L Andolfatto
email: loic.andolfatto@lurpa.ens-cachan.fr

S Lavernhe
email: sylvain.lavernhe@lurpa.ens-cachan.fr

J R R Mayer

Evaluation of servo, geometric and dynamic error sources on five axis high-speed machine tool

Keywords: Machine tool, geometric errors, servo errors, dynamic errors, high-speed machining

Many sources of errors exist in the manufacturing process of complex shapes. Some approximations occur at each step from the design geometry to the machined part.

The aim of the paper is to present a method to evaluate the effect of high speed and high dynamic load on volumetric errors at the tool center point.

The interpolator output signals and the machine encoder signals are recorded and compared to evaluate the contouring errors resulting from each axis follow-up error. The machine encoder signals are also compared to the actual tool center point position as recorded with a non-contact measuring instrument called CapBall to evaluate the total geometric errors. The novelty of the work lies in the method that is proposed to decompose the geometric errors in two categories: the quasi-static geometric errors independent from the speed of the trajectory and the dynamic geometric errors, dependent on the programmed feed rate and resulting from the machine structure deflection during the acceleration of its axes.

The evolution of the respective contributions for contouring errors, quasi-static geometric errors and dynamic geometric errors is experimentally evaluated and a relation between programmed feed rate and dynamic errors is highlighted.

Introduction

High speed machining is known to reduce machining time and improve surface quality, due to its particular cutting process [START_REF] Lavernhe | Kinematical performance prediction in multi-axis machining for process planning optimization[END_REF]. The ability to control the tool orientation with respect to the workpiece also leads to productivity improvements.

The manufacturing process includes several steps. First, the part to machine, generally described by a digital model, is used to generate the appropriate tool path for machining via a computer-aided machining software. This step generally comes with approximations in the part geometry: a complex shape can be interpolated and discretized, leading to differences between the generated tool path and the numerical model of the part.

The post processing of the computer-aided machining file is required to convert the tool path into CNC commands. The tool path, originally described in the workpiece coordinate system (WCS) must be transformed in the joint coordinate system (JCS). This inverse kinematic transformation is most often performed during the post processing or sometime directly calculated by the NC-unit, but in any case, approximations may occur [START_REF] Lavernhe | Kinematical performance prediction in multi-axis machining for process planning optimization[END_REF][START_REF] Lavernhe | Optimization of 5axis high-speed machining using a surface based approach[END_REF].

Then, the NC-unit interpolates the given tool path expressed in the JCS to provide synchronous and dynamically admissible input for the machine drives. Each machine axis is subject to follow-up errors, leading to orientation and position errors of the tool [START_REF] Lavernhe | Kinematical performance prediction in multi-axis machining for process planning optimization[END_REF].

The machine structure, in its quasi-static state, suffers from link and motion errors causing position and orientation errors of the tool [START_REF] Abbaszadeh-Mir | Theory and simulation for the identification of the link geometric errors for a five-axis machine tool using a telescoping magnetic ball-bar[END_REF][START_REF] Bringmann | Machine tool calibration: Geometric test uncertainty depends on machine tool performance[END_REF][START_REF] Zargarbashi | Single setup estimation of a five-axis machine tool eight link errors by programmed end point constraint and on the fly measurement with capball sensor[END_REF]. Moreover, thermal variations of the machine is another source of errors [START_REF] Schmitz | Case study: a comparison of error sources in high-speed milling[END_REF].

When programmed feed rate and actual velocity increase, as is usual during the high-speed machining process, the dynamic solicitations of the structure become higher because of the acceleration of the different parts of the machine. This may result in some alterations of the machine geometry, causing further tool position and orientation errors [START_REF] Altintas | Virtual machine tool[END_REF][START_REF] Cano | A new approach to identifying the elastic behaviour of a manufacturing machine[END_REF].

Finally, the forces appearing during the cutting process lead to tool deflection, causing another source of machined surface location error [START_REF] Schmitz | Case study: a comparison of error sources in high-speed milling[END_REF].

Schmitz et al. compared the contributions of the geometric, thermal, controller and cutting forces errors to inaccuracies on a three-axis geometry, using different methods and instruments to measure and evaluate the respective contributions at different programmed feed rates [START_REF] Schmitz | Case study: a comparison of error sources in high-speed milling[END_REF].

Zhu et al. identified the repeatable errors of machine tool using B-spline models using a cross-grid scale system [START_REF] Zhu | Machine tool component error extraction and error compensation by incorporating statistical analysis[END_REF]. Ibaraki et al. identified kinematic errors of a five axis machine tool from geometric errors of finished workpieces and compared the results to ball bar measurements [START_REF] Ibaraki | Machining tests to identify kinematic errors on five-axis machine tools[END_REF]. Bringmann and Knapp measured the relative tool center point (TCP) deviations between a sphere and a nest of four linear probes to calibrate a five axis machine tool [START_REF] Bringmann | Model-based 'chase-the-ball' calibration of a 5-axes machining center[END_REF]. Erkan and Mayer used the machine own touch trigger probe to measure a set of sphere of uncalibrated relative position to calibrate the machine and assess its positioning performance [START_REF] Erkan | Volumetric distortion assessment of a five-axis machine by probing a 3D reconfigurable uncalibrated master ball artefact[END_REF]. Finally, Schwenke et al. provide a comprehensive overview of other measurement method to identify machine tool error in [START_REF] Schwenke | Geometric error measurement and compensation of machines-an update[END_REF].

A method to evaluate the contributions of error sources to the Cartesian volumetric errors at the tool center point of a five axis machine tool at different programmed feed rates is described in this paper. The Cartesian volumetric errors are defined as the three components of the vector from the theoretical position of the TCP relative to the workpiece frame to its actual position. They are decomposed into the contribution of three error sources:

• the effect of follow-up errors of the axis drives, later called contouring errors and written δ c ;

• the quasi-static geometric errors of the machine, which include link and motion errors and thermal drift, written δ qs ;

• the dynamic geometric errors, resulting from the machine structure deflection under dynamic load, and written δ d .

The evaluation of those three error sources can help quantifying the relative impact of dynamic errors to the total volumetric errors, and the relevance of an associated model for corrective actions.

The paper begins with a presentation of the principle of the method is presented. Then, the mathematical models and the hypothesis drawn to evaluate each error source is developed. The experimental setup is described and finally, the results gathered from low to high speed motion are given and discussed.

Principle of the method

The nominal position of the tool center point relative to the workpiece is evaluated with the nominal direct kinematic transformation (DKT) of the machine fed with the controller inputs of the machine.

The actual position of the tool relative to the workpiece is measured with a non-contact sensor called CapBall, developed in house [START_REF] Zargarbashi | Single setup estimation of a five-axis machine tool eight link errors by programmed end point constraint and on the fly measurement with capball sensor[END_REF], which provides the position of a ball mounted on the machine table relative to the TCP.

The difference between the nominal and the actual position of the tool relative to the workpiece, pictured on Fig. 1, is due to the servo-errors of each axis of the machine and to all the geometric defects of the machine structure. This difference corresponds to the sum of δ c , δ qs and δ d , respectively the contouring error, the quasi-static geometric error and the dynamic geometric error.

The contouring error δ c can be evaluated by recording the machine controller inputs and encoder actual values 3and comparing the relative position of the tool and the workpiece from the two points of view.

At low velocity, the dynamic geometric errors δ d can be considered negligible because the dynamic load is low with respect to the usual high stiffness of machines. Thus, once contouring errors have been accounted for, the remaining errors measured at a low programmed feed rate can be defined as the quasi-static geometric errors δ qs .

Finally when the programmed feed rate and the machine velocity increase, alterations of the machine structure under dynamic load cause the dynamic geometric errors δ d . They can be evaluated by measuring the total geometric errors along a single trajectory at different programmed feed rates and removing the contouring error and quasi-static geometric error contributions.

Model for error contributions

Decomposition of the total errors

During a measurement sequence, n points, equally distributed, are recorded on each of the three channels of the CapBall. The CapBall readings provide the values of the 3 components of the measured difference between P t -the actual tool center point -and P w -the actual center of the master ball mounted on the machine table -, written τ for each of the n recorded points (see Fig. 1):

τ = P t -P w (1)
The results are gathered in a n × 3 matrix written χ, as shown in eq.( 2):

χ =    τ 1 T . . . τ n T    (2)
where τ k is the CapBall reading for k-th point of the trajectory. The effect of the master ball and sensing head set-up positioning errors on volumetric errors are previously identified with the method described in [START_REF] Zargarbashi | Single setup estimation of a five-axis machine tool eight link errors by programmed end point constraint and on the fly measurement with capball sensor[END_REF][START_REF] Andolfatto | Adaptive Monte Carlo applied to uncertainty estimation in five axis machine tool link errors identification with thermal disturbance[END_REF] and removed from χ.

The direct kinematic transformation (DKT) associated with the nominal machine geometry and the five axis controller inputs allows to calculate:

• the position of P t,nom -the nominal TCP -relative to the machine frame, considering the machine at its nominal geometry;

• the position of P w,nom -the nominal master ball center -also relative to the machine frame and also considering the machine with no geometric defect.

The difference of position between those two points can be expressed as τ nom calculated with the axis controller inputs (see Fig. 1 and eq.( 3)).

τ nom = P t,nom -P w,nom (3)
τ nom = DKT (C nom , A nom , Y nom , X nom , Z nom ) (4)
The nominal difference matrix χ nom -calculated from the controller inputs -is formed as described in eq. [START_REF] Zargarbashi | Single setup estimation of a five-axis machine tool eight link errors by programmed end point constraint and on the fly measurement with capball sensor[END_REF].

χ nom =    τ nom,1 T . . . τ nom,n T    (5)
Then, the difference between χ and χ nom expresses the effect of the contouring error, the quasi-static geometric error and the dynamic geometric error, as explicited in Fig. 2 and eq.( 6):

χ -χ nom = δ c + δ qs + δ d (6)

Contouring error

The actual effect of follow-up errors on Cartesian volumetric errors is defined by the contouring error ǫ, which is the orthogonal deviation of the actual tool path with respect to the controller inputs tool path in the part coordinate system [START_REF] Sencer | Modeling and control of contouring errors for five-axis machine tools.Part I: modeling[END_REF]. The difference between Cartesian follow-up error and contouring error is schematically depicted in Fig. 4: in case 1, the follow-up errors along x and y are smaller than in case 2, but the resulting contouring error ǫ 1 is higher than ǫ 2 .

