Self-localization and the entorhinal-hippocampal system

Exploring the Remediation of Behavioral Disturbances of Spatial Cognition in Community-Dwelling Senior Citizens with Mild Cognitive Impairment via Innovative Technological Apparatus (BDSC-MCI Project): Protocol for a Prospective, Multi-Center Observational Study

Spatial navigation (SN) has been reported to be one of the first cognitive domains to be affected in Alzheimer's disease (AD), which occurs as a result of progressive neuropathology involving specific brain areas. Moreover, the epsilon 4 isoform of apolipoprotein-E (APOE-ε4) has been associated with both sporadic and familial late-onset AD, and patients with mild cognitive impairment (MCI) due to AD are more likely to progressively deteriorate. Spatial navigation performance will be examined on a sample of 76 community-dwelling senior citizens (25 healthy controls; 25 individuals with subjective cognitive decline (SCD); and 26 patients with MCI due to AD) via a virtual computer-based task (i.e., the AppleGame) and a naturalistic task (i.e., the Detour Navigation Test-modified version) for which a wearable device with sensors will be used for recording gait data and revealing physiological parameters that may be associated with spatial disorientation. We expect that patients with MCI due to AD and APOE-ε4 carriers will show altered SN performances compared to individuals with SCD and healthy controls in the experimental tasks, and that VR testing may predict ecological performance. Impaired SN performances in people at increased risk of developing AD may inform future cognitive rehabilitation protocols for counteracting spatial disorientation that may occur during elders' traveling to unfamiliar locations. The research protocol has been approved by the Ethics Committee of the Istituto Auxologico Italiano. Findings will be published in peer-reviewed medical journals and discussed in national and international congresses.

A Safety Study of the Effects of 2-Dimensional Shear Wave Elastography on Synaptic Morphologic Characteristics and Function in the Hippocampus of Neonatal Mice

OBJECTIVES

The aim of this study was to determine the effects of 2-dimensional (2D) shear wave elastography (SWE) on synaptic morphologic characteristics and function in the neonatal mouse hippocampus and whether it affects the capacity for learning and memory later in life.

METHODS

We divided neonatal mice into a control group and a 2D SWE group scanned for 10, 20, or 30 minutes. Hippocampal morphologic characteristics were assessed by hematoxylin-eosin and Nissl staining. Ultrastructures of hippocampal neurons were visualized by electron microscopy. Protein and messenger RNA expression levels of synaptophysin, N-methyl-d-aspartate receptor 1 (NMDAR1), NMDAR2A, and NMDAR2B were quantified by a western blot and polymerase chain reaction, respectively. Learning and memory of adult mice were evaluated by the Morris water maze and the novel object recognition task.

RESULTS

Compared with the control group, the hippocampal morphologic characteristics of the experimental groups did not differ under light microscopy, and the synaptic structures assessed by electron microscopy appeared normal. Western blot and polymerase chain reaction results showed that expression of synaptophysin, NMDAR1, NMDAR2A, and NMDAR2B were downregulated after exposure to 2D SWE, but there were no statistical differences between the experimental groups. This downregulation disappeared within 24 hours. The results of the Morris water maze and novel object recognition suggested that the 2D SWE scanning on neonatal mice had no effect on learning and memory in adulthood.

CONCLUSIONS

This study demonstrated that when the mice were exposed to neonatal cranial ultrasound by 2D SWE lasting for longer than 10 minutes, the expression of genes involved in synaptic function was affected, but this effect lasted no longer than 24 hours and did not affect learning and memory in adulthood.

