In feedback processing, higher-level representations provide contextual information to lower levels, and facilitate perceptual functions such as contour integration and figure–ground segmentation3. However, we have limited understanding of the circuit and cellular mechanisms that mediate feedback influence. Here we use long-range all-optical connectivity mapping in mice to show that feedback influence from the lateromedial higher visual area (LM) to the primary visual cortex (V1) is spatially organized. When the source and target of feedback represent the same area of visual space, feedback is relatively suppressive. By contrast, when the source is offset from the target in visual space, feedback is relatively facilitating. Two-photon calcium imaging data show that this facilitating feedback is nonlinearly integrated in the apical tuft dendrites of V1 pyramidal neurons: retinotopically offset (surround) visual stimuli drive local dendritic calcium signals indicative of regenerative events, and two-photon optogenetic activation of LM neurons projecting to identified feedback-recipient spines in V1 can drive similar branch-specific local calcium signals. Our results show how neocortical feedback connectivity and nonlinear dendritic integration can together form a substrate to support both predictive and cooperative contextual interactions.Sensory processing in the neocortex requires both feedforward and feedback information flow between cortical areas Feedback influence from a higher visual area to primary visual cortex in mice engages nonlinear dendritic integration. However, feedback may recruit the active properties of apical dendrites to compensate for this distance-dependent attenuation5, providing a layer of nonlinear processing7. To map feedback connections and determine whether they can drive active dendritic processes, we focused on V1 and one of its prominent feedback sources—LM, which is considered to be the mouse homologue to primate V2 (ref. 8). We studied layer 5 intratelencephalic (IT) neurons, which project to other cortical areas9, possess apical dendrites capable of intrinsic electrogenesis10 and can be targeted using the Tlx3-cre transgenic mouse line9.To determine how cortico-cortical feedback modifies activity in the recipient circuit, we must solve two problems. First, we must map feedback connectivity and, second, we must understand how feedback is integrated at the single-cell level. A substantial proportion of feedback inputs innervate pyramidal cell apical dendrites in layer 1 -Kv2.1 in layer 5 IT neurons across V1 and LM , we compared each neuron’s responses to visual stimulation with and without photostimulation Fig.  by perfo18 of local functional connectivity in V1  and feedback (LM to V1) functional connectivity depends on relative topography. Locally, in both V1 and LM, photostimulation caused a spatially restricted facilitation consisting of directly targeted and synaptically recruited neurons , dendritic calcium spikes or a combination of both27. To assess whether global dendritic events carry a similar signature of surround facilitation as local events, we imaged somata and apical dendrites expressing GCaMP7s semi-sparsely, while presenting Gabor patches of increasing size as visual stimuli, which contain increasingly higher surround energy  of cells individually showed a significant effect of visual stimulus size on dendritic activity after controlling for somatic activity  on linear regression residuals, P < 0.05; n = 131), dendritic residuals were biased to prefer larger visual stimuli than their parent somata . Detection of spines active in isolation  target grid in LM composed of thousands of targets and recorded the responses of all of the visible spines on apical dendrites that we imaged in V1 Fig. . In thesD target P = 0.0002; Fig. Having identified excitatory connections between LM neurons and V1 apical dendrites, we next examined whether this excitatory feedback can recruit local dendritic calcium signals. Notably, in the apical tuft of some V1 layer 5 pyramidal neurons, LM stimulation triggered local dendritic calcium events that resembled the visually evoked local events shown in Fig. Taken together, these results reveal several features of feedback. First, feedback suppression is dense, arising from many LM neurons. Second, feedback facilitation is sparse, arising from few LM neurons. Third, feedback can drive dendritic branch-specific local calcium signals that are spatially extended beyond individual feedback-recipient spines. Finally, feedback-driven dendritic calcium signals can be large enough to account for local dendritic calcium events driven by visual stimuli. Overall, these results establish a causal connection between LM feedback and apical dendritic calcium signals reflecting nonlinear postsynaptic integration.29, behaviour6 or, on shorter timescales, by moment-to-moment variations in behavioural state25. To examine whether behavioural state regulates feedback and dendrites, we focused on locomotion31 and found that it enhances visual responses in layer 5 of LM . Identifying the inhibitory circuits that mediate feedback suppression will be crucial. Our demonstration of a ‘facilitating surround’ in turn provides a circuit mechanism for cooperative interactions between stimuli and their sensory context41 as well as for excitatory responses to surround-only visual stimuli42. Silencing LM reduces V1 responses to surround-only visual stimuli17, which is consistent with our results on LM to V1 functional connectivity, and our demonstration that LM inputs can engage dendritic nonlinearities in V1. The generality of these results may be constrained by technical factors such as the limited temporal resolution of GCaMP, which may obscure faster modulations of feedback43. Similarly, functional connectivity may depend on visual contrast, feature selectivity, cell types, cortical layer and source area. It will be crucial to understand these dependencies and identify the synaptic wiring diagram that underlies functional connectivity.Our experiments reveal findings about the organization of cortical feedback, nonlinear dendritic integration and their relationship in vivo. First, we developed a powerful all-optical strategy for investigating the functional connectivity between brain areas at cellular resolution, which revealed a retinotopic organization of feedback in visual cortex—LM is relatively more suppressive of V1 when connections are between regions responsive to the same part of visual space. Conversely, LM is relatively more facilitating of V1 when connections are between regions responsive to more distant parts of visual space. This ‘suppressive centre, facilitating surround’ organization contrasts with feedback from the frontal cortex—projections from cingulate cortex exhibit a facilitating centre and suppressive surround in V126 but could also involve other mechanisms, such as other types of dendritic spikes21 or intracellular calcium release44.To understand how feedback works, it is essential to reveal how it is implemented at the cellular level. By combining targeted stimulation of neurons in LM with high-resolution imaging of dendritic arbours in V1, we provide a demonstration of independent local dendritic events selectively recruited by sensory stimuli designed to enhance feedback. We then identify feedback-recipient spines and show directly that the stimulation of feedback inputs to these spines can both drive and enhance branch-specific dendritic calcium signals extending beyond the identified spines. These findings suggest that feedback from LM contributes to the generation of active dendritic events in response to visual stimuli. It will be important to determine whether LM inputs or any other specific inputs are necessary for the recruitment of active dendritic events, and whether natural patterns of feedback activity recruit them. It will also be important to confirm the underlying voltage profile, true frequency and biophysical basis of these events, which are consistent with NMDA spikes47. Here we show that sensory context  also engages nonlinear dendritic mechanisms within apical tuft dendrites. By showing that feedback inputs can trigger local events in individual dendritic branches, and can also produce branch-specific boosting of dendritic activity, our study provides crucial support for the longstanding proposal that branch-specific computations are exploited in vivo26. Describing dendritic recruitment rules under natural behavioural and sensory conditions will be critical to a mechanistic understanding of how feedback contributes to cortical computations such as contour integration and figure–ground segmentation3. Feedback may generate somatic responses directly17 by driving active dendritic events, or it could