A novel paradigm for observational learning in rats.

The ability to learn by observing the behavior of others is energy efficient and brings high survival value, making it an important learning tool that has been documented in a myriad of species in the animal kingdom. In the laboratory, rodents have proven useful models for studying different forms of observational learning, however, the most robust learning paradigms typically rely on aversive stimuli, like foot shocks, to drive the social acquisition of fear. Non-fear-based tasks have also been used but they rarely succeed in having observer animals perform a new behavior de novo. Consequently, little known regarding the cellular mechanisms supporting non-aversive types of learning, such as visuomotor skill acquisition. To address this we developed a reward-based observational learning paradigm in adult rats, in which observer animals learn to tap lit spheres in a specific sequence by watching skilled demonstrators, with successful trials leading to rewarding intracranial stimulation in both observers and performers. Following three days of observation and a 24-hour delay, observer animals outperformed control animals on several metrics of task performance and efficiency, with a subset of observers demonstrating correct performance immediately when tested. This paradigm thus introduces a novel tool to investigate the neural circuits supporting observational learning and memory for visuomotor behavior, a phenomenon about which little is understood, particularly in rodents.

The quality and complexity of pairwise maximum entropy models for large cortical populations.

We investigate the ability of the pairwise maximum entropy (PME) model to describe the spiking activity of large populations of neurons recorded from the visual, auditory, motor, and somatosensory cortices. To quantify this performance, we use (1) Kullback-Leibler (KL) divergences, (2) the extent to which the pairwise model predicts third-order correlations, and (3) its ability to predict the probability that multiple neurons are simultaneously active. We compare these with the performance of a model with independent neurons and study the relationship between the different performance measures, while varying the population size, mean firing rate of the chosen population, and the bin size used for binarizing the data. We confirm the previously reported excellent performance of the PME model for small population sizes N < 20. But we also find that larger mean firing rates and bin sizes generally decreases performance. The performance for larger populations were generally not as good. For large populations, pairwise models may be good in terms of predicting third-order correlations and the probability of multiple neurons being active, but still significantly worse than small populations in terms of their improvement over the independent model in KL-divergence. We show that these results are independent of the cortical area and of whether approximate methods or Boltzmann learning are used for inferring the pairwise couplings. We compared the scaling of the inferred couplings with N and find it to be well explained by the Sherrington-Kirkpatrick (SK) model, whose strong coupling regime shows a complex phase with many metastable states. We find that, up to the maximum population size studied here, the fitted PME model remains outside its complex phase. However, the standard deviation of the couplings compared to their mean increases, and the model gets closer to the boundary of the complex phase as the population size grows.

Behavioral decomposition reveals rich encoding structure employed across neocortex in rats.

The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations.

Visuomotor interactions in the mouse forebrain mediated by extrastriate cortico-cortical pathways.

Introduction: The mammalian visual system can be broadly divided into two functional processing pathways: a dorsal stream supporting visually and spatially guided actions, and a ventral stream enabling object recognition. In rodents, the majority of visual signaling in the dorsal stream is transmitted to frontal motor cortices via extrastriate visual areas surrounding V1, but exactly where and to what extent V1 feeds into motor-projecting visual regions is not well known. Methods: We employed a dual labeling strategy in male and female mice in which efferent projections from V1 were labeled anterogradely, and motor-projecting neurons in higher visual areas were labeled with retrogradely traveling adeno-associated virus (rAAV-retro) injected in M2. We characterized the labeling in both flattened and coronal sections of dorsal cortex and made high-resolution 3D reconstructions to count putative synaptic contacts in different extrastriate areas. Results: The most pronounced colocalization V1 output and M2 input occurred in extrastriate areas AM, PM, RL and AL. Neurons in both superficial and deep layers in each project to M2, but high resolution volumetric reconstructions indicated that the majority of putative synaptic contacts from V1 onto M2-projecting neurons occurred in layer 2/3. Discussion: These findings support the existence of a dorsal processing stream in the mouse visual system, where visual signals reach motor cortex largely via feedforward projections in anteriorly and medially located extrastriate areas.

Histological E-data Registration in rodent Brain Spaces.

