Spatial goal coding in the hippocampal formation

Tentacle Microelectrode Arrays Uncover Soft Boundary Neurons in Hippocampal CA1

Hippocampal CA1 neurons show intense firing at specific spatial locations, modulated by isolated landmarks. However, the impact of real-world scene transitions on neuronal activity remains unclear. Moreover, long-term neural recording during movement challenges device stability. Conventional rigid-based electrodes cause inflammatory responses, restricting recording durations. Inspired by the jellyfish tentacles, the multi-conductive layer ultra-flexible microelectrode arrays (MEAs) are developed. The tentacle MEAs ensure stable recordings during movement, thereby enabling the discovery of soft boundary neurons. The soft boundary neurons demonstrate high-frequency firing that aligns with the boundaries of scene transitions. Furthermore, the localization ability of soft boundary neurons improves with more scene transition boundaries, and their activity decreases when these boundaries are removed. The innovation of ultra-flexible, high-biocompatible tentacle MEAs improves the understanding of neural encoding in spatial cognition. They offer the potential for long-term in vivo recording of neural information, facilitating breakthroughs in the understanding and application of brain spatial navigation mehanisms.

Reactivation strength during cued recall is modulated by graph distance within cognitive maps

Declarative memory retrieval is thought to involve reinstatement of neuronal activity patterns elicited and encoded during a prior learning episode. Furthermore, it is suggested that two mechanisms operate during reinstatement, dependent on task demands: individual memory items can be reactivated simultaneously as a clustered occurrence or, alternatively, replayed sequentially as temporally separate instances. In the current study, participants learned associations between images that were embedded in a directed graph network and retained this information over a brief 8 min consolidation period. During a subsequent cued recall session, participants retrieved the learned information while undergoing magnetoencephalographic recording. Using a trained stimulus decoder, we found evidence for clustered reactivation of learned material. Reactivation strength of individual items during clustered reactivation decreased as a function of increasing graph distance, an ordering present solely for successful retrieval but not for retrieval failure. In line with previous research, we found evidence that sequential replay was dependent on retrieval performance and was most evident in low performers. The results provide evidence for distinct performance-dependent retrieval mechanisms, with graded clustered reactivation emerging as a plausible mechanism to search within abstract cognitive maps.

A hippocampus-accumbens code guides goal-directed appetitive behavior

The dorsal hippocampus (dHPC) is a key brain region for the expression of spatial memories, such as navigating towards a learned reward location. The nucleus accumbens (NAc) is a prominent projection target of dHPC and implicated in value-based action selection. Yet, the contents of the dHPC→NAc information stream and their acute role in behavior remain largely unknown. Here, we found that optogenetic stimulation of the dHPC→NAc pathway while mice navigated towards a learned reward location was both necessary and sufficient for spatial memory-related appetitive behaviors. To understand the task-relevant coding properties of individual NAc-projecting hippocampal neurons (dHPC→NAc), we used in vivo dual-color two-photon imaging. In contrast to other dHPC neurons, the dHPC→NAc subpopulation contained more place cells, with enriched spatial tuning properties. This subpopulation also showed enhanced coding of non-spatial task-relevant behaviors such as deceleration and appetitive licking. A generalized linear model revealed enhanced conjunctive coding in dHPC→NAc neurons which improved the identification of the reward zone. We propose that dHPC routes specific reward-related spatial and behavioral state information to guide NAc action selection.

Neural representation in active inference: Using generative models to interact with-and understand-the lived world

This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action-perception cycles to those that underwrite planning and imagination; namely, from explicit models that entail variables for predicting concurrent sensations, like objects, faces, or people-to action-oriented models that predict action outcomes. It then elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models for understanding an agent's cognitive capabilities in relation to its ecological niche. The paper concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities-and the gradual transition from pragmatic to detached neural representations. The analysis on offer foregrounds the diverse roles that generative models play in cognitive processes and the evolution of neural representation.

A different perspective on avian hippocampus function: Visual-spatial perception

The behavioral and neural mechanisms that support spatial cognition have been an enduring interest of psychologists, and much of that enduring interest is attributable to the groundbreaking research of Ken Cheng. One manifestation of this interest, inspired by the idea of studying spatial cognition under natural field conditions, has been research carried out to understand the role of the avian hippocampal formation (HF) in supporting homing pigeon navigation. Emerging from that research has been the conclusion that the role of HF in homing pigeon navigation aligns well with the canonical narrative of a hippocampus important for spatial memory and the implementation of such memories to support navigation. However, recently an accumulation of disparate observations has prompted a rethinking of the avian HF as a structure also important in shaping visual-spatial perception or attention antecedent to any memory processing. In this perspective paper, we summarize field observations contrasting the behavior of intact and HF-lesioned homing pigeons from several studies, based primarily on GPS-recorded flight paths, that support a recharacterization of HF's functional profile to include visual-spatial perception. Although admittedly still speculative, we hope the offered perspective will motivate controlled, experimental-laboratory studies to further test the hypothesis of a HF important for visual-perceptual integration, or scene construction, of landscape elements in support of navigation.