indirectly affect dendritic integration, as engaging dendritic nonlinearities can change input–output gain both locally48 and globally24 to make other inputs, such as long range horizontal inputs49, more effective. Such gain control may allow contour integration to rely on the cooperative interaction of feedback and horizontal excitatory connections50. As basal dendrites also receive feedback4, it will be important to understand how their excitability may also be involved in mediating feedback influence.Active dendritic integration has been shown to contribute to feature selectivityFinally, we find that active behavioural states are associated with increased activity in a prominent feedback source to V1, increased input onto apical dendrites and modulation of dendritic calcium signals in a manner consistent with feedback topography. Our results suggest a model in which coordinated regulation of feedback and apical dendritic excitability contributes to sculpting visual representations. As interareal feedback projections and active dendritic integration are both ubiquitous features of the neocortex, the fact that they are systematically related suggests that these mechanisms may represent general principles governing coordination among cortical areas.All experimental procedures were carried out under license from the UK Home Office in accordance with the UK Animals (Scientific Procedures) Act (1986).Tlx3-cre or Tlx3-cre;CaMKII-tTA;TITL-GCaMP6s mice aged between seven and ten weeks were used. Tlx3-cre (PL56) is a GENSAT BAC transgenic and has been previously described51. The other two parental lines were obtained from The Jackson Laboratories , 024104, ref. 53). Four to eight hours before surgery, mice were given an injection of dexamethasone 54. Immediately before surgery, mice were given a subcutaneous injection of buprenorphine hydrochloride  and anaesthetized with isoflurane . The scalp was removed and an aluminium or titanium headplate with an 11 mm circular opening was fixed to the skull with dental cement . A craniotomy was performed over the caudal-lateral cortex and the dura was carefully removed. A calibrated pipette  bevelled to a sharp point and connected to a hydraulic injection system (Narishige MO-1) was used to inject virus, which was diluted in a buffer solution . Virus injections were made 500 µm below the surface at 0.1 µl min−1. Injection locations were determined using stereotactic coordinates and blood vessel patterns. Subsequent retinotopic mapping was used to confirm intended coverage of the visual cortex. After each injection, the pipette was maintained in position for 5 min before retraction. Chronic imaging windows were constructed using a single 4 mm coverslip with small pieces of coverslip optically glued to the top side to serve as an added surface to support the dental cement. Craniotomies were sealed with cyanoacrylate glue  and windows were fixed in place with dental cement. The animals were allowed to recover for at least 5 days. Subsequently, the animals were acclimatized to the microscopes and Styrofoam running wheels for 2–5 sessions before experiments. The number of mice included in each experiment was as follows: two-photon stimulation and population imaging . Expression of calcium indicator and opsin was achieved by injecting AAV2/9-Ef1a-DIO-C1V1(t/t)-mRuby2-Kv2.1  diluted 1:13 from a stock concentration of around 6.9 × 1014 genome copies (g.c.) per ml into Tlx3-cre;CaMKII-tTA;TITL-GCaMP6s animals. 200 nl of virus each was injected into a grid of six locations positioned about 300 µm apart over LM and V1, guided by the blood vessel patterns. Two-photon calcium imaging was performed using 920 nm light delivered from a tuneable laser . Simultaneous two-photon optogenetic excitation was performed using 1,030 nm light delivered from a fixed wavelength fibre laser at a 1 MHz repetition rate . The objective used was a 16×/0.8 NA  or a 10×/0.5 NA  objective, yielding FOV sizes of 1,215 or 1,920 µm respectively. Volumetric calcium imaging data were acquired using an electrically tuneable lens  focusing four planes spaced by 30 µm  or two planes spaced by 50 µm . Power post-objective was between 50–100 mW depending on expression level and imaging depth, which was 350–450 µm below the pia. Two-photon optogenetic stimulation was performed using a programmable reflective spatial light modulator (SLM) installed in-line with the stimulation path63. The 16×/0.8 NA objective was paired with an SLM (Boulder Nonlinear Systems) with 512 × 512 pixels and 7.68 mm × 7.68 mm active area, whereas the 10×/0.5 NA objective was paired with an SLM (Meadowlark Optics) with 1,920 × 1,152 pixels and 17.6 mm × 10.7 mm active area. Phase masks were computed using the weighted Gerchberg–Saxton algorithm and loaded using Blink (Meadowlark). The SLM was calibrated to compensate for the decrease in diffraction efficiency for peripheral targets, and power per neuron kept constant at 12 mW. Imaging space to SLM space conversion was achieved by burning 3D patterns into plastic slides, taking volumetric stacks, measuring burn locations and fitting affine transformations. To increase stimulation efficiency, the centre of the SLM space was offset using galvanometers such that it was close to the centroid of the current stimulation targets. Calibrations were performed using custom software written in MATLAB64 (https://github.com/llerussell/SLMTransformMaker3D). Stimulation patterns consisted of multiple beamlets targeting between 6 and 14 neurons. Beamlets were scanned using galvanometers moving in spiral scan patterns . Synchronization was performed as previously described64. FOVs over V1 and LM were determined using retinotopic maps obtained from preparatory wide-field and two-photon retinotopic mapping sessions (see below). For stimulation experiments, FOVs were relocated using blood vessel patterns and the data were affine transformed to register the field to previously obtained retinotopic maps. At the beginning of the experiment, neurons responsive to photostimulation were detected using the near automatic photoactivation response mapping  protocol described previously64. Stimulation clusters were then designed by randomly choosing seed neurons and finding their nearest neighbours from all photoresponsive neurons. A 200-µm-wide V1/LM border zone and the top 50 lines of the two-photon frames were excluded from consideration as targets. In each experiment, between 5 and 10 (8 ± 1.1) target clusters were stimulated for a total of 129 clusters in LM and 180 clusters in V1 in 42 sessions, 15 animals. Experiments contained 1,337 ± 142 trials (mean ± s.d.). Of these trials, 20% (in 40 out of 42 experiments) or 50% (in 2 out of 42 experiments) contained only visual stimulation composed of a 2 s stimulus and 6 s intertrial interval . The remaining trials contained the same visual stimulus and a two-photon photostimulus  of a single target cluster . Each cluster was stimulated in 52 to 175 (mean = 133.4 ± 25) trials.Simultaneous all-optical interrogation across LM and V1 circuits was carried out by adapting existing approachesEf1a-DIO-FLPo  diluted 1:75,000 to 1:100,000 from a stock concentration of 1.4 × 1013 g.c. per ml and AAVDJ-Ef1a-fDIO-GCaMP6s  diluted 1:9 from a stock concentration of 7.0 × 1012 g.c. per ml. Dilutions reported are final. A total of 100 nl of virus was injected into each of two to four locations positioned about 500 µm apart in V1 of Tlx3-cre mice. High-magnification apical tuft imaging , or 4–6 z-depths when C1V1 expression was Cre-independent and spanned the depth of LM . Targets were stimulated in random groups of 8 to 25 targets , with each group stimulated only once. A total of 420 to 1,260 unique groups  were used per experiment, in which every target participated in 8 to 16 groups . Stimulation was performed with 12–16 mW per target every 1.25 s (21 recordings) or 2 s (5 recordings) and lasted 500 ms. The imaging and stimulation scan paths were configured to be parfocal, with the SLM addressing light to stimulate spots both above and below its focal plane. The imaging plane was moved along the z-axis to image either somatic or dendritic signals using an ETL. Dendritic imaging FOVs spanned 80 to 150 µm to a side. Responses were recorded for 15 to 25 min using 30 to 50 mW average power, and imaging data were rigidly registered as they were acquired to correct for motion artifacts online.We developed a new strategy for simultaneous ultrasparse two-photon dendritic imaging in V1 and two-photon optogenetic stimulation in LM. Expression of calcium indicator and opsin were achieved by injecting the same virus mixtures and dilutions as above for two-photon optogenetic stimulation during population imaging, and dendritic imaging of apical tufts with ultrasparse expression, with one