Splitting sensory information into parallel pathways is a common strategy in sensory systems. Yet, how circuits in these parallel pathways are composed to maintain or even enhance the encoding of specific stimulus features is poorly understood. Here, we have investigated the parallel pathways formed by mitral and tufted cells of the olfactory system in mice and characterized the emergence of feature selectivity in these cell types via distinct lateral inhibitory circuits. We find differences in activity-dependent lateral inhibition between mitral and tufted cells that likely reflect newly described differences in the activation of deep and superficial granule cells. Simulations show that these circuit-level differences allow mitral and tufted cells to best discriminate odors in separate concentration ranges, indicating that segregating information about different ranges of stimulus intensity may be an important function of these parallel sensory pathways.DOI:http://dx.doi.org/10.7554/eLife.16039.001 The brain often processes different features of sensory information in separate pathways. For example, when seeing an object, information about colour and movement are processed by separate types of neurons in the eye. These neurons in turn relay information to different sets of brain areas, all of which are active at the same time. Such parallel processing was originally not thought to apply to information about smell. This was because in mammals, the two types of neurons in the brain area that processes smell seemed to play the same role. However, more recent work suggests that there are in fact differences in the responses of these two neuron types  to odors, suggesting that the brain might use parallel processing for information about smells too.Information travels along neurons in the form of electrical signals, and this activity is often seen in the form of a series of “spikes”. In a process called lateral inhibition, the activity of one neuron can feed back and inhibit the activity of its neighbors. This is important for enhancing contrast; in terms of the sense of smell, lateral inhibition is thought to help distinguish between similar odors.A technique called optogenetics allows the activity of particular neurons in an animal’s brain to be controlled by shining light onto them. Geramita et al. have now used this technique in mice to investigate whether there are differences in how lateral inhibition works in mitral cells and tufted cells. This revealed that lateral inhibition affects mitral cells only when they are spiking at intermediate firing rates, whereas tufted cells are only affected by lateral inhibition when spiking at low firing rates. Using computer simulations, Geramita et al. show that these different responses mean that mitral cells are best at distinguishing similar smells when they are present at high concentrations, while tufted cells are best at distinguishing similar smells that are present at low concentrations. These differences also mean that, by working together, mitral and tufted cells can distinguish between smells much better than either type of neuron on its own.These results demonstrate that, as with the other senses, the brain processes information about smell using parallel pathways. Future work is now needed to see what effect switching off the activity of either mitral or tufted cells will have on an animal’s behavior.DOI:http://dx.doi.org/10.7554/eLife.16039.002 Brain sensory systems use parallel pathways to encode different components of sensory information. Motion and color are segregated in the visual system , sound lIn the mammalian olfactory bulb, firing of olfactory sensory neurons (OSNs) excites two classes of projection neurons – mitral cells and tufted cells (MCs and TCs). While long viewed as essentially equivalent neuron classes, emerging evidence shows that MCs and TCs exhibit distinct activity in vivo , suggestThroughout the brain, lateral inhibitory circuits enhance contrast and facilitate discrimination of similar stimuli by decorrelating neural responses . In the Here, we show that optogenetic activation of a single, gene-targeted glomerulus elicits larger and more asynchronous lateral inhibitory currents in nearby MCs than in TCs. Moreover, this same photostimulation paradigm inhibits spiking differently in MCs and TCs. While MCs are affected by lateral inhibition at intermediate firing rates (~50 Hz), TCs are affected when firing at low firing rates (<25Hz). This difference arises, in part, due to differential recruitment of morphologically distinct classes of GCs by MCs and TCs. Finally, we use simulations to explore how these circuit-level differences between MCs and TCs influence odor discrimination. Specifically, the combination of activity-dependent lateral inhibition at both low and intermediate rates enables TCs and MCs to collectively encode odors better than either population alone and supports novel computations that are unlikely to occur with a single neuron type.To analyze lateral inhibition, we optically activated M72-expressing OSN axons in acute slices from M72-ChR2-YFP mice  while reWe also explored two potential causes of cell-to-cell variability in lateral inhibition. The strength of lateral inhibition onto MCs and TCs did not depend on whether the apical dendrite was truncated during the slicing procedure, indicating that lateral inhibition originating in the glomerular layer  did not To confirm that these results are not specific to the M72 glomerulus, we performed an analogous experiment in OMP-ChR2-YFP mice  by photoFinally, using photostimulation of a single glomerulus in OMP-ChR2-YFP mice, we tested whether GCs contribute similar proportions of lateral inhibition onto MCs and TCs using a previously described strategy  to diffeWe next explored how lateral inhibition influences MC and TC spiking. To do this, we stimulated MCs and TCs by step current injection and measured firing rates to construct input-output curves in cells near the M72 glomerulus. On interleaved trials we activated M72 OSN axons via photostimulation ,3. We usThe average fractional reduction in firing rate was much larger in TCs than in MCs , though This difference in activity-dependent lateral inhibition (ADLI) may arise from differences in the lateral inhibitory circuits engaged by MCs and TCs. Our finding that inhibition is largely unaffected by apical dendrite truncation suggests that differences in ADLI between MCs and TCs most likely involves inhibitory circuitry within the external plexiform layer (EPL). Consistent with MCs and TCs engaging distinct lateral inhibitory circuits within the EPL, classical morphological studies suggest that GCs are subdivided into superficial GCs (sGCs), which innervate the superficial EPL, and deep GCs (dGCs), which innervate the deep EPL . This puSeveral previous findings are consistent with this hypothesis. GC soma position correlates with GC subtype  and odorTherefore, to more directly test our above hypothesis, we recorded the excitatory synaptic input and spiking response of GCs to activation of single nearby glomeruli, with post-hoc recovery of Neurobiotin-filled cell morphologies. For this experiment, we switched from selective optogenetic stimulation of M72 glomeruli to extracellular stimulation of untagged glomeruli in order to test a large number of GC-glomerulus pairs. While this approach introduces a degree of glomerulus-to-glomerulus variability to our data, we capitalized on the well-established all-or-none nature of glomerular activation at low stimulation intensities  to enablConsistent with previous morphological accounts , GCs exhIn agreement with our hypothesis, a strikingly higher percentage of sGCs than dGCs fired in response to activation of a single glomerulus  due, at As an additional test of our hypothesis that differences in the excitability of GCs provide one potential mechanism underlying the functional difference in ADLI between MCs and TCs, we measured the effects of lateral inhibition on MC spiking before and after increasing the excitability of GCs with the mGluR agonist (RS)-3,5-dihydroxyphenylglycine  . At thisTogether these data suggest that distinct odor-evoked activity observed in MCs and TCs in vivo arises, in part, due to differences in how ADLI affects each cell type . To begiWe simulated an olfactory discrimination task in which a presented odor must be identified from a panel of similar odors. Because the goal of the simulations was to understand how the differences in MC and TC circuit properties described above influence population coding, we used simple firing rate models in which we could directly and independently modify lateral inhibition properties without changing other model features. We therefore made relatively few assumptions in performing our simulations, mostly relating to how odor concentration is encoded , one in which ADLI affected intermediate rates , and a control population that lacked any inhibition. ADLI was modeled by explicitly adjusting the sensitivity of MC and TC firing rates to inhibition without changing other parameters of the model . When thNext we tested how well different forms of activity-independent inhibition compare to ADLI in their ability to improve discrimination accuracy. Specifically, we compared discrimination accuracy (in panels consisting of 32 odors) between 3 populations of neurons; one with subtractive inhibition , one witPrior work has shown that, in addition to ADLI differences, TCs are more intrinsically excitable  and receFinally, we asked more generally how sensory systems, including the olfactory system, might benefit from splitting information into multiple channels with distinct ADLI. First, we asked whether models containing a combination of MCs and TCs discriminate odors better than models that have only MCs or TCs. We used a variant of the models presented above: here, each glomerulus provided input to 2 neurons instead of 1. We compared three different output neuron configurations: 2 MCs per glomerulus, 2 TCs per glomerulus, and 1 MC and 1 TC per glomerulus . HoweverParallel pathways are a common feature of many sensory systems. Yet how local circuit activity creates stimulus selectivity in parallel pathways remains poorly understood. Here, we have identified a novel circuit mechanism for generating differential responses across two parallel pathways (formed by MCs and TCs) in the olfactory system and examined the emergence of feature selectivity. We find that differences in ADLI selectively reduce intermediate firing rates in MCs and low firing rates in TCs. We provide evidence that these effects could be caused, in part, by differences in the excitability of subclasses of GCs that preferentially inhibit TCs vs. MCs. Moreover, using simulations, we show that differences in the effective activity range of lateral inhibition, along with other intrinsic and circuit-level differences between MCs and TCs, work cooperatively to enable MCs and TCs to best discriminate between similar odors in separate concentration ranges. Finally, we show that the combination of MCs and TCs facilitates odor discrimination across a wide range of odor concentrations.The activity-dependence of lateral inhibition depends on three cell populations – the 'presynaptic' M/TCs associated with the M72 glomerulus , the inhibitory interneurons and the 'postsynaptic' M/TCs. Our prior work has shown that increasing the firing rate of presynaptic MCs (the M72 MCs in this case) shifts the range of MC firing rates influenced by lateral inhibition . Given tOur analysis supports the hypothesis that TCs and MCs are preferentially connected to sGCs and dGCs, respectively. Additionally, we provide indirect evidence that differences in the recruitability of sGCs and dGCs may be one potential mechanism underlying the differences in ADLI between MCs and TCs. Our data suggests that sGCs spike with a higher probability than dGCs following the activation of a single glomerulus. Consequently, postsynaptic TCs can effectively recruit lateral inhibition