Shack-Hartmann wave front measurements in cortical tissue for deconvolution of large three-dimensional mosaic transmitted light brightfield micrographs

Relationships between structure, in vivo function and long-range axonal target of cortical pyramidal tract neurons

Pyramidal tract neurons (PTs) represent the major output cell type of the neocortex. To investigate principles of how the results of cortical processing are broadcasted to different downstream targets thus requires experimental approaches, which provide access to the in vivo electrophysiology of PTs, whose subcortical target regions are identified. On the example of rat barrel cortex (vS1), we illustrate that retrograde tracer injections into multiple subcortical structures allow identifying the long-range axonal targets of individual in vivo recorded PTs. Here we report that soma depth and dendritic path lengths within each cortical layer of vS1, as well as spiking patterns during both periods of ongoing activity and during sensory stimulation, reflect the respective subcortical target regions of PTs. We show that these cellular properties result in a structure-function parameter space that allows predicting a PT's subcortical target region, without the need to inject multiple retrograde tracers.The major output cell type of the neocortex - pyramidal tract neurons (PTs) - send axonal projections to various subcortical areas. Here the authors combined in vivo recordings, retrograde tracings, and reconstructions of PTs in rat somatosensory cortex to show that PT structure and activity can predict specific subcortical targets.

3D reconstruction and standardization of the rat facial nucleus for precise mapping of vibrissal motor networks

The rodent facial nucleus (FN) comprises motoneurons (MNs) that control the facial musculature. In the lateral part of the FN, populations of vibrissal motoneurons (vMNs) innervate two groups of muscles that generate movements of the whiskers. Vibrissal MNs thus represent the terminal point of the neuronal networks that generate rhythmic whisking during exploratory behaviors and that modify whisker movements based on sensory-motor feedback during tactile-based perception. Here, we combined retrograde tracer injections into whisker-specific muscles, with large-scale immunohistochemistry and digital reconstructions to generate an average model of the rat FN. The model incorporates measurements of the FN geometry, its cellular organization and a whisker row-specific map formed by vMNs. Furthermore, the model provides a digital 3D reference frame that allows registering structural data - obtained across scales and animals - into a common coordinate system with a precision of ∼60 µm. We illustrate the registration method by injecting replication competent rabies virus into the muscle of a single whisker. Retrograde transport of the virus to vMNs enabled reconstruction of their dendrites. Subsequent trans-synaptic transport enabled mapping the presynaptic neurons of the reconstructed vMNs. Registration of these data to the FN reference frame provides a first account of the morphological and synaptic input variability within a population of vMNs that innervate the same muscle.

EM connectomics reveals axonal target variation in a sequence-generating network

The sequential activation of neurons has been observed in various areas of the brain, but in no case is the underlying network structure well understood. Here we examined the circuit anatomy of zebra finch HVC, a cortical region that generates sequences underlying the temporal progression of the song. We combined serial block-face electron microscopy with light microscopy to determine the cell types targeted by HVC(RA) neurons, which control song timing. Close to their soma, axons almost exclusively targeted inhibitory interneurons, consistent with what had been found with electrical recordings from pairs of cells. Conversely, far from the soma the targets were mostly other excitatory neurons, about half of these being other HVC(RA) cells. Both observations are consistent with the notion that the neural sequences that pace the song are generated by global synaptic chains in HVC embedded within local inhibitory networks.

Generation of dense statistical connectomes from sparse morphological data

Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results.

Direct imaging of phase objects enables conventional deconvolution in bright field light microscopy

In transmitted optical microscopy, absorption structure and phase structure of the specimen determine the three-dimensional intensity distribution of the image. The elementary impulse responses of the bright field microscope therefore consist of separate absorptive and phase components, precluding general application of linear, conventional deconvolution processing methods to improve image contrast and resolution. However, conventional deconvolution can be applied in the case of pure phase (or pure absorptive) objects if the corresponding phase (or absorptive) impulse responses of the microscope are known. In this work, we present direct measurements of the phase point- and line-spread functions of a high-aperture microscope operating in transmitted bright field. Polystyrene nanoparticles and microtubules (biological polymer filaments) serve as the pure phase point and line objects, respectively, that are imaged with high contrast and low noise using standard microscopy plus digital image processing. Our experimental results agree with a proposed model for the response functions, and confirm previous theoretical predictions. Finally, we use the measured phase point-spread function to apply conventional deconvolution on the bright field images of living, unstained bacteria, resulting in improved definition of cell boundaries and sub-cellular features. These developments demonstrate practical application of standard restoration methods to improve imaging of phase objects such as cells in transmitted light microscopy.

3D reconstruction and standardization of the rat vibrissal cortex for precise registration of single neuron morphology

The three-dimensional (3D) structure of neural circuits is commonly studied by reconstructing individual or small groups of neurons in separate preparations. Investigation of structural organization principles or quantification of dendritic and axonal innervation thus requires integration of many reconstructed morphologies into a common reference frame. Here we present a standardized 3D model of the rat vibrissal cortex and introduce an automated registration tool that allows for precise placement of single neuron reconstructions. We (1) developed an automated image processing pipeline to reconstruct 3D anatomical landmarks, i.e., the barrels in Layer 4, the pia and white matter surfaces and the blood vessel pattern from high-resolution images, (2) quantified these landmarks in 12 different rats, (3) generated an average 3D model of the vibrissal cortex and (4) used rigid transformations and stepwise linear scaling to register 94 neuron morphologies, reconstructed from in vivo stainings, to the standardized cortex model. We find that anatomical landmarks vary substantially across the vibrissal cortex within an individual rat. In contrast, the 3D layout of the entire vibrissal cortex remains remarkably preserved across animals. This allows for precise registration of individual neuron reconstructions with approximately 30 µm accuracy. Our approach could be used to reconstruct and standardize other anatomically defined brain areas and may ultimately lead to a precise digital reference atlas of the rat brain.

