Tonotopic and non-auditory organization of the mouse dorsal inferior colliculus revealed by two-photon imaging — TEI-tagged view

WongpersName, BorstpersName, KingpersName, BathellierpersName, BathellierpersName, DahmenpersName, LlanopersName (2019date). “Tonotopic and non-auditory organization of the mouse dorsal inferior colliculus revealed by two-photon imaging.” eLifetitle·j.

Object of study — the functional organization of the dorsal and lateral cortices of the inferior colliculus, about which RELATIVELY LITTLE IS KNOWN

Research question — where the borderterm between DCICterm and LCICterm actually lies, given that THERE IS LITTLE AGREEMENT ON THE PRECISE BORDERSterm OF THE DIFFERENT NUCLEI and that ITS PARCELLATION HAS BEEN DIFFERENT BASED ON WHETHER CELL MORPHOLOGY, INPUTS, OR PHYSIOLOGICAL PROPERTIES WERE CHOSEN AS THE MAIN CLASSIFIER

Contribution — a reversal of the frequencyterm gradient, plus a subset of movement-sensitive neurons on one side of it only, which together PROVIDE FUNCTIONAL EVIDENCE FOR REDEFINING THE BORDERterm BETWEEN DCICterm AND LCICterm

Full text — tagged

Tonotopicterm and non-auditory organization of the mouse dorsal inferior colliculus revealed by two-photon imagingterm eLife 8 :e49091.

https://doi.org/10.7554/eLife.49091 Copy to clipboard Download BibTeX Download .RIS Abstract Introduction Results Discussion Materials and methods Data availability References Article and author information Metrics The dorsal (DCICterm) and lateral cortices (LCICterm) of the inferior colliculus are major targets of the auditory and non-auditory cortical areas, suggesting a role in complex multimodal information processing. However, relatively little is known about their functional organization. We utilized in vivo two-photon Ca 2+ imagingterm in awaketerm mice expressing GCaMP6sterm in GABAergicterm or non-GABAergic neurons in the IC to investigate their spatial organization. We found different classes of temporal responses, which we confirmed with simultaneous juxtacellularterm electrophysiologyterm·mth. Both GABAergicterm and non-GABAergic neurons showed spatial microheterogeneityterm in their temporal responses. In contrast, a robust, double rostromedial-caudolateral gradient of frequencyterm tuning was conserved between the two groups, and even among the subclasses. This, together with the existence of a subset of neurons sensitive to spontaneous movementsterm, provides functional evidence for redefining the borderterm between DCICterm and LCICterm.

https://doi.org/10.7554/eLife.49091.001 The inferior colliculus (IC) is a major auditory processing center, which receives input from most brainstem auditory nuclei. The IC is usually divided into three main regions: the central nucleus (CNICterm), the lateral cortex (LCICterm), and the dorsal cortex (DCICterm; Oliver, 2005 ). The latter two, together also known as the ‘shell region’ of the IC, are part of the non-lemniscal pathway, and are heavily innervated by feedback projections from the cerebral cortex. The DCICterm is often defined as the part that covers the CNICterm dorsally (e.g. Zhou and Shore, 2006 ). The LCICterm is characterized by distinct neurochemical modulesterm, which can be visualized with various histochemical methods such as acetylcholinesterase or NADPH diaphorase staining, as well as dense labeling of GABAergicterm terminals and sparse calretinin immunoreactivity ( Lesicko et al., 2016 ; Dillingham et al., 2017 ). These modulesterm show a distinct complement of Eph-ephrin guidance molecules during development ( Wallace et al., 2016 ; Gay et al., 2018 ) and receive input from non-auditory areas ( Lesicko et al., 2016 ; Patel et al., 2017 ), hinting at their integral role in multisensory integration in the IC. Here, we refer to the external cortex and lateral nucleus of the IC as the lateral cortex (LCICterm; Loftus et al., 2008 ), which includes layer three or the ventrolateral nucleus, and refer to the dorsal cortex and pericentral nucleus as the dorsal cortex of the IC (DCICterm). The DCICterm and LCICterm are at the surface of the mouse brain, making the dorsal IC an accessible structure for in vivo imagingterm ( Geis and BorstpersName, 2013 ; Barnstedt et al., 2015 ; Babola et al., 2018 ).

Because of the prominence of descending, cortical input, the DCICterm and LCICterm is ideally studied in awaketerm, behaving animals. A number of studies have addressed the firing of IC neurons in awaketerm bats (e.g. Xie et al., 2005 ; Xie et al., 2007 ; Xie et al., 2008 ; Andoni and Pollak, 2011 ; Gittelman and Li, 2011a ; Gittelman and Pollak, 2011b ; Gittelman et al., 2012 ) or mice ( Gittelman et al., 2013 ; Grimsley et al., 2013 ; Duque and Malmierca, 2015 ; Ayala et al., 2016 ; Grimsley et al., 2016 ; Longenecker and Galazyuk, 2016 ; Galazyuk et al., 2017 ). However, the yield of such recordings is limited, and the acute nature of some of the studies means that residual anesthetics and analgesics may have interfered with neuronal activity.

Moreover, relatively little is known about different cell types in the DCICterm and LCICterm. Around one-fourth of neurons in the IC are GABAergicterm ( Schofield and Beebe, 2019 ). In particular the large GABAergicterm neurons seem to form a distinct subclass ( Ito et al., 2009 ; Ito and Oliver, 2012 ; Geis and BorstpersName, 2013 ), but based on histology, at least four different subclasses of GABAergicterm neurons can be discriminated, which all contribute to the ascending projections to the medial geniculate body of the thalamus ( Beebe et al., 2018 ).

Here, we describe the use of two transgenic mouse lines to characterize GABAergicterm and glutamatergicterm neuronal subpopulations in the dorsal IC in awaketerm animals using in vivo two-photon Ca 2+ imagingterm. We studied GABAergicterm neurons with a Gad2-IRES-Cre mouse ( Taniguchi et al., 2011 ) that was crossed with the GCaMP6sterm reporter line Ai96 ( Madisen et al., 2015 ) and a sub-population of non-GABAergic neurons using the Thy1-driven GCaMP6sterm transgenic line GP4.3term ( Dana et al., 2014 ). We show a rich diversity of sound-evoked responses in both GABAergicterm and non-GABAergic neurons in the awaketerm mouse, confirmed with simultaneous juxtacellularterm electrophysiologyterm·mth in awaketerm animals. Remarkably, we observed a reversal of the characteristic frequency (CF)term·def gradient in the rostromedial-caudolateral direction, which was conserved between GABAergicterm and non-GABAergic cells, as well as among cells with different classes of sound-evoked response. Moreover, we found a subset of neurons that were responsive to spontaneous movementterm of the animal, and were potentially associated with multisensory neurochemical modulesterm ( Lesicko et al., 2016 ). These findings suggest that the large majority of the dorsal IC surface belongs to the LCICterm.

To better understand the response heterogeneity observed in IC neurons, we used transgenic lines in which the GCaMP reporter was selectively expressed in subpopulations. Two transgenic mouse lines were used: GP4.3term, a Thy1-driven GCaMP6sterm expression line ( Dana et al., 2014 ), and a cross between Gad2-IRES-Cre line ( Taniguchi et al., 2011 ) and Ai96, a Cre-dependent GCaMP6sterm reporter line ( Madisen et al., 2015 ). We will refer to the latter as Gad2;Ai96.

To confirm the neurochemical identity of GCaMP6s-positive neurons in the transgenic lines, we performed immunolabeling of GAD67term. Figure 1 shows example staining and the proportion of GCaMP-positive neurons expressing GAD67term in each line. We did not distinguish between the different subregions of the IC in this analysis. The large majority (4651/4898; 95%) of GCaMP-positive neurons in the GP4.3term line were not positive for GAD67term ( Figure 1A–D ), showing that the Thy1-promoter preferentially expressed GCaMP6sterm in non-GABAergic cells in the IC. Not all non-GABAergic cells were GCaMP-positive, as shown by the NeuN-positive, GCaMP-negative cell bodies in Figure 1C (arrowheads). In particular, we observed that GCaMP6s-positive neurons are enriched at the borderterm of neurochemical modulesterm characterized by dense GAD67term terminals ( Figure 1E–G ).

Figure 1 with 1 supplement see all Download asset Open asset Co-expression between GCaMP6sterm and GAD67term in the two transgenic mouse lines.

( A ) Single optical section of an IC brain slice from a GP4.3term mouse immunolabeled for GAD67term (magenta) and GCaMP6sterm (green). ( B ) Distribution of GCaMP+ and GAD67term+ cells within the 40 µm brain slice in A , color-coded by their immunoreactivity to GFP and GAD67term antibodies. GP+/−: GCaMP-positive/negative. ( C ) Enlarged image from A (small square), showing different combinations of immunoreactivity: GCaMP (green), GAD67term (magenta) and NeuN (blue). Arrowheads point at two GP−GAD67term+ cells. Due to optical sectioning only a subset of cells marked in B are visible. ( D ) Percentage of GCaMP+ cells showing immunoreactivity for GAD67term antibodies (error bars: s.e.m.; GP4.3term: n = 3 slices from three animals; Gad2;Ai96: n = 4 slices from three animals) ( E–G ) Enlarged image from large square in A showing two GAD67-dense modulesterm marked by dashed lines. GP+ cells in GP4.3term were concentrated at the borderterm of these modulesterm. ( H–I ) Same as A and B, but from a Gad2;Ai96 mouse. ( J–K ) Enlarged region from H (square). Arrowheads point at two GP−GAD67term+ cells. ( L–O ) Examples of GP+GAD67term+ cells from G showing images from GAD67term and GCaMP channels separately.

https://doi.org/10.7554/eLife.49091.002 Figure 1—source data 1 CellCounter source data XML files generated by Cell counter plug-in in FIJI containing the actual counted datapoints of each cell type, with text files explaning the different cell types being counted.

https://doi.org/10.7554/eLife.49091.004 Download elife-49091-fig1-data1-v2.zip In contrast, we detected GAD67term immunoreactivity in >93% (1702/1828) of GCaMP-positive neurons in the Gad2;Ai96 mice ( Figure 1D,H–O ). Not all GAD67-positive cells in this mouse line were labeled by GCaMP6sterm (e.g. arrowheads in Figure 1J ).