when firing at low rates. dGCs are less excitable and therefore require more input to be activated. Therefore M72 photostimulation alone causes relatively weak activation of dGCs. However, when the postsynaptic MC fires at intermediate rates, additional dGCs will become activated and mediate lateral inhibition. In support of this mechanism, we show that increasing the excitability of GCs by activating mGluRs  shifts tWhile preferential connectivity of TCs with sGCs and MCs with dGCs can explain the observed differences in the activity-dependence of lateral inhibition, other circuit mechanisms may also contribute. In particular, EPL interneurons (EPL-INs) can mediate inhibition onto M/TCs , and it Differential connectivity of MCs and TCs with distinct GC subclasses has long been predicted based on the putative morphological subdivisions of GC apical dendritic morphologies  and sepaOur data describe local, circuit-level mechanisms that can account for several differences between MC and TC odor-evoked responses observed in vivo. Weaker lateral inhibitory currents may contribute to the finding that TCs are less frequently inhibited by odors . AdditioThese circuit-level differences between MCs and TCs likely affect olfactory discrimination . ADLI, bPerforming these experiments in acute slices provides the best opportunity to explore the causes and consequences of differences in lateral inhibition between MCs and TCs. Given the novel features and mechanisms of ADLI, using a reduced and carefully controlled system in which a single glomerulus can be reliably activated is an important first step. Moreover, our in vitro approach allowed us to apply pharmacological manipulations that were vital in identifying differences in GC excitability  rather tWe note, however, that our in vitro approach also has certain limitations. In particular, the slicing procedure may introduce artifacts that could confound our conclusions. Importantly, however, our findings that MCs receive stronger lateral inhibitory currents and are affected at different ranges of firing rates than TCs are unlikely to reflect slicing artifacts. Due to slicing, some MCs and TCs that project to the M72 glomerulus will be truncated, and cells that reside farther from the M72 glomerulus have a higher probability of being truncated. However, our findings do not depend on the cell’s distance from the M72 glomerulus . AdditioOur in vitro approach additionally cannot address multiple important factors that are only present in the intact animal. For instance, respiration and centrifugal feedback likely modulate ADLI in vivo. Addressing the extent to which ADLI affects odor-evoked responses in MCs and TCs in vivo is thus an important future direction.Finally, what are the benefits of parallel processing? In other sensory systems, different pathways may arise from functional differences at the initial stages of stimulus detection, which are then maintained through selective feedforward connectivity. In the olfactory system there is no evidence that MCs and TCs are targeted by distinct subsets of OSNs. Rather, we show that differences in bulbar circuitry are sufficient to generate important differences in response properties. Here we show that MCs and TCs perform odor discriminations best at separate concentration ranges and that a combination of MCs and TCs discriminates similar odors better than either population alone. These results suggests that parallel processing may offer similar benefits in other sensory systems in which stimulus intensities can vary over many orders of magnitude. For instance, rods and cones in the retina function best at different ranges of light intensity. Other similarities between the olfactory and visual systems suggest that the mechanisms behind parallel processing may be shared across sensory systems. In the retina, feature selectivity in each ganglion cell type emerges due to its connectivity to specific bipolar and amacrine cell types . SimilarAll experiments were completed in compliance with the guidelines established by the Institutional Animal Care and Use Committee of Carnegie Mellon University (IACUC # AS15-010) and University of Pittsburgh (IACUC # 15116582).3, 1.25 NaH2PO4, 7 MgCl2 and 0.5 CaCl2. Sagittal slices (280 μm thick) of the MOB were prepared using a vibratome . Slices recovered for 15–30 min in 37°C oxygenated Ringer solution that was identical to the dissection solution except for lower Mg2+ concentrations (1 mM MgCl2) and higher Ca2+ concentrations (2 mM CaCl2). Slices were then stored in room temperature oxygenated Ringer solution until recording. For MC and TC recordings in OMP-ChR2-YFP mice, horizontal slices (280 μm thick) were prepared from postnatal day 17–21 mice. For GC recordings, equivalent methods were used to prepare horizontal slices (310 μm) of the MOB from postnatal day 18–28 C57BL/6, Thy1-YFP-G  that reside completely in the EPL. Cell bodies resided in the superficial half of the EPL. All TCs included in our final dataset had at least 1 lateral dendrite and did not display the rhythmic bursting characteristic of external tufted cells . MCs wer2+ unless otherwise noted. Current clamp recordings were made from individual cells using electrodes filled with (in mM) 120 potassium gluconate, 2 KCl, 10 Hepes, 10 sodium phosphocreatine, 4 Mg-ATP, 0.3 Na3GTP, 0.2 EGTA, 0–0.025 Alexa Fluor 594  and 0.2% Neurobiotin . Voltage clamp recordings were made using electrodes filled with (in mM): 140 Cs-gluconate, 10 HEPES, 2 KCl, 10 sodium phosphocreatine, 3 Mg-ATP, and 0.3 Na3GTP.Cells were visualized using infrared differential interference contrast video microscopy. For MC and TC recordings, slices were continuously superfused with 37°C oxygenated Ringer solution that contained 0.2 mM MgM72 photostimulation was provided by a 250 μm multimode optical fiber (Thorlabs) coupled to a high-intensity light emitting diode  and driver (DC2100: Thorlabs) controlled by TTL pulses. For photostimulation in OMP-ChR2-YFP, slices were illuminated with 100 ms light pulses by a xenon arc lamp directed through an YFP filter set and 60x water-immersion objective centered on a single glomerulus. Photostimulation was confined to single glomeruli by closing the field stop as previously described . All dat2+ and 2 mM Ca2+. Current clamp recordings were made as described above. Voltage clamp recordings were made using electrodes filled with either the Cs-based solution supplemented with 10 mM QX−314 and 0.2% Neurobiotin or the K-based solution. To examine GC activity following activation of a single glomerulus, extracellular stimulation of olfactory sensory neuron fibers within a single glomerulus was performed as previously described  containing 1 mM Mgescribed .Lateral inhibitory currents were measured in 5 trials at a holding potential of +10 mV. Analysis of IPSCs was performed using custom Matlab (Mathworks) analysis software. The presence or absence of IPSCs was calculated by taking the average trace of 5 trials and finding the mean and standard deviation of the trace during the second prior to photostimulation. Then the baseline current (mean of the second prior to photostimulation) was subtracted from each trace. IPSCs evoked through lateral inhibition were present if positive deflections of the current trace exceeded 3*s.d. for longer than 10 ms in the 500 ms time window following M72 photostimulation.Lateral inhibitory currents were split into early and late phases and the peak current amplitude and charge transfer were calculated in each. Charge transfer was calculated as the integral of the current trace in either the early phase (0–250 ms) or late phase (250–1500 ms) following photostimulation.The effect of lateral inhibition on spiking was measured by performing FI curves in MCs and TCs via somatic current injection of increasing amplitudes. At each current step (500 ms), we measured the number of action potentials evoked with and without M72 photostimulation (10 ms pulses at 15 Hz). Two full FI curves (a full FI curve is defined as having current steps with and without photostimulation) were performed on each cell and the average change in firing rate at each current step was calculated and used for the presented analysis. Lateral inhibition was defined to have a significant effect on a cell if there was a greater than 10% decrease in firing rate in at least 2 consecutive current steps.Intrinsic biophysical properties of GCs, including passive membrane, action potential, and spike train properties were calculated as previously described .presentation), we first made Odor 1. To do this, we randomly sampled 1/3 of pixels to represent non-activatable (NA) pixels that are not responsive to odors, regardless of concentration. Next a concentration threshold (Ti) was sampled from a uniform distribution between 0 and 1000 for each activatable pixel . Activatable pixels were then divided into ON and OFF pixels. ON pixels were defined as having Ti < Ipresentation, while OFF pixels are ones where Ti > Ipresentation. Each ON pixel then got a mean activation intensity sampled from a normal distribution ).Models of odors and olfactory bulb circuitry were developed in Matlab (Mathworks) (see Source code). The scheme for generating odor panels and individual odor trials is depicted in The next step in the construction of the odor panel was to make an arbitrary number of other odors that are 90% similar to Odor 1. To make these odors, we enforced a set of rules.Each pixel in Odor 1 had a 10% probability of changing.P(NA – NA) = 1/3P(NA – ON) = 2/3base=NIf a NA pixel became an ON pixel, it received an activation intensity. IFor each NA pixel that was chosen to change:P(ON – NA) = 1/3P(ON – ON) = 2/3base=Nif an ON pixel remained ON, it received a new activation intensity. IFor each ON pixel that was chosen to change:P(OFF – OFF) = 1For each OFF pixel that was chosen to change:The last step in odor panel construction was to add noise to create trial-to-trial variability. To do this, we enforced a set of rules for sampling the activation strength of each pixel on each trial.trial = UThe strength of activation of NA and OFF pixels: Itrial = NThe strength of activation of ON pixels: IThese odors became the glomerular input for olfactory bulbs composed of either MC or TCs. Each MC/TC was represented by a continuous firing rate variable, v. Each neuron received a leak current, an inhibitory current and an excitatory current input from 1 pixel . The excOne of N odors from the panel was presented to the MC or TC bulb on each of 2000 trials. The MC or TC outputs from half of the trials are used to train a naïve Bayes classifier which was then used to predict which odor is being presented on the remaining half of trials. The percent correct is used as the discrimination accuracy for that odor panel. For simulations, we constructed 100 odor panels at each concentration. Concentrations in The simulations used to generate the data in  In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Naoshige Uchida as the Reviewing Editor and Gary Westbrook as the Senior Editor. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Thank you for submitting your article "Distinct lateral inhibitory circuits drive parallel processing of sensory information in the mammalian olfactory bulb" for consideration by Summary:The authors report that tufted cells are inhibited by lateral inhibition from neighboring glomeruli at lower firing rate ranges than for mitral cells. That is, activity-dependent lateral inhibition (ADLI) occurs at different firing rate ranges in tufted versus mitral cells. The authors also present evidence suggesting that the difference in ADLI is caused by differences in excitation of two sub-classes of granule cells. Finally, the authors used computational modeling to show that differential ADLIs between mitral and tufted cells help improve discrimination of odors at wider concertation ranges.eLife's policy not to suggest experiments that will take more than 2 months. Reviewers agreed that the experiments in reduced preparations (slice) have certain advantages. However, the reviewers had other concerns that were considered substantive and therefore the authors must address these concerns before publication.All the reviewers thought the main finding were very interesting. During discussion between the reviewers, however, there were different opinions whether it was necessary to determine whether differential ADLIs occurs in vivo. Although such an experiment would greatly strengthen the significance of this work, it is Essential revisions:1) It is not convincing that the difference in ADLIs between mitral and tufted cells is not a result of tissue slicing. Furthermore, it is unclear whether the different properties of superficial versus deep granule cells that might have caused the differences in ADLIs are a side effect of slicing. The authors have to provide more convincing, quantitative arguments to exclude artifacts associated with slicing.2) The authors examined the significance of differential ADLI between mitral and tufted cells using modeling. However, mitral and tufted cells are different not only in their ADLI properties but also their intrinsic and synaptic input properties. In the modeling, all of these are changed at the same time, and therefore, it is unclear whether improved odor discriminability at different odor concentrations is due to ADLI alone, differences in intrinsic/synaptic properties alone, or a combination of all factors. Please clarify this issue with additional analysis.3) In 4) in vivo experiments would greatly increase the significance of the present study as lateral inhibition may be sensitive to subtle details of the network properties, spontaneous activity and breathing etc. that can be seen only in an intact network. If the authors decide not to perform in vivo experiments, potential caveats of their in vitro experiments must be explicitly discussed.Reviewer #1:This study explores differences in the olfactory bulb's output mitral cells (MCs) and tufted cells (TCs) in a previously-described phenomenon known as activity dependent lateral inhibition (ADLI). Evidence is provided based on slice recordings that MCs and TCs differ in the kinetics of lateral inhibition, the spike frequency range over which ADLI is observed, as well was the relative effect of ADLI on spiking. Also, recordings from granule cells (GCs) suggest that differences in ADLI in MCs versus TCs could reflect differences in excitation of two sub-classes of GCs. Finally, computational modeling is used to make the case that differences in ADLI between MCs and TCs can confer differences in the concentration ranges over which the two neuron types best discriminate odors and may also expand the concentration ranges over which odors can be effectively discriminated by the bulb.Overall, this is an interesting study that addresses a broadly relevant question: How can two parallel sensory processing paths  enhance sensory discrimination? Much of the study also employs a powerful experimental paradigm involving optogenetic stimulation of a single, molecularly-defined glomerulus (M72) as a means to drive lateral inhibition. This strategy should eliminate ambiguities about whether only one glomerulus is being stimulated and, also, should reduce variabilities across experiments. Some of the results are also basically convincing, for example that MCs and TCs have different kinetics for lateral inhibition and also differ in the frequency range over which ADLI occurs. However, I have a number of concerns with both the experimental and modeling sections of the paper.1) The analysis methods used raise questions about results suggesting that TCs display a larger percent decrease in spike rate due to ADLI than MCs . The leg2) That differences in the properties of superficial versus deep GCs (sGCs and dGCs) contribute to differences in ADLI between MCs and TCs is not completely convincing. The argument is based on the parallel observations that TCs display ADLI at lower spike frequencies than MCs and also that sGCs  are more responsive to glomerular stimulation. However, the authors need to exclude better the possibility that the greater spike probability and evoked currents in sGCs is not a slicing artifact. sGCs, which are closer to glomeruli, may naturally be expected to have more of their input circuitry intact in slices. The fact that sGCs appear to have greater intrinsic excitability helps their argument, but it is not sufficient. Comparing ADLI and the responsiveness of GCs is also complicated by the fact that the experiments assaying these two features appear to have been conducted in differing magnesium concentrations (0.2 mM versus 1 mM).The authors also use the fact that the mGluR agonist DHPG reduces the frequency range for ADLI in MCs to argue that differences in ADLI between MCs and TCs are due to GC properties. This is based on prior observations that DHPG can enhance GC excitability. DHPG appears not alter MC spiking due to direct current injection , yet oth3) The computational results suggesting that differences in ADLI between MCs and TCs enable these cells to perform odor discrimination at different concentrations are not completely convincing. The most important results are shown in Reviewer #2:eLife should the authors address several concerns listed below.Geramita, Burton & Urban report through a series of elegant experiments in acute olfactory bulb preparations that the two types of bulb principal neurons, tufted and mitral cells, receive different levels of inhibition from granule cells . The authors show through a combination of patch-clamp recordings, current injections and optogenetic stimulation of genetically labeled glomeruli that activity dependent lateral inhibition (ADLI) occurs at low firing rate regimes in tufted cells and intermediate firing rates in mitral cells. They further propose as underlying substrate at play for the different ADLI regimes two distinct populations of superficial and deep granule cells . Anatomical reconstructions and clustering suggest that sGCs and dGCs contact differentially the lateral dendrites of TC and respectively MCs. Further functional analysis reveals differences in intrinsic excitability and threshold for action potential firing between sGCs and dGCs consistent with their proposed roles. In my opinion, the manuscript adds important novel understanding by documenting that functional differences between mitral and tufted cells emerge not only due to differences in intrinsic excitability, but also in their local connectivity with inhibitory interneurons. These findings bring timely mechanistic insight that parsimoniously explains recently published differences in TCs and MCs responses to odors, across concentrations, and to modulation of cortical feedback. Therefore, I consider the manuscript fit for publication in Importantly, I have doubts regarding the necessity of the computational model presented and some of its underlying assumptions. Given the temporal complexity of active sampling (sniffing) in vivo, relevant time window for odor identification , possible effects of the slice preparation on the functional connectivity of the bulb, and lack of top-down regulation  of mitral and tufted cell activity in the slice preparation, I suggest focusing the manuscript on the experimental results with fewer incursions into the simulations.1) The authors present in 2) What is the functional relevance of the concentration regime sampled? What does 20% to 80% of maximal concentration translate to in terms of absolute odor concentration? Are such concentrations ever encountered by the animal?3) Why is the classifier trained independently for each of the concentrations sampled? This seems an unrealistic regime compared to processes that may occur in the brain.4) Differences in functional properties of sGCs and dGCs can be in principle heavily modulated by top-down signals that are absent in the slice. The current version of the manuscript does not discuss this possibility.5) MC and TCs have been reported to project with differential biases to downstream target areas. How do such biases contribute to the ability of the decoder to incorporated odor information carried by both TC and MC?In Reviewer #3:The authors present a detailed in vitro analysis of differences in lateral inhibition experienced by MCs and TCs. They attribute these differences to different innervation of different populations of GCs and use a simplified model to illustrate that the differential inhibition can lead to improved discriminability overall (with TCs aiding to low-concentration and MCs to high-concentration discrimination).In a previous submission  there were numerous criticisms that the authors largely address well. One key concern that was reiterated by all reviewers was that the findings of differential inhibition were exclusively based on in vitro experiments (and simulations) with little direct link to how sensory information might be processed. Here I think the current manuscript is still lacking. While the authors argue – rightly so – that they perform an in depth mechanistic analysis (which is difficult in vivo) I have to say I tend to agree in that the relevance / role of the differential inhibition for odor processing is still unclear. If indeed – as stated in the response to prior reviewer 1 – the variability / signal-to-noise will mask the effect in vivo one might question how dominant it could be in a behaving context. I surely don't argue for repeating all experiments in an awake behaving animal but key experiments parts of  and 4 ateLife. Your revised article has been favorably evaluated by Gary Westbrook (Senior editor), a Reviewing editor, and three reviewers.Thank you for resubmitting your work entitled "Distinct lateral inhibitory circuits drive parallel processing of sensory information in the mammalian olfactory bulb" for further consideration at The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance as agreed upon by the reviewers in discussion following their original reviews that are appended below. Specifically, while all the referees agreed that the manuscript has been greatly improved, there are two remaining concerns. First, the reviewers thought that it remains unclear whether the authors can completely exclude the possibility that slicing biased the contribution of superficial versus deep granule cells in activity-dependent lateral inhibition (ADLI) (point # 1 of reviewer 1). Furthermore, the interpretation of the experiment using DHPG should be revised so that the possibility of the network effect  is appreciated. We think that both points can be addressed with revisions to the text as outlined by reviewer 1. For more details, please see the reviewers' original reviews below.Reviewer #1:The Reviewers have adequately addressed most of my concerns. Especially helpful are their new modeling results showing that differences in ADLI between MCs and TCs contribute to odor discrimination across a wider range of odor concentrations even in the presence of other important differences between MCs and TCs. Some concerns about slice artifacts and their interpretation of differences in excitation of sGCs and dGCs however remain, as do concerns about their DHPG experiments (both brought up in Major Point 2 of my prior review). These, which are explained below, however will just require changes in the text. Their overall story is quite interesting, and I would be satisfied if they simply backed off on some of their claims pertaining to GCs.1) That the greater evoked responses in sGCs versus dGCs is due to greater excitatory input and intrinsic excitability rather than slice artifacts is still not completely convincing. In response to this concern, raised previously, the authors provided three lines of evidence in the rebuttal letter and Results section, which I will address individually (authors' text is in parentheses).A) . The results do not support that sGCs have synaptic and intrinsic properties that make them more responsive.B)  These data are not especially helpful for excluding