Précis of O'Keefe & Nadel's The hippocampus as a cognitive map

A Bionic Localization Memristive Circuit Based on Spatial Cognitive Mechanisms of Hippocampus and Entorhinal Cortex

In this article, a bionic localization memristive circuit is proposed, which mainly consists of head direction cell module, grid cell module, place cell module and decoding module. This work modifies the two-dimensional Continuous Attractor Network (CAN) model of grid cells into two one-dimensional models in X and Y directions. The head direction cell module utilizes memristors to integrate angular velocity and represents the real orientation of an agent. The grid cell module uses memristors to sense linear velocity and orientation signals, which are both self-motion cues, and encodes the position in space by firing in a periodic mode. The place cell module receives the grid cell module's output and fires in a specific position. The decoding module decodes the angle or place information and transfers the neuron state to a 'one-hot' code. This proposed circuit completes the localizing task in space and realizes in-memory computing due to the use of memristors, which can shorten the execution time. The functions mentioned above are implemented in LTSPICE. The simulation results show that the proposed circuit can realize path integration and localization. Moreover, it is shown that the proposed circuit has good robustness and low area overhead. This work provides a possible application idea in a prospective robot platform to help the robot localize and build maps.

Remapping revisited: how the hippocampus represents different spaces

The representation of distinct spaces by hippocampal place cells has been linked to changes in their place fields (the locations in the environment where the place cells discharge strongly), a phenomenon that has been termed 'remapping'. Remapping has been assumed to be accompanied by the reorganization of subsecond cofiring relationships among the place cells, potentially maximizing hippocampal information coding capacity. However, several observations challenge this standard view. For example, place cells exhibit mixed selectivity, encode non-positional variables, can have multiple place fields and exhibit unreliable discharge in fixed environments. Furthermore, recent evidence suggests that, when measured at subsecond timescales, the moment-to-moment cofiring of a pair of cells in one environment is remarkably similar in another environment, despite remapping. Here, I propose that remapping is a misnomer for the changes in place fields across environments and suggest instead that internally organized manifold representations of hippocampal activity are actively registered to different environments to enable navigation, promote memory and organize knowledge.

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.

Exploratory Rearing Is Governed by Hypothalamic Melanin-Concentrating Hormone Neurons According to Locus Ceruleus

Information seeking, such as standing on tiptoes to look around in humans, is observed across animals and helps survival. Its rodent analog-unsupported rearing on hind legs-was a classic model in deciphering neural signals of cognition and is of intense renewed interest in preclinical modeling of neuropsychiatric states. Neural signals and circuits controlling this dedicated decision to seek information remain largely unknown. While studying subsecond timing of spontaneous behavioral acts and activity of melanin-concentrating hormone (MCH) neurons (MNs) in behaving male and female mice, we observed large MN activity spikes that aligned to unsupported rears. Complementary causal, loss and gain of function, analyses revealed specific control of rear frequency and duration by MNs and MCHR1 receptors. Activity in a key stress center of the brain-the locus ceruleus noradrenaline cells-rapidly inhibited MNs and required functional MCH receptors for its endogenous modulation of rearing. By defining a neural module that both tracks and controls rearing, these findings may facilitate further insights into biology of information seeking.

Representational drift as a result of implicit regularization

Recent studies show that, even in constant environments, the tuning of single neurons changes over time in a variety of brain regions. This representational drift has been suggested to be a consequence of continuous learning under noise, but its properties are still not fully understood. To investigate the underlying mechanism, we trained an artificial network on a simplified navigational task. The network quickly reached a state of high performance, and many units exhibited spatial tuning. We then continued training the network and noticed that the activity became sparser with time. Initial learning was orders of magnitude faster than ensuing sparsification. This sparsification is consistent with recent results in machine learning, in which networks slowly move within their solution space until they reach a flat area of the loss function. We analyzed four datasets from different labs, all demonstrating that CA1 neurons become sparser and more spatially informative with exposure to the same environment. We conclude that learning is divided into three overlapping phases: (i) Fast familiarity with the environment; (ii) slow implicit regularization; and (iii) a steady state of null drift. The variability in drift dynamics opens the possibility of inferring learning algorithms from observations of drift statistics.

Disrupting direct inputs from the dorsal subiculum to the granular retrosplenial cortex impairs flexible spatial memory in the rat

In a changing environment, animals must process spatial signals in a flexible manner. The rat hippocampal formation projects directly upon the retrosplenial cortex, with most inputs arising from the dorsal subiculum and terminating in the granular retrosplenial cortex (area 29). The present study examined whether these same projections are required for spatial working memory and what happens when available spatial cues are altered. Consequently, injections of iDREADDs were made into the dorsal subiculum of rats. In a separate control group, GFP-expressing adeno-associated virus was injected into the dorsal subiculum. Both groups received intracerebral infusions within the retrosplenial cortex of clozapine, which in the iDREADDs rats should selectively disrupt the subiculum to retrosplenial projections. When tested on reinforced T-maze alternation, disruption of the subiculum to retrosplenial projections had no evident effect on the performance of those alternation trials when all spatial-cue types remained present and unchanged. However, the same iDREADDs manipulation impaired performance on all three alternation conditions when there was a conflict or selective removal of spatial cues. These findings reveal how the direct projections from the dorsal subiculum to the retrosplenial cortex support the flexible integration of different spatial cue types, helping the animal to adopt the spatial strategy that best meets current environmental demands.

Building a realistic, scalable memory model with independent engrams using a homeostatic mechanism

Memory formation is usually associated with Hebbian learning and synaptic plasticity, which changes the synaptic strengths but omits structural changes. A recent study suggests that structural plasticity can also lead to silent memory engrams, reproducing a conditioned learning paradigm with neuron ensembles. However, this study is limited by its way of synapse formation, enabling the formation of only one memory engram. Overcoming this, our model allows the formation of many engrams simultaneously while retaining high neurophysiological accuracy, e.g., as found in cortical columns. We achieve this by substituting the random synapse formation with the Model of Structural Plasticity. As a homeostatic model, neurons regulate their activity by growing and pruning synaptic elements based on their current activity. Utilizing synapse formation based on the Euclidean distance between the neurons with a scalable algorithm allows us to easily simulate 4 million neurons with 343 memory engrams. These engrams do not interfere with one another by default, yet we can change the simulation parameters to form long-reaching associations. Our model's analysis shows that homeostatic engram formation requires a certain spatiotemporal order of events. It predicts that synaptic pruning precedes and enables synaptic engram formation and that it does not occur as a mere compensatory response to enduring synapse potentiation as in Hebbian plasticity with synaptic scaling. Our model paves the way for simulations addressing further inquiries, ranging from memory chains and hierarchies to complex memory systems comprising areas with different learning mechanisms.

