Brain networks manifest a continuous interplay between internal ongoing activity and stimulus-driven (evoked) responses to form perception. Numerous studies have shown that cortical states modulate ongoing activity and its interaction with sensory-evoked input (Arieli et al., 1996; Deneux and Grinvald, 2016; Ferezou and Deneux, 2017; Ferezou et al., 2007; Fiser et al., 2010; Fox et al., 2006; Haider et al., 2007; He, 2013; Kasanetz et al., 2002; Kenet et al., 2003; Luczak et al., 2009; Markram et al., 1998; McGinley et al., 2015; Niell and Stryker, 2010; Raichle, 2015; Schölvinck et al., 2015; Shimaoka et al., 2019) that is further controlled by various gain mechanisms (Carandini and Heeger, 2012). Neuromodulators that affect the state of cortical networks (Marder, 2012), however, can alter the balance between ongoing (partly top-down) and evoked (largely bottom-up) activity. Therefore, they can crucially influence the formation of perceptual events (Cassidy et al., 2018; Pinto et al., 2013; Yu and Dayan, 2002) and higher cognitive functions (Doya, 2008; Hesselmann et al., 2008; Hurley et al., 2004; Sadaghiani et al., 2010). One prominent neuromodulator involved in the modulation of the cortical state is serotonin (5-hydroxytryptamine; 5-HT) (Rapport et al., 1948), which is mainly released from 5-HT neurons in the dorsal raphe (DR) and median raphe (MR) nuclei (Dahlström and Fuxe, 1964; Descarries et al., 1982; Ishimura et al., 1988; Mengod et al., 2006). The serotonergic system comprises widespread projections to all cortical and subcortical areas (Hale and Lowry, 2011; Jacobs and Azmitia, 1992; Mengod et al., 2006; Vertes and Linley, 2007; Waterhouse et al., 1986) with different 5-HT receptors (inhibitory or depolarizing) co-distributed across different cortical cell types (Hannon and Hoyer, 2008; Leysen, 2004; Santana et al., 2004). Altogether, this makes 5-HT a likely candidate for the contribution to fine-tuned scaling of both ongoing and evoked activity (Shimegi et al., 2016) as well as their integration across brain networks (Berger et al., 2009; Conio et al., 2019; Lesch and Waider, 2012).

In the visual cortex, pioneering studies using electrical stimulation of the dorsal raphe nucleus (DRN) revealed its general modulatory influence on evoked cortical responses (Gasanov et al., 1989; Moyanova and Dimov, 1986). Cortical application of 5-HT or 5-HT receptor agonists via microiontophoresis and single-cell recordings in vivo showed either suppressive or facilitative effects (Krnjević and Phillis, 1963; Reader, 1978; Watakabe et al., 2009; Waterhouse et al., 1990). Iontophoretic application of 5-HT into the visual cortex of awake monkeys in a recent study demonstrated that at the population level, however, 5-HT decreases mainly the gain of evoked responses without effecting spontaneous activity (Seillier et al., 2017). Such a distinct 5-HT effect on response gain was recently attributed to selective activation of 5-HT2A receptors (Zhang and Stackman, 2015) via several different approaches: after subcutaneous injection of a hallucinogenic 5-HT2A receptor agonist in mice (Michaiel et al., 2019), through whole-brain modelling (Deco et al., 2018) of human 5-HT2A receptor density and stimulation with lysergic acid diethylamide (LSD), and by direct and specific optogenetic activation of 5-HT2A receptors in the mouse visual cortex (Eickelbeck et al., 2019). Intriguingly, using optogenetic stimulation of 5-HT neurons in the mouse DRN (Dugué et al., 2014; Kapoor et al., 2016; Matias et al., 2017), only one study in olfactory cortex has shown so far a 5-HT-induced (divisive) gain control of spontaneous firing, without any effect on the gain of stimulus-driven population responses (Lottem et al., 2016). This suggests that DRN activation could separately reduce the weight of ongoing cortical activity relative to evoked activity (Lottem et al., 2016), thereby possibly changing the balance of integration between internal priors (Berkes et al., 2011; Fiser et al., 2010) and external sensory input (Lottem et al., 2016).

In this study, we employed optogenetic stimulation of 5-HT neurons in the DRN to investigate 5-HT-induced effects on ongoing and evoked population activity in the mouse primary visual cortex (V1) using wide-field Ca²⁺ imaging of RCaMP signal complemented with recordings of multi-unit spiking activity. Our results provide evidence for 5-HT-induced separable suppression of evoked and ongoing activity, affecting the gain of both these components in a divisive manner. Concurrent iontophoretic application of specific antagonists of 5-HT1A and 5-HT2A receptors (Dyck and Cynader, 1993; Jakab and Goldman-Rakic, 1998; Leysen, 2004; Riga et al., 2016; Shukla et al., 2014) suggest a distinct role of these receptors in regulating suppression levels of spontaneous and evoked population activity, respectively (Azimi et al., 2018).

Finally, we investigated how the divisive nature of 5-HT modulation affects evoked population responses to varying input intensities and integration with ongoing activity (Deco et al., 2015). Addressing this question is important because it allows estimating the extent of 5-HT-induced scaling of activity preserving the information content, as formalized by a model of divisive normalization (Carandini and Heeger, 2012). We found that normalization of responses in the anesthetized state is achieved with additive contribution of ongoing activity, indicating integration of spontaneous and evoked activity with increased weight of internal priors. In awake mice, normalization is largely independent of suppression in ongoing activity. This suggests that 5-HT provides a discrete divisive gain control of spontaneous ongoing and evoked visual activity, while preserving information content and regulating the balance between these components depending on the cortical state.

To trigger the activation of 5-HT neurons in the DRN with precise timing, we used a transgenic ePet-Cre mouse line (Scott et al., 2005), which allows expression of Channelrhodopsin2 (ChR2) in 5-HT neurons by Cre-dependent expression of double-floxed adeno-associated virus (AAV, see Materials and methods). This enabled real-time activation of 5-HT neurons via photostimulation (Li et al., 2005; Figure 1) in vivo (see Figure 1—figure supplement 1 for an example of extracellular recordings in the DRN). In order to simultaneously record activity of a large number of neurons across V1, we employed wide-field optical imaging of Ca²⁺ signals, shown to reflect suprathreshold population activity across upper cortical layers (Kim et al., 2016; Lütcke et al., 2013; Lütcke et al., 2010; Wallace et al., 2008; Xiao et al., 2017). Specifically, we used the red-shifted fluorescent probe RCaMP (Akerboom et al., 2013; Dana et al., 2016; Figure 1a) to minimize interference with the blue light employed to activate serotonergic neurons in the DRN (Figure 1b) and to reduce light scattering caused by hemodynamic signals in comparison to GCaMP.

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Photostimulation of 5-HT neurons in the DRN suppresses neuronal responses in primary visual cortex (V1)

As control conditions we recorded evoked responses to visual stimuli (vertical grating with 100% contrast, presented 10 times at intervals of 3 s with 200 ms duration) and spontaneous activity over a total of 30 s (Figure 2ai, [V] and Figure 2aiii [S], respectively). In addition, we recorded the activity during these conditions with photostimulation (16 s train of 470 nm light pulses at 20 Hz and 50% duty cycle, marked as blue bars in Figure 2aii, [V_ph] and Figure 2aiv, [S_ph]) to activate 5-HT neurons in the DRN. For each condition, Figure 2a shows the time course of RCaMP signals as mean spatial averages across V1 (25–50 trials per condition) derived from eight animals under anesthesia. Under control conditions without DRN photostimulation, activation over V1 shows each stimulus occurrence as a rapid ramp-up of the RCaMP signal followed by a slower decay towards baseline level (Figure 2ai). In contrast, after the onset of photostimulation, a strong suppression of evoked visual responses is observed, succeeded by a subsequent increase of the Ca²⁺ signal above pre-stimulation levels after cessation of photostimulation (Figure 2aii).

Figure 2

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Importantly, 5-HT-mediated suppression of cortical activity is present without external visual input; that is, following photostimulation, ongoing cortical activity rapidly declines below baseline levels (Figure 2aiv). This suppression of spontaneous activity includes cortical areas beyond V1 (white contours in Figure 2b, 4th row; for assignment of cortical areas, see Figure 1aiv), suggesting 5-HT affects spontaneous drive through widespread ascending projections from the DRN across the entire cortex (Hale and Lowry, 2011).

Suppression of ongoing activity

We next quantified the effects of DRN photostimulation on spontaneous cortical activity. The traces in Figure 3ai depict spatial averages of Ca²⁺ signals over V1. A comparison between spontaneous activity under control conditions (black stippled lines) and upon DRN photostimulation (S_ph, light blue line) reveals a significant suppression (−0.10±0.02, n=8 animals, p=0.039; one-sample t test; Figure 3aii, left bar). The suppression is significant 680 ms (8 animals, p=0.04; paired t test with permutation correction) after the onset of DRN photostimulation, then it reaches a local minimum followed by an increase in activity (Figure 3ai). This later elevation in the RCaMP signal could indicate an increase of intracellular Ca²⁺ levels (Eickelbeck et al., 2019) associated with the 5-HT-receptor-mediated activation of the Gq/11 pathway (Millan et al., 2008) and concomitant activation of store-operated channels (Celada et al., 2013). By restricting the averaging window to the period where suppression of the RCaMP signal is significant (as marked with red rectangle in Figure 3ai), the amount of suppression increased to −0.33±0.02 (8 animals, p<0.001, one-sample t test; Figure 3aii, right bar).