slice artifacts because the spontaneous events in GCs (sEPSCs) could reflect spontaneous release of glutamate from pieces of M/T lateral dendrites that remain in the slice but are not associated with a cell body. This differs from responses evoked by stimulation of a single glomerulus, which requires intact cell bodies so that action potentials can pass to the lateral dendrites. That the experiments were conducted in the absence of TTX is not very supportive of there being intact cell bodies, since no evidence is provided to suggest that a major portion of the sEPSCs are being driven by action potentials. They could be mEPSCs . In addition, it cannot be excluded that there are spontaneous action potentials in pieces of lateral dendrites that are dissociated from cell bodies. Full-sized action potentials can propagate down mitral cell lateral dendrites, suggesting the presence of sodium channels in these dendrites. To use the spontaneous events as an argument against slice artifacts, the authors would need to perform additional controls .Taking these points together, I still am not convinced that the differences in evoked responses in dGCs and sGCs do not mainly reflect a slice artifact. However, at this point, I would be satisfied if the authors make changes in the text and reduce their emphasis on differences in the synaptic and intrinsic properties of the two GC sub-types being causal to the different ADLI properties of MCs versus TCs.2) Some concern also remains about the DHPG experiments, which the authors use to argue that the requirement for higher spike frequencies in MCs to obtain ADLI reflects the excitatory properties of GCs. I previously raised the issue that the DHPG-induced shifts in the effective range of lateral inhibition could reflect drug-effects on glomerular layer neurons rather than GCs. In response, the authors point out that 2 MCs with cut apical dendrites (that do not receive inputs from glomerular layer cells) show similar DHPG-induced shifts in the effective frequency range for ADLI as those MCs with intact apical dendrites. However, these data do not exclude the following plausible network effect involving DHPG-induced excitation of external tufted cells in the glomerular layer : DHPG-induced excitation of eTCs causes greater feedforward excitation of a population of MCs at a glomerulus; this in turn leads to greater excitation of GCs and GC-mediated inhibition. Such an effect, involving GC inputs onto MC lateral dendrites, would not depend on a test MC having intact apical dendrites.Despite this caveat, their results showing that the 2 MCs with cut apical dendrites show similar DHPG-induced shifts in the effective range of lateral inhibition as MCs are helpful. They at least support the conclusion that changes in the degree of GC excitation (either direct or indirect) can control the frequency range over which the ADLI occurs, which is itself interesting.Reviewer #2:The authors addressed the concerns raised and, in my opinion, the manuscript is fit for publication at this point.Reviewer #3:The authors are discussing my key concern (whether the findings hold true in vivo) very well in the rebuttal and following their logic it is indeed very likely that most of the key findings will hold true. I find the well-structured and expanded (compared to the Discussion) overview given in the rebuttal very helpful and would suggest incorporating this version into the Discussion. Essential revisions:1) It is not convincing that the difference in ADLIs between mitral and tufted cells is not a result of tissue slicing. Furthermore, it is unclear whether the different properties of superficial versus deep granule cells that might have caused the differences in ADLIs are a side effect of slicing. The authors have to provide more convincing, quantitative arguments to exclude artifacts associated with slicing.We agree with the reviewers that the issue of tissue slicing is important. However, we believe that the differences between MCs and TCs and between sGCs and dGCs reported here are not slicing artifacts, but true features of the olfactory bulb circuit. Below, we provide rationale for why each of the three main experimental findings are not artifacts of the slicing procedure. We additionally state how our revised manuscript presents these rationale.Main finding 1: Lateral inhibitory currents are larger and more asynchronous onto MCs than TCs Due to slicing, some MCs and TCs that project to the M72 glomerulus may be truncated, and cells that reside farther from the M72 glomerulus will be expected to have a higher probability of being truncated. Therefore, we are likely to lose more M72 MCs than M72 TCs with the slicing procedure. Additionally, prior work  shows that lateral dendrites of MCs and TCs project radially in all directions. Therefore, the lateral dendrites of the remaining MCs and TCs still connecting to the M72 glomerulus are likely to be affected approximately equally by the slicing procedure. Consequently, we would expect that slicing would be more likely to reduce M72-mediated lateral inhibition onto MCs than TCs. However, in Main finding 2: Lateral inhibition affects intermediate firing rates in MCs and low firing rates in TCs , 3Similar to the above argument, we include data in Finally, the lateral dendrites of MCs and TCs innervate distinct strata of the external plexiform layer and these differences could result in differences in the fraction of the original connections left intact following slicing. However, the effect of lateral inhibition on MCs that are observed here following activation of an entire glomerulus closely mirrors the effects that were observed when activating a single presynaptic MC in our previous work . That is, only the probability of finding connections and the absolute magnitude of the effect are increased by activating all of the cells associated with a glomerulus (compared to the prior study when only a single presynaptic cell was activated). This suggests that the critical feature of the effect  is a property of single connections rather than one that depends on having a full repertoire of connections intact.Main finding 3: Compared with deep GCs, superficial GCs spike with higher probability and receive stronger excitatory currents following glomerular stimulation We agree with the reviewers that the greater recruitment of sGCs following glomerular activation may be a consequence of our use of an acute slice preparation. Specifically, as TC circuitry is closer to any given glomerulus than MC circuitry, TC-mediated input to GCs (likely sGCs) may be better preserved than MC-mediated input to GCs (likely dGCs) in the acute slice, leading to stronger sGC excitation and recruitment following glomerular activation. We explicitly note this as a caveat in the Results section of our revised manuscript.We note, however, that three lines of evidence argue against this possibility, and support greater feedforward recruitment of sGCs as a physiological feature of the olfactory bulb circuit.A) Our in vitro observation of greater sGC firing following glomerular activation  correspoB) Examination of GC biophysical properties revealed several intrinsic differences supporting greater recruitment of sGCs than dGCs, including a more hyperpolarized action potential threshold in sGCs , Table 2C) Analysis of spontaneous synaptic activity revealed no difference in event frequency or amplitude between sGCs and dGCs. We have included this new analysis in In view of these three lines of evidence, we believe that our results strongly suggest that sGCs are more strongly recruited than dGCs following activation of a single glomerulus due to stronger excitatory input and greater intrinsic excitability.In addition to the specific revisions to our manuscript described above, we have also broadly summarized this rationale in the following section of our revised Discussion:“Performing these experiments in acute slices provides the best opportunity to explore the causes and consequences of differences in lateral inhibition between MCs and TCs. […]Addressing the extent to which ADLI affects odor-evoked responses in MCs and TCs in vivois thus an important future direction.”2) The authors examined the significance of differential ADLI between mitral and tufted cells using modeling. However, mitral and tufted cells are different not only in their ADLI properties but also their intrinsic and synaptic input properties. In the modeling, all of these are changed at the same time, and therefore, it is unclear whether improved odor discriminability at different odor concentrations is due to ADLI alone, differences in intrinsic/synaptic properties alone, or a combination of all factors. Please clarify this issue with additional analysis.We agree with the reviewer that understanding how each of the differences between MCs and TCs contribute to concentration-dependent differences in odor discrimination is important and have updated We make two conclusions from these simulations. First, each of three experimentally determined differences between MCs and TCs  alone is sufficient to allow TCs perform better at low concentration. Second, TCs are best at performing low concentration odor discrimination and MCs are best at performing high concentration discriminations when all three differences are present. Therefore, because these intrinsic and circuit-level differences between MCs and TCs all lead to the same functional difference between MCs and TCs, this functional difference is likely to be an important feature of processing of odor-evoked information.We have updated the Results, 3) In We apologize for the confusion caused by the To reduce confusion, we have changed the 4) in vivo experiments would greatly increase the significance of the present study as lateral inhibition may be sensitive to subtle details of the network properties, spontaneous activity and breathing etc. that can be seen only in an intact network. If the authors decide not to perform in vivo experiments, potential caveats of their in vitro experiments must be explicitly discussed.We agree that exploring how ADLI influences odor-evoked responses in MCs and TCs in vivowill be important to the field. However, we believe that the reduced slice preparation that we use in our work provides several advantages for exploring the novel features and mechanisms of ADLI in MCs and TCs. Therefore, we have added an additional section to our Discussion that more explicitly addresses the advantages and limitations of performing our experiments in vitro. We refer the reviewer to this section and to our response to Essential Revision #1 above.Reviewer #1:Overall, this is an interesting study that addresses a broadly relevant question: How can two parallel sensory processing paths  enhance sensory discrimination? Much of the study also employs a powerful experimental paradigm involving optogenetic stimulation of a single, molecularly-defined glomerulus (M72) as a means to drive lateral inhibition. This strategy should eliminate ambiguities about whether only one glomerulus is being stimulated and, also, should reduce variabilities across experiments. Some of the results are also basically convincing, for example that MCs and TCs have different kinetics for lateral inhibition and also differ in the frequency range over which ADLI occurs. However, I have a number of concerns with both the experimental and modeling sections of the paper.1) The analysis methods used raise questions about results suggesting that TCs display a larger percent decrease in spike rate due to ADLI than MCs . The legWe apologize for the confusion caused by the 2) That differences in the properties of superficial versus deep GCs (sGCs and dGCs) contribute to differences in ADLI between MCs and TCs is not completely convincing. The argument is based on the parallel observations that TCs display ADLI at lower spike frequencies than MCs and also that sGCs  are more responsive to glomerular stimulation. However, the authors need to exclude better the possibility