The in-vivo investigation of highly dynamic biological samples, for example the beating zebrafish heart, requires high-speed volume imaging techniques. Light-sheet microscopy is ideal for such samples as it records high-contrast images of entire planes within large samples at once. However, in order to obtain images of different planes, it has been necessary to move the sample relative to the fixed focal plane of the detection objective lens. This mechanical movement limits speed, precision and may be harmful to the sample. We have built a light-sheet microscope that uses remote focusing with an electrically tunable lens (ETL). Without moving specimen or objective we have thereby achieved flexible volume imaging at much higher speeds than previously reported. Our high-speed microscope delivers 3D snapshots of sensitive biological samples. As an example, we imaged 17 planes within a beating zebrafish heart at 510 frames per second, equivalent to 30 volume scans per second. Movements, shape changes and signals across the entire volume can be followed which has been impossible with existing reconstruction techniques. Abstract: The in-vivo investigation of highly dynamic biological samples, for example the beating zebrafish heart, requires high-speed volume imaging techniques. Light-sheet microscopy is ideal for such samples as it records high-contrast images of entire planes within large samples at once. However, in order to obtain images of different planes, it has been necessary to move the sample relative to the fixed focal plane of the detection objective lens. This mechanical movement limits speed, precision and may be harmful to the sample. We have built a light-sheet microscope that uses remote focusing with an electrically tunable lens (ETL). Without moving specimen or objective we have thereby achieved flexible volume imaging at much higher speeds than previously reported. Our high-speed microscope delivers 3D snapshots of sensitive biological samples. As an example, we imaged 17 planes within a beating zebrafish heart at 510 frames per second, equivalent to 30 volume scans per second. Movements, shape changes and signals across the entire volume can be followed which has been impossible with existing reconstruction techniques.

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.

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Adaptive behaviour crucially depends on flexible decision-making, which in mammals relies on the frontal cortex, specifically the orbitofrontal cortex (OFC) 1−9 . How OFC encodes decision variables and instructs sensory areas to guide adaptive behaviour are key open questions. Here we developed a reversal learning task for head-fixed mice, monitored the activity of neurons of the lateral OFC using twophoton calcium imaging and investigated how OFC dynamically interacts with primary somatosensory cortex (S1). Mice learned to discriminate 'go' from 'no-go' tactile stimuli 10,11 and adapt their behaviour upon reversal of stimulus-reward contingency ('rule switch'). Imaging individual neurons longitudinally across all behavioural phases revealed a distinct engagement of S1 and lateral OFC, with S1 neural activity reflecting initial task learning, whereas lateral OFC neurons responded saliently and transiently to the rule switch. We identified direct long-range projections from lateral OFC to S1 that can feed this activity back to S1 as value prediction error. This top-down signal updated sensory representations in S1 by functionally remapping responses in a subpopulation of neurons that was sensitive to reward history. Functional remapping crucially depended on top-down feedback as chemogenetic silencing of lateral OFC neurons disrupted reversal learning, as well as plasticity in S1. The dynamic interaction of lateral OFC with sensory cortex thus implements computations critical for value prediction that are history dependent and error based, providing plasticity essential for flexible decision-making.