Lateral entorhinal cortex subpopulations represent experiential epochs surrounding reward

During goal-directed navigation, 'what' information, describing the experiences occurring in periods surrounding a reward, can be combined with spatial 'where' information to guide behavior and form episodic memories. This integrative process likely occurs in the hippocampus, which receives spatial information from the medial entorhinal cortex; however, the source of the 'what' information is largely unknown. Here, we show that mouse lateral entorhinal cortex (LEC) represents key experiential epochs during reward-based navigation tasks. We discover separate populations of neurons that signal goal approach and goal departure and a third population signaling reward consumption. When reward location is moved, these populations immediately shift their respective representations of each experiential epoch relative to reward, while optogenetic inhibition of LEC disrupts learning the new reward location. Therefore, the LEC contains a stable code of experiential epochs surrounding and including reward consumption, providing reward-centric information to contextualize the spatial information carried by the medial entorhinal cortex.

Endotaxis: A neuromorphic algorithm for mapping, goal-learning, navigation, and patrolling

An animal entering a new environment typically faces three challenges: explore the space for resources, memorize their locations, and navigate towards those targets as needed. Here we propose a neural algorithm that can solve all these problems and operates reliably in diverse and complex environments. At its core, the mechanism makes use of a behavioral module common to all motile animals, namely the ability to follow an odor to its source. We show how the brain can learn to generate internal "virtual odors" that guide the animal to any location of interest. This endotaxis algorithm can be implemented with a simple 3-layer neural circuit using only biologically realistic structures and learning rules. Several neural components of this scheme are found in brains from insects to humans. Nature may have evolved a general mechanism for search and navigation on the ancient backbone of chemotaxis.

Grid-like entorhinal representation of an abstract value space during prospective decision making

How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming a trajectory through an abstract two-dimensional value space. During this task, the entorhinal cortex exhibited a grid-like representation with an orientation aligned to the axis through the value space most informative for choices. A network of brain regions, including ventromedial prefrontal cortex, tracked the prospective value difference between options. These findings suggest that the entorhinal grid system supports the prediction of future values by representing a cognitive map, which might be used to generate lower-dimensional value signals to guide prospective decision making.

Hippocampal sequences span experience relative to rewards

Hippocampal place cells fire in sequences that span spatial environments and non-spatial modalities, suggesting that hippocampal activity can anchor to the most behaviorally salient aspects of experience. As reward is a highly salient event, we hypothesized that sequences of hippocampal activity can anchor to rewards. To test this, we performed two-photon imaging of hippocampal CA1 neurons as mice navigated virtual environments with changing hidden reward locations. When the reward moved, the firing fields of a subpopulation of cells moved to the same relative position with respect to reward, constructing a sequence of reward-relative cells that spanned the entire task structure. The density of these reward-relative sequences increased with task experience as additional neurons were recruited to the reward-relative population. Conversely, a largely separate subpopulation maintained a spatially-based place code. These findings thus reveal separate hippocampal ensembles can flexibly encode multiple behaviorally salient reference frames, reflecting the structure of the experience.

Grid codes underlie multiple cognitive maps in the human brain

Grid cells fire at multiple positions that organize the vertices of equilateral triangles tiling a 2D space and are well studied in rodents. The last decade witnessed rapid progress in two other research lines on grid codes-empirical studies on distributed human grid-like representations in physical and multiple non-physical spaces, and cognitive computational models addressing the function of grid cells based on principles of efficient and predictive coding. Here, we review the progress in these fields and integrate these lines into a systematic organization. We also discuss the coordinate mechanisms of grid codes in the human entorhinal cortex and medial prefrontal cortex and their role in neurological and psychiatric diseases.

Organization of pRF size along the AP axis of the hippocampus and adjacent medial temporal cortex is related to specialization for scenes versus faces

The hippocampus is largely recognized for its integral contributions to memory processing. By contrast, its role in perceptual processing remains less clear. Hippocampal properties vary along the anterior-posterior (AP) axis. Based on past research suggesting a gradient in the scale of features processed along the AP extent of the hippocampus, the representations have been proposed to vary as a function of granularity along this axis. One way to quantify such granularity is with population receptive field (pRF) size measured during visual processing, which has so far received little attention. In this study, we compare the pRF sizes within the hippocampus to its activation for images of scenes versus faces. We also measure these functional properties in surrounding medial temporal lobe (MTL) structures. Consistent with past research, we find pRFs to be larger in the anterior than in the posterior hippocampus. Critically, our analysis of surrounding MTL regions, the perirhinal cortex, entorhinal cortex, and parahippocampal cortex shows a similar correlation between scene sensitivity and larger pRF size. These findings provide conclusive evidence for a tight relationship between the pRF size and the sensitivity to image content in the hippocampus and adjacent medial temporal cortex.