that the greater spike probability and evoked currents in sGCs is not a slicing artifact. sGCs, which are closer to glomeruli, may naturally be expected to have more of their input circuitry intact in slices. The fact that sGCs appear to have greater intrinsic excitability helps their argument, but it is not sufficient. Comparing ADLI and the responsiveness of GCs is also complicated by the fact that the experiments assaying these two features appear to have been conducted in differing magnesium concentrations (0.2 mM versus 1 mM).We agree that understanding how the slicing may contribute to our reported findings is vital and have addressed this issue above under Essential Revision #1.The authors also use the fact that the mGluR agonist DHPG reduces the frequency range for ADLI in MCs to argue that differences in ADLI between MCs and TCs are due to GC properties. This is based on prior observations that DHPG can enhance GC excitability. DHPG appears not alter MC spiking due to direct current injection , yet othThe reviewer brings up a good point that DHPG could enhance lateral inhibition mediated by glomerular layer circuits. However, we have indicated in 3) The computational results suggesting that differences in ADLI between MCs and TCs enable these cells to perform odor discrimination at different concentrations are not completely convincing. The most important results are shown in We have made Reviewer #2:Geramita, Burton & Urban report through a series of elegant experiments in acute olfactory bulb preparations that the two types of bulb principal neurons, tufted and mitral cells, receive different levels of inhibition from granule cells . The authors show through a combination of patch-clamp recordings, current injections and optogenetic stimulation of genetically labeled glomeruli that activity dependent lateral inhibition (ADLI) occurs at low firing rate regimes in tufted cells and intermediate firing rates in mitral cells. They further propose as underlying substrate at play for the different ADLI regimes two distinct populations of superficial and deep granule cells . Anatomical reconstructions and clustering suggest that sGCs and dGCs contact differentially the lateral dendrites of TC and respectively MCs. Further functional analysis reveals differences in intrinsic excitability and threshold for action potential firing between sGCs and dGCs consistent with their proposed roles. In my opinion, the manuscript adds important novel understanding by documenting that functional differences between mitral and tufted cells emerge not only due to differences in intrinsic excitability, but also in their local connectivity with inhibitory interneurons. These findings bring timely mechanistic insight that parsimoniously explains recently published differences in TCs and MCs responses to odors, across concentrations, and to modulation of cortical feedback. Therefore, I consider the manuscript fit for publication in eLife should the authors address several concerns listed below.Importantly, I have doubts regarding the necessity of the computational model presented and some of its underlying assumptions. Given the temporal complexity of active sampling (sniffing) in vivo, relevant time window for odor identification , possible effects of the slice preparation on the functional connectivity of the bulb, and lack of top-down regulation  of mitral and tufted cell activity in the slice preparation, I suggest focusing the manuscript on the experimental results with fewer incursions into the simulations.1) The authors present in We thank the reviewer for bringing this study to our attention. In our updated manuscript , we have added this reference as a caveat to our assumption that MCs and TCs encode odor concentration as firing rate changes.While the Meredith work indicates that some MC/TCs may display concentration response curves that are not monotonic, the other cited studies show that firing rate is one of several properties that consistently vary with changes in concentration. Even if some MCs and TCs do not display monotonic concentration response curves, the results of our simulations will still be important for understanding how ADLI may influence the representations encoded in large numbers of MCs and TCs.2) What is the functional relevance of the concentration regime sampled? What does 20% to 80% of maximal concentration translate to in terms of absolute odor concentration? Are such concentrations ever encountered by the animal?The x-axis in the We have included an explanation of our rationale for using this quantification metric in the updated Methods .3) Why is the classifier trained independently for each of the concentrations sampled? This seems an unrealistic regime compared to processes that may occur in the brain.The reviewer’s question is an important one. We chose to train the classifier independently for each concentration to mimic typical behavioral experiments where animals are trained to discriminate between different odors presented at similar odor concentrations. We believe that in order to train the classifier on odors presented at multiple concentrations, we would need to introduce assumptions about how the same odor is represented at different concentrations. Indeed, this question of how MC/TC representations of odor identity remain invariant across a range of concentrations is important but ultimately one that cannot be adequately addressed with our model.In the manuscript (Results), we have added the following caveat. “While understanding how animals discriminate between odors presented at a variety of concentrations is important, we confined our discriminations to odors presented at the same concentration to more closely match behavioral experiments in mice  and to keep from making a number of assumptions about how the representation of individual odors varies across concentration.”4) Differences in functional properties of sGCs and dGCs can be in principle heavily modulated by top-down signals that are absent in the slice. The current version of the manuscript does not discuss this possibility.We agree with the reviewer that both superficial and deep GCs may be heavily influenced by top-down modulation from a variety of brain areas and have addressed this caveat in the updated manuscript. Our response to this point as well as our discussion of other differences that may occur in vivocan be found under Essential Revisions #1 and #4 above.5) MC and TCs have been reported to project with differential biases to downstream target areas. How do such biases contribute to the ability of the decoder to incorporated odor information carried by both TC and MC?The reviewer brings up a good point that MCs and TCs project to separate sets of downstream areas. However, current data suggest that there are areas, such as the anterior piriform cortex, that receive input from both MCs and TCs. The simulation that generated the data in Our simulations do not address how other areas such as the anterior olfactory tubercle, which receives stronger input from TCs than MCs, might be integrating or decoding information transmitted in both channels. Therefore, we have refrained from drawing conclusions about how information is integrated in these other downstream areas.In We agree that in order to compare GC-mediated and glomerular layer mediated inhibition between MCs and TCs, only cells with intact apical dendrites should be analyzed. However, after removing cells with cut apical dendrites and redoing the statistical analysis done in Reviewer #3:The authors present a detailed in vitro analysis of differences in lateral inhibition experienced by MCs and TCs. They attribute these differences to different innervation of different populations of GCs and use a simplified model to illustrate that the differential inhibition can lead to improved discriminability overall (with TCs aiding to low-concentration and MCs to high-concentration discrimination).In a previous submission  there were numerous criticisms that the authors largely address well. One key concern that was reiterated by all reviewers was that the findings of differential inhibition were exclusively based on in vitro experiments (and simulations) with little direct link to how sensory information might be processed. Here I think the current manuscript is still lacking. While the authors argue – rightly so – that they perform an in depth mechanistic analysis (which is difficult in vivo) I have to say I tend to agree in that the relevance / role of the differential inhibition for odor processing is still unclear. If indeed – as stated in the response to prior reviewer 1 – the variability / signal-to-noise will mask the effect in vivo one might question how dominant it could be in a behaving context. I surely don't argue for repeating all experiments in an awake behaving animal but key experiments parts of  and 4 atWe thank the reviewer for his comments. We agree that understanding how lateral inhibition affects odor-evoked responses in MCs and TCs in vivois critical. We have added a paragraph to our Discussion that addresses the limitations of our in vitroapproach. It can be found above under Essential Revision #1.The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance as agreed upon by the reviewers in discussion following their original reviews that are appended below. Specifically, while all the referees agreed that the manuscript has been greatly improved, there are two remaining concerns. First, the reviewers thought that it remains unclear whether the authors can completely exclude the possibility that slicing biased the contribution of superficial versus deep granule cells in activity-dependent lateral inhibition (ADLI) (point # 1 of reviewer 1). Furthermore, the interpretation of the experiment using DHPG should be revised so that the possibility of the network effect  is appreciated. We think that both points can be addressed with revisions to the text as outlined by reviewer 1. For more details, please see the reviewers' original reviews below.Reviewer #1:The Reviewers have adequately addressed most of my concerns. Especially helpful are their new modeling results showing that differences in ADLI between MCs and TCs contribute to odor discrimination across a wider range of odor concentrations even in the presence of other important differences between MCs and TCs. Some concerns about slice artifacts and their interpretation of differences in excitation of sGCs and dGCs however remain, as do concerns about their DHPG experiments (both brought up in Major Point 2 of my prior review). These, which are explained below, however will just require changes in the text. Their overall story is quite interesting, and I would be satisfied if they simply backed off on some of their claims pertaining to GCs.1) That the greater evoked responses in sGCs versus dGCs is due to greater excitatory input and intrinsic excitability rather than slice artifacts is still not completely convincing. In response to this concern, raised previously, the authors provided three lines of evidence in the rebuttal letter and Results section, which I will address individually (authors' text is in parentheses).A) . The results do not support that sGCs have synaptic and intrinsic properties that make them more responsive.B)  These data are not especially helpful for excluding slice artifacts because the spontaneous events in GCs (sEPSCs) could reflect spontaneous release of glutamate from pieces of M/T lateral dendrites that remain in the slice but are not associated with a cell body. This differs from responses evoked by stimulation of a single glomerulus, which requires intact cell bodies so that action potentials can pass to the lateral dendrites. That the experiments were conducted in the absence of TTX is not very supportive of there being intact cell bodies, since no evidence is provided to suggest that a major portion of the sEPSCs are being driven by action potentials. They could be mEPSCs . In addition, it cannot be excluded that there