The effective connectivity analysis of fMRI based on asymmetric detection of transfer brain entropy

It is important to explore causal relationships in functional magnetic resonance imaging study. However, the traditional effective connectivity analysis method is easy to produce false causality, and the detection accuracy needs to be improved. In this paper, we introduce a novel functional magnetic resonance imaging effective connectivity method based on the asymmetry detection of transfer entropy, which quantifies the disparity in predictive information between forward and backward time, subsequently normalizing this disparity to establish a more precise criterion for detecting causal relationships while concurrently reducing computational complexity. Then, we evaluate the effectiveness of this method on the simulated data with different level of nonlinearity, and the results demonstrated that the proposed method outperforms others methods on the detection of both linear and nonlinear causal relationships, including Granger Causality, Partial Granger Causality, Kernel Granger Causality, Copula Granger Causality, and traditional transfer entropy. Furthermore, we applied it to study the effective connectivity of brain functional activities in seafarers. The results showed that there are significantly different causal relationships between different brain regions in seafarers compared with non-seafarers, such as Temporal lobe related to sound and auditory information processing, Hippocampus related to spatial navigation, Precuneus related to emotion processing as well as Supp_Motor_Area associated with motor control and coordination, which reflects the occupational specificity of brain function of seafarers.

Impoverished details with preserved gist in remote and recent spatial memory following hippocampal and fornix lesions

INTRODUCTION

Cognitive Map Theory predicts that the hippocampus (HPC) plays a specialized, time-invariant role in supporting allocentric spatial memory, while Standard Consolidation Theory makes the competing prediction that the HPC plays a time-limited role, with more remote memories gaining independence of HPC function. These theories, however, are largely informed by the results of laboratory-based tests that are unlikely to simulate the demands of representing real-world environments in humans. Validation of these theories is further limited by an overall focus on spatial memory of newly encountered environments and on individuals with extensive lesions to the HPC and to surrounding medial temporal lobe (MTL) regions. The current study incorporates naturalistic tests of spatial memory based on recently and remotely encountered environments navigated by individuals with lesions to the HPC/MTL or that are limited to the HPC's major output, the fornix.

METHODS

Four participants with bilateral HPC/MTL and/or fornix lesions drew sketch maps of recently and remotely experienced neighbourhoods and houses. Tests of the appearance, distances, and routes between landmarks from the same real-world environments were also administered. Performance on the tasks was compared to that of control participants closely matched in terms of exposure to the same neighbourhoods and home environments as well as to actual maps.

RESULTS

The performance of individuals with fornix/MTL lesions was found to be largely comparable to that of controls on objective tests of spatial memory, other than one case who was impaired on remote and recent conditions for several tasks. The nature of deficits in recent and remote spatial memory were further revealed on house floorplan drawings, which contained spatial distortions, room/structure transpositions, and omissions, and on neighbourhood sketch maps, which were intact in terms of overall layout but sparse in details such as landmarks.

CONCLUSION

Lab-based tests of spatial memory of newly learned environments are unlikely to fully capture patterns of spared and impaired representations of real-world environments (e.g., peripheral features, configurations). Naturalistic tasks, including generative drawing tasks, indicate that contrary to Cognitive Map Theory, neither HPC nor MTL are critical for allocentric gross representations of large-scale environments. Conversely, the HPC appears critical for representing detailed spatial information of local naturalistic environments and environmental objects regardless of the age of the memory, contrary to Standard Consolidation Theory.

Representational drift as a result of implicit regularization

Recent studies show that, even in constant environments, the tuning of single neurons changes over time in a variety of brain regions. This representational drift has been suggested to be a consequence of continuous learning under noise, but its properties are still not fully understood. To investigate the underlying mechanism, we trained an artificial network on a simplified navigational task. The network quickly reached a state of high performance, and many units exhibited spatial tuning. We then continued training the network and noticed that the activity became sparser with time. Initial learning was orders of magnitude faster than ensuing sparsification. This sparsification is consistent with recent results in machine learning, in which networks slowly move within their solution space until they reach a flat area of the loss function. We analyzed four datasets from different labs, all demonstrating that CA1 neurons become sparser and more spatially informative with exposure to the same environment. We conclude that learning is divided into three overlapping phases: (i) Fast familiarity with the environment; (ii) slow implicit regularization; (iii) a steady state of null drift. The variability in drift dynamics opens the possibility of inferring learning algorithms from observations of drift statistics.

Cortical Correlates of Visuospatial Switching Processes Between Egocentric and Allocentric Frames of Reference: A fNIRS Study

Human beings represent spatial information according to egocentric (body-to-object) and allocentric (object-to-object) frames of reference. In everyday life, we constantly switch from one frame of reference to another in order to react effectively to the specific needs of the environment and task demands. However, to the best of our knowledge, no study to date has investigated the cortical activity of switching and non-switching processes between egocentric and allocentric spatial encodings. To this aim, a custom-designed visuo-spatial memory task was administered and the cortical activities underlying switching vs non-switching spatial processes were investigated. Changes in concentrations of oxygenated and deoxygenated haemoglobin were measured using functional near-infrared spectroscopy (fNIRS). Participants were asked to memorize triads of geometric objects and then make two consecutive judgments about the same triad. In the non-switching condition, both spatial judgments considered the same frame of reference: only egocentric or only allocentric. In the switching condition, if the first judgment was egocentric, the second one was allocentric (or vice versa). The results showed a generalized activation of the frontal regions during the switching compared to the non-switching condition. Additionally, increased cortical activity was found in the temporo-parietal junction during the switching condition compared to the non-switching condition. Overall, these results illustrate the cortical activity underlying the processing of switching between body position and environmental stimuli, showing an important role of the temporo-parietal junction and frontal regions in the preparation and switching between egocentric and allocentric reference frames.

Association Between Hippocampal Volumes and Cognition in Cerebral Amyloid Angiopathy

BACKGROUND AND OBJECTIVES

Accumulating evidence suggests that gray matter atrophy, often considered a marker of Alzheimer disease (AD), can also result from cerebral small vessel disease (CSVD). Cerebral amyloid angiopathy (CAA) is a form of sporadic CSVD, diagnosed through neuroimaging criteria, that often co-occurs with AD pathology and leads to cognitive impairment. We sought to identify the role of hippocampal integrity in the development of cognitive impairment in a cohort of patients with possible and probable CAA.

METHODS

Patients were recruited from an ongoing CAA study at Massachusetts General Hospital. Composite scores defined performance in the cognitive domains of memory, language, executive function, and processing speed. Hippocampal subfields' volumes were measured from 3T MRI, using an automated method, and multivariate linear regression models were used to estimate their association with each cognitive domain and relationship to CAA-related neuroimaging markers.

RESULTS

One hundred twenty patients, 36 with possible (age mean [range]: 75.6 [65.6-88.9]), 67 with probable CAA (75.9 [59.0-94.0]), and 17 controls without cognitive impairment and CSVD (72.4 [62.5-82.7]; 76.4% female patients), were included in this study. We found a positive association between all investigated hippocampal subfields and memory and language, whereas specific subfields accounted for executive function (CA4 [Estimate = 5.43; 95% CI 1.26-9.61; p = 0.020], subiculum [Estimate = 2.85; 95% CI 0.67-5.02; p = 0.022]), and processing speed (subiculum [Estimate = 1.99; 95% CI 0.13-3.85; p = 0.036]). These findings were independent of other CAA-related markers, which did not have an influence on cognition in this cohort. Peak width of skeletonized mean diffusivity (PSMD), a measure of white matter integrity, was negatively associated with hippocampal subfields' volumes (CA3 [Estimate = -0.012; 95% CI -0.020 to -0.004; p = 0.034], CA4 [Estimate = -0.010; 95% CI -0.020 to -0.0007; p = 0.037], subiculum [Estimate = -0.019; 95% CI -0.042 to -0.0001; p = 0.003]).

