Viola S Störmer
email: violastörmervstormer@fas.harvard.edu

George A Alvarez

Patrick Cavanagh

Within-hemifield competition in early visual areas limitsthe ability to track multiple objects with attention

It is much easier to divide attention across the left and right visual hemifields than within the same visual hemifield. Here we investigate whether this benefit of dividing attention across separate visual fields is evident at early cortical processing stages. We measured the steady-state visual evoked potential (SSVEP), an oscillatory response of the visual cortex elicited by flickering stimuli, of moving targets and distractors while human observers performed a tracking task. The amplitude of responses at the target frequencies was larger than that of the distractor frequencies when participants tracked two targets in separate hemifields, indicating that attention can modulate early visual processing when it is divided across hemifields. However, these attentional modulations disappeared when both targets were tracked within the same hemifield. These effects were not due to differences in task performance, because accuracy was matched across the tracking conditions by adjusting target speed (with control conditions ruling out effects due to speed alone). To investigate later processing stages, we examined the P3 component over central-parietal scalp sites that was elicited by the test probe at the end of the trial. The P3 amplitude was larger for probes on targets than on distractors, regardless of whether attention was divided across or within a hemifield, indicating that these higher-level processes were not constrained by visual hemifield. These results suggest that modulating early processing stages enables more efficient target tracking, and that within-hemifield competition limits the ability to modulate multiple target representations within the hemifield-maps of the early visual cortex.

Introduction

By directing attention to a specific region in a visual scene, information at the attended location can be selected for enhanced processing [START_REF] Laberge | Attentional Processing: The Brain's Art of Mindfulness[END_REF].

Traditionally, attention is thought of as a centrally organized process that controls selection similarly along the entire processing stream [START_REF] Broadbent | Perception and communication[END_REF]Eriksen&Yeh, 1985;Moran&Desimone, 1985). Recent studies, however, suggest that attentional mechanisms are fundamentally constrained by properties of lower-level cortical areas. For example, it is easier to process multiple targets across the left and right visual hemifields, than within the same visual hemifield (Awh&Pashler, 2000;[START_REF] Alvarez | Anatomical constraints on attention: Hemifield independence is a signature of multifocal spatial selection[END_REF]Chakravarthi&Cavanagh, 2009;[START_REF] Reardon | Bilateral attentional advantage on elementary visual tasks[END_REF]Sereno&Kosslyn, 1991). These findings suggest that separate attentional resources exist for the left and right visual fields to select multiple targets, effectively doubling the resources available when targets are distributed in both visual fields compared to when they are all in only one visual hemifield. This across-hemifield advantage is particularly pronounced in tasks that require sustained selection of targets from distractors, such as attentional tracking:

Participants can track twice as many target objects among distractors when they appear in separate visual fields compared to when they appear in the same hemifield (Alvarez&Cavanagh, 2005;Holcombe&Chen, 2012;Hudson, How, Little, 2012). These findings are consistent with the possibility that hemifield independence arises due to limitations at the earliest stages of visual processingduring sensory processing. If this were the case, sensory enhancement in visual areas should be larger for targets presented across hemifields relative to targets that are presented within the same hemifield.The present study usedelectrophysiological recordingstomeasure processing at early stages directly, enabling us to assess whether hemifieldindependence is evident during early sensory processing.

Specifically, the present study combines behavioral measures and electrophysiological recordings of steady-state visual evoked potentials (SSVEPs)over visual cortex and event-related potentials (ERPs) in an attentive tracking task (see Walter et al, in press, for a similar approach using a detection task). Participants tracked one target, or two targets that either appeared in separate visual fields (bottom-left and bottom-right) or in the same visual hemifield (bottom-right and top-right). Performance was matched across tracking conditions by adjusting target speed. Early visual processing of targets and distractors was quantified by measuring the SSVEPselicited by these stimuli (Störmer et al., 2013).

To assess later processing stages related to identification and discrimination processes, the P3 component was examined [START_REF] Polich | Updating P300: an integrative theory of P3a and P3b[END_REF].

We hypothesized that there would be greater modulation of SSVEP responses in early visual areas when attention was divided across hemifields than within a hemifield. This would provide direct evidence that attention cannot modulate early visual responses for multiple items within a hemifield, and would suggest that this constraint underlies the across-hemifield advantage. Furthermore, if later higher-order processes indexed by the P3 component show no effects of hemifield, this would suggest that attentional processing limits consist of a set of distinct constraints along the processing chain,and that their interplay, rather than one unified boundary, ultimately determines attentional capacity limits.

Methods

Participants

Fifteen volunteers participated in the experiment after giving informed consent.

Data from two participants had to be excluded from the analysis because > 40% of their trials were rejected as a result of artifacts in the EEG; data from one other participant was excluded because of technical problems with the eyetracker during the experiment. Of the remaining 12 participants (age range 18-28 years; 8 female), all were right-handed and reported normal or corrected-to-normal vision.