are spontaneous action potentials in pieces of lateral dendrites that are dissociated from cell bodies. Full-sized action potentials can propagate down mitral cell lateral dendrites, suggesting the presence of sodium channels in these dendrites. To use the spontaneous events as an argument against slice artifacts, the authors would need to perform additional controls .Taking these points together, I still am not convinced that the differences in evoked responses in dGCs and sGCs do not mainly reflect a slice artifact. However, at this point, I would be satisfied if the authors make changes in the text and reduce their emphasis on differences in the synaptic and intrinsic properties of the two GC sub-types being causal to the different ADLI properties of MCs versus TCs.We thank the reviewer for these comments and agree that we cannot completely rule out the possibility that the differences between evoked responses in sGCs and dGCs may be due to slice effects. We also agree that we have not provided direct evidence that differences between dGCs and sGCs cause differences in ADLI between MCs and TCs. However, we believe that we do provide evidence that differences in ADLI are not caused of glomerular layer lateral inhibitory circuits and are thus due to external plexiform layer circuits. Additionally, the data presented in The revised manuscript reflects this shift in tone in several areas listed below:A) “Several previous findings are consistent with this hypothesis. GC soma position correlates with GC subtype…”B) “However, despite the fact that these observations were made in vitro, three lines of evidence support greater feedforward recruitment of sGCs as a physiological feature of the olfactory bulb circuit. First, our in vitroobservation of…”C) “In total, our results thus support the hypothesis that sGCs are more strongly recruited than dGCs following activation of a single glomerulus due to stronger excitatory input and greater intrinsic excitability, although we cannot rule out an important role for other mechanisms, especially in the intact system in vivo.”D) “As an additional test of our hypothesis that differences in the excitability of GCs provide one potential mechanism underlying thefunctional difference in ADLI between MCs and TCs, we measured the effects of lateral inhibition on MC spiking before and after increasing the excitability of GCs with the mGluR agonist, DHPG.”E) “Despite these observations, however, we note that increased GC excitability may not be the sole mechanism responsible for these DHPG-induced shifts in the effective range of lateral inhibition. For instance, DHPG-induced increases in the excitability of external tufted(Dong and Ennis 2014) cells may, in turn, increase the activity in M72-MCs, the activity in GCs and GC-mediated inhibition onto the recorded MC.”F) “These data –5 providG) “We provide evidence that these effects could be caused, in part, by differences in the excitability of subclasses of GCs that preferentially inhibit TCs vs. MCs.”H) “Additionally, we provide indirect evidence that differences in the recruitability of sGCs and dGCs may be one potential mechanism underlying of the differences in ADLI between MCs and TCs. Our data suggests that sGCs spike with a higher probability than dGCs following the activation of a single glomerulus.”I) “Additionally, these differences between sGCs and dGCs can explain why the upper bound on the effective activity range of lateral inhibition differs between MCs and TCs.”2) Some concern also remains about the DHPG experiments, which the authors use to argue that the requirement for higher spike frequencies in MCs to obtain ADLI reflects the excitatory properties of GCs. I previously raised the issue that the DHPG-induced shifts in the effective range of lateral inhibition could reflect drug-effects on glomerular layer neurons rather than GCs. In response, the authors point out that 2 MCs with cut apical dendrites (that do not receive inputs from glomerular layer cells) show similar DHPG-induced shifts in the effective frequency range for ADLI as those MCs with intact apical dendrites. However, these data do not exclude the following plausible network effect involving DHPG-induced excitation of external tufted cells in the glomerular layer : DHPG-induced excitation of eTCs causes greater feedforward excitation of a population of MCs at a glomerulus; this in turn leads to greater excitation of GCs and GC-mediated inhibition. Such an effect, involving GC inputs onto MC lateral dendrites, would not depend on a test MC having intact apical dendrites.Despite this caveat, their results showing that the 2 MCs with cut apical dendrites show similar DHPG-induced shifts in the effective range of lateral inhibition as MCs are helpful. They at least support the conclusion that changes in the degree of GC excitation (either direct or indirect) can control the frequency range over which the ADLI occurs, which is itself interesting.We agree with the reviewer that DHPG-induced shifts in the effective range of lateral inhibition onto MCs can, in part, be explained by increases in GC excitability, based on the 2 MCs that lack apical dendrites. However, we agree that we cannot completely exclude the possibility that DHPG also increases the excitability of ETCs, which, in turn, can increase the activity in M72 MCs, the activity of GCs, and the amount of GC-mediated inhibition.Therefore, in the updated manuscript we have added the following sentence: “As a caveat, however, we note that increased GC excitability may not be the sole mechanism responsible for these DHPG-induced shifts in the effective range of lateral inhibition. For instance, DHPG-induced increases in the excitability of external tufted cells  may, in turn, increase the activity in M72-MCs, the activity in GCs and GC-mediated inhibition onto the recorded MC.”Reviewer #3:The authors are discussing my key concern (whether the findings hold true in vivo) very well in the rebuttal and following their logic it is indeed very likely that most of the key findings will hold true. I find the well-structured and expanded (compared to the Discussion) overview given in the rebuttal very helpful and would suggest incorporating this version into the Discussion.We thank the reviewer and agree that it is useful to add more of the detailed logic from our first response to reviewers. In addition to the changes above, several of which address this issue and reiterate the logic from the previous rebuttal letter, we have added the following to our Discussion:“Additionally, the lateral dendrites of MCs and TCs innervate distinct strata of the external plexiform layer and these differences could result in differences in the fraction of original connections left intact following slicing. […] This suggests that the critical feature of the effect  is a property of single connections rather than one that depends on having a full repertoire of connections intact.”


It is used to express the energy cost of physical activity in multiples of MET. However, universal application of the 1-MET standard was questioned in previous studies, because it does not apply well to all individuals. Height, weight and resting metabolic rate  were measured in adolescent males (n = 50) and females (n = 50), women during pregnancy , women 24–53 weeks postpartum (n = 27), and active men (n = 30), and were compared to values predicted by the 1-MET standard. The RMR of adolescent males  was significantly higher than that of adolescent females , with or without the effects of puberty stage and physical activity levels. The RMR of the pregnant and post-pregnant subjects were not significantly different. The RMR of the active normal weight  and overweight  adult males were significantly lower than the 1-MET value. It follows that the 1-MET standard is inadequate for use not only in adult men and women, but also in adolescents and physically active men. It is therefore recommended that practitioners estimate RMR with equations taking into account individual characteristics, such as sex, age and Body Mass Index, and not rely on the 1-MET standard.“Metabolic Equivalent” (MET) represents a standard amount of oxygen consumed by the body under resting conditions, and is defined as 3.5 mL O Resting metabolic rate (RMR) is defined as the energy expended by the body in a resting condition. It accounts for the largest portion of a subject’s total daily energy needs (60%–70%), the remainder being accounted for by diet-induced thermogenesis ~10%) and physical activity-induced energy expenditure  [0% and phTypically, the RMR is measured with a subject physically and mentally at rest, in a supine position, after an overnight fast and in a thermo-neutral environment, to prevent activation of non-RMR heat-generating processes . Because2/kg × min) or ~1 kcal per kg body mass per hour  [The term “Metabolic Equivalent” (MET) is commonly used by exercise physiologists, nutritionists and the medical community, in circumstances when the RMR is not directly measured. It is defined as the quantity of oxygen consumed by the body from inspired air under resting conditions, that is, 3.5 mL of oxygen per kg body mass per minute (3.5 mL O/kg × h) . The METHowever, the widespread application of the conventional 1-MET value has begun to be questioned, because it does not apply well to all individuals, nor to all population subgroups . This isDespite those reported effects of demographic and anthropometric characteristics on RMR, there is still a paucity of data comparing RMR of other specific population subgroups with the conventional 1-MET value, particularly in youths, pregnant and non-pregnant women, or physically active subjects. These population sub-groups are particularly important, because other factors like growth (adolescence), foetal demands (pregnancy) and energy costs of milk synthesis (lactation) could significantly influence RMR and, thus, cause its value to deviate from the conventional 1-MET value. In addition, there are at present no data examining the RMR of these specific subgroups while taking into consideration their physical activity levels (PAL), that is, their total energy expenditure in multiples of RMR. The purpose of this study is to examine the RMR of adolescents, pregnant and non-pregnant women, as well as active male subjects, using RMR data acquired during several metabolic studies performed in our laboratories, and to compare the measured RMR values with the conventional 1-MET values.n = 27) after their pregnancy (24–53 weeks postpartum (mean of 40 weeks)) [, Genève, No. 09/031 (26 June 2009)) approved the original studies. Subject characteristics are presented in In the course of several research activities recently performed by our research groups, RMR and PAL were measured in 100 adolescent males and females (unpublished data), 46 pregnant women (35–41 weeks of gestation mean of 38 weeks)), a subgroup of the same women ( weeks),  weeks)) . Those dBody weight was measured to the nearest 0.01 kg using a calibrated beam scale  and body height to the nearest 0.01 cm using a height rod (Seca Ltd.), with subjects in underwear and without shoes. BMI was calculated for all subgroups and classified into under-, normal-, overweight and obese using the following categories: For active adult males and adult non-pregnant females according to standard classification ; for preRMR was assessed by indirect calorimetry using ventilated hood systems; either a Moxus Metabolic System  in the adolescent and active male adults, or a Deltatrac II metabolic monitor  in the pregnant women, under the standardized conditions described below. Reliability and validity of the devices have been reported elsewhere ,18.2) and carbon dioxide production (V’CO2) were measured for 30 min with the subjects in a supine position and completely at rest in a quiet and thermo-neutral environment (20–22 °C). The first 5 min of data were eliminated as an acclimation artefact. From the remaining 25 min, segments of a minimum of 10 consecutive 1-min measures