A novel somatosensory spatial navigation system outside the hippocampal formation

Hierarchical Gradients of Encoded Spatial and Sensory Information in the Neocortex Are Attenuated by Dorsal Hippocampal Lesions

During navigation, the neocortex actively integrates learned spatial context with current sensory experience to guide behaviors. However, the relative encoding of spatial and sensorimotor information among cortical cells, and whether hippocampal feedback continues to modify these properties after learning, remains poorly understood. Thus, two-photon microscopy of male and female Thy1-GCaMP6s mice was used to longitudinally image neurons spanning superficial retrosplenial cortex and layers II-Va of primary and secondary motor cortices before and after bilateral dorsal hippocampal lesions. During behavior on a familiar cued treadmill, the locations of two obstacles were interchanged to decouple place-tuning from cue-tuning among position-correlated cells with fields at those locations. Subpopulations of place and cue cells each formed interareal gradients such that higher-level cortical regions exhibited higher fractions of place cells, whereas lower-level regions exhibited higher fractions of cue cells. Position-correlated cells in the motor cortex also formed translaminar gradients; more superficial cells were more likely to exhibit fields and were more sparsely and precisely tuned than deeper cells. After dorsal hippocampal lesions, a neural representation of the learned environment persisted, but retrosplenial cortex exhibited significantly increased cue-tuning, and, in motor cortices, both position-correlated cell recruitment and population activity at the unstable obstacle locations became more homogeneously elevated across laminae. Altogether, these results support that the hippocampus continues to modulate cortical responses in familiar environments, and the relative impact of descending feedback obeys hierarchical interareal and interlaminar gradients opposite to the flow of ascending sensory inputs.

Alterations in Gray Matter Structural Networks in Amnestic Mild Cognitive Impairment: A Source-Based Morphometry Study

Background

Amnestic mild cognitive impairment (aMCI), considered as the prodromal stage of Alzheimer's disease, is characterized by isolated memory impairment and cerebral gray matter volume (GMV) alterations. Previous structural MRI studies in aMCI have been mainly based on univariate statistics using voxel-based morphometry.

Objective

We investigated structural network differences between aMCI patients and cognitively normal older adults by using source-based morphometry, a multivariate approach that considers the relationship between voxels of various parts of the brain.

Methods

Ninety-one aMCI patients and 80 cognitively normal controls underwent structural MRI and neuropsychological assessment. Spatially independent components (ICs) that covaried between participants were estimated and a multivariate analysis of covariance was performed with ICs as dependent variables, diagnosis as independent variable, and age, sex, education level, and site as covariates.

Results

aMCI patients exhibited reduced GMV in the precentral, temporo-cerebellar, frontal, and temporal network, and increased GMV in the left superior parietal network compared to controls (pFWER < 0.05, Holm-Bonferroni correction). Moreover, we found that diagnosis, more specifically aMCI, moderated the positive relationship between occipital network and Mini-Mental State Examination scores (pFWER < 0.05, Holm-Bonferroni correction).

Conclusions

Our results showed GMV alterations in temporo-fronto-parieto-cerebellar networks in aMCI, extending previous results obtained with univariate approaches.

Electrophysiological signatures of veridical head direction in humans

Information about heading direction is critical for navigation as it provides the means to orient ourselves in space. However, given that veridical head-direction signals require physical rotation of the head and most human neuroimaging experiments depend upon fixing the head in position, little is known about how the human brain is tuned to such heading signals. Here we adress this by asking 52 healthy participants undergoing simultaneous electroencephalography and motion tracking recordings (split into two experiments) and 10 patients undergoing simultaneous intracranial electroencephalography and motion tracking recordings to complete a series of orientation tasks in which they made physical head rotations to target positions. We then used a series of forward encoding models and linear mixed-effects models to isolate electrophysiological activity that was specifically tuned to heading direction. We identified a robust posterior central signature that predicts changes in veridical head orientation after regressing out confounds including sensory input and muscular activity. Both source localization and intracranial analysis implicated the medial temporal lobe as the origin of this effect. Subsequent analyses disentangled head-direction signatures from signals relating to head rotation and those reflecting location-specific effects. Lastly, when directly comparing head direction and eye-gaze-related tuning, we found that the brain maintains both codes while actively navigating, with stronger tuning to head direction in the medial temporal lobe. Together, these results reveal a taxonomy of population-level head-direction signals within the human brain that is reminiscent of those reported in the single units of rodents.

Border cells without theta rhythmicity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is a key brain structure for higher cognitive functions such as decision-making and goal-directed behavior, many of which require awareness of spatial variables including one's current position within the surrounding environment. Although previous studies have reported spatially tuned activities in mPFC during memory-related trajectory, the spatial tuning of mPFC network during freely foraging behavior remains elusive. Here, we reveal geometric border or border-proximal representations from the neural activity of mPFC ensembles during naturally exploring behavior, with both allocentric and egocentric boundary responses. Unlike most of classical border cells in the medial entorhinal cortex (MEC) discharging along a single wall, a large majority of border cells in mPFC fire particularly along four walls. mPFC border cells generate new firing fields to external insert, and remain stable under darkness, across distinct shapes, and in novel environments. In contrast to hippocampal theta entrainment during spatial working memory tasks, mPFC border cells rarely exhibited theta rhythmicity during spontaneous locomotion behavior. These findings reveal spatially modulated activity in mPFC, supporting local computation for cognitive functions involving spatial context and contributing to a broad spatial tuning property of cortical circuits.

Cognitive maps and the magnetic sense in vertebrates

Navigation requires a network of neurons processing inputs from internally generated cues and external landmarks. Most studies on the neuronal basis of navigation in vertebrates have focused on rats and mice and the canonical senses vision, hearing, olfaction, and somatosensation. Some animals have evolved the ability to sense the Earth's magnetic field and use it for orientation. It can be expected that in these animals magnetic cues are integrated with other sensory cues in the cognitive map. We provide an overview of the behavioral evidence and brain regions involved in magnetic sensing in support of this idea, hoping that this will guide future experiments.

