DeepD3, an open framework for automated quantification of dendritic spines.

Dendritic spines are the seat of most excitatory synapses in the brain, and a cellular structure considered central to learning, memory, and activity-dependent plasticity. The quantification of dendritic spines from light microscopy data is usually performed by humans in a painstaking and error-prone process. We found that human-to-human variability is substantial (inter-rater reliability 82.2±6.4%), raising concerns about the reproducibility of experiments and the validity of using human-annotated 'ground truth' as an evaluation method for computational approaches of spine identification. To address this, we present DeepD3, an open deep learning-based framework to robustly quantify dendritic spines in microscopy data in a fully automated fashion. DeepD3's neural networks have been trained on data from different sources and experimental conditions, annotated and segmented by multiple experts and they offer precise quantification of dendrites and dendritic spines. Importantly, these networks were validated in a number of datasets on varying acquisition modalities, species, anatomical locations and fluorescent indicators. The entire DeepD3 open framework, including the fully segmented training data, a benchmark that multiple experts have annotated, and the DeepD3 model zoo is fully available, addressing the lack of openly available datasets of dendritic spines while offering a ready-to-use, flexible, transparent, and reproducible spine quantification method.

Functional and structural features of L2/3 pyramidal cells continuously covary with pial depth in mouse visual cortex.

Pyramidal cells of neocortical layer 2/3 (L2/3 PyrCs) integrate signals from numerous brain areas and project throughout the neocortex. These PyrCs show pial depth-dependent functional and structural specializations, indicating participation in different functional microcircuits. However, whether these depth-dependent differences result from separable PyrC subtypes or whether their features display a continuum correlated with pial depth is unknown. Here, we assessed the stimulus selectivity, electrophysiological properties, dendritic morphology, and excitatory and inhibitory connectivity across the depth of L2/3 in the binocular visual cortex of mice. We find that the apical, but not the basal dendritic tree structure, varies with pial depth, which is accompanied by variation in subthreshold electrophysiological properties. Lower L2/3 PyrCs receive increased input from L4, while upper L2/3 PyrCs receive a larger proportion of intralaminar input. In vivo calcium imaging revealed a systematic change in visual responsiveness, with deeper PyrCs showing more robust responses than superficial PyrCs. Furthermore, deeper PyrCs are more driven by contralateral than ipsilateral eye stimulation. Importantly, the property value transitions are gradual, and L2/3 PyrCs do not display discrete subtypes based on these parameters. Therefore, L2/3 PyrCs' multiple functional and structural properties systematically correlate with their depth, forming a continuum rather than discrete subtypes.

Orientation and direction tuning align with dendritic morphology and spatial connectivity in mouse visual cortex.

The functional properties of neocortical pyramidal cells (PCs), such as direction and orientation selectivity in visual cortex, predominantly derive from their excitatory and inhibitory inputs. For layer 2/3 (L2/3) PCs, the detailed relationship between their functional properties and how they sample and integrate information across cortical space is not fully understood. Here, we study this relationship by combining functional in vivo two-photon calcium imaging, in vitro functional circuit mapping, and dendritic reconstruction of the same L2/3 PCs in mouse visual cortex. Our work reveals direct correlations between dendritic morphology and functional input connectivity and the orientation as well as direction tuning of L2/3 PCs. First, the apical dendritic tree is elongated along the postsynaptic preferred orientation, considering the representation of visual space in the cortex as determined by its retinotopic organization. Additionally, sharply orientation-tuned cells show a less complex apical tree compared with broadly tuned cells. Second, in direction-selective L2/3 PCs, the spatial distribution of presynaptic partners is offset from the soma opposite to the preferred direction. Importantly, although the presynaptic excitatory and inhibitory input distributions spatially overlap on average, the excitatory input distribution is spatially skewed along the preferred direction, in contrast to the inhibitory distribution. Finally, the degree of asymmetry is positively correlated with the direction selectivity of the postsynaptic L2/3 PC. These results show that the dendritic architecture and the spatial arrangement of excitatory and inhibitory presynaptic cells of L2/3 PCs play important roles in shaping their orientation and direction tuning.