Recording technologies for rodents have seen huge advances in the last decade, allowing users to sample thousands of neurons simultaneously from multiple brain regions. This has prompted the need for digital tool kits to aid in curating anatomical data, however, existing tools either provide limited functionalities or require users to be proficient in coding to use them. To address this we created HERBS (Histological E-data Registration in rodent Brain Spaces), a comprehensive new tool for rodent users that offers a broad range of functionalities through a user-friendly graphical user interface. Prior to experiments, HERBS can be used to plan coordinates for implanting electrodes, targeting viral injections or tracers. After experiments, users can register recording electrode locations (e.g. Neuropixels and tetrodes), viral expression, or other anatomical features, and visualize the results in 2D or 3D. Additionally, HERBS can delineate labeling from multiple injections across tissue sections and obtain individual cell counts.Regional delineations in HERBS are based either on annotated 3D volumes from the Waxholm Space Atlas of the Sprague Dawley Rat Brain or the Allen Mouse Brain Atlas, though HERBS can work with compatible volume atlases from any species users wish to install. HERBS allows users to scroll through the digital brain atlases and provides custom-angle slice cuts through the volumes, and supports free-transformation of tissue sections to atlas slices. Furthermore, HERBS allows users to reconstruct a 3D brain mesh with tissue from individual animals. HERBS is a multi-platform open-source Python package that is available on PyPI and GitHub, and is compatible with Windows, macOS, and Linux operating systems.

Action representation in the mouse parieto-frontal network.

The posterior parietal cortex (PPC) and frontal motor areas comprise a cortical network supporting goal-directed behaviour, with functions including sensorimotor transformations and decision making. In primates, this network links performed and observed actions via mirror neurons, which fire both when individuals perform an action and when they observe the same action performed by a conspecific. Mirror neurons are believed to be important for social learning, but it is not known whether mirror-like neurons occur in similar networks in other social species, such as rodents, or if they can be measured in such models using paradigms where observers passively view a demonstrator. Therefore, we imaged Ca2+ responses in PPC and secondary motor cortex (M2) while mice performed and observed pellet-reaching and wheel-running tasks, and found that cell populations in both areas robustly encoded several naturalistic behaviours. However, neural responses to the same set of observed actions were absent, although we verified that observer mice were attentive to performers and that PPC neurons responded reliably to visual cues. Statistical modelling also indicated that executed actions outperformed observed actions in predicting neural responses. These results raise the possibility that sensorimotor action recognition in rodents could take place outside of the parieto-frontal circuit, and underscore that detecting socially-driven neural coding depends critically on the species and behavioural paradigm used.

Organization of Posterior Parietal-Frontal Connections in the Rat.

Recent investigations of the rat posterior parietal cortex (PPC) suggest that this region plays a central role in action control together with the frontal cortical areas. Posterior parietal-frontal cortical connections have been described in rats, but little is known about whether these connections are topographically organized as in the primate. Here, we injected retrograde and anterograde tracers into subdivisions of PPC as well as the frontal midline and orbital cortical areas to explore possible topographies within their connections. We found that PPC projects to several frontal cortical areas, largely reciprocating the densest input received from the same areas. All PPC subdivisions are strongly connected with the secondary motor cortex (M2) in a topographically organized manner. The medial subdivision (medial posterior parietal cortex, mPPC) has a dense reciprocal connection with the most caudal portion of M2 (cM2), whereas the lateral subdivision (lateral posterior parietal cortex, lPPC) and the caudolateral subdivision (PtP) are reciprocally connected with the intermediate rostrocaudal portion of M2 (iM2). Sparser reciprocal connections were seen with anterior cingulate area 24b. mPPC connects with rostral, and lPPC and PtP connect with caudal parts of 24b, respectively. There are virtually no connections with area 24a, nor with prelimbic or infralimbic cortex. PPC and orbitofrontal cortices are also connected, showing a gradient such that mPPC entertains reciprocal connections mainly with the ventral orbitofrontal cortex (OFC), whereas lPPC and PtP are preferentially connected with medial and central portions of ventrolateral OFC, respectively. Our results thus indicate that the connections of PPC with frontal cortices are organized in a topographical fashion, supporting functional heterogeneity within PPC and frontal cortices.

Architecture and organization of mouse posterior parietal cortex relative to extrastriate areas.

The posterior parietal cortex (PPC) is a multifaceted region of cortex, contributing to several cognitive processes, including sensorimotor integration and spatial navigation. Although recent years have seen a considerable rise in the use of rodents, particularly mice, to investigate PPC and related networks, a coherent anatomical definition of PPC in the mouse is still lacking. To address this, we delineated the mouse PPC, using cyto- and chemoarchitectural markers from Nissl-, parvalbumin-and muscarinic acetylcholine receptor M2-staining. Additionally, we performed bilateral triple anterograde tracer injections in primary visual cortex (V1) and prepared flattened tangential sections from one hemisphere and coronal sections from the other, allowing us to co-register the cytoarchitectural features of PPC with V1 projections. This revealed that extrastriate area A was largely contained within lateral PPC, that medial PPC overlapped with the anterior portion of area AM, and that anterior RL overlapped partially with area PtP. Furthermore, triple anterograde tracer injections in PPC showed strong projections to associative thalamic nuclei as well as higher visual areas, orbitofrontal, cingulate and secondary motor cortices. Retrograde circuit mapping with rabies virus further showed that all cortical connections were reciprocal. These combined approaches provide a coherent definition of mouse PPC that incorporates laminar architecture, extrastriate projections, thalamic, and cortico-cortical connections.

