Aurélien Debelle

G Gutierrez

Alexandre Boulle

F Garrido

O Najjar

E Olebunne

F Pallier

C Cabet

L Thomé

Disordering kinetics in

I -Introduction

The late 20 th century to early 21 st century has been described as the Silicon Age, for this element represents the key (semiconductor) material in microelectronics [START_REF] Hull | Properties of crystalline silicon[END_REF][START_REF] Thompson | Moore's law: the future of Si microelectronics[END_REF][3]. In its bulk form, or as a thin layer deposited onto an insulator (so-called silicon on insulator, SOI) [START_REF] Nguyen | A review of SOI technology and its applications[END_REF], it is mainly used to create a PN junction which constitutes the building brick of transistors, diodes, integrated circuits and so on. Those elements are then used to design ever increasingly complex electronic devices. Therefore, Si-based materials are found in various fields of physics and materials science that include, to cite just a few, central processing units, energetic particle detectors (for instance in large-scale accelerator facilities) [START_REF] Dervan | Silicon strip detectors for the ATLAS HL-LHC upgrade[END_REF][START_REF] Moll | Displacement Damage in Silicon Detectors for High Energy Physics IEEE Trans[END_REF], sensors for space applications [START_REF] Morselli | Silicon detectors in space for γ-ray astroparticle physics[END_REF], photovoltaic cells [START_REF] Hall | Silicon photovoltaic cells Solid-State Electronics[END_REF] and lithium batteries [START_REF] Dimov | Practical silicon-based composite anodes for lithium-ion batteries: fundamental and technological features[END_REF][START_REF] Mcgehee W R | Direct-Write Lithiation of Silicon Using a Focused Ion Beam of Li +[END_REF]. For most of these uses, and also for functional design at the nanoscale such as nanobubble formation [START_REF] Maleville | Wafer bonding and H-implantation mechanisms involved in the Smart-cut technology[END_REF] or doping [START_REF] Hull | Properties of crystalline silicon[END_REF][START_REF] Manchester | Doping of silicon by ion implantation[END_REF], silicon is subjected to ion irradiation, an operation during which complex energy deposition processes are involved. These latter may lead to intricate modifications of the material microstructure and can potentially have detrimental effects on its physical properties.

The slowing-down of a charged particle with a low velocity (as compared to the rootmean square velocity of its own electrons) passing through matter can be essentially described by elastic (so-called nuclear or ballistic) collisions between the projectile and the screened nuclei of the target atoms. During this type of interactions, part of the projectile kinetic energy is transferred to target atoms. If this transferred energy is larger than a threshold displacement energy (E d ), the primary knock-on atom is ejected with a velocity sufficient to induce collective displacements of target atoms; this phenomenon is referred to as a collision cascade [START_REF] Wesch | Ion Beam Modification of Solids[END_REF] and the associated slowing-down process is called nuclear stopping power (S n ).

Swift charged particles essentially interact with electrons of the target atoms, which leads to excitations and ionizations, and this slowing-down is usually referred to as electronic stopping power(S e ). Yet, via an electron-phonon coupling, a significant amount of the deposited energy can reach the atomic network, which may produce atomic displacements [START_REF] Wesch | Ion Beam Modification of Solids[END_REF]. Understanding the energy partitioning between the electronic and atomic networks constitutes an important issue to tackle, and it currently represents a hot topic, as demonstrated by a recent review paper on that very subject (see [START_REF] Zhang | Ion irradiation and modification: The role of coupled electronic and nuclear energy dissipation and subsequent nonequilibrium processes in materials[END_REF] and references therein). One reason for this interest lies in the fact that combined -hereafter denoted as S n &S e -effects can take place and these latter are not necessarily additive. In that case, they are frequently referred to as synergistic effects (i.e. the result is not the algebraic sum of the different contributions). A comprehensive description and understanding of these complex phenomena can help designing materials for tailored properties [START_REF] Wesch | Ion Beam Modification of Solids[END_REF][START_REF] Zhang | Ion irradiation and modification: The role of coupled electronic and nuclear energy dissipation and subsequent nonequilibrium processes in materials[END_REF]. One way to address this subject is to perform dual-beam irradiation experiments in order to have both, selected S n and S e components (another option consists in using tens of MeV ions for which both components are present).

It is not in the scope of this paper to provide a review of irradiation-induced disordering or annealing effects in Si (the reader can refer to review papers for that purpose [START_REF] Priolo | Ion-beam-induced epitaxial crystallization and amorphization in silicon[END_REF][START_REF] Pelaz | Ion-beam-induced amorphization and recrystallization in silicon[END_REF]).

Here, we will only recall that Si is highly sensitive to nuclear collisions and undergoes amorphization when irradiated at room temperature (RT) at a fraction of displacement per atom (dpa). In contrast, Si is particularly resistant against ionizing events occurring with highvelocity ions [START_REF] Kamarou | Radiation damage formation in InP, InSb, GaAs, GaP, Ge, and Si due to fast ions[END_REF] (one of the reasons why it is used to detect high-energy particles [START_REF] Allport | Applications of silicon strip and pixel-based particle tracking detectors[END_REF]). Both low- [START_REF] Priolo | Ion-beam-induced epitaxial crystallization and amorphization in silicon[END_REF] and high-velocity [START_REF] Sahoo | Swift heavy ion beam induced recrystallization of amorphous Si layers[END_REF] ions can be used to induce recrystallization of amorphous Si layers at temperatures around 200-400°C. This phenomenon is referred to as the (swift-heavy) ion-beam-induced epitaxial crystallization (SH-IBIEC) phenomenon [START_REF] Priolo | Ion-beam-induced epitaxial crystallization and amorphization in silicon[END_REF][START_REF] Pelaz | Ion-beam-induced amorphization and recrystallization in silicon[END_REF][START_REF] Sahoo | Swift heavy ion beam induced recrystallization of amorphous Si layers[END_REF]. Recently, we even demonstrated that disorder annealing can occur during dual-beam irradiation [START_REF] Thomé | Combined effects of nuclear and electronic energy losses in solids irradiated with a dual-ion beam[END_REF]. More precisely, a substantial quantity of defects generated by nuclear collisions (S n ) are eliminated by the deposited electronic energy of swift ions (S e ). This phenomenon (referred to as SNEEL, which stands for synergy between nuclear and electronic energy-losses) does take place in Si [START_REF] Thomé | Ionization-induced annealing in silicon upon dual-beam irradiation[END_REF]. We showed that its magnitude increases with the flux ratio between the S e -and the S nbeam. In that study, we investigated only the final stage of the amorphisation process, i.e. we used samples irradiated at fluences that would normally lead to full amorphization. In the present paper, we provide complete, quantitative disordering kinetics (under S n and S n &S e irradiations); in addition, we compare bulk Si and Si thin layers deposited onto an oxide substrate.

II -Experimental

The samples used in this study are n-type {100}-oriented Si single crystals with a thickness of 280 µm provided by Neyco (hereafter referred to as Si-b), and Si layers with a thickness of about 500 nm deposited onto a sapphire (Al 2 O 3 ) substrate provided by MTI Corporation (hereafter referred to as Si-tl).

Si-b and Si-tl were irradiated together at RT at the JANNuS-Saclay facility [START_REF] Gentils | Investigating radiation damage in nuclear energy materials using JANNuS multiple ion beams[END_REF] with either a single 900 keV I ion beam (hereafter referred to as S n ) or a dual beam of 900 keV I and 27 MeV Fe ions (hereafter referred to as S n &S e ). The ion fluences were increased up to 3x10 14 cm -2 for I and 5.4x10 14 cm -2 for Fe; the ratio between S e and S n ion fluxes was 1.8 in order to maximize the synergy effect [START_REF] Thomé | Combined effects of nuclear and electronic energy losses in solids irradiated with a dual-ion beam[END_REF]). The irradiation temperature was monitored with thermocouples and with a thermal imaging camera. Simulations of the ion/silicon interactions were performed with the SRIM2011 code in full damage cascades mode [START_REF] Ziegler | The Stopping and Range of Ions in Solids[END_REF], using a threshold displacement energy of 20 eV [START_REF] Holmström | Threshold defect production in silicon determined by density functional theory molecular dynamics simulations[END_REF]. These results are presented and commented in section III.1.

Rutherford backscattering spectrometry in channeling condition (RBS/C) was performed using a 1.4 MeV He ion beam delivered by the ARAMIS accelerator of the JANNuS-SCALP platform at IJClab in Orsay [START_REF] Gentils | Investigating radiation damage in nuclear energy materials using JANNuS multiple ion beams[END_REF]. Experimental spectra were fitted using the McChasy Monte-Carlo code developed at the National Centre for Nuclear Research (NCBJ) in Warsaw [START_REF] Nowicki | Modern analysis of ion channeling data by Monte Carlo simulations[END_REF], with the assumption that a fraction of atoms, f D , are randomly displaced from their regular crystallographic site.

High-resolution X-ray diffraction characterizations were carried out on a Bruker D8 Discover at IRCER in Limoges. A parallel and monochromatic (=0.15406 nm) incident X-ray beam was used to probe the 004 Bragg reflection performing so-called θ-2θ scans.

Experimental data were fitted with the computer code named RaDMaX-Online [START_REF] Souilah | RaDMaX: a graphical program for the determination of strain and damage profiles in irradiated crystals[END_REF][START_REF] Boulle | RaDMaX online: a web-based program for the determination of strain and damage profiles in irradiated crystals using X-ray diffraction[END_REF]. From these simulations, elastic-strain depth profiles were determined in the irradiated samples.