Cell-type-specific representation of spatial context in the rat prefrontal cortex

The ability to represent one's own position in relation to cues, goals, or threats is crucial to successful goal-directed behavior. Using optotagging in knock-in rats expressing Cre recombinase in parvalbumin (PV) neurons (PV-Cre rats), we demonstrate cell-type-specific encoding of spatial and movement variables in the medial prefrontal cortex (mPFC) during goal-directed reward seeking. Single neurons encoded the conjunction of the animal's spatial position and the run direction, referred to as the spatial context. The spatial context was most prominently represented by the inhibitory PV interneurons. Movement toward the reward was signified by increased local field potential (LFP) oscillations in the gamma band but this LFP signature was not related to the spatial information in the neuronal firing. The results highlight how spatial information is incorporated into cognitive operations in the mPFC. The presented PV-Cre line opens the door for expanded research approaches in rats.

Vestibular dysfunction leads to cognitive impairments: State of knowledge in the field and clinical perspectives (Review)

The vestibular system may have a critical role in the integration of sensory information and the maintenance of cognitive function. A dysfunction in the vestibular system has a significant impact on quality of life. Recent research has provided evidence of a connection between vestibular information and cognitive functions, such as spatial memory, navigation and attention. Although the exact mechanisms linking the vestibular system to cognition remain elusive, researchers have identified various pathways. Vestibular dysfunction may lead to the degeneration of cortical vestibular network regions and adversely affect synaptic plasticity and neurogenesis in the hippocampus, ultimately contributing to neuronal atrophy and cell death, resulting in memory and visuospatial deficits. Furthermore, the extent of cognitive impairment varies depending on the specific type of vestibular disease. In the present study, the current literature was reviewed, potential causal relationships between vestibular dysfunction and cognitive performance were discussed and directions for future research were proposed.

A persistent prefrontal reference frame across time and task rules

Behavior can be remarkably consistent, even over extended time periods, yet whether this is reflected in stable or 'drifting' neuronal responses to task features remains controversial. Here, we find a persistently active ensemble of neurons in the medial prefrontal cortex (mPFC) of mice that reliably maintains trajectory-specific tuning over several weeks while performing an olfaction-guided spatial memory task. This task-specific reference frame is stabilized during learning, upon which repeatedly active neurons show little representational drift and maintain their trajectory-specific tuning across long pauses in task exposure and across repeated changes in cue-target location pairings. These data thus suggest a 'core ensemble' of prefrontal neurons forming a reference frame of task-relevant space for the performance of consistent behavior over extended periods of time.

Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity

Many cognitive functions are represented as cell assemblies. In the case of spatial navigation, the population activity of place cells in the hippocampus and grid cells in the entorhinal cortex represents self-location in the environment. The brain cannot directly observe self-location information in the environment. Instead, it relies on sensory information and memory to estimate self-location. Therefore, estimating low-dimensional dynamics, such as the movement trajectory of an animal exploring its environment, from only the high-dimensional neural activity is important in deciphering the information represented in the brain. Most previous studies have estimated the low-dimensional dynamics (i.e., latent variables) behind neural activity by unsupervised learning with Bayesian population decoding using artificial neural networks or gaussian processes. Recently, persistent cohomology has been used to estimate latent variables from the phase information (i.e., circular coordinates) of manifolds created by neural activity. However, the advantages of persistent cohomology over Bayesian population decoding are not well understood. We compared persistent cohomology and Bayesian population decoding in estimating the animal location from simulated and actual grid cell population activity. We found that persistent cohomology can estimate the animal location with fewer neurons than Bayesian population decoding and robustly estimate the animal location from actual noisy data.

P2Y6 Receptor-Dependent Microglial Phagocytosis of Synapses during Development Regulates Synapse Density and Memory

During brain development, excess synapses are pruned (i.e., removed), in part by microglial phagocytosis, and dysregulated synaptic pruning can lead to behavioral deficits. The P2Y6 receptor (P2Y6R) is known to regulate microglial phagocytosis of neurons, and to regulate microglial phagocytosis of synapses in cell culture and in vivo during aging. However, currently it is unknown whether P2Y6R regulates synaptic pruning during development. Here, we show that P2Y6R KO mice of both sexes had strongly reduced microglial internalization of synaptic material, measured as Vglut1 within CD68-staining lysosomes of microglia at postnatal day 30 (P30), suggesting reduced microglial phagocytosis of synapses. Consistent with this, we found an increased density of synapses in the somatosensory cortex and the CA3 region and dentate gyrus of the hippocampus at P30. We also show that adult P2Y6R KO mice have impaired short- and long-term spatial memory and impaired short- and long-term recognition memory compared with WT mice, as measured by novel location recognition, novel object recognition, and Y-maze memory tests. Overall, this indicates that P2Y6R regulates microglial phagocytosis of synapses during development, and this contributes to memory capacity.SIGNIFICANCE STATEMENT The P2Y6 receptor (P2Y6R) is activated by uridine diphosphate released by neurons, inducing microglial phagocytosis of such neurons or synapses. We tested whether P2Y6R regulates developmental synaptic pruning in mice and found that P2Y6R KO mice have reduced synaptic material within microglial lysosomes, and increased synaptic density in the brains of postnatal day 30 mice, consistent with reduced synaptic pruning during development. We also found that adult P2Y6R KO mice had reduced memory, consistent with persistent deficits in brain function, resulting from impaired synaptic pruning. Overall, the results suggest that P2Y6R mediates microglial phagocytosis of synapses during development, and the absence of this results in memory deficits in the adult.