Circuit mechanisms of navigation strategy learning in mice

Navigation tasks involve the gradual selection and deployment of increasingly effective searching procedures to reach targets. The brain mechanisms underlying such complex behavior are poorly understood, but their elucidation might provide insights into the systems linking exploration and decision making in complex learning. Here, we developed a trial-by-trial goal-related search strategy analysis as mice learned to navigate identical water mazes encompassing distinct goal-related rules and monitored the strategy deployment process throughout learning. We found that navigation learning involved the following three distinct phases: an early phase during which maze-specific search strategies are deployed in a minority of trials, a second phase of preferential increasing deployment of one search strategy, and a final phase of increasing commitment to this strategy only. The three maze learning phases were affected differently by inhibition of retrosplenial cortex (RSC), dorsomedial striatum (DMS), or dorsolateral striatum (DLS). Through brain region-specific inactivation experiments and gain-of-function experiments involving activation of learning-related cFos+ ensembles, we unraveled how goal-related strategy selection relates to deployment throughout these sequential processes. We found that RSC is critically important for search strategy selection, DMS mediates strategy deployment, and DLS ensures searching consistency throughout maze learning. Notably, activation of specific learning-related ensembles was sufficient to direct strategy selection (RSC) or strategy deployment (DMS) in a different maze. Our results establish a goal-related search strategy deployment approach to dissect unsupervised navigation learning processes and suggest that effective searching in navigation involves evidence-based goal-related strategy direction by RSC, reinforcement-modulated strategy deployment through DMS, and online guidance through DLS.

Mental search of concepts is supported by egocentric vector representations and restructured grid maps

The human hippocampal-entorhinal system is known to represent both spatial locations and abstract concepts in memory in the form of allocentric cognitive maps. Using fMRI, we show that the human parietal cortex evokes complementary egocentric representations in conceptual spaces during goal-directed mental search, akin to those observable during physical navigation to determine where a goal is located relative to oneself (e.g., to our left or to our right). Concurrently, the strength of the grid-like signal, a neural signature of allocentric cognitive maps in entorhinal, prefrontal, and parietal cortices, is modulated as a function of goal proximity in conceptual space. These brain mechanisms might support flexible and parallel readout of where target conceptual information is stored in memory, capitalizing on complementary reference frames.

Goal-seeking compresses neural codes for space in the human hippocampus and orbitofrontal cortex

Humans can navigate flexibly to meet their goals. Here, we asked how the neural representation of allocentric space is distorted by goal-directed behavior. Participants navigated an agent to two successive goal locations in a grid world environment comprising four interlinked rooms, with a contextual cue indicating the conditional dependence of one goal location on another. Examining the neural geometry by which room and context were encoded in fMRI signals, we found that map-like representations of the environment emerged in both hippocampus and neocortex. Cognitive maps in hippocampus and orbitofrontal cortices were compressed so that locations cued as goals were coded together in neural state space, and these distortions predicted successful learning. This effect was captured by a computational model in which current and prospective locations are jointly encoded in a place code, providing a theory of how goals warp the neural representation of space in macroscopic neural signals.

A goal-centric outlook on learning

Goals play a central role in human cognition. However, computational theories of learning and decision-making often take goals as given. Here, we review key empirical findings showing that goals shape the representations of inputs, responses, and outcomes, such that setting a goal crucially influences the central aspects of any learning process: states, actions, and rewards. We thus argue that studying goal selection is essential to advance our understanding of learning. By following existing literature in framing goal selection within a hierarchy of decision-making problems, we synthesize important findings on the principles underlying goal value attribution and exploration strategies. Ultimately, we propose that a goal-centric perspective will help develop more complete accounts of learning in both biological and artificial agents.

Theta oscillatory power decreases in humans are associated with spatial learning in a virtual water maze task

Theta oscillations (4-8 Hz) in humans play a role in navigation processes, including spatial encoding, retrieval and sensorimotor integration. Increased theta power at frontal and parietal midline regions is known to contribute to successful navigation. However, the dynamics of cortical theta and its role in spatial learning are not fully understood. This study aimed to investigate theta oscillations via electroencephalogram (EEG) during spatial learning in a virtual water maze. Participants were separated into a learning group (n = 25) who learned the location of a hidden goal across 12 trials, or a time-matched non-learning group (n = 25) who were required to simply navigate the same arena, but without a goal. We compared all trials, at two phases of learning, the trial start and the goal approach. We also compared the first six trials with the last six trials within-groups. The learning group showed reduced low-frequency theta power at the frontal and parietal midline during the start phase and largely reduced theta combined with a short increase at both midlines during the goal-approach phase. These patterns were not found in the non-learning group, who instead displayed extensive increases in low-frequency oscillations at both regions during the trial start and at the parietal midline during goal approach. Our results support the theory that theta plays a crucial role in spatial encoding during exploration, as opposed to sensorimotor integration. We suggest our findings provide evidence for a link between learning and a reduction of theta oscillations in humans.