Raman characterizations with a frequency-doubled Nd:YAG (532 nm) laser and a 2400 groove/mm grating were performed for pristine and irradiated samples using an Invia Reflex Renishaw spectrometer coupled to a Leica microscope with a 100x objective. A laser power lower than 0.05 mW was used in order to avoid sample modifications during measurements.

The Raman spectrometer was calibrated by using standard silicon monocrystalline samples.

III -Results

III.1. SRIM results

Figure 1 presents the S n and S e depth profiles of both 900 keV and 27 MeV Fe ions.

Only the first µm is shown because this thickness fully encompasses the region perturbed by I ions, and this work focuses on the evolution of this very region upon sole S n or dual S n &S e irradiations. In this region, the S n component of 900 keV I ions, referred to as S n (I), peaks at 2 keV/nm, which is high enough to induce a significant disorder, as shown in, e.g. [START_REF] Pelaz | Ion-beam-induced amorphization and recrystallization in silicon[END_REF][START_REF] Thomé | Ionization-induced annealing in silicon upon dual-beam irradiation[END_REF][START_REF] Edmondson | Amorphization of crystalline Si due to heavy and light ion irradiation[END_REF] and hereafter. In contrast, S e (I) is below 1 keV/nm, which is far below the threshold level (~37 keV/nm) for significant disordering in Si [START_REF] Kamarou | Radiation damage formation in InP, InSb, GaAs, GaP, Ge, and Si due to fast ions[END_REF]. S n (Fe), which is about 0.1 keV/nm in the first µm, can be neglected in terms of damage creation, as shown in the Supplementary Information (SI) file that presents the RBS/C results for the sole 27 MeV irradiation (Fig. S1), and as reported in [START_REF] Luketic | Investigation of Ion Irradiation Effects in Silicon and Graphite Produced by 23 MeV I Beam Materials[END_REF] with similar ions (23 MeV I). Note that S n (Fe) is more significant at the endof-range of the 27 MeV Fe ions, and at this depth, it does induce disorder, not visible by RBS/C (Fig. S1), but obvious in the Raman cross-section provided in the SI file (see Fig. S2). In contrast, S e (Fe) is ~5.5 keV/nm, a level sufficient to induce defect annealing, as previously reported by the authors in [START_REF] Thomé | Ionization-induced annealing in silicon upon dual-beam irradiation[END_REF], and as further demonstrated hereafter. In summary, the present work considers that only S n (I) creates disorder and S e (Fe) partially heals this disorder.

III.2. RBS/C

Figure 2 (a,b) presents raw and simulated RBS/C data for Si-b and Si-tl irradiated either with a single 900 keV I ion beam (Fig. 2a) or simultaneously with a dual 900 keV I and 27 MeV Fe ion beam (Fig. 2b). Figure 2 (c,d) presents the damage fractions (f D ) extracted from McChasy simulations of RBS/C spectra plotted in Figure 2 (a,b). Data recorded in the case of single I ion irradiation (Fig. 2 a,c) exhibit the presence of a damage peak at a depth of ~250 nm, with a magnitude that increases with the I fluence, for both Si-b and Si-tl. This peak reaches the random level (f D =1) at a fluence of 1.5x10 14 cm -2 , suggesting that the samples are amorphized at 250 nm at (and above) this fluence. The amorphous layer expands towards both the surface and greater depth as the I fluence is further increased (3x10 14 cm -2 ). It is worth mentioning that pristine Si layers are intrinsically slightly defective (because of epitaxial growth defects) and are thus characterized by an initial disorder level higher than that of bulk Si crystals, as indicated by the RBS/C spectra recorded on these samples (compare curves labelled 'virgin' in Fig. 2a).

Data recorded in the case of dual I and Fe ion irradiation (Fig. 2 b,d) show less defective crystals at similar I fluences than in the case of I irradiation alone, and for the two types of materials. Moreover, amorphization of both Si-b and Si-tl is prevented at 1.5x10 14 cm -2 and even at 3x10 14 cm -2 (f D is lower than 1 all over the irradiated region). These results confirm that a synergistic effect takes place in bulk Si irradiated with a dual low-and high-energy ion beam (see Ref. [START_REF] Thomé | Ionization-induced annealing in silicon upon dual-beam irradiation[END_REF]), and they show that this effect also occurs in Si layers.

III.3. XRD

Figure 3 presents XRD data for irradiated Si-b (Fig. 3 a,c) and Si-tl (Fig. 3 b,d). Only XRD curves for which full amorphization was not achieved (as estimated by this technique) are displayed in this figure. Full amorphization was assumed when the scattered intensity became extremely low. An exception was made for some samples where a severely disordered, but still crystalline region at the backside of the amorphized layer was present, allowing an acceptable fit. In Figure 3a, XRD results corresponding to Si-b irradiated with 900 keV I (S n ) are shown. Such type of XRD signal has been extensively described elsewhere [START_REF] Souilah | RaDMaX: a graphical program for the determination of strain and damage profiles in irradiated crystals[END_REF][START_REF] Boulle | RaDMaX online: a web-based program for the determination of strain and damage profiles in irradiated crystals using X-ray diffraction[END_REF][START_REF] Debelle | XRD investigation of the strain/stress state of ion-irradiated crystals[END_REF]. The fringe pattern at low scattering angle indicates the presence of a tensile strain depth profile. This latter can be retrieved by simulating the experimental data (see black solid lines in Fig. 3a), and the corresponding profiles are displayed in the inset of Fig. 3a. It can be noted that both the shape and the depth extension of the strain profiles are in agreement with those of the disorder distributions determined by RBS/C (Fig. 2c), meaning that both techniques provide consistent results. The strain level increases with increasing I fluence, until full amorphization (with the viewpoint of this technique) takes place at 1.5x10 14 cm -2 over 280 nm; this is the reason why the corresponding strain profile is truncated from the surface until this depth.

Figure 3b shows XRD data of I-irradiated Si-tl. The corresponding signals consist in single, broad peaks (because of a thin damaged layer), with a huge asymmetry on the low-angle side.

The right-side component comes from the remaining pristine layer (because the total layer thickness is slightly larger than the damaged thickness), while the left-side component is due to the irradiated, strained part of the layers. Hence, a tensile strain developed in these layers, similar to what happened in the bulk samples (note that the position of the Bragg peak for the pristine layers is not that for the single-crystals because the layers exhibit an intrinsicepitaxial -strain due to the lattice misfit between the Si layer and the sapphire substrate).

Corresponding strain profiles are displayed in the inset of Figure 3b. These profiles (i.e., overall, bell-shape-like profiles) are similar to those found for bulk Si and thus, they also agree with the f D profiles determined by RBS/C. In Fig. 3 (c,d) are plotted similar data as in Fig. 3(a,b) but for dual-beam (S n &S e ) irradiated materials. The abscissae are identical to those used for the single-beam irradiation.

It can hence be readily observed that the signal extension or shift towards low angles is much less pronounced for S n &S e irradiation than it is for S n irradiation alone. This finding indicates that the strain developing during the I&Fe irradiation exhibits a lower level than that measured for I irradiation alone. Strain profiles are displayed in the insets of Figure 3 (c,d).

They globally exhibit a shape similar to that of the sole S n irradiation, but the strain magnitude is much lower. Importantly, it was possible to determine the strain level up to higher fluences, i.e. 1.5x10 14 cm -2 (for S n &S e ) vs 9x10 13 cm -2 (for S n ) in the case of Si-b.

III.4. Raman

Figure 4 shows typical Raman data recorded on pristine and ion-irradiated silicon. The pristine spectrum (Fig. 4a) exhibits the characteristic Raman mode of crystalline silicon: a longitudinal optical (LO) phonon band at 520 cm -1 (c-Si). When a Si crystal is amorphized, the c-Si peak disappears and a broad peak, centred at 480 cm -1 (a-Si), is observed. In the case of single I ion irradiation (S n ), the spectrum recorded at the sample surface (Fig. 4a) exhibits the presence of both c-Si and a-Si peaks. On the contrary, in the case of dual I and Fe ion irradiation (S e ), only the c-Si peak is observed. Figure 4(b,c) presents the 2D Raman intensity distribution (so-called 2D maps) obtained by recording Raman spectra on a cross-section sample as a function of the depth along the I and Fe ion path. Figure 4b corresponds to Si-b irradiated with 900 keV I ions and Fig. 4c to Si-b irradiated with a dual 900 keV I and 27 MeV Fe ion beam; in both cases, the same 3x10 14 cm -2 iodine fluence was used. The Raman signal was recorded over 0.7 µm for each sampling depth point performed every 0.1 µm. Each spectrum of the map is thus the result of the intensity integrated over the laser spot surface. As the damaged depth is smaller than the laser spot size, a signal coming from both the damaged and the pristine parts is always measured. In Fig. 4b,i.e. for the S n irradiation alone, the intensity of the a-Si peak is intense up to a depth of ~350 nm, whereas only the c-Si peak is observed for the S n &S e irradiation (Fig. 4c). For the S n irradiation, the concomitant presence of a-Si and c-Si peaks between 0 and 400 nm can be explained by the laser spot size (0.7 µm). It can be noted that the depth extension of the Raman map is in good agreement with the disorder distribution determined by RBS/C (Fig. 2c), which indicates consistent results between the two techniques.