In addition to GAD67term, the calcium buffer parvalbumin (PV) is another marker for neurochemical modulesterm in the rat ( Chernock et al., 2004 ), while the calcium buffer calretinin (CR) shows a complementary expression (i.e. in the extramodular region) in early postnatal and juvenile mice ( Dillingham et al., 2017 ). To get a better idea of the relative contribution of modular and extramodular regions to GCaMP6term responses, we investigated the co-expression of GCaMP6term with PV or CR in the two transgenic lines ( Figure 1—figure supplement 1 ). We found that a large majority (94%) of GCaMP+ cells in GP4.3term did not show strong immunoreactivity for either marker (CR++: 2.2%; PV++: 2.9%; PV++CR++: 0.9%), whereas in the Gad2;Ai96 line a larger fraction of GCaMP+ cells were positive for CR or PV (CR++: 17%; PV++: 22%; PV++CR++: 7%; Figure 1—figure supplement 1G ). On the other hand, GCaMP was expressed in 38% of CR++ cells and 70% of PV++ cells in the IC of Gad2;Ai96 mice, while a lower fraction of CR++ (9.1%) and PV++ (13.4%) cells were positive for GCaMP in GP4.3term mice ( Figure 1—figure supplement 1H,I ). At the single neuron level, the presence or absence of the two buffers was insufficient to indicate whether the neurons lay within a moduleterm. These results suggest that for both lines there is not a clear enrichment of GCaMP6term+ neurons within the neurochemical modulesterm.

Unanaesthetized, head-fixed mice with implanted cranial windows ( Figure 2A–B ) were imaged with two photon microscopy ( Figure 2C–D ) and subjected to 1 s pure tones of various frequencies and intensities ( Figure 2E ). Average fluorescenceterm·var of regions-of-interest (ROIs) encompassing the cell body were analyzed, after subtracting the fluorescent change of a background region surrounding the cell body ( Figure 2D ). The use of longer stimuli allowed a detailed characterization of the kinetics of the fluorescence change (ΔF GCaMP ). Importantly, we observed both increases, which were either transient or sustainedterm, and decreases in F GCaMP during the presentation of stimuli, and some cells showed a sharp increase in F GCaMP directly after the cessation of the sound ( Figure 2E ). The different fluorescence responses were classified as excitation, inhibitoryterm and offsetterm, respectively (see Materials and methods, Figure 3A–D ). The excitatory responses were further divided into onsetterm and sustainedterm classes based on the kinetics of the fluorescence change ( Figure 3A,B , Figure 3—figure supplement 1 ). The decrease in fluorescence upon sound stimulation was likely due to sound-evoked inhibition of spontaneous firing in these cells. Some cells showed a mixture of response kinetics, some even to the same stimulus. Particularly common was the combination of inhibitoryterm and offsetterm responses (e.g. Figure 3E,M ). Another common combination were onset-offset cells in which a lower frequencyterm elicited an onsetterm/sustainedterm response, while a slightly higher frequencyterm elicited an offsetterm response (e.g. Figure 3I ). Inhibitoryterm and offsetterm responses were not reported in earlier imagingterm experiments performed in anesthetizedterm mice ( Ito et al., 2014 ; Barnstedt et al., 2015 ); their use of shorter stimuli did not allow a distinction between onsetterm and sustainedterm responses. A great variety of frequencyterm response areas (FRAs) was observed ( Figure 3F–M ), with some cells showing responses to tones as high as 64 kHz, the highest frequencyterm presented in this study (e.g. Figure 3G ).

Figure 2 with 1 supplement see all Download asset Open asset Calcium imagingterm of dorsal inferior colliculus in awaketerm mice.

( A ) Illustration of the cranial window construct imaged with a numerical aperture (NA) 0.95 water-immersion objective. ( B ) Top-down view of cranial window, showing optically exposed inferior colliculus (IC), superior colliculus (SC), cerebral cortex (cortex) and cerebellum (Cb). ( C ) Averaged GCaMP6sterm fluorescence in a 256 × 128 μm area, showing regions-of-interest (ROIs; dotted lines) defined around neuronal somata. ( D ) Enlarged view from C, showing pixels included in an ROI (green overlay) and a surrounding 2 μm wide background region (magenta overlay). Pixels belonging to other ROIs were excluded from the background region. ( E ) Background-subtracted fluorescence over time of the ROIs labeled a,b,c in C. Tones of 1 s duration with different frequencies and intensities were played, evoking different responses in IC neurons. The same sound (shaded area) evoked an inhibitoryterm response in ROI a, an offsetterm response in ROI b and a sustainedterm excitatory response in ROI c.

https://doi.org/10.7554/eLife.49091.005 Figure 3 with 2 supplements see all Download asset Open asset Different sound evoked responses and frequencyterm response areas of representative example cells.

( A ) An onsetterm fluorescence response to a 1 s pure tone. Gray vertical lines indicate onsetterm and offsetterm of sound stimulus. Colored and gray traces are average and individual trial fluorescence changes, respectively, normalized to a one-second baseline immediately before the stimulus onsetterm (ΔF/F b ). ( B ) A sustainedterm fluorescence response. ( C ) An inhibitoryterm response. ( D ) An offsetterm response. ( E ) A mixed inhibitoryterm and offsetterm response. Example FRAs from GP4.3term ( F–I ) and Gad2;Ai96 ( J–M ) mice. Each subplot shows the average ΔF/F b to a stimulus of the specified frequencyterm and intensity. Background color shows average Pearson’s correlation among repetitions, indicating consistency of response ( Geis et al., 2011 ). Black squares mark significant correlation from bootstrapterm·stat analysis. Cells in ( G ) and ( J ) are examples of cells with an onsetterm FRA; cells in ( F ) and ( K ) showed a sustainedterm FRA; cells in ( H ) and ( L ) were inhibited by sound; cells in ( I ) and ( M ) showed a mixture of different response classes. ( I ) A typical onset-offset cell with frequency-dependent responses: onsetterm fluorescence responses to 2.5 kHz tones and offsetterm fluorescent responses to 3.2 and 4 kHz tones. ( M ) A cell showing intensity-dependent responses: at 12.7 kHz, low intensity tones evoked a decrease in fluorescence (inhibited) while tones at 80 dB elicited an offsetterm response. Tones at 60–70 dB elicited a mixture of inhibition and offsetterm responses. Vertical scale bars in ( F–I ) indicates 1 F b .

https://doi.org/10.7554/eLife.49091.007 Figure 3—source data 1 Fluorescence kinetics source data CSV file containing fluorescence kinetics of ROIs, genotype of animal and type of FRA.

https://doi.org/10.7554/eLife.49091.010 Download elife-49091-fig3-data1-v2.zip In GP4.3term mice, 64% of the cells (696 out of 1090) cells showed detectable fluorescence changes in response to 1 s pure tone stimuli. We classified the responses and the overall FRA of a cell based on the criteria described in the Materials and methods. Among the responsive cells, 30% (210 cells) showed excitatory FRAs (e.g. Figure 3—figure supplement 2 ), with fluorescence increasing during sound presentation; while 13% (89 cells) showed offsetterm FRAs, with fluorescence increasing after sound presentation. Another 30% (207 cells) showed inhibitoryterm FRAs, with fluorescence decreasing during sound. The FRAs of the remaining 27% (190 cells) showed mixtures of these response categories. The proportion of different FRA classes are summarized in Figure 4A . The proportion of cells showing sound-evoked inhibition was clearly higher than the 2–23% reported for anesthetizedterm C57BL/6 mice in Willott et al. (1988a) .

Figure 4 Download asset Open asset Proportion of response classes and relationship with cell size.

( A–B ) Proportions of response classes in GP4.3term ( A ) and GAD2;Ai96 animals ( B ). ( C ) Bee swarm plot and mean ±s.d. for cell size for ROIs of different non-mixed response classes, separated by genotypes, measured as the size of the ROI ( Area ) in imagingterm experiments. Estimated diameters (d) were calculated by assuming a circular shape (i.e. d = 2 A r e a / π ). Cells imaged in Gad2;Ai96 mice were on average larger than those in GP4.3term mice.

https://doi.org/10.7554/eLife.49091.011 Figure 4—source data 1 IC ROI Area source data CSV file containing fluorescence area and estimated diameter of ROI, genotype of animal and type of FRA.

https://doi.org/10.7554/eLife.49091.012 Download elife-49091-fig4-data1-v2.zip In Gad2;Ai96 mice 73% (247 out of 342 cells) of GCaMP6s-positive IC neurons showed consistent fluorescence responses to 1 s pure tone stimuli. Among the responsive cells, 46% (115 cells) showed excitatory FRAs. Four percent (11 cells) showed offsetterm FRAs. Another 26% (65 cells) showed inhibitoryterm FRAs. The remaining 23% (56 cells) showed mixtures of the three response categories. The proportion of different FRA classes in Gad2;Ai96 mice are summarized in Figure 4B ; it was similar to that of GP4.3term mice, but with a somewhat smaller fraction of offsetterm and a larger fraction of excitatory FRAs.

GABAergicterm cells had a larger soma size, as reported previously (cat: Oliver et al., 1994 ; rat: Merchán et al., 2005 ). The estimated diameters for Gad2;Ai96 and GP4.3term cells, defined as 4/π times the square root of the ROI area in imagingterm experiments, were 21.9 ± 4.9 µm (mean ±s.d.) and 15.9 ± 2.6 µm, respectively ( Figure 4C , p<0.001 Wilcoxon Rank Testterm·stat). Within each genotype, soma size did not differ significantly among cells with different FRA classes. For GP4.3term: onsetterm cells 12.3 ± 2.6 µm, sustainedterm 12.5 ± 2.0 µm, inhibited 13.0 ± 1.8 µm, offsetterm 12.3 ± 2.0 µm (p=0.112, Kruskal-Wallis Rank testterm·stat). For Gad2;Ai96: onsetterm cells 16.6 ± 3.4 µm, sustainedterm 17.4 ± 3.6 µm, inhibited 18.1 ± 3.3 µm, offsetterm 15.6 ± 3.1 µm ( Figure 4C ; p=0.033, Kruskal-Wallis Rank testterm·stat, followed by Dunn’s [Dunn-Holland-Wolfe] testterm·stat where none of the comparisons reached critical value; only cells with non-mixed FRAs were compared because of the heterogeneity and small sample size of the different mixed response classes).