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To investigate whether the observed suppression is indeed sustained during photostimulation and whether it reflects a decrease in spiking output of V1, we recorded multi-unit activity (MUA), n=9 animals, 104 MUAs, using the same experimental paradigm as in the wide-field RCaMP imaging. Similar to RCaMP imaging, spontaneous activity revealed by MUAs is significantly (below two times standard deviation of pre-photostimulation activity) suppressed after 750±184 ms of DRN photostimulation in comparison to baseline spontaneous firing (Figure 3bi, light blue and stippled black line, respectively) when averaged over the early phase (red rectangle in Figure 3ai and 3bi) of suppression (−0.48±0.07, n=9 animals, p<0.001, one-sample t test; Figure 3bii, right bar). Note that in contrast to the RCaMP signal, spiking activity is devoid of a subsequent elevation. Instead, the suppression remains highly significant throughout photostimulation (−0.43±0.08; n=9 animals, p<0.001; one-sample t test; Figure 3bii, left bar). This further suggests that the observed rise of the RCaMP signal may represent intracellular accumulation of Ca²⁺, rather than increase in spiking activity. The assumption is also supported by subsequent 5-HT receptor blocking experiments (see below). Altogether, it can be inferred that augmented activity of 5-HT neurons via DRN photostimulation results in suppression of spontaneous activity in the visual cortex. Additional analysis using linear regression shows that this suppression is divisive (Figure 4).

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Suppression of visually evoked activity

Next, we compared the conditions with visual input (V and V_ph). While visually evoked responses of control conditions are characterized by repeated increase of the Ca²⁺ signal with a small adaptive decrease in the response amplitudes over time (Figure 5ai and 5bii, black trace), the amplitude of activity declines toward negative values in the presence of DRN photostimulation (Figure 5aii, dark blue trace). Note that both the amplitude of the evoked responses and their baseline are reduced. To assess how much of the suppression in amplitude is due to the suppression of its baseline level, we subtracted image frames obtained under S_ph conditions from those under V_ph conditions (pixelwise and across single trials). The outcome (Figure 5aii, gray trace) is the photostimulation-induced suppression of the evoked response independent of suppression in spontaneous activity, that we refer to as the evoked component.

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To quantify these observations, three measurements are depicted in Figure 5b. (see Methods for details). The first measurement is the amplitude of evoked activity, defined as an average over the time window w₁ (Figure 5ai inset). Following DRN photostimulation, amplitudes of evoked responses (Figure 5bi dark blue curve) and evoked component (Figure 5bi gray curve) are significantly lower than those of the control condition (Figure 5bi black curve; p<0.05; paired t test with permutation correction). In the early part of the photostimulation window (stimulus #2–4), however, amplitudes of evoked responses are also significantly below amplitudes of the evoked component (p<0.05; paired t test with permutation correction). Using a second measurement, that is, the baseline of the traces (averaged over a 200 ms time window before the onset of each visual stimulus (w₂, Figure 5ai inset) indicates that this difference arises from additional suppression seen in spontaneous activity (Figure 3ai). Indeed, the time course of the baseline in the evoked responses during photostimulation is analogous to spontaneous activity during photostimulation (Figure 5bii, cf. dark blue and light blue traces, respectively); both are characterized by an initial suppression followed by the previously referred rise in RCaMP signal. We, therefore, define the baseline of the evoked response as the baseline component and it is approximated via spontaneous activity.

In order to verify that the suppression of the evoked component is independent of the suppression of spontaneous activity, the magnitude of responses (i.e. response gain, calculated as absolute change of the amplitude from baseline) is calculated as a third measurement (Figure 5biii). The suppression of magnitude is highly significant as compared to control (Figure 5biii, blue and black curves, respectively; p<0.05, paired t test with permutation correction). Moreover, in the photostimulated condition the magnitude of the evoked response resembles the evoked component (Figure 5biii, cf. overlapping blue and gray curves, respectively; across all stimuli, #1:10, p>0.21, paired t test with permutation correction), confirming that the suppression in response magnitude is separable from suppression of spontaneous activity.

Extracellular recordings of MUA in V1 substantiate the observed suppressive effects on evoked responses and their independence of baseline suppression at the spiking level (Figure 5—figure supplement 1). Figure 5—figure supplement 1b shows the quantification of the spike recordings using similar analysis as applied to the Ca²⁺ imaging data and Figure 5—figure supplement 1c shows an example recording of MUA.

Figure 5c summarizes a comparison between Ca²⁺ imaging data and MUA data using average of amplitude and magnitude values during the period of photostimulation (stimulus #2–7) after subtraction of controls. Evoked responses (blue) and evoked component (gray), obtained with Ca²⁺ imaging and MUA indicate a highly significant reduction in amplitude (Figure 5ci, Ca²⁺ imaging data: −0.450.02 [blue] and −0.39±0.02 [gray], n=8 animals, p<0.001, one-sample t test; MUA data: −0.55±0.04 [blue] and −0.41±0.04 [gray], n=9 animals, p<0.001, one-sample t test). The smaller suppression in the amplitude of the Ca²⁺ signal compared to MUA data reflects that the chosen averaging window also includes the rising baseline of the Ca²⁺ signal (Figure 5bii). Consequently, the magnitude of the responses which is independent from baseline changes reveals a similar significant reduction in Ca²⁺ and MUA data (Figure 5cii, Ca²⁺ imaging data: −0.38±0.01 [blue], −0.41±0.01 [gray], n=8 animals, p<0.001, one-sample t test; MUA data: −0.38±0.02 [blue], −0.39±0.02 [gray], n=9 animals, p<0.001, one-sample t test). This again demonstrates that 5-HT-induced reduction in the gain of evoked activity is independent of the reduction of ongoing activity and is well-captured by response magnitude in both recording methods. Analogous to spontaneous activity, using linear regression, we found that the suppression of the evoked component is divisive (Figure 5—figure supplement 2). Altogether, these results suggest that increasing activity of 5-HT neurons in the DRN affects cortical activity in a divisive manner via two suppressive components: one suppressing ongoing activity and another reducing the gain of visually evoked activity.

Distinct and independent contribution of 5-HT2A and 5-HT1A receptors to suppression of evoked and spontaneous activity

We next asked whether the observed two suppressive components might be mediated via different 5-HT receptors (Hannon and Hoyer, 2008; Leysen, 2004; Santana et al., 2004). After blocking 5-HT2A receptors via microiontophoresis of MDL (see Methods) and parallel photostimulation of 5-HT neurons in the DRN, the amplitude of the evoked response remains suppressed, while its magnitude is only slightly reduced (Figure 6ai, blue). Hence, after subtraction of the spontaneous component (Figure 6ai, light blue), the trace of the evoked component (Figure 6aii, gray) is nearly identical to control conditions (Figure 6aii, black) with no significant difference between magnitude values (Figure 6bi) except for a period immediately after onset of drug application (Figure 6bi, stimulus #2). This is most likely due to delayed onset of the drug effect. In contrast, the suppression of the baseline is preserved (Figure 6bii, dark blue) and is similar to spontaneous activity during photostimulation and MDL treatment (Figure 6bii, light blue). It is noteworthy that the rising part of the RCaMP signal in the S_ph condition during MDL application (Figure 6bii, light blue, values #5:7) is significantly reduced as compared to S_ph without MDL treatment (Figure 5bii, light blue; p=0.04, two-sample t test on the detrended traces). This suggests a reduction of the aforementioned intracellular Ca²⁺ accumulation (Eickelbeck et al., 2019) by effectively blocking 5-HT2A receptors. However, the continued rise of the RCaMP signal after the initial dip suggests contribution of further 5-HT receptor types (Jang et al., 2012; Millan et al., 2008) involved in intracellular Ca²⁺ accumulation that remain active during MDL application (Villalobos et al., 2005; Varga et al., 2009).

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Conversely, blocking of 5-HT1A receptors by microiontophoresis of WAY (see Materials and methods) abolishes the suppression in spontaneous activity (Figure 6ci, light blue and Figure 6dii), whereas the evoked component (Figure 6cii, gray) and hence, the magnitude of the response, remain significantly suppressed almost the entire time of drug application and photostimulation (Figure 6di, p<0.05, paired t test with permutation correction).