difference. Expressing calcium indicator in LM neurons causes their axons to fluoresce in layer 1 of V1, interfering with sparse imaging of the apical dendrites of V1 neurons. To avoid this problem, the calcium indicator virus injections were targeted to V1 only, using blood vessel patterns as a guide. The opsin virus injections were targeted to LM only to avoid unintended activation of V1 neurons. The expression locations were later confirmed using retinotopic mapping. Experiments were performed using the same equipment as the two-photon optogenetic stimulation and population imaging experiments above, with a 10×/0.5 NA objective. An image of the brain surface over the two-photon FOV was affine transformed onto the brain surface image obtained previously in wide-field intrinsic imaging. The wide-field retinotopic map was then used to assign a retinotopic location for each position in the two-photon FOV. For the experiments that produced the non-specific suppression results shown in Fig. 66. We therefore searched for feedback-responsive spines in apical dendrites using the following strategy. The registered recordings and their average images were used to place small elliptical ROIs over all protrusions from the dendrite that could represent a spine. ROIs were assigned and fluorescence-extracted using ImageJ. These traces were transformed to (F − F0)/F0 where F0 was defined as the 10th percentile of a 90 s moving window. A stimulus response for each ROI on each trial (∆R) was calculated by averaging fluorescence in the nine frames before each stimulation and subtracting it from the average fluorescence in the seven frames after the offset of each stimulation, avoiding any stimulation artifact. Independent spine activity was used to identify spines that were potentially driven by stimulation. ∆R for each spine across trials was compared to the average ∆R across all spines (∆Rmean). As most activity was correlated across spines, these plots often contained diagonally extended distributions of data  of these trials, they were further collected for inspection of all of the trials on which those targets were stimulated, regardless of whether they generated independent activity. This analysis was then repeated iteratively, while varying the thresholds set on ∆R (mean + 0.5 s.d. to 3 s.d.), ∆Rmean (mean + 0.5 s.d. to 1.5 s.d.) and the percentage reliability (10 to 20%). This process reduced the number of possibly effective target–spine combinations to a number that could be visually inspected online. Among these possible connections, the 1 to 15  most promising candidates were selected on the basis of the overall reliability and temporal profiles of the responses. New stimulation groups composed of these targets were designed to confirm whether any were indeed connected. In early experiments (n = 2) these confirmation blocks were composed of 20 min of recording in which 22 random combinations of the selected targets were stimulated, and the experiment ended there. Data from these confirmation blocks were used for the boosting analysis in Fig. n = 16) the experiment was started by mapping receptive fields using sparse noise stimulation and somatic imaging. When both a confirmed target–spine combination as well as a receptive field were obtained in the same neuron, feedback stimulation was combined with presentation of an inverse visual stimulus , we also delivered sparse noise stimuli during feedback stimulation. These data are not shown separately.Feedback inputs in the visual cortex are known to make contacts with both apical and basal dendrites of L5 pyramidal neurons13 g.c. per ml and AAV2/1- or AAV2/9-CAG-FLEX-tdTomato  diluted 1:150 from a stock concentration of 2.1 × 1013 g.c. per ml. A total of 20–50 nl of virus was injected into each of four locations around 500 µm apart in V1 of Tlx3-cre mice. Imaging was performed using the same set-up as for apical tuft imaging (above). An ETL was used for volume imaging, with two planes positioned in layer 5 to capture somata, and two imaging planes around the bifurcation of apical dendrites at the layer 1 to layer 2/3 transition67. Imaging was performed at 6.6 Hz final framerate per plane using 920 nm excitation.Semisparse expression of calcium indicator was achieved  diluted 1:2 from a stock concentration of 2.7 × 1013 g.c. per ml, and AAV2/1-CAG-FLEX-iGABASnFR.F102G  diluted 1:2 from a stock concentration of 5.1 × 1012 g.c. per ml. A total of 500 nl of virus was injected into each of two locations in V1 positioned 1 mm apart. Simultaneous expression of red calcium indicator and green glutamate indicator70 was achieved using the following virus mixture: AAV2/1-Synapsin1-FLEX-NES-jRGECO1a  diluted 3:4 from a stock concentration of 2.7 × 1013 g.c. per ml mixed with AAV2/1-CAG-FLEX-SF-iGluSnFR-A184S diluted 1:4 from a stock concentration of 1–5 × 1012 g.c. per ml (gift from J. Marvin and L. Looger). A total of 200 nl of virus was injected into each of four locations positioned about 300 µm apart in V1 of Tlx3-cre mice. Imaging was performed using the same equipment as for dendritic imaging, with the addition of a Coherent Fidelity-2 fibre laser for excitation of jRGECO1a at 1,070 nm. The lasers were co-aligned through one scan path and the total power was kept below 100 mW. FOVs were 250 µm to 400 µm wide. Volume imaging was performed using either a piezoelectric objective positioner (Physik Instrumente) or an ETL (Optotune). When using a piezoelectric objective positioner, one plane was acquired in layer 5 and one plane was acquired in layer 1. Layer 1 imaging planes were positioned 30 to 100 µm below the pia. When using an ETL, two planes were acquired in each layer. Imaging was performed at 6.6 Hz final framerate per plane.Simultaneous expression of red calcium indicator71. Wide-field imaging was performed using calcium fluorescence for all animals except for those used in the two-photon optogenetic stimulation during dendritic imaging experiments. These animals had calcium indicator expression restricted to V1 only. We therefore used intrinsic signals obtained under anaesthesia to produce retinotopic maps. This allowed localization of LM and V1 to guide the appropriate placement of two-photon imaging FOVs. Ultrasparse apical tuft imaging experiments were started with wide-field-map-guided FOV placement and proceeded with receptive field mapping using forward correlation. The stimulus used here was an 8 by 8 grid of 8° squares that transitioned from grey to black to white and back at 2 Hz for 2 s, one at a time on a grey background. Squares were visited in pseudorandom order, with a 1 s intertrial interval for a total of 8 times per square in one 10 min run. Receptive fields were calculated online by averaging deconvolved responses to each grid position, using data from one to three runs. Ultrasparse volume imaging experiments  spatial frequency drifting in one of eight directions  at a 2 Hz temporal frequency. During stimulation, a full-field grating was displayed  drifting in one of four directions—0°, 90°, 180°, 270°—for 2 s, followed by a 4 s baseline period. In ultrasparse imaging experiments  using the cftool in MATLAB. The surface fits were used to infer receptive field positions for optogenetic experiment targeting and analysis after ROI coordinates were corrected for two effects. First, they were transformed to compensate for magnification changes associated with ETL engagement. Second, ROI coordinates were transformed to compensate for FOV changes across imaging sessions using affine transformations fit to match surface blood vessel patterns recorded in receptive field mapping sessions and photostimulation sessions. Finally, we used the centroid locations of responding neurons to infer their azimuth and elevation preferences from the fitted surface models. For online receptive field mapping  sparse noise receptive field mapping, neuropil-subtracted and deconvolved event traces were used. Event traces were denoised by thresholding at twice their s.d. over their mean. Event-triggered stimulus ensembles were generated for every neuron by collecting the stimuli that preceded each event in a 2 s period and weighting those stimuli by the size of each event they preceded. The mean over event-triggered stimulus ensembles was calculated for that 2 s window and the value in each stimulus frame and sparse noise grid position (10 × 10) was expressed as a rse Fig. ) fluoresF − F0)/F0 representation, where F0 was assigned as the 10th percentile of all samples in a 2,000 frame rolling window. The response of every neuron on every trial was represented as a signal-to-background ratio. First, the mean (F − F0)/F0 value in a 500 ms window after the end of photostimulation , was computed . Next, the mean (F − F0)/F0 value in a 500 ms window preceding visual