the whole BF (p < 0.05, uncorrected) and the Ch4p subfield (p < 0.05, Bonferroni corrected), but comparable EC and hippocampal volumes with the controls. In the SCD cohort, the allocentric errors were negatively correlated with total BF (r = −0.625, p < 0.001), Ch4p (r = −0.625, p < 0.001), total EC (r = −0.423, p = 0.031), and left EC volumes (r = −0.442, p = 0.024), adjusting for age, gender, years of education, total intracranial volume, and hippocampal volume. This study demonstrates that SN deficits and BF atrophy may be promising indicators for the early detection of incipient AD patients. The reduced BF volume, especially in the Ch4p subfield, may serve as a structural basis for allocentric disorientation in SCD subjects independent of hippocampal atrophy. Our findings may have further implications for the preclinical diagnosis and intervention for potential AD patients.

Ego- and allo-network disconnection underlying spatial disorientation in subjective cognitive decline

Patients with Alzheimer's disease (AD) related dementia and mild cognitive impairment experience difficulties with spatial navigation (SN). However, SN has rarely been investigated in individuals with subjective cognitive decline (SCD), a preclinical stage with elevated progression rate to symptomatic AD. In this study, 30 SCD subjects and 30 controls underwent cognitive scale (CS) evaluation, a 2D computerized SN test, and resting-state functional magnetic resonance imaging scanning. Two SN brain networks (ego-network and allo-network), each with 10 selected spherical regions, were defined. We calculated the average network functional connectivity (FC) and region-to-region FC within the two networks and evaluated correlations with SN performance. Compared with the controls, the SCD group performed worse in the SN test and showed decreased FC between the right retrosplenial and right prefrontal cortices in the ego-network, and between the right retrosplenial cortex and right hippocampus in the allo-network. The logistic regression model based on SN and FC measures revealed a high area under the curve of .880 in differentiating SCD individuals from controls. These results suggest that SN network disconnection contributes to spatial deficits in SCD, and SN and FC measures could benefit the preclinical detection of subjects with incipient AD dementia.

Differential Brain Activity in Regions Linked to Visuospatial Processing During Landmark-Based Navigation in Young and Healthy Older Adults

Older adults have difficulties in navigating unfamiliar environments and updating their wayfinding behavior when faced with blocked routes. This decline in navigational capabilities has traditionally been ascribed to memory impairments and dysexecutive function, whereas the impact of visual aging has often been overlooked. The ability to perceive visuospatial information such as salient landmarks is essential to navigating efficiently. To date, the functional and neurobiological factors underpinning landmark processing in aging remain insufficiently characterized. To address this issue, functional magnetic resonance imaging (fMRI) was used to investigate the brain activity associated with landmark-based navigation in young and healthy older participants. The performances of 25 young adults (μ = 25.4 years, σ = 2.7; seven females) and 17 older adults (μ = 73.0 years, σ = 3.9; 10 females) were assessed in a virtual-navigation task in which they had to orient using salient landmarks. The underlying whole-brain patterns of activity as well as the functional roles of specific cerebral regions involved in landmark processing, namely the parahippocampal place area (PPA), the occipital place area (OPA), and the retrosplenial cortex (RSC), were analyzed. Older adults' navigational abilities were overall diminished compared to young adults. Also, the two age groups relied on distinct navigational strategies to solve the task. Better performances during landmark-based navigation were associated with increased neural activity in an extended neural network comprising several cortical and cerebellar regions. Direct comparisons between age groups revealed that young participants had greater anterior temporal activity. Also, only young adults showed significant activity in occipital areas corresponding to the cortical projection of the central visual field during landmark-based navigation. The region-of-interest analysis revealed an increased OPA activation in older adult participants during the landmark condition. There were no significant between-group differences in PPA and RSC activations. These preliminary results hint at the possibility that aging diminishes fine-grained information processing in occipital and temporal regions, thus hindering the capacity to use landmarks adequately for navigation. Keeping sight of its exploratory nature, this work helps towards a better comprehension of the neural dynamics subtending landmark-based navigation and it provides new insights on the impact of age-related visuospatial processing differences on navigation capabilities.

The Role of Hp-NCL Network in Goal-Directed Routing Information Encoding of Bird: A Review

Goal-directed navigation is a crucial behavior for the survival of animals, especially for the birds having extraordinary spatial navigation ability. In the studies of the neural mechanism of the goal-directed behavior, especially involving the information encoding mechanism of the route, the hippocampus (Hp) and nidopallium caudalle (NCL) of the avian brain are the famous regions that play important roles. Therefore, they have been widely concerned and a series of studies surrounding them have increased our understandings of the navigation mechanism of birds in recent years. In this paper, we focus on the studies of the information encoding mechanism of the route in the avian goal-directed behavior. We first summarize and introduce the related studies on the role of the Hp and NCL for goal-directed behavior comprehensively. Furthermore, we review the related cooperative interaction studies about the Hp-NCL local network and other relevant brain regions supporting the goal-directed routing information encoding. Finally, we summarize the current situation and prospect the existing important questions in this field. We hope this paper can spark fresh thinking for the following research on routing information encoding mechanism of birds.