The temporal kinetics of the F GCaMP response of each cell were assessed by averaging the fluorescence change across all stimuli that showed a significant response. Single exponential functions were fit to the onsetterm (0–1 s re stimulus onsetterm) and the offsetterm/decay (0.5–4 s re stimulus offsetterm) periods ( Figure 3—figure supplement 1A,B ). Time constants were restricted to be positive. Due to the limited stimulus duration, any fit resulting in an onsetterm time constant (τ onsetterm ) greater than 1000 ms to an increase in fluorescence was considered sustainedterm activity and these fit constants were not used for averaging. For excitatory responses (onsetterm, sustainedterm and offsetterm), a time constant of around 1 s ( Figure 3—figure supplement 1D ) was found for the decay period, similar to the decay time constant reported previously for GCaMP6sterm ( Chen et al., 2013 ).

To relate the different fluorescence responses to spiking patterns, which are highly heterogeneous within the IC (e.g. Willott et al., 1988a ; Willott et al., 1988b ; Tan and BorstpersName, 2007 ), we combined Ca 2+ imagingterm with in vivo juxtacellularterm recordings in awaketerm mice. We recorded from neurons showing onsetterm, sustainedterm and inhibitoryterm tone-evoked fluorescence responses. For fluorescence responses that we classified as onsetterm, electrophysiological recordings showed that this class can represent a cell whose firing rate quickly adapted during our one-second long stimuli (example in Figure 5A–C,D left). We observed sustainedterm fluorescence responses that corresponded to sustainedterm firing ( Figure 5D middle) with different amount of adaptation. Inhibitoryterm responses corresponded to cells that reduced their spontaneous firing upon sound stimulation ( Figure 5D right).

Figure 5 with 3 supplements see all Download asset Open asset Relationship between GCaMP6sterm fluorescence and spikes in IC neurons.

( A ) Imagingterm of a GCaMP6sterm+ cell (green) in an awaketerm GP4.3term animal with simultaneous juxtacellularterm recording with a pipette filled with Alexa 594 (red). ( B ) Spiking pattern (upper) and fluorescence (lower) of the example cell can be well related by a linear convolution of spike rate with a linear ramp, exponential decay kernel (model: green). Fit parameters: F 0 = 28.8 a.u.; ΔF 1AP = 10.2 a.u.; t rise = 532 ms; τ decay = 859 ms. Numbers above bursts indicate number of spikes, and asterisks (*) mark single spikes. ( C ) Frequencyterm tuning of the cell. Peristimulus time histogram (PSTH; upper, 50 ms bins, 10 repetitions) and mean fluorescence change of the cell in response to 1 s tone bursts. ( D ) Raster plots, PSTHs and fluorescence responses (mean: black; individual: gray) of an onsetterm cell (same example as A-C), a sustainedterm cell and an inhibited cell. Due to their rarity, we have not obtained a simultaneous recording for offsetterm cells. ( E ) Relation between normalized single action potential amplitude (F 1AP /F 0 ) and decay time constant (τ decay ). ( F ) Relation between rise time (zero-to-peak; t rise ) and τ decay . Color in E and F indicate response class (red: inhibited; dark green: onsetterm; light green: sustainedterm; black: no tone-evoked response) of the cell.

https://doi.org/10.7554/eLife.49091.013 Figure 5—source data 1 Ground-truth model fitting source data CSV file containing model parameters from ground-truth data fitting and the variance explainedterm·stat, genotype of animal and type of FRA.

https://doi.org/10.7554/eLife.49091.017 Download elife-49091-fig5-data1-v2.zip We further characterized the relationship between fluorescence responses and firing patterns by fitting a model to our data set ( Figure 5E,F , Figure 5—figure supplements 1 – 3 ; see Materials and methods for equations). We found that on average, an action potential led to a median increase of 0.35 (GP4.3term; n = 5 cells) or 0.14 (Gad2;Ai96; n = 12 cells) times the minimal fluorescence (F 0 ), with a median zero-to-peak rise time of 480 ms (GP4.3term) or 560 ms (Gad2;Ai96) and a median decay time constant of 1.04 s (GP4.3term) or 1.36 s (Gad2;Ai96). The model could explain between 50% and 95% of the varianceterm in the fluorescence (median: 79%; average ±s.d.: 77 ± 13%).

The widespread and homogeneous expression of GCaMP6sterm in the IC of the transgenic mice allowed a good overview of its functional organization. We aligned the position of the cells from multiple animals (GP4.3term: n = 7 mice; Gad2;Ai96: n = 6 mice) by anatomical landmarks (midline, anterior and posterior extent of the exposed IC, lateral extent of the exposed IC), and plotted the cells on this common anatomical coordinate system ( Figure 6A ; Figure 6—video 1 ).

Figure 6 with 9 supplements see all Download asset Open asset Tonotopicterm organization.

( A ) Combined spatial distribution of characteristic frequencies (CFsterm) in the two transgenic lines, aligned to the same top-down image of an exposed left IC. Symbol size represents the size of the ROI, while colors indicate different CFsterm. Cells from Gad2;Ai96 mice were marked by diamonds. For GP4.3term, the shape of the symbol represents ROIs from C57BL/6J (circles) or B6CBAF1 (squares) background. To capture a direction of tonotopy, CFterm was fitted with a 4 th -order polynomialterm r = x cos ⁡θ + y sin⁡θ where r is a presumed direction of tonotopy at an angle θ (i.e. r = xcosθ+ysinθ), with the origin being the contact point between superior and inferior colliculi at the midline. The best fit yielded an angle θ of 50° from the medial-lateral axis. Contour lines indicate the predicted CFterm of the fit. ( B ) Geometric mean (open circles) and probability distribution (background shading) of CFterm along the 50° line, in 75 μm bins. Black trace shows the fitted 4 th -order polynomialterm. ( C ) Geometric mean of CFterm along the 50° line for the GP4.3term (black) and Gad2-cre*Ai96 (gray) lines. Size of symbol represent number of cells in each 75 μm bin. ( D ) Geometric mean of CFterm for cells of onsetterm, sustainedterm, inhibited or offsetterm FRAs. ( E ) Depth dependence of CFsterm along the 50° line. ( F ) Histogram of CFterm grouped according to depth from pia surface. Note that low CFterm cells are present at all imagingterm depths.

https://doi.org/10.7554/eLife.49091.018 Figure 6—source data 1 IC CFterm Distribution source data CSV file containing 3D coordinate of ROIs, projected distance of ROIs, genotype of animal and type of FRA.

Source code for fit function used for fitting the spatial distribution.

https://doi.org/10.7554/eLife.49091.027 Download elife-49091-fig6-data1-v2.zip Interestingly, we observed a central strip running in the caudomedial-rostrolateral orientation of cells responding to lower frequencies, while CFterm progressively increased in both the caudolateral and the rostromedial direction. We tried to estimate the orientation of the spatial organization by projecting the x,y-coordinates of all neurons onto an axis with a parametrized angle θ, while simultaneously fitting the log-transformed CFterm using a polynomialterm model (see Materials and methods). We used a polynomialterm model fit as a way to extract any general direction along which CFsterm may diverge, without imposing any presumption about the spatial CFterm dependence. We found that a fourth order polynomialterm captured the varianceterm maximally; further increasing its order did not lead to better fits. The results of the fit are presented as contour lines in Figure 6A , with the best orientation (θ) 50° from the medial-lateral (x) axis. A plot along this orientation shows a high fraction of low CFterm (~4 kHz) neurons near the 625 μm position, with the mode going towards ~20 kHz at the 1300 μm end ( Figure 6B ). The increase in CFsterm on the rostromedial side was not as pronounced, likely due to the low number of neurons sampled in this region. The solid line in Figure 6B shows the best polynomialterm fit, which explained around 13% of the varianceterm in CFsterm. This tonotopicterm organization can also be appreciated in individual animals in which a wide extent of the dorsal IC was imaged ( Figure 6—figure supplements 1 – 3 ). Additional examples of the tonotopicterm organization in individual animals are shown in Figure 6—figure supplements 4 – 6 . A similar spatial distribution of CFsterm was observed for GABAergicterm and glutamatergicterm neurons ( Figure 6C ) and for cells showing different response classes ( Figure 6D ).

Based on a clustering analysis, Barnstedt et al. (2015) suggested that the central strip of low frequencyterm neurons were from the most dorsal end of the central nucleus, and we did observe a small but significant correlation between depth and log(CFterm) ( Figure 6—figure supplement 7 ; correlation coefficientterm·stat = −0.22; n = 799; p=3 × 10 −10 ). However, a plot of CFterm along the best orientation from the polynomialterm fit as a function of depth illustrates that most cells were located within 100 µm from the surface, and that the low frequencyterm neurons were also among the most superficial cells ( Figure 6E ). When we limited the fit to neurons < 50 μm from the pia surface, the same tonotopicterm pattern appeared ( Figure 6—figure supplement 8 ). There was an over-representation of low CFterm neurons in the deepest regions (121–160 μm deep, Figure 6E,F ). We attribute this to a sampling bias in which the low frequencyterm region coincided with the center of the cranial window, where it was possible to image somewhat deeper than towards the edges ( Figure 6E ). Objects in the center of the window profit from utilization of the full NA for focusing excitation light, which is especially critical for two-photon excitation, and in the center both excitation and fluorescence emission light is least obstructed ( Figure 2A ). Restricting the analysis to cells in the central strip (525–725 μm of projected area) reduced the correlation coefficientterm·stat for the relation between depth and log(CFterm), but it remained significant ( Figure 6—figure supplement 7 ; correlation coefficientterm·stat = −0.17, n = 295; p=0.003), hinting at differences between deeper and the most superficial cells. While we do not exclude the possibility of imagingterm into the central nucleus of the IC, we believe the observed tonotopy to be a good representation of the IC shell region because all CFsterm were represented among the most superficial neurons ( Figure 6E,F ).