The neural ingredients for a language of thought are available

The classical notion of a 'language of thought' (LoT), advanced prominently by the philosopher Jerry Fodor, is an influential position in cognitive science whereby the mental representations underpinning thought are considered to be compositional and productive, enabling the construction of new complex thoughts from more primitive symbolic concepts. LoT theory has been challenged because a neural implementation has been deemed implausible. We disagree. Examples of critical computational ingredients needed for a neural implementation of a LoT have in fact been demonstrated, in particular in the hippocampal spatial navigation system of rodents. Here, we show that cell types found in spatial navigation (border cells, object cells, head-direction cells, etc.) provide key types of representation and computation required for the LoT, underscoring its neurobiological viability.

Multiple long-range projections convey position information to the agranular retrosplenial cortex

Neuronal signals encoding the animal's position widely modulate neocortical processing. While these signals are assumed to depend on hippocampal output, their origin has not been investigated directly. Here, we asked which brain region sends position information to the retrosplenial cortex (RSC), a key circuit for memory and navigation. We comprehensively characterized the long-range inputs to agranular RSC using two-photon axonal imaging in head-fixed mice performing a spatial task in darkness. Surprisingly, most long-range pathways convey position information, but with notable differences. Axons from the secondary motor and posterior parietal cortex transmit the most position information. By contrast, axons from the anterior cingulate and orbitofrontal cortex and thalamus convey substantially less position information. Axons from the primary and secondary visual cortex contribute negligibly. This demonstrates that the hippocampus is not the only source of position information. Instead, the RSC is a hub in a distributed brain network that shares position information.

Recruitment of grid-like responses in human entorhinal and piriform cortices by odor landmark-based navigation

Olfactory navigation is universal across the animal kingdom. Humans, however, have rarely been considered in this context. Here, we combined olfactometry techniques, virtual reality (VR) software, and neuroimaging methods to investigate whether humans can navigate an olfactory landscape by learning the spatial relationships among discrete odor cues and integrating this knowledge into a spatial map. Our data show that over time, participants improved their performance on the odor navigation task by taking more direct paths toward targets and completing more trials within a given time period. This suggests that humans can successfully navigate a complex odorous environment, reinforcing the notion of human olfactory navigation. fMRI data collected during the olfactory navigation task revealed the emergence of grid-like responses in entorhinal and piriform cortices that were attuned to the same grid orientation. This result implies the existence of a specialized olfactory grid network tasked with guiding spatial navigation based on odor landmarks.

Locating causal hubs of memory consolidation in spontaneous brain network in male mice

Memory consolidation after learning involves spontaneous, brain-wide network reorganization during rest and sleep, but how this is achieved is still poorly understood. Current theory suggests that the hippocampus is pivotal for this reshaping of connectivity. Using fMRI in male mice, we identify that a different set of spontaneous networks and their hubs are instrumental in consolidating memory during post-learning rest. We found that two types of spatial memory training invoke distinct functional connections, but that a network of the sensory cortex and subcortical areas is common for both tasks. Furthermore, learning increased brain-wide network integration, with the prefrontal, striatal and thalamic areas being influential for this network-level reconfiguration. Chemogenetic suppression of each hub identified after learning resulted in retrograde amnesia, confirming the behavioral significance. These results demonstrate the causal and functional roles of resting-state network hubs in memory consolidation and suggest that a distributed network beyond the hippocampus subserves this process.

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.

Spatial cognition: Uncovering navigational representations in prefrontal cortices

A new study identifies representations of navigational variables in six prefrontal regions in freely moving macaques, expanding our view of how the brain represents space outside of the broader hippocampal formation.

Widespread coding of navigational variables in prefrontal cortex

To navigate effectively, we must represent information about our location in the environment. Traditional research highlights the role of the hippocampal complex in this process. Spurred by recent research highlighting the widespread cortical encoding of cognitive and motor variables previously thought to have localized function, we hypothesized that navigational variables would be likewise encoded widely, especially in the prefrontal cortex, which is associated with volitional behavior. We recorded neural activity from six prefrontal regions while macaques performed a foraging task in an open enclosure. In all regions, we found strong encoding of allocentric position, allocentric head direction, boundary distance, and linear and angular velocity. These encodings were not accounted for by distance, time to reward, or motor factors. The strength of coding of all variables increased along a ventral-to-dorsal gradient. Together, these results argue that encoding of navigational variables is not localized to the hippocampus and support the hypothesis that navigation is continuous with other forms of flexible cognition in the service of action.

An automated, low-latency environment for studying the neural basis of behavior in freely moving rats

BACKGROUND

Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes).

RESULTS

To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding areas, multiple sound sources, high-resolution behavioral tracking, and simultaneous electrophysiological recordings. The paper provides detailed information about the construction of the RIFF and the software used to control it. To illustrate the flexibility of the RIFF, we describe two complex tasks implemented in the RIFF, a foraging task and a sound localization task. Rats quickly learned to obtain rewards in both tasks. Neurons in the auditory cortex as well as neurons in the auditory field in the posterior insula had sound-driven activity during behavior. Remarkably, neurons in both structures also showed sensitivity to non-auditory parameters such as location in the arena and head-to-body angle.

CONCLUSIONS

The RIFF provides insights into the cognitive capabilities and learning mechanisms of rats and opens the way to a better understanding of how brains control behavior. The ability to do so depends crucially on the combination of wireless electrophysiology and detailed behavioral documentation available in the RIFF.

Empirically validated theoretical analysis of visual-spatial perception under change of nervous system arousal

Introduction

Visual-spatial perception is a process for extracting the spatial relationship between objects in the environment. The changes in visual-spatial perception due to factors such as the activity of the sympathetic nervous system (hyperactivation) or parasympathetic nervous system (hypoactivation) can affect the internal representation of the external visual-spatial world. We formulated a quantitative model of the modulation of visual-perceptual space under action by hyperactivation or hypoactivation-inducing neuromodulating agents. We showed a Hill equation based relationship between neuromodulator agent concentration and alteration of visual-spatial perception utilizing the metric tensor to quantify the visual space.