To compare 5-HT-induced effect on evoked and spontaneous components with and without drug application, time-averaged values during photostimulation are summarized in Figure 7. Suppression of the response magnitude (Figure 7a, left two bars) is significantly (p<0.01, two-sample t test) reduced via blocking 5-HT2A receptors (−0.18±0.03 [blue] and −0.16±0.03 [gray], middle two bars, n=6 animals, p>0.05; one-sample t test). No significant difference was found in magnitude of the evoked component by blocking 5-HT1A receptors (−0.36±0.05 [blue] and −0.37±0.05 [gray], right two bars; n=4 animals, p<0.001, one-sample t test). This suggests that 5-HT2A receptors dominantly contribute to the suppression of the evoked component by controlling the gain of the evoked response. In contrast, suppression of spontaneous activity (Figure 7b, left blue bar) is abolished via blocking of 5-HT1A receptors (0.02±0.02, n=4 animals, p>0.5, one-sample t test; Figure 7b, right blue bar), while no such change is seen by blocking 5-HT2A receptors (−0.4±0.02, n=6 animals, p<0.01; one-sample t test; Figure 7b, middle blue bar). Thus, activation of 5-HT1A receptors dominantly contributes to suppression of spontaneous activity.

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Together these results establish 5-HT1A and 5-HT2A receptors as major contributors to the suppression of activity in V1 induced by activation of 5-HT neurons in the DRN with separable impact on the gain of evoked and spontaneous components.

Intensity of visual input is scaled by 5-HT-induced normalization of cortical activity

To explore how sensitively 5-HT-induced suppression affects scaling of cortical activity, we employed the well-studied sensitivity of neurons in V1 to different stimulus contrasts. To obtain a contrast response function for different stimulus intensities, we presented gratings at 100, 50, 25, 12.5, and 6.25% contrast. Responses were imaged under control conditions (Figure 8ai) interleaved with conditions in which the DRN was photostimulated (Figure 8aii). As expected from earlier studies in mice (Porciatti et al., 1999), visual responses progressively decline in amplitude with decreasing contrast. To obtain an objective measure of the underlying contrast tuning the maximum of evoked response (peak) for each contrast is fitted to the Naka-Rushton function (Equation 6 in Materials and methods). The resulting fit is shown in Figure 8di as solid black curve (R²=0.93). Upon photostimulation of the DRN, we found that overall amplitudes for each contrast are systematically suppressed (Figure 8aii, dark blue traces), leading to a strong downward shift of the fitted tuning curve (Figure 8di, solid blue, R²=0.93). Furthermore, we found a systematic increase in the latency and significant decrease in the duration of evoked response (Figure 8—figure supplement 1). In addition, we confirmed the suppression of spontaneous activity independent of visual input (Figure 8aii, light blue trace). Above we showed that this suppressive spontaneous component contributes additively to the 5-HT-induced overall suppression of visual responses (Figure 5). Note that the evoked component is obtained by subtraction of the spontaneous component from the evoked responses for each contrast (Figure 8aiii). Therefore, the fitted tuning curve of the evoked component (Figure 8di, solid gray, R²=0.92) shows a shift toward tuning of control conditions that reflects the portion of suppression in the evoked response (Figure 8di, solid blue) attributed to the spontaneous component.

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Next, to account for normalization the traces of evoked responses (Figure 8aii) and evoked component (Figure 8aiii) are scaled by their maximum value at 100% contrast (Figure 8ci and cii, respectively). Such divisive scaling fails to fully replicate contrast tuning of controls (Figure 8di, solid black curve) when considering evoked responses, particularly at low stimulus contrasts (Figure 8di, blue stippled curve, R²=0.92). This is because of a significant contribution of the spontaneous component to the overall suppression (i.e., gain) of evoked responses at low stimulus contrasts: Whereas the magnitude of the evoked component shows no further reduction at these lower contrasts (Figure 8bi, two right gray bars), the corresponding suppression in the magnitude of evoked responses (which include the suppression in spontaneous activity) are significant (Figure 8bi, two right blue bars; 12%: −0.19±0.005, p<0.001; 6%: −0.15±0.003, p<0.01; n=18 animals, one-sample t test). This indicates that at low contrast suppression is mainly due to the suppression in the spontaneous component. Also note that the suppression at these lower contrasts is similar to 5-HT-induced suppression of spontaneous activity (S_ph; −0.17±0.02, n=18 animals, p<0.001, one-sample t test; Figure 8bii). Consequently, fitting the Naka-Rushton function to the added values of evoked and spontaneous components (Figure 8di, gray stippled curve; R²=0.93) reveals a close match to contrast tuning of control conditions (Figure 8di, solid black curve), indicating normalization across all contrasts. Importantly, following the same experimental paradigm and quantification methods, MUA recordings leads to equivalent findings (Figure 8dii, 108 MUAs, n=3 animals; see Figure 8—figure supplement 2 for response traces and similar analysis). We conclude that in the anesthetized state, 5-HT-induced normalization of visual responses to different stimulus intensities is achieved by a linear combination of 5-HT-induced suppression of spontaneous and evoked components of cortical activity.

Finally, we explored the extent to which the above conclusion depends on the cortical state. Previous studies suggest that during awake state the cortical 5-HT levels are increased (Mukaida et al., 2007; Portas et al., 2000). Because our results characterize 5-HT-induced suppression as divisive, both for spontaneous and evoked activity (Figure 4 and Figure 5—figure supplement 2, respectively), 5-HT baseline levels may crucially affect the quantity of inducible suppression. Hence, the impact of activating the DRN on cortical activity may differ under wakeful conditions compared to conditions where the animals are anesthetized. Therefore, we recorded cortical activity of awake mice (5) that were head-fixed and habituated to walk and stay on a treadmill (using the same experimental paradigm as shown in Figure 8). Figure 9a depicts the time traces of spatially averaged RCaMP signals across V1, evoked by different stimulus contrasts. As in anesthetized animals, following DRN photostimulation cortical activity was suppressed as compared to controls (Figure 9ai and aii, blue and black (control) traces, respectively). In comparison to the anesthetized state, however, suppression at higher contrast (100%–25%) is significantly reduced (100%: p=0.010, 50%: p=0.012, 25%: p=0.019, 12%: p=0.392, 6%: p=0.694, n=5 animals, two-paired t test; Figure 9—figure supplement 1 shows the data derived from the same animals when they were anesthetized). Importantly, in the awake state, the contrast-dependent decline in the magnitudes is not different between suppression of evoked activity and evoked component (Figure 9bi, blue and gray bars, respectively; p>0.31, paired t test). This suggests that normalization is largely controlled without the contribution of the spontaneous component (Figure 9ci, blue (R²=0.98) and gray (R²=0.95) curves for evoked response and evoked component, respectively). Indeed, fitting normalized data (i.e. traces scaled by their maximum value at 100% contrast) to the Naka-Rushton function reveals a similar contrast tuning function for evoked responses and evoked component (Figure 9cii, stippled blue (R²=0.97) and gray (R²=0.98) curves, respectively) as controls (Figure 9cii, solid black curve). Thus, in the awake state, suppression of spontaneous activity (−0.11±0.3, n=5 animals, p=0.022, one-sample t test; Figure 9bii, left blue bar), even though similarly significant as in the anesthetized state (−0.17±0.04, n=5 animals, p=0.005, one-sample t test; Figure 9bii, right blue bar), constitutes an independent component with little influence on the magnitude and consequently, on normalization of stimulus-evoked responses.

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We show that activation of the serotonergic system impacts two entities of population activity in the visual cortex (V1): internally ongoing (spontaneous) and visually driven (evoked) responses, affecting both in a separable and divisive manner. Each of these components is scaled through separate suppressive effects of 5-HT1A and 5-HT2A receptors, respectively.

Previous studies in V1, using specific agonists for 5-HT1B and 5-HT2A receptors combined with single-unit recordings in anesthetized monkey, found a bi-directional modulation dependent on instantaneous firing levels. Application of 5-HT2A agonist caused suppression of neurons with strong responses and facilitation of those with weak responses, the opposite occurred when applying 5-HT1B receptor agonist (Shimegi et al., 2016; Watakabe et al., 2009). At the population level, 5-HT microiontophoresis in awake monkey revealed predominant suppressive effects (Seillier et al., 2017), similar to our study. In contrast to our findings, suppression was restricted to divisive scaling of evoked responses while no change in spontaneous activity was observed (Seillier et al., 2017). This discrepancy may indeed point to species-specific differences in individual 5-HT receptor sets or ‘receptomes’. On the other hand, limitations associated with local iontophoretic 5-HT application, such as determining the exact onset of drug effects or the inevitable lack of cortical stimulation with layer- and cell type-specific synaptic weights of DRN synapses could be an alternative explanation. Here, we applied optogenetic approaches to activate 5-HT neurons in the DRN and to specifically target the serotonergic system as a whole circuit (Jacobs and Azmitia, 1992; Ogawa et al., 2014; Pollak Dorocic et al., 2014; Weissbourd et al., 2014) in order to explore subsequent changes in V1. Considering the broad topographic organization within the DRN (Muzerelle et al., 2016), other cortical and subcortical areas modulated by activation of 5-HT neurons may additionally influence activity in V1 (Gilbert and Li, 2013). It should also be noted that besides 5-HT neurons, subpopulations of glutamatergic cells in the raphe nuclei express ePet (McDevitt et al., 2014; Sos et al., 2017). ePet in non-serotonergic neurons is mainly observed in the median raphe nucleus (Pelosi et al., 2014; Sos et al., 2017), while in the dorsal and caudal nuclei (B6 and B7) only few neurons positive for ePet are non-serotonergic (Pelosi et al., 2014). Thus, by using the ePet-Cre mouse line and the fact that 5-HT-neurons may use glutamate co-transmission (Kapoor et al., 2016; Liu et al., 2014; Szőnyi et al., 2016), an indirect activation of other (none-5-HT) circuits could principally be involved in the observed suppressive effects. However, as seen in our experiments pharmacological blocking of 5-HT receptors in V1 largely diminished the induced suppressive effects, contribution from other modulatory systems appears negligible for the present study.