We next asked whether there was any obvious spatial organization of the different response classes. Figure 7A shows the proportion of different response classes along our presumed tonotopicterm axis, which looked rather homogenous, without any obvious difference between cells rostromedial and caudolateral to the CFterm minimum. The same pattern holds for the orthogonal direction ( Figure 7B ).

Figure 7 Download asset Open asset Spatial organization of response classes.

Similar proportions of response classes along ( A ) the presumed tonotopicterm axis (bin size 50 μm) and ( B ) the direction orthogonal to the axis (bin size 100 μm). Zero position was taken as the contact point between superior and inferior colliculi at the midline. Vertical dashed line in ( A ) denotes the minimal CFterm position based on our polynomialterm fit (625 μm).

https://doi.org/10.7554/eLife.49091.029 Figure 7—source data 1 IC Response Distribution source data CSV file containing 3D coordinate of ROIs, projected distance of ROIs, genotype of animal and type of FRA.

https://doi.org/10.7554/eLife.49091.030 Download elife-49091-fig7-data1-v2.zip Interestingly, we observed cells that showed fluorescence transients in the absence of sound presentation ( Figure 8A,B ). Numerous studies have shown both ascending and descending somatosensoryterm projections to the IC ( Aitkin et al., 1981 ; Künzle, 1998 ; Jain and Shore, 2006 ; Zhou and Shore, 2006 ; Lesicko et al., 2016 ; Patel et al., 2017 ), as well as from nuclei that are upstream from IC such as the dorsal cochlear nucleus, which also receive somatosensoryterm inputs ( Wu et al., 2014 ). In addition, the IC receives inputs from the motor cortex ( Cooper and Young, 1976 ; Olthof et al., 2019 ). This prompted us to investigate whether these ‘spontaneous’ activities could be attributed to non-auditory inputs. Our recordings were performed while the animal was passively awaketerm, which allowed us to observe and correlate the voluntary movementterm of the animal to simultaneously recorded calcium transients.

Figure 8 with 1 supplement see all Download asset Open asset Cells with motion-related responses.

( A ) Two example cells that were spontaneously active in the absence of sound presentation. Calcium transients occurred when the animal was moving its paws or showing facial movementterm (e.g. whisking). These transients decayed much more slowly than motion artefacts (image shifts, bottom trace; see also Figure 8—figure supplement 1 ). ( B ) Facial movementsterm were quantified from a simultaneously recorded video of the animal by calculating the root-mean-square of the changes in pixel intensity between consecutive frames of a rectangular area at the whisker pad. ( C–D ) Cells showing motion-related activity were predominently located in the caudolateral part of the dorsal IC. Broken line indicates the minimum CFterm position obtained from the polynomialterm fit. ( F ) The motion-related calcium transients were unlikely to be caused by sounds, as the two cells showed either an inhibitoryterm FRA (cell 1) or no clear tone-evoked response (cell 2).

https://doi.org/10.7554/eLife.49091.031 Figure 8—source data 1 IC Movementterm cells source data CSV file containing 3D coordinate of ROIs, projected distance of ROIs, genotype of animal, type of FRA and parameters related to movement-related response.

https://doi.org/10.7554/eLife.49091.033 Download elife-49091-fig8-data1-v2.zip We found that the onsetterm of many of these spontaneous transients coincided with movementterm events of the animal (paw and facial movementsterm in Figure 8A ). By correlating movementterm and fluorescence, we detected 165 (out of 1359) cells that showed a positive correlationterm·stat ( r > 0.25) with facial movementsterm during the spontaneous recording period. To exclude potential false-positive detection due to motion artefacts (i.e. cells moving into and out of focus), we excluded cells with fluorescence transients that did not show the typical ~1 s exponential decay kinetics, which last much longer than the brief image shifts that could accompany movementterm events (image shifts in Figure 8A , Figure 8—figure supplement 1 ). Since animal movementterm inevitably produces sound that may activate the IC neurons, leading to an apparent movementterm sensitivity, we also excluded the cells that showed excitatory or offsetterm responses in their FRA. In the end, 41 cells showed spontaneous calcium transients that correlated with animal movementterm and that could not be explained by their FRA, which was either inhibited-type or showed no clear pure tone evoked responses (example FRAs in Figure 8F ). These cells seemed to be enriched at the caudolateral side of the dorsal IC ( Figure 8C–D ). Four of the 41 cells were found in the Gad2;Ai96 line, in agreement with a recent report that inputs from motor or somatosensoryterm cortex can directly target GABAergicterm cells ( Olthof et al., 2019 ), and the remainder in the GP4.3term line, making them 1% of GABAergicterm and 4% of investigated glutamatergicterm cells, respectively.

Figure 9A and E show two relatively superficial brain sections (within 80 μm and 120 μm from dorsal surface, respectively) from one Gad2;Ai96 and one GP4.3term animal stained for GAD67term after two photon imagingterm. We overlaid the line representing the neurons with the lowest CFterm and compared its location with the borderterm of LCICterm and DCICterm traced from the latest Allen Reference Atlasterm (CCFv3) and from the classical reference atlasterm by Paxinos and Franklin (2001) . The minimum frequencyterm line aligns with the demarcation from the Allen Reference Atlasterm, while that by Paxinos and Franklin lays in the orthogonal direction.

Figure 9 with 7 supplements see all Download asset Open asset Comparison of tonotopicterm organization with histological data and literature.

( A ) Epifluorescence image of the IC in a horizontal brain section stained for GAD67term. This brain slice was from a Gad2;Ai96 mouse after two-photon imagingterm. Black straight line indicates the minimum frequencyterm location derived from fitting two-photon imagingterm data. Dashed curve represents the demarcation between the dorsal and the lateral (external) cortices traced from version 3 of the Allen Reference Atlasterm. Circles connected with solid and broken lines mark the demarcation at the dorsal brain surface traced from the atlasterm by Paxinos and Franklin (2001) . The rostral and caudal end of this demarcation are marked by a dashed line because at the indicated positions on the anterior-posterior axis the whole structure was labeled as LCICterm or DCICterm, respectively. Modulesterm with dense GAD67term staining, considered to be a hallmark for the LCICterm, were observed both medially and laterally from each of the three demarcations (arrowheads). We observed a region in the center of the IC whose GAD67term staining density was at least as strong as in the neurochemical modulesterm (square labeled B). ( B–D ) Single confocal optical sections of GAD67term (black) and GCaMP6sterm (green) staining in different areas of the brain slice corresponding to the yellow squares in A . ( B ) Dense GAD67term area in the central region of the IC (<80 µm from dorsal surface). ( C ) An area showing a GAD67-dense moduleterm ( m ) in the center, cut transversely and surrounded by extramodular region (e) with sparse GAD67term staining. (D1-2) Optical sections at different focal depths of an area showing another GAD67term moduleterm from the same slice (m), cut tangentially. Arrow in D2 indicates a cell showing motion-related responses. ( E ) Similar to A but from an imaged GP4.3term mouse. ( F ) Single confocal section for GCaMP6sterm (green) and GAD67term (black) staining in region marked in E. Arrow marks another cell with motion-related response. Scale bars, A,E: 500 μm; B-D,F: 50 μm.

https://doi.org/10.7554/eLife.49091.034 Neurochemical modulesterm with a high density of GAD67-positive terminals have been reported as a hallmark for the LCICterm ( Chernock et al., 2004 ; Lesicko et al., 2016 ; Dillingham et al., 2017 ). We indeed found modulesterm with higher density of GAD67term terminals in our animals as well (arrowheads in Figure 9A,E,a clear example in Figure 9C ). In the most superficial sections, these modulesterm were not as well defined, but they were contiguous to the more densely stained modulesterm in deeper sections ( Figure 9—figure supplements 1 and 4 ; 3D reconstruction in Figure 9—video 1 ), and the superficial modulesterm also had reduced calretinin staining ( Figure 9—figure supplements 2 and 5 ), in line with previous findings ( Dillingham et al., 2017 ). These modulesterm are the predominant target of the somatosensoryterm projections from the cerebral cortex as well as other brainstem areas ( Lesicko et al., 2016 ). We also observed a central strip of dense GABAergicterm staining (enlarged in Figure 9B ), which was not contiguous with the modulesterm ( Figure 9—figure supplements 1 and 4 ). GCaMP expression in these two example animals are presented for comparison in Figure 9—figure supplements 3 and 6 .

How do motion-sensitive cells associate with the GAD67-dense modulesterm? Figure 9D2 and F show two motion-sensitive neurons retrieved in histology (cells 3 and 4, marked by arrows), both of which resided in close proximity to a GAD67-dense moduleterm. We observed that although the somata of both cells seemed to reside in the extramodular regions, both possessed dendritesterm that extended into a GAD67-dense moduleterm ( Figure 10 ). Figure 10A and B show a dendritic extension of cell 3. For cell 4, a pixel-wise correlation of the in vivo somatic fluorescence change ( Junek et al., 2009 ) nicely revealed its dendritic arbor at the same focal plane ( Figure 10C,E ). Aligning this to post hoc histological staining ( Figure 10D ), we can demonstrate that cell four has dendritic branches extending both inside and outside of a GAD67term moduleterm ( Figure 10F ). We suggest that this may be a functional connection scheme for extramodular neurons to enable them to integrate somatosensoryterm or motor with auditory inputs to the IC ( Figure 10G ).

Figure 10 Download asset Open asset Example motion-sensitive cells with dendritic arbor extending into GAD67-dense modulesterm.