Methods

We computed the dynamics of the psilocybin (hyperactivation-inducing agent) and chlorpromazine (hypoactivation-inducing agent) in brain tissue. Then, we validated our quantitative model by analyzing the findings of different independent behavioral studies where subjects were assessed for alterations in visual-spatial perception under the action of psilocybin and under chlorpromazine. To validate the neuronal correlates, we simulated the effect of the neuromodulating agent on the computational model of the grid-cell network, and also performed diffusion MRI-based tractography to find the neural tracts between the cortical areas involved: V2 and the entorhinal cortex.

Results

We applied our computational model to an experiment (where perceptual alterations were measured under psilocybin) and found that for n (Hill-coefficient) = 14.8 and k = 1.39, the theoretical prediction followed experimental observations very well (χ2 test robustly satisfied, p > 0.99). We predicted the outcome of another psilocybin-based experiment using these values (n = 14.8 and k = 1.39), whereby our prediction and experimental outcomes were well corroborated. Furthermore, we found that also under hypoactivation (chlorpromazine), the modulation of the visual-spatial perception follows our model. Moreover, we found neural tracts between the area V2 and entorhinal cortex, thus providing a possible brain network responsible for encoding visual-spatial perception. Thence, we simulated the altered grid-cell network activity, which was also found to follow the Hill equation.

Conclusion

We developed a computational model of visuospatial perceptual alterations under altered neural sympathetic/parasympathetic tone. We validated our model using analysis of behavioral studies, neuroimaging assessment, and neurocomputational evaluation. Our quantitative approach may be probed as a potential behavioral screening and monitoring methodology in neuropsychology to analyze perceptual misjudgment and mishaps by highly stressed workers.

Hippocampal conjunctive and complementary CA1 populations relate sensory events to movement

Hippocampal CA1 neurons respond to sensory stimuli during enforced immobility, movement, and their transitions in a new conveyor belt task. Head-fixed mice were exposed to light flashes or air streams while at rest, spontaneously moving, or running a fixed distance. Two-photon calcium imaging of CA1 neurons revealed that 62% of 3341 imaged cells were active during one or more of 20 sensorimotor events. Of these active cells, 17% were active for any given sensorimotor event, with a higher proportion during locomotion. The study found two types of cells: Conjunctive cells that were active across multiple events, and complementary cells that were active only during individual events, encoding novel sensorimotor events or their delayed repetitions. The configuration of these cells across changing sensorimotor events may signify the role of hippocampus in functional networks integrating sensory information with ongoing movement making it suitable for movement guidance.

Peripersonal encoding of forelimb proprioception in the mouse somatosensory cortex

Conscious perception of limb movements depends on proprioceptive neural responses in the somatosensory cortex. In contrast to tactile sensations, proprioceptive cortical coding is barely studied in the mammalian brain and practically non-existent in rodent research. To understand the cortical representation of this important sensory modality we developed a passive forelimb displacement paradigm in behaving mice and also trained them to perceptually discriminate where their limb is moved in space. We delineated the rodent proprioceptive cortex with wide-field calcium imaging and optogenetic silencing experiments during behavior. Our results reveal that proprioception is represented in both sensory and motor cortical areas. In addition, behavioral measurements and responses of layer 2/3 neurons imaged with two-photon microscopy reveal that passive limb movements are both perceived and encoded in the mouse cortex as a spatial direction vector that interfaces the limb with the body's peripersonal space.

Spatial coding in the hippocampus and hyperpallium of flying owls

The elucidation of spatial coding in the hippocampus requires exploring diverse animal species. While robust place-cells are found in the mammalian hippocampus, much less is known about spatial coding in the hippocampus of birds. Here we used a wireless-electrophysiology system to record single neurons in the hippocampus and other two dorsal pallial structures from freely flying barn owls (Tyto alba), a central-place nocturnal predator species with excellent navigational abilities. The owl's 3D position was monitored while it flew between perches. We found place cells-neurons that fired when the owl flew through a spatially restricted region in at least one direction-as well as neurons that encoded the direction of flight, and neurons that represented the owl's perching position between flights. Many neurons encoded combinations of position, direction, and perching. Spatial coding was maintained stable and invariant to lighting conditions. Place cells were observed in owls performing two different types of flying tasks, highlighting the generality of the result. Place coding was found in the anterior hippocampus and in the posterior part of the hyperpallium apicale, and to a lesser extent in the visual Wulst. The finding of place-cells in flying owls suggests commonalities in spatial coding across mammals and birds.

Effects of neuromodulation-inspired mechanisms on the performance of deep neural networks in a spatial learning task

In recent years, the biological underpinnings of adaptive learning have been modeled, leading to faster model convergence and various behavioral benefits in tasks including spatial navigation and cue-reward association. Furthermore, studies have investigated how the neuromodulatory system, a major driver of synaptic plasticity and state-dependent changes in the brain neuronal activities, plays a role in training deep neural networks (DNNs). In this study, we extended previous studies on neuromodulation-inspired DNNs and explored the effects of neuromodulatory components on learning and single unit activities in a spatial learning task. Under the multiscale neuromodulatory framework, plastic components, dropout probability modulation, and learning rate decay were added to the single unit, layer, and whole network levels of DNN models, respectively. We observed behavioral benefits including faster learning and smaller error of ambulation. We then concluded that neuromodulatory components can affect learning trajectories, outcomes, and single unit activities, in a component- and hyperparameter-dependent manner.