IV -Discussion

Using three different techniques, namely RBS/C, XRD and Raman, it has been shown that the electronic energy deposition (S e ) due to 27 MeV Fe ions significantly reduces the disorder created by ballistic collisions (S n ) induced by 900 keV I ions when both ion beams are used simultaneously. Hereafter, for a more quantitative description of this effect, we plot the variation of the disorder determined by RBS/C and of the elastic strain derived from XRD as a function of the iodine fluence; these curves are called disordering kinetics.

Figure 5 presents the disordering kinetics obtained from the RBS/C data shown in Figure 2 (i.e. f D as a function of the I ion fluence). Note that, in this figure, f D represents the peak damage measured at around 250-300 nm (for some thin layers where there is no identifiable peak, the disorder was also taken in this depth region). Note also that the intrinsic disorder component in the thin layers has been subtracted to the disorder determined in the irradiated layers. Yet, the results show that f D for Si-tl is always higher than f D for Si-b at the same ion fluence. This feature should be related to the fact that the pristine layers exhibit an intrinsic disorder that is much more pronounced than their bulk counterparts, and this initial disorder may accelerate the disordering process upon irradiation. In the case of I ion irradiation alone, f D increases monotonously but exhibits a sharp rise above ~7x10 13 cm -2 for both Si-b and Si-tl samples; it reaches a value of 1 at 1.5x10 14 cm -2 , meaning that full amorphization occurred at this fluence. As reviewed in [START_REF] Priolo | Ion-beam-induced epitaxial crystallization and amorphization in silicon[END_REF], and later modelled in an original way by Edmondson et al. [START_REF] Edmondson | Amorphization of crystalline Si due to heavy and light ion irradiation[END_REF], amorphization in Si should in fact, upon the current conditions, be heterogeneous, i.e. it proceeds from a multi-step process. In the current work, the variation of f D can indeed be described by a two-step mechanism, similarly to what was done for ionirradiated SiC [START_REF] Debelle | Characterization and modelling of the ion-irradiation induced disorder in 6H-SiC and 3C-SiC single crystals[END_REF] using a dedicated (called MSDA) model [START_REF] Jagielski | Multi-step damage accumulation in irradiated crystals[END_REF]. The fitting result is displayed as a solid blue line in Figure 5 (note that, for clarity purposes, and because the fit was only made for a qualitative description, both sets of data, i.e. Si-b and Si-tl, were fitted together).

The disordering kinetics in the case of dual I and Fe ion irradiation are different from those observed for the sole I irradiation, in the sense that the disorder level is significantly lowered over the entire investigated fluence range for both Si-b and Si-tl. Therefore, even at the highest investigated fluence, f D never reaches unity upon S e &S n irradiation, indicating that amorphization was never completed. It is important to mention, that, even though the maximum disorder is found to be 0.8, a substantial damage annealing did occur, as evidenced by the profiles shown in Fig. 2 (c,d). Another evidence of this annealing can be provided looking at the disorder level at the I fluence of 9x10 13 cm -2 : it is 0.8 after the sole I irradiation, while it does not exceed 0.2 after the dual-beam experiment, which is a significant decrease. Such a very similar reduction in the disorder level has been very recently observed in silicon submitted to 23 MeV I irradiation subsequent to 600 keV I irradiation [START_REF] Luketic | Investigation of Ion Irradiation Effects in Silicon and Graphite Produced by 23 MeV I Beam Materials[END_REF].

Qualitatively, the overall shape of the disordering curves is yet similar to the one observed upon S n irradiation; in particular, the two-step mechanism is still present, although the disordering rate for each step is significantly lowered. It is however important to mention that the f D parameter does not take into account the defect nature, which prevents any firm interpretation of a possible change in the amorphization mechanism. For instance, in bulk Si, it was shown that a different microstructure develops upon dual-beam irradiation as compared to single low-energy irradiation [START_REF] Thomé | Ionization-induced annealing in silicon upon dual-beam irradiation[END_REF]. The thermal energy brought to the system by the electronic energy deposition is supposed to enhance the defect mobility, which leads to both defect reorganization (i.e. new defects, such as dislocations) and recombination. Hence, the disordering process may be different upon the two beam conditions, but a detailed microscopy analysis is required to provide a definitive conclusion. Finally, it is worth mentioning that the disordering rate is higher in Si-tl than it is in Si-b, which suggests that the initial disorder in the layers not only affects the amorphization process upon the sole S n irradiation, but it also decreases the annealing efficiency of the electronic energy deposition process. A similar result was provided in the early 1980's by Svensson et al. who compared the recrystallization taking place in pre-damaged bulk Si and in silicon on sapphire layers submitted to elastic energy deposition at 200 and 300 °C [START_REF] Svenson | Ion-beam induced annealing of radiation damage in silicon on sapphire[END_REF]. Although the annealing mechanism was not similar to the one involved in the current work (IBIEC vs SNEEL), two conclusions that may also hold here were drawn: pre-existing defects in thin layers seem to be highly stable and cannot be annealed upon (any type of) ion irradiation, and those defects most likely stabilize part of the irradiation-induced defects.

Figure 6 presents the strain buildups extracted from the XRD data of Figure 3, where the maximum strain of the profiles shown in Figure 3 is plotted as a function of the I fluence (note that the intrinsic epitaxial strain component in the thin layers has been subtracted to the measured strain). Regarding S n irradiations, the results show that both Si-b and Si-tl exhibit an overall similar behavior (but noticeable differences exist, as discussed hereafter). For both types of materials, the strain increases almost linearly with the I fluence in a first stage, i.e. up to ~7x10 13 cm -2 . This finding is in agreement with the results of a seminal paper on the strain developing during the irradiation-induced amorphization process in Si [START_REF] Speriosu | X-ray rocking curve study of Siimplanted GaAs, Si, and[END_REF]. It is worth mentioning that this fluence corresponds to the one for which the disorder determined by RBS/C dramatically increases (i.e., the beginning of the second step of the amorphization process). Above this fluence, the Si layers are too defective for the strain to be determined; however, for the single-crystals, a maximum strain of ~1 % can still be measured at 9x10 13 cm -2 . Besides, an increase of the strain rate is noticed between 7x10 13 cm -2 and 9x10 13 cm -2 . These results are in agreement with previous works that showed a similar multistep strain buildup (with values very close to those currently measured) in irradiated Si singlecrystals [START_REF] Speriosu | X-ray rocking curve study of Siimplanted GaAs, Si, and[END_REF][START_REF] Bai | Defects production and annealing in self-implanted[END_REF]. Regarding bulk Si versus Si on thin layer, there exists two major differences: the smaller fluence range for which Si layers remains partially crystalline, and the higher strain levels that they systematically exhibit. Thus, the current XRD results tend to indicate that the intrinsic disorder in the thin layers increases the strain rate.

For S n &S e irradiations, strain develops in both types of materials, but the strain rate is significantly decreased as compared to the case of sole S n irradiations. Moreover, the strain can be determined up to the fluence of 1.5x10 14 cm -2 for both Si-b and Si-tl, because the crystalline lattice is less severely damaged than in the case of the S n irradiations alone.

Consequently, the strain levels are systematically lower, i.e., for instance, less than 0.2 % at 9x10 13 cm -2 for Si-b irradiated upon S e &S n as compared to ~1 % at the same fluence upon S n .

At the same fluence, for Si-tl, the maximum strain measured upon S e &S n is lower than 0.4 %, while it was already not anymore measurable during the S n irradiation only. These quantitative results provide additional support of (i) the annealing process occurring upon dual-beam irradiation, and of (ii) the lower efficiency of this process in the thin layers as compared to the single-crystals. The consequence of this dynamic annealing is an increased fluence range over which the (silicon) crystalline structure is maintained, as illustrated in both Figures 5 and6.

.

Conclusion

The amorphization process of Si exposed to ion irradiation was investigated in two cases: (i) using 900 keV I for which the nuclear energy loss (S n ) is dominant, and (ii) with a dualbeam, i.e. 900 keV I and 27 MeV Fe, designed to lead to concomitant electronic (S e ) and nuclear energy depositions. Both bulk Si single crystals (Si-b) and epitaxial Si thin layers (Si-tl) deposited onto sapphire were studied using RBS/C, XRD and Raman techniques. Only the first µm was studied, which is the region where I ions generate disorder. The elastic strain and the disorder fraction were determined in this region as a function of the I fluence. One major, dramatic difference was observed between the disordering kinetics determined for S n irradiation alone on the one hand, and coupled S n &S e experiments on the other hand: while full amorphization was reached at the damage peak at 1.5x10 14 cm -2 in the former case, a partially crystalline lattice was still present at 3x10 14 cm -2 in the latter case. In fact, the disordering rate was significantly reduced upon S n &S e irradiation over the entire investigated fluence range. The strain developing in the S n -irradiated region is also considerably reduced (more than twice), in agreement with a lower disorder fraction, and thus with a lower defect density. The electronic energy deposition (S e ) allows part of the defects generated during elastic collisions (S n ) to be annealed. However, the intrinsic defects present in the epitaxial layers are stable against this energy deposition, and they seem to both increase the disordering rate and decrease the annealing efficiency. This work provides useful data as Si (either in its bulk form or as a thin layer) is widely used as a material for radiation-harsh applications.

Figure 1 Nuclear (S n ) and electronic (S e ) energy losses vs depth for Si irradiated with low-energy I ions (blue and cyan areas, respectively) and high-energy Fe ions (green and yellow areas, respectively). Calculations were performed with the SRIM2011 code [START_REF] Ziegler | The Stopping and Range of Ions in Solids[END_REF]. Online program [START_REF] Boulle | RaDMaX online: a web-based program for the determination of strain and damage profiles in irradiated crystals using X-ray diffraction[END_REF]. Fluences (in cm -2 ) are given next to each curve. In insets are displayed the elastic-strain depth profiles derived from the fits with RaDMaX.