DISCUSSION

These results suggest that hippocampal integrity is an independent contributor to cognitive impairment in patients with CAA and that it might be related to loss of integrity in the white matter. Further studies exploring potential causes and directionality of the relationship between white matter and hippocampal integrity may be warranted.

Social play exclusion model in adolescent rats: Monitoring locomotor and emotional behavior associated with social play and examining c-Fos expression in the brain

The exclusion of social play within an adolescent group interferes with learning and the acquisition of essential social behavior during development and can cause modulations in the social brain areas. However, despite the importance of social play in adolescence, an in-depth explanation of its physiological mechanisms is limited because of the lack of experimental animal models that embody social play exclusion in human society. To determine the mechanism of social play in adolescence, we identified differences in emotional behavior and brain activity in animal models of social play exclusion that mimicked human society. Emotional changes in the social play exclusion and non-exclusion groups were examined by tracking social play-related social interaction behavior, social play-related space preference, social play-related locomotor behavior, and anxiety-like behavior using a behavioral data analysis program. Differences in brain activity among groups were identified using immunohistochemical staining. During the social play exclusion model, the rats preferred the partition zone to the other areas in the test chamber. The exclusion group preferred the partition and the center zone over the non-exclusion group. When comparing before and after the social play exclusion, the exclusion group showed a decrease in mobility and an increase in anxiety-like behavior compared to the non-exclusion group. We found that c-Fos expression in the dentate gyrus (DG) of the exclusion group was lower than that in the non-exclusion group, whereas c-Fos expression in the lateral habenula (LHb) of the exclusion group was higher than that in the non-exclusion group. Taken together, in adolescence, exclusion from social play with peers can increase anxiety-like behavior in the exclusion group and change the neuronal activity of the DG and LHb, suggesting that exclusion from social play is linked to modifications in the DG and LHb, which are regions associated with mood regulation.

MK-801 and cognitive functions: Investigating the behavioral effects of a non-competitive NMDA receptor antagonist

RATIONALE

MK-801 (dizocilpine) is a non-competitive NMDA receptor antagonist originally explored for anticonvulsant potential. Despite its original purpose, its amnestic properties led to the development of pivotal models of various cognitive impairments widely employed in research and greatly impacting scientific progress. MK-801 offers several advantages; however, it also presents drawbacks, including inducing dose-dependent hyperlocomotion or ambiguous effects on anxiety, which can impact the interpretation of behavioral research results.

OBJECTIVES

The present review attempts to summarize and discuss the effects of MK-801 on different types of memory and cognitive functions in animal studies.

RESULTS

A plethora of behavioral research suggests that MK-801 can detrimentally impact cognitive functions. The specific effect of this compound is influenced by variables including developmental stage, gender, species, strain, and, crucially, the administered dose. Notably, when considering the undesirable effects of MK-801, doses up to 0.1 mg/kg were found not to induce stereotypy or hyperlocomotion.

CONCLUSION

Dizocilpine continues to be of significant importance in preclinical research, facilitating the exploration of various procognitive therapeutic agents. However, given its potential undesirable effects, it is imperative to meticulously determine the appropriate dosages and conduct supplementary evaluations for any undesirable outcomes, which could complicate the interpretation of the findings.

Sharpening the blades of the dentate gyrus: how adult-born neurons differentially modulate diverse aspects of hippocampal learning and memory

For decades, the mammalian hippocampus has been the focus of cellular, anatomical, behavioral, and computational studies aimed at understanding the fundamental mechanisms underlying cognition. Long recognized as the brain's seat for learning and memory, a wealth of knowledge has been accumulated on how the hippocampus processes sensory input, builds complex associations between objects, events, and space, and stores this information in the form of memories to be retrieved later in life. However, despite major efforts, our understanding of hippocampal cognitive function remains fragmentary, and models trying to explain it are continually revisited. Here, we review the literature across all above-mentioned domains and offer a new perspective by bringing attention to the most distinctive, and generally neglected, feature of the mammalian hippocampal formation, namely, the structural separability of the two blades of the dentate gyrus into "supra-pyramidal" and "infra-pyramidal". Next, we discuss recent reports supporting differential effects of adult neurogenesis in the regulation of mature granule cell activity in these two blades. We propose a model for how differences in connectivity and adult neurogenesis in the two blades can potentially provide a substrate for subtly different cognitive functions.

Postnatal Maturation of Membrane Potential Dynamics during in Vivo Hippocampal Ripples

Sharp-wave ripples (SWRs) are transient high-frequency oscillations of local field potentials (LFPs) in the hippocampus and play a critical role in memory consolidation. During SWRs, CA1 pyramidal cells exhibit rapid spike sequences that often replay the sequential activity that occurred during behavior. This temporally organized firing activity gradually emerges during 2 weeks after the eye opening; however, it remains unclear how the organized spikes during SWRs mature at the intracellular membrane potential (Vm) level. Here, we recorded Vm of CA1 pyramidal cells simultaneously with hippocampal LFPs from anesthetized immature mice of either sex after the developmental emergence of SWRs. On postnatal days 16 and 17, Vm dynamics around SWRs were premature, characterized by prolonged depolarizations without either pre- or post-SWR hyperpolarizations. The biphasic hyperpolarizations, features typical of adult SWR-relevant Vm, formed by approximately postnatal day 30. This Vm maturation was associated with an increase in SWR-associated inhibitory inputs to pyramidal cells. Thus, the development of SWR-relevant inhibition restricts the temporal windows for spikes of pyramidal cells and allows CA1 pyramidal cells to organize their spike sequences during SWRs.SIGNIFICANCE STATEMENT Sharp-wave ripples (SWRs) are prominent hippocampal oscillations and play a critical role in memory consolidation. During SWRs, hippocampal neurons synchronously emit spikes with organized temporal patterns. This temporal structure of spikes during SWRs develops during the third and fourth postnatal weeks, but the underlying mechanisms are not well understood. Here, we recorded in vivo membrane potentials from hippocampal neurons in premature mice and suggest that the maturation of SWR-associated inhibition enables hippocampal neurons to produce precisely controlled spike times during SWRs.

Assessments of dentate gyrus function: discoveries and debates

There has been considerable speculation regarding the function of the dentate gyrus (DG) - a subregion of the mammalian hippocampus - in learning and memory. In this Perspective article, we compare leading theories of DG function. We note that these theories all critically rely on the generation of distinct patterns of activity in the region to signal differences between experiences and to reduce interference between memories. However, these theories are divided by the roles they attribute to the DG during learning and recall and by the contributions they ascribe to specific inputs or cell types within the DG. These differences influence the information that the DG is thought to impart to downstream structures. We work towards a holistic view of the role of DG in learning and memory by first developing three critical questions to foster a dialogue between the leading theories. We then evaluate the extent to which previous studies address our questions, highlight remaining areas of conflict, and suggest future experiments to bridge these theories.

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.