Functional network topography of the medial entorhinal cortex.

The medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head-direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here, we examined the topographic arrangement of spatially modulated neurons in the superficial layers of MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD, and OV cells tended to intermingle. These data suggest that grid cell networks might be largely distinct from those of border, HD, and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types.

Mouse visual cortex areas represent perceptual and semantic features of learned visual categories.

Associative memories are stored in distributed networks extending across multiple brain regions. However, it is unclear to what extent sensory cortical areas are part of these networks. Using a paradigm for visual category learning in mice, we investigated whether perceptual and semantic features of learned category associations are already represented at the first stages of visual information processing in the neocortex. Mice learned categorizing visual stimuli, discriminating between categories and generalizing within categories. Inactivation experiments showed that categorization performance was contingent on neuronal activity in the visual cortex. Long-term calcium imaging in nine areas of the visual cortex identified changes in feature tuning and category tuning that occurred during this learning process, most prominently in the postrhinal area (POR). These results provide evidence for the view that associative memories form a brain-wide distributed network, with learning in early stages shaping perceptual representations and supporting semantic content downstream.

Spaced training enhances memory and prefrontal ensemble stability in mice.

It is commonly acknowledged that memory is substantially improved when learning is distributed over time, an effect called the "spacing effect". So far it has not been studied how spaced learning affects the neuronal ensembles presumably underlying memory. In the present study, we investigate whether trial spacing increases the stability or size of neuronal ensembles. Mice were trained in the "everyday memory" task, an appetitive, naturalistic, delayed matching-to-place task. Spacing trials by 60 min produced more robust memories than training with shorter or longer intervals. c-Fos labeling and chemogenetic inactivation established the involvement of the dorsomedial prefrontal cortex (dmPFC) in successful memory storage. In vivo calcium imaging of excitatory dmPFC neurons revealed that longer trial spacing increased the similarity of the population activity pattern on subsequent encoding trials and upon retrieval. Conversely, trial spacing did not affect the size of the total neuronal ensemble or the size of subpopulations dedicated to specific task-related behaviors and events. Thus, spaced learning promotes reactivation of prefrontal neuronal ensembles processing episodic-like memories.

Limited functional convergence of eye-specific inputs in the retinogeniculate pathway of the mouse.

Segregation of retinal ganglion cell (RGC) axons by type and eye of origin is considered a hallmark of dorsal lateral geniculate nucleus (dLGN) structure. However, recent anatomical studies have shown that neurons in mouse dLGN receive input from multiple RGC types of both retinae. Whether convergent input leads to relevant functional interactions is unclear. We studied functional eye-specific retinogeniculate convergence using dual-color optogenetics in vitro. dLGN neurons were strongly dominated by input from one eye. Most neurons received detectable input from the non-dominant eye, but this input was weak, with a prominently reduced AMPAR:NMDAR ratio. Consistent with this, only a small fraction of thalamocortical neurons was binocular in vivo across visual stimuli and cortical projection layers. Anatomical overlap between RGC axons and dLGN neuron dendrites alone did not explain the strong bias toward monocularity. We conclude that functional eye-specific input selection and refinement limit convergent interactions in dLGN, favoring monocularity.

Mouse prefrontal cortex represents learned rules for categorization.

The ability to categorize sensory stimuli is crucial for an animal's survival in a complex environment. Memorizing categories instead of individual exemplars enables greater behavioural flexibility and is computationally advantageous. Neurons that show category selectivity have been found in several areas of the mammalian neocortex1-4, but the prefrontal cortex seems to have a prominent role4,5 in this context. Specifically, in primates that are extensively trained on a categorization task, neurons in the prefrontal cortex rapidly and flexibly represent learned categories6,7. However, how these representations first emerge in naive animals remains unexplored, leaving it unclear whether flexible representations are gradually built up as part of semantic memory or assigned more or less instantly during task execution8,9. Here we investigate the formation of a neuronal category representation throughout the entire learning process by repeatedly imaging individual cells in the mouse medial prefrontal cortex. We show that mice readily learn rule-based categorization and generalize to novel stimuli. Over the course of learning, neurons in the prefrontal cortex display distinct dynamics in acquiring category selectivity and are differentially engaged during a later switch in rules. A subset of neurons selectively and uniquely respond to categories and reflect generalization behaviour. Thus, a category representation in the mouse prefrontal cortex is gradually acquired during learning rather than recruited ad hoc. This gradual process suggests that neurons in the medial prefrontal cortex are part of a specific semantic memory for visual categories.