Have I Been Here? Sense of Location in People With Alzheimer's Disease

Background: When navigating in a particular space, a sense of being at a current location is of great help for the navigators in reaching their destination or getting back to the start. To accomplish this work, interwoven neural structures and neurons are called into play. This system is called the heading direction cell-place cell-grid cell circuit. Evidence from various neuroscience studies has revealed that the regions responsible for this circuit are damaged in the early stages of Alzheimer's disease (AD). This may explain why wayfinding difficulty is one of the most frequent symptoms in persons with AD. The aim of this study was to examine the sense of location (SoL) in persons with mild AD, persons with prodromal AD (prAD), and those who were cognitively unimpaired (CU). Methods: We invited people with mild AD, prAD, and CU to participate in this study. The venue of the core experiment to assess SoL was a 660-m path located on the university campus. The participants were instructed to take a walk on the path and press a device to indicate their arrival at each of the five carefully chosen targets. The linear deviations from the target site were compared among the groups. Results: A total of 20 AD, 28 prAD, and 29 CU persons completed the study. Their Mini-Mental State Examination scores were on average 20 (SD 3), 24 (SD 3), and 28 (SD 2). The groups were well differentiated regarding several measurements for cognitive ability and spatial navigation. As for the SoL, the hit rates of exact location with linear deviation of 16 m or less were 0.05, 0.54, and 0.86 for AD, prAD, and CU persons, respectively. The hit rates were well correlated with the presence of getting lost. Also, SoL differentiated well among CU, PrAD, and AD in terms of average linear deviation. Conclusions: Our employing linear deviation by utilizing a grid-cell function device as an assessment for SoL showed distinct features among the three groups. This model can be used to develop more delicate devices or instruments to detect, monitor, and aid spatial navigation in persons with prAD and AD.

Robustness Improvement of Visual Templates Matching Based on Frequency-Tuned Model in RatSLAM

This paper describes an improved brain-inspired simultaneous localization and mapping (RatSLAM) that extracts visual features from saliency maps using a frequency-tuned (FT) model. In the traditional RatSLAM algorithm, the visual template feature is organized as a one-dimensional vector whose values only depend on pixel intensity; therefore, this feature is susceptible to changes in illumination intensity. In contrast to this approach, which directly generates visual templates from raw RGB images, we propose an FT model that converts RGB images into saliency maps to obtain visual templates. The visual templates extracted from the saliency maps contain more of the feature information contained within the original images. Our experimental results demonstrate that the accuracy of loop closure detection was improved, as measured by the number of loop closures detected by our method compared with the traditional RatSLAM system. We additionally verified that the proposed FT model-based visual templates improve the robustness of familiar visual scene identification by RatSLAM.

Spatial planning with long visual range benefits escape from visual predators in complex naturalistic environments

It is uncontroversial that land animals have more elaborated cognitive abilities than their aquatic counterparts such as fish. Yet there is no apparent a-priori reason for this. A key cognitive faculty is planning. We show that in visually guided predator-prey interactions, planning provides a significant advantage, but only on land. During animal evolution, the water-to-land transition resulted in a massive increase in visual range. Simulations of behavior identify a specific type of terrestrial habitat, clustered open and closed areas (savanna-like), where the advantage of planning peaks. Our computational experiments demonstrate how this patchy terrestrial structure, in combination with enhanced visual range, can reveal and hide agents as a function of their movement and create a selective benefit for imagining, evaluating, and selecting among possible future scenarios-in short, for planning. The vertebrate invasion of land may have been an important step in their cognitive evolution.

Three brain states in the hippocampus and cortex

Contemporary brain research seeks to understand how cognition is reducible to neural activity. Crucially, much of this effort is guided by a scientific paradigm that views neural activity as essentially driven by external stimuli. In contrast, recent perspectives argue that this paradigm is by itself inadequate and that understanding patterns of activity intrinsic to the brain is needed to explain cognition. Yet, despite this critique, the stimulus-driven paradigm still dominates-possibly because a convincing alternative has not been clear. Here, we review a series of findings suggesting such an alternative. These findings indicate that neural activity in the hippocampus occurs in one of three brain states that have radically different anatomical, physiological, representational, and behavioral correlates, together implying different functional roles in cognition. This three-state framework also indicates that neural representations in the hippocampus follow a surprising pattern of organization at the timescale of ∼1 s or longer. Lastly, beyond the hippocampus, recent breakthroughs indicate three parallel states in the cortex, suggesting shared principles and brain-wide organization of intrinsic neural activity.

Transition Scale-Spaces: A Computational Theory for the Discretized Entorhinal Cortex

Although hippocampal grid cells are thought to be crucial for spatial navigation, their computational purpose remains disputed. Recently, they were proposed to represent spatial transitions and convey this knowledge downstream to place cells. However, a single scale of transitions is insufficient to plan long goal-directed sequences in behaviorally acceptable time.