The difference τ enc is calculated for each point, considering the direct kinematic transform of the machine at its nominal geometry and the encoder values:

τ enc = P t,enc -P w,enc (7)

Controller input TCP position

Actual TCP positioncase 1

Actual TCP positioncase 2 Controller input tool path

x y ± 1,x ± 1,y ± 2,y ± 2,x ² 1 ² 2
Fig. 4: Schematic example of the difference between axis by axis Cartesian follow-up error δ and contouring error ǫ (adapted from [START_REF] Sencer | Modeling and control of contouring errors for five-axis machine tools.Part I: modeling[END_REF]).

τ enc = DKT (C enc , A enc , Y enc , X enc , Z enc ) (8)
The encoder actual values volumetric difference matrix is built by the same process as in eq.( 5):

χ enc =    τ enc,1 T . . . τ enc,n T    (9)
The contouring error is evaluated by computing the difference between the nominal volumetric difference matrix χ nom and the encoder actual values volumetric difference matrix χ enc .

The controller input signals must be synchronised with the encoders actual values to evaluate the effect of the follow-up errors on the volumetric errors at the tool tip without taking into account the delay introduced by the recording process of the axis controllers signals. The recordings performed show that the delay between encoder signals and controller inputs signals was 18 ms regardless of the programmed feed rate F . The encoder volumetric difference matrix χ enc is obtained by bringing backward the encoder values by 18 ms. The synchronised controller inputs and encoders volumetric errors are plotted on Fig. 3.

The contouring error along the experimental trajectory is given by eq.( 10): where δ c has a n×3 size, representing the contouring error expressed in the machine frame. Combining eqs.( 6) and ( 10) allows to express the quasistatic geometric error and the dynamic geometric error as the difference of the recorded signals using eq.( 11):

δ c = χ enc -χ nom (10)
P w P t O m δγ Y δβ A δγ A δα Z δβ Z δα C δβ C
χ -χ enc = δ qs + δ d (11)
3.3. Quasi-static geometric errors

Definition

The quasi-static geometric error δ qs is defined as the geometric error independent of the machine velocity. It is decomposed into three sources:

• the link errors that represents the axis to axis location errors of the machine;

• the motion errors of each axis;

• the thermal drift of the machine.

Consequently, the quasi-static geometric error is written as:

δ qs = δ l + δ m + δ td ( 12
)
where δ l , δ m and δ td are respectively the contribution of the link errors, the motion errors and the thermal drift.

Link errors

Mir et al. proposed a model to express the effect of axis-to-axis link errors on volumetric errors [START_REF] Abbaszadeh-Mir | Theory and simulation for the identification of the link geometric errors for a five-axis machine tool using a telescoping magnetic ball-bar[END_REF]. In this model, the link errors for a five axis machine tool are described by a set of eight geometric errors of the machine structure. For the example in Fig. 5, the link errors are:

• δγ Y , the out-of-squareness between X and Y;

• δα Z , the out-of-squareness between Y and Z;

• δβ Z , the out-of-squareness between X and Z;

• δβ A , the tilt of A around y;

• δγ A , the tilt of A around z;

• δα C , the tilt of C around x;

• δβ C , the tilt of C around y;

• δy C , the offset of A relative to C in y.

They are gathered in an array written δq l :

δq l = (δγ Y δα Z δβ Z δβ A δγ A δα C δβ C δy C ) T ( 13
)
The model is based on a Jacobian principle. The volumetric errors due to the eight link errors of the machine at a pose k, written as a three components column vector τ l,k , is given by eq.( 14):

τ l,k = J l,k • δq l (14)
where J l,k is the link errors Jacobian matrix expressed at a pose k. More details are available in [START_REF] Abbaszadeh-Mir | Theory and simulation for the identification of the link geometric errors for a five-axis machine tool using a telescoping magnetic ball-bar[END_REF][START_REF] Zargarbashi | Single setup estimation of a five-axis machine tool eight link errors by programmed end point constraint and on the fly measurement with capball sensor[END_REF]. Zargarbashi and Mayer described a method using CapBall data to identify the eight machine errors [START_REF] Zargarbashi | Single setup estimation of a five-axis machine tool eight link errors by programmed end point constraint and on the fly measurement with capball sensor[END_REF][START_REF] Andolfatto | Adaptive Monte Carlo applied to uncertainty estimation in five axis machine tool link errors identification with thermal disturbance[END_REF]. This method is also used here to identify the eight parameters of the model. Then, for each known pose of the machine, corresponding to the encoder actual values, the link errors Jacobian matrix J l,k and then τ l,k are calculated, leading to the expression for the contributions of the link errors δ l (eq.( 15)):

δ l =    τ l,1 T . . . τ l,n T    (15)
where δ l has a n × 3 size, representing the three Cartesian components of the modelled contribution of the link errors to the volumetric errors at each point along the trajectory.

Motion errors

A reference thermal state of the machine, in which the value of the drift is considered to be zero, must be chosen for a test at low programmed feed rate. Then, the portion of measured errors during this test not explained by the link errors is calculated by eq.( 16) and is attributed to the motion errors and local dynamic errors.

χ -χ enc -δ l = δ m + δ d δ td = 0 (16)
In [START_REF] Bringmann | Machine tool calibration: Geometric test uncertainty depends on machine tool performance[END_REF], Bringmann and Knapp proposed a Fourier series to model the motion errors of a link. Slamani et al. proposed a polynomial model for motion errors in [START_REF] Slamani | Modeling and experimental validation of machine tool motion errors using degree optimized polynomial including motion hysteresis[END_REF]. In both cases the effects of motion errors are defined by continuous and smooth mathematical functions. In order to evaluate the volumetric contribution of motion errors, a polynomial model is used. The only aim of this model is to locally predict the effect of the five axes motion errors on volumetric errors along the experimental trajectory to subtract it from the measured volumetric errors. The polynomial method proved to be easier to implement while providing satisfactory results.

The dynamic geometric error proved to be negligible at a low programmed feed rate (compared to link and motion errors), and they are visible only locally 4 along the trajectory, as depicted in Fig. 6.

A normalised path parameter t n is created to describe the experimental trajectory. It has n linearly distributed components, from 0 for the first point to 1 for the last point. The residual errors matrix is curve-fitted with polynomial functions of t n . The approximation leads to 3 identified polynomials P x , P y and P z . The applied polynomial curve fitting leads to a filtering of local dynamic errors and measurement noise.

Experimental results show that, for the machine tested, 20 was a suitable value for the degree of the polynomial. Below 20, the curve fitting did not represent the residual 4 Dynamic geometric error mainly appears at the beginning and the end of a trajectory, and at sharp corners.

errors well, and above 20, some unexpected oscillations appeared. The model predicted contribution of motion errors is compared to actual measurement in Fig. 6.

The contributions of motion errors to volumetric errors δ m are modelled in eq.( 17):

δ m =         P x (
        ( 17
)
where t n,k is the k-th component of the normalised path parameter.

The main weakness of this method is to compute motion error contributions based on the time instead of the actual pose of the machine at each point. However, the small differential rate of the contributions of the motion errors reduces the effect of the approximation used.

Thermal drift

Even if a warm-up is performed and care is taken to favour the thermal stability of the machine, a small thermal drift can be present.

As the execution of an experimental trajectory can take less than 15 s, it can be considered as instantaneous compared to the movement of the sensing head due to thermal drift. From that point of view, the effect of the thermal drift on the volumetric errors can be modelled as an offset from the reference thermal state on the measured volumetric errors. For each test, this offset is given by the mean value of the difference between the measured deviation χ and the encoder only prediction with a nominal model, the modelled link errors and the motion errors contributions, as expressed in eq.( 18):

td = 1 n n i=1 i χ -i χ enc -i δ l -i δ m ( 18
)
where i χ is the i-th line of the matrix χ.

Finally, the drift, defined as constant for all the measurement point of a test is expressed by a n × 3 matrix δ td , composed of n lines equal to td:

δ td =    td . . . td    (n×3) (19)

Dynamic geometric errors

The dynamic geometric errors are here defined as the additional errors occurring when programmed feed rate, and so dynamic forces on the machine structure, increases. The dynamic errors result from varying alterations of the machine components under dynamic forces such as deflection of the machine structure.

Eqs.( 6) and ( 12) allow to express the dynamic geometric errors δ d as the contribution that does not show at low speed, in eq.( 20):

δ d = (χ -χ enc ) -δ qs (20)

Experimental setup and conditions

Machine tool

This study was carried out on a Huron KX8-five five axis machine tool depicted in Fig. 7. This machine has a WCAYFXZT structure, with a 45-degree-tilted A rotary axis. It is equipped with a Siemens Sinumerik 840D Powerline numerical command unit. The NC unit allows the recording of system variables such as axis controller inputs and encoder actual values for each axis (X,Y,Z,A and C). The machine documentation specifies that both axis controller inputs and encoder actual values already include backlash compensations [START_REF] Siemens | D -List of System Variables -Parameter Manual[END_REF], so this potential source of error is not included in this study.

Previous tests show that the axis controller inputs remain the same for each execution of a program. Thus, the recording of controller inputs can be performed separately. Finally, all 10 channels (5 for the controller input and 5 for the encoder actual values) are gathered.

The NC cycle time is 3 ms and the sampling frequency of the CapBall is 10 kHz. To accurately synchronise and compare all the signals, the 10 NC signals are linearly interpolated at 10 kHz. A point is added at the beginning of the experimental trajectory to provide a tag dedicated to synchronisation of all signals together. More details are given at the end of subsection 4.3.

External measuring instrument

The CapBall consists of a precision master ball mounted on the table and a sensing head fitted with three capacitive sensors, mounted in a tool holder in the spindle (see Fig. 7).

The three capacitive sensors axes are nominally orthogonal to each other and intersecting in one point called P t , chosen as the virtual TCP. This forms an orthogonal measurement frame.

The capacitive sensors are pre-calibrated for the spherical target using a set of three high precision linear stages. The response non-linearity is kept under 0.5% as long as the eccentricity is kept within ±300 µm and the distance between the sensor and the ball is in a ±300 µm range centred on the position at which the sensor gives a 0 Volt signal. The machine is programmed to keep the center of the master ball P w close to P t to avoid exceeding the measurement range of the sensors. In this range, standard type A uncertainty on the sensors output has been evaluated below 0.4 µm [START_REF] Andolfatto | Adaptive Monte Carlo applied to uncertainty estimation in five axis machine tool link errors identification with thermal disturbance[END_REF]. The spindle orientation is regulated to keep the sensing head orientation constant relative to the machine coordinate system -or machine frame -(x, y, z) (Fig. 7).