The involvement of ADAR1 in chronic unpredictable stress-induced cognitive impairment by targeting DARPP-32 with miR-874-3p in BALB/c mice

Introduction: Chronic stress exposure is the main environmental factor leading to cognitive impairment, but the detailed molecular mechanism is still unclear. Adenosine Deaminase acting on double-stranded RNA1(ADAR1) is involved in the occurrence of chronic stress-induced cognitive impairment. In addition, dopamine and Adenosine 3'5'-monophosphate-regulated phospho-protein (DARPP-32) gene variation affects cognitive function. Therefore, we hypothesized that ADAR1 plays a key role in chronic stress-induced cognitive impairment by acting on DARPP-32. Methods: In this study, postnatal 21-day-old male BALB/c mice were exposed to chronic unpredictable stressors. After that, the mice were treated with ADAR1 inducer/inhibitor. The cognitive ability and cerebral DARPP-32 protein expression of BALB/c mice were evaluated. In order to explore the link between ADAR1 and DARPP-32, the effects of ADAR1 high/low expression on DARPP-32 protein expression in vitro were detected. Results: ADAR1 inducer alleviates cognitive impairment and recovers decreased DARPP-32 protein expression of the hippocampus and prefrontal cortex in BALB/c mice with chronic unpredictable stress exposure. In vivo and in vitro studies confirm the results predicted by bio-informatics; that is, ADAR1 affects DARPP-32 expression via miR-874-3p. Discussion: The results in this study demonstrate that ADAR1 affects the expression of DARPP-32 via miR-874-3p, which is involved in the molecular mechanism of pathogenesis in chronic unpredictable stress-induced cognitive impairment. The new findings of this study provide a new therapeutic strategy for the prevention and treatment of stress cognitive impairment from epigenetics.

Excitatory-inhibitory recurrent dynamics produce robust visual grids and stable attractors

Spatially modulated grid cells have been recently found in the rat secondary visual cortex (V2) during active navigation. However, the computational mechanism and functional significance of V2 grid cells remain unknown. To address the knowledge gap, we train a biologically inspired excitatory-inhibitory recurrent neural network to perform a two-dimensional spatial navigation task with multisensory input. We find grid-like responses in both excitatory and inhibitory RNN units, which are robust with respect to spatial cues, dimensionality of visual input, and activation function. Population responses reveal a low-dimensional, torus-like manifold and attractor. We find a link between functional grid clusters with similar receptive fields and structured excitatory-to-excitatory connections. Additionally, multistable torus-like attractors emerged with increasing sparsity in inter- and intra-subnetwork connectivity. Finally, irregular grid patterns are found in recurrent neural network (RNN) units during a visual sequence recognition task. Together, our results suggest common computational mechanisms of V2 grid cells for spatial and non-spatial tasks.

Generalized Simultaneous Localization and Mapping (G-SLAM) as unification framework for natural and artificial intelligences: towards reverse engineering the hippocampal/entorhinal system and principles of high-level cognition

Simultaneous localization and mapping (SLAM) represents a fundamental problem for autonomous embodied systems, for which the hippocampal/entorhinal system (H/E-S) has been optimized over the course of evolution. We have developed a biologically-inspired SLAM architecture based on latent variable generative modeling within the Free Energy Principle and Active Inference (FEP-AI) framework, which affords flexible navigation and planning in mobile robots. We have primarily focused on attempting to reverse engineer H/E-S "design" properties, but here we consider ways in which SLAM principles from robotics may help us better understand nervous systems and emergent minds. After reviewing LatentSLAM and notable features of this control architecture, we consider how the H/E-S may realize these functional properties not only for physical navigation, but also with respect to high-level cognition understood as generalized simultaneous localization and mapping (G-SLAM). We focus on loop-closure, graph-relaxation, and node duplication as particularly impactful architectural features, suggesting these computational phenomena may contribute to understanding cognitive insight (as proto-causal-inference), accommodation (as integration into existing schemas), and assimilation (as category formation). All these operations can similarly be describable in terms of structure/category learning on multiple levels of abstraction. However, here we adopt an ecological rationality perspective, framing H/E-S functions as orchestrating SLAM processes within both concrete and abstract hypothesis spaces. In this navigation/search process, adaptive cognitive equilibration between assimilation and accommodation involves balancing tradeoffs between exploration and exploitation; this dynamic equilibrium may be near optimally realized in FEP-AI, wherein control systems governed by expected free energy objective functions naturally balance model simplicity and accuracy. With respect to structure learning, such a balance would involve constructing models and categories that are neither too inclusive nor exclusive. We propose these (generalized) SLAM phenomena may represent some of the most impactful sources of variation in cognition both within and between individuals, suggesting that modulators of H/E-S functioning may potentially illuminate their adaptive significances as fundamental cybernetic control parameters. Finally, we discuss how understanding H/E-S contributions to G-SLAM may provide a unifying framework for high-level cognition and its potential realization in artificial intelligences.

Flexible cue anchoring strategies enable stable head direction coding in both sighted and blind animals

Vision plays a crucial role in instructing the brain’s spatial navigation systems. However, little is known about how vision loss affects the neuronal encoding of spatial information. Here, recording from head direction (HD) cells in the anterior dorsal nucleus of the thalamus in mice, we find stable and robust HD tuning in rd1 mice, a model of photoreceptor degeneration, that go blind by approximately one month of age. In contrast, placing sighted animals in darkness significantly impairs HD cell tuning. We find that blind mice use olfactory cues to maintain stable HD tuning and that prior visual experience leads to refined HD cell tuning in blind rd1 adult mice compared to congenitally blind animals. Finally, in the absence of both visual and olfactory cues, the HD attractor network remains intact but the preferred firing direction of HD cells drifts over time. These findings demonstrate flexibility in how the brain uses diverse sensory information to generate a stable directional representation of space.

Vision plays an important role in the head direction cell system in animals. Here the authors recorded from head direction cells in rd1 mice that show retinal degeneration at 1 month, and find that they use smell cues to maintain stable HD tuning.