with <10% coefficient of variation in V’O2 and V’CO2 were considered as steady-state. Average V’O2 and V’CO2 values were then used to calculate RMR using the abbreviated Weir equation [In short, calibration of the gas analysers and the flow measurement module was carried out before each measurement according to the manufacturer’s instructions. The subjects were instructed to arrive in the research unit in the morning, after an overnight fast (12 h), avoiding any strenuous physical effort for a minimum of 24 h before the RMR measurement. After acclimating and relaxing on a bed for 30 min, a ventilated hood was placed over their heads and the measurements started. Oxygen consumption (V’Oequation .Activity energy expenditure (AEE) was estimated by analysing 24-h recordings of heart rate and movement (acceleration). A lightweight (10 g), waterproof combined heart rate and movement sensor  was clipped onto two standard electrocardiography electrodes  on the left thorax just below the level of the apex of the sternum . The devT-tests and ANOVA with Scheffé post hoc tests for in between-group comparisons of RMR were also performed. An analysis of covariance (ANCOVA) was additionally used to control for the covariates, such as puberty (Tanner stage) and PAL. Spearman correlation was used to assess the relationship between age, BMI, the RMR, and the time of measurement (pregnancy and postpartum week). p-values < 0.05 were considered statistically significant. SPSS software  was used for data description and statistical analyses.Descriptive data and continuous variables are reported as mean ± standard deviation (SD) or 95% Confidence Intervals (CI). All RMR data are expressed in kcal/kg × h and compared with the 1-MET standard value of 1 kcal/kg × h. The data were normally distributed apart from age, height, weight, and BMI, according to the Kolmogorov-Smirnov test. p = 0.0001). The RMR of the adolescent males was 1.28 kcal/kg × h (95% CI = 1.24–1.33), and that of the adolescent females was 1.11 kcal/kg × h (95% CI = 1.07–1.14) (p = 0.002) and Tanner stage 2 (pubic hair) (p = 0.0001). The RMR of male adolescents did not differ by Tanner stage 1 (p = 0.96) but differed by Tanner stage 2 (p = 0.006). The RMR of female adolescents differed by Tanner stage 1 and 2 .The overall mean value for RMR from all 203 measurements was 1.08 kcal/kg × h (95% CI = 1.06–1.11), and was significantly different from the conventional 1-MET value  (07–1.14) . The ovep < 0.0001). The RMR of adolescent males and females were significantly different by age (p = 0.002). When analysed separately, the RMR of male adolescents were significantly different by age (p = 0.002), while those of the female adolescents were not (p = 0.063). The RMR of adolescent males and females were significantly higher than the RMR of any other adult subgroup , and the conventional 1-MET value .The RMR of the adolescent males was significantly higher than that of the adolescent females, with or without the effects of puberty stage  and PAL . RMR of adolescent males aged 12–14 years old was similar to that of adolescent males aged 15–17 years  vs. 1.26 kcal/kg × h (95% CI = 1.21–1.31), p = 0.978). Adolescent females aged 12–14 years had a significantly lower RMR than their male counterparts (p = 0.001). Adolescent females aged 15–17 years old had a significantly lower RMR than their male counterparts (p = 0.007). RMR of adolescent females aged 12–14 years and of those aged 15–17 years were significantly higher than the conventional 1-MET value of 1 kcal/kg × h . RMR of all male adolescent age subgroups were significantly higher than the conventional 1-MET value . There was a tendency for a negative correlation between age and RMR for all adolescents .RMR of adolescent females aged 12–14 years was similar to that of adolescent females aged 15–17 years  vs. 1.11 kcal/kg × h (95% CI = 1.07–1.16), n = 5) had significantly higher RMR compared with normal weight male adolescents (n = 44)  vs. 1.26 kcal/kg × h (95% CI = 1.22–1.30), p = 0.001) (p < 0.0001). RMR of the normal weight and overweight female adolescents were similar  vs. 1.03 kcal/kg × h (95% CI = 0.86–1.21), p = 0.06). The RMR of the normal weight female adolescents were found to be significantly higher (p < 0.0001) than, and those of the overweight adolescents similar (p = 0.63) to, the conventional 1-MET value.The underweight male adolescents (= 0.001) . The RMRp = 0.997) . The RMR of pregnant and post-pregnant women were not significantly different from the conventional 1-MET value . Thirteen of the post-pregnant female subjects were lactating, while 14 were not, but their RMR/kg × h was not influenced by lactation status  vs. 0.98 kcal/kg × h (95% CI = 0.92–1.05), p = 0.54).The RMR of the pregnant female subjects was not different from that of the post-pregnant female subjects  vs. 1.00 kcal/kg × h (95% CI = 0.95–1.04), = 0.997) . The RMRp = 0.001). No significant difference in RMR was found between adult male and post-pregnant female subjects  vs. 1.00 kcal/kg × h (95% CI = 0.95–1.04), p = 0.09)), including when adjusted for PAL (p = 0.26). The RMR of the pregnant female subjects was significantly higher than those of the active male subjects  vs. 0.91 kcal/kg × h (95% CI = 0.88–0.93), p = 0.01). Active adult male subjects had significantly lower RMR than the conventional 1-MET value (p = 0.001). A negative correlation was found between age and RMR for active adult males , females excluding pregnant women , and females including pregnant women .The PAL of 1.9 in active male subjects was significantly higher that the PAL of 1.7 in post-pregnant female subjects (p = 0.322). The RMR of normal weight and overweight active adult males were significantly lower than the conventional 1-MET value of 1 kcal/kg × h . The RMR of normal weight post-pregnant females was significantly higher than that of the overweight post-pregnant females  vs. 0.88 kcal/kg × h (95% CI = 0.82–0.97), p = 0.009). While the RMR of normal weight post-pregnant women was not significantly different from the conventional 1-MET value (p = 0.19), that of the overweight post-pregnant women was significantly lower (p = 0.007).p > 0.05). There was a significant negative correlation between BMI and RMR for post-pregnant females , adult females  , and active adult males .The RMR of normal weight, overweight, and obese pregnant females were not significantly different from the conventional 1-MET value  leads to considerably greater error than using actual RMR measurements ,7. We haWhen expressed in kcal/kg × h, the mean RMR of both adolescent males and females were significantly higher than the mean RMR of any other adult subgroup and the conventional 1-MET value. In teenagers (age group 11 to 17 years), the values in males were significantly higher than those in females, regardless of obesity status, puberty stage or age.Holliday et al. studied the relationship between metabolic rate and body mass in different age groups and reported that RMR/kg in humans during growth could be as high as 56 kcal in infants below 6 months, weighing about 6 kg  . The ratn = 512) expending, on average, 1.17 kcal/kg × h, and boys (n = 480) 1.32 kcal/kg × h. Finally, our own measurements presented in this study yielded similar results  Human Energy Requirements report, the energy needed during resting state is 33 kcal/kg to 27 kcal/kg for boys aged 12 to 17 years ), and 29 kcal/kg to 25 kcal/kg for girls of the same age group ) . We revi results , showingThe RMR values of the pregnant women we assessed did not differ significantly from the conventional 1-MET value, regardless of their obesity status. Pregnancy was shown to increase absolute RMR in concert with body weight gain, in about the same proportion . The mosIt should also be noted that the RMR of the post-pregnant female subjects was found to be independent of lactation status. Our results are in line with other longitudinal studies that found no difference in RMR between lactating and non-lactating women , even whThe RMR of lactating women would be expected to be elevated as a result of the energy cost of milk synthesis . The facWe found a negative correlation between age and RMR for all adult subgroups . The decline in RMR was reported to be mainly attributable to the progressive absolute and proportional loss of fat-free mass observed with aging , and proThe RMR of the adult active males were similar to those of the non-pregnant female adults, but in the former, it was lower than the conventional 1-MET value, regardless of BMI. This observation was previously reported by McMurray et al. , who revThe surprisingly similar RMR values per kg in men and women, which are not often reported, can partly be explained by the physical characteristics of the two groups: The absolute difference between males and females was 19 kg in weight , 14 cm in height and 3 units BMI greater in males, although both males and females had BMI within the reference range. We know that there is a negative curvilinear relationship between body weight and RMR per unit body weight in both males and females, with a downward shift in females; this suggests that the large gap in body weight in males as compared with females would have attenuated the relative difference in RMR between females and males.Furthermore, it should be noted that the RMR of the adult men presented in this study were measured after an 8-week-long exercise intervention program (daily activities for ~90 min at moderate and ~10 min at high intensity levels (PAL = 1.9)) leading to a loss of body mass. The PAL of the active male subjects were significantly higher than the PAL of the non-pregnant women. The engagement in such high activity levels in combination with a negative energy balance might have decreased the RMR of these active male subjects .Some cross-sectional ,71 and lExtreme exercise interventions, however, may induce reductions in RMR, in spite of the increases in lean tissue mass that they cause . Some auThe use of the per-ratio model facilitates comparison between individuals, assuming that: (1) the RMR rises proportionately to the increase in body mass so that the value per kg remains constant; and that (2) the relationship between the measurements is linear and passes through the origin . HoweverA limitation of this study is that we did not perform body composition assessment within the scope of our several metabolic research activities in adolescents, pregnant, non-pregnant women and active male subjects whose measured RMR data are assembled herein. Body composition data would have allowed us to further examine the factors potentially influencing the discrepancies between the measured RMR and conventional 1-MET value. Nonetheless, we succeeded in reporting the deviations of measured RMR from the conventional 1-MET as expressed in terms of body mass ratio , which was the main objective of the study.The strength of our study is that it is, to our knowledge, the first investigation to compare measured RMR with the commonly-accepted 1-MET value in a population comprising adolescents of both sex, active adults, and both pregnant and post-pregnant women. McMurray et al.  and ByrnWe report discrepancies between measured RMR and the 1-MET standard in adolescents (aged 12–17 years), pregnant women (35–41 weeks of gestation), post-pregnant women (24–53 weeks postpartum) and active men (PAL = 1.9), extending earlier observations in adults. It follows that indiscriminate use of the conventional 1-MET value is likely to bias the true relative energy cost of exercise expressed in MET, and may have implications for the formulation of exercise prescription for specific population subgroups. We recommend that instead of using the 1-MET standard, the RMR is estimated using validated equations taking into account at least sex, age and BMI.