To express the position of P t relative to P w in the machine tool frame, the orientation of the sensors axes are calibrated. Then, the position of P t relatively to P w can be projected in the machine tool frame, to express τ .

The sensing head described in [START_REF] Zargarbashi | Single setup estimation of a five-axis machine tool eight link errors by programmed end point constraint and on the fly measurement with capball sensor[END_REF] was completely redesigned to significantly increase its stiffness and to ensure negligible displacement of the sensors during a measurement under dynamic solicitations in the maximum operating range of the machine tool. The master ball base is a 40 mm diameter steel bar screwed to the machine table via a solid post (Fig. 7).

The sensors readings are acquired trough a LABView application. All the computation are implemented in MAT-LAB programs.

Experimental trajectory

To evaluate the contributions of the contouring, quasistatic and dynamic errors at different feed rates, an exper-imental trajectory is chosen to provide several characteristics.

It must not last longer than 15 seconds when executed at the lowest programmed feed rate (i.e. 1000 mm/min), in order to avoid exceeding the NC unit recording buffer size. This constraint reduces the maximum length of the trajectory, forbidding performing standard tests as Schmitz et al. did in [START_REF] Schmitz | Case study: a comparison of error sources in high-speed milling[END_REF].

The motion of the master ball results from the rotary axis motion so its path is a complex curve. As the sensing head motion was programmed with linear interpolation, a resulting programmed difference of position between P w and P t appears. The maximum admissible difference was chosen as 100 µm in each direction of the machine frame.

The experimental trajectory -with a nearly square corner -was chosen to provide sizeable geometric discontinuities which require accelerations of several axes. This is the solution chosen to generate a large range of dynamic loads while the programmed feed rate varies. The chosen experimental trajectory is described for each axis as a function of a normalised parameter u varying from 0 to 1 in Fig. 8. This parameter represents the linearly scaled curvilinear abscissa along the trajectory. The trajectory, as perceived in the coordinate system attached to the Ystage, is also depicted. The trajectory is described by 17 linear segments (programmed with G01 blocks). The linear interpolation format leads to acceleration peaks at the transition between each segment, as shown in Fig. 10.

The motion of each axis is programmed with linear in- terpolation, and all the axes are synchronised (FGROUP(X, Y, Z, A, C)). The machine is commanded in joint space (TRAFOOF option)to provide the sought dynamic solicitations. To avoid critical speed decreasing at the corner formed by the nominal path at each block transition, a contouring option is used, allowing rounding the corners with an axial tolerance set at 10 µm.

The trajectory is run at six different programmed feed rates F , geometrically from 1 000 mm/min to 18 896 mm/min.

Results

Mean value of the norm

The mean percentage value of the norm along the perimental trajectory, called k,% for the source k, is used to compare the contributions of each source of error and is calculated as follows:

δ k,% 1 n n i=1 i δ k i δ c + i δ qs + i δ d × 100 (21)
where i δ k is the i-th line of the matrix δ k , and k can be c for contouring errors, qs for quasi-static geometric errors and d for dynamic errors. Thus, δ k,% gives the mean proportion of the total error due to the source k along the trajectory. The repartition of the error sources for the six tests is given in Table 1.

For the geometric errors, the distinction is made between the three identified sources. The experiments were carried out with deactivated compensation tables, avoid- ing any effect of software compensation of the link and motion errors. In an industrial context, the effect of link errors can be compensated, as it is a model-based calculated contribution.

The increasing relative impact of the thermal drift errors (see Table 1) may not be related to the increasing feed rate, but the drift is slowly increasing from test to test while the thermal condition are getting away of the reference thermal state. Moreover, the effect of the thermal drift observed during this series of tests is not reflecting actual machining conditions because the spindle is not running but only regulating its angular position. More sizeable errors can be expected under heavier spindle use.

Table 1 also shows the relative importance of the quasistatic geometric errors, compared to the two other sources for the small feed rates. As expected, the summed con-tributions of the contouring errors and the dynamic errors are increasing from 1.7 % to 14.3 % for programmed feed rate of 1 000 mm/min and 18 896 mm/min respectively.

Maximum errors

The ISO standards on geometric specifications [START_REF]2004 -Geometrical Product Specifications (GPS) -Geometrical tolerancing -Tolerances of form, orientation, location and run-out[END_REF] generally define tolerance zones in which all the machined surface must be located. Considering this, the most penalising errors are the maximum errors.

The maximum errors |δ| max of a contribution δ are defined by the maximum absolute value among the terms of each column x δ, y δ and z δ of δ (eq.( 22)).

|δ| max = (max(| x δ|), max(| y δ|), max(| z δ|)) (22)
Table 2 gives the maximum errors for the quasi-static geometric errors along the experimental trajectory. The maximum drift errors given are the maximum observed during the seven tests. Also, the effect of link errors depends on the pose of the machine, and the maximum error can be calculated offline for any tool path, and can be higher than the one observed in this study for other points in the working volume of the machine.

Table 3 shows the evolution of the contributions of the contouring and dynamic errors with the programmed feed rate. The dynamic errors are not negligible, particularly when the programmed feed rate is over 10 000 mm/min. Even for the first test at F = 1 000 mm/min, dynamic errors occurred, but as shown in Fig. 9, only locally at the sharp corner of the experimental trajectory. The higher the feed rate, the higher the dynamic errors magnitude. As the feed-rate increases Fig. 10 shows that the dynamic errors also increase.

Contributions along the trajectory

Fig. 9 and Fig. 10 are two examples of the calculated contributions of δ c , δ qs and δ d along the experimental trajectory, respectively for the first and the sixth test. The acceleration of each axis is plotted to show that the contouring errors and dynamic errors can, up to a certain point, be related to the acceleration. The block transition extracted from the NC unit is also plotted. The 17 linearly interpolated segments of the trajectory, previously mentioned in 4.3, are visible on those figures. The expected acceleration peaks, which are related to the block transitions, are visible in Fig. 10. Those acceleration peaks are responsible for the sudden appearance of dynamic loads, themselves related to dynamic errors. In the conditions of those experiments, it shows that the machine geometry is affected by accelerations mainly due to the linear interpolation format. The peak-to-peak magnitude of the resulting dynamic errors is higher than 5 µm along the y direction.

The corner visible near the middle of the trajectory in Fig. 8 requires high acceleration of several axes, visible in Fig. 9 and Fig. 10. The high dynamic load generated on purpose results in visible dynamic geometric errors. Therefore, Fig. 10 shows that the machine accuracy is not equally affected in all directions. For instance, high acceleration of the X-axis seems to have little effect on dynamic errors according to Fig. 10.

Root mean square of the dynamic errors

The root mean square value of the dynamic errors along the trajectory in each Cartesian direction are given in Table 4. Fig. 11 shows the evolution of δ d,rms as a function of F on a logarithmic plot. The dashed lines have equations of the form given by eq.( 23).

δ rms = κ • F N (23)
The values of κ and N are obtained by curve fitting for each error and each direction. The aim of the curve fitting is not to propose a general model for dynamic RMS errors evolution, but only to notice a particular result for the experimental conditions of this work. As the κ and N values depend on the experimental trajectory, those results can not lead to general conclusion about the performance of the machine in terms of dynamic stiffness, but it suggests a new performance indicator under dynamic load with a standard trajectory designed for this purpose.

Conclusion

The high-speed machining context requires high accelerations from the machine. Under those dynamic loads, the machine structure may no longer follow a rigid body behaviour. The method presented in this paper allows to measure the volumetric error at the tool tip, and to evaluate the contribution of the dynamic geometric errors.

The experiments at high programmed feed rates have been made possible by the use of a non-contact measuring instrument: the CapBall. The CapBall was re-designed to increase its stiffness for more reliable measurement under high dynamic loads.

The evaluation of the respective magnitude of the contouring errors, the quasi-static geometric errors and the dynamic geometric errors, using the mean values of the norm or the maximum errors, quantifies the relative impact of the dynamic errors, which can reach nearly 5% of the total volumetric error, considering the mean value of the norm.

Furthermore, the study of the root mean square values of the errors shows that in this particular case, the evolution of the RMS errors with respect to the programmed feed rate can be approximated by a logarithmic law.

Finally, the main interest of this experimental work is to propose a method to evaluate dynamic errors directly at the tool tip. Even if the method can only be applied on five -or more -axis machine tool, due to the close kinematic chain principle, it can be a powerful mean to validate models for the dynamic behaviour of the structure with in-situ measurement. It has been shown that the linear interpolation generates acceleration and dynamic errors peaks. The influence of the NC interpolation and controller command law on dynamic errors can also be investigated with this method.

Fig. 1 :

 1 Fig. 1: Difference between the nominal position of the TCP relatively to workpiece τ nom calculated from controller inputs and direct kinematic model and its actual position τ measured with the CapBall.

Fig. 3 :

 3 Fig. 3: Example of the three components of the Cartesian volumetric difference projected in the machine frame, computed with synchronised controllers inputs (χnom) and actual encoders values (χenc) for a programmed feed rate F = 5, 000 mm/min.

Fig. 5 :

 5 Fig. 5: Influence of the eight link errors on the geometric errors for the five axis machine tool studied.

Fig. 6 :

 6 Fig. 6: Comparison of the local polynomial model for motion errors contributions δm and measured residual errors δm,exp (sum of the motion errors and local dynamic errors) along a trajectory at a programmed feed rate of F = 1 000 mm/min.

Fig. 7 :

 7 Fig. 7: Huron KX8-five five axis machine tool fitted with the modified CapBall system.

Fig. 8 :

 8 Fig. 8: Experimental trajectory: left, evolution of each axis setpoint as a function of a normalised path parameter u representing the linearly scaled curvilinear abscissa and right, view of the master ball center Pw trajectory in the machine coordinate system (attached to the Y-stage).

Fig. 9 :

 9 Fig.9: Computed contributions of the follow-up errors, quasi-static and dynamic errors and the associated machine axes acceleration and block transition at a programmed feed rate of F = 1 000 mm/min.

Fig. 10 :

 10 Fig. 10: Computed contributions of the follow-up errors, quasi-static and dynamic errors and the associated machine axes acceleration and block transition at a programmed feed rate of F = 18 896 mm/min.

Fig. 11 :

 11 Fig. 11: Evolution of δ d,rms function of the programmed feed rate F in a logarithmic plot. The dashed line are curve fitted logarithmic models.