Efficient cortical coding of 3D posture in freely behaving rats.

Animals constantly update their body posture to meet behavioral demands, but little is known about the neural signals on which this depends. We therefore tracked freely foraging rats in three dimensions while recording from the posterior parietal cortex (PPC) and the frontal motor cortex (M2), areas critical for movement planning and navigation. Both regions showed strong tuning to posture of the head, neck, and back, but signals for movement were much less dominant. Head and back representations were organized topographically across the PPC and M2, and more neurons represented postures that occurred less often. Simultaneous recordings across areas were sufficiently robust to decode ongoing behavior and showed that spiking in the PPC tended to precede that in M2. Both the PPC and M2 strongly represent posture by using a spatially organized, energetically efficient population code.

Movement Coding at the Mesoscale in Posterior Parietal Cortex.

Neural correlates of movement planning have been studied most commonly using signals isolated from single cells. However, in this issue of Neuron, Wilber et al. (2017) show that movement trajectories are encoded and replayed in the collective activity of thousands of cells at a time in the posterior parietal cortex.

Posterior parietal cortex.

The posterior parietal cortex, along with temporal and prefrontal cortices, is one of the three major associative regions in the cortex of the mammalian brain. It is situated between the visual cortex at the caudal pole of the brain and the somatosensory cortex just behind the central sulcus. Technically, any cortex covered by the parietal bone is referred to as 'parietal cortex', but the posterior sector, formally referred to as posterior parietal cortex, is indeed its own functional section of cortex, consisting of Brodmann's areas 5, 7, 39, and 40 in humans, areas 5 and 7 in macaques, and area 7 in rodents (Figure 1). Whereas the anterior parietal cortex in humans comprises primary somatosensory areas, the posterior parietal cortex has several higher-order functions. It is referred to as an 'associative' cortical region because it is neither strictly sensory nor motor, but combines inputs from a number of brain areas including somatosensory, auditory, visual, motor, cingulate and prefrontal cortices, and it integrates proprioceptive and vestibular signals from subcortical areas.

Corrigendum: Navigating actions through the rodent parietal cortex.

[This corrects the article on p. 293 in vol. 8, PMID: 24860475.].

Navigating actions through the rodent parietal cortex.

The posterior parietal cortex (PPC) participates in a manifold of cognitive functions, including visual attention, working memory, spatial processing, and movement planning. Given the vast interconnectivity of PPC with sensory and motor areas, it is not surprising that neuronal recordings show that PPC often encodes mixtures of spatial information as well as the movements required to reach a goal. Recent work sought to discern the relative strength of spatial vs. motor signaling in PPC by recording single unit activity in PPC of freely behaving rats during selective changes in either the spatial layout of the local environment or in the pattern of locomotor behaviors executed during navigational tasks. The results revealed unequivocally a predominant sensitivity of PPC neurons to locomotor action structure, with subsets of cells even encoding upcoming movements more than 1 s in advance. In light of these and other recent findings in the field, I propose that one of the key contributions of PPC to navigation is the synthesis of goal-directed behavioral sequences, and that the rodent PPC may serve as an apt system to investigate cellular mechanisms for spatial motor planning as traditionally studied in humans and monkeys.

Head direction maps remain stable despite grid map fragmentation.

Areas encoding space in the brain contain both representations of position (place cells and grid cells) and representations of azimuth (head direction cells). Previous studies have already suggested that although grid cells and head direction cells reside in the same brain areas, the calculation of head direction is not dependent on the calculation of position. Here we demonstrate that realignment of grid cells does not affect head direction tuning. We analyzed head direction cell data collected while rats performed a foraging task in a multi-compartment environment (the hairpin maze) vs. an open-field environment, demonstrating that the tuning of head direction cells did not change when the environment was divided into multiple sub-compartments, in the hairpin maze. On the other hand, as we have shown previously (Derdikman et al., 2009), the hexagonal firing pattern expressed by grid cells in the open-field broke down into repeating patterns in similar alleys when rats traversed the multi-compartment hairpin maze. The grid-like firing of conjunctive cells, which express both grid properties and head direction properties in the open-field, showed a selective fragmentation of grid-like firing properties in the hairpin maze, while the head directionality property of the same cells remained unaltered. These findings demonstrate that head direction is not affected during the restructuring of grid cell firing fields as a rat actively moves between compartments, thus strengthening the claim that the head direction system is upstream from or parallel to the grid-place system.