Health-related quality of life (HRQL) for nursing home residents is important, however, the concept of quality of life is broad, encompasses many domains and is difficult to assess in people with dementia. Basic activities of daily living (ADL) are measured routinely in nursing homes using the Resident Assessment Instrument-Minimum Data Set Version 2.0 (RAI-MDS) and Functional Independence Measure (FIM) instrument. We examined the relationship between HRQL and ADL to assess the future possibility of ADL dependency level serving as a surrogate measure of HRQL in residents with dementia. To assess ADL, measures derived from the RAI-MDS and FIM data were gathered for 111 residents at the beginning of our study and at 6-month follow-up. Higher scores for independence in ADL were correlated with higher scores for a disease-specific HRQL measure, the Quality of Life—Alzheimer’s Disease Scale. Preliminary evidence suggests that FIM-assessed ADL is associated with HRQL for these residents. The associations of the dressing and toileting items with HRQL were particularly strong. This finding suggests the importance of ADL function in HRQL. The RAI-MDS ADL scales should be used with caution to evaluate HRQL. The maintenance or improvement of health-related quality of life (HRQL) is important in the treatment of persons with dementia . ApplicaWith varying operational definitions of HRQL, a wide variety of measures exist that assesses fundamentally different constructs. When many HRQL instruments are used there may be confusion as to what is really being assessed. There have been attempts to determine which domains most accurately measure HRQL ,6 but fuet al. [et al. [The taxonomy of HRQL includes generic or disease-specific measures yet methodological concerns still exist. For example, Ettema et al.  examinedet al.  only fouet al. , but a s [et al.  claimed  [et al. .Basic activities of daily living (ADL), such as dressing, eating, toileting, and transfers, are outcomes that are more observable and perhaps more relevant to persons with dementia ,11. NursTo our knowledge, no studies have examined this relationship using the FIM and Resident Assessment Instrument-Minimum Data Set Version 2.0  in a frail older population with dementia. The objective of this study was to perform an exploratory analysis of the relationship between dependency in ADL and HRQL scores in nursing home residents with a dementia diagnosis.The present study is a secondary analysis of the original quasi-experimental Mobility of Vulnerable Elders (MOVE) study  which reUpon obtaining consent and assent, a disease-specific HRQL measure, the Quality of Life-Alzheimer’s Disease (QOL-AD) and disability measure of the assistance required to perform activities of daily living, FIM were administered by trained research assistants via proxy-interviews with health care aides for each resident at baseline (upon recruitment to the study) and at 6-month follow-up. These health care aides provided direct care to the resident and were familiar with the resident’s activities on a daily basis. In contrast, items on the RAI-MDS directly related to ADL were recorded quarterly by health care aides on 7-day tracking forms. These data were then integrated into the final RAI-MDS assessments completed by Registered Nurses. We used the quarterly RAI-MDS assessments administered closest to each resident’s baseline and six-month time points. The FIM was used to validate findings with the RAI-MDS. Data were collected from July 2011 to February 2013. The study was approved by the University of Alberta Health Research Ethics Board.The original version of the Quality of Life—Alzheimer’s Disease (QOL-AD)  is a 13-The RAI-MDS, a comprehensive assessment tool for nursing homes with over 300 items, has demonstrated adequate reliability and validity in institutionalized adults with dementia ,23,24. Wet al. [The Functional Independence Measure (FIM) is a performance-based measure that evaluates the assistance required to perform ADL. It consists of 18-items each measured with a scale of 1 (Dependent) to 7 (Independent). Total FIM scores range from 18 to 126, with higher scores representing greater independence . The FIMet al. .et al. [et al. [Descriptive analyses were performed on resident characteristics. Cases with missing QOL-AD scores were removed from analysis. Incomplete or missing cases were compared with the analyzed sample to identify any differences in age, sex depression, cognition or medical instability. Due to small numbers of participants in the independent category, residents’ levels of ADL dependency were recoded into three groups, developed by Granger et al. : Indepenet al. ,34. This [et al.  (Table 1post hoc tests were performed to correct for the multiple comparisons. Data for residents who scored an 8 (activity did not occur) for the Walk in Room RAI-MDS item were removed from the analysis, as an 8 was not included in the crosswalk.We analyzed the data using Analysis of Variance (ANOVA) to identify the individual ADL factors associated with lower scores of HRQL at baseline and 6-months later. Change in ADL or change in HRQL over the six-months was not examined as this was not the focus of the paper. To examine the differences in the means of the QOL-AD scores across the three levels of dependency in RAI-MDS items and FIM items, several one-way analyses of variance were completed. Bonferroni p-value < 0.20, in a bivariate regression of covariates and the dependent variable QOL-AD, were selected to assess for confounding in further analyses [A multivariate linear regression was also performed to determine the magnitude and direction of level of ADL (FIM and RAI) that explained QOL-AD. ADL Short, ADL Long, ADL Hierarchy, and FIM Total were the independent variables. From the original MOVE study, resident age, sex, cognition (CPS score), depression (DRS score) and medical instability (CHESS score) data were available as covariates. All variables with a analyses . To asseanalyses ,38. Thosp < 0.05 level.Pearson’s correlations for each item on both instruments were calculated. Statistical significance was defined at the p = 0.001), however they did not differ in age, sex, cognition, and medical instability (p > 0.05).Two-hundred and seventy-four residents were recruited for the original study and 111 residents who completed baseline and six-month assessments were used in this analysis. The majority of residents were female (70.8%), and the mean age was 86.3 (SD = 7.27) years. Most residents had moderate cognitive impairment , mild depression  and low medical instability . Dementia diagnoses abstracted from the health record included 28 (25.2%) residents with Alzheimer’s disease, 21 (18.9%) with mixed dementia, 12 (10.8%) with vascular dementia and 50 (45.1%) with unspecified dementia. Residents with missing QOL-AD scores showed fewer symptoms of depression (p < 0.001), Grooming (p < 0.001), Upper Body Dressing (p < 0.001), Lower Body Dressing (p < 0.001), Toileting (p < 0.001), Bladder Management (p < 0.001), Bowel Management (p = 0.002), and Toilet Transfers (p = 0.01).In general, residents who were able to perform ADL with greater independence had higher mean QOL-AD scores than those with Modified Dependence in ADL . Similarp ≤ 0.003). The mean QOL-AD difference for Personal Hygiene was 11.32 between independent residents  and those who were completely dependent . Similarly, there was a 9.66 mean difference in QOL-AD between residents who were independent in Toilet Use  and those who were completely dependent . Sample sizes ranged from 2 to 69 at baseline and 4 to 80 at six months. Results of these one-way ANOVAs, with the RAI-MDS items as the independent variables, are reported in At baseline, six of nine items on the RAI-MDS  had higher mean QOL-AD scores in the higher independence categories; however these differences were not statistically significant. At six months, five of these six items were statistically significant, with higher QOL-AD scores in the higher independence categories. Personal Hygiene and Toilet Use had the largest differences at six months  and six months  explained a higher HRQL score. The same trend was seen with ADL Long scores at baseline  and six months . The RAI-MDS ADL Hierarchy scale demonstrated an effect on HRQL at baseline and at six months. After adjusting for confounders, the RAI-MDS ADL scale regressions were not statistically significant at both time points. .The bivariate linear regression of QOL-AD and FIM total scores showed a large positive relationship at both baseline  and six months  see .Dressing, Eating, and Toilet Use in the RAI-MDS and Eating, Grooming, Bathing Dressing Upper and Lower Body, Toileting, Bladder and Bowel Management, and Toilet Transfers in the FIM were the only items that were significantly correlated at both time points . Within The results demonstrate that basic ADL such as dressing, eating and toilet use had a reasonably positive association with HRQL: Greater independence in ADL was associated with higher HRQL scores in nursing home residents with dementia. Walking and transfers did not have a significant association with HRQL in our sample. Perhaps this is because only a small proportion of participants (34%) were able to walk at baseline. The ability to groom and dress the upper body may be indicators of dignity, which is linked to HRQL . Similaret al. [Our findings are consistent with the findings of others. A systematic review of factors associated with HRQL in residents with dementia found a negative relationship between ADL dependence and HRQL ratings in bivariate analyses but ambiguous results in multivariate analysis . Similaret al.  found a et al.  and sugget al. ,42.Generally, not as many factors of the RAI-MDS were significant compared with the number of FIM domains. This was seen as well with the ADL scales. Nonetheless, both the RAI-MDS and the FIM exhibited the same trend in associations between the individual items and total scores. A possible explanation for the difference may be that the FIM and QOL-AD were gathered at the same time in our study, by the same people , in a similar manner (proxy interviews); whereas the RAI-MDS assessments were completed once every quarter, in accordance with routine facility schedules, by nursing home staff who also rely on proxy reports from direct care providers. Reliability of the data may be questioned because staff members completing the assessment complete it for funding and administrative purposes rather than for research purposes. Furthermore, changes in the resident may go undetected between routine assessments. The RAI-MDS may reflect more HRQL domains and could have other confounders. Attempting to use the RAI-MDS as a surrogate measure appears suboptimal as such issues undermine the reliability of the data. The RAI-MDS should probably not be used in this manner to shape institutional care plans as this may impair quality of care.As with all studies, this study has limitations. The original quasi-experimental study did not involve randomization. While we have no reason to believe that this sample of participants was unusual, generalizing beyond this study must be done cautiously. Although many factors influence HRQL, we focused solely on the ADL component; therefore future research is recommended to strengthen the association of ADL and HRQL by accounting for other covariates.Another limitation of this study is that the FIM and HRQL data were gathered from proxy sources, which may have led to over or underestimating HRQL scores . LiteratWe found that ADL function is an integral component of HRQL for people with dementia. Given that in 2010 there were 35.6 million people living with dementia worldwide, and that this number is expected to double every 20 years , increasThe present study demonstrates there is an association between independence in activities of daily living, such as toileting and personal hygiene, and higher health-related quality of life in nursing home residents with dementia. This relationship is strongly supported by the FIM. Thus, with future longitudinal research, the FIM has potential to be a surrogate measure for quality of life while the widespread use of the FIM in facilities increases the utility of findings.