Here, a scale-space data structure is suggested to optimally accelerate retrievals from transition systems, called transition scale-space (TSS). Remaining exclusively on an algorithmic level, the scale increment is proved to be ideally [Formula: see text] for biologically plausible receptive fields. It is then argued that temporal buffering is necessary to learn the scale-space online. Next, two modes for retrieval of sequences from the TSS are presented: top down and bottom up. The two modes are evaluated in symbolic simulations (i.e., without biologically plausible spiking neurons). Additionally, a TSS is used for short-cut discovery in a simulated Morris water maze. Finally, the results are discussed in depth with respect to biological plausibility, and several testable predictions are derived. Moreover, relations to other grid cell models, multiresolution path planning, and scale-space theory are highlighted. Summarized, reward-free transition encoding is shown here, in a theoretical model, to be compatible with the observed discretization along the dorso-ventral axis of the medial entorhinal cortex. Because the theoretical model generalizes beyond navigation, the TSS is suggested to be a general-purpose cortical data structure for fast retrieval of sequences and relational knowledge.

Source code for all simulations presented in this paper can be found at https://github.com/rochus/transitionscalespace .

Altered hypothalamic functional connectivity with autonomic circuits and the locus coeruleus in migraine

The hypothalamus has been implicated in migraine based on the manifestation of autonomic symptoms with the disease, as well as neuroimaging evidence of hypothalamic activation during attacks. Our objective was to determine functional connectivity (FC) changes between the hypothalamus and the rest of the brain in migraine patients vs. control subjects. This study uses fMRI (functional magnetic resonance imaging) to acquire resting state scans in 12 interictal migraine patients and 12 healthy matched controls. Hypothalamic connectivity seeds were anatomically defined based on high-resolution structural scans, and FC was assessed in the resting state scans. Migraine patients had increased hypothalamic FC with a number of brain regions involved in regulation of autonomic functions, including the locus coeruleus, caudate, parahippocampal gyrus, cerebellum, and the temporal pole. Stronger functional connections between the hypothalamus and brain areas that regulate sympathetic and parasympathetic functions may explain some of the hypothalamic-mediated autonomic symptoms that accompany or precede migraine attacks.

Bayesian integration of information in hippocampal place cells

Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We compare the predictions of our model with physiological data from rats. Our results suggest that useful predictions regarding the firing fields of place cells can be made based on a single underlying principle, Bayesian cue integration, and that such predictions are possible using a remarkably small number of model parameters.

Independence of landmark and self-motion-guided navigation: a different role for grid cells

Recent interest in the neural bases of spatial navigation stems from the discovery of neuronal populations with strong, specific spatial signals. The regular firing field arrays of medial entorhinal grid cells suggest that they may provide place cells with distance information extracted from the animal's self-motion, a notion we critically review by citing new contrary evidence. Next, we question the idea that grid cells provide a rigid distance metric. We also discuss evidence that normal navigation is possible using only landmarks, without self-motion signals. We then propose a model that supposes that information flow in the navigational system changes between light and dark conditions. We assume that the true map-like representation is hippocampal and argue that grid cells have a crucial navigational role only in the dark. In this view, their activity in the light is predominantly shaped by landmarks rather than self-motion information, and so follows place cell activity; in the dark, their activity is determined by self-motion cues and controls place cell activity. A corollary is that place cell activity in the light depends on non-grid cells in ventral medial entorhinal cortex. We conclude that analysing navigational system changes between landmark and no-landmark conditions will reveal key functional properties.

Integration of visual motion and locomotion in mouse visual cortex

Successful navigation through the world requires accurate estimation of one's own speed. To derive this estimate, animals integrate visual speed gauged from optic flow and run speed gauged from proprioceptive and locomotor systems. The primary visual cortex (V1) carries signals related to visual speed, and its responses are also affected by run speed. To study how V1 combines these signals during navigation, we recorded from mice that traversed a virtual environment. Nearly half of the V1 neurons were reliably driven by combinations of visual speed and run speed. These neurons performed a weighted sum of the two speeds. The weights were diverse across neurons, and typically positive. As a population, V1 neurons predicted a linear combination of visual and run speeds better than either visual or run speeds alone. These data indicate that V1 in the mouse participates in a multimodal processing system that integrates visual motion and locomotion during navigation.