( A ) Maximum projection of GCaMP staining showing dendritic arbor of cell three in Figure 9D2 , overlaid with a single optical section of GAD67term staining showing a moduleterm (m; at same focus as Figure 9D2 ). While its soma is extramodular ( e ), at least one branch of its dendriteterm (arrowheads) appeared to extend into the modular region. ( B ) A single confocal section of cell three showing the root (arrow) of the dendriteterm labeled in A (small arrowheads). ( C ) Averaged GCaMP6sterm fluorescence for the in vivo session imagingterm area in Figure 9F , revealing a dendriteterm of cell four extending into the modular region. ( D ) Single confocal section of a fixed brain slice stained for GCaMP6sterm. ( E ) Dendritic arbor of cell four was revealed using pixel-wise correlation to the average somatic fluorescence ( Junek et al., 2009 ), showing extension into the modular region (arrowheads). ( F ) Background subtracted pixel correlation from E (green) overlaid onto GAD67term staining (black). ( G ) Schematic representation of hypothesis that integration of auditory and non-auditory inputs by multisensory neurons in the IC can be based on extension of their dendritesterm into both modular and extramodular regions. Scale bars: A: 20 μm; B: 10 μm; C-F: 50 μm.

https://doi.org/10.7554/eLife.49091.042 We investigated the functional organization of the dorsal IC in awaketerm mice at the single neuron level. We found that the dorsal IC is tonotopically organized, with isofrequency bands running in a rostrolateral-caudomedial orientation with frequencyterm tuning varying along the caudolateral-rostromedial direction. The lowest CFterm band was found in the middle, dividing the dorsal IC into two reversed tonotopicterm gradients. In the caudolateral part, but not in the rostromedial part, neurons that were sensitive to whisker or other movementsterm were found, which was in agreement with the view that the caudolateral and rostromedial part corresponded to the LCICterm and DCICterm, respectively. We observed four different types of firing patterns in response to tones, but other than the tonotopical organization, no obvious topographical organization was observed for the firing patterns. GABAergicterm neurons were on average somewhat larger, but otherwise there were not clear differences with glutamatergicterm neurons in spatial organization or firing patterns. Our experiments thus provide a functional definition of the major organization principles of the dorsal IC in adult mice.

Because of the prominence of GABAergicterm neurons and their substantial contribution to ascending projections ( Schofield and Beebe, 2019 ), we compared the responses and functional organization of GABAergicterm and glutamatergicterm neurons in the dorsal IC using in vivo two-photon calcium imagingterm. We confirmed that virtually all neurons expressing GCaMP6sterm in the GP4.3term line were glutamatergicterm, but not all glutamatergicterm neurons were labeled. There may have been a preponderance of labeled cells around the modulesterm in the LCICterm ( Figure 1D ), but a systematic screen of markers would be needed to test for a selective enrichment of glutamatergicterm subtypes in the GP4.3term line. The large majority of GCaMP6s-positive neurons in the IC of mice from the Gad2;Ai96 line expressed GAD67term, in agreement with findings in a related mouse line ( Gay et al., 2018 ). In our hands, these two transgenic lines had the advantage that the kinetics of the responses were relatively homogeneous and well approximated by a linear model ( Figure 5B ), suggesting that the expression levels, which are a major determinant of the Ca 2+ kinetics (e.g. Éltes et al., 2019 ), were similar across cells. Moreover, in contrast to pilot experiments in which we expressed GCaMP6term using adeno-associated viruses, we found little evidence for toxicity. The more sparse expression facilitated the isolation of the responses of individual neurons.

A substantial fraction of cells did not respond to tones. Low probability responses may have been below detection, since the juxtacellularterm recordings indicated that single APs could not always be detected. Some cells may respond preferentially to more complex sound stimuli, as previously found for neurons in the shell region ( Ehret and Moffat, 1985 ; Aitkin et al., 1994 ). As discussed below, some cells may prefer somatosensoryterm or motor stimuli instead of sound stimuli.

In both transgenic lines, we observed four different tone-evoked fluorescence response patterns in awaketerm mice: onsetterm, sustainedterm, offsetterm and inhibitoryterm. Our simultaneous juxtacellularterm recordings showed corresponding patterns. These types were typically also observed in several earlier electrophysiological studies (e.g. Willott et al., 1988a ; Willott et al., 1988b ; Jain and Shore, 2006 ; Xie et al., 2007 ). Apart from a possibly lower fraction of GABAergicterm neurons with pure offsetterm responses ( Figure 4B ), our results are thus in line with a recent study that showed that GABAergicterm and glutamatergicterm IC neurons have similar response properties throughout the IC ( Ono et al., 2017 ).

The prominence of inhibitoryterm responses in the IC (~44% of sound-responsive neurons) in both transgenic lines was a striking finding in our recordings. An important factor contributing to their prominence is probably that our experiments were done in awaketerm animals, as a recent single unit recording study showed the presence of inhibitoryterm responses as well as higher spontaneous spike rates in IC neurons of awaketerm mice compared to mice under urethane anesthesia ( Duque and Malmierca, 2015 ), and synaptic inhibition has also been shown to be prominently present in whole-cell recordings in awaketerm bats ( Xie et al., 2007 ).

Offsetterm responses can be found throughout the auditory system including the IC, and they may have an important role in perceptual grouping or in duration discrimination ( Kopp-Scheinpflug et al., 2018 ). However, studies in the IC of anesthetizedterm mice, rats and chinchillas showed that offsetterm responses are generally restricted to cells showing band-pass duration tuning, which only responded to much shorter tones than the 1 s employed here ( Chen, 1998 ; Brand et al., 2000 ; Pérez-González et al., 2006 ). Another striking finding was therefore that we saw clear evidence for offsetterm responses in 3–11% of sound-responsive cells. A whole-cell study in the mouse IC showed that in most cases offsetterm responses are inherited from upstream, but that they may also be generated de novo as a rebound from inhibition ( Kasai et al., 2012 ). Similar to the inhibition class, we therefore suggest that the prominence of offsetterm responses may be related to the increased impact of synaptic inhibition in the IC of awaketerm animals. A study using communication calls suggests that offsetterm responses may be even more prominent following more complex sound stimuli, such as communication calls ( Akimov et al., 2017 ), possibly by a summation of inhibition at different frequencyterm bands ( Sanchez et al., 2008 ).

Following pooling of the data from several experiments, we observed a tonotopicterm gradient that ran along a gradient from caudolateral to rostromedial. The gradient reversed at the site where the CFsterm were the lowest. This reversal is in line with the banding patterns observed with epifluorescent calcium imagingterm in unanesthetized mice before and at hearing onsetterm; the pre-hearing spontaneous neural activities originate from the cochlea, thus regions activated synchronously likely receive input from the same tonotopicterm area ( Babola et al., 2018 ). In addition, they observed a double band pattern with higher frequencyterm stimulation in the juvenile (p15) mice. Interestingly, our data are also compatible with two earlier two-photon calcium imagingterm studies ( Ito et al., 2014 ; Barnstedt et al., 2015 ). Ito et al. (2014) reported gradients in the medial regions of the dorsal IC, which ran from lateral (low-frequency) to medial (high-frequency), whereas Barnstedt et al. (2015) reported gradients in a mediorostral to laterocaudal direction.

We found considerable variability in CFsterm within a band. Imprecisions in the alignment of imagingterm areas and variability between animals may have contributed to the variability, but substantial variability was also observed within a single animal, in line with previous results ( Ito et al., 2014 ; Barnstedt et al., 2015 ). Two-photon calcium imagingterm studies in the mouse auditory cortex have met with variable amount of microheterogeneityterm, apparently depending on layer, calcium dye, or the use of anesthetics ( Bandyopadhyay et al., 2010 ; Rothschild et al., 2010 ; Winkowski and Kanold, 2013 ; Issa et al., 2014 ; Kato et al., 2017 ; Tischbirek et al., 2019 ).

The four response types showed a similar tonotopicterm organization, but considerable microheterogeneityterm. This microheterogeneityterm was larger than in an earlier study in which bulk loading of an organic Ca indicator was used ( Ito et al., 2014 ), which may have made it more difficult to isolate responses from individual cells. Our results are in line with patch-clamp results showing considerable heterogeneity between adjacent cells within the dorsal IC, which extended to heterogeneity in their inputs ( Geis et al., 2011 ). The microheterogeneityterm was similar for GABAergicterm and glutamatergicterm neurons. Our results thus differ from auditory cortex, where response patterns are different and local microheterogeneityterm is much smaller for (parvalbumin-positive) GABAergicterm neurons than for glutamatergicterm neurons ( Maor et al., 2016 ; Liang et al., 2018 ; Liu et al., 2019 ). We conclude that despite the shared input and firing behavior during development ( Babola et al., 2018 ), functional heterogeneity dominates within bands in the dorsal IC of adult mice. Whereas some of the mechanisms that underlie the microheterogeneityterm within the auditory cortex are being elucidated ( Kato et al., 2017 ; Tao et al., 2017 ; Vasquez-Lopez et al., 2017 ), they remain to be explored for the dorsal IC.

We monitored spontaneous whisker and general body movementsterm, and used strict criteria to exclude movementterm artefacts. As we restricted the analysis to neurons that were not excited by tones, we consider it unlikely that the observed movement-related responses were caused by self-generated sounds. Despite these severe restrictions, we did find that a few percent of the cells were excited during whisker or body movementsterm, suggesting a substantial role for somatosensoryterm or motor inputs. Little is known about the functional characteristics of motor inputs that are not related to eye movementsterm ( Gruters and Groh, 2012 ). For somatosensoryterm inputs, the dominant effect appears to be inhibitoryterm and only a minority of cells have been shown to respond to unimodal tactile stimuli ( Aitkin et al., 1978 ; Aitkin et al., 1981 ; Zhou and Shore, 2006 ), which would not help detection based on our selection criteria. We did not further discriminate between different movementsterm as they tended to be heavily correlated. Moreover, it is known that neurons in the LCICterm have broad tuning for somatosensoryterm input ( Aitkin et al., 1981 ). Movement-sensitive neurons were not found in the high-frequency DCICterm regions, but only in the putative CNICterm region and the LCICterm.