Replay, the default mode network and the cascaded memory systems model

The spontaneous replay of patterns of activity related to past experiences and memories is a striking feature of brain activity, as is the coherent activation of sets of brain areas - particularly those comprising the default mode network (DMN) - during rest. We propose that these two phenomena are strongly intertwined and that their potential functions overlap. In the 'cascaded memory systems model' that we outline here, we hypothesize that the DMN forms the backbone for the propagation of replay, mediating interactions between the hippocampus and the neocortex that enable the consolidation of new memories. The DMN may also independently ignite replay cascades, which support reactivation of older memories or high-level semantic representations. We suggest that transient cortical activations, inducing long-range correlations across the neocortex, are a key mechanism supporting a hierarchy of representations that progresses from simple percepts to semantic representations of causes and, finally, to whole episodes.

Are Grid-Like Representations a Component of All Perception and Cognition?

Grid cells or grid-like responses have been reported in the rodent, bat and human brains during various spatial and non-spatial tasks. However, the functions of grid-like representations beyond the classical hippocampal formation remain elusive. Based on accumulating evidence from recent rodent recordings and human fMRI data, we make speculative accounts regarding the mechanisms and functional significance of the sensory cortical grid cells and further make theory-driven predictions. We argue and reason the rationale why grid responses may be universal in the brain for a wide range of perceptual and cognitive tasks that involve locomotion and mental navigation. Computational modeling may provide an alternative and complementary means to investigate the grid code or grid-like map. We hope that the new discussion will lead to experimentally testable hypotheses and drive future experimental data collection.

Multiple-Timescale Representations of Space: Linking Memory to Navigation

When navigating through space, we must maintain a representation of our position in real time; when recalling a past episode, a memory can come back in a flash. Interestingly, the brain's spatial representation system, including the hippocampus, supports these two distinct timescale functions. How are neural representations of space used in the service of both real-world navigation and internal mnemonic processes? Recent progress has identified sequences of hippocampal place cells, evolving at multiple timescales in accordance with either navigational behaviors or internal oscillations, that underlie these functions. We review experimental findings on experience-dependent modulation of these sequential representations and consider how they link real-world navigation to time-compressed memories. We further discuss recent work suggesting the prevalence of these sequences beyond hippocampus and propose that these multiple-timescale mechanisms may represent a general algorithm for organizing cell assemblies, potentially unifying the dual roles of the spatial representation system in memory and navigation.

Sharp Tuning of Head Direction and Angular Head Velocity Cells in the Somatosensory Cortex

Head direction (HD) cells form a fundamental component in the brain's spatial navigation system and are intricately linked to spatial memory and cognition. Although HD cells have been shown to act as an internal neuronal compass in various cortical and subcortical regions, the neural substrate of HD cells is incompletely understood. It is reported that HD cells in the somatosensory cortex comprise regular-spiking (RS, putative excitatory) and fast-spiking (FS, putative inhibitory) neurons. Surprisingly, somatosensory FS HD cells fire in bursts and display much sharper head-directionality than RS HD cells. These FS HD cells are nonconjunctive, rarely theta rhythmic, sparsely connected and enriched in layer 5. Moreover, sharply tuned FS HD cells, in contrast with RS HD cells, maintain stable tuning in darkness; FS HD cells' coexistence with RS HD cells and angular head velocity (AHV) cells in a layer-specific fashion through the somatosensory cortex presents a previously unreported configuration of spatial representation in the neocortex. Together, these findings challenge the notion that FS interneurons are weakly tuned to sensory stimuli, and offer a local circuit organization relevant to the generation and transmission of HD signaling in the brain.

Restricted truncal sagittal movements of rapid eye movement behaviour disorder

Unlike sleep-walkers, patients with rapid-eye-movement-behaviour disorder (RBD) rarely leave the bed during the re-enactment of their dreams. RBD movements may be independent of spatial co-ordinates of the ‘outside-world’, and instead rely on (allocentric) brain-generated virtual space-maps, as evident by patients’ limited truncal/axial movements. To confirm this, a semiology analysis of video-polysomnography records of 38 RBD patients was undertaken and paradoxically restricted truncal/thoraco-lumbar movements during complex dream re-enactments demonstrated.

Neurophysiological Evidence for Cognitive Map Formation during Sequence Learning

Humans deftly parse statistics from sequences. Some theories posit that humans learn these statistics by forming cognitive maps, or underlying representations of the latent space which links items in the sequence. Here, an item in the sequence is a node, and the probability of transitioning between two items is an edge. Sequences can then be generated from walks through the latent space, with different spaces giving rise to different sequence statistics. Individual or group differences in sequence learning can be modeled by changing the time scale over which estimates of transition probabilities are built, or in other words, by changing the amount of temporal discounting. Latent space models with temporal discounting bear a resemblance to models of navigation through Euclidean spaces. However, few explicit links have been made between predictions from Euclidean spatial navigation and neural activity during human sequence learning. Here, we use a combination of behavioral modeling and intracranial encephalography (iEEG) recordings to investigate how neural activity might support the formation of space-like cognitive maps through temporal discounting during sequence learning. Specifically, we acquire human reaction times from a sequential reaction time task, to which we fit a model that formulates the amount of temporal discounting as a single free parameter. From the parameter, we calculate each individual's estimate of the latent space. We find that neural activity reflects these estimates mostly in the temporal lobe, including areas involved in spatial navigation. Similar to spatial navigation, we find that low-dimensional representations of neural activity allow for easy separation of important features, such as modules, in the latent space. Lastly, we take advantage of the high temporal resolution of iEEG data to determine the time scale on which latent spaces are learned. We find that learning typically happens within the first 500 trials, and is modulated by the underlying latent space and the amount of temporal discounting characteristic of each participant. Ultimately, this work provides important links between behavioral models of sequence learning and neural activity during the same behavior, and contextualizes these results within a broader framework of domain general cognitive maps.