Stimuli

The stimuli were white arcs (quarter of a circle; 2.5° inner boundary, 1.5° width; luminance: 132 cd/m 2 ) with a narrow red outline (Figure 1A).A pair of arc stimuli was presented in each quadrant of the visual field, 7° from the center of the screen. The diameter of the inner circle of the two arcs measured 2.8°. On each trial, the direction of rotation (clockwise or counterclockwise) was determined randomly and independently for each arc pair, and throughout the tracking period the rotation direction changed at random intervals and independently of each other, moving at least 500 ms in the same direction, but never more than 3,000 ms. Within each arc pair, the motion direction change was not simultaneous for the two items, such that the arcs in a pair moved asynchronous of each other,but never touched each other. This prevented observers from tracking the two arcs as a single perceptual unit.

Each arc stimulus flickered at a distinct frequency during the rotation period, allowing SSVEP responses to be aligned with particular items in the display. In the upper right quadrant one of the arcs flickered at ~7.7 Hz (mean luminance: 60.2 cd/m 2 ), and the other one at ~9.4 Hz(mean luminance: 58.8 cd/m 2 ); in the lower right quadrant one of the arcs flickered at ~10.6 Hz(mean luminance: 66.2 cd/m 2 ), and the other one at ~12.2 Hz(mean luminance: 56.7 cd/m 2 ); in the lower left quadrant, one of the arcs flickered at ~14.2 Hz(mean luminance: 66.0 cd/m 2 ), and the other one at ~17.0 Hz(mean luminance: 53.0 cd/m 2 ); lastly, in the upper left quadrant, one of the arcs flickered at ~21.3 Hz(mean luminance: 66.1 cd/m 2 ), and the other one at ~28.3 Hz(mean luminance: 44.1 cd/m 2 ). These distinct frequencies allowed the clear separation of target and distractor processing within each stimulus pair in the SSVEP responses. The SSVEP is the oscillatory potential field generated by the visual cortex in response to flickering stimuli that has the same fundamental frequency as the driving stimulus [START_REF] Regan | Human brain electrophysiology: Evoked potentials and evoked magnetic fields in science and medicine[END_REF]. Its amplitude is increased for attended compared to unattended stimuli [START_REF] Morgan | Selective attention to stimulus location modulates the steady-state visual evoked potential[END_REF]; for a review, see Andersen et al., 2011).On half of the trials, the targets flickered at the relatively lower frequency within a pair (i.e., 7.7 Hz, 10.6 Hz, 14.2 Hz), and the distractors flickered at the relatively higher frequency (i.e., 9.4 Hz, 12.2 Hz, 17.0 Hz); this assignment was reversed on the remaining half of the trials. The arcs in the upper left quadrant were never assigned to be targets, in order to increase the number of trials and statistical power for targets in the other 3 quadrants.

The test probe at the end of the trial consisted of a red flash (6.9 cd/m 2 ) that appeared on the target on half of the trials, and on the distractor in the remaining half of the trials. The red test probe remained on the screen until the participant hit a response button indicating whether the probed item was a target. The eventrelated potential (ERP) elicited by the red test probe allowed us to examine the P3 component over central-parietal scalp sites separately forprobes on the target and the distractor (see Electrophysiological recordings and Analysis). Thiscentral-parietal P3 component reflects later identification-and decision-processes and is sensitive to the accuracy and confidence with which targets are discriminated from distractors [START_REF] Squires | Vertex potentials evoked during auditory signal detection: Relation to decision criteria[END_REF]Hillyard&Picton, 1987;[START_REF] Polich | Updating P300: an integrative theory of P3a and P3b[END_REF].

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Procedure

The experiment was conducted in a sound-attenuated and electrically shielded chamber that was dimly lit throughout the experiment. Participants were seated 57 cm in front of a 13-inch CRT monitor (1024 X 768 pixels, refresh rate: 85Hz). The background color of the screen was black (0.34 cd/m 2 ) throughout the experiment.

Participants were instructed to maintain their gaze at a white fixation cross (0.6° X 0.6°) in the center of the screen throughout each trial. Fixation was controlled by tracking participants' eyes with aSMI RED-m eyetracker(SensoriMotor Instruments). When participants moved their gaze away from fixation (>1.5°) during the tracking period, the current trial was immediately aborted.

At the beginning of each trial, a target item within a stimulus pair was highlighted in red for 800 ms. Then all stimuli turned back to white, flickering continuously at their respective frequencies from black to white (square function) and rotated for 3,400ms. At the end of the trial, one of the items within a pair was highlighted in red and the participant had to indicate whether the probed item was a target or not by pressing the left or right button on a keyboard. When two targets were tracked, participants were asked about both items in a random order (see Figure 1A) and both test probes had to be correctly identified in order to count as a correct trial response. On half of the trials, the target stimulus within a pair was probed; on the remaining half of the trials the distractor stimulus within a pair was probed.