A defining feature of the LCICterm is the presence of neurochemical modulesterm, which have been shown in many species, including rats ( Chernock et al., 2004 ; Choy Buentello et al., 2015 ), but also in both adult ( Choy Buentello et al., 2015 ; Lesicko et al., 2016 ; Patel et al., 2017 ) and developing mice ( Dillingham et al., 2017 ). While it is still unclear how neurons in these modulesterm and extramodular zones connect with each other, there is evidence that somatosensoryterm inputs project predominantly to the modulesterm, while auditory input projects to the extramodular region ( Lesicko et al., 2016 ). The main sources for somatosensoryterm input to the LCICterm are the spinal trigeminal nucleus, the dorsal column nuclei and the somatosensoryterm cortex (reviewed in Gruters and Groh, 2012 ). These inputs target the layer two modulesterm, which constitute only a small fraction of the LCICterm volume. Moreover, neurons in the modulesterm do not seem to target extramodular IC neurons ( Lesicko and LlanopersName, 2019 ). This raises the question how so many cells in the LCICterm can be sensitive to non-auditory inputs. We obtained anecdotal evidence that neurons at the borderterm of the modulesterm can extend dendritesterm into the modulesterm ( Figure 10A,F ), which would allow them to sample non-auditory inputs. Indeed, neurons in LCICterm can have extensive dendritic trees ( Smith, 1992 ), and Golgi stainings show that cells in layer 3 of LCICterm can send dendritesterm up to layer 1 ( Meininger et al., 1986 ; Malmierca et al., 2011 ). The CNICterm has few somatosensoryterm inputs, but at least half of the cells in CNICterm are affected by stimulation of the dorsal column nuclei ( Gruters and Groh, 2012 ). The CNICterm may get somatosensoryterm inputs indirectly via the dorsal cochlear nucleus, which is innervated by the spinal trigeminal nucleus and the dorsal column nuclei, or in the form of intracollicular input from the LCICterm. Direct stimulation of the different non-auditory inputs would be needed to obtain a better idea of their importance for the observed facial or body movement-related responses.

There is little agreement on the precise bordersterm of the different nuclei of the IC, and its parcellation has been different based on whether cell morphology, inputs, or physiological properties were chosen as the main classifier ( Oliver, 2005 ). Here we used physiological properties as the main criterionterm to look at the bordersterm between the DCICterm, LCICterm and CNICterm in the dorsal IC. Our findings suggest that the laterocaudal area with high frequencies is the dorsal edge of the LCICterm, whereas the mediorostral part of the dorsal IC belongs to the DCICterm. The tonotopicterm reversal would thus provide a functional demarcation between the dorsal and lateral cortices of the IC. Earlier tracing studies of intracollicular projections in the guinea pig ( Malmierca et al., 1995 ) and the rat ( Saldaña and Merchán, 1992 ), as well as ascending projections from the cochlear nucleus in the rat ( Malmierca et al., 2002 ), have shown interesting V-shaped arrangements in coronal sections, where the medial side corresponds to isofrequency laminae in CNICterm and DCICterm, while the lateral side corresponds to those in the LCICterm. These V-shaped axon terminal plexuses, if extended to the dorsal surface of the IC, provide an anatomical explanation for the observed tonotopicterm reversal. This is also in agreement with the latest anatomical framework published by the Allen Brain Institute ( Figure 9A ; Allen Mouse Common Coordinate Framework, 2015), previous imagingterm studies ( Ito et al., 2014 ; Barnstedt et al., 2015 ; Babola et al., 2018 ), the known somatosensoryterm inputs to the LCICterm, and both the descending and ascending inputs to the IC ( Aitkin et al., 1981 ; Künzle, 1998 ; Jain and Shore, 2006 ; Zhou and Shore, 2006 ; Lesicko et al., 2016 ; Patel et al., 2017 ). Surprisingly, we observed GAD67-dense modulesterm in both the medial and the lateral aspect of the IC (arrowheads Figure 9A,G ), that is within both LCICterm and DCICterm in either atlasterm. The medial modulesterm could not be imaged within this study, so their association with somatosensoryterm inputs is currently unclear.

The central strip with neurons tuned to low frequencies in between the LCICterm and the DCICterm may be the most dorsal extension of the dorsolateral low frequencyterm area of the CNICterm ( Stiebler and Ehret, 1985 ; Barnstedt et al., 2015 ). This strip contains the large density of GABAergicterm inputs ( Figure 9A,B ) that is characteristic of the CNICterm ( Choy Buentello et al., 2015 ). Lemniscal inputs are known to extend quite dorsally, almost up to the surface, and neurons with short latency sound responses have been found in the dorsal IC, although their exact location was not studied ( Geis and BorstpersName, 2013 ). The low tuning in the central strip extended close to the surface, but a more systematic study of their properties would be needed to be able to assign the most superficial layers to either the DCICterm or another region. From our data it thus appears that the three main areas of the IC, LCICterm, CNICterm, DCICterm, are readily accessible at the dorsal IC. Their accessibility for imagingterm studies will thus help to further delineate their functions and the role of their inputs in the future.

Key resources table Reagent type (species) or resource Designation Source or reference Identifiers Additional information Genetic reagent ( Mus musculus ) B6;129S6- Gt(ROSA)26Sor tm96(CAG-GCaMP6s)Hze /J The Jackson Laboratory; originally reported in Madisen et al. (2015) IMSR Cat# JAX:024106, RRID: IMSR_JAX:024106 Designated as ‘Ai96’ in this manuscript. Maintained in heterozygous state by backcrossing to C57BL/6J.

Genetic reagent ( Mus musculus ) STOCK Gad2 tm2(cre)Zjh /J The Jackson Laboratory; originally reported in Taniguchi et al. (2011) IMSR Cat# JAX:010802, RRID: IMSR_JAX:010802 Designated as ‘Gad2-IRES-Cre’ in this manuscript. Maintained in homozygous state after > 10 generations of backcrossing to C57BL/6J, and re-backcrossed to C57BL/6J every 4–5 generations.

Genetic reagent ( Mus musculus ) C57BL/6J-Tg(Thy1-GCaMP6s)GP4.3Dkim/J The Jackson Laboratory; originally reported in Dana et al. (2014) IMSR Cat# JAX:024275, RRID: IMSR_JAX:024275 Designated as ‘GP4.3term’ in this manuscript. Maintained in heterozygous state by backcrossing to C57BL/6J, or crossed with CBA/JRj to obtain mice with B6CBAF1/J background.

Strain, strain background ( Mus musculus ) JAX C57BL/6 J Charles Rivers Laboratories IMSR Cat# JAX:000664, RRID: IMSR_JAX:000664 Strain, strain background ( Mus musculus ) CBA/JRj Janvier Labs MGI Cat# 6157506, RRID: MGI:6157506 antibody chicken anti-GFP (Chicken polyclonal) Aves Aves Labs Cat# GFP-1020, RRID: AB_10000240 IF(1:1000) Antibody mouse anti-Gad67 (Mouse monoclonal) Millipore Millipore Cat# MAB5406, RRID: AB_2278725 IF(1:1000) Antibody rabbit anti-NeuN (Rabbit polyclonal) Millipore Millipore Cat# ABN78, RRID: AB_10807945 IF(1:1000) Antibody mouse anti-parvalbumin (Mouse monoclonal) Swant Swant Cat# 235, RRID: AB_10000343 IF(1:7000) Antibody rabbit anti-calretinin (Rabbit polyclonal) Swant Swant Cat# 7699/4, RRID: AB_2313763 IF(1:5000) Antibody Alexa Fluor 488-conjugated Donkey anti-chicken antibody (Donkey polyclonal) Jackson ImmunoResearch Labs Cat# 703-545-155, RRID: AB_2340375 IF(1:200) Antibody Alexa Fluor 594-conjugated Donkey anti-mouse antibody (Donkey polyclonal) Jackson ImmunoResearch Labs Cat# 715-585-150, RRID: AB_2340854 IF(1:200) Antibody Alexa Fluor 647-conjugated Donkey anti-rabbit antibody (Donkey polyclonal) Jackson ImmunoResearch Labs Cat# 711-605-152, RRID: AB_2492288 IF(1:200) Software, algorithm IGOR Pro Wavemetrics RRID: SCR_000325 Analysis of calcium imagingterm and electrophysiologyterm·mth data Software, algorithm pClamp Molecular Devices RRID: SCR_011323 Signal digitization. software, algorithm MATLAB MathWorks RRID: SCR_001622 Stimulus generation and presentation Software, algorithm LabView National Instruments RRID: SCR_014325 Control of microscope and other hardware Software, algorithm Fiji http://fiji.sc RRID: SCR_002285 Processing and analysis of images from immunohistochemistry Detailed two-photon imagingterm experiments were conducted on seven GP4.3term transgenic animals ( Dana et al., 2014 ) (three in C57BL/6J background and four in B6CBAF1/J background) and six F1 progeny between Gad2-IRES-cre ( Taniguchi et al., 2011 ), and Ai96 reporter line (B6;129S6- Gt(ROSA)26Sor tm96(CAG-GCaMP6s)Hze /J) ( Madisen et al., 2015 ). We will refer to the Gad2-IRES-Cre x Ai96 cross as Gad2;Ai96. Postnatal age at recordings ranged between 11–35 weeks (median: 19; Q1: 15; Q3: 23). Ground-truth juxtacellularterm recordings were performed on four GP4.3term and three Gad2;Ai96 animals. Immunohistochemistry for cell counting was performed on three GP4.3term and three Gad2;Ai96 animals.

GP4.3term animals were originally obtained from the Jackson Laboratory (C57BL/6J-Tg(Thy1-GCaMP6s)GP4.3Dkim/J; JAX stock #024275); they were maintained in a heterozygous state by backcrossing to C57BL/6J from Charles Rivers (JAX C57BL/6J). To create GP4.3term animals with B6CBAF1/J background, heterozygous GP4.3term in C57BL/6J background were crossed with CBA/JRj mice from Janvier. Gad2-IRES-Cre (originally STOCK Gad2 tm2(cre)Zjh /J, the Jackson Laboratory) was maintained in homozygous state after >10 generations of backcrossing to C57BL/6J, and re-backcrossed to C57BL/6J every 4–5 generations. Ai96 mice were obtained from Jackson Laboratory with already 3 generations of backcross to C57BL/6J (N3), and were subsequently maintained by backcrossing to C57BL/6J for 5–7 generations. All experiments complied with the ethical guidelines for laboratory animals within our institute and with European guidelines, and were approved by the animal ethical committee of the Erasmus MC.

