Two-photon imaging and analysis of neural network dynamics

The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behaviour. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so called 'microcircuits') remains comparably poor. In large parts, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near- millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits.Comment: 36 pages, 4 figures, accepted for publication in Reports on Progress in Physic

Post hoc immunostaining of GABAergic neuronal subtypes following in vivo two-photon calcium imaging in mouse neocortex

GABAergic neurons in the neocortex are diverse with regard to morphology, physiology, and axonal targeting pattern, indicating functional specializations within the cortical microcircuitry. Little information is available, however, about functional properties of distinct subtypes of GABAergic neurons in the intact brain. Here, we combined in vivo two-photon calcium imaging in supragranular layers of the mouse neocortex with post hoc immunohistochemistry against the three calcium-binding proteins parvalbumin, calretinin, and calbindin in order to assign subtype marker profiles to neuronal activity. Following coronal sectioning of fixed brains, we matched cells in corresponding volumes of image stacks acquired in vivo and in fixed brain slices. In GAD67-GFP mice, more than 95% of the GABAergic cells could be unambiguously matched, even in large volumes comprising more than a thousand interneurons. Triple immunostaining revealed a depth-dependent distribution of interneuron subtypes with increasing abundance of PV-positive neurons with depth. Most importantly, the triple-labeling approach was compatible with previous in vivo calcium imaging following bulk loading of Oregon Green 488 BAPTA-1, which allowed us to classify spontaneous calcium transients recorded in vivo according to the neurochemically defined GABAergic subtypes. Moreover, we demonstrate that post hoc immunostaining can also be applied to wild-type mice expressing the genetically encoded calcium indicator Yellow Cameleon 3.60 in cortical neurons. Our approach is a general and flexible method to distinguish GABAergic subtypes in cell populations previously imaged in the living animal. It should thus facilitate dissecting the functional roles of these subtypes in neural circuitr

Calcium indicator loading of neurons using single-cell electroporation

Studies of subcellular Ca2+ signaling rely on methods for labeling cells with fluorescent Ca2+ indicator dyes. In this study, we demonstrate the use of single-cell electroporation for Ca2+ indicator loading of individual neurons and small neuronal networks in rat neocortex in vitro and in vivo. Brief voltage pulses were delivered through glass pipettes positioned close to target cells. This approach resulted in reliable and rapid (within seconds) loading of somata and subsequent complete labeling of dendritic and axonal arborizations. By using simultaneous whole-cell recordings in brain slices, we directly addressed the effect of electroporation on neurons. Cell viability was high (about 85%) with recovery from the membrane permeabilization occurring within a minute. Electrical properties of recovered cells were indistinguishable before and after electroporation. In addition, Ca2+ transients with normal appearance could be evoked in dendrites, spines, and axonal boutons of electroporated cells. Using negative-stains of somata, targeted single-cell electroporation was equally applicable in vivo. We conclude that electroporation is a simple approach that permits Ca2+ indicator loading of multiple cells with low background staining within a short amount of time, which makes it especially well suited for functional imaging of subcellular Ca2+ dynamics in small neuronal network

Dynamic reorganization of the cortico-basal ganglia-thalamo-cortical network during task learning

Adaptive behavior is coordinated by neuronal networks that are distributed across multiple brain regions such as in the cortico-basal ganglia-thalamo-cortical (CBGTC) network. Here, we ask how cross-regional interactions within such mesoscale circuits reorganize when an animal learns a new task. We apply multi-fiber photometry to chronically record simultaneous activity in 12 or 48 brain regions of mice trained in a tactile discrimination task. With improving task performance, most regions shift their peak activity from the time of reward-related action to the reward-predicting stimulus. By estimating cross-regional interactions using transfer entropy, we reveal that functional networks encompassing basal ganglia, thalamus, neocortex, and hippocampus grow and stabilize upon learning, especially at stimulus presentation time. The internal globus pallidus, ventromedial thalamus, and several regions in the frontal cortex emerge as salient hub regions. Our results highlight the learning-related dynamic reorganization that brain networks undergo when task-appropriate mesoscale network dynamics are established for goal-oriented behavior

Representation of Thermal Information in the Antennal Lobe of Leaf-Cutting Ants

Insects are equipped with various types of antennal sensilla, which house thermosensitive neurons adapted to receive different parameters of the thermal environment for a variety of temperature-guided behaviors. In the leaf-cutting ant Atta vollenweideri, the physiology and the morphology of the thermosensitive sensillum coeloconicum (Sc) has been thoroughly investigated. However, the central projections of its receptor neurons are unknown. Here we selectively stained the three neurons found in single Sc and tracked their axons into the brain of Atta vollenweideri workers. Each of the three axons terminates in a single glomerulus of the antennal lobe (Sc-glomeruli). Two of the innervated glomeruli are adjacent to each other and are located laterally, while the third one is clearly separated and located medially in the antennal lobe. Using two-photon Ca2+ imaging of antennal lobe projection neurons, we studied where in the antennal lobe thermal information is represented. In the 11 investigated antennal lobes, we found up to 10 different glomeruli in a single specimen responding to temperature stimulation. Both, warm- and cold-sensitive glomeruli could be identified. The thermosensitive glomeruli were mainly located in the medial part of the antennal lobe. Based on the general representation of thermal information in the antennal lobe and functional data on the Sc-glomeruli we conclude that temperature stimuli received by Sc are processed in the medial of the three target glomeruli. The present study reveals an important role of the antennal lobe in temperature processing and links a specific thermosensitive neuron to its central target glomerulus