Table 1 :

 1 Repartition of the mean value of the error sources along the experimental trajectory for the six tests.

	F (mm/min)	δ c,%	δ qs,% δ l,% δ m,% δ td,%	δ d,%
	1 000	1.1	86.9	11.4	0.0	0.6
	1 800	1.7	85.9	11.3	0.4	0.7
	3 240	2.4	84.7	11.1	0.9	0.9
	5 832	3.9	82.6	10.8	1.1	1.5
	10 498	6.5	77.7	10.2	2.3	3.3
	18 896	9.5	72.8	9.5	3.3	4.8

Table 2 :

 2 Maximum errors of the three Cartesian components of the geometrical errors contributions in the 3 directions of the machine frame.

	Contribution	x	y	z
	Link errors |δ l |max (µm)	4.5 54.7 16.2
	Motion errors |δm|max (µm)	3.1	6.8	5.9
	Thermal drift |δ td (µm)	2.0	1.2	1.8

Table 3 :

 3 Maximum errors of contouring errors and dynamic errors contributions in the 3 directions of the machine frame for the 6 tested programmed feed rates.

	F	|δc|max (µm)	|δ d |max (µm)
	(mm/min)	x	y	z	x	y	z
	1 000	8.1	7.5	10.1	1.1 1.7	3.1
	1 800	7.3	11.2 10.3	1.5 2.9	3.2
	3 240	11.0 13.9 10.6	1.2 3.5	5.4
	5 832	11.2 16.9 10.5	1.8 4.1	7.1
	10 498	11.5 17.0 12.2	3.0 6.2	8.9
	18 896	11.5 17.0 12.5	3.7 7.6 10.4

Table 4 :

 4 Evolution of the root mean square values of the errors in each direction for different feed rates.

	F	δ d,rms (µm)
	(mm/min)	x	y	z
	1 000	0.2 0.2 0.2
	1 800 0.7	0.3 0.3 0.3
	3 240 0.9	0.4 0.4 0.5
	5 832 1.5	0.5 0.8 1.1
	10 498 2.2	0.8 1.9 2.1
	18 896 2.9	1.1 2.7 3.4

From position feedback linear encoders for linear axes and angular position feedback encoders for rotary axes.

Acknowledgements

This work was partially funded with a Discovery Grant from the National Science and Engineering Research Council of Canada and conducted on equipment purchased with a grant from the Canadian Foundation for Innovation.


Therese M Eriksson

Philippe Delagrange

PhD Michael Spedding

Prof Maurizio Popoli

Prof Aleksander A Mathé

Prof Sven Ove Ögren

Emotional memory impairments in a genetic rat model of depression; involvement of 5-HT/MEK/Arc signaling in restoration

Keywords: passive avoidance, MAPK, antidepressant, signal transduction, BDNF, TrkB

Cognitive dysfunctions are common in major depressive disorder, but have been difficult to recapitulate in animal models. This study shows that Flinders Sensitive Line (FSL) rats, a genetic rat model of depression, display a pronounced impairment of emotional memory function in the passive avoidance (PA) task, accompanied by reduced transcription of Arc in prefrontal cortex and hippocampus. At the cellular level, FSL rats have selective reductions in levels of NMDA receptor subunits, serotonin 5-HT 1A receptors and MEK activity. Treatment with chronic escitalopram, but not with an antidepressant regimen of nortriptyline, restored memory performance and increased Arc transcription in FSL rats. Multiple pharmacological manipulations demonstrated that procognitive effects could also be achieved by either disinhibition of 5-HT 1A R/MEK/Arc or stimulation of 5-HT 4 R/MEK/Arc signaling cascades.

Taken together, studies of FSL rats in the PA task revealed reversible deficits in emotional memory processing, providing a potential model with predictive and construct validity for assessments of procognitive actions of antidepressant drug therapies.

Introduction

The clinical impact of emotional dysfunction on cognitive capacity is recognized but difficult to treat. [START_REF] Agid | How can drug discovery for psychiatric disorders be improved?[END_REF][START_REF] Clark | Neurocognitive mechanisms in depression: implications for treatment[END_REF][START_REF] Montgomery | Why do we need new and better antidepressants?[END_REF] Beside depressed mood, the DSM-IV criteria of major depressive disorder (MDD) involve cognitive aspects, i.e. diminished ability to think and concentrate, or indecisiveness, with devastating effects on executive functions, short-and long-term learning and memory. [START_REF] Clark | Neurocognitive mechanisms in depression: implications for treatment[END_REF][START_REF] Montgomery | Why do we need new and better antidepressants?[END_REF] These cognitive impairments appear to involve alterations in the neuronal processing of emotional stimuli i.e. negative attentional bias including feelings of worthlessness or excessive guilt and recurrent thoughts of suicide. [START_REF] Harmer | Serotonin and emotional processing: does it help explain antidepressant drug action?[END_REF] Multiple brain areas, involved in emotionality and cognition i.e. prefrontal cortex, hippocampus, parahippocampal region, amygdala and striatum, show altered functions in MDD. [START_REF] Agid | How can drug discovery for psychiatric disorders be improved?[END_REF][START_REF] Clark | Neurocognitive mechanisms in depression: implications for treatment[END_REF][START_REF] Mcewen | The neurobiological properties of tianeptine (Stablon): from monoamine hypothesis to glutamatergic modulation[END_REF] In particular, volume reduction and impaired functionality of hippocampus have been repeatedly reported in MDD. [START_REF] Clark | Neurocognitive mechanisms in depression: implications for treatment[END_REF][START_REF] Macqueen | Course of illness, hippocampal function, and hippocampal volume in major depression[END_REF][START_REF] Neumeister | Reduced hippocampal volume in unmedicated, remitted patients with major depression versus control subjects[END_REF] Studies in depressed patients have linked dysfunction of the central serotonergic system with abnormal cognitive processing of emotional stimuli and indicated that an important component in antidepressant therapy is support of cognitive functions, which can be separated from elevation of mood. [START_REF] Roiser | The effects of tryptophan depletion on neural responses to emotional words in remitted depression[END_REF] The clinical efficacy of selective serotonin reuptake inhibitors (SSRI) in MDD is exerted by several of the 14 cloned 5-HT receptors, with 5-HT 1A R being the most studied. [START_REF] Ogren | The role of 5-HT(1A) receptors in learning and memory[END_REF] Several studies have described alteration of 5-HT 1A R in post-mortem samples from patients with MDD. [START_REF] Arango | Serotonin 1A receptors, serotonin transporter binding and serotonin transporter mRNA expression in the brainstem of depressed suicide victims[END_REF][START_REF] Bhagwagar | Persistent reduction in brain serotonin1A receptor binding in recovered depressed men measured by positron emission tomography with [11C]WAY-100635[END_REF][START_REF] Borg | Molecular imaging of the 5-HT(1A) receptor in relation to human cognition[END_REF][START_REF] Hirvonen | Decreased brain serotonin 5-HT1A receptor availability in medication-naive patients with major depressive disorder: an in-vivo imaging study using PET and [carbonyl-11C]WAY-100635[END_REF][START_REF] Savitz | 5-HT(1A) receptor function in major depressive disorder[END_REF][START_REF] Stockmeier | Antagonist but not agonist labeling of serotonin-1A receptors is decreased in major depressive disorder[END_REF] Interestingly, 5-HT 1A R antagonists facilitate learning and counteract memory impairments. [START_REF] Ogren | The role of 5-HT(1A) receptors in learning and memory[END_REF] In addition, 5-HT 4 R agonists may have antidepressant [START_REF] Lucas | Serotonin(4) (5-HT(4)) receptor agonists are putative antidepressants with a rapid onset of action[END_REF] and procognitive effects in learning and memory tasks. [START_REF] Fontana | The effects of novel, selective 5-hydroxytryptamine (5-HT)4 receptor ligands in rat spatial navigation[END_REF] The delayed onset of SSRI's and most other antidepressants implicate that therapeutic effects are mediated beyond elevations of monoamines, such as changes of receptor coupling to intracellular signaling cascades and cross-talk with non-monoaminergic mechanisms.

Several lines of evidence indicate that BDNF-induced activation of TrkB mediate actions of antidepressants. [START_REF] Rantamäki | Pharmacologically diverse antidepressants rapidly activate brain-derived neurotrophic factor receptor TrkB and induce phospholipase-Cgamma signaling pathways in mouse brain[END_REF][START_REF] Saarelainen | Activation of the TrkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects[END_REF][START_REF] Martinowich | New insights into BDNF function in depression and anxiety[END_REF][START_REF] Pittenger | Stress, depression, and neuroplasticity: a convergence of mechanisms[END_REF] TrkB receptors, in turn, stimulate several intracellular cascades including the mitogen-activated protein kinase (MAPK), AKT and phospholipase C (PLC) pathways. 21- 22 In particular, the MAPK pathway is involved in behavioral effects of antidepressants and an important modulator of ionotropic receptor signaling, structural remodeling and consolidation of fear memories. [START_REF] Stork | Crosstalk between cAMP and MAP kinase signaling in the regulation of cell proliferation[END_REF][START_REF] Duman | A role for MAP kinase signaling in behavioral models of depression and antidepressant treatment[END_REF][START_REF] Yuan | Protein kinase modulation of dendritic K+ channels in hippocampus involves a mitogen-activated protein kinase pathway[END_REF] Synaptic activation of MAPK induces, via CREB and Elk-1, expression of activity-related cytoskeletal-associated protein (Arc/Arg 3.1). [START_REF] Stork | Crosstalk between cAMP and MAP kinase signaling in the regulation of cell proliferation[END_REF][START_REF] Bramham | The immediate early gene arc/arg3.1: regulation, mechanisms, and function[END_REF][START_REF] Panja | Novel translational control in Arc-dependent long term potentiation consolidation in vivo[END_REF][START_REF] Rao | AMPA receptors regulate transcription of the plasticity-related immediate-early gene Arc[END_REF] Arc expression is induced by long-term potentiation (LTP)-inducing stimuli, requiring NMDAR [START_REF] Panja | Novel translational control in Arc-dependent long term potentiation consolidation in vivo[END_REF][START_REF] Steward | Selective targeting of newly synthesized Arc mRNA to active synapses requires NMDAR activation[END_REF] , involved in synaptic memory consolidation and enriched in hippocampal dendritic spines where its activation is required for acquisition of contextual and spatial learning. [START_REF] Bramham | The immediate early gene arc/arg3.1: regulation, mechanisms, and function[END_REF][START_REF] Montag-Sallaz | Learning-induced arg 3.1/arc mRNA expression in the mouse brain[END_REF][START_REF] Plath | Arc/Arg3.1 is essential for the consolidation of synaptic plasticity and memories[END_REF] Arc expression is also activated by several other mechanism(s) including BDNF [START_REF] Rao | AMPA receptors regulate transcription of the plasticity-related immediate-early gene Arc[END_REF] , protein kinase A (PKA) [START_REF] Montag-Sallaz | Learning-induced arg 3.1/arc mRNA expression in the mouse brain[END_REF] , and pertussis-induced inhibition of G i -mediated signaling. [START_REF] Waltereit | Arg3.1/Arc mRNA induction by Ca2+ and cAMP requires protein kinase A and mitogenactivated protein kinase/extracellular regulated kinase activation[END_REF] Accordingly, blockade of 5-HT 1A R augments the effect of an acute dose of paroxetine on increasing transcription of Arc mRNA. [START_REF] Tordera | Effect of different 5-HT1A receptor antagonists in combination with paroxetine on expression of the immediate-early gene Arc in rat brain[END_REF] Thus, Arc transcription may be a key nodal point in integration of monoaminergic antidepressant effects with glutamate-driven activity-dependent neuronal adaptations regulating gene transcription associated with information processing and associative learning.