stimulus onset was computed (Bi). Finally, the difference Si − Bi was divided by the s.d. of the Bi values over trials i-2, i-1 and i. We call this value RiV+P if during that trial both a visual stimulus and a photostimulus were delivered, and RiV if only a visual stimulus was delivered. For every stimulated cluster separately, significantly responsive neurons (responders) were detected in two steps. First, after randomly sampling of RiV trials to match the proportions of visual stimulus orientations between RiV+P and RiV trials, a Wilcoxon rank-sum test was performed between the two trial types (RiV+P and RiV). Running different random samples did not change the ultimate result. Second, multiple comparisons were corrected for by controlling the FDR using mafdr in MATLAB74. The results reported in Figs. P < 0.025) produced such a negative difference, while a substantial proportion did in the feedforward direction (P ≫ 0.025). This indicates that the suppressive-centre facilitating-surround profile of feedback was maintained in stimulation-strength-matched samples, and was therefore not caused by differences in local stimulation strength. We then repeated this analysis, equalizing retinotopic spread and physical distance to across-area responders, neither of which abolished the effect  divided by the total number of trials yielded a response probability (Presponse). All distances were measured as the Euclidean distance in 3D. For axial measurements, only ROIs that had a target within one lateral HWHM (20.7 µm) were taken into account and the axial distance was measured as the Z-offset to this target.The spatial extent of the photostimulation was quantified using an approach similar to previously published methods−1. Two datasets were combined for this analysis: visual stimulus only (V-type) trials from the functional connectivity experiments (n = 42 sessions) described above and V-type trials from a separate set of optogenetic connectivity experiments (n = 32 sessions), the same as the above in every respect other than that we presented 20° gratings during photostimulation instead of full-field gratings. For this analysis, the visual response of every recorded neuron was represented as the difference Si − Bi as described above. Neurons were included for comparison based on retinotopic representation, visual response magnitude and reliability. Neurons were required to have retinotopic locations within 30° of the stimulus centre. For full field stimuli, the centre was defined as the centre of a very large Gaussian mask that was present over the stimulus but had negligible effect on the visible contrast. Neurons were required to pass a Wilcoxon signed-rank test for visual responsiveness (Bi versus Si) at P = 0.01 after Bonferroni correction, for at least one of the two stimuli displayed. Furthermore, neurons were required to have responded significantly on 30% of trials, with significance assessed using the threshold Z = 1.64 computed as above, under resolution measurement. To quantify the modulation of visually evoked responses with locomotion, a modulation index was computed per neuron as the difference between the mean response to the preferred stimulus of that neuron R = (Si − Bi) on locomotion trials and the mean response on stationary trials, normalized to the mean response on stationary trials (Δresponse = (Rrun − Rsit)/Rsit). This value was averaged across all neurons in the same area within each session and a signed-rank test was performed between paired measurements of Δresponse from LM and V1 across all sessions.Styrofoam wheel motion was recorded using quadrature encoders (Kubler). Wheel displacement traces were differentiated and filtered with a 2.5 s moving average. Any trial of stimulus presentation in any experiment was assigned as a locomotion trial if the running speed during that trial exceeded a threshold of 3 cm s78 in fine apical tuft dendrites of individual pyramidal cells expressing GCaMP using our ultrasparse expression strategy, imaging data were motion-corrected and downsampled fourfold in time to produce videos for inspection. Events were required to involve at least two spines active simultaneously, along with the dendritic branch between them, in the absence of simultaneous activity on the proximal end of the imaged dendrite. On the basis of these criteria, two experimenters (M.F. and D.H.), blinded to the visual stimulus timing and type, inspected all of the videos acquired independently, and then resolved discrepancies to arrive at consensus on the location and timing of dendritic events. ROIs were then hand drawn over the dendritic segments where events were identified, and over dendritic segments proximal to those, to compare integrated fluorescence and confirm the presence of an event in the distal ROI and the absence of the event in the proximal ROI. Automated detection of these events proved challenging for several reasons. First, local events could occur anywhere along the dendrite and could have varying spatial extents. Second, local events had varying signal-to-noise and varying rise and decay times in comparison to global events recorded in the same branch. Third, many events were bright and clearly involved a single spine and its parent branch, but a second spine could not be unambiguously identified. Some of these events must also be true multispine events in which the additional spines were not spatially resolved by our imaging, but we chose to be conservative and excluded any such events in which a second spine was not identifiable. Together, these features made the automated assignment of spatial ROIs, thresholds and other exclusion criteria a high dimensional task poorly constrained by the limited number of local events that we found /F0, where F0 was assigned as the 10th percentile of the fluorescence in a moving window 45 s wide. This trace was then normalized to the s.d. of the whole trace over time. Fluorescence was also smoothed across space within individual time bins with a 2 µm moving average. Finally, the spatial profile of each event was calculated by averaging across identified frames, and events aligned and normalized to their respective fluorescence peaks across space. An idealized local event was generated by averaging across events, which was then fit with the sum of three Gaussians.To identify local eventsImaging data were motion-corrected offline using the two-step procedure of Suite2P (v.0.9.2), and ROIs were hand drawn to avoid cross-talk with nearby processes. For the five neurons that showed a significant positive effect, we confirmed that ROIs that were segmented and neuropil subtracted using Suite2P produced the same result. Visual responses were quantified as the peak difference in a seven-frame (~1 s) window starting three frames after visual stimulus onset in comparison to baseline measured in a four-frame window ending one frame before visual stimulus onset. Responses were averaged across all apical dendritic ROIs  and all basal ROIs excluding the soma (in the deepest imaging plane). From this point onwards, only trials that produced a visual response in the average of basal ROI signals that was greater than 20% of peak response in the average of basal ROIs were included in the analysis to focus on global events, similar to the analysis for semisparse dendritic imaging. The ratios between the apical and basal responses were quantified trial by trial. Responses to the two Gabor stimuli were pooled to construct a low-surround stimulus class and responses to the inverse and full-field stimuli were pooled for a high-surround class. The difference between the average ratios for these two stimulus classes was computed. To assess the significance of the ratio difference, the procedure was repeated 3,000 times, with trials shuffled between the stimulus classes, replicating the number of trials obtained for each class. Neurons that produced a difference of larger than 95% of shuffles were regarded as significant. To measure correlations between ROIs, the apical to basal ratios were computed taking the response of each apical ROI and comparing it to the average of all basal ROIs. This resulted in a vector of ratios for each apical ROI. The correlation between these vectors was computed for the last panel of Extended Data Fig. z-stacks, but not always unambiguously so, as even a slight density of expression commonly leads to crossings of neuronal processes at distances smaller than the imaging resolution. Changing the correlation thresholds to 0.55 (F) and 0.35 (events) did not alter the results qualitatively. Fluorescence traces were converted to (F − F0)/F0 where F0 was assigned as the mean fluorescence of that ROI across the entire recording duration. To measure the effect of visual stimulus size on dendritic activity, responses