Multisensory input modulates memory-guided spatial navigation in humans

Efficient navigation is supported by a cognitive map of space. The hippocampus plays a key role for this map by linking multimodal sensory information with spatial memory representations. However, in human navigation studies, the full range of sensory information is often unavailable due to the stationarity of experimental setups. We investigated the contribution of multisensory information to memory-guided spatial navigation by presenting a virtual version of the Morris water maze on a screen and in an immersive mobile virtual reality setup. Patients with hippocampal lesions and matched controls navigated to memorized object locations in relation to surrounding landmarks. Our results show that availability of multisensory input improves memory-guided spatial navigation in both groups. It has distinct effects on navigational behaviour, with greater improvement in spatial memory performance in patients. We conclude that congruent multisensory information shifts computations to extrahippocampal areas that support spatial navigation and compensates for spatial navigation deficits.

Lateral entorhinal cortex subpopulations represent experiential epochs surrounding reward

During goal-directed navigation, "what" information, which describes the experiences occurring in periods surrounding a reward, can be combined with spatial "where" information to guide behavior and form episodic memories1,2. This integrative process is thought to occur in the hippocampus3, which receives spatial information from the medial entorhinal cortex (MEC)4; however, the source of the "what" information and how it is represented is largely unknown. Here, by establishing a novel imaging method, we show that the lateral entorhinal cortex (LEC) of mice represents key experiential epochs during a reward-based navigation task. We discover a population of neurons that signals goal approach and a separate population of neurons that signals goal departure. A third population of neurons signals reward consumption. When reward location is moved, these populations immediately shift their respective representations of each experiential epoch relative to reward, while optogenetic inhibition of LEC disrupts learning of the new reward location. Together, these results indicate the LEC provides a stable code of experiential epochs surrounding and including reward consumption, providing reward-centric information to contextualize the spatial information carried by the MEC. Such parallel representations are well-suited for generating episodic memories of rewarding experiences and guiding flexible and efficient goal-directed navigation5-7.

A comparison of behavioral paradigms assessing spatial memory in tree shrews

Impairments in spatial navigation in humans can be preclinical signs of Alzheimer's disease. Therefore, cognitive tests that monitor deficits in spatial memory play a crucial role in evaluating animal models with early stage Alzheimer's disease. While Chinese tree shrews (Tupaia belangeri) possess many features suitable for Alzheimer's disease modeling, behavioral tests for assessing spatial cognition in this species are lacking. Here, we established reward-based paradigms using the radial-arm maze and cheeseboard maze for tree shrews, and tested spatial memory in a group of 12 adult males in both tasks, along with a control water maze test, before and after bilateral lesions to the hippocampus, the brain region essential for spatial navigation. Tree shrews memorized target positions during training, and task performance improved gradually until reaching a plateau in all 3 mazes. However, spatial learning was compromised post-lesion in the 2 newly developed tasks, whereas memory retrieval was impaired in the water maze task. These results indicate that the cheeseboard task effectively detects impairments in spatial memory and holds potential for monitoring progressive cognitive decline in aged or genetically modified tree shrews that develop Alzheimer's disease-like symptoms. This study may facilitate the utilization of tree shrew models in Alzheimer's disease research.

Neural representation of goal direction in the monarch butterfly brain

Neural processing of a desired moving direction requires the continuous comparison between the current heading and the goal direction. While the neural basis underlying the current heading is well-studied, the coding of the goal direction remains unclear in insects. Here, we used tetrode recordings in tethered flying monarch butterflies to unravel how a goal direction is represented in the insect brain. While recording, the butterflies maintained robust goal directions relative to a virtual sun. By resetting their goal directions, we found neurons whose spatial tuning was tightly linked to the goal directions. Importantly, their tuning was unaffected when the butterflies changed their heading after compass perturbations, showing that these neurons specifically encode the goal direction. Overall, we here discovered invertebrate goal-direction neurons that share functional similarities to goal-direction cells reported in mammals. Our results give insights into the evolutionarily conserved principles of goal-directed spatial orientation in animals.

A map of spatial navigation for neuroscience

Spatial navigation has received much attention from neuroscientists, leading to the identification of key brain areas and the discovery of numerous spatially selective cells. Despite this progress, our understanding of how the pieces fit together to drive behavior is generally lacking. We argue that this is partly caused by insufficient communication between behavioral and neuroscientific researchers. This has led the latter to under-appreciate the relevance and complexity of spatial behavior, and to focus too narrowly on characterizing neural representations of space-disconnected from the computations these representations are meant to enable. We therefore propose a taxonomy of navigation processes in mammals that can serve as a common framework for structuring and facilitating interdisciplinary research in the field. Using the taxonomy as a guide, we review behavioral and neural studies of spatial navigation. In doing so, we validate the taxonomy and showcase its usefulness in identifying potential issues with common experimental approaches, designing experiments that adequately target particular behaviors, correctly interpreting neural activity, and pointing to new avenues of research.