Generalization of cognitive maps across space and time

Prominent theories posit that associative memory structures, known as cognitive maps, support flexible generalization of knowledge across cognitive domains. Here, we evince a representational account of cognitive map flexibility by quantifying how spatial knowledge formed one day was used predictively in a temporal sequence task 24 hours later, biasing both behavior and neural response. Participants learned novel object locations in distinct virtual environments. After learning, hippocampus and ventromedial prefrontal cortex (vmPFC) represented a cognitive map, wherein neural patterns became more similar for same-environment objects and more discriminable for different-environment objects. Twenty-four hours later, participants rated their preference for objects from spatial learning; objects were presented in sequential triplets from either the same or different environments. We found that preference response times were slower when participants transitioned between same- and different-environment triplets. Furthermore, hippocampal spatial map coherence tracked behavioral slowing at the implicit sequence transitions. At transitions, predictive reinstatement of virtual environments decreased in anterior parahippocampal cortex. In the absence of such predictive reinstatement after sequence transitions, hippocampus and vmPFC responses increased, accompanied by hippocampal-vmPFC functional decoupling that predicted individuals' behavioral slowing after a transition. Collectively, these findings reveal how expectations derived from spatial experience generalize to support temporal prediction.

Social navigation modulates the anterior and posterior hippocampal circuits in the resting brain

Social navigation is a dynamic and complex process that requires the collaboration of multiple brain regions. However, the neural networks for navigation in a social space remain largely unknown. This study aimed to investigate the role of hippocampal circuit in social navigation from a resting-state fMRI data. Here, resting-state fMRI data were acquired before and after participants performed a social navigation task. By taking the anterior and posterior hippocampus (HPC) as the seeds, we calculated their connectivity with the whole brain using the seed-based static functional connectivity (sFC) and dynamic FC (dFC) approaches. We found that the sFC and dFC between the anterior HPC and supramarginal gyrus, sFC or dFC between posterior HPC and middle cingulate cortex, inferior parietal gyrus, angular gyrus, posterior cerebellum, medial superior frontal gyrus were increased after the social navigation task. These alterations were related to social cognition of tracking location in the social navigation. Moreover, participants who had more social support or less neuroticism showed a greater increase in hippocampal connectivity. These findings may highlight a more important role of the posterior hippocampal circuit in the social navigation, which is crucial for social cognition.

The Action Cycle Theory of Perception and Mental Imagery

The Action Cycle Theory (ACT) is an enactive theory of the perception and a mental imagery system that is comprised of six modules: Schemata, Objects, Actions, Affect, Goals and Others' Behavior. The evidence supporting these six connected modules is reviewed in light of research on mental imagery vividness. The six modules and their interconnections receive empirical support from a wide range of studies. All six modules of perception and mental imagery are influenced by individual differences in vividness. Real-world applications of ACT show interesting potential to improve human wellbeing in both healthy people and patients. Mental imagery can be applied in creative ways to make new collective goals and actions for change that are necessary to maximize the future prospects of the planet.

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'.

DREADD-inactivation of dorsal CA1 pyramidal neurons in mice impairs retrieval of object and spatial memories

The hippocampus, a medial temporal lobe brain region, is critical for the consolidation of information from short-term memory into long-term episodic memory and for spatial memory that enables navigation. Hippocampal damage in humans has been linked to amnesia and memory loss, characteristic of Alzheimer's disease and other dementias. Numerous studies indicate that the rodent hippocampus contributes significantly to long-term memory for spatial and nonspatial information. For example, muscimol-induced depression of CA1 neuronal activity in the dorsal hippocampus impairs the encoding, consolidation, and retrieval of nonspatial object memory in mice. Here, a chemogenetic designer receptor exclusively activated by designer drugs (DREADDs) approach was used to test the selective involvement of CA1 pyramidal neurons in memory retrieval for objects and for spatial location in a cohort of male C57BL/6J mice. Activation of the inhibitory (hM4Di) DREADDs receptor expressed in CA1 neurons significantly impaired the retrieval of object memory in the spontaneous object recognition task and of spatial memory in the Morris water maze. Silencing of CA1 neuronal activity in hM4Di-expressing mice was confirmed by comparing Fos expression in vehicle- and clozapine-N-oxide-treated mice after exploration of a novel environment. Histological analyses revealed that expression of the hM4Di receptor was limited to CA1 neurons of the dorsal hippocampus. These results suggest that a common subset of CA1 neurons (i.e., those expressing hM4Di receptors) in mouse hippocampus contributed to the retrieval of long-term memory for nonspatial and spatial information. Our findings support the view that the contribution of the rodent hippocampus is like that of the primate hippocampus, specifically essential for global memory. Our results further validate mice as a suitable model system to study the neurobiological mechanisms of human episodic memory, but also in developing treatments and understanding the underlying causes of diseases affecting long-term memory, such as Alzheimer's disease.

Exploring the sociodemographic, clinical and neuropsychological factors associated with relational memory in schizophrenia

INTRODUCTION

The Transverse Patterning (TP) task has been used to measure episodic relational memory (RM) deficits in clinical populations. Individuals with schizophrenia often fail to learn TP with standard, and sometimes extensive training. Identifying the differences between TP learners and non-learners can improve our understanding of successful TP performance and its underlying mechanisms, which may help improve interventions aimed at ameliorating RM performance. We investigated sociodemographic, clinical and neuropsychological factors associated with TP performance in schizophrenia.

METHODS

Sixty-six participants with schizophrenia completed a semantically rich and a relational-binding dependent version of the TP task and reported on their task awareness and strategy use.

RESULTS

Twenty-six participants failed to learn the task rules after extensive training. Learners had superior verbal, visual and working memory, executive functions and overall cognitive functioning compared to non-learners. Learners also had superior awareness of task rules and pairs relationships and used elaborated cognitive strategies more often.

CONCLUSIONS

Our results support previous findings that some individuals with schizophrenia show RM impairment even with extensive TP training. We shed light on neuropsychological and metacognitive factors associated with TP performance. This knowledge could enhance interventions targeted to improve relational memory in schizophrenia when extensive training fails.

Hippocampal non-theta state: The "Janus face" of information processing

The vast majority of studies on hippocampal rhythms have been conducted on animals or humans in situations where their attention was focused on external stimuli or solving cognitive tasks. These studies formed the basis for the idea that rhythmical activity coordinates the work of neurons during information processing. However, at rest, when attention is not directed to external stimuli, brain rhythms do not disappear, although the parameters of oscillatory activity change. What is the functional load of rhythmical activity at rest? Hippocampal oscillatory activity during rest is called the non-theta state, as opposed to the theta state, a characteristic activity during active behavior. We dedicate our review to discussing the present state of the art in the research of the non-theta state. The key provisions of the review are as follows: (1) the non-theta state has its own characteristics of oscillatory and neuronal activity; (2) hippocampal non-theta state is possibly caused and maintained by change of rhythmicity of medial septal input under the influence of raphe nuclei; (3) there is no consensus in the literature about cognitive functions of the non-theta-non-ripple state; and (4) the antagonistic relationship between theta and delta rhythms observed in rodents is not always observed in humans. Most attention is paid to the non-theta-non-ripple state, since this aspect of hippocampal activity has not been investigated properly and discussed in reviews.