Topographically organized representation of space and context in the medial prefrontal cortex

The neocortex is composed of areas with specialized functions (e.g., sensory versus associational). Despite this functional diversity, emerging evidence suggests that the encoding of space might be a universal feature of cortical circuits. Here, we identified a gradient of spatial tuning depth along the dorsoventral axis. A complex topography of spatial tuning properties might support a division of labor among medial prefrontal cortical subnetworks to support local circuit computation relevant for the execution of context-dependent behavioral outcomes.

Spatial tuning of neocortical pyramidal cells has been observed in diverse cortical regions and is thought to rely primarily on input from the hippocampal formation. Despite the well-studied hippocampal place code, many properties of the neocortical spatial tuning system are still insufficiently understood. In particular, it has remained unclear how the topography of direct anatomical connections from hippocampus to neocortex affects spatial tuning depth, and whether the dynamics of spatial coding in the hippocampal output region CA1, such as remapping in novel environments, is transmitted to the neocortex. Using mice navigating through virtual environments, we addressed these questions in the mouse medial prefrontal cortex, which receives direct input from the hippocampus. We found a rapidly emerging prefrontal representation of space in the absence of task rules, which discriminates familiar from novel environments and is reinstated upon reexposure to the same familiar environment. Topographical analysis revealed a dorsoventral gradient in the representation of the own position, which runs opposite to the innervation density of hippocampal inputs. Jointly, these results reveal a dynamically emerging and topographically organized prefrontal place code during spontaneous locomotion.

A neural surveyor to map touch on the body

Perhaps the most recognizable “sensory map” in neuroscience is the somatosensory homunculus. Although the homunculus suggests a direct link between cortical territory and body part, the relationship is actually ambiguous without a decoder that knows this mapping. How the somatosensory system derives a spatial code from an activation in the homunculus is a longstanding mystery we aimed to solve. We propose that touch location is disambiguated using multilateration, a computation used by surveying and global positioning systems to localize objects. We develop a Bayesian formulation of multilateration, which we implement in a neural network to identify its computational signature. We then detect this signature in psychophysical experiments. Our results suggest that multilateration provides the homunculus-to-body mapping necessary for localizing touch.

Perhaps the most recognizable sensory map in all of neuroscience is the somatosensory homunculus. Although it seems straightforward, this simple representation belies the complex link between an activation in a somatotopic map and the associated touch location on the body. Any isolated activation is spatially ambiguous without a neural decoder that can read its position within the entire map, but how this is computed by neural networks is unknown. We propose that the somatosensory system implements multilateration, a common computation used by surveying and global positioning systems to localize objects. Specifically, to decode touch location on the body, multilateration estimates the relative distance between the afferent input and the boundaries of a body part (e.g., the joints of a limb). We show that a simple feedforward neural network, which captures several fundamental receptive field properties of cortical somatosensory neurons, can implement a Bayes-optimal multilateral computation. Simulations demonstrated that this decoder produced a pattern of localization variability between two boundaries that was unique to multilateration. Finally, we identify this computational signature of multilateration in actual psychophysical experiments, suggesting that it is a candidate computational mechanism underlying tactile localization.

Duration of oral contraceptive use relates to cognitive performance and brain activation in current and past users

Previous studies indicate effects of oral contraceptive (OC) use on spatial and verbal cognition. However, a better understanding of the OC effects is still needed, including the differential effects of androgenic or anti-androgenic OC use and whether the possible impact persists beyond the OC use. We aim to investigate the associations of OC use duration with spatial and verbal cognition, differentiating between androgenic and anti-androgenic OC. Using functional magnetic resonance imaging (MRI), we scanned a group of 94 past and current OC-users in a single session. We grouped current OC users (N=53) and past OC users with a natural cycle (N=41) into androgenic and anti-androgenic user. Effects of OC use duration were observed for current use and after discontinuation. Duration of OC use was reflected only in verbal fluency performance but not navigation: The longer the current OC use, the less words were produced in the verbal fluency task. During navigation, deactivation in the caudate and postcentral gyrus was duration-dependent in current androgenic OC users. Only during the verbal fluency task, duration of previous OC use affects several brain parameters, including activation of the left putamen and connectivity between right-hemispheric language areas (i.e., right inferior frontal gyrus and right angular gyrus). The results regarding performance and brain activation point towards stronger organizational effects of OCs on verbal rather than spatial processing. Irrespective of the task, a duration-dependent connectivity between the hippocampus and various occipital areas was observed. This could suggest a shift in strategy or processing style with long-term contraceptive use during navigation/verbal fluency. The current findings suggest a key role of the progestogenic component of OCs in both tasks. The influence of OC use on verbal fluency remains even after discontinuation which further points out the importance of future studies on OC effects and their reversibility.

Neural correlates of beneficial effects of young plasma treatment in aged mice: PET-SPM analyses and neuro-behavioural/molecular biological studies

PURPOSE

To investigate the in vivo neurofunctional changes and therapeutic effects of young blood plasma (YBP) in aged mice, as well as the molecular mechanisms underlying the therapeutic effects of YBP ex vivo and in vitro.

METHODS

Aged C57/BL6 mice received systemic administrations of phosphate-buffered saline (PBS) or YBP twice a week, for 4 weeks. In vivo 2-[¹⁸F]-fluoro-2-deoxy-D-glucose positron emission tomography (¹⁸F-FDG PET) under conscious state and cognitive behavioural tests were performed after 4-week treatment. In addition, an in vitro senescent model was established, and the expressions of key cognition-associated proteins and/or the alterations of key neuronal pathways were analysed in both brain tissues and cultured cells.