Disparity Sensitivity and Binocular Integration in Mouse Visual Cortex Areas.

Binocular disparity, the difference between the two eyes' images, is a powerful cue to generate the 3D depth percept known as stereopsis. In primates, binocular disparity is processed in multiple areas of the visual cortex, with distinct contributions of higher areas to specific aspects of depth perception. Mice, too, can perceive stereoscopic depth, and neurons in primary visual cortex (V1) and higher-order, lateromedial (LM) and rostrolateral (RL) areas were found to be sensitive to binocular disparity. A detailed characterization of disparity tuning across mouse visual areas is lacking, however, and acquiring such data might help clarifying the role of higher areas for disparity processing and establishing putative functional correspondences to primate areas. We used two-photon calcium imaging in female mice to characterize the disparity tuning properties of neurons in visual areas V1, LM, and RL in response to dichoptically presented binocular gratings, as well as random dot correlograms (RDC). In all three areas, many neurons were tuned to disparity, showing strong response facilitation or suppression at optimal or null disparity, respectively, even in neurons classified as monocular by conventional ocular dominance (OD) measurements. Neurons in higher areas exhibited broader and more asymmetric disparity tuning curves compared with V1, as observed in primate visual cortex. Finally, we probed neurons' sensitivity to true stereo correspondence by comparing responses to correlated RDC (cRDC) and anticorrelated RDC (aRDC). Area LM, akin to primate ventral visual stream areas, showed higher selectivity for correlated stimuli and reduced anticorrelated responses, indicating higher-level disparity processing in LM compared with V1 and RL.SIGNIFICANCE STATEMENT A major cue for inferring 3D depth is disparity between the two eyes' images. Investigating how binocular disparity is processed in the mouse visual system will not only help delineating the role of mouse higher areas for visual processing, but also shed light on how the mammalian brain computes stereopsis. We found that binocular integration is a prominent feature of mouse visual cortex, as many neurons are selectively and strongly modulated by binocular disparity. Comparison of responses to correlated and anticorrelated random dot correlograms (RDC) revealed that lateromedial area (LM) is more selective to correlated stimuli, while less sensitive to anticorrelated stimuli compared with primary visual cortex (V1) and rostrolateral area (RL), suggesting higher-level disparity processing in LM, resembling primate ventral visual stream areas.

Area-Specific Mapping of Binocular Disparity across Mouse Visual Cortex.

Depth perception is a fundamental feature of many visual systems across species. It is relevant for crucial behaviors, like spatial orientation, prey capture, and predator detection. Binocular disparity, the difference between left and right eye images, is a powerful cue for depth perception, as it depends on an object's distance from the observer [1,2]. In primates, neurons sensitive to binocular disparity are found throughout most of the visual cortex, with distinct disparity tuning properties across primary and higher visual areas, suggesting specific roles of different higher areas for depth perception [1-3]. Mouse primary visual cortex (V1) has been shown to contain disparity-tuned neurons, similar to those found in other mammals [4,5], but it is unknown how binocular disparity is processed beyond V1 and whether it is differentially represented in higher areas. Beyond V1, higher-order, lateromedial (LM) and rostrolateral (RL) areas contain the largest representation of the binocular visual field [6,7], making them candidate areas for investigating downstream processing of binocular disparity in mouse visual cortex. In turn, comparison of disparity tuning across different mouse visual areas might help delineating their functional specializations, which are not well understood. We find clear differences in neurons' preferred disparities across areas, suggesting that higher visual area RL is specialized for encoding visual stimuli very close to the mouse. Moreover, disparity preference is related to visual field elevation, likely reflecting an adaptation to natural image statistics. Our results reveal ethologically relevant areal specializations for binocular disparity processing across mouse visual cortex.