Representation of visual scenes by local neuronal populations in layer 2/3 of mouse visual cortex

How are visual scenes encoded in local neural networks of visual cortex? In rodents, visual cortex lacks a columnar organization so that processing of diverse features from a spot in visual space could be performed locally by populations of neighboring neurons. To examine how complex visual scenes are represented by local microcircuits in mouse visual cortex we measured visually evoked responses of layer 2/3 neuronal populations using 3D two-photon calcium imaging. Both natural and artificial movie scenes (10 seconds duration) evoked distributed and sparsely organized responses in local populations of 70–150 neurons within the sampled volumes. About 50% of neurons showed calcium transients during visual scene presentation, of which about half displayed reliable temporal activation patterns. The majority of the reliably responding neurons were activated primarily by one of the four visual scenes applied. Consequently, single-neurons performed poorly in decoding, which visual scene had been presented. In contrast, high levels of decoding performance (>80%) were reached when considering population responses, requiring about 80 randomly picked cells or 20 reliable responders. Furthermore, reliable responding neurons tended to have neighbors sharing the same stimulus preference. Because of this local redundancy, it was beneficial for efficient scene decoding to read out activity from spatially distributed rather than locally clustered neurons. Our results suggest a population code in layer 2/3 of visual cortex, where the visual environment is dynamically represented in the activation of distinct functional sub-networks

iDISCO+ for the Study of Neuroimmune Architecture of the Rat Auditory Brainstem

The lower stations of the auditory system display a complex anatomy. The inner ear labyrinth is composed of several interconnecting membranous structures encased in cavities of the temporal bone, and the cerebellopontine angle contains fragile structures such as meningeal folds, the choroid plexus (CP), and highly variable vascular formations. For this reason, most histological studies of the auditory system have either focused on the inner ear or the CNS by physically detaching the temporal bone from the brainstem. However, several studies of neuroimmune interactions have pinpointed the importance of structures such as meninges and CP; in the auditory system, an immune function has also been suggested for inner ear structures such as the endolymphatic duct (ED) and sac. All these structures are thin, fragile, and have complex 3D shapes. In order to study the immune cell populations located on these structures and their relevance to the inner ear and auditory brainstem in health and disease, we obtained a clarified-decalcified preparation of the rat hindbrain still attached to the intact temporal bone. This preparation may be immunolabeled using a clearing protocol (based on iDISCO+) to show location and functional state of immune cells. The observed macrophage distribution suggests the presence of CP-mediated communication pathways between the inner ear and the cochlear nuclei

Fast two-layer two-photon imaging of neuronal cell populations using an electrically tunable lens

Functional two-photon Ca2+-imaging is a versatile tool to study the dynamics of neuronal populations in brain slices and living animals. However, population imaging is typically restricted to a single two-dimensional image plane. By introducing an electrically tunable lens into the excitation path of a two-photon microscope we were able to realize fast axial focus shifts within 15 ms. The maximum axial scan range was 0.7 mm employing a 40x NA0.8 water immersion objective, plenty for typically required ranges of 0.2–0.3 mm. By combining the axial scanning method with 2D acousto-optic frame scanning and random-access scanning, we measured neuronal population activity of about 40 neurons across two imaging planes separated by 40 μm and achieved scan rates up to 20–30 Hz. The method presented is easily applicable and allows upgrading of existing two-photon microscopes for fast 3D scanning

Unsupervised Behaviour Analysis and Magnification (uBAM) using Deep Learning

Motor behaviour analysis is essential to biomedical research and clinical diagnostics as it provides a non-invasive strategy for identifying motor impairment and its change caused by interventions. State-of-the-art instrumented movement analysis is time- and cost-intensive, since it requires placing physical or virtual markers. Besides the effort required for marking keypoints or annotations necessary for training or finetuning a detector, users need to know the interesting behaviour beforehand to provide meaningful keypoints. We introduce unsupervised behaviour analysis and magnification (uBAM), an automatic deep learning algorithm for analysing behaviour by discovering and magnifying deviations. A central aspect is unsupervised learning of posture and behaviour representations to enable an objective comparison of movement. Besides discovering and quantifying deviations in behaviour, we also propose a generative model for visually magnifying subtle behaviour differences directly in a video without requiring a detour via keypoints or annotations. Essential for this magnification of deviations even across different individuals is a disentangling of appearance and behaviour. Evaluations on rodents and human patients with neurological diseases demonstrate the wide applicability of our approach. Moreover, combining optogenetic stimulation with our unsupervised behaviour analysis shows its suitability as a non-invasive diagnostic tool correlating function to brain plasticity.Comment: Published in Nature Machine Intelligence (2021), https://rdcu.be/ch6p

Transport Coefficients from Large Deviation Functions

We describe a method for computing transport coefficients from the direct evaluation of large deviation function. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which is a scaled cumulant generating function analogous to the free energy. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green-Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.Comment: 11 pages, 5 figure