Animals were anaesthetised through respiratory intake of isoflurane and maintained at surgical level of anaesthesia, assessed through the hind limb withdrawal reflex. A heating pad with rectal feedback probe (40-90-8C; FHC, Bowdoinham, ME, USA) was used to maintain body core temperature at 36–37°C. Eye ointment (Duratears; Alcon Nederland, Gorinchem, The Netherlands) was used to keep the eyes moist during surgery. A bolus of buprenorphine (0.05 mg/kg; Temgesic, Merck Sharp and Dohme, Inc, Kenilworth, NJ, USA) was injected subcutaneously at the beginning of surgery. The skin overlying the IC was incised. Lidocaine (Xylocaine 10%; AstraZeneca, Zoetermeer, The Netherlands) was applied before removing the periosteum and cleaning the skull. After etching the bone surface with phosphoric acid gel (Etch Rite; Pulpdent Corporation, Watertown, MA, USA), a titanium head plate was glued to the cleaned bone above the left IC using dental adhesive (OptiBond FL; Kerr Italia S.r.l., Scafati, SA, Italy) and further secured with dental composite (Charisma; Heraeus Kulzer GmbH, Hanau, Germany).

Through an opening in the head plate, a craniotomy of 3 mm diameter centered at one of the ICs was made by thinning and removing the skull bone. A cranial window, made by gluing a 3 mm cover slip (CS-3R-0; Warner Instrument Inc, Hamden, CT, USA) on a custom built, 500 µm thick steel ring with UV-cured optical adhesive (NOA68; Norland Products), was installed over the exposed brain surface and secured with superglue. Each animal was allowed to recover for at least two days before the first measurements. For in vivo electrophysiologyterm·mth, the cranial window construct was gently removed, and the dura mater covering the IC and part of the cerebellum was carefully punctured and removed with a pair of fine forceps.

After all recordings had been done, animals received an intraperitoneal injection of pentobarbital (300 mg/kg) and were perfused transcardially, first with physiological saline (Baxter Healthcare, Zurich, Switzerland), followed by 4% paraformaldehyde (PFA) in 0.1 M phosphate buffer (PB; 4% PFA in PB, pH 7.4; Merck).

For two-photon imagingterm of the IC, a 20X water-immersion objective (LUMPlanFI/IR, 20X, NA: 0.95; Olympus Corporation, Tokyo, Japan) on a custom-built two-photon microscope was used, except for simultaneous juxtacellularterm recordings, for which a long working distance 40x objective (LUMPlanFl/IR, 40X, NA: 0.80, Olympus Corporation, Tokyo, Japan) was used. Excitation light was provided by a MaiTai Ti:Sapphire laser (Spectra Physics Lasers, Mountain View, CA, USA) tuned to a wavelength of 920 nm. A layer of Ringer solution was put between the objective and the cranial window. GCaMP6sterm fluorescence was captured by a photomultiplier tube (H6780-20, Hamamatsu, Japan) after a barrier filter at 720 nm (FF01-720/SP-25; Semrock), a secondary dichroic at 558 nm and a green bandpass filter centered at 510 nm (bandwidth: 84 nm; FF01-510/84-25; Semrock); AlexaFluor 594 fluorescence was captured at the second channel with a red bandpass filter centered at 630 nm (bandwidth: 60 nm; D630/60; Chroma). Images (256 × 128 pixels) were collected at 9 Hz (2 μs/pixel; 1–2 μm/pixel). To minimize acoustic noise from scanning, a sinusoidal waveform was used for the X Galvo-scanner (for acoustic spectra see Figure 2—figure supplement 1 ). Data were acquired in the middle 80% of the sinusoidal waveform to minimize nonlinearity. Multiple regions were imaged sequentially in multiple sessions in awaketerm, head-fixed animals. For depth estimation, a Z-stack was acquired over a 512 × 512 µm area at 1 × 1 × 1 µm voxel size. Depth of each imaged area was estimated by measuring the Z-distance from the pia surface. Imaged neurons lay between 15–155 μm from the pia surface. The relative position of each region was tracked through the micromanipulator (MP-285, Sutter Instrument) that controlled the microscope objective. The positions of imaged areas were further aligned across animals to a common coordinate using the midline, lateral extreme and anterior-posterior extremes of the IC as anatomical landmarks in bright field images (SZ 61,Olympus) of the cranial window.

Frame timing of the scanner, timing of the sound stimuli, and animal movementsterm were digitized using a Digidata 1440A (Molecular Devices, Sunnyvale, CA, USA) with Clampex v. 10.3 (Molecular Devices, Sunnyvale, CA, USA).

In vivo juxtacellularterm recordings were made under two-photon guidance ( Kitamura et al., 2008 ). Glass pipettes were pulled from 1.5 mm, thick-walled borosilicate capillaries (Hilgenberg, Malsfeld, Germany) to 1–2 µm tip diameter (P-97; Sutter Instrument, Novato, CA) and filled with internal solution containing (in mM): potassium gluconate 138, KCl 8, Na 2 -phosphocreatine 10, Mg-ATP 4, Na 2 -GTP 0.3, EGTA 0.5, HEPES 10, (pH 7.2 with KOH; Merck). The internal solution also contained 40 µM Alexa Fluor 594 hydrazide. Ringer solution containing 1–2% agarose and (in mM): NaCl 135, KCl 5.4, MgCl 2 1, CaCl 2 1.8, HEPES 5, was applied on the brain surface to reduce movementterm artefacts. A positive pressure of about 300 mbar was maintained before penetration of the pia surface, and reduced to about 30 mbar upon pia entry; pressure was removed upon cell approach. Electrode resistances were constantly monitored and recording started when resistance increased to >25 MΩ. Juxtacellularterm potentials were acquired with a MultiClamp 700A amplifier (Molecular Devices, Sunnyvale, CA, USA) in current-clamp mode. Signals were low-pass filtered at 10 kHz (four-pole Bessel filter) and digitized at 25 kHz (Digidata 1322A). Data were recorded with pCLAMP 9.2 (Molecular Devices). In some cases a large current injection (1–6 nA) was used to elicit (positive current) or suppress (negative current) spikes of the cell being recorded (nanostimulation; for example Houweling et al., 2010 ), usually for cells that did not show obvious change in spike rate upon pure-tone stimulations. These data were also used for fitting the fluorescence ground-truth model.

Tone stimuli were generated in MATLAB v7.6.0 (The MathWorks, Natick, MA, USA) and played back via a TDT System3 setup (RX6 processor, PA5 attenuator, ED1 electrostatic speaker driver and two EC1 electrostatic speakers; Tucker Davis Technologies, Alachua, FL, USA). Sound stimuli were presented bilaterally in open field. Sound intensities were calibrated using a condenser microphone (ACO pacific Type 7017; ACO Pacific, Inc, Belmont, CA, USA) connected to a calibrated pre-amplifier and placed at the position of the pinnae.

For measurement of FRAs, 1 s tones (including 2.5 ms cosine-squared rise/decay times) with frequencies between 1 and 64 kHz with three steps per octave were presented at intensities between 30 and 80 dB sound pressure level (dB SPL) in steps of 10 dB. The set of stimuli was presented 6–10 times per experiment each in a pseudorandom order at an inter-stimulus interval of 1.5 s. For juxtacellularterm recordings, due to the limited recording time tones were only presented at one or two intensities (70 dB SPL; or 50 and 70 dB SPL).

Visual recordings were made using an RS Miniature CCD Camera (RS Components, Corby, UK) at 3 Hz. The camera was aimed at the animal’s head from a roughly right lateral perspective, in order to clearly record the animal’s right eye and whiskers. Facial movementterm was detected by calculating the root-mean-square intensity change between successive frames in a rectangular region behind the whisker pad (facial ROI in Figure 8B ). General movementterm of the animal was registered using a piezo-electric motion sensor under the front paws of the mouse (pressure sensor in Figure 8B ), digitized without further amplification using an AD channel of the Digidata 1440A.

Gelatin-embedded, 40 μm sections of PFA-fixed mouse brains were stained with the following antibodies: mouse anti-Gad67 (cat. no.: MAB5406; Millipore; 1:1000; RRID: AB_2278725 ); chicken anti-GFP (cat. no.: GFP-1020; Aves; 1:1000; RRID: AB_10000240 ); rabbit anti-NeuN (cat. no.: ABN78; Millipore; 1:1000; RRID: AB_10807945 ); mouse anti-parvalbumin (cat. no.: 235; Swant; 1:7000; RRID: AB_10000343 ); rabbit anti-calretinin (cat. no.: 7699/4; Swant; 1:5000; RRID: AB_2313763 ); and AlexaFluor-, Cy3- or Cy5-conjugated secondary antibodies (Invitrogen or Jackson ImmunoResearch). To ensure a more homogeneous GAD67term fluorescence for the post-hoc immunostaining of imaged brains, the brain slices were incubated twice in the primary antibody solution, each for 1 week at 4°C. The secondary antibody was also applied twice, but overnight at room temperature. Cell counting was performed manually in FIJI using the Cell Counter plug-in on confocal z-stacks. Confocal images were acquired using a Zeiss LSM700 microscope. Overview epifluorescence images were acquired using a Zeiss AxioImagerM2 equipped with a Zeiss Axiocam 503 mono camera.

Data analysis was performed with Igor Pro (WaveMetrics, Inc, Lake Oswego, OR, USA) using custom written procedures. Two-photon images and behavior video were aligned to ClampEx data using stimulus timing. Whisking behavior was assessed by calculating the root-mean-square of the frame to frame intensity difference in an area at the whisker pad.

Movementterm artefacts in two-photon images were corrected based on the built-in ImageRegistration operation in Igor Pro, which is based on a published algorithm ( Thévenaz et al., 1998 ). Neuronal cell bodies were identified visually based on the average image of the motion-corrected image series, and a higher sampling Z-stack of the area (0.5 × 0.5 µm pixels; 1 µm z steps) taken directly after each experiment. Regions-of-interests (ROIs) were drawn around cell bodies. Average fluorescenceterm·var values for individual ROIs were corrected for background fluorescenceterm·var, which was defined as the change in average fluorescenceterm·var in a 2 µm wide contour surrounding the ROI, excluding any pixel directly belonging to another ROI ( Figure 2D ).