RESULTS

Aged mice treated with YBP demonstrated higher glucose metabolism in the right hippocampus and bilateral somatosensory cortices, and lower glucose metabolism in the right bed nucleus of stria terminalis and left cerebellum. YBP treatment exerted beneficial effects on the spatial and long-term social recognition memory, and significantly increased the expressions of several cognition-related proteins and altered the key neuronal signalling pathways in the hippocampus and somatosensory cortex. Further in vitro studies suggested that YBP but not aged blood plasma significantly upregulated the expressions of several cognition-associated proteins.

CONCLUSION

Our results highlight the role of the hippocampus and somatosensory cortex in YBP-induced beneficial effects on recognition memory in aged mice. ¹⁸F-FDG PET imaging under conscious state provides a new avenue for exploring the mechanisms underlying YBP treatment against age-related cognitive decline.

Uncovering spatial representations from spatiotemporal patterns of rodent hippocampal field potentials

Spatiotemporal patterns of large-scale spiking and field potentials of the rodent hippocampus encode spatial representations during maze runs, immobility, and sleep. Here, we show that multisite hippocampal field potential amplitude at ultra-high-frequency band (FPAuhf), a generalized form of multiunit activity, provides not only a fast and reliable reconstruction of the rodent's position when awake, but also a readout of replay content during sharp-wave ripples. This FPAuhf feature may serve as a robust real-time decoding strategy from large-scale recordings in closed-loop experiments. Furthermore, we develop unsupervised learning approaches to extract low-dimensional spatiotemporal FPAuhf features during run and ripple periods and to infer latent dynamical structures from lower-rank FPAuhf features. We also develop an optical flow-based method to identify propagating spatiotemporal LFP patterns from multisite array recordings, which can be used as a decoding application. Finally, we develop a prospective decoding strategy to predict an animal's future decision in goal-directed navigation.

Inferences on a multidimensional social hierarchy use a grid-like code

Generalizing experiences to guide decision-making in novel situations is a hallmark of flexible behavior. Cognitive maps of an environment or task can theoretically afford such flexibility, but direct evidence has proven elusive. In this study, we found that discretely sampled abstract relationships between entities in an unseen two-dimensional social hierarchy are reconstructed into a unitary two-dimensional cognitive map in the hippocampus and entorhinal cortex. We further show that humans use a grid-like code in entorhinal cortex and medial prefrontal cortex for inferred direct trajectories between entities in the reconstructed abstract space during discrete decisions. These grid-like representations in the entorhinal cortex are associated with decision value computations in the medial prefrontal cortex and temporoparietal junction. Collectively, these findings show that grid-like representations are used by the human brain to infer novel solutions, even in abstract and discrete problems, and suggest a general mechanism underpinning flexible decision-making and generalization.

Spatial Representations in Rat Orbitofrontal Cortex

The orbitofrontal cortex (OFC) and hippocampus share striking cognitive and functional similarities. As a result, both structures have been proposed to encode "cognitive maps" that provide useful scaffolds for planning complex behaviors. However, while this function has been exemplified by spatial coding in neurons of hippocampal regions-particularly place and grid cells-spatial representations in the OFC have been investigated far less. Here we sought to address this by recording OFC neurons from male rats engaged in an open-field foraging task like that originally developed to characterize place fields in rodent hippocampal neurons. Single-unit activity was recorded as rats searched for food pellets scattered randomly throughout a large enclosure. In some sessions, particular flavors of food occurred more frequently in particular parts of the enclosure; in others, only a single flavor was used. OFC neurons showed spatially localized firing fields in both conditions, and representations changed between flavored and unflavored foraging periods in a manner reminiscent of remapping in the hippocampus. Compared with hippocampal recordings taken under similar behavioral conditions, OFC spatial representations were less temporally reliable, and there was no significant evidence of grid tuning in OFC neurons. These data confirm that OFC neurons show spatial firing fields in a large, two-dimensional environment in a manner similar to hippocampus. Consistent with the focus of the OFC on biological meaning and goals, spatial coding was weaker than in hippocampus and influenced by outcome identity.SIGNIFICANCE STATEMENT The orbitofrontal cortex (OFC) and hippocampus have both been proposed to encode "cognitive maps" that provide useful scaffolds for planning complex behaviors. This function is exemplified by place and grid cells identified in hippocampus, the activity of which maps spatial environments. The current study directly demonstrates very similar, though not identical, spatial representatives in OFC neurons, confirming that OFC-like hippocampus-can represent a spatial map under the appropriate experimental conditions.

Post-Training Sleep Modulates Topographical Relearning-Dependent Resting State Activity

Continuation of experience-dependent neural activity during offline sleep and wakefulness episodes is a critical component of memory consolidation. Using functional magnetic resonance imaging (fMRI), offline consolidation effects have been evidenced probing behavioural and neurophysiological changes during memory retrieval, i.e., in the context of task practice. Resting state fMRI (rsfMRI) further allows investigating the offline evolution of recently learned information without the confounds of online task-related effects. We used rsfMRI to investigate sleep-related changes in seed-based resting functional connectivity (FC) and amplitude of low frequency fluctuations (ALFF) after spatial navigation learning and relearning. On Day 1, offline resting state activity was measured immediately before and after topographical learning in a virtual town. On Day 4, it was measured again before and after relearning in an extended version of the town. Navigation-related activity was also recorded during target retrieval, i.e., online. Participants spent the first post-training night under regular sleep (RS) or sleep deprivation (SD) conditions. Results evidence FC and ALFF changes in task-related neural networks, indicating the continuation of navigation-related activity in the resting state. Although post-training sleep did not modulate behavioural performance, connectivity analyses evidenced increased FC after post-training SD between navigation-related brain structures during relearning in the extended environment. These results suggest that memory traces were less efficiently consolidated after post-learning SD, eventually resulting in the use of compensatory brain resources to link previously stored spatial elements with the newly presented information.