The Flinders Sensitive Line (FSL) is a rat strain associated with distinct behavioral and neurochemical features of major depression, including face validity, i.e. psychomotor retardation and increased REM sleep. FSL rats display a genetic vulnerability to environmental stressors and have been successfully used for validation of antidepressant effects. [START_REF] Overstreet | The Flinders Sensitive Line rat: a selectively bred putative animal model of depression[END_REF] Interestingly, promotion of hippocampal neuroplasticity, by means of intracerebroventricular injections of bone-marrow mesenchymal stem cells, reverses the depressive-like phenotype of FSL rats. [START_REF] Tfilin | Mesenchymal stem cells increase hippocampal neurogenesis and counteract depressive-like behavior[END_REF] LTP is also reduced in the CA1 area of hippocampus, shown during in vivo recordings in anesthetized FSL rats [START_REF] Ryan | Remodelling by early-life stress of NMDA receptor-dependent synaptic plasticity in a gene-environment rat model of depression[END_REF] paralleled by reduced NR1 subunits of the NMDAR in hippocampal synaptosomes. [START_REF] Ryan | Remodelling by early-life stress of NMDA receptor-dependent synaptic plasticity in a gene-environment rat model of depression[END_REF] FSL rats also have reduced hippocampal volume and dendritic spines, which is reversed by antidepressants. [START_REF] Chen | Imipramine treatment increases the number of hippocampal synapses and neurons in a genetic animal model of depression[END_REF] These alterations may affect emotional memory processes that, indeed, are believed to depend on enduring remodeling of neuronal morphology and activity-dependent structural plasticity, particularly of glutamatergic dendritic spines, indicating possible cognitive impairments in FSL rats.

In the present study, we performed behavioral, pharmacological, biochemical and histological experiments to examine whether FSL rats exhibit impairments in emotional learning which may respond differentially to various antidepressant therapies and/or selective manipulations of 5-HT neurotransmission.

Materials and methods

Animals and pharmacological treatments

Adult FSL and FRL rats were bred at the Department of Physiology and Pharmacology at Karolinska Institute, and were tested at 2-4 months of age. Rats were kept in standard cages (TypeIV Macrolon ® , 26x42x15cm) with sawdust, at room temperature and relative humidity (45-55%) under a constant light/dark cycle (lights on at 7.00a.m.). Water and food pellets (LactaminR36, Stockholm, Sweden) were available ad libitum. Experimental procedures were approved by the local Animal Ethics Committee (Stockholms Norra Djurförsöksetiska Nämnd).

FRL and FSL rats were randomly assigned to groups given either escitalopram, nortriptyline or vehicle administered to standard rat pellets [START_REF] Khoury | Adult life behavioral consequences of early maternal separation are alleviated by escitalopram treatment in a rat model of depression[END_REF][START_REF] Petersén | Nortriptyline mediates behavioral effects without affecting hippocampal cytogenesis in a genetic rat depression model[END_REF] (Fig. S4) (Lactamin AB).

Escitalopram, was given at 340mg/kg pellets for 3 weeks, followed by 410mg/kg pellets.

Nortriptyline was administered at 330mg/kg pellet. NAD-299 [(R)-3-N,N-dicyclobutylamino-8-fluoro-3,4-dihydro-2H-1-benzopyran-5carboxamide hydrogen (2R,3R)tartrate monohydrate](1mg/kg s.c.; AstraZeneca R&D, Södertälje, Sweden) and RS67333(1mg/kg, i.p.; Tocris) were administered 30 minutes prior to testing. [START_REF] Eglen | Pharmacological characterization of two novel and potent 5-HT4R agonists, RS 67333 and RS 67506, in vitro and in vivo[END_REF][START_REF] Lüttgen | Analysis of the role of 5-HT1A receptors in spatial and aversive learning in the rat[END_REF] [(methylsulfonyl)amino]ethyl]-4-piperidinyl]-1H-indole-3-methylcarboxylate sulfamate ](10 mg/kg i.p.; Tocris) was given 60 min pretraining. [START_REF] Fontana | The effects of novel, selective 5-hydroxytryptamine (5-HT)4 receptor ligands in rat spatial navigation[END_REF] Drugs were dissolved in 2ml/kg of 0.9%NaCl. PD184161(Servier, Suresness, France) was administered 60 min prior to testing at a dose of 30 mg/kg i.p and dissolved in 1%Tween80 in 6ml/kg of 0.9%NaCl.

Passive avoidance (PA), Forced-swim test (FST), Open-Field (OF) and Elevated Plus-Maze (EPM).

The step-through PA was performed as described earlier [START_REF] Lüttgen | Analysis of the role of 5-HT1A receptors in spatial and aversive learning in the rat[END_REF] (see supplementary Fig. S1).

During PA training, rats were placed in the bright compartment and allowed to explore for 120s. Thereafter, the sliding door was opened and once the rat had entered the dark compartment the sliding door was automatically closed and a weak electrical stimulus (0.4mA, 2s scrambled current) was delivered through the grid floor. Twenty-four hours after training, the animal was again gently placed in the light compartment and the latency to enter the dark compartment with all four paws was automatically measured (retention latency) with a cut-off time for testing after 9 min. See supplementary information regarding the procedures for FST and OF(Fig. S4) and EPM(Fig. S5).

Histological measurements of Arc and BDNF transcription and 5-HT receptors

For in situ hybridization experiments, rat brains were rapidly dissected after decapitation and immediately frozen at -80°C. Fresh frozen (12µm) coronal cryostat sections were prepared and hybridized with [START_REF] Tfilin | Mesenchymal stem cells increase hippocampal neurogenesis and counteract depressive-like behavior[END_REF] S-radiolabeled antisense riboprobes against Arc and BDNF according to a previous protocol. [START_REF] Svenningsson | Cellular distribution of adenosine A2A receptor mRNA in the primate striatum[END_REF] For receptor autoradiography procedure with

Immunoprecipitation and immunoblotting of total protein and their phosphorylation state

The levels of the studied proteins and their phosphorylation state were assessed by immunoblotting. To preserve protein phosphorylation, rats were sacrificed using focused microwave irradiation (Muromachi Kikai, Tokyo, Japan) with brain regions dissected and frozen at -80°C. Alternatively, rats were decapitated, their head snap frozen, brain regions rapidly dissected out and processed to avoid dephosphorylation events. These procedures have been described earlier. [START_REF] Svenningsson | Cellular distribution of adenosine A2A receptor mRNA in the primate striatum[END_REF][START_REF] Svenningsson | Alterations in 5-HT1B receptor function by p11 in depression-like states[END_REF] For detailed immunoprecipitation and immunoblotting protocols, see supplementary information in Table S1.

Statistical analysis

The data were analyzed with one-way or two-way ANOVAs with drug treatment, rat strain or brain region as factors in multiple comparisons. For each significant F-ratio, Newman-Keuls test was used for Post-hoc comparison of effects following one-way ANOVA, while Bonferroni Post-hoc test was used after two-way ANOVA. When only two groups were compared (FRL with FSL), a two-tailed unpaired Student's T-test was used. p<0.05 was considered statistically significant.

Results

Baseline performance in PA and Arc transcription in FSL and FRL rats FSL rats of both sexes displayed reduced performance in the PA task compared to the control FRL rats (Fig. 1A). To determine biochemical measures corresponding to the deficit in contextual memory, assessment of Arc mRNA levels was made in several brain regions. Arc mRNA expression was specifically reduced in medial prefrontal cortex and in hippocampal CA1 and dentate gyrus subterritories, but not in parahippocampus, somatosensory cortex, amygdala or thalamus (Fig. 1D-M).

Baseline regulation of glutamate and 5-HT receptors and signaling molecules

Arc mRNA expression is regulated by glutamate and serotonin neurotransmission and, in accordance with reduced Arc mRNA, western blotting showed lower levels of NR1 subunits of the NMDAR complex in prefrontal cortex, hippocampus and parahippocampus of FSL rats (Fig. 2A). The compositions of the different NMDAR subunits determine gating and kinetic properties the NMDAR, with important consequences for synaptic plasticity and memory. 44- 45 The NR2B subunit is specifically involved in NMDAR interactions with the MAPK cascade. [START_REF] Krapivinsky | The NMDA receptor is coupled to the ERK pathway by a direct interaction between NR2B and RasGRF1[END_REF] In FSL rats, NR2A and NR2B subunits were specifically lowered in prefrontal cortex and hippocampus (Fig. 2A). In none of the studied regions, GluR1 subunits of the AMPAR complex were different between FSL and FRL rats (Fig. 2A). Serotonin 5-HT 1A R, but not 5-HT 1B R or 5-HT 4 R, were reduced in all studied regions in FSL rats (Fig. 2A).

Likewise, labeling of 5-HT 1A R by [ 3 H]8-OH-DPAT was reduced in hippocampal sections from male (Fig. S2A-C) and female (Fig. S2A,D-E) FSL rats, whereas there were no alterations in 5-HT 1B R or 5-HT 4 R-like binding, using [ 125 I]cyanopindolol and [ 3 H]GR113808 respectively (Fig. S2F-O).