Place cells dynamically refine grid cell activities to reduce error accumulation during path integration in a continuous attractor model

Navigation is one of the most fundamental skills of animals. During spatial navigation, grid cells in the medial entorhinal cortex process speed and direction of the animal to map the environment. Hippocampal place cells, in turn, encode place using sensory signals and reduce the accumulated error of grid cells for path integration. Although both cell types are part of the path integration system, the dynamic relationship between place and grid cells and the error reduction mechanism is yet to be understood. We implemented a realistic model of grid cells based on a continuous attractor model. The grid cell model was coupled to a place cell model to address their dynamic relationship during a simulated animal's exploration of a square arena. The grid cell model processed the animal's velocity and place field information from place cells. Place cells incorporated salient visual features and proximity information with input from grid cells to define their place fields. Grid cells had similar spatial phases but a diversity of spacings and orientations. To determine the role of place cells in error reduction for path integration, the animal's position estimates were decoded from grid cell activities with and without the place field input. We found that the accumulated error was reduced as place fields emerged during the exploration. Place fields closer to the animal's current location contributed more to the error reduction than remote place fields. Place cells' fields encoding space could function as spatial anchoring signals for precise path integration by grid cells.

Improved Visual SLAM Using Semantic Segmentation and Layout Estimation

The technological advances in computational systems have enabled very complex computer vision and machine learning approaches to perform efficiently and accurately. These new approaches can be considered a new set of tools to reshape the visual SLAM solutions. We present an investigation of the latest neuroscientific research that explains how the human brain can accurately navigate and map unknown environments. The accuracy suggests that human navigation is not affected by traditional visual odometry drifts resulting from tracking visual features. It utilises the geometrical structures of the surrounding objects within the navigated space. The identified objects and space geometrical shapes anchor the estimated space representation and mitigate the overall drift. Inspired by the human brain’s navigation techniques, this paper presents our efforts to incorporate two machine learning techniques into a VSLAM solution: semantic segmentation and layout estimation to imitate human abilities to map new environments. The proposed system benefits from the geometrical relations between the corner points of the cuboid environments to improve the accuracy of trajectory estimation. Moreover, the implemented SLAM solution semantically groups the map points and then tracks each group independently to limit the system drift. The implemented solution yielded higher trajectory accuracy and immunity to large pure rotations.

Functional neuronal circuitry and oscillatory dynamics in human brain organoids

Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.

Toward Cognitive Navigation: Design and Implementation of a Biologically Inspired Head Direction Cell Network

As a vital cognitive function of animals, the navigation skill is first built on the accurate perception of the directional heading in the environment. Head direction cells (HDCs), found in the limbic system of animals, are proven to play an important role in identifying the directional heading allocentrically in the horizontal plane, independent of the animal's location and the ambient conditions of the environment. However, practical HDC models that can be implemented in robotic applications are rarely investigated, especially those that are biologically plausible and yet applicable to the real world. In this article, we propose a computational HDC network that is consistent with several neurophysiological findings concerning biological HDCs and then implement it in robotic navigation tasks. The HDC network keeps a representation of the directional heading only relying on the angular velocity as an input. We examine the proposed HDC model in extensive simulations and real-world experiments and demonstrate its excellent performance in terms of accuracy and real-time capability.

The physiological control of eating: signals, neurons, and networks

During the past 30 yr, investigating the physiology of eating behaviors has generated a truly vast literature. This is fueled in part by a dramatic increase in obesity and its comorbidities that has coincided with an ever increasing sophistication of genetically based manipulations. These techniques have produced results with a remarkable degree of cell specificity, particularly at the cell signaling level, and have played a lead role in advancing the field. However, putting these findings into a brain-wide context that connects physiological signals and neurons to behavior and somatic physiology requires a thorough consideration of neuronal connections: a field that has also seen an extraordinary technological revolution. Our goal is to present a comprehensive and balanced assessment of how physiological signals associated with energy homeostasis interact at many brain levels to control eating behaviors. A major theme is that these signals engage sets of interacting neural networks throughout the brain that are defined by specific neural connections. We begin by discussing some fundamental concepts, including ones that still engender vigorous debate, that provide the necessary frameworks for understanding how the brain controls meal initiation and termination. These include key word definitions, ATP availability as the pivotal regulated variable in energy homeostasis, neuropeptide signaling, homeostatic and hedonic eating, and meal structure. Within this context, we discuss network models of how key regions in the endbrain (or telencephalon), hypothalamus, hindbrain, medulla, vagus nerve, and spinal cord work together with the gastrointestinal tract to enable the complex motor events that permit animals to eat in diverse situations.

Spatialization of Time in the Entorhinal-Hippocampal System

The functional role of the entorhinal-hippocampal system has been a long withstanding mystery. One key theory that has become most popular is that the entorhinal-hippocampal system represents space to facilitate navigation in one's surroundings. In this Perspective article, I introduce a novel idea that undermines the inherent uniqueness of spatial information in favor of time driving entorhinal-hippocampal activity. Specifically, by spatializing events that occur in succession (i.e., across time), the entorhinal-hippocampal system is critical for all types of cognitive representations. I back up this argument with empirical evidence that hints at a role for the entorhinal-hippocampal system in non-spatial representation, and computational models of the logarithmic compression of time in the brain.

The hippocampal formation and action at a distance

The question of why our conceptions of space and time are intertwined with memory in the hippocampal formation is at the forefront of much current theorizing about this brain system. In this article I argue that animals bridge spatial and temporal gaps through the creation of internal models that allow them to act on the basis of things that exist in a distant place and/or existed at a different time. The hippocampal formation plays a critical role in these processes by stitching together spatiotemporally disparate entities and events. It does this by 1) constructing cognitive maps that represent extended spatial contexts, incorporating and linking aspects of an environment that may never have been experienced together; 2) creating neural trajectories that link the parts of an event, whether they occur in close temporal proximity or not, enabling the construction of event representations even when elements of that event were experienced at quite different times; and 3) using these maps and trajectories to simulate possible futures. As a function of these hippocampally driven processes, our subjective sense of both space and time are interwoven constructions of the mind, much as the philosopher Immanuel Kant postulated.

In search of a naturalistic neuroimaging approach: Exploration of general feasibility through the case of VR-fMRI and application in the domain of episodic memory

Virtual Reality (VR) is an increasingly widespread tool for research as it allows the creation of experiments taking place in multimodal and daily-life-like environments, while keeping a strong experimental control. Adding neuroimaging to VR leads to a better understanding of the underlying brain networks activated during a naturalistic task, whether for research purposes or rehabilitation. The present paper focuses on the specific use of concurrent VR and fMRI and its technical challenges and feasibility, with a brief examination of the general existing solutions. Following the PRISMA guidelines, the review investigates the particular case of how VR-fMRI has explored episodic memory so far, with a comparison of object- and place-based episodic memory. This review confirms the involvement of cerebral regions well-known to be implicated in episodic memory and unravels other regions devoted to bodily and narrative aspects of the self, promoting new avenues of research in the domain of naturalistic episodic memory. Future studies should develop more immersive and interactive virtual neuroimaging features to increase ecological and embodied neurocognition aspects.