Sensory experience restructures thalamocortical axons during adulthood

The brain's capacity to rewire is thought to diminish with age. It is widely believed that development stabilizes the synapses from thalamus to cortex and that adult experience alters only synaptic connections between cortical neurons. Here we show that thalamocortical (TC) inputs themselves undergo massive plasticity in adults. We combined whole-cell recording from individual thalamocortical neurons in adult rats with a recently developed automatic tracing technique to reconstruct individual axonal trees. Whisker trimming substantially reduced thalamocortical axon length in barrel cortex but not the density of TC synapses along a fiber. Thus, sensory experience alters the total number of TC synapses. After trimming, sensory stimulation evoked more tightly time-locked responses among thalamorecipient layer 4 cortical neurons. These findings indicate that thalamocortical input itself remains plastic in adulthood, raising the possibility that the axons of other subcortical structures might also remain in flux throughout life.

Large-scale automated histology in the pursuit of connectomes

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Cell type-specific three-dimensional structure of thalamocortical circuits in a column of rat vibrissal cortex

Soma location, dendrite morphology, and synaptic innervation may represent key determinants of functional responses of individual neurons, such as sensory-evoked spiking. Here, we reconstruct the 3D circuits formed by thalamocortical afferents from the lemniscal pathway and excitatory neurons of an anatomically defined cortical column in rat vibrissal cortex. We objectively classify 9 cortical cell types and estimate the number and distribution of their somata, dendrites, and thalamocortical synapses. Somata and dendrites of most cell types intermingle, while thalamocortical connectivity depends strongly upon the cell type and the 3D soma location of the postsynaptic neuron. Correlating dendrite morphology and thalamocortical connectivity to functional responses revealed that the lemniscal afferents can account for some of the cell type- and location-specific subthreshold and spiking responses after passive whisker touch (e.g., in layer 4, but not for other cell types, e.g., in layer 5). Our data provides a quantitative 3D prediction of the cell type–specific lemniscal synaptic wiring diagram and elucidates structure–function relationships of this physiologically relevant pathway at single-cell resolution.

Adaptive optics for fluorescence wide-field microscopy using spectrally independent guide star and markers

We describe the implementation and use of an adaptive optics loop in the imaging path of a commercial wide field microscope. We show that it is possible to maintain the optical performances of the original microscope when imaging through aberrant biological samples. The sources used for illuminating the adaptive optics loop are spectrally independent, in excitation and emission, from the sample, so they do not appear in the final image, and their use does not contribute to the sample bleaching. Results are compared with equivalent images obtained with an identical microscope devoid of adaptive optics system.

Three-dimensional axon morphologies of individual layer 5 neurons indicate cell type-specific intracortical pathways for whisker motion and touch

The cortical output layer 5 contains two excitatory cell types, slender- and thick-tufted neurons. In rat vibrissal cortex, slender-tufted neurons carry motion and phase information during active whisking, but remain inactive after passive whisker touch. In contrast, thick-tufted neurons reliably increase spiking preferably after passive touch. By reconstructing the 3D patterns of intracortical axon projections from individual slender- and thick-tufted neurons, filled in vivo with biocytin, we were able to identify cell type-specific intracortical circuits that may encode whisker motion and touch. Individual slender-tufted neurons showed elaborate and dense innervation of supragranular layers of large portions of the vibrissal area (total length, 86.8 ± 5.5 mm). During active whisking, these long-range projections may modulate and phase-lock the membrane potential of dendrites in layers 2 and 3 to the whisking cycle. Thick-tufted neurons with soma locations intermingling with those of slender-tufted ones display less dense intracortical axon projections (total length, 31.6 ± 14.3 mm) that are primarily confined to infragranular layers. Based on anatomical reconstructions and previous measurements of spiking, we put forward the hypothesis that thick-tufted neurons in rat vibrissal cortex receive input of whisker motion from slender-tufted neurons onto their apical tuft dendrites and input of whisker touch from thalamic neurons onto their basal dendrites. During tactile-driven behavior, such as object location, near-coincident input from these two pathways may result in increased spiking activity of thick-tufted neurons and thus enhanced signaling to their subcortical targets.

Automated three-dimensional detection and counting of neuron somata

We present a novel approach for automated detection of neuron somata. A three-step processing pipeline is described on the example of confocal image stacks of NeuN-stained neurons from rat somato-sensory cortex. It results in a set of position landmarks, representing the midpoints of all neuron somata. In the first step, foreground and background pixels are identified, resulting in a binary image. It is based on local thresholding and compensates for imaging and staining artifacts. Once this pre-processing guarantees a standard image quality, clusters of touching neurons are separated in the second step, using a marker-based watershed approach. A model-based algorithm completes the pipeline. It assumes a dominant neuron population with Gaussian distributed volumes within one microscopic field of view. Remaining larger objects are hence split or treated as a second neuron type. A variation of the processing pipeline is presented, showing that our method can also be used for co-localization of neurons in multi-channel images. As an example, we process 2-channel stacks of NeuN-stained somata, labeling all neurons, counterstained with GAD67, labeling GABAergic interneurons, using an adapted pre-processing step for the second channel. The automatically generated landmark sets are compared to manually placed counterparts. A comparison yields that the deviation in landmark position is negligible and that the difference between the numbers of manually and automatically counted neurons is less than 4%. In consequence, this novel approach for neuron counting is a reliable and objective alternative to manual detection.