The role of the fornix in human navigational learning

Experiments on rodents have demonstrated that transecting the white matter fibre pathway linking the hippocampus with an array of cortical and subcortical structures - the fornix - impairs flexible navigational learning in the Morris Water Maze (MWM), as well as similar spatial learning tasks. While diffusion magnetic resonance imaging (dMRI) studies in humans have linked inter-individual differences in fornix microstructure to episodic memory abilities, its role in human spatial learning is currently unknown. We used high-angular resolution diffusion MRI combined with constrained spherical deconvolution-based tractography, to ask whether inter-individual differences in fornix microstructure in healthy young adults would be associated with spatial learning in a virtual reality navigation task. To efficiently capture individual learning across trials, we adopted a novel curve fitting approach to estimate a single index of learning rate. We found a statistically significant correlation between learning rate and the microstructure (mean diffusivity) of the fornix, but not that of a comparison tract linking occipital and anterior temporal cortices (the inferior longitudinal fasciculus, ILF). Further, this correlation remained significant when controlling for both hippocampal volume and participant gender. These findings extend previous animal studies by demonstrating the functional relevance of the fornix for human spatial learning in a virtual reality environment, and highlight the importance of a distributed neuroanatomical network, underpinned by key white matter pathways, such as the fornix, in complex spatial behaviour.

Age-Related Differences in Functional and Structural Connectivity in the Spatial Navigation Brain Network

Spatial navigation involves multiple cognitive processes including multisensory integration, visuospatial coding, memory, and decision-making. These functions are mediated by the interplay of cerebral structures that can be broadly separated into a posterior network (subserving visual and spatial processing) and an anterior network (dedicated to memory and navigation planning). Within these networks, areas such as the hippocampus (HC) are known to be affected by aging and to be associated with cognitive decline and navigation impairments. However, age-related changes in brain connectivity within the spatial navigation network remain to be investigated. For this purpose, we performed a neuroimaging study combining functional and structural connectivity analyses between cerebral regions involved in spatial navigation. Nineteen young (μ = 27 years, σ = 4.3; 10 F) and 22 older (μ = 73 years, σ = 4.1; 10 F) participants were examined in this study. Our analyses focused on the parahippocampal place area (PPA), the retrosplenial cortex (RSC), the occipital place area (OPA), and the projections into the visual cortex of central and peripheral visual fields, delineated from independent functional localizers. In addition, we segmented the HC and the medial prefrontal cortex (mPFC) from anatomical images. Our results show an age-related decrease in functional connectivity between low-visual areas and the HC, associated with an increase in functional connectivity between OPA and PPA in older participants compared to young subjects. Concerning the structural connectivity, we found age-related differences in white matter integrity within the navigation brain network, with the exception of the OPA. The OPA is known to be involved in egocentric navigation, as opposed to allocentric strategies which are more related to the hippocampal region. The increase in functional connectivity between the OPA and PPA may thus reflect a compensatory mechanism for the age-related alterations around the HC, favoring the use of the preserved structural network mediating egocentric navigation. Overall, these findings on age-related differences of functional and structural connectivity may help to elucidate the cerebral bases of spatial navigation deficits in healthy and pathological aging.

Hexagonal Grid Fields Optimally Encode Transitions in Spatiotemporal Sequences

Grid cells of the rodent entorhinal cortex are essential for spatial navigation. Although their function is commonly believed to be either path integration or localization, the origin or purpose of their hexagonal firing fields remains disputed. Here they are proposed to arise as an optimal encoding of transitions in sequences. First, storage requirements for transitions in general episodic sequences are examined using propositional logic and graph theory. Subsequently, transitions in complete metric spaces are considered under the assumption of an ideal sampling of an input space. It is shown that memory capacity of neurons that have to encode multiple feasible spatial transitions is maximized by a hexagonal pattern. Grid cells are proposed to encode spatial transitions in spatiotemporal sequences, with the entorhinal-hippocampal loop forming a multitransition system.

Sharp-wave ripples as a signature of hippocampal-prefrontal reactivation for memory during sleep and waking states

It is widely believed that memories that are encoded and retrieved during waking behavior are consolidated during sleep. Recent studies on the interactions between the hippocampus and the prefrontal cortex have greatly advanced our understanding of the physiological bases of these memory processes. Although hippocampal-prefrontal network activity differs in many aspects during waking and sleep states, here we review evidence that hippocampal sharp-wave ripples (SWRs) emerge as a common neurophysiological pattern in both states, facilitating communication between these two regions via coordinated reactivation of stored memory information. We further consider whether sleep and awake reactivation mediate similar memory processes or have different mnemonic functions, and the mechanistic role of this cross-regional dialogue in learning and memory. Finally, we provide an integrated view of how these two forms of reactivation might work together to support spatial learning and memory.