Individual baseline fluorescence values of an ROI were measured for each trial by averaging the fluorescence in the 1 s preceding each stimulus onsetterm. To mitigate carry over effects from earlier stimuli caused by the slow kinetics of GCaMP6sterm, the distribution of these baseline values was fitted with a Gaussian distributionterm·stat. Any trial with a more extreme average baseline fluorescence than μ ± 3 σ was excluded from further analysis.

To analyze the FRA of each ROI, we isolated the stimulus-related response by extracting the signal autocorrelation ( Geis et al., 2011 ) by calculating the average Pearson correlation coefficientterm·stat among fluorescence waveforms to the same stimulus; the fluorescence trace within 1 s of the beginning or end of each stimulus was taken as the stimulus related waveform ( F i t for stimulus i ), that is between -1 s and +2 s of the stimulus onsetterm. For a stimulus that was repeated n times, we calculated the signal autocorrelation ( ρ - a u t o ) by averaging the Pearson’s correlation coefficientterm·stat ( ρ i , j ) for the n ( n - 1 ) 2 possible pairs of responses: ρ − a u t o = 2 n ( n − 1 ) ∑ i = 1 ; i < j n ρ i , j where ρ i , j was calculated from fluorescence waveforms at trial i and j with the StatsCorrelation function in Igor Pro using the standard formula: ρ i , j = ∑ ( F i t - F i - ) F j t - F j - ∑ ( F i t - F i - ) 2 ∑ ( F j t - F j - ) 2 Statistical significance of signal correlation was done by a bootstrap methodterm·stat: for each ROI, a distribution of average Pearson correlation coefficientterm·stat was constructed by drawing 30,000 random samples of n fluorescence trace segments within an experimental session, where n is again the number of stimulus repetitions. The p-value of each stimulus was calculated as the fraction of n -member samples having a greater (for frequencyterm autocorrelation area; Geis et al., 2011 ) signal autocorrelation than that of the stimulus. The ranked p-values were then tested for significance with α = 0.05 and Holm-Bonferroni correction for the number of different stimuli presented (19 frequencies × 6 intensities=114 for FRA measurements). The characteristic frequency (CF)term·def of an ROI was defined as the sound frequencyterm at which the lowest intensity evoked a significant response. If multiple frequencies evoked significant responses at the lowest level, their geometric mean was taken as CFterm.

The FRA of a cell is generally continuous in frequency-intensity space. Making use of this, we refined the FRA by quantifying the similarity of responses to “adjacent” stimuli by analogously calculating the signal crosscorrelation ( ρ - c r o s s ).

ρ - c r o s s = 1 n m ∑ i = 1 n ∑ j = 1 m ρ i , j where n and m are the number of repetitions of the two adjacent stimuli, leading to n×m possible pairs of responses and ρ i , j is again the Pearson correlation coefficientterm·stat of the two responses. Note that, different from the cell to cell comparison described in Geis et al. (2011) , none of the response pairs here were simultaneous. If the maximum ρ - c r o s s calculated against up to 8 (i.e. including diagonals) neighbors of a particular stimulus was >0.12, the stimulus was included for classification of its response type. For this purpose, the fluorescence response was calculated for four periods: onsetterm (0-500 ms re onsetterm), steady (500-1000 ms re onsetterm), offsetterm (0-500 ms re offsetterm) and off-late (500-1000 ms re offsetterm). We used the following scheme (in pseudocode) to classify individual responses within an FRA as excitatory, inhibitoryterm or offsetterm: Response class Criteria (non-exclusive) Excitation (onsetterm and sustainedterm) F onsetterm – F baseline > 2 × s.d. baseline; OR F steady – F baseline > 2 × s.d. baseline Inhibition F steady – F baseline < –2 × s.d. baseline; OR F offsetterm – F baseline < –2 × s.d. baseline Offsetterm If (excitation) F off-late – F offsetterm > 2 x s.d. baseline elseif (inhibition) F off-late – F offsetterm > 2 x s.d. baseline; AND F off-late > F baseline else F offsetterm – F steady > 2 x s.d. baseline; OR F off-late – F steady > 2 x s.d. baseline Unclassified If none of the above, for example due to low signal-to-noise ratio If at least 25% of all significant responses to frequency-intensity combinations belonged to the same class (e.g. inhibition), we named the FRA after that response (e.g. inhibition FRA). Typically an ROI showed a dominant response class in the majority of its significant responses: 20% of cells showed a dominant class in all significant responses; 54% of cells in ≥75% of significant responses; 92% of cells in ≥50% of significant responses. If more than one class reached the threshold of 25% of the significant responses, the FRA of an ROI was classified as mixed (e.g. Figure 3I,M ).

Finally, to distinguish between onsetterm and sustainedterm responses, we averaged all excitatory responses of an ROI that were not immediately preceded or followed by any significant responses. The kinetics of sound-evoked responses were fitted by a single exponential function with the form A ( 1 - e x p ⁡ ( - t / τ onsetterm ) ) . If this onsetterm time constant, τ onsetterm , was >1 s, the ROI response type was designated as sustainedterm, else as onsetterm.

To find the most prominent direction of CFterm gradient, we parametrized the location of each neuron as a projected distance r from the anatomical origin along a line with an angle θ with the medial-lateral orientation: r = x cos ⁡ θ + y sin ⁡ θ where x and y are coordinates (in micrometers) of cells along the medial-lateral and anterior-posterior axes, respectively. We then model CFterm as a polynomialterm function of r : a 0 + a 1 r 1 + a 2 r 2 + a 3 r 3 + a 4 r 4 + … = ∑ i = 0 n a i r i This whole function was then fitted to the logarithm of the CFterm values of the recorded neurons using the Levenberg-Marquardt least-squares methodterm·stat, implemented in Igor Pro, that is: a r g m i n θ , a 0 − 4 ∑ x = 1 n ( log ⁡ ( CFterm x ) − ∑ i = 0 4 a i r i ) 2 A 4 th order polynomialterm was used in Figure 6 because increasing the number of exponents did not increase the explained varianceterm further. The best fit parameters were θ = 0.875 rad (≈50°), a 0 = 6.95, a 1 = −0.0135 dec μm −1 , a 2 = 1.95 × 10 −5 dec μm −2 , a 3 = −1.11 × 10 −8 dec μm −3 , a 4 = 2.17 × 10 −12 dec μm −4 . Cross-validationterm·stat (70% fitting/30% test) indicated a slight overfitting. We also considered 2D polynomialterm fits in the form ∑ a i j x i y j , where 0 ≤ i + j ≤ n , and found that a 3 rd order ( n = 3 ) fit would be an optimal compromise between bias (underfitting) and varianceterm (overfitting). However, we opted for the single dimension polynomialterm to avoid potential overinterpretation of the complex contour created by the 2D polynomialterm.

Traces from juxtacellularterm recording were first subjected to a digital DC remove filter which subtracts at each point in time the average potential within ±1 ms to remove DC drift or offsetterm introduced by nanostimulation ( Houweling et al., 2010 ). Traces were blanked around the start and end of each current injection (2 ms before and 3 ms after) to remove stimulus artefacts. Spikes were then detected by a simple thresholding procedure, with spike times defined as the peak time of the spikes, which presumably corresponds to the maximum rate of rise of the action potential.

For spike vs fluorescence model, spike times were converted to number of spikes over time ( n ( t ) ) at the same sampling rate of the imagingterm (114.4 ms bins). It was then convolved with a simple ramp-decay kernel ( g ( t ) ) according to the equations: F ( t ) = F 0 + n ( t ) ∗ g ( t ) g ( t ) = { F 1 A P ( t t rise ) , t < t rise F 1 A P ( 1 − exp ⁡ ( t − t rise τ decay ) ) , t ≥ t rise where F 1AP is the amplitude of the fluorescence change per action potential, t rise is the rise time of the fluorescence and τ decay is the decay time constant for the fluorescence. An offsetterm (F 0 ) is added, which represents the minimal fluorescence at zero spike rate.

This 4-parameter model was fitted to the fluorescence trace using a genetic fitting routine in Igor Pro (Gencurvefit XOP, kindly provided by Andrew Nelson, Australian Nuclear Science and Technology Organization).

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https://doi.org/10.1002/cne.20863 PubMed Google Scholar Author details Aaron Benson WongpersName Department of Neuroscience, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands Contribution Conceptualization, Formal analysis, Funding acquisition, Writing—original draft, Writing—review and editing Competing interests No competing interests declared "This ORCID iD identifies the author of this article:" 0000-0003-1650-2710 J Gerard G BorstpersName Department of Neuroscience, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands Contribution Conceptualization, Software, Supervision, Funding acquisition, Writing—original draft, Writing—review and editing For correspondence g.borstpersName@erasmusmc.nl Competing interests No competing interests declared "This ORCID iD identifies the author of this article:" 0000-0002-6092-1544 J Gerard G BorstpersName Aaron Benson WongpersName J Gerard G BorstpersName J Gerard G BorstpersName The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

We thank Kees Donkersloot and Elize Haasdijk for their excellent technical support and Alba Membrilla Esteban for performing part of the immunohistochemistry analysis, Zhenyu Gao for sharing the design of the chronic cranial window, and Travis Babola and Dwight Bergles for helpful discussions on tonotopy. We thank Douglas Kim and the GENIE Project at the Janelia Research Campus for making the GP4.3term mouse line available.

This work was supported by a NeuroBasic PharmaPhenomics grant (Agentschap NL of the Ministry of Health, Welfare and Sports of the Netherlands) and a TOP subsidy (#91218033) from ZonMW to JGGB. ABW was supported by an Individual Fellowship (660157-OPTIMAPIC) through the Marie Skłodowska-Curie actions (European Commission).

Animal experimentation: All experiments in this study were performed in accordance with the ethical guidelines for laboratory animals within our institute and with European guidelines. The study was carried out under the project license (AVD2016789) approved by the Centrale Commissie Dierproeven (CCD) and the animal ethical committee (Instantie voor Dierenwelzijn; IvD) of the Erasmus MC. All recovery surgeries were performed under general isoflurane anesthesia supplemented with lidocaine, carprofen and buprenorphine as peri-operative analgesics. Terminal transcardiac perfusion was performed under pentobarbital anesthesia. Every effort was made to minimize suffering.

© 2019, WongpersName and BorstpersName This article is distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use and redistribution provided that the original author and source are credited.