Ageing effects on path integration and landmark navigation

Navigation abilities show marked decline in both normal ageing and dementia. Path integration may be particularly affected, as it is supported by the hippocampus and entorhinal cortex, both of which show severe degeneration with ageing. Age differences in path integration based on kinaesthetic and vestibular cues have been clearly demonstrated, but very little research has focused on visual path integration, based only on optic flow. Path integration is complemented by landmark navigation, which may also show age differences, but has not been well studied either. Here we present a study using several simple virtual navigation tasks to explore age differences in path integration both with and without landmark information. We report that, within a virtual environment that provided only optic flow information, older participants exhibited deficits in path integration in terms of distance reproduction, rotation reproduction, and triangle completion. We also report age differences in triangle completion within an environment that provided landmark information. In all tasks, we observed a more restricted range of responses in the older participants, which we discuss in terms of a leaky integrator model, as older participants showed greater leak than younger participants. Our findings begin to explain the mechanisms underlying age differences in path integration, and thus contribute to an understanding of the substantial decline in navigation abilities observed in ageing.

Grid cells, place cells, and geodesic generalization for spatial reinforcement learning

Reinforcement learning (RL) provides an influential characterization of the brain's mechanisms for learning to make advantageous choices. An important problem, though, is how complex tasks can be represented in a way that enables efficient learning. We consider this problem through the lens of spatial navigation, examining how two of the brain's location representations--hippocampal place cells and entorhinal grid cells--are adapted to serve as basis functions for approximating value over space for RL. Although much previous work has focused on these systems' roles in combining upstream sensory cues to track location, revisiting these representations with a focus on how they support this downstream decision function offers complementary insights into their characteristics. Rather than localization, the key problem in learning is generalization between past and present situations, which may not match perfectly. Accordingly, although neural populations collectively offer a precise representation of position, our simulations of navigational tasks verify the suggestion that RL gains efficiency from the more diffuse tuning of individual neurons, which allows learning about rewards to generalize over longer distances given fewer training experiences. However, work on generalization in RL suggests the underlying representation should respect the environment's layout. In particular, although it is often assumed that neurons track location in Euclidean coordinates (that a place cell's activity declines "as the crow flies" away from its peak), the relevant metric for value is geodesic: the distance along a path, around any obstacles. We formalize this intuition and present simulations showing how Euclidean, but not geodesic, representations can interfere with RL by generalizing inappropriately across barriers. Our proposal that place and grid responses should be modulated by geodesic distances suggests novel predictions about how obstacles should affect spatial firing fields, which provides a new viewpoint on data concerning both spatial codes.

Rapid effects of aggressive interactions on aromatase activity and oestradiol in discrete brain regions of wild male white-crowned sparrows

Testosterone is critical for the activation of aggressive behaviours. In many vertebrate species, circulating testosterone levels rapidly increase after aggressive encounters during the early or mid-breeding season. During the late breeding season, circulating testosterone concentrations did not change in wild male white-crowned sparrows after an aggressive encounter and, in these animals, changes in local neural metabolism of testosterone might be more important than changes in systemic testosterone levels. Local neural aromatisation of testosterone into 17β-oestradiol (E(2)) often mediates the actions of testosterone, and we hypothesised that, in the late breeding season, brain aromatase is rapidly modulated after aggressive interactions, leading to changes in local concentrations of E(2). In the present study, wild male white-crowned sparrows in the late breeding season were exposed to simulated territorial intrusion (STI) (song playback and live decoy) or control (CON) for 30 min. STI significantly increased aggressive behaviours. Using the Palkovits punch technique, 13 brain regions were collected. There was high aromatase activity in several nuclei, although enzymatic activity in the CON and STI groups did not differ in any region. E(2) concentrations were much higher in the brain than the plasma. STI did not affect circulating levels of E(2) but rapidly reduced E(2) concentrations in the hippocampus, ventromedial nucleus of the hypothalamus and bed nucleus of the stria terminalis. Unexpectedly, there were no correlations between aromatase activity and E(2) concentrations in the brain, nor were aromatase activity or brain E(2) correlated with aggressive behaviour or plasma hormone levels. This is one of the first studies to measure E(2) in microdissected brain regions, and the first study to do so in free-ranging animals. These data demonstrate that social interactions have rapid effects on local E(2) concentrations in specific brain regions.