V1 as an egocentric cognitive map

We typically distinguish between V1 as an egocentric perceptual map and the hippocampus as an allocentric cognitive map. In this article, we argue that V1 also functions as a post-perceptual egocentric cognitive map. We argue that three well-documented functions of V1, namely (i) the estimation of distance, (ii) the estimation of size, and (iii) multisensory integration, are better understood as post-perceptual cognitive inferences. This argument has two important implications. First, we argue that V1 must function as the neural correlates of the visual perception/cognition distinction and suggest how this can be accommodated by V1's laminar structure. Second, we use this insight to propose a low-level account of visual consciousness in contrast to mid-level accounts (recurrent processing theory; integrated information theory) and higher-level accounts (higher-order thought; global workspace theory). Detection thresholds have been traditionally used to rule out such an approach, but we explain why it is a mistake to equate visibility (and therefore the presence/absence of visual experience) with detection thresholds.

Effects of early noise exposure on hippocampal-dependent behaviors during adolescence in male rats: influence of different housing conditions

Central nervous system (CNS) development is a very complex process that can be altered by environmental stimuli such as noise, which can generate long-term auditory and/or extra-auditory impairments. We have previously reported that early noise exposure can induce hippocampus-related behavioral alterations in postnatal day (PND) 28 adolescent rats. Furthermore, we recently found biochemical modifications in the hippocampus (HC) of these animals that seemed to endure even in more mature animals (i.e. PND35) and that have not been studied along with behavioral correlates. Thus, the aim of this work was to reveal novel data about the effects of early noise exposure on hippocampal-dependent behaviors in more mature animals. Additionally, extended enriched environment (EE) housing was evaluated to determine its capacity to induce behavioral modifications, either by its neuroprotective ability or the greater stimulation that it generates. Male Wistar rats were exposed to different noise schemes at PND7 or PND15. Upon weaning, some animals were transferred to EE whereas others were kept in standard cages. At PND35, different hippocampal-dependent behavioral assessments were performed. Results showed noise-induced behavioral changes that differed according to the scheme and age of exposure used. In addition, housing in an EE was effective either in preventing some of these changes or in inducing the appearance of new behavioral modifications. These findings suggest that CNS development would be sensitive to the effects of different type of environmental stimuli such as noise or enriched housing, leading to maladaptive behavioral changes that last even until adolescence.

The Role of the Posterior Hypothalamus in the Modulation and Production of Rhythmic Theta Oscillations

Theta rhythm recorded as an extracellular synchronous field potential is generated in a number of brain sites including the hippocampus. The physiological occurrence of hippocampal theta rhythm is associated with the activation of a number of structures forming the ascending brainstem-hippocampal synchronizing pathway. Experimental evidence indicates that the supramammillary nucleus and posterior hypothalamic nuclei, considered as the posterior hypothalamic area, comprise a critical node of this ascending pathway. The posterior hypothalamic area plays an important role in movement control, place-learning, memory processing, emotion and arousal. In the light of multiplicity of functions of the posterior hypothalamic area and the influence of theta field oscillations on a number of neural processes, it is the authors' intent to summarize the data concerning the involvement of the supramammillary nucleus and posterior hypothalamic nuclei in the modulation of limbic theta rhythmicity as well as the ability of these brain structures to independently generate theta rhythmicity.

Do hippocampal pyramidal cells respond to nonspatial stimuli?

There are currently a number of theories of rodent hippocampal function. They fall into two major groups that differ in the role they impute to space in hippocampal information processing. On one hand, the cognitive map theory sees space as crucial and central, with other types of nonspatial information embedded in a primary spatial framework. On the other hand, most other theories see the function of the hippocampal formation as broader, treating all types of information as equivalent and concentrating on the processes carried out irrespective of the specific material being represented, stored, and manipulated. One crucial difference, therefore, is the extent to which theories see hippocampal pyramidal cells as representing nonspatial information independently of a spatial framework. Studies have reported the existence of single hippocampal unit responses to nonspatial stimuli, both to simple sensory inputs as well as to more complex stimuli such as objects, conspecifics, rewards, and time, and these findings been interpreted as evidence in favor of a broader hippocampal function. Alternatively, these nonspatial responses might actually be feature-in-place signals where the spatial nature of the response has been masked by the fact that the objects or features were only presented in one location or one spatial context. In this article, we argue that when tested in multiple locations, the hippocampal response to nonspatial stimuli is almost invariably dependent on the animal's location. Looked at collectively, the data provide strong support for the cognitive map theory.

Spatial Memory in a Spiking Neural Network with Robot Embodiment

Cognitive maps and spatial memory are fundamental paradigms of brain functioning. Here, we present a spiking neural network (SNN) capable of generating an internal representation of the external environment and implementing spatial memory. The SNN initially has a non-specific architecture, which is then shaped by Hebbian-type synaptic plasticity. The network receives stimuli at specific loci, while the memory retrieval operates as a functional SNN response in the form of population bursts. The SNN function is explored through its embodiment in a robot moving in an arena with safe and dangerous zones. We propose a measure of the global network memory using the synaptic vector field approach to validate results and calculate information characteristics, including learning curves. We show that after training, the SNN can effectively control the robot’s cognitive behavior, allowing it to avoid dangerous regions in the arena. However, the learning is not perfect. The robot eventually visits dangerous areas. Such behavior, also observed in animals, enables relearning in time-evolving environments. If a dangerous zone moves into another place, the SNN remaps positive and negative areas, allowing escaping the catastrophic interference phenomenon known for some AI architectures. Thus, the robot adapts to changing world.

Region-Dependent Modulation of Neural Plasticity in Limbic Structures Early after Traumatic Brain Injury

Traumatic brain injury (TBI)-induced disruptions in synaptic function within brain regions and across networks in the limbic system may underlie a vulnerability for maladaptive plasticity and contribute to behavioral comorbidities. In this study we measured how synaptic proteins respond to lateral fluid percussion injury (FPI) brain regions known to regulate emotion and memory, including the basolateral amygdala (BLA), dorsal and ventral hippocampus (DH, VH), and medial prefrontal cortex (PFC). We investigated proteins involved in regulating plasticity, including synaptic glutamatergic a-amino-3-hydroxy5-methyl-4-isoxazolepropionic acid (AMPA; GluA1, GluA2) and N-methyl-D-aspartate (NMDA; NR1, NR2A, NR2B) receptor subunits as well as inhibitory gamma-aminobutyric acid (GABA) synthetic enzymes (GAD67, GAD65) via western blot. Adult male rats received a mild-moderate lateral FPI or sham surgery and ipsi- and contralateral BLA, DH, VH, and PFC were collected 6 h, 24 h, 48 h, and 7 days post-injury. In the ipsilateral BLA, there was a significant decrease in NR1 and GluA2 24 h after injury, whereas NR2A and NR2B were increased in the contralateral BLA at 48 h compared with sham. GAD67 was increased ipsilaterally at 24 h, but decreased contralaterally at 48 h in the BLA. In the DH, both NMDA (NR2A, NR2B) and GABA-synthetic (GAD65, GAD67) proteins were increased acutely at 6 h compared with sham. GAD67 was also robustly increased in the ipsilateral VH at 6 h. In the contralateral VH, NR2A significantly increased between 6 h and 24 h after FPI, whereas GAD65 was decreased across the same time-points in the contralateral VH. In the medial PFC at 24 h we saw bilateral increases in GAD67 and a contralateral decrease in GluA1. Later, there was a significant decrease in GAD67 in contralateral PFC from 48 h to 7 days post-injury. Collectively, these data suggest that lateral FPI causes a dynamic homeostatic response across limbic networks, leading to an imbalance of the proteins involved in plasticity in neural systems underlying cognitive and emotional regulation.