Hippocampal timestamp for goals

Our brain must manage multiple goals that differ in their temporal proximity. Some goals require immediate attention, while others have already been accomplished, or will be relevant later in time. Here, we examined how the hippocampus represents the temporal distance to different goals using a novel space-themed paradigm during 7T functional MRI (n=31). The hippocampus has an established role in mental time travel and a system in place to stratify information along its longitudinal axis on the basis of representational granularity. Previous work has documented a functional transformation from fine-grained, detail rich representations in the posterior hippocampus to coarse, gist-like representations in the anterior hippocampus. We tested whether the hippocampus uses this long axis system to dissociate goals based upon their temporal distance from the present. We hypothesized that the hippocampus would distinguish goals relevant for ones' current needs from those that are removed in time along the long axis, with temporally removed past and future goals eliciting increasingly anterior activation. We sent participants on a mission to Mars where they had to track goals that differed in when they needed to be accomplished. We observed a long-axis dissociation, where temporally removed past and future goals activated the left anterior hippocampus and current goals activated the left posterior hippocampus. Altogether, this study demonstrates that the timestamp attached to a goal is a key driver in where the goal is represented in the hippocampus. This work extends the scope of the hippocampus' long axis system to the goal-mapping domain.

Altered hippocampal subfield volumes in major depressive disorder with and without anhedonia

BACKGROUND

Previous neuroimaging findings have demonstrated the association between anhedonia and the hippocampus. However, few studies have focused on the structural changes in the hippocampus in major depressive disorder (MDD) patients with anhedonia. Meanwhile, considering that multiple and functionally specialized subfields of the hippocampus have their own signatures, the present study aimed to investigate the volumetric alterations of the hippocampus as well as its subfields in MDD patients with and without anhedonia.

METHODS

A total of 113 subjects, including 30 MDD patients with anhedonia, 40 MDD patients without anhedonia, and 43 healthy controls (HCs), were recruited in the study. All participants underwent high-resolution brain magnetic resonance imaging (MRI) scans, and the automated hippocampal substructure module in FreeSurfer 6.0 was used to evaluate the volumes of hippocampal subfields. We compared the volumetric differences in hippocampal subfields among the three groups by analysis of variance (ANOVA, post hoc Bonferroni), and partial correlation was used to explore the association between hippocampal subregion volumes and clinical characteristics.

RESULTS

ANOVA showed significant volumetric differences in the hippocampal subfields among the three groups in the left hippocampus head, mainly in the cornu ammonis (CA) 1, granule cell layer of the dentate gyrus (GC-ML-DG), and molecular layer (ML). Compared with HCs, both groups of MDD patients showed significantly smaller volumes in the whole left hippocampus head. Interestingly, further exploration revealed that only MDD patients with anhedonia had significantly reduced volumes in the left CA1, GC-ML-DG and ML when compared with HCs. No significant difference was found in the volumes of the hippocampal subfields between MDD patients without anhedonia and HCs, either the two groups of MDD patients. However, no association between hippocampal subfield volumes and clinical characteristics was found in either the subset of patients with anhedonia or in the patient group as a whole.

CONCLUSIONS

These preliminary findings suggest that MDD patients with anhedonia exhibit unique atrophy of the hippocampus and that subfield abnormalities in the left CA1 and DG might be associated with anhedonia in MDD.

Rat hippocampal CA1 region represents learning-related action and reward events with shorter latency than the lateral entorhinal cortex

The hippocampus and entorhinal cortex are deeply involved in learning and memory. However, little is known how ongoing events are processed in the hippocampal-entorhinal circuit. By recording from head-fixed rats during action-reward learning, here we show that the action and reward events are represented differently in the hippocampal CA1 region and lateral entorhinal cortex (LEC). Although diverse task-related activities developed after learning in both CA1 and LEC, phasic activities related to action and reward events differed in the timing of behavioral event representation. CA1 represented action and reward events almost instantaneously, whereas the superficial and deep layers of the LEC showed a delayed representation of the same events. Interestingly, we also found that ramping activity towards spontaneous action was correlated with waiting time in both regions and exceeded that in the motor cortex. Such functional activities observed in the entorhinal-hippocampal circuits may play a crucial role for animals in utilizing ongoing information to dynamically optimize their behaviors.

Memory-guided navigation in amyotrophic lateral sclerosis

BACKGROUND

Previous studies have yielded inconsistent results about hippocampal involvement in non-demented patients with amyotrophic lateral sclerosis (ALS). We hypothesized that testing of memory-guided spatial navigation i.e., a highly hippocampus-dependent behaviour, might reveal behavioural correlates of hippocampal dysfunction in non-demented ALS patients.