Figure 2 (

 2 Figure 2 (a,b) RBS spectra (Si signal) recorded along random (Si-b, black stars and Si-tl, grey stars) and <001> axial (other symbols) directions on Si-b (dark-blue and dark-red symbols) and Si-tl (lightblue and light-red symbols) irradiated at RT with 900 keV I ions (a) or with 900 keV I ions and 27 MeV Fe ions (b). The numbers are the I fluences (in cm -2 ) used for both S n and S n &S e irradiations. Solid lines are best fits to experimental data using the McChasy code [25]. (c,d) Damage fraction (f D ) as a function of depth, extracted from the fits to experimental RBS/C data of Fig. 2 (a,b), for Si-b (dark-blue and dark-red lines) and Si-tl (light-blue and light-red lines) irradiated at RT with 900 keV I ions (c) or with 900 keV I ions and 27 MeV Fe ions (d).

Figure 3 XRD

 3 Figure 3 XRD signals around the (004) reflection recorded on Si-b (a,c) and Si-tl (b,d). Figures a and b

  correspond to samples irradiated with 900 keV I ions only (S n ), while figures c and d refer to crystals irradiated with both 900 keV I ions and 27 MeV Fe ions (S n &S e ). Experimental data are represented by symbols and solid lines are best fits to those data obtained with the RaDMaX-

Figure 4 (Figure 5

 45 Figure 4

Figure 6 Elastic

 6 Figure 6

Acknowledgments

We acknowledge the French EMIR-A network for providing irradiation beamtime and we grant the JANNuS-Saclay staff for their efficiency in performing the irradiation experiments. We also thank the JANNuS-SCALP platform staff for their help during the RBS/C measurements.

Conflict of interest

Authors declare no conflict of interest at all.

Supplementary Information

Below is the link to the electronic supplementary material.


Julie Boulanger-Bertolus
email: jboulangerbertolus@gmail.com

Sandrine Parrot

Valérie Doyère

Anne-Marie Mouly

Julie Boulanger

Dorsal striatum and the temporal expectancy of an aversive event in Pavlovian odor fear learning

Keywords: Interval timing, odor fear conditioning, respiration, dorsal striatum, dopamine microdialysis

Interval timing, the ability to encode and retrieve the memory of intervals from seconds to minutes, guides fundamental animal behaviors across the phylogenetic tree. In Pavlovian fear conditioning, an initially neutral stimulus (conditioned stimulus, CS) predicts the arrival of an aversive unconditioned stimulus (US, generally a mild foot-shock) at a fixed time interval. Although some studies showed that temporal relations between CS and US events are learned from the outset of conditioning, the question of the memory of time and its underlying neural network in fear conditioning is still poorly understood. The aim of the present study was to investigate the role of the dorsal striatum in timing intervals in odor fear conditioning in male rats. To assess th interval timing ability in this paradigm, we used the respiratory frequency. This enabled us to detect the emergence of temporal patterns related to the odor-shock time interval from the early stage of learning, confirming that rats are able to encode the odor-shock time interval after few training trials. We carried out reversible inactivation of the dorsal striatum before the acquisition session and before a shift in the learned time interval, and measured the effects of this treatment on the temporal pattern of the respiratory rate. In addition, using intracerebral microdialysis, we monitored extracellular dopamine level in the dorsal striatum throughout odor-shock conditioning and in response to a shift of the odor-shock time interval. Contrary to our initial predictions based 2 on the existing literature on interval timing, we found evidence suggesting that transient inactivation of the dorsal striatum may favor a more precocious buildup of the respiratory temporal pattern during the odor-shock interval in a manner that reflected the duration of the interval. Our data further suggest that the conditioning and the learning of a novel time interval were associated with a decrease in dopamine level in the dorsal striatum, but not in the nucleus accumbens. These findings prompt a reassessment of the role of the striatum and striatal dopamine in interval timing, at least when considering Pavlovian aversive conditioning.

Introduction

Learning time intervals is crucial to survival and goal reaching across the phylogenetic tree. In Pavlovian fear conditioning, an initially neutral stimulus predicts the arrival of an aversive unconditioned stimulus, after a time interval that is encoded, a process pertaining to interval timing [START_REF] Molet | Timing: An attribute of associative learning[END_REF][START_REF] Kirkpatrick | Associative learning and timing[END_REF]. How the brain processes and encodes such information remains poorly understood [START_REF] Merchant | Neural Basis of the Perception and Estimation of Time[END_REF]Tallot & Doyère, 2020). From a neurobiological point of view, there is substantial support for the involvement of the dorsal striatum and its dopaminergic inputs in interval timing [START_REF] Buhusi | What makes us tick? Functional and neural mechanisms of interval timing[END_REF], both from lesion experiments of the dorsal striatum or intrastriatal infusion of dopaminergic antagonists [START_REF] De Corte | Striatal dopamine and the temporal control of behavior[END_REF][START_REF] Meck | Neuroanatomical localization of an internal clock: A functional link between mesolimbic, nigrostriatal, and mesocortical dopaminergic systems[END_REF], and from lesion or optogenetic manipulation of the substantia nigra pars compacta (SNc), the primary source of dorsostriatal dopamine [START_REF] Meck | Neuroanatomical localization of an internal clock: A functional link between mesolimbic, nigrostriatal, and mesocortical dopaminergic systems[END_REF][START_REF] Soares | Midbrain dopamine neurons control judgment of time[END_REF].

Electrophysiological recordings of single neurons in the dorsal striatum of rats also show that striatal neurons firing rate is correlated with the duration of the time interval between signaling cue and reward [START_REF] Bakhurin | Differential Encoding of Time by Prefrontal and Striatal Network Dynamics[END_REF][START_REF] Gouvêa | Striatal dynamics explain duration judgments[END_REF][START_REF] Matell | Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons[END_REF][START_REF] Mello | A Scalable Population Code for Time in the Striatum[END_REF], and intrastriatal muscimol infusions produce an impairment in the ability to discriminate durations [START_REF] Gouvêa | Striatal dynamics explain duration judgments[END_REF]. In the context of fear conditioning, using 2-Deoxyglucose (2-DG) metabolic mapping we previously showed that odor-shock pairing in rats was associated with an increase in 2-DG uptake in the dorsal striatum [START_REF] Boulanger Bertolus | Infant rats can learn time intervals before the maturation of the striatum: Evidence from odor fear conditioning[END_REF]. Furthermore, recent work recording oscillatory neural activity in the dorsal striatum in Pavlovian fear conditioning correlated its maximum power in theta and gamma bands with the time at which the rat expected the aversive stimulus [START_REF] Dallérac | Updating temporal expectancy of an aversive event engages striatal plasticity under amygdala control[END_REF]. Timing in fear conditioning is also associated with plasticity in the striatum [START_REF] Dallérac | Updating temporal expectancy of an aversive event engages striatal plasticity under amygdala control[END_REF].

Notably, a majority of studies investigating the neurobiological substrate of interval timing in rodent models rely on operant conditioning. Such protocol relies heavily on the motor response of the subject, which could bias our understanding of the neural substrate of interval timing per se. Indeed, the striatum and cortico-striatal inputs are also a neural substrate for motor and procedural learning [START_REF] Barnes | Activity of striatal neurons reflects dynamic encoding and recoding of procedural memories[END_REF][START_REF] Koralek | Temporally Precise Cell-Specific Coherence Develops in Corticostriatal Networks during Learning[END_REF][START_REF] Martiros | Inversely Active Striatal Projection Neurons and Interneurons Selectively Delimit Useful Behavioral Sequences[END_REF], and action selection when the task involves temporal discrimination [START_REF] Howard | Dynamic Nigrostriatal Dopamine Biases Action Selection[END_REF]. To avoid these possibly confounding factors, we used a non-striatum-dependent behavioral measure, the respiratory frequency, to assess the interval timing ability in a Pavlovian fear conditioning associating an odor to a mild footshock. Indeed, the pattern of respiratory frequency has been shown to be a good index temporal expectation of the shock arrival [START_REF] Boulanger Bertolus | Infant rats can learn time intervals before the maturation of the striatum: Evidence from odor fear conditioning[END_REF][START_REF] Dupin | Respiration and brain neural dynamics associated with interval timing during odor fear learning in rats[END_REF]Shionoya et al., 2013). This allowed us to look more closely at the role of dorsal striatum and its dopamine level in the initial acquisition of an interval duration, as well as when a change in this duration is applied. Based on the existing literature, we made two hypotheses 1) inactivating the dorsal striatum should impair timing behavior and its adaptation to a new interval duration and 2) dopamine level in the dorsal striatum should increase when a new interval duration is introduced. We report that, while a transient inactivation of the striatum did alter the expression of the temporal pattern of respiration, and dopamine level in the striatum was indeed modulated during the learning of a new duration, the directions of the effects were the opposite of those hypothesized. These findings prompt a reconsideration of the role of the striatum and striatal dopamine in interval timing, at least when considering Pavlovian aversive conditioning.