Prior to the EEG experiment,rotation speed thresholds for 80% accuracy were obtained for each individual and condition: one target, two targets that were presented across visual hemifields, or two targets that were presented within one visual hemifield. Trial types were randomly intermixed and speed thresholds were computed online using QUEST [START_REF] Watson | QUEST: a Bayesian adaptive psychometric method[END_REF]. Participants performed 96 trials overall. The resulting speed thresholds were used in the EEG experimentto remove any performance differences between across-and within-hemifield tracking when there were two targets. Thus, participants tracked two targets that were either presented (1) across hemifields (i.e., bottom-left and bottom-right)at a fast speed,(2) within a hemifield(i.e., bottom-right and top-right) at a slower speedso that performance was matched to the across-hemifields condition; or they tracked (3) one target at the same rotation speed ("fast") asduring across-hemifield tracking (bottom-right), or(4) one target at the same rotation speed ("slow") as during within-hemifield tracking (bottom-right). Testing a single target at both the fast and slow speed allowed us to determine whether speed differences alone would affect target and distractor processing. All trial types were randomly intermixed within each block. The EEG experiment consisted of 20 blocks of 32 trials each.

Data analysis

Behavioral analysis: Individual speed thresholds (degrees/sec) were analyzed using repeated-measures analysis of variance (ANOVA) with tracking condition as the factor (single target, two targets across hemifields, two targets within a hemifield). To examine performance in the main EEG task, accuracy rates (% correct) were computedseparately for the four tracking conditions:(1) single target at fast speed, (2) single target at slow speed, (3) two targets across hemifields(fast speed), (4) two targets within a hemifield(slow speed), and analyzed by means of a repeated-measures ANOVA. Follow-up pairwise comparisons were conducted to see at which level the effectswere present.

Electrophysiological Recordings and Analysis: EEG was recorded continuously from 32 Ag/AgCI electrodes mounted in an elastic cap and amplified by an ActiCHampamplifier (BrainVision LLC). Electrodes were arranged according to the 10-10 systemwith three additional electrodes positioned inferior to the occipital sites to ensure adequate spatial sampling from the posterior scalp. The horizontal electro-oculogram (HEOG) was acquired using a bipolar pair of electrodes positioned at the external ocular canthi and the vertical electro-oculogram (VEOG) was measured at electrode FP1, located above the left eye. All scalp electrodes were referenced to an electrode on the left mastoid, and were digitized at 500 Hz.

Continuous EEG data was filtered with a bandpass of 0.01-112.5 Hz offline. The EEG analysis was carried out for correct trials only. Individual trials were rejected when contaminated with ocular artifacts. Blinks were detected using a semiautomated procedure, in which differences between minimum and maximum voltageswere compared with a threshold value. Threshold values were determined by visual inspection for each subject individually (cf., Störmer, Li et al., 2013;[START_REF] Green | Lateralized frontal activity elicited by attention-directing visual and auditory cues[END_REF]. Eyemovements were detected with the eyetracker during the recording (see Procedure), and trials in which an eyemovement occurred were excluded from the analysis.Artifact-free data was digitally re-referenced to the average reference.

The SSVEP was computed by a Fourier transform of the time interval 400 to 3,380 ms after tracking onset.SSVEP amplitudes were quantified as the absolute value of the complex Fourier coefficients for each frequency; that is, for each participant and condition the maximum absolute value within a small band of the respective stimulation frequency (+/-0.4 Hz) was chosen, and then averaged across six posterior electrodes (O1, Oz, O2, I3, Iz, I4). The SSVEP amplitudes were normalized for each condition and frequency by dividing the amplitude by the mean amplitude of target and distractor for that particular frequency separately for each participant (Andersen et al., 2011b). The normalized amplitudes were then collapsed across frequencies to reveal amplitude values for targets and distractors in each of the conditions. Our primary question is whether the magnitude of attentional modulation depends on tracking condition. Thus, we computed an index of attentional modulation by subtracting the normalized amplitude for distractors from the normalized amplitude for targets separately for each condition. The magnitude of attentional modulation across the different tracking conditions was thenexamined in two ways. First, to investigate how the attention effects would differ for withinvs. across-hemifield tracking, the indices of attentional modulation were collapsed across target location (i.e., across left and right targets in the acrosshemifieldcondition, and across top and bottom targets in the within-hemifield condition). These attentional modulations were computed separatelyfor each subject and then analyzed with arepeated-measures ANOVA to test for effects of tracking condition.