METHODS

We conducted a prospective study of spatial cognition in 43 non-demented ALS outpatients (11f, 32 m, mean age 60.0 years, mean disease duration 27.0 months, mean ALSFRS-R score 40.0) and 43 healthy controls (14f, 29 m, mean age 57.0 years). Participants were tested with a virtual memory-guided navigation task derived from animal research ("starmaze") that has previously been used in studies of hippocampal function. Participants were further tested with neuropsychological tests of visuospatial memory (SPART, 10/36 Spatial Recall Test), fluency (5PT, five-point test) and orientation (PTSOT, Perspective Taking/Spatial Orientation Test).

RESULTS

Patients successfully learned and navigated the starmaze from memory, both in conditions that forced memory of landmarks (success: patients 50.7%, controls 47.7%, p = 0.786) and memory of path sequences (success: patients 96.5%, controls 94.0%, p = 0.937). Measures of navigational efficacy (latency, path error and navigational uncertainty) did not differ between groups (p ≥ 0.546). Likewise, SPART, 5PT and PTSOT scores did not differ between groups (p ≥ 0.238).

CONCLUSIONS

This study found no behavioural correlate for hippocampal dysfunction in non-demented ALS patients. These findings support the view that the individual cognitive phenotype of ALS may relate to distinct disease subtypes rather than being a variable expression of the same underlying condition.

Multi-scale goal distance representations in human hippocampus during virtual spatial navigation

Goal-directed navigation relies on both coarse and fine-grained coding of spatial distance between the current position of a navigating subject and a goal destination. However, the neural signatures underlying goal distance coding remain poorly understood. Using intracranial EEG recordings from the hippocampus of drug-resistant epilepsy patients who performed a virtual spatial navigation task, we found that the right hippocampal theta power was significantly modulated by goal distance and decreased with goal proximity. This modulation varied along the hippocampal longitudinal axis such that theta power in the posterior hippocampus decreased more strongly with goal proximity. Similarly, neural timescale, reflecting the duration across which information can be maintained, increased gradually from the posterior to anterior hippocampus. Taken together, this study provides empirical evidence for multi-scale spatial representations of goal distance in the human hippocampus and links the hippocampal processing of spatial information to its intrinsic temporal dynamics.

Entropy and a sub-group of geometric measures of paths predict the navigability of an environment

Despite extensive research on navigation, it remains unclear which features of an environment predict how difficult it will be to navigate. We analysed 478,170 trajectories from 10,626 participants who navigated 45 virtual environments in the research app-based game Sea Hero Quest. Virtual environments were designed to vary in a range of properties such as their layout, number of goals, visibility (varying fog) and map condition. We calculated 58 spatial measures grouped into four families: task-specific metrics, space syntax configurational metrics, space syntax geometric metrics, and general geometric metrics. We used Lasso, a variable selection method, to select the most predictive measures of navigation difficulty. Geometric features such as entropy, area of navigable space, number of rings and closeness centrality of path networks were among the most significant factors determining the navigational difficulty. By contrast a range of other measures did not predict difficulty, including measures of intelligibility. Unsurprisingly, other task-specific features (e.g. number of destinations) and fog also predicted navigation difficulty. These findings have implications for the study of spatial behaviour in ecological settings, as well as predicting human movements in different settings, such as complex buildings and transport networks and may aid the design of more navigable environments.

History of suicide attempt associated with amygdala and hippocampus changes among individuals with schizophrenia

Abnormalities in subcortical brain structures may reflect higher suicide risk in mood disorders, but less is known about its associations for schizophrenia. This cross-sectional imaging study aimed to explore whether the history of suicide attempts was associated with subcortical changes among individuals with schizophrenia. We recruited 44 individuals with schizophrenia and a history of suicide attempts (SZ-SA) and 44 individuals with schizophrenia but without a history of suicide attempts (SZ-NSA) and 44 healthy controls. Linear regression showed that SZ-SA had smaller volumes of the hippocampus (Cohen's d = -0.72), the amygdala (Cohen's d = -0.69), and some nuclei of the amygdala (Cohen's d, -0.57 to -0.72) than SZ-NSA after adjusting for age, sex, illness phase, and intracranial volume. There was no difference in the volume of the subfields of the hippocampus. It suggests the history of suicide attempts is associated with subcortical volume alterations in schizophrenia.

New Approaches to 3D Vision

New approaches to 3D vision are enabling new advances in artificial intelligence and autonomous vehicles, a better understanding of how animals navigate the 3D world, and new insights into human perception in virtual and augmented reality. Whilst traditional approaches to 3D vision in computer vision (SLAM: simultaneous localization and mapping), animal navigation (cognitive maps), and human vision (optimal cue integration) start from the assumption that the aim of 3D vision is to provide an accurate 3D model of the world, the new approaches to 3D vision explored in this issue challenge this assumption. Instead, they investigate the possibility that computer vision, animal navigation, and human vision can rely on partial or distorted models or no model at all. This issue also highlights the implications for artificial intelligence, autonomous vehicles, human perception in virtual and augmented reality, and the treatment of visual disorders, all of which are explored by individual articles. This article is part of a discussion meeting issue 'New approaches to 3D vision'.