Methods

Animals

Twenty-five pair-housed and fifteen single-housed male Long Evans rats (Janvier, France) contributed data for experiment 1 and 2 respectively. They weighed 250-300 g at the start of the

Surgery

Details of the procedures can be found in the supplementary methods. Briefly, animals were anesthetized, received subcutaneous local analgesia and were placed in a stereotaxic frame. For experiment 1, rats were implanted bilaterally in the dorsal striatum with stainless steel guide cannulae. For experiment 2, rats were implanted unilaterally (left side) with a guide cannula targeting the dorsal striatum. To assess the specific involvement of the dopaminergic system innervating the dorsal striatum in this task, control rats were implanted in the nucleus accumbens which receives abundant dopaminergic inputs, albeit from another source, the ventral tegmental area (VTA). All animals were allowed two weeks of post-surgical recovery. During this period, the suffering was detected, the animal was injected with 2-4mg/kg carprofen i.p.

Experimental apparatus and paradigm

The experimental cages (described in previous studies [START_REF] Hegoburu | Differential dynamics of amino acid release in the amygdala and olfactory cortex during odor fear acquisition as revealed with simultaneous high temporal resolution microdialysis[END_REF][START_REF] Hegoburu | The RUB cage: Respiration ultrasonic vocalizations behavior acquisition setup for assessing emotional memory in rats[END_REF] and detailed in the supplementary methods) consist of a whole-body plethysmograph for Experiment 1 and Plexiglass cylinder for Experiment 2, both customized with tubing in the ceiling connected to a programmable custom olfactometer, and a shock floor. In this setup, rats underwent odor fear conditioning. Twenty-four hours later, they received 6 presentations of the odor alone to assess their learned fear to the odor (Retention test). Forty-eight hours after conditioning, they were re-injected with the same drug they received previously, and trained in a Shift session where they received 1 odor-shock pairing with a 20-s odor-shock interval followed by 9 odor-shock pairings with a 30-s interval. B) Training protocol for Experiment 2. The microdialysis probe was inserted in the left dorsal striatum or left nucleus accumbens and the animals were placed in the experimental cage for a 3h probe equilibration period after which they were trained with 6 Odor-Shock pairings with a 20-s interval, followed with a single Odor-Shock pairing with a 30-s interval.

For Experiment 1 (Figure 1A), after familiarization to the conditioning cage, the animals received a Conditioning session (ten odor-shock pairings with a 20s odor-shock interval), a

Retention test (six odor presentations) and a Shift session (one 20-s odor-shock pairing, followed by nine 30-s odor-shock pairings) at 24h intervals. They were injected with 0.5 µL of either lidocaine (2%, Sigma-Aldrich France, in sterile saline 0.9%, Lidocaine group, n = 13) or saline (Control group, n = 14) just before the Conditioning and Shift sessions. During each session, the For Experiment 2 (Figure 1B), after a 3-hour probe equilibration period, rats received a conditioning session including six 20-s odor-shock pairings, followed by one 30-s odor-shock pairing. Dialysates from the dorsal striatum (n = 7) and the nucleus accumbens (n = 8) were collected every 2 min.

At the end of the experiment, the animals were sacrificed with a lethal dose of pentobarbital for histological verification of the canulae tips localization (Figure S1 and S2 for Experiment 1 and 2 respectively).

Data acquisition, pre-processing and analysis

In Experiment 1, the respiratory signal and behavior were analyzed as described before [START_REF] Boulanger Bertolus | Infant rats can learn time intervals before the maturation of the striatum: Evidence from odor fear conditioning[END_REF]. We assessed the effects of treatment on the temporal dynamics of the respiratory frequency from the odor onset to shock arrival. For this analysis, the time course of the respiratory frequency, in 1-s time bins, during the 19 seconds of the odor-shock interval was compared using a two-way ANOVA with Group (Lidocaine or Control) as an independent factor, and Time (1 to 19 seconds) as a repeated measure factor. During the Retention test, the freezing rate was analyzed using a two-way ANOVA with Group as an independent factor, and Period (Pre-Odor vs Odor) as a repeated measure factor. For the Shift session, a three-way ANOVA was performed with Group as an independent factor, and Time (1 to 19 seconds) and Interval (20s vs 30s) as repeated measures factors.

In Experiment 2, microdialysis data were acquired as previously described to accurately correlate the neurochemical data with the behavioral events [START_REF] Parrot | High temporal resolution for in vivo monitoring of neurotransmitters in awake epileptic rats using brain microdialysis and capillary electrophoresis with laser-induced fluorescence detection[END_REF][START_REF] Hegoburu | Differential dynamics of amino acid release in the amygdala and olfactory cortex during odor fear acquisition as revealed with simultaneous high temporal resolution microdialysis[END_REF][START_REF] Hegoburu | High Temporal Resolution Brain Microdialysis as a Tool to Investigate the Dynamics of Interactions Between Olfactory Cortex and Amygdala in Odor Fear Conditioning[END_REF], using homemade concentric microdialysis probes (see supplementary methods) continuously infused with artificial cerebrospinal fluid (aCSF). Dialysates were collected in PCR tubes rinsed with an acidic preservative medium, and stored at -30°C until analysis using ultra-high-performance liquid chromatography (see supplementary methods).

Data were expressed as percentage of the baseline obtained by averaging the dopamine concentrations measured in the seven samples collected before the start of the conditioning.

Changes in dopamine concentration were then analyzed using a two-way ANOVA with Structure (dorsal striatum or nucleus accumbens) as an independent factor, and Time as a repeated measure factor.

All ANOVA results are reported in the legend of the corresponding figures. For all statistical comparisons performed, post-hoc pairwise comparisons were carried out when allowed by the ANOVA results, the significance level being set at 0.05.

Results

Experiment 1: Reversible inactivation of the dorsal striatum during the shift session hastens the adaptation of the respiratory temporal curve to the new interval duration

We previously showed that adult rats submitted to an odor fear conditioning exhibit a typical temporal respiratory frequency pattern (using 1-s time bins) during the odor-shock interval, consisting in a rapid respiratory frequency increase upon odor delivery and a U-shaped decrease just before shock arrival [START_REF] Boulanger Bertolus | Infant rats can learn time intervals before the maturation of the striatum: Evidence from odor fear conditioning[END_REF]Shionoya et al., 2013). We assessed the effects of dorsal striatum inactivation on this respiratory temporal pattern.

During the Conditioning session, rats with lidocaine-inactivated dorsal striatum exhibited the typical temporal respiratory frequency pattern as early as within the first 3 trials following the first odor-shock presentation (Figure 2A). Within-group comparisons showed that the respiratory rate increased in response to odor arrival in both groups (p < 0.05 from second 4 on), but contrary to the Control group, the Lidocaine group showed a U-shaped decrease preceding shock arrival (significant difference between seconds 8-10 and seconds 15-18). Importantly, the temporal patterns of respiration were similar in both groups by the end of the session, as well as in subsequent odor presentations (Figure S3). Furthermore, during the Retention test, 24h later, both the experimental and control groups showed a significant increase of freezing to the odor compared to the pre-odor baseline (Figure 2B), suggesting a similarly strong odor-shock association in the two groups.

For the Shift session, we compared the mean respiratory frequency temporal pattern obtained during the two first trials (in which the two groups expected the shock at 20s and presented similar respiratory patterns, see Figure S3C) with that obtained during the next three odor-shock pairings during which the animals experienced the shock at 30s. The data showed an early adaptation to the new duration in the Lidocaine group, but not in the Control group (Figure 2C). The scalar rule, a hallmark of interval timing according to which the error in estimating a duration is proportional to the timed duration, predicts a superior superposition of patterns of responses to different time intervals when the time axis is normalized than when it is absolute (Gibbon, 1977). To assess this, the time axis for the 30-s data was multiplicatively rescaled to fit that of the 20-s data (Figure S4) and superposition was indexed by eta-squared ( 2 ) as described before [START_REF] Boulanger Bertolus | Infant rats can learn time intervals before the maturation of the striatum: Evidence from odor fear conditioning[END_REF][START_REF] Brown | Effects of intratrial stimulus change on fixed-interval performance: The roles of clock and memory processes[END_REF]Shionoya et al., 2013). This analysis indicated that the scalar property was respected for the Lidocaine group, but not for the Control group, further confirming that the shift occurred earlier in the Lidocaine group (Figure S4A). Importantly, by the end of the Shift session the temporal patterns of the respiratory response were not different between groups, and the scalar property was respected for both group (Figure S4B).

Together, these data suggest that reversible inactivation of the dorsal striatum hastens an adaptation of the respiratory temporal curve to a newly presented interval duration. presentation (Pre-Odor) and during the 6min during which 20-s odor presentations are applied at the beginning of each minute (Odor). The ANOVA confirmed a significant effect of Period (F1,24 = 175.4, p < 0.001), but no effect of Group (F < 1) and no significant Period x Group interaction (F1,24 = 2.24, p = 0.15). $ Significant difference between Pre-Odor and Odor periods, p<0. Experiment 2: Modulation of striatal dopamine level during the acquisition of a new duration

We then monitored dopamine content in dorsal striatum and nucleus accumbens using intracerebral microdialysis with a 2-min sampling rate, during the acquisition session. The session included seven odor-shock pairings, six pairings with a 20-s odor-shock interval and the last pairing with a 30-s odor-shock interval. Such analysis revealed significant differences in dopamine modulation throughout the session, between the dorsal and ventral (nucleus accumbens) striatum (Figure 3A). Structure-specific analyses showed significant modulation of the dopamine level throughout the conditioning in the dorsal striatum, but not in the nucleus accumbens. Post-hoc analysis in the dorsal striatum showed that dopamine level decreased from the beginning of the conditioning, reaching significant differences from baseline from sample 5 (3 rd odor-shock presentation) to 10 (except sample 9) after conditioning onset. Dopamine level then slowly reincreased for samples 11 and 12. Interestingly, the last odor-shock pairing for which the interval was shifted to 30s instead of 20s (sample 13) was associated with a significant drop in dopamine level (significant difference with preceding sample, p = 0.046, and following sample, p = 0.016, Figure 3B). More specifically, this drop was observed for 6 out of 7 animals (Figure 3B right panel).