Suppression of Circadian Timing and Its Impact on the Hippocampus

In this article, I describe the development of the disruptive phase shift (DPS) protocol and its utility for studying how circadian dysfunction impacts memory processing in the hippocampus. The suprachiasmatic nucleus (SCN) of the Siberian hamster is a labile circadian pacemaker that is easily rendered arrhythmic (ARR) by a simple manipulation of ambient lighting. The DPS protocol uses room lighting to administer a phase-advancing signal followed by a phase-delaying signal within one circadian cycle to suppress clock gene rhythms in the SCN. The main advantage of this model for inducing arrhythmia is that the DPS protocol is non-invasive; circadian rhythms are eliminated while leaving the animals neurologically and genetically intact. In the area of learning and memory, DPS arrhythmia produces much different results than arrhythmia by surgical ablation of the SCN. As I show, SCN ablation has little to no effect on memory. By contrast, DPS hamsters have an intact, but arrhythmic, SCN which produces severe deficits in memory tasks that are accompanied by fragmentation of electroencephalographic theta oscillations, increased synaptic inhibition in hippocampal circuits, and diminished responsiveness to cholinergic signaling in the dentate gyrus of the hippocampus. The studies reviewed here show that DPS hamsters are a promising model for translational studies of adult onset circadian dysfunction in humans.

Single-trial regression of spatial exploration behavior indicates posterior EEG alpha modulation to reflect egocentric coding

Learning to navigate uncharted terrain is a key cognitive ability that emerges as a deeply embodied process, with eye movements and locomotion proving most useful to sample the environment. We studied healthy human participants during active spatial learning of room-scale virtual reality (VR) mazes. In the invisible maze task, participants wearing a wireless electroencephalography (EEG) headset were free to explore their surroundings, only given the objective to build and foster a mental spatial representation of their environment. Spatial uncertainty was resolved by touching otherwise invisible walls that were briefly rendered visible inside VR, similar to finding your way in the dark. We showcase the capabilities of mobile brain/body imaging using VR, demonstrating several analysis approaches based on general linear models (GLMs) to reveal behavior-dependent brain dynamics. Confirming spatial learning via drawn sketch maps, we employed motion capture to image spatial exploration behavior describing a shift from initial exploration to subsequent exploitation of the mental representation. Using independent component analysis, the current work specifically targeted oscillations in response to wall touches reflecting isolated spatial learning events arising in deep posterior EEG sources located in the retrosplenial complex. Single-trial regression identified significant modulation of alpha oscillations by the immediate, egocentric, exploration behavior. When encountering novel walls, as well as with increasing walking distance between subsequent touches when encountering novel walls, alpha power decreased. We conclude that these oscillations play a prominent role during egocentric evidencing of allocentric spatial hypotheses.

Basal Ganglia and Thalamic Contributions to Language Function: Insights from A Parallel Distributed Processing Perspective

Cerebral representations are encoded as patterns of activity involving billions of neurons. Parallel distributed processing (PDP) across these neuronal populations provides the basis for a number of emergent properties: 1) processing occurs and knowledge (long term memories) is stored (as synaptic connection strengths) in exactly the same networks; 2) networks have the capacity for setting into stable attractor states corresponding to concepts, symbols, implicit rules, or data transformations; 3) networks provide the scaffold for the acquisition of knowledge but knowledge is acquired through experience; 4) PDP networks are adept at incorporating the statistical regularities of experience as well as frequency and age of acquisition effects; 5) networks enable content-addressable memory; 6) because knowledge is distributed throughout networks, they exhibit the property of graceful degradation; 7) networks intrinsically provide the capacity for inference. This paper details the features of the basal ganglia and thalamic systems (recurrent and distributed connectivity) that support PDP. The PDP lens and an understanding of the attractor trench dynamics of the basal ganglia provide a natural explanation for the peculiar dysfunctions of Parkinson's disease and the mechanisms by which dopamine deficiency is causal. The PDP lens, coupled with the fact that the basal ganglia of humans bears strong homology to the basal ganglia of lampreys and the central complex of arthropods, reveals that the fundamental function of the basal ganglia is computational and involves the reduction of the vast dimensionality of a complex multi-dimensional array of sensorimotor input into the optimal choice from a small repertoire of behavioral options - the essence of reactive intention (automatic responses to sensory input). There is strong evidence that the sensorimotor basal ganglia make no contributions to cognitive or motor function in humans but can cause serious dysfunction when pathological. It appears that humans, through the course of evolution, have developed cortical capacities (working memory and volitional and reactive attention) for managing sensory input, however complex, that obviate the need for the basal ganglia. The functions of the dorsal tier thalamus, however, even viewed with an understanding of the properties of population encoded representations, remain somewhat more obscure. Possibilities include the enabling of attractor state constellations that optimize function by taking advantage of simultaneous input from multiple cortical areas; selective engagement of cortical representations; and support of the gamma frequency synchrony that enables binding of the multiple network representations that comprise a full concept representation.

Link Between Topographic Memory and the Combined Presentation of ADHD (ADHD-C): A Pilot Study

Background: Topographic memory is the ability to reach various places by recognizing spatial layouts and getting oriented in familiar environments. It involves several different cognitive abilities, in particular executive functions (EF), such as attention, working memory, and planning. Children with attention deficit hyperactivity disorder (ADHD) show impairments in inhibitory control, regulation of attention, planning, and working memory. Aim: The aim of this study was to evaluate the topographic memory in children with ADHD-combined subtype (ADHD-C). Method: Fifteen children (8-10 years) with a diagnosis of ADHD-C (DSM-5) (ADHD-C group) were compared to 15 children with typical development (TD group) of the same age. All children performed Raven's colored progressive matrices (CPM) test to obtain a measure related with cognitive functioning. The walking Corsi test (WalCT), a large-scale version of the Corsi block-tapping test, was used to assess topographic memory in experimental environment. Results: A higher impairment was observed in ADHD-C than TD with significant differences in the WalCT, in particular on the topographic short-term memory (TSTM) task, on the topographic learning (TL) task, and on the repetition number (RN) task during the TL task. Perseverative errors were reported in performing the square-sequence in the WalCT. Zero-order correlations showed a positive correlation between TSTM and auditory attention, and memory of design of NEPSY-II and digit span of WISC-IV. No statistically significant differences were found between the ADHD-C group and TD group in the TL task in the WalCT condition. Conclusion: In ADHD-C, initial topographic learning was compromised whereas the long-term retention of learned topographical material seemed to not be impaired. In particular, these impairments seem to be linked with difficulties in sustained attention, in spatial memory for novel visual materials, in a poor working memory, and in perseverative behaviors.