The DRN was photostimulated for 16 s in the first set of our experiments. This is relatively long in comparison to the brisk activation of DRN neurons observed in certain behavioral contexts (Heym et al., 1982; Ranade and Mainen, 2009). However, this does not exclude additional longer-lasting tonic increase in DRN activity under natural conditions. For instance, direct retinal projections to the DRN (Pickard et al., 2015; Ren et al., 2013; Zhang et al., 2016) suggest its regulation well beyond the stimulation time window chosen in our study. In addition, slow periodic changes in 5-HT release occur naturally during day-night cycle (Portas et al., 2000; Tyree and de Lecea, 2017) and depend on seasonal factors (Spindelegger et al., 2012). Importantly, using the ePet-Cre mouse model and comparable photostimulation parameters as in our experiments (i.e. similar blue light intensity and frequency) to activate the DRN via fiber optics, a consistent increase of DRN activity in fMRI and MUA recordings over 20 s of photostimulation was revealed (Grandjean et al., 2019). Prolonged (12 s) photostimulation of the DRN in SERT-Cre mice increased perceptual thresholds for tactile stimuli (Dugué et al., 2014), altogether suggesting that sustained or repeated elevation of DRN activity correlates with meaningful and behaviorally relevant changes in neuronal responses (Correia et al., 2017; Lőrincz and Adamantidis, 2017; Miyazaki et al., 2011).

We used wide-field RCaMP imaging, an optogenetic method that enables recordings of suprathreshold neuronal activity across several millimeters of cortical target areas (Kirmse et al., 2015; Michaiel et al., 2019; Shimaoka et al., 2019; Silasi et al., 2016; Xiao et al., 2017), carrying information encoded by large populations of neurons (Dayan and Abbott, 2001). Wide-field recordings of RCaMP signals may also correlate with activity in the neuropil (Allen et al., 2017). To rule out this possibility, we performed complementary recordings of MUA. These largely reproduced the imaged suppressive effects, indicating that the observed reduction of RCaMP signals indeed reflects reduced spiking output at the cortical population level. Our recorded RCaMP signals also showed an increase above the baseline level before the end of DRN photostimulation. Autoreceptor-mediated suppression of 5-HT neurons within the DRN is an unlikely explanation for producing such late increase. First, the applied photostimulation parameters induce sustained elevation in activity of 5-HT neurons in the DRN during the entire time window of photostimulation (Figure 1—figure supplement 1 and see Grandjean et al., 2019). Second, we show using MUA that spiking activity in V1 is consistently suppressed during photostimulation. Third, the evoked component of visual responses remains suppressed during DRN photostimulation and finally, the late increase of RCaMP signals was selectively reduced by 5-HT2A antagonist. We suggest that intracellular Ca²⁺ accumulation of cortical neurons produces the late rise in the RCaMP signal (Eickelbeck et al., 2019) due to 5-HT receptor-mediated activation of the Gq/11 pathway (Jang et al., 2012; Millan et al., 2008) with further activation of store-operated channels (Celada et al., 2013). Additionally, Ca²⁺ signals could increase through activation of 5-HT3 receptors (Nichols and Mollard, 1996) that are also capable of providing fast disynaptic inhibition via activation of interneurons (Varga et al., 2009). Finally, the late increase of the RCaMP signal did not affect our conclusions but may be considered when using wide-field Ca²⁺ recordings of cortical activity in future studies.

Using different stimulus intensities, we identified normalization of visual responses. In anesthetized animals, ongoing activity supplemented response normalization as a subtractive factor. In the awake state, normalization was controlled by the gain of the evoked component and independent of concomitant suppression in ongoing activity. Inhibition tends to dominate activity in awake cortex (Haider et al., 2013), possibly accompanied by increased 5-HT levels (Mukaida et al., 2007; Portas et al., 2000). Therefore, because suppression of spontaneous activity is divisive (i.e., dependent on initial baseline levels), the additional contribution of the spontaneous component to normalization in the anesthetized state may result from large fluctuations in its amplitude rarely exhibited during wakefulness (Haider et al., 2013). Thus, the degree of 5-HT-controlled integration of sensory input and ongoing activity depends on cortical state and initial 5-HT levels.

Our pharmacological blocking experiments suggest that (hyperpolarizing) 5-HT1A receptors convey the suppression of the spontaneous component to a large extent. However, both RCaMP imaging and measurements of multi-unit activity, as applied here, do not allow identifying cell type specific contributions. At the population level, suppression of ongoing activity may reflect an overall reduction of pyramidal cell spiking caused by hyperpolarization or by decrease in synaptic transmission (Lőrincz and Adamantidis, 2017). In fact, hyperpolarization of excitatory neurons was recently shown as an additional source of normalization processes (Sato et al., 2014). In contrast, divisive scaling of evoked responses is most likely conveyed by predominant activation of (excitatory) 5-HT2A receptors, as suppression of the evoked component largely diminished after specific blocking. Moreover, 5-HT2A receptors couple to the Gq/11 pathway (Hannon and Hoyer, 2008) leading to an increase in neuronal firing rather than suppression. Therefore, activation of GABAergic neurons may mediate reduction in activity of pyramidal neurons (Gellman and Aghajanian, 1993). In fact, divisive modulation of visual cortical responses was shown to be specifically dependent on activation of soma-targeting parvalbumin expressing interneurons (Wilson et al., 2012, but see Lee et al. (2012) and Seybold et al., 2015) that dominantly express 5-HT2A receptors (Puig and Gulledge, 2011; Weber and Andrade, 2010). Activation of 5-HT2A receptors may also cause concomitant increase in depolarizing currents in pyramidal neurons, producing shunting inhibition, which results in increased conductance. Such a mechanism is known to affect the gain and the time constant of neuronal responses (Carandini and Heeger, 2012). Consistent with shunting inhibition, we find that response-onset latency decreases as a function of stimulus contrast while response duration in both control and photostimulated conditions increases. Furthermore, we find the duration of responses declined during photostimulation of the DRN as compared to controls. This suggests a shortened time window for temporal summation that in turn reduces response amplitudes (Mante et al., 2008). Thus, reduction in response duration under the influence of 5-HT may indicate involvement of shunting inhibition in pyramidal neurons to effectively control response gain. Suprathreshold excitatory drive by 5-HT2A activation may further be amplified by shaping the duration of 5-HT1A-mediated inhibition (Avesar and Gulledge, 2012; Stephens et al., 2014). Altogether, we propose that 5-HT circuits modulate evoked visual population responses by partly plugging into the existing canonical machinery performing divisive normalization (Atallah et al., 2012; Carandini and Heeger, 2012; Lee et al., 2012; Wilson et al., 2012). Further studies are needed to clarify 5-HT-dependent microcircuit mechanisms at the single-cell level (Tang and Trussell, 2017).

In two recent studies, selective activation of 5-HT2A receptors produced a strikingly consistent suppressive effect on the gain of visually evoked population responses (Eickelbeck et al., 2019; Michaiel et al., 2019), despite cell-type and layer-specific differences across single cells (Michaiel et al., 2019). These results strongly support our current finding of DRN-triggered scaling of evoked responses by cortical 5-HT2A receptors at the neuronal population level. It also implicates that the distribution of a single neurotransmitter receptor density (‘receptome’) can account for a distinct function in sensory processing (Akimova et al., 2009; Carhart-Harris et al., 2016; Deco et al., 2018; Goldberg and Finnerty, 1979; González-Maeso et al., 2007; Tauscher et al., 2001). While 5-HT2A receptors control response gain, DRN-triggered scaling of ongoing V1 activity seems dominantly controlled by 5-HT1A receptors.

In summary, joint action of 5-HT1A and 5-HT2A receptors unfold a separable and powerful scaling of ongoing and evoked components of population activity in V1. A major difference that we observe in normalization between awake and anesthetized states is an overall stronger 5-HT-induced suppression of response gain in the anesthetized state, which implicates that in the awake state response normalization is less dependent on ongoing activity and is possibly less influenced by internal cortical broadcasts. Considering that ongoing activity contains (top-down) internal expectations, whereas evoked responses carry (bottom-up) signals about external sensory events, imbalance in the recruitment of these receptors (e.g. through specific agonist intake or disordered receptor expression pattern) affects integration of these components, and thus, cortical information flow. This may either lead to overemphasis of internally generated expectations (i.e. favoring ‘priors’ Berkes et al., 2011; Fiser et al., 2010) relative to sensory input or vice versa (Lottem et al., 2016). Long-term malfunction of such interplay facilitates psychiatric disorders like anxiety, depression and schizophrenia (Friston, 2005; Geyer and Vollenweider, 2008; Jardri et al., 2016; Lucki, 1998; Soubrié, 1986; Urban et al., 2016; Zhang et al., 2016). Our study may help to develop new ways of diagnosis and therapy (Carhart-Harris et al., 2018) by rebalancing of these components.