Discussion

In the present study, we investigated how reversible inactivation of the dorsal striatum impacts the learning of novel time intervals using the respiratory frequency to assess male oral expectation in an olfactory fear conditioning paradigm. We further investigated the modulations of striatal dopamine extracellular level in that task. Contrary to our hypotheses, we found that reversible inactivation of the dorsal striatum was associated with a hastening of the adaptation of the respiratory frequency temporal pattern during the odor-shock interval. We also showed that the fear conditioning and the learning of a novel interval duration were associated with decreases of dopamine level in the dorsal striatum, while no change in dopamine level was observed in the nucleus accumbens.

In line with the literature [START_REF] Davis | Temporal specificity of fear conditioning: Effects of different conditioned stimulus-unconditioned stimulus intervals on the fear-potentiated startle effect[END_REF][START_REF] Dìaz-Mataix | Detection of a Temporal Error Triggers Reconsolidation of Amygdala-Dependent Memories[END_REF][START_REF] Drew | Temporal control of conditioned responding in goldfish[END_REF][START_REF] Dupin | Respiration and brain neural dynamics associated with interval timing during odor fear learning in rats[END_REF][START_REF] Hegoburu | High Temporal Resolution Brain Microdialysis as a Tool to Investigate the Dynamics of Interactions Between Olfactory Cortex and Amygdala in Odor Fear Conditioning[END_REF][START_REF] Laurent-Demir | Paradoxical facilitatory effect of fornix lesions on acquisition of contextual fear conditioning in mice[END_REF][START_REF] Ohyama | Learninginduced plasticity in deep cerebellar nucleus[END_REF]Tallot et al., 2020), our results support the assumption that learning a time interval happens early in conditioning, and further suggest that the expression of that learning can be modulated by the dorsal striatum. Indeed, inactivation of the dorsal striatum hastened behavioral adaptation of the animal to a novel duration. Importantly, individual differences observed in response to the shift under lidocaine inactivation (Figure 2C) were not associated with differences in the cannula placement (Figure S1), suggesting they may instead result from interindividual variability in timing abilities (see [START_REF] Dupin | Respiration and brain neural dynamics associated with interval timing during odor fear learning in rats[END_REF] for a discussion of timing abilities and associated brain dynamics).

This result suggests that an intact dorsal striatum allows the preservation of the temporal behavioral response pattern to the previously learned time interval at the detriment of the shift of the pattern toward the new duration. This may seem inconsistent with the existing literature.

Indeed, electrophysiological recordings in the dorsal striatum during interval timing tasks have consistently shown that the activity of striatal neurons is correlated with the behavioral temporal response [START_REF] Bakhurin | Differential Encoding of Time by Prefrontal and Striatal Network Dynamics[END_REF][START_REF] Gouvêa | Striatal dynamics explain duration judgments[END_REF][START_REF] Matell | Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons[END_REF][START_REF] Mello | A Scalable Population Code for Time in the Striatum[END_REF]. Furthermore, lesioning or inactivating the striatum abolishes temporal performance of subjects trained to lever-press for food at a fixed interval [START_REF] Meck | Neuroanatomical localization of an internal clock: A functional link between mesolimbic, nigrostriatal, and mesocortical dopaminergic systems[END_REF], or to discriminate between durations [START_REF] Gouvêa | Striatal dynamics explain duration judgments[END_REF]. However, these studies have in common that they rely on operant conditioning tasks that require extensive training of the animal. Importantly, lesions of the dorsal striatum impair the expression of both innate and learned motor sequences [START_REF] Bailey | The Role of Striatum in Initiation and Execution of Learned Action Sequences in Rats[END_REF][START_REF] Cromwell | Implementation of Action Sequences by a Neostriatal Site: A Lesion Mapping Study of Grooming Syntax[END_REF]. Consequently, in operant tasks, the specific role of the striatum in the encoding of time cannot be investigated independently from the motor execution of a timed response. Here, using a non-motor task -Pavlovian fear conditioning -and assessing the animals behavioral temporal response through respiration, allowed us to overcome this confound, uncovering a previously undescribed role for the striatum. Our results also concur with previous findings indicating that measuring the respiratory response is relevant to understand the brain activity associated with emotions [START_REF] Dupin | New Insights from 22-kHz Ultrasonic Vocalizations to Characterize Fear Responses: Relationship with Respiration and Brain Oscillatory Dynamics[END_REF][START_REF] Moberly | Olfactory inputs modulate respiration-related rhythmic activity in the prefrontal cortex and freezing behavior[END_REF], including in the context of interval timing [START_REF] Dupin | Respiration and brain neural dynamics associated with interval timing during odor fear learning in rats[END_REF]. As animals were first conditioned to a 20-s interval duration and then shifted to a 30-s duration, one may wonder whether the respiratory patterns observed for these two durations could reflect non-specific changes in performance with trials repetition instead of temporal adaptation to the new duration. However, this is unlikely, as we have shown previously that the respiration curves obtained in animals trained only with a 30-s interval were similar to those of animals shifted to a 30-s interval after training with a 20-s interval as in the present study [START_REF] Boulanger Bertolus | Infant rats can learn time intervals before the maturation of the striatum: Evidence from odor fear conditioning[END_REF][START_REF] Dupin | Respiration and brain neural dynamics associated with interval timing during odor fear learning in rats[END_REF].

Importantly, another difference between the present work and previous studies is that most of them used appetitive conditioning to probe the role of striatum in interval timing, while we used an aversive one. Interestingly, [START_REF] Dallérac | Updating temporal expectancy of an aversive event engages striatal plasticity under amygdala control[END_REF] used a Pavlovian aversive conditioning task, and reported a decreased synaptic plasticity in the striatum when the expected time interval was shifted to a new duration. That study also showed that the amygdala was activated by a shift to a novel interval to time [START_REF] Dallérac | Updating temporal expectancy of an aversive event engages striatal plasticity under amygdala control[END_REF][START_REF] Dìaz-Mataix | Detection of a Temporal Error Triggers Reconsolidation of Amygdala-Dependent Memories[END_REF], and its inhibition resulted in a faster shift toward the new learned duration. Here, we show that, ak inhibiting the striatum resulted in a speeding of the shift of the behavioral pattern towards the new duration. Together, our data and those of [START_REF] Dallérac | Updating temporal expectancy of an aversive event engages striatal plasticity under amygdala control[END_REF] suggest that the disengagement of the dorsal striatum, possibly under the control by the amygdala, might facilitate flexible temporal behaviors in Pavlovian aversive conditioning.

Dallérac et al suggested ( 2017) that this disengagement of the dorsal striatum could be facilitated by dopamine-regulated plasticity [START_REF] Calabresi | Dopamine-mediated regulation of corticostriatal synaptic plasticity[END_REF][START_REF] Tritsch | Dopaminergic Modulation of Synaptic Transmission in Cortex and Striatum[END_REF].

Using intracerebral microdialysis of dopamine, we were able to show that dopamine level in the dorsal striatum, but not in the nucleus accumbens, decreases when the animal learns the odorshock association, and when the time interval is changed. A few studies have shown that the dorsal striatum might be involved in fear conditioning [START_REF] Jeanblanc | Differential involvement of dopamine in the anterior and posterior parts of the dorsal striatum in latent inhibition[END_REF][START_REF] Kathirvelu | Effects of lentivirus-mediated CREB expression in the dorsolateral striatum: Memory enhancement and evidence for competitive and cooperative interactions with the hippocampus[END_REF][START_REF] Matsumoto | Two types of dopamine neuron distinctly convey positive and negative motivational signals[END_REF][START_REF] White | Mnemonic functions of dorsal striatum and hippocampus in aversive conditioning[END_REF]. On the other hand, although a few studies have suggested its possible involvement in Pavlovian fear conditioning [START_REF] Fadok | Long-Term Memory for Pavlovian Fear Conditioning Requires Dopamine in the Nucleus Accumbens and Basolateral Amygdala[END_REF][START_REF] Wendler | The roles of the nucleus accumbens core, dorsomedial striatum, and dorsolateral striatum in learning: Performance and extinction of Pavlovian fear-conditioned responses and instrumental avoidance responses[END_REF], the nucleus accumbens has been mostly implicated in appetitive conditioning (for a review see [START_REF] Schultz | Reward functions of the basal ganglia[END_REF]. It might be argued that the observed decreases in dopamine levels in the dorsal striatum were related to non-temporal cognitive processes, such as the mere learning of the odor-shock association or the novelty of the experience. However, changing the interval duration without changing other elements of the association resulted in a further decrease in dopamine level (highlighted in figure 3B), supporting

the assumption that dopamine in the dorsal striatum is indeed modulated by the temporal manipulation. Of note, in our study, dopamine level was analyzed every two minutes, which does not allow to ascribe the observed changes to the arrival of the odor or of the shock specifically.

Nevertheless, this sampling rate permitted a dynamic assessment of dopamine level that revealed a transient change in response to the shift in duration that had not been described before. These data suggest that the dopamine decrease observed in the dorsal striatum could contribute to support two distinct phenomena: the learning of the association itself (or the development of the behavioral response to that learning), which is associated with a progressive decrease in dorsostriatal dopamine, and the detection of a change in the temporal relationships of the elements of the association, which is associated with a transient dopamine decrease.