to the more effective orientation (two directions) were used. The response of every ROI on every trial was quantified as the modulation from the baseline, where the baseline was defined as the mean fluorescence in the three frames preceding stimulus onset and the response was defined as the mean fluorescence in the ten frames after stimulus onset. Next, the value for every trial was normalized to the peak fluorescence recorded from that ROI in any trial. The trials were then sorted and binned by the somatic activity level separately for each stimulus size. Binning was performed with 5% bin width, going from −40% of peak to 100% of peak. All trials from all neurons in each bin were then averaged to obtain one population level value each for soma and dendrite for each stimulus size and bin. Next, a two-way ANOVA was performed on population data to determine the effect of somatic activity, stimulus size and their interaction on dendritic activity , and were clearly a section through a soma and not an apical dendrite of a deeper soma. All ROIs segmented from our second most superficial imaging plane, which was placed just below layer 1, were included for analysis as ‘dendrite ROIs’. Our most superficial imaging plane often extended into layer 1 where apical dendrites had already ramified and the density of fluorescent processes was high. These data were excluded to analyse only sections through apical dendritic trunks of pyramidal neurons, with the goal of coming as close as possible to imaging the nexus across a population with variable nexus locations. Connected somata and dendrites were identified by examining correlations between fluorescence traces as well as the deconvolved event traces for every possible pairing of soma and dendrite ROIs /F0 where F0 was calculated as the 10th percentile of F across all timepoints separately for each acquisition block of 10 or 20 min. When two planes were acquired in each layer, the SnFR signals from the two planes within layer were averaged together. For the majority of iGluSnFR and all iGABASnFR sessions, receptive fields were mapped with sparse noise stimuli to confirm the retinotopic representation was well stimulated by our monitor. For the remaining iGluSnFR sessions, wide-field retinotopic maps were used. The linear models presented in Extended Data Figs. R2 = 0.292 ± 0.17 (mean ± s.d.) across 12 sessions. To assess the significance of interactions between locomotion and glutamate signals, we performed a Wald’s model comparison test, in which we compared the full model with a restricted model excluding both interaction terms. In total, 4 out of 12 sessions produced significance (Extended Data Fig. Layer 5 segmentations were manually curated to remove poorly sectioned neurons. Data were acquired in 10 or 20 min blocks of trials, and the first three trials excluded to remove a fast bleaching component. To represent population activity, the deconvolved event traces were averaged across segmented ROIs. To represent apical and basal SnFR fluorescence, the fluorescence recorded across the entire FOV was averaged and converted to (Further information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-023-06007-6.Reporting SummarySupplementary Video 1Local event observed in ultrasparse dendritic imaging. The video shows a single dendritic branch from a layer 5 pyramidal neuron in V1 with the proximal end identified. The recording is from a visual stimulation experiment and is downsampled fourfold in time from an acquisition rate of 26 Hz. During the recording, a single spine activation is seen first, followed by a local event involving multiple spines and a segment of the branch.Supplementary Video 2Global event observed in ultrasparse dendritic imaging. The video shows the same branch as in Supplementary Video 1. In this recording, a global event occurs, where the entire branch is active.Supplementary Video 3All-optical spine mapping experiment. The video shows two distal apical tuft dendrites of one neuron in V1. A spine responsive to photostimulation of a target location in LM is indicated by an arrowhead. Photostimulation times are indicated by a lightning symbol at the top left. The recording shows ten individual trials followed by an averaged response across 25 trials. The recording was downsampled fourfold in time from an acquisition rate of 30 Hz. The dendrite is the same recording as shown in Fig. 4f,h.Supplementary Video 4Photostimulation-induced local dendritic event. The video shows multiple apical tuft dendrites of one layer 5 pyramidal neuron in V1 with two photostimulation-responsive spines on the same branch, identified by pink arrowheads. Photostimulation is indicated by a lightning symbol at the top left. The recording shows three individual trials, of which the first two trials led to spine activations and the third trial led to an extended branch specific activation. This is followed by a global event with all of the branches active.


Here we combine heterologous expression and cellular electrophysiology with mathematical modeling to understand the mechanisms underlying this dual function of rat VGLUT1. When glutamate is the main cytoplasmic anion, VGLUT1 functions as H+-glutamate exchanger, with a transport rate of around 600 s−1 at −160 mV. Transport of other large anions, including aspartate, is not stoichiometrically coupled to H+ transport, and Cl- permeates VGLUT1 through an aqueous anion channel with unitary transport rates of 1.5 × 105 s−1 at −160 mV. Mathematical modeling reveals that H+ coupling is sufficient for selective glutamate accumulation in model vesicles and that VGLUT Cl- channel function increases the transport efficiency by accelerating glutamate accumulation and reducing ATP-driven H+ transport. In summary, we provide evidence that VGLUT1 functions as H+-glutamate exchanger that is partially or fully uncoupled by other anions.Vesicular glutamate transporters accumulate glutamate in synaptic vesicles, where they also function as a major Cl In glutamatergic neurons, synaptic vesicles contain glutamate, but not aspartate. Here, the authors show that vesicular glutamate transporters are H+/anion exchangers that attain high selectivity for glutamate via variable transport coupling. In the mammalian central nervous systems, three vesicular glutamate transporters  are responsible for filling the synaptic vesicles of excitatory neurons with glutamate4. VGLUTs are members of the SLC17 family, together with inorganic phosphate transporters, the lysosomal H+/sialic acid cotransporter sialin, and the vesicular nucleotide transporter VNUT1. Previous studies with vesicle preparations, with purified and reconstituted transporters or with a combination of heterologous expression and cellular electrophysiology demonstrated that VGLUTs are not only glutamate transporters, but also represent the main Cl- transport pathway in synaptic vesicles7. VGLUTs were additionally shown to function as K+/H+ exchangers in the synaptic vesicle, in the presence as well as in the absence of glutamate9, and to import phosphate from the extracellular space when residing in the plasma membrane10.Synaptic vesicles accumulate neurotransmitters via secondary active transporters that harness the electrochemical H+-coupled anion exchanger that varies its transport stoichiometry to select between different substrates and to permit Cl- efflux during glutamate accumulation.Here, we combine heterologous expression of plasma membrane-targeted mutant VGLUT1 and whole-cell patch clamping with mathematical modeling to describe the mechanistic basis of the glutamate transport and the anion channel functions and their role in selective glutamate transport into synaptic vesicles. We find that VGLUT1 functions as HPM) resulted in predominant surface membrane insertion in HEK293T cells  than VGLUT1PM currents , but above currents in untransfected cells . In agreement with earlier reports6, VGLUT1PM Cl− currents are activated by external Cl− and Br−, but not by I−  for cells dialyzed with internal Cl− or pKM = 6.1 ± 0.02  for cells dialyzed with internal NO3−  predict very fast opening and closing time constants. Experimental spectral densities exceeded the upper limit for the spectral density of uniporter-mediated shot noise (S = 4.4 × 10–29 A2/Hz) obtained by Schottky’s theorem (S(f) = 2Iq, with I = 273 ± 120 pA (n = 13) as the mean macroscopic current in the experiments used to determine the power spectra and the elementary charge as the net transported charge per shot17). Non-transfected HEK293T cells had lower current variances and power spectra resembling 1/f noise under the same conditions. These results demonstrate that VGLUT1 anion current-associated noise arises from the random opening and closing of individual channels.We used noise analysis to describe