All data generated or analysed during this study are included in the manuscript and supporting files. Source data file for Figure 3–9 are provided. Data can be downloaded from: https://doi.org/10.5061/dryad.931zcrjgk.

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Acceptance summary:

This paper explores the effects of serotonergic photostimulation on the mouse visual cortex. By combining state-of-the-art optogenetics, wide-field optical imaging, electrophysiology and pharmacological manipulations in vivo, the authors show that serotonergic neurons modulate both spontaneous and visually evoked responses by two separable cellular mechanisms. This study highlights an important, yet less examined role of serotonin in sensory processing.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "Subtraction and division of visual cortical population responses by the serotonergic system" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The reviewers have opted to remain anonymous.

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

In coming to our decision, we were aware that you could make additional experiments that would address this issue, but those experiments are likely to require substantial time and effort. Therefore, as per eLife's review policies, we decided to reject the manuscript. However, if you are able to collect single-unit data that support your claims, we would be willing to reconsider a resubmission. In that case, it would again be evaluated first by a Senior Editor and members of the Board of Reviewing Editors, who would decide whether or not to send it out for review.

Reviewer #1:

The neuromodulator serotonin is involved in a wide range of cognitive processes. Most current theories focus on its effects on learning, valuation and affect, leaving its involvement in sensory processing relatively less explored. In this timely report, Azimi et al. study this question by examining the effect of stimulating serotonergic neurons in the dorsal raphe nucleus on spontaneous and visually evoked activities in primary visual cortex of the mouse. They show that both are reduced following stimulation, but through different mechanisms: spontaneous activity is reduced due to activation of inhibitory 5-HT-1A receptors, and evoked activity is suppressed due to activation of excitatory 5-HT-2A receptors, suggesting a disynaptic circuit. From these data, the authors conclude that the serotonergic system provides gain control over the visual cortex that acts through both subtractive and divisive normalizations.

The experiments were very elegant, combining state-of-the-art optogenetic stimulation, wide-field optical imaging and pharmacological manipulations in vivo. While I generally support the publication of this paper, there are significant weaknesses in the manuscript, particularly in the statistical analysis and figure presentation that should be addressed before publication.

– The authors had made considerable efforts in performing detailed IHC, including testing expression of ChR2 in both DRN 5-HT neurons and their axons in V1, and looking at patterns of 5-HT receptor expression in V1. However, to support their claims, they should also provide quantification and statistical testing of these data.

– Generally speaking, the figures are very hard to understand and should be revised considerably. More specifically:

1) The authors should add figure legends for colored curves, shaded patches, rectangles on curves etc.

2) Axes titles should be more informative (for example, what is amplitude_W3 in Figure 5C?) and panel headers will be helpful in cases where multiple panels present similar data (for example Figure 3A)

3) The authors should refrain from asking the reader to compare different figures (for example, comparing Figures 3A and 5B). If the claim is important, the comparison should be tested explicitly.

4) Figure 2, inhibition's delay in the example seems fairly long compared to the averages shown in Figure 3? It would be nice to see more detailed analysis of individual mouse effects (also showing individual mouse data, maybe as a supplementary figure).

5) It would also be nice to see schemes of experimental protocols, and, related to this, Figure 2 would benefit from an entire example session.

6) In Figure 4—figure supplement 1, it's hard to assess the effect of photostimulation on firing, perhaps adding PSTHs would help.

– Statistical analysis is lacking. The main text barely mentions which statistical tests were made (except for one test for the similarity of responses across cortical layers, which is not well described), what are the corresponding values being compared (in the form of mean ± SD, p values, n's etc.), and what are the justifications for choosing particular tests. The authors should add all this information, and also provide further details regarding the exact procedures for data normalization and averaging (for example, in Figure 5 "Values were averaged across time windows during photostimulation in which activity levels were significantly below baseline", sounds too arbitrary).

– In the Discussion, the authors only briefly mention the functional implications of their findings with respect to existing theories of 5-HT function, they should elaborate on this matter.

Reviewer #2:

Azimi et al. stimulated serotonergic neurons in the dorsal raphe nucleus while measuring activity in the primary visual cortex of anesthetized mice. They show that stimulation produces normalization of V1 responses, due to 5-HT1A and 5-HT2A receptors. This is an interesting set of experiments, that has important consequences for serotonin's function in cortex. Unfortunately, the data do not strongly support the conclusions.

1) My main concern regards the choice of widefield imaging to measure the effects of 5-HT stimulation in V1. Given the nonlinearities in the relationship between firing rates and RCaMP activity, couldn't subtraction (for example) be mistaken for normalization? Electrophysiological recordings are reported, but this is a small sample size, and it's unclear whether these are single-unit (as reported in the Materials and methods) or multi-unit (as reported in the main text) recordings. Related to this, it is not possible to determine the layer of the neurons recorded electrophysiologically, using the techniques reported.

2) There is a relatively sparse description of the methods. How were firing rates normalized? Why are some values > 1? I couldn't tell until reading the Materials and methods that mice were anesthetized.

3) 16 s of stimulation is quite long, and could have caused autoreceptor-mediated suppression of 5-HT neurons, producing the late excitatory effects in Figure 2. This could be discussed; ideally, the stimulation parameters should be manipulated in a more physiological range.

4) What is the baseline in Figure 6? Is it different for each contrast? Could it change by contrast (e.g. in Figure 2, it looks like there is a pre-stimulus decrease in activity)?

5) The references used to support statements in the Introduction and Discussion are peculiar. For example, some of the references in the third paragraph of the Introduction did not study sensory processing or use optogenetics. Why must the suppression observed here be mediated disynaptically (Discussion, second paragraph)? Wouldn't work from Gulledge and colleagues (Avesar and Gulldedge, 2012; Stephens, Avesar and Gulledge2014; Front Neural Circ 12, 2, 2018) suggest it could be done only using differential expression of different 5-HT receptors in pyramidal neurons?

Reviewer #3:

The manuscript by Azimi et al. Explores the effect of serotonergic photostimulation on the spontaneous activity and visual evoked responses in the visual cortex of mice. The authors perform a series of optogenetic experiments combined with bulk imaging and electrophysiology to show that by stimulating serotonergic neurons in the raphe nuclei both spontaneous and evoked responses are altered. Using pharmacological techniques they further show that the normalization of visual cortical activity by 5-HT PS consists of a subtractive suppression of spontaneous activity mediated by 5-HT1a receptors and a divisive suppression of response gain mediated by 5-HT2a receptors. In addition, I found the global cortical suppression by 5-HT PS very intriguing.

The topic of the manuscript is of broad interest, the experiments performed and data analysis sound, results intriguing and most conclusions drawn backed up by the data. Overall I think the manuscript is worthy of publication in a very good journal with a broad audience. I have several critiques, questions and observations and hope the authors take them in a constructive way. These do not lessen my overall support of the story.

1) The recordings of the present study were performed under anesthesia. This leads to two issues, first, the visual responses might be different (see Durand et al. 2016 JNeurosci for a comparison of awake vs. anesth visual responses) and second, photostimulation of 5-HT neurons in the anesthetized state might overestimate the effect of DRN photostimulation (in addition to the already unnaturally synchronous stimulation of neurons). Ideally a loss of function experiment in the awake state would nicely complement the results of this study, however I am aware that this might raise several technical concerns.

2) The authors have chosen to use ePet-cre mice, but ePet is not the most specific marker for 5-HT neurons (see two papers from Gabor Nyiri in Brain Struct Funct). This could be discussed in the manuscript, but the effects identified in the pharmacological experiments argue for specific serotonergic effects.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Separable gain control of ongoing and evoked activity in the visual cortex by serotonergic input" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen Joshua Gold as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Magor Lorincz (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

Azimi et al. stimulated serotonergic neurons in the dorsal raphe nucleus while measuring activity in the primary visual cortex of mice. They show that stimulation produces normalization of V1 responses, due to 5-HT1A and 5-HT2A receptors. This is an interesting set of experiments, which have important consequences for serotonin's function in cortex. The careful revisions in light of the reviewers' comments and the added extracellular recordings, as well as experiments in awake animals, led to significant improvements in the manuscript's quality. As it stands, this manuscript is well written, interesting and timely. We do have the following comments.

Essential revisions:

1) Subsection “Distinct and independent contribution of 5-HT2A and 5-HT1A receptors to suppression of evoked and spontaneous activity”, first paragraph: The authors claim that the late increase in RCaMP signal that is usually observed following DRN photostimulation is suppressed by the application of MDL, yet do not support this claim with a statistical test. Furthermore, while the response does remain negative throughout drug application, it is increasing after an initial dip, and this increase cannot be explained by 5-HT1A receptor dynamics since these seem to be constant during photostimulation.