Modality-independent coding of spatial layout in the human brain

In many nonhuman species, neural computations of navigational information such as position and orientation are not tied to a specific sensory modality [1, 2]. Rather, spatial signals are integrated from multiple input sources, likely leading to abstract representations of space. In contrast, the potential for abstract spatial representations in humans is not known, because most neuroscientific experiments on human navigation have focused exclusively on visual cues. Here, we tested the modality independence hypothesis with two functional magnetic resonance imaging (fMRI) experiments that characterized computations in regions implicated in processing spatial layout [3]. According to the hypothesis, such regions should be recruited for spatial computation of 3D geometric configuration, independent of a specific sensory modality. In support of this view, sighted participants showed strong activation of the parahippocampal place area (PPA) and the retrosplenial cortex (RSC) for visual and haptic exploration of information-matched scenes but not objects. Functional connectivity analyses suggested that these effects were not related to visual recoding, which was further supported by a similar preference for haptic scenes found with blind participants. Taken together, these findings establish the PPA/RSC network as critical in modality-independent spatial computations and provide important evidence for a theory of high-level abstract spatial information processing in the human brain.

Painful heat reveals hyperexcitability of the temporal pole in interictal and ictal migraine States

During migraine attacks, alterations in sensation accompanying headache may manifest as allodynia and enhanced sensitivity to light, sound, and odors. Our objective was to identify physiological changes in cortical regions in migraine patients using painful heat and functional magnetic resonance imaging (fMRI) and the structural basis for such changes using diffusion tensor imaging (DTI). In 11 interictal patients, painful heat threshold + 1°C was applied unilaterally to the forehead during fMRI scanning. Significantly greater activation was identified in the medial temporal lobe in patients relative to healthy subjects, specifically in the anterior temporal pole (TP). In patients, TP showed significantly increased functional connectivity in several brain regions relative to controls, suggesting that TP hyperexcitability may contribute to functional abnormalities in migraine. In 9 healthy subjects, DTI identified white matter connectivity between TP and pulvinar nucleus, which has been related to migraine. In 8 patients, fMRI activation in TP with painful heat was exacerbated during migraine, suggesting that repeated migraines may sensitize TP. This article investigates a nonclassical role of TP in migraineurs. Observed temporal lobe abnormalities may provide a basis for many of the perceptual changes in migraineurs and may serve as a potential interictal biomarker for drug efficacy.

Persistent posterior and transient anterior medial temporal lobe activity during navigation

A functional segregation along the posterior-anterior axis of the medial temporal lobe (MTL) has been suggested. In brief, it is thought that the posterior hippocampus represents environmental detail and/or encodes space, whereas the anterior part represents the environment more as a whole and/or subserves behavior. Different phases of navigation should thus recruit different structures within the MTL. Based on animal studies and neuroimaging data from humans, the initial phase of navigation, i.e., self-localization, target localization and path planning, should depend on the anterior MTL independent of upcoming navigational demands, whereas posterior MTL should be active throughout navigation. We tested this prediction using fMRI with navigation in a learned large-scale virtual office landscape with numerous complex landmarks under different navigational conditions. The initial navigational phase specifically engaged the anterior MTL. Increased activity was found bilaterally in the rostral and caudal entorhinal cortex. This is, to our knowledge, the first report of entorhinal activity in virtual navigation detected in a direct comparison. Also bilateral anterior hippocampus and anterior parahippocampal cortex were significantly more active during the initial phase. Activity lasting throughout the navigational period was found in the right posterior hippocampus and parahippocampal cortex. Hippocampal activity for the entire navigation period was only detected when the virtual environment remained unaltered. Navigational success was positively correlated with activity in the anterior right hippocampus for the initial phase, and more posteriorly in the hippocampus for the whole navigation period. Plots of the BOLD signal time course demonstrated that activity in the anterior hippocampus was transient whereas activity in the posterior hippocampus peaked regularly throughout the entire navigation period. These results support a functional segregation within the MTL with regard to navigational phases. The anterior MTL appears to complete associations related to the environment at large and provide a behavioral plan for navigation, whereas the posterior part keeps track of current location.