In contrast to the reduced levels of NMDAR subunits, their phosphorylation states appeared to be generally increased in FSL rats, possibly as a compensatory mechanism(s). Specifically, NR1 subunits showed significantly increased phosphorylation of Ser 896 , a PKC site, and Ser 897 , a PKA site, in the hippocampus (Fig. 2B). In prefrontal cortices, the phosphorylation at the NR1 subunit at site Ser 896 was increased and the NR2A subunit exhibited an increased phosphorylation at Ser 1232 , a cdk5 site (Fig. 2B). The phosphorylation states of NR2B subunits at Ser 1303 , a CaMKII site, and Tyr 1472 , a SRC tyrosine kinase site, were not altered in FSL rats (Fig. 2B). The phosphorylation levels of GluR1 subunits at Ser 831 , a PKC/CaMKII site, and Ser 845 , a PKA site, were not altered (Fig. 2B). The total levels of MEK, p42-MAPK and p44-MAPK were increased in prefrontal cortex and hippocampus of FSL rats (Fig. 2C). No changes in the phosphorylation of Ser 217/221 -MEK were found (Fig. 2D).

However, reduced phosphorylations at Thr 183/Tyr185 -p42 and Thr 202/Tyr204 -p44 in hippocampus were found, indicative of a reduced MEK activity in FSL rats (Fig. 2D). In contrast, total levels or phosphorylation states of CaMKII, GSK-3β, AKT or in PSD-95, a postsynaptically enriched protein, were not altered (Fig. 2C-D). These data suggest that MEK/MAPK signaling is particularly dysregulated in FSL rats and that decreased MEK activity, perhaps related to reduced NMDAR and 5-HT receptor-mediated transmission, parallels with memory impairments and reduced Arc mRNA expression in FSL rats.

Impairing effect on PA performance by NMDAR blockade in both FSL and FRL rats

NMDAR are critically implicated in the acquisition and consolidation of several types of memories including the PA task [START_REF] Ogren | The role of 5-HT(1A) receptors in learning and memory[END_REF] . In agreement with previous reports, treatment with an amnesic dose of MK-801, a non-competitive NMDAR antagonist, of FRL rats severely disrupted retention performance, mimicking the memory impairments seen in FSL rats (Fig. S3 and summary Fig. S7A-C).

Effects of escitalopram and nortriptyline on behavioral performance in PA, FST, OF, EPM and transcription of Arc

To test whether the impairment in memory performance in FSL rats could be reversed by antidepressants, FSL and FRL rats were treated chronically with vehicle, escitalopram or nortriptyline. [START_REF] Khoury | Adult life behavioral consequences of early maternal separation are alleviated by escitalopram treatment in a rat model of depression[END_REF][START_REF] Petersén | Nortriptyline mediates behavioral effects without affecting hippocampal cytogenesis in a genetic rat depression model[END_REF] In FSL rats, escitalopram, but not nortriptyline, reversed the impairment of memory performance in the PA test (Fig. 3A). In contrast, escitalopram was without effect on memory performance in FRL rats, comparable with lack of effects of paroxetine in Sprague-Dawley rats [START_REF] Misane | Effects of Hypericum perforatum (St. John's wort) on passive avoidance in the rat: evaluation of potential neurochemical mechanisms underlying its antidepressant activity[END_REF] , while nortriptyline impaired performance (Fig. 3A). Escitalopram, but not nortriptyline, specifically increased expression of Arc mRNA in the CA1 and dentate gyrus subregions of hippocampus of FSL rats (Fig. 3B-E). Escitalopram reduced immobility in the FST in FSL rats. [START_REF] Khoury | Adult life behavioral consequences of early maternal separation are alleviated by escitalopram treatment in a rat model of depression[END_REF] Similarly, nortriptyline decreased immobility of FSL rats in the FST (Fig. S4A), via mechanisms unrelated to alterations in locomotion (Fig. S4B-C). Notably, the differential effect of escitalopram and nortriptyline in the PA test could not be correlated to EPM performance, as both agents induced anxiolytic-like effects in control FRL rats (Fig. S4D-E). FSL rats displayed a basal anxiolytic phenotype and nortriptyline was without effect, while escitalopram further reduced anxiety-like behavior (Fig. S4D-E).

Measurements of BDNF mRNA and protein and phosphorylated TrkB under baseline conditions and following escitalopram and nortriptyline

Several antidepressant actions are mediated via BDNF and its predominant receptor TrkB and BDNF signaling is reflected by the phosphorylation state of TrkB. [START_REF] Rantamäki | Pharmacologically diverse antidepressants rapidly activate brain-derived neurotrophic factor receptor TrkB and induce phospholipase-Cgamma signaling pathways in mouse brain[END_REF][START_REF] Saarelainen | Activation of the TrkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects[END_REF][START_REF] Martinowich | New insights into BDNF function in depression and anxiety[END_REF][START_REF] Pittenger | Stress, depression, and neuroplasticity: a convergence of mechanisms[END_REF][START_REF] Huang | Trk receptors: roles in neuronal signal transduction[END_REF] BDNF signaling increases Arc mRNA and protein expression in neurons [START_REF] Stork | Crosstalk between cAMP and MAP kinase signaling in the regulation of cell proliferation[END_REF] and could potentially act upstream of Arc under baseline conditions and/or following escitalopram treatment in FSL rats. Immunoblotting revealed regional-specific differences of basal proBDNF, with reduced levels in the hippocampus of FSL rats when compared to FRL rats, but increased levels in the parahippocampal region and unaltered levels in the prefrontal cortex (Fig. S5A). However, basal levels of mature BDNF, as well as total and phosphorylated TrkB, did not differ between the genotypes in the examined regions (Fig. S5A-B).

In response to both escitalopram and nortriptyline, FSL rats showed increased of expression of BDNF mRNA in the dentate gyrus, but not in the CA1, of hippocampus (Fig. S5C-F). In comparison, no significant alterations of proBDNF or BDNF proteins were found in total hippocampal or parahippocampal homogenates from antidepressant-treated animals (Fig. S5G). Nortriptyline and escitalopram induced treatment-, region-and site-specific changes of TrkB phoshorylation, without affecting total TrkB. Specifically, both nortriptyline and escitalopram increased phosphorylation of TrkB at Tyr 816 , whereas nortriptyline, but not escitalopram, increased phoshorylation at Tyr 705 -TrkB, and none of these treatments regulated Tyr 515 -TrkB in hippocampus (Fig. S5H). No corresponding alterations were found in the parahippocampal region (Fig. S5H). It should be noted that the antisera towards phosphorylated TrkB can also detect phosphorylated TrkA, and both TrkB and TrkA are found in hippocampal extracts (Fig. S6A-B). In view of this, immunoprecipitations of TrkB were done from hippocampal brain tissue and, subsequently, analyzed for total TrkA and TrkB receptors as well as phosphorylated TrkB (Fig. S6C-E). No TrkA was found in TrkB immunoprecipitates (Fig. S6E). However, immunoreactivity of the antidepressant-responsive Tyr 816 -TrkB site was readily detected in TrkB immunoprecipitates (Fig. S6D). In response to treatment with escitalopram and nortriptyline, levels of Tyr 816 -TrkB were increased in hippocampal TrkB immunoprecipitates (Fig. S6D,F). Vice versa, in a confirmatory experiment, immunoprecipitation of Tyr 816 -TrkB resulted in higher levels of TrkB immunoreactivity in antidepressant-treated rats (Fig. S6C). Notably, no TrkA was found in Tyr 816 -TrkB immunoprecipitates (Fig. S6E), indicating that phosphorylation at this site in hippocampus occurs mainly at TrkB.

Effects of selective 5-HT 1A R and 5-HT 4 R ligands, with and without a MEK inhibitor, on PA performance and transcription of Arc

Based on the procognitive effects of escitalopram in the PA test in FSL rats and reduced 5-HT 1A R levels, we studied 5-HT receptor subtypes in modulating memory performance in FSL rats. The 5-HT 1A R agonist 8-OH-DPAT impaired performance in the PA test in FRL rats (Fig. 4A). On the other hand, NAD-299, a 5-HT 1A R antagonist, enhanced performance in the PA test in FRL rats and reversed the memory dysfunction in the FSL rats, reminiscent of the action of escitalopram (Fig. 4A). Inhibition of presynaptic 5-HT 1A R causes an increase in the firing rate of serotonin neurons, while inhibition of postsynaptic 5-HT 1A R causes a decrease of inhibitory serotonin transmission in specific circuits. [START_REF] Ogren | The role of 5-HT(1A) receptors in learning and memory[END_REF] Next, we pretreated the rats with a 5-HT 4 R antagonist, known to mediate its actions at the postsynaptic site. GR125487, at a concentration where it had no intrinsic effect, blocked the effect of NAD-299 indicating that NAD-299 exerts at least some of its effects via stimulation of 5-HT 4 R (Fig. 4A). The 5-HT 4 R agonist, RS67333, also restored memory performance in the PA test (Fig. 4A). Both 5-HT 1A R 9, 48 and 5-HT 4 R [START_REF] Huang | 5-Hydroxytryptamine induces a protein kinase A/mitogenactivated protein kinase-mediated and macromolecular synthesis-dependent late phase of long-term potentiation in the amygdala[END_REF][START_REF] Norum | Ras-dependent ERK activation by the human G(s)-coupled serotonin receptors 5-HT4(b) and 5-HT7(a)[END_REF] have been shown to regulate the MEK/MAPK cascade and since the biochemical data indicated that MEK/MAPK signaling is altered in FSL rats (Fig. 2A-B), we investigated whether the MEK/MAPK signaling cascade is mediating procognitive actions of NAD-299 and/or RS67333. Rats were pretreated with a MEK inhibitor, PD184161 [START_REF] Saarelainen | Activation of the TrkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects[END_REF] , at a dose where it had no intrinsic effect, prior to treatment with either NAD-299 or RS67333.

PD184161 completely blocked the enhancing effects of NAD-299 or RS67333 in the PA test (Fig. 4A).

We also found that NAD-299 and/or RS67333 could mimic the region-specific stimulatory effects of escitalopram on Arc mRNA in the CA1 and dentate gyrus subregions of hippocampus (Fig. 4D,F,H). Moreover, while PD184161 had no effects by itself on Arc transcription in FSL rats (Fig. 4C,H) it significantly counteracted the actions of both NAD-299 and RS67333 on Arc mRNA (Fig. 4E,G,H). It seems that MEK/MAPK signaling is a nodal point in mediating some behavioral and biochemical postsynaptic serotonergic effects critically involved in procognitive effects in the PA paradigm.