Temporal context and latent state inference in the hippocampal splitter signal

The hippocampus is thought to enable the encoding and retrieval of ongoing experience, the organization of that experience into structured representations like contexts, maps, and schemas, and the use of these structures to plan for the future. A central goal is to understand what the core computations supporting these functions are, and how these computations are realized in the collective action of single neurons. A potential access point into this issue is provided by 'splitter cells', hippocampal neurons that fire differentially on the overlapping segment of trajectories that differ in their past and/or future. However, the literature on splitter cells has been fragmented and confusing, owing to differences in terminology, behavioral tasks, and analysis methods across studies. In this review, we synthesize consistent findings from this literature, establish a common set of terms, and translate between single-cell and ensemble perspectives. Most importantly, we examine the combined findings through the lens of two major theoretical ideas about hippocampal function: representation of temporal context and latent state inference. We find that unique signature properties of each of these models are necessary to account for the data, but neither theory, by itself, explains all of its features. Specifically, the temporal gradedness of the splitter signal is strong support for temporal context, but is hard to explain using state models, while its flexibility and task-dependence is naturally accounted for using state inference, but poses a challenge otherwise. These theories suggest a number of avenues for future work, and we believe their application to splitter cells is a timely and informative domain for testing and refining theoretical ideas about hippocampal function.

Representational integration and differentiation in the human hippocampus following goal-directed navigation

As we learn, dynamic memory processes build structured knowledge across our experiences. Such knowledge enables the formation of internal models of the world that we use to plan, make decisions, and act. Recent theorizing posits that mnemonic mechanisms of differentiation and integration - which at one level may seem to be at odds - both contribute to the emergence of structured knowledge. We tested this possibility using fMRI as human participants learned to navigate within local and global virtual environments over the course of 3 days. Pattern similarity analyses on entorhinal cortical and hippocampal patterns revealed evidence that differentiation and integration work concurrently to build local and global environmental representations, and that variability in integration relates to differences in navigation efficiency. These results offer new insights into the neural machinery and the underlying mechanisms that translate experiences into structured knowledge that allows us to navigate to achieve goals.

Plasticity of synapses and reward circuit function in the genesis and treatment of depression

What changes in brain function cause the debilitating symptoms of depression? Can we use the answers to this question to invent more effective, faster acting antidepressant drug therapies? This review provides an overview and update of the converging human and preclinical evidence supporting the hypothesis that changes in the function of excitatory synapses impair the function of the circuits they are embedded in to give rise to the pathological changes in mood, hedonic state, and thought processes that characterize depression. The review also highlights complementary human and preclinical findings that classical and novel antidepressant drugs relieve the symptoms of depression by restoring the functions of these same synapses and circuits. These findings offer a useful path forward for designing better antidepressant compounds.

The little brain and the seahorse: Cerebellar-hippocampal interactions

There is a growing appreciation for the cerebellum beyond its role in motor function and accumulating evidence that the cerebellum and hippocampus interact across a range of brain states and behaviors. Acute and chronic manipulations, simultaneous recordings, and imaging studies together indicate coordinated coactivation and a bidirectional functional connectivity relevant for various physiological functions, including spatiotemporal processing. This bidirectional functional connectivity is likely supported by multiple circuit paths. It is also important in temporal lobe epilepsy: the cerebellum is impacted by seizures and epilepsy, and modulation of cerebellar circuitry can be an effective strategy to inhibit hippocampal seizures. This review highlights some of the recent key hippobellum literature.

Humans account for cognitive costs when finding shortcuts: An information-theoretic analysis of navigation

When faced with navigating back somewhere we have been before we might either retrace our steps or seek a shorter path. Both choices have costs. Here, we ask whether it is possible to characterize formally the choice of navigational plans as a bounded rational process that trades off the quality of the plan (e.g., its length) and the cognitive cost required to find and implement it. We analyze the navigation strategies of two groups of people that are firstly trained to follow a "default policy" taking a route in a virtual maze and then asked to navigate to various known goal destinations, either in the way they want ("Go To Goal") or by taking novel shortcuts ("Take Shortcut"). We address these wayfinding problems using InfoRL: an information-theoretic approach that formalizes the cognitive cost of devising a navigational plan, as the informational cost to deviate from a well-learned route (the "default policy"). In InfoRL, optimality refers to finding the best trade-off between route length and the amount of control information required to find it. We report five main findings. First, the navigational strategies automatically identified by InfoRL correspond closely to different routes (optimal or suboptimal) in the virtual reality map, which were annotated by hand in previous research. Second, people deliberate more in places where the value of investing cognitive resources (i.e., relevant goal information) is greater. Third, compared to the group of people who receive the "Go To Goal" instruction, those who receive the "Take Shortcut" instruction find shorter but less optimal solutions, reflecting the intrinsic difficulty of finding optimal shortcuts. Fourth, those who receive the "Go To Goal" instruction modulate flexibly their cognitive resources, depending on the benefits of finding the shortcut. Finally, we found a surprising amount of variability in the choice of navigational strategies and resource investment across participants. Taken together, these results illustrate the benefits of using InfoRL to address navigational planning problems from a bounded rational perspective.