the anion channel function of VGLUT15.5 Fig. . VGLUT1PPM by variation of the external pH and measured stationary current noise at the end of 100–500 ms voltage steps to −160 mV  and 13 cells with internal NO3− . These values correspond to transport rates of 1.5 × 105 s−1 (intracellular Cl−) and 2.4 × 105 s−1 (intracellular NO3−), which largely exceed the transport rates of known transporters, thus demonstrating that anion conduction occurs via diffusion along an aqueous conduction pathway20. Noise analysis also provided the number of channels per cell, and these values were used to calculate the absolute open probabilities  than for NO3− .Figure ies Fig. . For the21. Figure 21), on the filter frequency. Solid lines represent the effect of filtering on normalized standard deviations of simulated single channel currents with one open and one closed state15 and with open times of 20, 28, and 40 µs. We conclude that VGLUT1 functions as Cl− or NO3− channel with very short open states.Since filtering in the range of the single event duration modifies apparent unitary current amplitudes, the duration of channel openings can be estimated by quantifying the consequences of low pass filtering on the current noise− channel that opens and closes upon changes in voltages. A physiologically important consequence of VGLUT1 channel gating is its pronounced inward rectification  to zero current levels  after dialysis with small anions, intracellular dialysis with large anions resulted in measurable positive currents that permitted quantification of the current reversal potential. This modification is due to alterations in the voltage dependence of VGLUT1PM. VGLUT1PM anion channels completely deactivate at positive potentials in cells internally dialyzed with Cl− , we observed less positive potentials for all other large anions . We conclude that VGLUT1PM transports multiple large anions across the membrane, but with the highest driving force for glutamate.Current amplitudes observed for glutamate and aspartate, gluconate, MES, MSA and isethionate were comparable at negative voltages. However, whereas glutamate currents reversed at −7.6 ± 5.7 mV  and increases inward currents, resulting in a shift of the current reversal potential to more positive values. Control experiments illustrate negligible background currents under these ionic conditions for all tested pHi. Figure rev) as function of the Nernst potential for H+ (EH) for VGLUT1PM glutamate currents for two different conditions, either with glutamate or with gluconate as main external anion. At pHi = 8.5 and glutamate on both membrane sides, reversal potentials  are positive to the predicted reversal potential for a glutamate uniporter (8.6 mV). The measured reversal potentials are neither compatible with glutamate uniport nor with choline-glutamate exchange by VGLUT1PM. Current reversal potentials become more negative with increasing [Cl−]o, opposite to the predictions of Cl−-glutamate exchange  or H+ (EH), F Faraday’s constant, R the universal gas constant, and T the absolute temperature. Weighted linear regression to EH-Erev plots   Fig. . Changes8.5 Fig. . These rnts Fig. , indicati and [Cl−]o with sums of H+-glutamate exchange currents (at 1:1 stoichiometry) and Cl− currents predicted by the Goldman-Hodgkin-Katz equation , and obtained unitary glutamate current amplitudes of 0.18 fA. Division of this unitary glutamate current amplitude by the two elementary charges that are translocated in one H+-glutamate exchange cycle results in a transport rate of around 561 ± 123 s−1 at −160 mV.We next determined unitary glutamate transport rates from macroscopic current–fluorescence plots for Clity Fig.  can be u+ coupling affect the vesicular neurotransmitter accumulation, we developed a continuum quantitative model of synaptic vesicles that describes acidification, substrate accumulation, and Cl- efflux using a set of differential equations33. We studied two VGLUT transport modes: stoichiometrically coupled H+-glutamate exchange and aspartate uniport as oversimplification of the partial uncoupling by aspartate ) with internal Cl- than for WT VGLUT1PM under the same conditions ; Fig. PM single channel amplitudes with internal NO3- were not increased compared with internal Cl- ). Figure PM anion currents for various small and large anions. H120A changes the relative I− conductance and, more importantly, shifts the VGLUT1 current reversal potentials measured in cells dialyzed with glutamate− or aspartate− toward more negative potentials : low transport rates at voltages around 0 mV make it difficult to detect changes in activity upon varying ΔpH. Additional experimental support for exclusively voltage-driven VGLUT transport was obtained from imaging experiments that demonstrated lower proton efflux rates for glutamatergic than for GABAergic synaptic vesicles36. Since absolute transport rates of VGATs have not yet been determined and little is known about vesicular H+ or HCO3− leak current, we believe that these experiments leave space for coupled exchange combined with additional anion channel activity by VGLUTs.VGLUTs are currently assumed to function as glutamate uniportersPM transport functions fully account for earlier work with vesicle preparations, and VGLUT1PM whole-cell currents closely resemble whole-cell or whole oocyte currents of another surface membrane-optimized mutant VGLUT6 and whole endosome currents of WT VGLUT17. All these results indicate that the amino acid substitutions in VGLUT1PM do not cause major changes in transport functions. To test for coupled H+-glutamate exchange, we measured the pHi dependence of current reversal potentials  and that aspartate and H+ transport are partially uncoupled. H120A reduces glutamate uptake30 via abolished proton coupling .HEK293T cells (Sigma-Aldrich) were transiently transfected using a lipofectamine precipitation method and examined 24 h later. Stably transfected Flp-In T-Rex 293 were used after induction with 1.5 µg/ml tetracycline for a maximum of 24 h6, we mutated various dileucine-like endocytosis motifs to alanine to promote plasma membrane insertion  predominantly localized to the surface membrane  at the 3ʹ end of the transporter coding region. Using a method similar to Eriksen et al.46. We used borosilicate pipettes  with resistances of 0.9–3 MΩ and applied series resistance compensation and capacitance cancellation, resulting in a voltage error of <5 mV. The standard bath solution contained (in mM) 136 choline chloride, 2 MgCl2, and 30 HEPES, and we adjusted the osmolarity of the bath solution with glucose to a value of 15 mOsm/l higher than the internal solution. For external and internal pH values between 6.5 and 8.5, HEPES was used as the buffer and adjusted with choline hydroxide; for more acidic perfusion solutions, 30 mM HEPES was replaced with 50 mM MES and the pH was adjusted with choline hydroxide. Experiments with an internal pH of <6.5 activated endogenous currents, which prevented the reliable determination of VGLUT1PM currents under these conditions. In experiments with large polyatomic anions in the pipette solution, 100 mM choline chloride was replaced by choline gluconate in the bath solution; and cells were held at −50 mV. In some of the experiments to assess the transport stoichiometry, gluconate was fully substituted by glutamate  140 choline anionX, 5 EGTA, 5 Mg(OH)2, and 30 HEPES, adjusted to pH 7.4 with TMA-OH . Solutions containing HCO3− were oxygenated with carbogen (5% CO2 in O2) until the start of the experiment. We used external and/or internal agar salt bridges (made from plastic tubing filled with 0.5 M KCl in 2% agar) to connect the Ag/AgCl electrode. Junction potentials were used to correct the results. VGLUT1PM currents are much larger than background for all tested anions, and VGLUT1PM currents are blocked by Rose Bengal ate Fig. , and in 47. Mean fluorescence intensities were determined for the whole cell body using Fiji (http://www.fiji.sc) and given as arbitrary units (AU). Since transporters are expressed as fluorescent fusion proteins, whole-cell eGFP fluorescences are proportional to the number of transporters per cell. We did not distinguish fluorescences of intracellular compartments and the surface membrane. Cells are always imaged before establishing the whole-cell mode, and we assume that every tested cell exhibits a similar subcellular distribution of transporters and that the whole-cell fluorescence provides a value proportional to the number of transporters in the surface membrane48. Possible limitations of this approach are changes in the percentage of transporters in the surface membrane because of saturation of the intracellular trafficking machinery49 and inaccuracies due to predominant intracellular localizations of the protein under