Conclusion

The findings of our study suggest that inactivation of the dorsal striatum hastens the behavioral adaptation of the respiratory response to the time interval embedded in an aversive conditioning. They further indicate that this behavioral adaptation is likely associated with a decreased release of dopamine in the dorsal striatum. Furthermore, they are in stark contrast to our initial predictions based on the existing literature and suggest a need to rethink the role of the striatum and striatal dopamine in interval timing. This discrepancy further calls attention to the advantage for the field to diversify the tasks and behaviors used to study interval timing in order to discriminate between the brain structures involved in the learning of time intervals and those necessary for the expression of these learned time intervals.

determined as the inverse of the respiratory cycle (inspiration plus expiration) duration, averaged on a second by second basis, and synchronized to the odor arrival and shock delivery using TTL signals. The video signal collected through the four video cameras was acquired with homemade acquisition software using the Matrox Imaging Library and a Matrox acquisition card (Morphis QxT via a LabView homemade software that had been validated by comparison to hand scoring by an . Data were analyzed using scripts in Python.

Data analysis

We assessed the effects of treatment on the temporal dynamics of the respiratory frequency in presence of the CS odor. For this analysis, the time course, in 1-second time bins, of the respiratory frequency during the 19 first seconds of the odor presentation was compared using a two-way ANOVA with the group (Lidocaine vs Control) as an independent factor and the time (seconds 1 to 19) as a repeated measure factor. Post-hoc pairwise comparisons were then carried out when allowed by the ANOVA results. For all statistical comparisons performed, the significance level was set at 0.05.

During the Retention test, the conditioned fear response was assessed by comparing the amount of freezing per minute before and during the odor introduction, using a two-way ANOVA with the group as an independent factor and the period (Pre-Odor vs Odor) as a repeated measure factor. Pairwise comparisons were then carried out when allowed by the ANOVA results.

EXPERIMENT 2: Microdialysis during odor fear conditioning

Animals

Twenty-one male Long Evans rats (Janvier Labs, France), weighing 250-300 g at the start of the experimentation were used for this experiment (6 animals were excluded for wrong positioning of the probe or technical problem during the session). They were individually housed in the environmental conditions described above.

Surgery

The animals were anesthetized with ketamine (70 mg/kg) and xylazine (6 mg/kg) administrated by intraperitoneal injection, and placed in a stereotaxic frame (Stoelting, USA). Before head skin incision, lidocaine (1% solution; Sigma-Aldrich, Saint-Quentin Fallavier, France) was administered subcutaneously for local anesthesia. The rats were implanted unilaterally (left side) with a guide cannula for microdialysis probe (CMA12, Phymep, France) and positioned 3.5 mm above the targeted location of the dialysis membrane tip, whose final stereotaxic coordinates from [START_REF] Paxinos | The rat brain in stereotaxic coordinates[END_REF], relative to bregma, were as follows: dorsal striatum AP: 0.6 mm; L: 3.5 mm; DV: -5.7 mm from dura) or nucleus accumbens (AP: 2 mm; L: 1.2 mm; DV: -7.6 mm from dura). The cannula was fixed to the skull with dental acrylic cement and anchored with two surgical screws. Stylets of the length of the guide cannula were inserted in it to prevent clogging. The animals were allowed 2 weeks of postsurgical recovery during which they were regularly handled and habituated to the experimental chamber for 20 min daily during the four days preceding the microdialysis experiment. Microdialysis on behaving animals requires long tubing (0.9-1.2 m). At a given flow rate, the dead volume of these tubing (i.e. the tubing volume between the dialysis membrane and the outlet of the probe) results in a dead time that must be taken into account to accurately correlate the neurochemical data with the behavioral events [START_REF] Parrot | High temporal resolution for in vivo monitoring of neurotransmitters in awake epileptic rats using brain microdialysis and capillary electrophoresis with laser-induced fluorescence detection[END_REF][START_REF] Hegoburu | Differential dynamics of amino acid release in the amygdala and olfactory cortex during odor fear acquisition as revealed with simultaneous high temporal resolution microdialysis[END_REF][START_REF] Hegoburu | High Temporal Resolution Brain Microdialysis as a Tool to Investigate the Dynamics of Interactions Between Olfactory Cortex and Amygdala in Odor Fear Conditioning[END_REF], estimated to be ~ 2 min.

Microdialysis procedure

Experimental apparatus

The apparatus has been described in a previous study [START_REF] Hegoburu | Differential dynamics of amino acid release in the amygdala and olfactory cortex during odor fear acquisition as revealed with simultaneous high temporal resolution microdialysis[END_REF]. It consisted of a Plexiglas transparent cylinder (diameter = 21 cm, height = 21.5 cm) with a lateral door placed in a sound-attenuating cage. The ceiling of the cage was perforated with a central aperture allowing the passage of microdialysis tubing and the branching of three Tygon tubing connected to the programmable custom olfactometer described for experiment 1. The bottom of the cage was equipped with the shock floor as described above and connected to an exhaust fan allowing continuous evacuation of the odorant stream from the cage with four video cameras (B/W CMOS PINHOLE camera, Velleman, Belgium) placed at each corner of the sound-attenuating cage.

Experimental paradigm

On the day of the experiment, the microdialysis probe was inserted into the guide-cannula (Dorsal striatum group : n = 7, Nucleus Accumbens group: n = 8) and the animal was introduced in the experimental cage described in experiment 1. After a 3-hour probe equilibration period, the conditioning session was initiated (Figure 1B). Six odor-shock pairings with a 20-s CS-US interval were presented, with an intertrial interval of 4 minutes. An additional pairing was then presented using a 30s CS-US interval. All along the session, dialysates were collected every 2 min in PCR tubes previously rinsed with an acidic preservative medium. The samples were immediately stored at -20°C. Once all the samples were collected, they were transferred into a -30°C freezer until analysis. These procedures permit to limit greatly the degradation of DA from oxidation due to heat, light and the non-acidic aCSF matrix. Of note, even though the paradigm was conducted in a plethysmograph, the microdialysis tubing prevented the sealing of the plethysmograph and thus the collection of the respiratory signal in this experiment.

Microdialysis samples analysis

The dialysates were analyzed using ultra-high-performance liquid chromatography (UHPLC).

Dopamine, 1-octanesulfonic acid (OSA), triethylamine (TEA), ethylene diamine tetra-acetic acid (EDTA) disodium salt, and sodium hydroxide were purchased from Sigma (St. Louis, MO, USA), potassium dihydrogenphosphate and methanol U-HPLC gradient grade from Fisher Scientific (Loughborough, UK). Ultrapure water was produced using a Milli-Q system (Millipore, Bedford, MA, USA). Standard solutions of 1 mmol/L of dopamine wer °C as aliquots in 0.1 mol/L hydrochloric acid.

The UHPLC system consisted of a Prominence degasser, a LC-30 AD pump and a SIL-30AC autosampler (Shimadzu, Tokyo, Japan). Detection was carried out at 40°C using a Decade II electrochemical detector fitted with a 0.7 mm glass carbon working electrode, a salt-bridge Ag/AgCl reference electrode, and a 25 m spacer (cell volume 80 nL, Antec, Leyden, The Netherlands). Separations were performed at 40°C (in detector oven) using a 100 × 0.32 mm Kappa Hypersil Gold 1.9 m C18 column (Thermo Scientific). The mobile phase, which was adapted from [START_REF] Ferry | Analysis of microdialysate monoamines, including noradrenaline, dopamine and serotonin, using capillary ultra-high performance liquid chromatography and electrochemical detection[END_REF], consisted of 0.14 mol/L potassium phosphate, 0.1 mmol/L EDTA, 6 mmol/L OSA, 0.01% TEA (v/v), pH adjusted to 5 with 10 mmol/L sodium hydroxide, 6% methanol, filtered through a 0.22 m cellulose acetate membrane before elution at 8.5 µL/ min.

Analytes were detected at an oxidation potential of 700 mV versus the reference electrode.

Chromatograms were acquired at a rate of 10 Hz using Lab Solutions software. The acquisition time was 22 min. The injection volume was 1 µL. The sample analysis started the same day of the microdialysis collection to prevent dopamine degradation as much as possible, as 25 samples were collected per animal. In some rare cases of chromatographic matters, the analysis was postponed, but not later than 2 days after collection. On the day of analysis, the samples were placed in the autosampler and kept at +4°C before injection. Concentrations of dopamine were calculated using a day calibration curve. Data were expressed as percentage (mean ± SEM) of the baseline obtained by averaging the dopamine concentrations measured in the seven samples collected before the start of the conditioning session. Changes in dopamine concentration were then analyzed using a two-way ANOVA with the structure (dorsal striatum or nucleus accumbens)

as an independent factor and the time as a repeated measure factor. Post-hoc pairwise comparisons were then carried out when allowed by the ANOVA results.

Supplementary Figures

Figure 1 :

 1 Figure 1: A) Training protocol for Experiment 1. After a period of habituation to the experimental setup for four 20-min sessions, animals were injected with either lidocaine or vehicle in the dorsal striatum, and immediately trained with 10 Odor-Shock pairings using a 20-s odor-shock interval (Conditioning session).Twenty-four hours later, they received 6 presentations of the odor alone to assess their learned fear to the odor (Retention test). Forty-eight hours after conditioning, they were re-injected with the same drug they received previously, and trained in a Shift session where they received 1 odor-shock pairing with a 20-s odor-shock interval followed by 9 odor-shock pairings with a 30-s interval. B) Training protocol for Experiment 2. The microdialysis probe was inserted in the left dorsal striatum or left nucleus accumbens and the animals were placed in the experimental cage for a 3h probe equilibration period after which they were trained with 6 Odor-Shock pairings with a 20-s interval, followed with a single Odor-Shock pairing with a 30-s interval.