Discussion

A substantial proportion of depressed patients exhibit deficits in several memory tasks, including declarative verbal and recollection memory, executive functions and emotional word processing. [START_REF] Clark | Neurocognitive mechanisms in depression: implications for treatment[END_REF][START_REF] Macqueen | Course of illness, hippocampal function, and hippocampal volume in major depression[END_REF][START_REF] Roiser | The effects of tryptophan depletion on neural responses to emotional words in remitted depression[END_REF][START_REF] Savitz | 5-HT(1A) receptor function in major depressive disorder[END_REF][START_REF] Pittenger | Stress, depression, and neuroplasticity: a convergence of mechanisms[END_REF][START_REF] Frodl | Reduced hippocampal volume correlates with executive dysfunctioning in major depression[END_REF][START_REF] Pfennig | Neurocognitive impairment and dementia in mood disorders[END_REF] Improvement of cognitive processing and emotional memory function in depression is believed to be important for the treatment outcome in MDD. [START_REF] Clark | Neurocognitive mechanisms in depression: implications for treatment[END_REF][START_REF] Harmer | Serotonin and emotional processing: does it help explain antidepressant drug action?[END_REF] In the present study, we provide data indicating that the genetic FSL rat line of depression may be utilized as a model for studies of reversible impairments in emotional processing and memory, displaying predictive validity for assessment of drugs supporting cognitive performance. [START_REF] Harmer | Serotonin and emotional processing: does it help explain antidepressant drug action?[END_REF][START_REF] Vetencourt | The antidepressant fluoxetine restores plasticity in the adult visual cortex[END_REF] The impairments of memory performance are in accordance with the findings of reduced Arc mRNA specifically in cortical and hippocampal subregions of FSL rats (Fig. 1D-M), consistent with accumulating data indicating that Arc transcription is activated by neuronal stimuli particularly important for encoding of one-trial hippocampaldependent learning and long-term neuroplasticity involved in consolidation of memories. 26-27, 31, 54 The marked alterations of glutamatergic receptors in the FSL rat line (Fig. 2AB) agree with a number of neuroimaging and post-mortem histological studies showing glutamatergic abnormalities in MDD [START_REF] Hashimoto | Emerging role of glutamate in the pathophysiology of major depressive disorder[END_REF][START_REF] Sanacora | Targeting the glutamatergic system to develop novel, improved therapeutics for mood disorders[END_REF] , e.g. magnetic resonance spectroscopy studies in patients with MDD demonstrated altered glutamate levels in several cortical subregions. [START_REF] Sanacora | Subtype-specific alterations of γ-aminobutyric acid and glutamate in patients with major depression[END_REF][START_REF] Hasler | Reduced prefrontal glutamate/glutamine and γ-aminobutyric acid levels in major depression determined using proton magnetic resonance spectroscopy[END_REF][START_REF] Auer | Reduced glutamate in the anterior cingulate cortex in depression: an in vivo proton magnetic resonance spectroscopy study[END_REF] Accordingly, NMDAR binding and subunits are decreased in cortical regions in depressed patients. [START_REF] Nudmamud-Thanoi | The NR1 subunit of the glutamate/NMDA receptor in the superior temporal cortex in schizophrenia and affective disorders[END_REF][START_REF] Nowak | Alterations in the N-methyl-d-aspartate (NMDA) receptor complex in the frontal cortex of suicide victims[END_REF][START_REF] Feyissa | Reduced levels of NR2A and NR2B subunits of NMDA receptor and PSD-95 in the prefrontal cortex in major depression[END_REF][START_REF] Beneyto | Lamina-specific abnormalities of NMDA receptorassociated postsynaptic protein transcripts in the prefrontal cortex in schizophrenia and bipolar disorder[END_REF][START_REF] Beneyto | Abnormal glutamate receptor expression in the medial temporal lobe in schizophrenia and mood disorders[END_REF] Similarly, the core NR1 subunit of the NMDAR was markedly reduced in FSL rats in the prefrontal cortex, parahippocampal region and hippocampal extracts, accompanied with reductions also of the NR2A and NR2B subunits in the prefrontal cortex and hippocampus (Fig. 2A). Selective reductions of several NMDAR subunits in corticolimbic brain regions in FSL rats further indicate that these alterations have severe consequences for synaptic plasticity and account for the impairments of LTP in FSL rats. [START_REF] Ryan | Remodelling by early-life stress of NMDA receptor-dependent synaptic plasticity in a gene-environment rat model of depression[END_REF] Consistent with findings reported from MDD patients [START_REF] Hashimoto | Emerging role of glutamate in the pathophysiology of major depressive disorder[END_REF][START_REF] Sanacora | Targeting the glutamatergic system to develop novel, improved therapeutics for mood disorders[END_REF] we observed only modest alterations of GluR1 levels. The phosphorylation state of NMDAR and AMPAR correlates with changes in synaptic strength. [START_REF] Lau | NMDA receptor trafficking in synaptic plasticity and neuropsychiatric disorders[END_REF] Despite the lower levels of NMDAR subunits found in FSL rats, phosphorylation levels were in several cases upregulated. Taken together, rather than subtype-specific alterations, regional-specific overall reductions of NMDAR, partially compensated by hyperphosphorylation were found in FSL rats.

The specific reductions of 5-HT 1A R, but not 5-HT 1B R or 5-HT 4 R-like binding, using immunoblotting (Fig. 2A) and autoradiography receptor binding in FSL rats (Fig. S2A-O) agree with a previous study [START_REF] Nishi | Both acute and chronic buspirone treatments have different effects on regional 5-HT synthesis in Flinders Sensitive Line rats (a rat model of depression) than in control rats[END_REF] The reduction of 5-HT 1A R are consistent with several neuroimaging studies and post-mortem data from patients with MDD. [START_REF] Arango | Serotonin 1A receptors, serotonin transporter binding and serotonin transporter mRNA expression in the brainstem of depressed suicide victims[END_REF][START_REF] Bhagwagar | Persistent reduction in brain serotonin1A receptor binding in recovered depressed men measured by positron emission tomography with [11C]WAY-100635[END_REF][START_REF] Borg | Molecular imaging of the 5-HT(1A) receptor in relation to human cognition[END_REF][START_REF] Hirvonen | Decreased brain serotonin 5-HT1A receptor availability in medication-naive patients with major depressive disorder: an in-vivo imaging study using PET and [carbonyl-11C]WAY-100635[END_REF][START_REF] Savitz | 5-HT(1A) receptor function in major depressive disorder[END_REF] It has however been difficult to distinguish primary effects and confounders in view of variations of 5-HT 1A R binding during onset and remission of depression, responses to antidepressants, differences in agonist vs. antagonist labeling, with the mixed results most likely also reflecting the clinical heterogeneity of depressed patients, drug treatment and/or aging [START_REF] Borg | Molecular imaging of the 5-HT(1A) receptor in relation to human cognition[END_REF][START_REF] Savitz | 5-HT(1A) receptor function in major depressive disorder[END_REF][START_REF] Stockmeier | Antagonist but not agonist labeling of serotonin-1A receptors is decreased in major depressive disorder[END_REF] After chronic antidepressant treatments, a discrepancy was found between escitalopram and nortriptyline on both behavioral outputs and on Arc mRNA expression (Fig. 3A-E). The restoring effects on Arc transcription and emotional memory performance of FSL rats are consistent with clinical findings supporting a serotonergic component in recovery of cognitive aspects. [START_REF] Harmer | Serotonin and emotional processing: does it help explain antidepressant drug action?[END_REF][START_REF] Roiser | The effects of tryptophan depletion on neural responses to emotional words in remitted depression[END_REF][START_REF] Hindmarch | Cognitive toxicity of pharmacotherapeutic agents used in social anxiety disorder[END_REF] Indeed, these results in FSL rats show predictive and face validity with data on clinical efficacy for escitalopram and nortriptyline, antidepressants which have been reported to be similar on three conventional depression-rating scales, but differentiate in a superior improvement of cognitive symptoms by escitalopram, while nortriptyline rather improved neurovegetative symptoms. [START_REF] Uher | Differential efficacy of escitalopram and nortriptyline on dimensional measures of depression[END_REF] Calculation of a proportional impairment-ratio in humans were found to be 3-9-fold higher for tricyclic antidepressants, than those reported for escitalopram, on a range of different psychometric tests for cognitive symptoms. The varying drug-induced cognitive impairment caused by tricyclic agents is attributed to their anticholinergic and antihistaminergic properties, decreasing cognitive performance and arousal, respectively. [START_REF] Hindmarch | Cognitive toxicity of pharmacotherapeutic agents used in social anxiety disorder[END_REF] Consistent with previous reports on antidepressant regimens, both escitalopram and nortriptyline increased BDNF mRNA in the dentate gyrus, but not CA1, of hippocampus (Fig. S5C-F). [START_REF] Martinowich | New insights into BDNF function in depression and anxiety[END_REF][START_REF] Pittenger | Stress, depression, and neuroplasticity: a convergence of mechanisms[END_REF][START_REF] Castrén | The role of BDNF and its receptors in depression and antidepressant drug action: Reactivation of developmental plasticity[END_REF] We could not detect any corresponding effects on protein levels of proBDNF and mature BDNF (Fig. S5G). As discussed previously (for reviews see [START_REF] Martinowich | New insights into BDNF function in depression and anxiety[END_REF][START_REF] Pittenger | Stress, depression, and neuroplasticity: a convergence of mechanisms[END_REF][START_REF] Castrén | The role of BDNF and its receptors in depression and antidepressant drug action: Reactivation of developmental plasticity[END_REF] ), a discrepancy between mRNA and protein expression of BDNF as found here may be due to several factors including the omission of subregional analysis of hippocampal BDNF protein, retrograde/anterograde transport of BDNF protein transcribed in the dentate gyrus and the lack of distinct measures of intra-and extracellular BDNF protein.