Benchmarking miniaturized microscopy against two-photon calcium imaging using single-cell orientation tuning in mouse visual cortex.

Miniaturized microscopes are lightweight imaging devices that allow optical recordings from neurons in freely moving animals over the course of weeks. Despite their ubiquitous use, individual neuronal responses measured with these microscopes have not been directly compared to those obtained with established in vivo imaging techniques such as bench-top two-photon microscopes. To achieve this, we performed calcium imaging in mouse primary visual cortex while presenting animals with drifting gratings. We identified the same neurons in image stacks acquired with both microscopy methods and quantified orientation tuning of individual neurons. The response amplitude and signal-to-noise ratio of calcium transients recorded upon visual stimulation were highly correlated between both microscopy methods, although influenced by neuropil contamination in miniaturized microscopy. Tuning properties, calculated for individual orientation tuned neurons, were strongly correlated between imaging techniques. Thus, neuronal tuning features measured with a miniaturized microscope are quantitatively similar to those obtained with a two-photon microscope.

Food and water restriction lead to differential learning behaviors in a head-fixed two-choice visual discrimination task for mice.

Head-fixed behavioral tasks can provide important insights into cognitive processes in rodents. Despite the widespread use of this experimental approach, there is only limited knowledge of how differences in task parameters, such as motivational incentives, affect overall task performance. Here, we provide a detailed methodological description of the setup and procedures for training mice efficiently on a two-choice lick left/lick right visual discrimination task. We characterize the effects of two distinct restriction regimens, i.e. food and water restriction, on animal wellbeing, activity patterns, task acquisition, and performance. While we observed reduced behavioral activity during the period of food and water restriction, the average animal discomfort scores remained in the 'sub-threshold' and 'mild' categories throughout the experiment, irrespective of the restriction regimen. We found that the type of restriction significantly influenced specific aspects of task acquisition and engagement, i.e. the number of sessions until the learning criterion was reached and the number of trials performed per session, but it did not affect maximum learning curve performance. These results indicate that the choice of restriction paradigm does not strongly affect animal wellbeing, but it can have a significant effect on how mice perform in a task.

High-yield in vitro recordings from neurons functionally characterized in vivo.

In vivo two-photon calcium imaging provides detailed information about the activity and response properties of individual neurons. However, in vitro methods are often required to study the underlying neuronal connectivity and physiology at the cellular and synaptic levels at high resolution. This protocol provides a fast and reliable workflow for combining the two approaches by characterizing the response properties of individual neurons in mice in vivo using genetically encoded calcium indicators (GECIs), followed by retrieval of the same neurons in brain slices for further analysis in vitro (e.g., circuit mapping). In this approach, a reference frame is provided by fluorescent-bead tracks and sparsely transduced neurons expressing a structural marker in order to re-identify the same neurons. The use of GECIs provides a substantial advancement over previous approaches by allowing for repeated in vivo imaging. This opens the possibility of directly correlating experience-dependent changes in neuronal activity and feature selectivity with changes in neuronal connectivity and physiology. This protocol requires expertise both in in vivo two-photon calcium imaging and in vitro electrophysiology. It takes 3 weeks or more to complete, depending on the time allotted for repeated in vivo imaging of neuronal activity.

Experience-dependent plasticity in the lateral geniculate nucleus.

Experience-dependent plasticity in the visual system is traditionally thought to be exclusively cortical whereas the dorsal lateral geniculate nucleus (dLGN) is classically considered to just be a 'relay' of visual information between the retina and the cortex. However, a number of recent experiments call into question the simplistic view of visual cortex being the only site of plasticity. Thalamic neurons, at least in mouse dLGN, combine inputs from ganglion cells located in both eyes and recent evidence suggests that the feature selectivity of dLGN neurons is subject to experience-dependent plasticity. Here we discuss new insights into the nature of thalamic visual processing, focusing on the unexpected degree and plasticity of functional binocular convergence in mouse dLGN.

Lateral geniculate neurons projecting to primary visual cortex show ocular dominance plasticity in adult mice.