Figure 2 :

 2 Figure 2: A) Respiratory frequency time course during the 20-s Odor-Shock interval of the Conditioning session, pooled over the 2nd, 3rd and 4th trials (as shown on the schema over the graph), for the Lidocaine (red) and Control (blue) groups. The baseline (B, black dots) corresponds to the average respiratory frequency over the 25s preceding the odor onset. A two-way ANOVA revealed a tendency for a significant Group x Time interaction (F18,450 = 1.54, p = 0.07). Filled dots are significantly different from baseline, p<0.05. Inserts represent individual curves. # Significant difference between designated points, p<0.05. B) Mean percentage of freezing per minute during the 2min period preceding the first odor

  05. C) Early shift: Respiratory frequency time course during the 20-s (dark colors; first 2 trials) versus 30-s (light colors; following 3 trials). Odor-Shock interval at the early stage of the Shift session, for the Lidocaine group (Left panel, red) and the Control group (Right panel, blue). A three-way ANOVA confirmed a significant Interval x Time x Group interaction (F18,450 = 1.84, p = 0.019). Follow-up analyses showed a significant Interval x Time interaction in the Lidocaine group (F18,216 = 8.57, p < 0.001), but not in the Control group (F < 1). (D) Late shift: Respiratory frequency time course during the 20-s (dark colors; first 2 trials) versus 30-s (light colors; last three trials) Odor-Shock intervals at the late stage of the Shift session, for the Lidocaine group (Left panel, in red) and the Control group (Right panel, in blue). The analysis showed an Interval x Time interaction comparing the 20-s trials with the last three trials of the shift (F18,450 = 64.19, p < 0.001), but no Group x Time interaction (F18,450 = 14.57, p = 0.13) nor Group x Interval x Time interaction (F18,450 = 12.41, p = 0.54), confirming that both groups shifted their anticipatory response towards the new interval by the end of the Shift session. Filled dots are significantly different from baseline (i.e. black dots, p<0.05). * Significant between intervals difference (p<0.05).

Figure 3 :

 3 Figure3: A. Dopamine level in the dorsal striatum (circles, black) and the nucleus accumbens (triangles, grey) during Experiment 2. Dopamine level is measured every two minutes and expressed as a percentage of baseline level measured during the 14min preceding the first Odor-Shock presentation (grey filled symbols). The session included six 20-s Odor-Shock pairings (O1 to O6, green vertical lines) and one 30-s Odor-Shock pairing (Shift, blue vertical line). A two-way ANOVA revealed a significant difference between Structures (F1,13 = 9.79, p = 0.008), as well as a significant Structure x Time interaction (F24,312 = 1.55, p = 0.050). Further analyses within each structure revealed a significant effect of Time in the dorsal striatum (F24,144 = 2.17, p = 0.003), but not in the nucleus accumbens (F24,168 = 1.24, p = 0.22). Black filled dots are significantly different from the baseline (p<0.05). B. Individual curves of the dopamine levels in the dorsal striatum (black, top) and the nucleus accumbens (grey, bottom). The right panels show a zoom on the 30-s Odor-Shock pairing (Shift).

Figure S1 :

 S1 Figure S1: Localization of the tip of the injectors in Experiment 1 for rats in the Lidocaine group (red) and the Control group (green).

Figure S2 :

 S2 Figure S2: Localization of the microdialysis membranes in Experiments 2 for the rats implanted in the dorsal striatum (left panel) and the nucleus accumbens (right panel).

Acknowledgements

This work was supported by the Centre National de la Recherche Scientifique, by Partner BEX CORTEX (ANR-11-LABX-0042) of -11-IDEX-0007) operated by the French National Research Agency. JBB was supported by the Department of Anesthesiology of the University of Michigan when writing this article. The authors warmly thank Ms Ounsa Jelassi-Ben Hellal for her continuous care of animals and Ms Morgane Gallet and Cyrielle Audiane for their technical help.

Author contributions

JBB, SP and AMM designed the study, did the experiments, carried out the analyses and wrote the manuscript; VD discussed the data, commented and edited the manuscript.

Supplementary Material Supplementary Methods

Experiment 1: Inactivation of the dorsal striatum during odor fear conditioning Animals Data were collected from 27 male Long Evans rats (Janvier, France), weighing 250-300 g at the start of the experimentation (2 animals were used and excluded due to wrong positioning of the injection cannulae). They were housed in pairs at 23°C and maintained under a 12h light dark cycle (lights on from 7:00 a.m. to 7:00 p.m.). Experiments were performed during the light phase. Food and water were available ad libitum. All experiments and surgical procedures were conducted in strict accordance with the 2010/63/EU Council Directive Decree and the French National Committee (87/848) for care and use of laboratory animals. The experiments were carried out under the approval of Direction of Veterinary Service (#69000692), and care was taken at all stages to minimize stress and discomfort to the animals.

Surgery

Animals were anesthetized with Equithesin, a mixture of chloral hydrate (127 mg/kg, i.p.) and sodium pentobarbital (30 mg/kg, i.p.), administrated by intraperitoneal injection, and placed in a stereotaxic frame (Stoelting, USA). Before head skin incision, lidocaine (1% solution; Sigma-Aldrich, Saint-Quentin Fallavier, France) was administered subcutaneously for local anesthesia.

Rats were implanted bilaterally with stainless steel guide cannulae (23G, Phymep, France) positioned 1.5 mm above the targeted location of the injection needle tips in the dorsal striatum, whose final stereotaxic coordinates from [START_REF] Paxinos | The rat brain in stereotaxic coordinates[END_REF] relative to bregma, were as follows: AP: 0.6 mm; L: 2.8 mm; DV: -4.5 mm from dura. The cannulae were fixed to the skull with dental acrylic cement and anchored with surgical screws. Stylets of the length of the guide cannula were inserted in it to prevent clogging. The animals were allowed two weeks of post-surgical recovery.

Experimental apparatus

The apparatus has been described in a previous study [START_REF] Hegoburu | The RUB cage: Respiration ultrasonic vocalizations behavior acquisition setup for assessing emotional memory in rats[END_REF]. It consisted of a whole-body customized plethysmograph (diameter 20cm, height 30cm, EmkaTechnologies, France) placed in a sound-attenuating cage. The ceiling of the plethysmograph was equipped with a tower which allowed the introduction of three Tygon tubing connected to a programmable custom olfactometer. Deodorized air flowed constantly through the cage (2L/min), a ventilation pump drawing air out of the bottom of the plethysmograph. When programmed, an odor (McCormick Pure Peppermint; 2 L/min; 1:10 peppermint vapor to air) was introduced in the air stream through the switching of a solenoid valve (Fluid automation systems, CH-1290 Versoix, Switzerland). The bottom of the plethysmograph was equipped with a shock floor connected to a behavior was monitored with four video cameras (B/W CMOS PINHOLE camera, Velleman, Belgium) placed at each corner of the sound-attenuating cage.

Experimental paradigm

Subjects were submitted to a 7d experimental paradigm consisting of 4d of Habituation to the conditioning cage (20min/day), followed by a Conditioning session, a Retention test and a Shift session (Figure 1A) at 24h intervals. During the Conditioning session, the animals were allowed free exploration for 4min, then received ten odor-shock trials during which the conditioned stimulus (CS), a peppermint odor, was introduced into the cage for 20s, the last second of which overlapped with the delivery of a 0.4 mA foot-shock, the unconditioned stimulus (US), with an intertrial interval of 4 minutes. During the Retention test, after a 2-min odor-free period in the experimental cage (equipped with new visual cues and with a plastic floor to avoid contextual fear expression), the CS was then presented 6 times for 20s with a 1-min intertrial interval. During the Shift session, the animals were re-conditioned by receiving a first odor-shock trial using the previously learned 20s interval, after which nine odor-shock trials were carried out with a new (30s) CS-US interval. During the different steps of t respiration were continuously monitored and recorded for offline analysis.

Pharmacological inactivation of the dorsal striatum

Five minutes prior to the Conditioning and Shift sessions, animals were injected with 0.5 µL of either lidocaine (2%, Sigma-Aldrich France, dissolved in sterile saline 0.9%, injection rate 0.5 µL/min, Lidocaine group, n = 13) or saline (Control group,n = 14). Injection needles (30G) extended 1.5 mm from the tip of the guide cannulae, and were connected via polyethylene tubing to two 10-mL Hamilton microsyringes driven by an automated microinfusion pump (Harvard Apparatus, France). After the injection, the needles were left in position for an additional minute to enable diffusion of the solution into the brain tissue.

At the end of the experiment, the animals were sacrificed with a lethal dose of pentobarbital for histological verification of the canulae tips.

Data acquisition and pre-processing

The respiratory signal collected from the plethysmograph was amplified and sent to an acquisition card (MC-1608FS, Measurement Computing, USA; Sampling rate = 1000 Hz) for storage and offline analysis. The detection of the respiratory cycles was achieved using an algorithm described in a previous study [START_REF] Roux | Respiratory cycle as time basis: An improved method for averaging olfactory neural events[END_REF]. Momentary respiratory frequency was 26