2) I do not understand the analysis that led to the conclusion that normalization is different between anesthetized and awake conditions. Specifically, if V_ph / V is constant (as suggested by the analysis) then (V_ph – S_ph)/ V shouldn't be constant, and vice versa. This could be the case, however, if S_ph is equal to zero. By looking at the traces shown in Figure 8Aii, it seems that at the time of peak evoked response, S_ph is indeed close to 0. Thus, the difference between the two conditions may simply be the result of slower suppression of spontaneous activity or faster evoked responses in the awake states.

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Reviewer #1:

[…] The experiments were very elegant, combining state-of-the-art optogenetic stimulation, wide-field optical imaging and pharmacological manipulations in vivo. While I generally support the publication of this paper, there are significant weaknesses in the manuscript, particularly in the statistical analysis and figure presentation that should be addressed before publication.

– The authors had made considerable efforts in performing detailed IHC, including testing expression of ChR2 in both DRN 5-HT neurons and their axons in V1, and looking at patterns of 5-HT receptor expression in V1. However, to support their claims, they should also provide quantification and statistical testing of these data.

The mentioned figure was meant as a proof of principle of the applied methodology rather than claiming quantifications. However, we agree with the reviewer that a thorough quantification would be necessary to support any specific claims about anatomical serotonergic innervation patterns in the visual cortex. As the focus of our study is on functional changes on V1 processing dynamics induced by activation of serotonergic neurons in the DRN and not on anatomical aspects (like projection pattern of fibers of 5-HT neurons in V1), we decided to skip this figure and refer to previous studies that have investigated such aspects in great detail (Dugué et al., 2014; Hale and Lowry, 2011; Leysen, 2004; Puig and Gulledge, 2011). However, we would like to keep the staining pattern of 5-HT neurons in the DRN expressing flx-ChR2 (former Figure 1C, now Figure 1B.) since it serves the depiction of experimental procedures.

– Generally speaking, the figures are very hard to understand and should be revised considerably. More specifically:

1) The authors should add figure legends for colored curves, shaded patches, rectangles on curves etc.

Done – we added figure legends for all such elements.

2) Axes titles should be more informative (for example, what is amplitude_W3 in Figure 5C?) and panel headers will be helpful in cases where multiple panels present similar data (for example Figure 3A).

Done – here applicable, axes titles were changed to exactly describe the presented parameter identities. Further, we added w of used abbreviations, and added panel headers (for instance, in Figure 5, former Figure 3, and Figures 6 and 7, several panel headers like “Visual stimulus”, “Amplitude”, “Magnitude”, etc. were added).

3) The authors should refrain from asking the reader to compare different figures (for example, comparing Figures 3A and 5B). If the claim is important, the comparison should be tested explicitly.

Done – To make the above-mentioned comparison easier to follow Figure 7 was added, which is summarizing the quantifications (magnitude and baseline values) shown in Figure 3 (spontaneous activity), Figure 5 (visually evoked activity) and Figure 6 (spontaneous and evoked activity with application of 5-HT1A and 5-HT2A receptors antagonists). Comparisons are verified by values and statistical tests in the main text.

4) Figure 2, inhibition's delay in the example seems fairly long compared to the averages shown in Figure 3? It would be nice to see more detailed analysis of individual mouse effects (also showing individual mouse data, maybe as a supplementary figure).

Done – Figure 2 depicts now all individual experiments. The difference in the onset of the suppression is calculated as mean ± SEM and stated in the main text. Average traces shown in Figure 3 and 5 were complemented with outlined SEM.

5) It would also be nice to see schemes of experimental protocols, and, related to this, Figure 2 would benefit from an entire example session.

Done – Figure 2A shows now all experimental protocols (systematically from top to bottom) and includes the time traces of activity recorded during the full time span of the trials. Also individual axes annotations and panel headers (depicting each stimulation condition) were added.

6) In Figure 4—figure supplement 1, it's hard to assess the effect of photostimulation on firing, perhaps adding PSTHs would help.

Done – PSTHs are added.

– Statistical analysis is lacking. The main text barely mentions which statistical tests were made (except for one test for the similarity of responses across cortical layers, which is not well described), what are the corresponding values being compared (in the form of mean ± SD, p values, n's etc.), and what are the justifications for choosing particular tests. The authors should add all this information, and also provide further details regarding the exact procedures for data normalization and averaging (for example, in Figure 5 "Values were averaged across time windows during photostimulation in which activity levels were significantly below baseline", sounds too arbitrary).

Done – whenever values mentioned in the main text the mean ± SEM is reported along with p values, type of the statistical test and number of subjects for that test. In addition, in the Materials and methods section the exact procedures of normalization, scaling or any other quantification steps are described. To find the onset of suppression and its effective duration (based on comparison between the traces of S and S_ph with paired t test corrected for multiple comparisons), we chose a window based on significance value: “The suppression is significant 680 ms (n=8 animals, p=0.04; paired t test with permutation correction) after the onset of DRN photostimulation, …”. “By restricting the averaging window to the period where suppression of the RCaMP signal is significant (as marked with red rectangle in Figure 3Ai.), …”

– In the Discussion, the authors only briefly mention the functional implications of their findings with respect to existing theories of 5-HT function, they should elaborate on this matter.

Done – we rewrote the Discussion and also discussed most recent publications closely related to our findings.

We wrote: “In two recent studies, selective activation of 5-HT2A receptors produced a strikingly consistent suppressive effect on the gain of visually evoked population responses (Eickelbeck et al., 2019; Michaiel et al., 2019), despite cell-type- and layer-specific differences across single cells (Michaiel et al., 2019). […] Our study may help to develop new ways of diagnosis and therapy (Carhart-Harris et al., 2018) by rebalancing of these components.”

In the Introduction we added: “Intriguingly, using optogenetic stimulation of 5-HT neurons in the mouse DRN (Dugué et al., 2014; Kapoor et al., 2016; Matias et al., 2017), only one study in olfactory cortex has shown so far a 5-HT-induced (divisive) gain control of spontaneous firing, without any effect on the gain of stimulus-driven population responses (Lottem et al., 2016). This suggests that DRN activation could separately reduce the weight of ongoing cortical activity relative to evoked activity (Lottem et al., 2016), thereby possibly changing the balance of integration between internal priors (Berkes et al., 2011; Fiser et al., 2010) and external sensory input (Lottem et al., 2016).”

Reviewer #2:

1) My main concern regards the choice of widefield imaging to measure the effects of 5-HT stimulation in V1. Given the nonlinearities in the relationship between firing rates and RCaMP activity, couldn't subtraction (for example) be mistaken for normalization? Electrophysiological recordings are reported, but this is a small sample size, and it's unclear whether these are single-unit (as reported in the Materials and methods) or multi-unit (as reported in the main text) recordings. Related to this, it is not possible to determine the layer of the neurons recorded electrophysiologically, using the techniques reported.

We thank the reviewer for her/his helpful review. We agree with the reviewer’s concern that, given potential nonlinearities in the relationship between firing rates and RCaMP activity, one should be careful in interpreting RCaMP signals with respect to spiking activity, which is, however, frequently ignored in recent studies.

New electrophysiological data added – We have performed a substantial number of new experiments using extracellular recordings of multi-unit activity and recorded firing rates based on well-isolated spikes in a new cohort of animals. The obtained extensive data set (previously 20 MUAs, new sample size in total 212 MUAs) fully supports our previous claims (please see new Figure 3, Figure 3—figure supplement 1, figure 4, Figure 5—figure supplement 2 and 3, Figure 8 and Figure 8—figure supplement 2). For both Ca²⁺ data and MUA data the 5-HT-induced suppression can be accounted for by a two-step normalization process (subtraction of spontaneous activity and scaling the gain of evoked activity, Figure 8di. and dii.). Therefore, potential nonlinearities between the RCaMP signal and firing rates do not affect our previous claims.

Corrected – we now refer to recording depth instead of layers. Thank you for the hint.

2) There is a relatively sparse description of the methods. How were firing rates normalized?

We generally improved explanations of the quantifications and analytical methods. In order to obtain a data format that allows comparison between firing rates and Ca²⁺ widefield imaging signals we employed two types of normalization:

“Traces of spike counts were averaged over time (200 ms bins) and across trials for each recorded condition. […] The normalized traces were then averaged over all the units and animals.”

With respect to contrast tuning we wrote: “Evoked responses to different visual contrasts were normalized to the peak of the evoked response at 100% grating contrast.”

Why are some values > 1?

As described above, all traces were divided by the average of activity obtained in response to the first presented visual stimulus (thus, acting as the reference response to all following stimuli). The mentioned later rise of the RCaMP signal that elevates evoked RCaMP signals to higher values than for the first stimulus, causes amplitude values >1.

I couldn't tell until reading the Materials and methods that mice were anesthetized.