Reconciling neuronal representations of schema, abstract task structure, and categorization under cognitive maps in the entorhinal-hippocampal-frontal circuits

Learning leads to a neuronal representation of acquired knowledge. This idea of knowledge representation was traditionally developed as a "cognitive map" of spatial memory represented in the hippocampus. The framework of cognitive mapping has been extended in the past decade to include not only spatial memory, but also non-spatial factual and temporal memory. Following this conceptual advancement, a line of recent neurophysiological research discovered such knowledge representations not only in the hippocampus, but also in the entorhinal cortex and frontal cortex. Although the distinct terms "cognitive map," "schema," "abstract task structure" or "categorization" were used in these studies, it is likely that these terms can be reconciled as a common mechanism of learned knowledge representations. Future experimental work will be required to differentiate the parametric nature of knowledge representations across brain areas.

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.

Linking external stimuli with internal drives: A role for the ventral hippocampus

The ventral hippocampus (vHPC) has long been thought of as the "emotional" hippocampus. Over the past several years, the complexity of vHPC has come to light, highlighting the diversity of cell types, inputs, and outputs that coordinate a constellation of positively and negatively motivated behaviors. Here, we review recent work on how vCA1 contributes to a network that associates external stimuli with internal motivational drive states to promote the selection of adaptive behavioral responses. We propose a model of vHPC function that emphasizes its role in the integration and transformation of internal and external cues to guide behavioral selection when faced with multiple potential outcomes.

Spatial representation by ramping activity of neurons in the retrohippocampal cortex

Neurons in the retrohippocampal cortices play crucial roles in spatial memory. Many retrohippocampal neurons have firing fields that are selectively active at specific locations, with memory for rewarded locations associated with reorganization of these firing fields. Whether this is the sole strategy for representing spatial memories is unclear. Here, we demonstrate that during a spatial memory task retrohippocampal neurons encode location through ramping activity that extends across segments of a linear track approaching and following a reward, with the rewarded location represented by offsets or switches in the slope of the ramping activity. Ramping representations could be maintained independently of trial outcome and cues marking the reward location, indicating that they result from recall of the track structure. When recorded in an open arena, neurons that generated ramping activity during the spatial memory task were more numerous than grid or border cells, with a majority showing spatial firing that did not meet criteria for classification as grid or border representations. Encoding of rewarded locations through offsets and switches in the slope of ramping activity also emerged in recurrent neural network models trained to solve a similar spatial memory task. Impaired performance of model networks following disruption of outputs from ramping neurons is consistent with this coding strategy supporting navigation to recalled locations of behavioral significance. Our results suggest that encoding of learned spaces by retrohippocampal networks employs both discrete firing fields and continuous ramping representations. We hypothesize that retrohippocampal ramping activity mediates readout of learned models for goal-directed navigation.

Predictive maps in rats and humans for spatial navigation

Much of our understanding of navigation comes from the study of individual species, often with specific tasks tailored to those species. Here, we provide a novel experimental and analytic framework integrating across humans, rats, and simulated reinforcement learning (RL) agents to interrogate the dynamics of behavior during spatial navigation. We developed a novel open-field navigation task ("Tartarus maze") requiring dynamic adaptation (shortcuts and detours) to frequently changing obstructions on the path to a hidden goal. Humans and rats were remarkably similar in their trajectories. Both species showed the greatest similarity to RL agents utilizing a "successor representation," which creates a predictive map. Humans also displayed trajectory features similar to model-based RL agents, which implemented an optimal tree-search planning procedure. Our results help refine models seeking to explain mammalian navigation in dynamic environments and highlight the utility of modeling the behavior of different species to uncover the shared mechanisms that support behavior.

Hippocampal representations of foraging trajectories depend upon spatial context

Animals learn trajectories to rewards in both spatial, navigational contexts and relational, non-navigational contexts. Synchronous reactivation of hippocampal activity is thought to be critical for recall and evaluation of trajectories for learning. Do hippocampal representations differentially contribute to experience-dependent learning of trajectories across spatial and relational contexts? In this study, we trained mice to navigate to a hidden target in a physical arena or manipulate a joystick to a virtual target to collect delayed rewards. In a navigational context, calcium imaging in freely moving mice revealed that synchronous CA1 reactivation was retrospective and important for evaluation of prior navigational trajectories. In a non-navigational context, reactivation was prospective and important for initiation of joystick trajectories, even in the same animals trained in both contexts. Adaptation of trajectories to a new target was well-explained by a common learning algorithm in which hippocampal activity makes dissociable contributions to reinforcement learning computations depending upon spatial context.