study50. For VGLUT1PM, there are no indications for saturation of whole-cell currents with increasing expression  set to 488 nm and recorded using a Neo 5.5 sCMOS (Andor)on Figs.  and 3i, x and fcx the amplitude and corner frequencies.For noise analysis, currents were digitized with a sampling frequency of 100 kHz, and power spectra were calculated from steady-state currents during 50-s voltage jumps to −100 mV  using fast Fourier transformation. Data were binned into 2300 data points, averaged over all measured cells, and fitted by the sum of double Lorentzian function and a term representing pink noise:PM can be caused by pH-dependent unitary current amplitudes or pH-dependent open probabilities. The current variance after correction for background variance  In principle, proton activation of VGLUT1Supplementary Fig. entclass1pt{minimaWe obtained the pH dependence of p or i from the pH dependence of the macroscopic current amplitude for each of the two assumptions and fitted the pH dependence of the variance with either Eq. 2–I plots did not span a full parabola, so we applied F-test model selection on all data sets obtained under each condition  to assess whether they could best be described by a parabola or a linear function. For both conditions, a parabolic function provided a significantly better fit than a linear function. Consequently, we calculated single channel amplitudes from parabolic fits:Unitary current amplitudes were determined by analyzing current noise over a period of 15 ms 100 ms after the voltage step to −160 mV  and an additional chloride channel (VGLUTCl)  and on luminal [Cl-] with the same concentration dependence  molecules:NA, βpH :−1mV−1 is the maximum VGLUT glutamate or aspartate transport rate and − fluxes through VGLUTs .33), with the inner  and cytoplasmic [glutamate] and [aspartate] to 10 mM57.Starting conditions for the mathematical modeling reflect the ion concentrations immediately after endocytosis of synaptic vesicles. The vesicular lumen contained solutions resembling the external solutions, with high [ClConfocal imaging of living HEK293T cells bathed in standard external solution was conducted using an inverted confocal laser scanning microscope  with a 63×/1.4 oil immersion objective. GFP was excited using a 488 nm laser and fluorescence emission was detected between 490 and 580 nm.58 . For patch clamp electrophysiology experiments, sample sizes correspond to the number of patched cells and are given in the figure or legend. For statistical analysis of two groups, we used two-tailed t-test for normally distributed data and the Mann–Whitney U-test for non-normally distributed data.Data are given either as the mean ± 95% confidence interval (CI) or as boxplots, including all single data and representing the mean value, median, upper and lower quartiles, and 95% CI. Measurements were taken from distinct samples. Mean and CIs of fit parameters and fitted curves are either from individual fits (single-channel currents or time-constants) or determined by bootstrap analysisFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Scoliosis curve angles were measured using the modified Ferguson method on DEXA scans (n = 1238) at age 20 years. For curve angle inter-rater reliability, two examiners measured angles (6–40°) on 41 scans. Likely, AIS was determined with quantitative and qualitative criteria .The inter-rater reliability for scoliosis curve angle measurement was good–excellent , and MDC95 was 6.2°. The prevalence of likely AIS was 2.1% (26/1238). Diagnosis of AIS was reported despite little or no scoliosis curve (< 3.8°) for 20 participants (1.6%), and diagnosis of AIS was not reported despite scoliosis curve ≥ 10° for 11 participants (0.9%). Results support the use of modified Ferguson method to measure scoliosis curve angles on DEXA. There is potential utility for using a combination of quantitative measurement and qualitative criteria to evaluate DEXA images, to identify likely AIS for reporting prevalence. Without formal school screening, the analysis of DEXA in this population sample suggested that relying on current health professional diagnosis alone could result in 2.5% of this cohort being at risk of false positive diagnosis or delay in necessary management due to non-diagnosis of AIS.Dual-energy X-ray absorptiometry (DEXA) scan is an emerging screening method for identifying likely adolescent idiopathic scoliosis (AIS). Using DEXA in an unbiased population sample (the Raine Study), we aimed to report the inter-rater reliability and minimal detectable change (MDCThe online version contains supplementary material available at 10.1007/s00223-023-01075-2. Adolescent idiopathic scoliosis (AIS) is a three-dimensional deformity of the spine that is diagnosed between the ages of 10 to 18 years. Diagnosis of AIS requires exclusion of other causes of spinal deformity and a ≥ 10° Cobb angle measurement of the scoliosis curve on a standing radiograph. AIS is most commonly reported to be present in 2–3% of the adolescent population worldwide [Formal school screening programs for scoliosis are usually performed for adolescents aged 11–14 years –7. OtherAn unbiased population sample is presented by the Raine Study, a prospective longitudinal cohort study with data collection on a broad range of health measures . The RaiDEXA is an emerging option for spinal screening to identify likely the presence of AIS and estimation of the population prevalence from the anteroposterior view of the spine in supine lying. To identify and measure scoliosis with DEXA scans, a modified Ferguson method was developed by Taylor et al.  in the A95) for scoliosis curve measurement on DEXA scans, (ii) to identify likely AIS and report its prevalence, using a combination of quantitative (modified Ferguson angle of ≥ 10°) and qualitative DEXA examination (expert review of images), and (iii) explore the concordance between health professional diagnosis of AIS with likely AIS identified via screening of the DEXA scans.In a sample from the Raine Study, the aims of this study were: (i) to report the inter-rater reliability and minimal detectable change (MDCwww.rainestudy.org.au). This longitudinal cohort recruited 2868 mothers (generation one) and their children (generation two) born between 1989 and 1991, with prospective collection of a wide array of biological, psychological, and social variables. The Raine Study has been demonstrated to be an unbiased sample, representing the general population in Western Australia [This study used data from the Raine Study . The Norland XR-36 densitometer  provided images of 96dpi with an image size of 280 × 730pixels, to measure lean and total fat mass. The research staff guided the participant’s upper and lower body to be in line with the pelvis while lying supine on the scanning table. Owing to skeletal maturity being likely at age 20, any scoliotic curves identified were expected to be at their maximum deformity  [Participants who attended for a DEXA scan at age 20 years were included , were independently marked and measured by a second examiner (PN), who was blind to the previous measurements.n = 142). The criteria that the expert applied to qualitatively evaluate scans are provided in Table An apparent curve on a DEXA scan may represent poor participant positioning for the scan, a shadow effect from internal organs, a spinal pathology other than AIS, or spinal curves consistent with AIS. Due to these potential confounders, a clinical research expert with 25 years of experience and publications in relation to AIS image analysis and clinical deformity measurement (author-MI) –17 condun = 2) were excluded from the dataset for likely AIS owing to juvenile-onset rather than adolescent-onset of their condition.At ages 1, 5, 8, 10, 14, 17, and 20 years, participants/parents of the Raine Study reported on their health conditions that had been diagnosed by a health professional, based on the question: “Does your child have now, or has your child had in the past, any of the following health professional diagnosed medical conditions or health problems?”