Functional split between parietal and entorhinal cortices in the rat.

Posterior parietal cortex (PPC) and medial entorhinal cortex (MEC) are important elements of the neural circuit for space, but whether representations in these areas are controlled by the same factors is unknown. We recorded single units simultaneously in PPC and MEC of freely foraging rats and found that a subset of PPC cells are tuned to specific modes of movement irrespective of the animals' location or heading, whereas grid cells in MEC expressed static spatial maps. The behavioral correlates of PPC cells switched completely when the same animals ran in a spatially structured maze or when they ran similar stereotypic sequences in an open arena. Representations in PPC were similar in identical mazes in different rooms where grid cells completely realigned their firing fields. The data suggest that representations in PPC are determined by the organization of actions while cells in MEC are driven by spatial inputs.

Fragmentation of grid cell maps in a multicompartment environment.

To determine whether entorhinal spatial representations are continuous or fragmented, we recorded neural activity in grid cells while rats ran through a stack of interconnected, zig-zagged compartments of equal shape and orientation (a hairpin maze). The distribution of spatial firing fields was markedly similar across all compartments in which running occurred in the same direction, implying that the grid representation was fragmented into repeating submaps. Activity at neighboring positions was least correlated at the transitions between different arms, indicating that the map split regularly at the turning points. We saw similar discontinuities among place cells in the hippocampus. No fragmentation was observed when the rats followed similar trajectories in the absence of internal walls, implying that stereotypic behavior alone cannot explain the compartmentalization. These results indicate that spatial environments are represented in entorhinal cortex and hippocampus as a mosaic of discrete submaps that correspond to the geometric structure of the space.

The levo enantiomer of amphetamine increases memory consolidation and gene expression in the hippocampus without producing locomotor stimulation.

Dextro-amphetamine enhances memory and other cognitive functions in animals and humans. The use of d-amphetamine as a memory enhancer, however, is limited by a robust stimulatory side-effect profile caused by release of dopamine. The levo enantiomer of amphetamine has been shown to be considerably less effective as a dopamine releaser and less potent in producing the stimulatory effects characteristic of d-amphetamine. In order to determine whether l-amphetamine and the structurally related compound, l-methamphetamine, retain cognitive-enhancing effects despite their lack of stimulatory activity, we administered the compounds to rats prior to activity monitoring experiments, and in different animals, immediately after training on inhibitory avoidance and object recognition tasks. Results demonstrated that l-amphetamine and l-methamphetamine did not increase locomotion and stereotypies beyond control levels, but did produce significant memory enhancement. In addition, l-amphetamine and l-methamphetamine alleviated scopolamine-induced amnesia in the inhibitory avoidance task. In all cases, these compounds produced an effect comparable to that of d-amphetamine, but required only one quarter of the d-amphetamine dose to produce the same effect size. We also found that l-amphetamine modulates learning-induced changes in hippocampal Arc/Arg3.1 protein synthesis that correlate with memory consolidation. These results suggest that l-amphetamine and l-methamphetamine are potent memory enhancers in rats and may ultimately be useful for treating memory disorders in humans.

Navigating from hippocampus to parietal cortex.

The navigational system of the mammalian cortex comprises a number of interacting brain regions. Grid cells in the medial entorhinal cortex and place cells in the hippocampus are thought to participate in the formation of a dynamic representation of the animal's current location, and these cells are presumably critical for storing the representation in memory. To traverse the environment, animals must be able to translate coordinate information from spatial maps in the entorhinal cortex and hippocampus into body-centered representations that can be used to direct locomotion. How this is done remains an enigma. We propose that the posterior parietal cortex is critical for this transformation.

Learning induces long-term potentiation in the hippocampus.

Years of intensive investigation have yielded a sophisticated understanding of long-term potentiation (LTP) induced in hippocampal area CA1 by high-frequency stimulation (HFS). These efforts have been motivated by the belief that similar synaptic modifications occur during memory formation, but it has never been shown that learning actually induces LTP in CA1. We found that one-trial inhibitory avoidance learning in rats produced the same changes in hippocampal glutamate receptors as induction of LTP with HFS and caused a spatially restricted increase in the amplitude of evoked synaptic transmission in CA1 in vivo. Because the learning-induced synaptic potentiation occluded HFS-induced LTP, we conclude that inhibitory avoidance training induces LTP in CA1.