Experience-dependent plasticity in the mature visual system is widely considered to be cortical. Using chronic two-photon Ca2+ imaging of thalamic afferents in layer 1 of binocular visual cortex, we provide evidence against this tenet: the respective dorsal lateral geniculate nucleus (dLGN) cells showed pronounced ocular dominance (OD) shifts after monocular deprivation in adult mice. Most (86%), but not all, of dLGN cell boutons were monocular during normal visual experience. Following deprivation, initially deprived-eye-dominated boutons reduced or lost their visual responsiveness to that eye and frequently became responsive to the non-deprived eye. This cannot be explained by eye-specific cortical changes propagating to dLGN via cortico-thalamic feedback because the shift in dLGN responses was largely resistant to cortical inactivation using the GABAA receptor agonist muscimol. Our data suggest that OD shifts observed in the binocular visual cortex of adult mice may at least partially reflect plasticity of eye-specific inputs onto dLGN neurons.

Building Bridges through Science.

Science is ideally suited to connect people from different cultures and thereby foster mutual understanding. To promote international life science collaboration, we have launched "The Science Bridge" initiative. Our current project focuses on partnership between Western and Middle Eastern neuroscience communities.

Interactions between synaptic homeostatic mechanisms: an attempt to reconcile BCM theory, synaptic scaling, and changing excitation/inhibition balance.

Homeostatic plasticity is proposed to be mediated by synaptic changes, such as synaptic scaling and shifts in the excitation/inhibition balance. These mechanisms are thought to be separate from the Bienenstock, Cooper, Munro (BCM) learning rule, where the threshold for the induction of long-term potentiation and long-term depression slides in response to changes in activity levels. Yet, both sets of mechanisms produce a homeostatic response of a relative increase (or decrease) in strength of excitatory synapses in response to overall activity-level changes. Here we review recent studies, with a focus on in vivo experiments, to re-examine the overlap and differences between these two mechanisms and we suggest how they may interact to facilitate firing-rate homeostasis, while maintaining functional properties of neurons.

Variance and invariance of neuronal long-term representations.

The brain extracts behaviourally relevant sensory input to produce appropriate motor output. On the one hand, our constantly changing environment requires this transformation to be plastic. On the other hand, plasticity is thought to be balanced by mechanisms ensuring constancy of neuronal representations in order to achieve stable behavioural performance. Yet, prominent changes in synaptic strength and connectivity also occur during normal sensory experience, indicating a certain degree of constitutive plasticity. This raises the question of how stable neuronal representations are on the population level and also on the single neuron level. Here, we review recent data from longitudinal electrophysiological and optical recordings of single-cell activity that assess the long-term stability of neuronal stimulus selectivities under conditions of constant sensory experience, during learning, and after reversible modification of sensory input. The emerging picture is that neuronal representations are stabilized by behavioural relevance and that the degree of long-term tuning stability and perturbation resistance directly relates to the functional role of the respective neurons, cell types and circuits. Using a 'toy' model, we show that stable baseline representations and precise recovery from perturbations in visual cortex could arise from a 'backbone' of strong recurrent connectivity between similarly tuned cells together with a small number of 'anchor' neurons exempt from plastic changes.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'.

Transplanted embryonic neurons integrate into adult neocortical circuits.

The ability of the adult mammalian brain to compensate for neuronal loss caused by injury or disease is very limited. Transplantation aims to replace lost neurons, but the extent to which new neurons can integrate into existing circuits is unknown. Here, using chronic in vivo two-photon imaging, we show that embryonic neurons transplanted into the visual cortex of adult mice mature into bona fide pyramidal cells with selective pruning of basal dendrites, achieving adult-like densities of dendritic spines and axonal boutons within 4-8 weeks. Monosynaptic tracing experiments reveal that grafted neurons receive area-specific, afferent inputs matching those of pyramidal neurons in the normal visual cortex, including topographically organized geniculo-cortical connections. Furthermore, stimulus-selective responses refine over the course of many weeks and finally become indistinguishable from those of host neurons. Thus, grafted neurons can integrate with great specificity into neocortical circuits that normally never incorporate new neurons in the adult brain.