Clarified – We now clarify that anesthetized animals were used directly in the Abstract, as well as in Figure 1 legend, Introduction, Results, and in Materials and methods. We further have now included new experiments where we compare results obtained under anesthesia with results obtained in awake animals (Figures 8 and 9). In this context we phrase: “Hence, the impact of activating the DRN on cortical activity may differ under wakeful conditions compared to conditions where the animals are anesthetized.”

3) 16 s of stimulation is quite long, and could have caused autoreceptor-mediated suppression of 5-HT neurons, producing the late excitatory effects in Figure 2. This could be discussed; ideally, the stimulation parameters should be manipulated in a more physiological range.

Thank you for raising these important points, which we have now addressed in detail in the Discussion.

We think that autoreceptor-mediated suppression is an unlikely mechanism contributing to our results for the following reasons: “Autoreceptor-mediated suppression of 5-HT neurons within the DRN is an unlikely explanation for producing such late increase. […] Second, we show using MUA that spiking activity in V1 is consistently suppressed during photostimulation. Third, the evoked component of visual responses remains suppressed during DRN photostimulation and finally, the late increase of RCaMP signals was selectively blocked by 5-HT2A antagonist.”

With respect to the late excitatory effect we wrote: “We suggest that intracellular Ca²⁺-accumulation of cortical neurons produces the late rise in the RCaMP signal (Eickelbeck et al., 2019) due to 5-HT receptor-mediated activation of the Gq/11 pathway (Jang et al., 2012; Millan et al., 2008) with further activation of store-operated channels (Celada et al., 2013). Finally, the late increase of the RCaMP signal did not affect our conclusions but may be considered when using wide-field Ca²⁺ recordings of cortical activity in future studies.”

We think that the used stimulation parameters are in a physiological range, as much as an experimental manipulation can be per se, in order to derive reasonable effect sizes. However, please note that even though we may drive neurons in the DRN with 20 Hz photostimulation strongly, it was recently shown that units in the intact DRN never fire at or close to 20 Hz in vivo (Grandjean et al., 2019). In this study it is also shown that DRN neurons increase their firing throughout 20 s of 20 Hz photostimulation without adaptation. Altogether, this indicates that DRN neurons may fire with their maximal output but within their physiological limits.

We wrote: “The DRN was photostimulated for 16 s in the first set of our experiments. This is relatively long in comparison to the brisk activation of DRN neurons observed in certain behavioral contexts (Heym et al., 1982; Ranade and Mainen, 2009). However, this does not exclude additional longer-lasting tonic increase in DRN activity under natural conditions. For instance, direct retinal projections to the DRN (Pickard et al., 2015; Ren et al., 2013; Zhang et al., 2016) suggest its regulation well beyond the stimulation time window chosen in our study. In addition, slow periodic changes in 5-HT release occur naturally during day-night cycle (Portas et al., 2000; Tyree and de Lecea, 2017) and depend on seasonal factors (Spindelegger et al., 2012). Importantly, using the ePet-Cre mouse model and comparable photostimulation parameters as in our experiments (i.e. similar blue light intensity and frequency) to activate the DRN via fiber optics, a consistent increase of DRN activity in fMRI and MUA recordings over 20 s of photostimulation was revealed (Grandjean et al., 2019). Prolonged (12s) photostimulation of the DRN in SERT-Cre mice increased perceptual thresholds for tactile stimuli (Dugué et al., 2014), altogether suggesting that sustained or repeated elevation of DRN activity correlates with meaningful and behaviorally relevant changes in neuronal responses (Correia et al., 2017; Lőrincz and Adamantidis, 2017; Miyazaki et al., 2011). “

4) What is the baseline in Figure 6? Is it different for each contrast?

In the revised manuscript the corresponding figure is Figure 8. The baseline that is subtracted from evoked responses to each contrast is derived from the condition that records ongoing activity during photostimulation (S_ph, Figure 8aii., light blue trace). Thus, this baseline is recorded once and is independent of contrast.

Could it change by contrast (e.g. in Figure 2, it looks like there is a pre-stimulus decrease in activity)?

Based on our results, the 5-HT-induced changes in spontaneous activity are proportional to pre-photostimulation firing rates and can be explained by a divisive gain control independent of visual input (Figure 4 and Figure 5—figure supplement 3). Following the linear summation hypothesis, ongoing activity and evoked responses are independent (Arieli, Sterkin, Grinvald, and Aertsen, 1996; Deneux and Grinvald, 2016; Ferezou and Deneux, 2017; Ferezou et al., 2007) and therefore, baseline (ongoing) activity should not be differently affected by different contrasts. Indeed, when using a two-step normalization process that treats these components as independent, we were able to recover the contrast tuning function of control conditions from those under the influence of 5-HT (Figure 8di/ii and Figure 9cii).

Nonetheless, we are aware of recent studies that consider also reciprocal effects of external stimuli on the structure of ongoing activity (Deneux and Grinvald, 2016; Ferezou and Deneux, 2017; He, 2013; Sadaghiani, Hesselmann, Friston, and Kleinschmidt, 2010). However, we felt that discussing this issue would go too far beyond our current findings.

Regarding the part of the reviewer's question in brackets: The pre-stimulus decrease seen in this example reflects the variability in ongoing activity. Please see the newly included other examples for comparison (Figure 2a). This pre-stimulus variability is negligible in comparison to the suppression induced by 5-HT input (Figure 2b, S_ph condition and Figure 3).

5) The references used to support statements in the Introduction and Discussion are peculiar. For example, some of the references in the third paragraph of the Introduction did not study sensory processing or use optogenetics.

Corrected – statements in Introduction and Discussion are now supplemented with adequate references, separating those that used optogenetics and those that did not.

Why must the suppression observed here be mediated disynaptically (Discussion, second paragraph)? Wouldn't work from Gulledge and colleagues (Avesar and Gulldedge, 2012; Stephens, Avesar and Gulledge, 2014; Front Neural Circ 12, 2, 2018) suggest it could be done only using differential expression of different 5-HT receptors in pyramidal neurons?

Possible misunderstanding – we did not suggest that all of the observed suppression was mediated disynaptically. We propose that a major part of the suppression, contributing to controlling response gain, involves activation of 5-HT2A receptors. We suggest that part of this suppression (note that this suppression was blocked by the 5-HT2A antagonist) is mediated via interneurons that are activated via 5-HT2A. Importantly, we mentioned another possible monosynaptic mechanism possibly contributing to suppression of response gain, that is, a 5-HT2A-mediated shunting in pyramidal neurons.

We skipped the terms mono- and di-synaptic, however, to improve clarity.

References added – further, we refer to two of the references suggested by the reviewer in the Discussion: “Thus, reduction in response duration under the influence of 5-HT may indicate involvement of shunting inhibition in pyramidal neurons to effectively control response gain. Suprathreshold excitatory drive by 5-HT2A activation may further be amplified by shaping the duration of 5-HT1A-mediated inhibition (Avesar and Gulledge, 2012; Stephens et al., 2014).”

Reviewer #3:

[…] The topic of the manuscript is of broad interest, the experiments performed and data analysis sound, results intriguing and most conclusions drawn backed up by the data. Overall I think the manuscript is worthy of publication in a very good journal with a broad audience. I have several critiques, questions and observations and hope the authors take them in a constructive way. These do not lessen my overall support of the story.

1) The recordings of the present study were performed under anesthesia. This leads to two issues, first, the visual responses might be different (see Durand et al. 2016 JNeurosci for a comparison of awake vs. anesth visual responses) and second, photostimulation of 5-HT neurons in the anesthetized state might overestimate the effect of DRN photostimulation (in addition to the already unnaturally synchronous stimulation of neurons). Ideally a loss of function experiment in the awake state would nicely complement the results of this study, however I am aware that this might raise several technical concerns.

New experiments added under awake conditions – We thank the reviewer for her/his comments. Motivated by these comments, we performed a new row of experiments, in which we imaged animals in the awake state. We are most happy that these new data further substantiated and elaborated our major previous claims (please see new Figure 9).

We added: “Finally, we explored the extent to which the above conclusion depends on the cortical state. […] Therefore, we recorded cortical activity of awake mice (n=5) that were head-fixed and habituated to walk and stay on a treadmill (using the same experimental paradigm as shown in Figure 8).”

We concluded a comparison between awake and anaesthetized conditions as follows: “We found that normalization of responses in the anesthetized state is achieved with additive contribution of ongoing activity, indicating integration of spontaneous and evoked activity with increased weight of internal priors. In awake mice, normalization is independent of suppression in ongoing activity. This suggests that 5-HT provides a discrete divisive gain control of spontaneous ongoing and evoked visual activity, while preserving information content and regulating the balance between these components depending on the cortical state.”

We agree with the reviewer that a loss of function experiment in the awake state would nicely complement the results, but in view of the many results obtained in our study and the extensive additional data that would be required, we feel that this would go beyond what is feasible in a single study. In addition to the technical difficulties pointed out by the reviewer, it will also be challenging to realize inhibition of DRN neurons within physiological ranges. Certainly, we will follow up on this difficult issue in our future studies.