. These reports were subsequently classified by Raine Study research staff using the ICD-9 . Those wlikely AIS,” (ii) “without scoliosis,” and (iii) “uncertain to have AIS,” both the quantitative modified Ferguson scoliosis curve measurements and qualitative expert evaluation of the DEXA scans were used  “sed Fig. . Of notesed Fig. , but not95 = 1.96 × SEM × √2 . The distribution of the difference scores was assessed using the Shapiro–Wilk test. The level of significance was set at p < 0.05.Descriptive statistics were used to report prevalence and curve characteristics. To assess the inter-rater reliability for modified Ferguson measures from DEXA scans, statistical analysis was performed using RStudio (2020) software . Bland–Altman plots were used to visualize the data, and intra-class correlation (ICC) with a two-way random effects model with absolute agreement were calculated. The ICC values were interpreted as poor (< 0.40), fair (0.40–0.59), good (0.60–0.74), and excellent (0.75–1.00)  inter-rap < 0.001). The difference between raters approximated a normal distribution (Shapiro–Wilk p = 0.28), the SEM: 2.2°; bias: 0.8°; and MDC95: 6.2°.Inter-rater reliability of the measurement of 41 DEXA scans of participants by two raters using the modified Ferguson method was good to excellent  modified Ferguson angle was 14.0 (3.5)° and ranged from 10 to 24°. Out of 142 scans that were evaluated by the expert, 116 scans were either without scoliosis or uncertain to have AIS.Twenty-six participants  were identified as without scoliosis is presented in Fig. n = 1165). Those classified as uncertain to have AIS (n = 73) are not included in this distribution. Out of 1165 participants, 50.8% of females and 46.5% of males were assessed as having a modified Ferguson angle = 0°, and 80.8% of the females and 79.5% of the males had a modified Ferguson angle of ≤ 6°.The cumulative distribution frequency of the modified Ferguson angles of participants with likely AIS and 95 of 6.2° for a 10° scoliosis curve, diagnosis of AIS was reported despite little or no scoliosis curve  for 20 participants (1.6%). Eleven (0.9%) were identified as likely AIS on DEXA scans but did not report a diagnosis of scoliosis.Reported diagnosis of idiopathic scoliosis/kyphoscoliosis was concordant with measured angle on DEXA ≥ 10° and expert evaluation for 15 participants 1.2%). There was notable discord between reported diagnosis and DEXA measured angle with expert evaluation as shown in Fig. %. There Two participants had a modified Ferguson angle of ≥ 10° and expert reviewed to have scoliosis inconsistent with AIS . Thirty-eight participants had a modified Ferguson angle of ≥ 10° on DEXA scan, but did not report a diagnosis of idiopathic scoliosis/kyphoscoliosis, and were evaluated by the expert DEXA review to be inconsistent with AIS . Thirty-two participants reported a diagnosis of idiopathic scoliosis/kyphoscoliosis but their modified Ferguson angle on DEXA scan was < 10° and were considered by the expert reviewer to have scoliosis inconsistent with AIS . There was one female (curve angle 9°) who reported a diagnosis of idiopathic scoliosis/kyphoscoliosis and was considered by the expert reviewer to have scoliosis consistent with AIS, but had a modified Ferguson angle < 10°.likely AIS in this Australian sample at age 20 was 2.1%. The discord between measured likely AIS from DEXA scans and reported health professional diagnosis of AIS (ICD-9 737.3) demonstrates that that there are a proportion of adolescents who have a scoliosis curve but have not been diagnosed and suggests that some adolescents may have been misdiagnosed. Although DEXA scans are not a diagnostic tool for spinal scoliosis, when available, they enable quantitative and qualitative screening of scoliosis curves prior to formal diagnostic examination.Our study built on the only prior study using DEXA to identify likely AIS in a community population  by: (i) 95 of 6.2° suggests the smallest angle which could be used to detect likely AIS on DEXA. This was 1.6° larger than that reported in the ALSPAC study (MDC95 of 4.6°) [likely AIS on DEXA scans, we recommend a combination of quantitative curve angle cutoff of ≥ 10° in order to exceed the SEM (2.2°) and the MDC95 (6.2°), as well as using the qualitative criteria for image examination provided in the current study. The Cobb method of scoliosis measurement from digital radiographs has well-established excellent inter-rater reliability [likely AIS can be identified from DEXA. Screening and identifying AIS in its early stages  is important as the risk of scoliosis curve progression is the greatest during rapid skeletal growth [The good–excellent inter-rater reliability supports the use of modified Ferguson method to measure scoliosis curve angles on DEXA. The MDCof 4.6°)  with simiability , 21), wiiability , approxil growth . More relikely AIS prevalence of 2.1% with a DEXA measurement cutoff of 10° was at the lower end of the estimated global prevalence of 2–3% [likely AIS. The prevalence of DEXA-identified AIS was determined with 26 participants (2.1%), after excluding 73 scans that were uncertain to have AIS. In the excluded group that we were uncertain to have AIS, 35/73 participants reported a diagnosis of idiopathic scoliosis/kyphoscoliosis. If those 35 participants were included, the estimated prevalence would increase to 4.9%. This expanded prevalence rate is much greater in comparison with previously reported prevalence rates (2–3%) [The DEXA scans were able to provide an estimate of AIS in an Australian sample, at age 20 in 2009–2012. Our  of 2–3% . The ALS of 2–3% . The low of 2–3% , 24–26,  of 2–3% . The higuncertain to have AIS and were classified in four sub-groups. Two of the sub-groups had disagreement between the measured curve angle and expert evaluation, which could represent apparent scoliosis curve angles due to organ shadowing (n = 38) and non-idiopathic scoliosis (n = 2). For the third sub-group, the measured curve angle and expert evaluation both determined that the participants did not have scoliosis, though a health professional diagnosis of idiopathic scoliosis/kyphoscoliosis had been reported (n = 32), which could represent participants who were falsely diagnosed with idiopathic scoliosis. The fourth sub-group (n = 1) was determined by the expert and a reported diagnosis of idiopathic scoliosis/kyphoscoliosis, but had a measured modified Ferguson angle of 9°, though it is possible that a larger angle may have been present if measured by standing radiograph and Cobb angle. We lacked any further clinical information to confirm diagnosis of idiopathic scoliosis. It is possible that those we were uncertain to have AIS may contain some people with AIS, but in the absence of any further clinical information, the specificity of screening for likely AIS was prioritized over sensitivity for this study. Future research could examine the sensitivity and specificity of the quantitative curve angle measurement on DEXA scans and expert qualitative evaluation against confirmed clinical diagnoses based on standing radiographs (the current gold standard for diagnosis of AIS).Out of 1238 participants, 73 were likely AIS identified on DEXA. For the Raine cohort, there was no information about the health professional who diagnosed the condition or diagnostic method used. Of the 50 people who first reported diagnosis of AIS from age 10 or older, 20 had little or no scoliosis curve visible on DEXA. False positive diagnosis raises the possibility of low-value use of health system resources, including unnecessary consultations, spinal imaging and interventions, and risk of psychosocial stress [A unique contribution of the Raine Study was the ability to explore the concordance between two methods of identifying AIS within the cohort: reported health professional diagnosis of idiopathic scoliosis/kyphoscoliosis and l stress . Of the l stress , and latl stress . In Austl stress . Furtherlikely AIS was modest (n = 26). A larger sample size of participants with likely AIS would allow greater confidence in the distribution of modified Ferguson angles and curve characteristics representative of the wider population with AIS. Despite these limitations, the Raine Study is a prospective longitudinal cohort that provided a uniquely unbiased sample to estimate population prevalence and explore curve characteristics of scoliosis. Future exploration of data associated with the groups identified in this study could provide insights toward factors that contribute to AIS as well as the clinical impacts and costs associated with AIS.Limitations in this study included the low-resolution images from 2009 to 2012, compared to images from contemporary scanners which could enable more accurate curve angle measurement. The sample size of those identified with likely AIS for reporting prevalence. Without formal school screening, the analysis of DEXA in this population sample suggested that relying on current health professional diagnosis alone could result in 2.5% of this cohort being at risk of false positive diagnosis or delay in necessary management due to non-diagnosis of AIS.The good–excellent inter-rater reliability supports the use of modified Ferguson method to measure scoliosis curve angles on DEXA. This study showed the potential utility of using a combination of quantitative measurement and qualitative criteria to evaluate DEXA images, to identify Supplementary file1 (PDF 746 KB)Below is the link to the electronic supplementary material.