Neural structures and mechanisms involved in scene recognition: a review and interpretation

Since the discovery in 1996 that a region within caudal parahippocampal cortex subserves learning and recall of topographical information, numerous studies aimed at elucidating the structures and pathways involved in scene recognition have been published. Neuroimaging studies, in particular, have revealed the locations and identities of some of the principal cortical structures that mediate these faculties. In the present study the detailed organization of the system is examined, based on a meta-analysis of neuroimaging studies of scene processing in human subjects, combined with reviews of the results of lesions on this type of processing, single neuron studies, and available hodological data in non-human primates. A cortical hierarchy of structures that mediate scene recognition is established based on these data, and an attempt is made to determine the function of the individual components of the system.

Finding the way with a noisy brain

Successful navigation is fundamental to the survival of nearly every animal on earth, and achieved by nervous systems of vastly different sizes and characteristics. Yet surprisingly little is known of the detailed neural circuitry from any species which can accurately represent space for navigation. Path integration is one of the oldest and most ubiquitous navigation strategies in the animal kingdom. Despite a plethora of computational models, from equational to neural network form, there is currently no consensus, even in principle, of how this important phenomenon occurs neurally. Recently, all path integration models were examined according to a novel, unifying classification system. Here we combine this theoretical framework with recent insights from directed walk theory, and develop an intuitive yet mathematically rigorous proof that only one class of neural representation of space can tolerate noise during path integration. This result suggests many existing models of path integration are not biologically plausible due to their intolerance to noise. This surprising result imposes significant computational limitations on the neurobiological spatial representation of all successfully navigating animals, irrespective of species. Indeed, noise-tolerance may be an important functional constraint on the evolution of neuroarchitectural plans in the animal kingdom.

The ability to navigate allows animals to vastly increase the action space for finding resources, mates, and to avoid predators. The benefits are many and it is commonly believed that modern brain functions have emerged from ancestral forms evolved for effective navigation. Since the time of Charles Darwin, it has been recognized that path integration is a navigation strategy innate to many species. Path integration involves adding the stepwise displacements during a circuitous journey to compute a net homeward direction. Over the past century, this phenomenon has been described for birds to mammals to arthropods, and a long list of mathematical, algorithmic, and neural network models have been proposed to explain the necessary computations. This work shows how the different types of models behave in the presence of noise. It turns out that only one class of models can function properly in the presence of noise. Since noise appears to be present at all levels of brain physiology, we arrive at the surprising conclusion that the general computational principles for path integration must be the same across all species. Two subtypes of path integration models share the same critical computational principles, and are compared to known neuroanatomy and physiology.

Theoretical accounts of spatial learning: a neurobiological view (commentary on Pearce, 2009)

Theories of learning have historically taken, as their starting point, the assumption that learning processes have universal applicability. This position has been argued on grounds of parsimony, but has received two significant challenges: first, from the observation that some kinds of learning, such as spatial learning, seem to obey different rules from others, and second, that some kinds of learning take place in processing modules that are separate from each other. These challenges arose in the behavioural literature but have since received considerable support from neurobiological studies, particularly single neuron studies of spatial learning, confirming that there are indeed separable (albeit highly intercommunicating) processing modules in the brain, which may not always interact (within or between themselves) according to classic associative principles. On the basis of these neurobiological data, reviewed here, it is argued that rather than assuming universality of associative rules, it is more parsimonious to assume sets of locally operating rules, each specialized for a particular domain. By this view, although almost all learning is associative in one way or another, the behavioural-level characterization of the rules governing learning may vary depending on which neural modules are involved in a given behaviour. Neurobiological studies, in tandem with behavioural studies, can help reveal the nature of these modules and the local rules by which they interact.