2) The authors have chosen to use ePet-cre mice, but ePet is not the most specific marker for 5-HT neurons (see two papers from Gabor Nyiri in Brain Struct Funct). This could be discussed in the manuscript, but the effects identified in the pharmacological experiments argue for specific serotonergic effects.

We thank the reviewer for this important remark. In the revised Discussion section we have addressed this concern. We wrote: “It should also be noted that besides 5-HT neurons, subpopulations of glutamatergic cells in the raphe nuclei express ePet (McDevitt et al., 2014; Sos et al., 2017). […] However, as seen in our experiments pharmacological blocking of 5-HT receptors in V1 largely diminished the induced suppressive effects, contribution from other modulatory systems appears negligible for the present study.”

[Editors’ note: what follows is the authors’ response to the second round of review.]

Essential revisions:

1) Subsection “Distinct and independent contribution of 5-HT2A and 5-HT1A receptors to suppression of evoked and spontaneous activity”, first paragraph: The authors claim that the late increase in RCaMP signal that is usually observed following DRN photostimulation is suppressed by the application of MDL, yet do not support this claim with a statistical test.

We removed the qualitative statement and report instead the p-value of a statistical test that compares baseline suppression of controls during DRN photostimulation (S_ph) with S_ph suppression obtained during application of MDL. Specifically, we analyzed the questioned rising part of the RCaMP signal after the initial dip. We found that the rising part of spontaneous activity during MDL application was significantly lower in comparison to controls (p=0.04, two-sample t test). This supports our suggestion of a reduction of intracellular Ca²⁺ accumulation when blocking 5-HT2A receptors and confirms that the late increase in RCaMP signal is partially suppressed by application of MDL.

Furthermore, while the response does remain negative throughout drug application, it is increasing after an initial dip, and this increase cannot be explained by 5-HT1A receptor dynamics since these seem to be constant during photostimulation.

We did not intend to claim that the late increase in the RCaMP signal is completely suppressed or is solely based on 5-HT2A receptor activation. The rising RCaMP signal after the initial dip during 5 HT2A blocking clearly suggests a residual contribution of other 5-HT receptors involved in intracellular Ca²⁺ accumulation that remain active during MDL application. We thank the reviewers for raising this important point that we now have addressed to avoid misunderstanding. As noted above, we removed the previous statement that the RCaMP signal remained negative throughout drug application and added further information about a likely contribution of other 5-HT receptors involved in the rise of the RCaMP signal, both in Results and in the Discussion.

2) I do not understand the analysis that led to the conclusion that normalization is different between anesthetized and awake conditions. Specifically, if V_ph / V is constant (as suggested by the analysis) then (V_ph – S_ph)/ V shouldn't be constant, and vice versa. This could be the case, however, if S_ph is equal to zero. By looking at the traces shown in Figure 8Aii, it seems that at the time of peak evoked response, S_ph is indeed close to 0. Thus, the difference between the two conditions may simply be the result of slower suppression of spontaneous activity or faster evoked responses in the awake states.

We thank the reviewer for this important point, which we address here in more detail. In the manuscript we added a new section about the contribution of spontaneous activity to normalization together with a new supplementary figure (Figure 9—figure supplement 2). To answer this question one needs to consider the suppressive gain of the evoked visual response as an adjusting factor, which we show is different in anesthetized and awake conditions. As suggested, assuming that V_ph/V is constant, the control visual response (V) can be approximated by the 5-HT-induced gain (i.e. the inverse of c) and the visual response during photostimulation (V_ph):

V_ph/V=c→V=1/c×V_ph (1)

Our main hypothesis here is that V_ph is a linear combination of the evoked component (E_ph) and its baseline component (b_ph). Further, we show (Figure 5b.) that b_ph is approximately equal to the suppression in spontaneous activity (S_ph) and that the effect of photostimulation is always suppressive (i.e. g>1).

V_ph=E_ph+b_ph

b_ph≅S_ph (2)

1/c=g→c<1;g>1

Thus, under these considerations Equation 1 can be rewritten as:

V=g(E_ph+S_ph) (3)

V=g×E_ph+g×S_ph (4).

Equation 4, shows that the gain (g) affects both the evoked and the spontaneous component and that normalization depends on their relative weights (see new Figure 9—figure supplement 2.).

Figure 9—figure supplement 2ai and aii. demonstrate how normalization influences the relative contribution of the baseline component (g×S_ph). In the anesthetized state, the weight of the baseline component is significantly larger than in the awake condition (-0.36±0.11, n=18, -0.11±0.02, n=5; p<0.001, two-sample t test). This affects normalization particularly at low contrasts, where the weights of the baseline and evoked components are comparable (Figure 9—figure supplement 2bi). This further suggests that the baseline component in the anesthetized state is a likely candidate for an additive contribution to normalization. In contrast, in the awake state, the weight of the components in Equation 4 is significantly (p<0.01, one-sample t test) biased towards the evoked component (Figure 9—figure supplement 2bii.)

One might argue, however, that the reduced contribution of the baseline component in the awake state is merely due to its smaller value (i.e. S_{ph aw}≤S_{ph an}) at the time of the peak of the evoked response (t_pk). Indeed, as the reviewer noticed correctly, we find that V_ph in the awake state reaches peak intensities significantly earlier than in the anesthetized state (mean over all contrasts: 311±32 ms (n=5 awake mice), 441±41 ms (n=18 anesthetized mice), p<0.001 two-sample t test). Consequently, the amount of suppression in S_ph at t_pk in the awake state, although significant (-0.09±0.03, n=5, p<0.01, one-sample t test), is lower as compared to the anesthetized state (-0.17±0.03, n=18, p<0.001, two-sample t test). To estimate the sensitivity of normalization to changes in the value of the baseline component in the awake state, we considered the same value of S_ph at t_pk as found for the anesthetized state (-0.17, i.e. S_{ph aw}≅S_{ph an}), while all other parameters in Equation 4 were kept the same (note that values of the evoked component do not change during photostimulation, Figure 4biii.). We find that even though the relative weight of the baseline component increases (-0.22±0.03, n=5, p<0.01, one-sample t test), its weight is still significantly smaller than in the anesthetized state (p<0.001 two-sample t test) and also significantly smaller than the weight of the evoked component over all contrasts (Figure 9—figure supplement 2biii.).

S_{ph aw}≤S_{ph an} and g_aw<g_as (5)

Our data suggest a reduction in the overall gain as the major difference between the awake and the anesthetized state (g_aw<g_an), as indicated by significantly decreased suppression of the peak response in the awake (0.75±0.11) compared to the anesthetized state (0.50±0.17, p<0.01 two-sample t test). As implicated by the calculations above and considering Equation 5 a lower gain in the awake state significantly decreases the relative weight of the baseline component [(g×S_ph)_aw <(g×S_ph)_an]. Additionally, as shown in our data, given that for all contrasts (g×E_ph) is significantly higher than (g×S_ph) in the awake state, Equation 4 can be written as

V≅g×E_ph (6).

Consequently, normalization is largely controlled by the gain of the evoked component. This supports our conclusion that in the awake state, through a reduction in the 5-HT-induced gain, the weight of contribution to normalization is biased towards the evoked component and largely achieved without the requirement of a significant additive contribution of the baseline component, as is the case in the anesthetized state (cf. Figures 8di-ii and Figure 9ci and cii).

Author details

1. Zohre Azimi

   1. Optical Imaging Group, Institut für Neuroinformatik, Ruhr University Bochum, Bochum, Germany
   2. International Graduate School of Neuroscience (IGSN), Ruhr University Bochum, Bochum, Germany

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5072-3264

2. Ruxandra Barzan

   1. Optical Imaging Group, Institut für Neuroinformatik, Ruhr University Bochum, Bochum, Germany
   2. International Graduate School of Neuroscience (IGSN), Ruhr University Bochum, Bochum, Germany

   Contribution

   Validation, Investigation, Writing - review and editing, Data acquisition (electrophysiology)

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8021-9330

3. Katharina Spoida

   Department of General Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany

   Contribution

   Conceptualization, Resources, Visualization, Methodology, Data acquisition (DRN electrophysiology)

   Competing interests

   No competing interests declared

4. Tatjana Surdin

   Department of General Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany

   Contribution

   Resources, Construction of AAV virus; In vitro validation of viral constructs

   Competing interests

   No competing interests declared

5. Patric Wollenweber

   Department of General Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany

   Contribution

   Resources, Methodology

   Competing interests

   No competing interests declared

6. Melanie D Mark

   Department of General Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany

   Contribution

   Resources, Supervision, Writing - review and editing

   Competing interests

   No competing interests declared

7. Stefan Herlitze

   Department of General Zoology and Neurobiology, Ruhr University Bochum, Bochum, Germany

   Contribution

   Conceptualization, Resources, Funding acquisition, Methodology, Project administration, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1785-0450

8. Dirk Jancke

   1. Optical Imaging Group, Institut für Neuroinformatik, Ruhr University Bochum, Bochum, Germany
   2. International Graduate School of Neuroscience (IGSN), Ruhr University Bochum, Bochum, Germany

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   dirk.jancke@rub.de

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8440-6259

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