Neural mechanisms of emotions, alexithymia, and depression

This chapter brings the powerful conceptual tools of the science of parallel distributed processing (PDP) to bear on the cognitive neuroscience of emotions discussed in this book. Cerebral representations are encoded as patterns of activity involving billions of neurons. PDP across these neuronal populations provides the basis for a number of emergent properties: (1) processing occurs and knowledge (long term memories) is stored (as synaptic connection strengths) in exactly the same networks; (2) networks have the capacity for setting into stable attractor states corresponding to concepts, symbols, implicit rules, or data transformations; (3) networks provide the scaffold for the acquisition of knowledge, but knowledge is acquired through experience; (4) PDP networks are adept at incorporating the statistical regularities of experience as well as frequency and age of acquisition effects; (5) networks enable content-addressable memory; (6) because knowledge is distributed throughout networks, they exhibit the property of graceful degradation; (7) networks intrinsically provide the capacity for inference. With this perspective, I propose a new model of emotional function that reasonably accounts for the effects of focal lesions at various points (insula, orbitofrontal cortex, convexity cortex, and intervening white matter) due to stroke, trauma, surgery, and degenerative disease, as reflected in disorders of affective prosody, facial emotional comprehension and expression, emotional behavior, and personality. I consider a modification of the James Lange theory that takes into account the role of a lifetime of subjective knowledge acquisition by the orbitofrontal cortex. Alexithymia is conceptualized as a disorder of the insula/orbitofrontal cortex/dorsolateral prefrontal cortex (DL-PFC) system, the function of which can be disrupted by degradation of knowledge at a number of different locations. Finally, I consider the possibility that depression reflects pathological learning involving the medial and lateral orbitofrontal cortices such that there is a pathologic engagement of the two regions, as suggested by Rolls. I conclude with a consideration of the peculiar responsivity of depression to serotonergic and noradrenergic agents, as well as to surgical orbitofrontal undercutting, and what that might be telling us about the mechanisms of depression and its treatment.

NavWell: A simplified virtual-reality platform for spatial navigation and memory experiments

Being able to navigate, recall important locations, and find the way home are critical skills, essential for survival for both humans and animals. These skills can be examined in the laboratory using the Morris water maze, often considered the gold standard test of animal navigation. In this task, animals are required to locate and recall the location of an escape platform hidden in a pool filled with water. Because animals can not see the platform directly, they must use various landmarks in the environment to escape. With recent advances in technology and virtual reality (VR), many tasks originally used in the animal literature can now be translated for human studies. The virtual water maze task is no exception. However, a number of issues are associated with these mazes, including cost, lack of flexibility, and lack of standardization in terms of experimental designs and procedures. Here we present a virtual water maze system (NavWell) that is readily downloadable and free to use. The system allows for the easy design of experiments and the testing of participants on a desktop computer or fully immersive VR environment. The data from four independent experiments are presented in order to validate the software. From these experiments, a set of procedures for use with a number of well-known memory tests is suggested. This potentially can help with the standardization of navigational research and with navigational testing in the clinic or in an educational environment. Finally, we discuss the limitations of the software and plans for its development and future use.

Toward a Unified Framework for Cognitive Maps

In this study, we integrated neural encoding and decoding into a unified framework for spatial information processing in the brain. Specifically, the neural representations of self-location in the hippocampus (HPC) and entorhinal cortex (EC) play crucial roles in spatial navigation. Intriguingly, these neural representations in these neighboring brain areas show stark differences. Whereas the place cells in the HPC fire as a unimodal function of spatial location, the grid cells in the EC show periodic tuning curves with different periods for different subpopulations (called modules). By combining an encoding model for this modular neural representation and a realistic decoding model based on belief propagation, we investigated the manner in which self-location is encoded by neurons in the EC and then decoded by downstream neurons in the HPC. Through the results of numerical simulations, we first show the positive synergy effects of the modular structure in the EC. The modular structure introduces more coupling between heterogeneous modules with different periodicities, which provides increased error-correcting capabilities. This is also demonstrated through a comparison of the beliefs produced for decoding two- and four-module codes. Whereas the former resulted in a complete decoding failure, the latter correctly recovered the self-location even from the same inputs. Further analysis of belief propagation during decoding revealed complex dynamics in information updates due to interactions among multiple modules having diverse scales. Therefore, the proposed unified framework allows one to investigate the overall flow of spatial information, closing the loop of encoding and decoding self-location in the brain.

Differences in reward biased spatial representations in the lateral septum and hippocampus

The lateral septum (LS), which is innervated by the hippocampus, is known to represent spatial information. However, the details of place representation in the LS, and whether this place information is combined with reward signaling, remains unknown. We simultaneously recorded from rat CA1 and caudodorsal lateral septum in rat during a rewarded navigation task and compared spatial firing in the two areas. While LS place cells are less numerous than in hippocampus, they are similar to the hippocampus in field size and number of fields per cell, but with field shape and center distributions that are more skewed toward reward. Spike cross-correlations between the hippocampus and LS are greatest for cells that have reward-proximate place fields, suggesting a role for the LS in relaying task-relevant hippocampal spatial information to downstream areas, such as the VTA.

Deficit in working memory and abnormal behavioral tactics in dopamine transporter knockout rats during training in the 8-arm maze

Understanding the role of the dopamine system in learning and memory processes is very important for uncovering central mechanisms underlying complex behavioral responses that can be impaired in patients with neuropsychiatric disorders caused by dopamine system dysfunction. One of the most useful animal models for dopaminergic dysregulation is the strain of dopamine transporter knockout (DAT-KO) rats that have no dopamine re-uptake and thus elevated extracellular dopamine levels. It is known that dopamine is involved in various cognitive processes such as learning, memory and attention. This investigation was focused on the ability of DAT-KO rats to learn and perform a behavioral task in the 8-arm radial maze test. It was found that DAT-KO rats are able to learn the behavioral task, but the level of task performance did not reach that of WT group. The behavioral tactics used by animals during training significantly differ in mutants. The behavioral tactics used by DAT-KO rats involved perseverations and resulted in worse task fulfillment in comparison to wild-type controls. The data obtained indicate that deficient dopamine reuptake results in an impairment of working memory and perseverative behavioral tactics in DAT-KO rats.

Neural Population Dynamics and Cognitive Function

Representations in the brain are encoded as patterns of activity of large populations of neurons. The science of population encoded representations, also known as parallel distributed processing (PDP), achieves neurological verisimilitude and has been able to account for a large number of cognitive phenomena in normal people, including reaction times (and reading latencies), stimulus recognition, the effect of stimulus salience on attention, perceptual invariance, simultaneous egocentric and allocentric visual processing, top-down/bottom-up processing, language errors, the effect of statistical regularities of experience, frequency, and age of acquisition, instantiation of rules and symbols, content addressable memory and the capacity for pattern completion, preservation of function in the face of noisy or distorted input, inference, parallel constraint satisfaction, the binding problem and gamma coherence, principles of hippocampal function, the location of knowledge in the brain, limitations in the scope and depth of knowledge acquired through experience, and Piagetian stages of cognitive development. PDP studies have been able to provide a coherent account for impairment in a variety of language functions resulting from stroke or dementia in a large number of languages and the phenomenon of graceful degradation observed in such studies. They have also made important contributions to our understanding of attention (including hemispatial neglect), emotional function, executive function, motor planning, visual processing, decision making, and neuroeconomics. The relationship of neural network population dynamics to electroencephalographic rhythms is starting to emerge. Nevertheless, PDP approaches have scarcely penetrated major areas of study of cognition, including neuropsychology and cognitive neuropsychology, as well as much of cognitive psychology. This article attempts to provide an overview of PDP principles and applications that addresses a broader audience.