BDNF-mediated signaling can be studied by measures of the phosphorylation state of the TrkB receptor. Binding of BDNF to the TrkB receptor induces its autophosphorylation at Tyr 705 -TrkB in the catalytic domain, which subsequently regulates the phosphorylation state at other tyrosine residues including Tyr 515 -TrkB, a Shc binding site, and Tyr 816 -TrkB, a PLCγ1 binding site. [START_REF] Uher | Differential efficacy of escitalopram and nortriptyline on dimensional measures of depression[END_REF] The latter phosphorylation site of TrkB is also regulated via transactivation by G-protein coupled receptors, independent of BDNF. [START_REF] Jeanneteau | Promoting neurotrophic effects by GPCR ligands[END_REF] In agreement with Rantamäki, Castrén and co-workers [START_REF] Rantamäki | Pharmacologically diverse antidepressants rapidly activate brain-derived neurotrophic factor receptor TrkB and induce phospholipase-Cgamma signaling pathways in mouse brain[END_REF][START_REF] Saarelainen | Activation of the TrkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects[END_REF] we found that both a tricyclic antidepressant, nortriptyline, and, a SSRI, escitalopram, increased phosphorylation at the PLCγ1 binding site Tyr 816 -TrkB, but not at the Shc binding site Tyr 515 -TrkB in hippocampus (Fig. S5H). It is interesting that studies with phosphomutant TrkB mice have shown that the PLCγ1 binding site is more important for synaptic plasticity than the Shc binding site [START_REF] Minichiello | Mechanism of TrkB-mediated hippocampal long-term potentiation[END_REF] S6C-F). Using direct immunoblotting from snapfrozen hippocampi, we also found that nortriptyline, but not escitalopram, increased Tyr 705 -TrkB at the studied timepoint suggesting a more sustained and/or stronger activation of TrkB by nortriptyline (Fig. S5H). However, it should be noted that we sacrificed the rats during daytime when they consumed less drugcontaining pellets and previous work has demonstrated that the autophosphorylation at Tyr 705 -TrkB is transient and most pronounced within one hour after an injection of a tricyclic or a SSRI antidepressant. [START_REF] Rantamäki | Pharmacologically diverse antidepressants rapidly activate brain-derived neurotrophic factor receptor TrkB and induce phospholipase-Cgamma signaling pathways in mouse brain[END_REF][START_REF] Saarelainen | Activation of the TrkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects[END_REF] Taken together, the increased BDNF transcription and Tyr 816 -TrkB phosphorylation by both nortriptyline and escitalopram in FSL rats correlate well with the antidepressant and anxiolytic effects of these agents, but not with the differential effects on recovery of emotional memory in the PA paradigm. On the other hand, the discrepancy of nortriptyline and escitalopram on Arc transcription corresponds better with their effects on PA memory performance. Arc, rather than BDNF, transcription was therefore chosen as a biochemical correlate in the mechanistic studies on serotonin-mediated modulation of PA using selective ligands. However, it should be noted that a contribution of BDNF/TrkB signaling to the effects of escitalopram on Arc transcription and PA performance cannot be excluded.

Given the restoring effects of escitalopram on PA in FSL rats and the alterations of 5-HT 1A R levels, we went on to investigate the effects of pharmacological modulation of specific 5-HT receptor subtypes. Stimulation of 5-HT 1A R impairs learning and memory functions in a range of rodent cognitive tasks. [START_REF] Ogren | The role of 5-HT(1A) receptors in learning and memory[END_REF] This agrees with the pharmacological response to the 5-HT 1A R agonist 8-OH-DPAT in FRL rats (Fig. 4A and Fig. S7D), resembling the impaired memory performance of untreated FSL rats compared to control FRL rats (Fig. 4A and Fig. 5A-B). The blunted response of FSL rats to 8-OH-DPAT is consistent with the findings of reduced postsynaptic 5-HT 1A R density (Fig. 2A). Conversely, the 5-HT 1A R antagonist NAD-299 facilitates several types of learning in rodents, attributed to alleviation of 5-HT 1A Ractivated G i/o -mediated signaling cascades in postsynaptic neurons (Fig. 4A). 9, 41 Thus, the effects of blockade of pre-and postsynaptic 5-HT 1A R resembled the effects of increased 5-HT function by escitalopram (Fig. 3A and Fig. 5C). Despite an important role of 5-HT 1A Rs in modulation of SSRI efficacy, chronic fluoxetine still has antidepressant-like effects in 5-HT 1A R KO mice, emphasizing an involvement of other 5-HT receptor subtypes. [START_REF] Holick | Behavioral effects of chronic fluoxetine in BALB/cJ mice do not require adult hippocampal neurogenesis or the serotonin 1A receptor[END_REF] Intriguingly, the 5-HT 4 R antagonist GR125487 blocked the facilitatory effects of NAD-299 on PA performance (Fig. 4A), indicating that activation of postsynaptic 5-HT 4 Rs is necessary for the restoring effect of 5-HT 1A R antagonism on PA performance in FSL rats. Likewise, direct agonist stimulation of 5-HT 4 R with RS67333 also restored PA performance (Fig. 4A).

Thus, these data indicate that not only does 5-HT 1A R antagonism disinhibit postsynaptic neurons by alleviating a tonic inhibition mediated by 5-HT, but also enables a shift in endogenous 5-HT transmission towards activation of the 5-HT 4 R and downstream signaling cascades (Fig. 5C). The effects of chronic SSRI administration on PA performance and Arc mRNA were thus replicated by either 5-HT 1A R antagonism or 5-HT 4 R agonism (Fig. 4A,D,F,H), further supporting that central 5-HT 4 R stimulation offers a potential target for improvement of emotional [START_REF] Lucas | Serotonin(4) (5-HT(4)) receptor agonists are putative antidepressants with a rapid onset of action[END_REF] and cognitive processing. [START_REF] Fontana | The effects of novel, selective 5-hydroxytryptamine (5-HT)4 receptor ligands in rat spatial navigation[END_REF] Systemic pretreatment with the MEK inhibitor PD184161 fully blocked the ability of both NAD-299 and RS67333 to restore memory function (Fig. 4A) and induce Arc mRNA expression (Fig. 4E,G,H). These data implicate an involvement of the MAPK signaling pathway as a nodal point in restoration of emotional memory consolidation. There is support for G i/o -protein and G s -protein mediated receptor modulation of the MEK/MAPK cascade. [START_REF] Ogren | The role of 5-HT(1A) receptors in learning and memory[END_REF][START_REF] Stork | Crosstalk between cAMP and MAP kinase signaling in the regulation of cell proliferation[END_REF][START_REF] Garnovskaya | Ras-dependent activation of fibroblast mitogen-activated protein kinase by 5-HT1AR via a G protein beta gamma-subunit-initiated pathway[END_REF][START_REF] Huang | 5-Hydroxytryptamine induces a protein kinase A/mitogenactivated protein kinase-mediated and macromolecular synthesis-dependent late phase of long-term potentiation in the amygdala[END_REF][START_REF] Norum | Ras-dependent ERK activation by the human G(s)-coupled serotonin receptors 5-HT4(b) and 5-HT7(a)[END_REF][START_REF] Chen | 5-HT1A receptor-mediated regulation of mitogenactivated protein kinase phosphorylation in rat brain[END_REF] Local increase of cAMP may trigger events that are involved in induction of shortterm plasticity and early stages of memory formation, while activation of MAPK signaling pathways may result in more long-lasting effects requiring nuclear gene transcription. [START_REF] Pittenger | Stress, depression, and neuroplasticity: a convergence of mechanisms[END_REF][START_REF] Stork | Crosstalk between cAMP and MAP kinase signaling in the regulation of cell proliferation[END_REF] Besides, fear conditioning and LTP-mediated increase of Arc expression in the lateral amygdala is dependent on activation of the MAPK cascade [START_REF] Ploski | The activityregulated cytoskeletal-associated protein (Arc/Arg3.1) is required for memory consolidation of pavlovian fear conditioning in the lateral amygdala[END_REF] and hippocampal cAMP/MAPK signaling is involved in long-term consolidation of contextual fear conditioning. [START_REF] Eckel-Mahan | Circadian oscillation of hippocampal MAPK activity and cAmp: implications for memory persistence[END_REF] Collectively, these findings emphasize a crucial involvement of the MEK/MAPK cascade as a nodal point in 5-HT 1A R/5-HT 4 R-mediated effects on emotional memory and expression of Arc mRNA (Fig. 5D).

In conclusion, emotional memory impairments and baseline reductions of Arc transcription were found in the FSL rat line of depression. Memory functions and enhancement of Arc transcription were specifically induced by escitalopram as well as pharmacological treatments increasing postsynaptic 5-HT function via stimulation of cAMP/MAPK signaling cascades. The FSL rat line provides a preclinical model recapitulating reversible deficits of cognitive processing that is disrupted in depression.

  (±)-8-OH-DPAT [8-hydroxy-2-(di-n-propylamino)tetralin](0.3mg/kg s.c.; Sigma, St Louis, MO, USA), and MK-801[(+)-10,11-dihydro-5-methyl-5H-dibenzo[a,d]cyclohepten-5,10-imine hydrogen maleate](0.05mg/kg s.c; Sigma, St Louis, MO, USA) were both administered 15 min pretraining. 41 GR125487[5-Fluoro-2-methoxy-[1-[2-

  [ 3 H]8-OH-DPAT, [ 125 I]cyanopindolol and [ 3 H]GR113808, see supplementary Fig.S2. Densitometric measurements were obtained from autoradiograms using the NIH ImageJ 1.40 software after subtraction of nonspecific binding.

  , suggesting that the observed activation of Tyr 816 -TrkB by nortriptyline and escitalopram may be of functional significance in mediating long-term antidepressant actions. Since the antisera towards phosphorylated TrkB can also detect phosphorylated TrkA and both these receptors are found in hippocampus (Fig S6A-B), we performed additional experiments to confirm that antidepressants specifically increase phosphorylation at Tyr 816 of TrkB. Indeed, in reciprocal immunoprecipitation experiments with antisera towards either TrkB or Tyr 816 -TrkB, both nortriptyline and escitalopram increased Tyr 816 specifically at TrkB without regulating TrkA (Fig.

Figure 1 .

 1 Figure 1. Male and female FSL rats display emotional memory impairments and reduction of

Figure 2 .

 2 Figure 2. Alterations of total proteins and phosphorylated forms of proteins in FSL rats

Figure 3 .

 3 Figure 3. Differential effect of escitalopram and nortriptyline in restoration of emotional

Figure 4 .

 4 Figure 4. Effects of 5-HT 1A R or 5-HT 4 R agonists and antagonists and involvement of MEK

Figure 5 .Fig. 5

 55 Figure 5. Schematic representation of mechanisms involved in effects on emotional memory

Acknowledgements

This work was supported by the Swedish Research Council, Swedish Royal Academy of Sciences, Söderberg´s stiftelse, Swedish Brain Fund and Karolinska Institute Faculty Funds (KID) (T.M.E.). We thank Dr. Xiaoqun Zhang, Dr. Hongshi Qi, Serena Balasso and Eleonora Tandoi for excellent experimental support.

Conflict of Interest

The authors declare no conflict of interest.

Supplementary information is available at Molecular Psychiatry's website