Second, we compared attentional modulations separately for each targetdistractor pair to rule out any effects due to speed alone. For example, we compared attentional modulation for 1-target-fast with attentional modulation at each of the target locations inthe across-hemifield condition (bottom-left and bottom-right quadrants), in which2targets moved at a fast speed.This additional analysis allowed us to directly compare the magnitude of attentional modulation for 1-target vs. 2targets while sensory input (i.e., flicker frequencies, target location, target speed) was matched (i.e., for targets in the bottom-right quadrant).

To examine later stages of target and distractor processing, we analyzed the P3 component of the averaged ERP to test probespresented at the end of each trial, either on a target or a distractor,for each tracking condition. The EEG was segmented into 1-s epochs starting 200 msbefore the onset of the probe and the averaged ERP waveforms were digitally low-pass filtered (-3 dB point at 25 Hz). For each participant, the mean amplitude of the ERP waveforms elicited by the test probe was measured between 300 and 400 ms at three central-parietal electrode sites (Cz, CP1, CP2). The resulting mean amplitudes were analyzed in a repeatedmeasures ANOVA with factors for test probe type (target vs. distractor) and tracking condition (single fast, single slow, across hemifields, within a hemifield).

Results

Behavior: As expected, individual rotation speed thresholds for 80% accuracydiffered between the single, across-hemifield, and withinhemifieldconditions,(F(2, 22) = 4.64, p = 0.038,  2 =0.30). As shown in Figure 1B, speed limits for within-hemifield tracking were lower than both acrosshemifield(t(11) =3.49, p = 0.005,  2 =0.53), and 1-target tracking(t(11) = 2.51, p = 0.029,  2 =0.36), but there was no significant difference between 1-target and across-hemifieldtracking(p=0.418,  2 =0.06).Thus, as shownin previous tracking tasks (Alvarez & Cavanagh, 2005;[START_REF] Holcombe | Exhausting attentional tracking resources with a single fast-moving object[END_REF], two targets could be tracked faster when they were presented across hemifields relative to when they were presented within a hemifield, but no worse than a single target.

To ensure that the observed effects were not due to differences in target location, we ran an additional group of subjects (N=6) using the same tracking task and assessed individual speed thresholds separately for tracking two targets in the upper (i.e., top-left and top-right) and lower (i.e., bottom-left and bottom-right) visual field, as well as for tracking two targets in the left (i.e., top-left and bottomleft) and right (i.e., top-right and bottom-right) visual field. No reliable differences in speed tresholds were observed for upper (261°/s, SEM: 31) vs. lower (277°/s, SEM: 27) visual field (p=0.63), or left (128 °/s, SEM: 25) vs. right (132 °/s, SEM: 26) visual field (p=0.73). Consistent with the results from the main experiment, speed thresholds for across-hemifield tracking were significantly higher relative to withinhemifield tracking (p=0.005).Given these data, we are confident that the effects described here are due to the hemifield effect, and are not driven by other asymmetries (e.g., lower visual field advantage, see [START_REF] He | Attentional resolution and the locus of visual awareness[END_REF].

The individual threshold speeds were used in the EEG experiment to match performance across conditions. Accuracy with these adjusted speeds was fairly uniform, varying within a range of 80% to 88%. An ANOVA was used to check how well performance was matched across conditions (1-target fast, 1-target slow, 2targets across, 2-targets within); it did show a main effect of condition, F(3, 33) = 4.62, p = 0.021,  2 = 0.29, but importantly, there was no reliable difference between across-hemifields relative to within-hemifield tracking (p=0.176;  2 =0.11; see Figure 1C).

---------Insert Figure 2 about here ---------Early visual processing stages: Across all four conditions, the amplitude spectrum obtained by Fourier-transformation shows clear peaks at the stimulating frequencies of the flickering target and distractor stimuli (see Figure 2). Targets elicited larger SSVEP amplitudes relative to the corresponding distractors, but as can be seen in Figure 3 the magnitude of the attentional modulation (target minus distractor) differed between tracking conditions (F(3, 33) = 4.20, p = 0.013,  2 =0.28), with particularly low attentional modulation in the 2-targets, withinhemifield condition. Follow-up contrasts confirmed that the attentional modulation during within-hemifield tracking was smallercompared to all other tracking conditions (see Figure 3A; within-hemifield vs. across-hemifields: t(11)=2.50, p=0.021,  2 =0.36; within-hemifield vs. 1-target slow: t(11)=3.32, p=0.007,  2 =0.50; within-hemifield vs. 1-target fast: t(11)=2.85, p=0.006,  2 =0.47). Indeed, the SSVEP amplitude of targets did not differ reliably from distractors in the within-hemifield condition (p=0.771,  2 =0.01), indicating that attention failed to effectively enhance visual processing for the two targets when they were presented in the same hemifield. In the across-hemifield tracking condition, the magnitude of the attentional modulation was smaller relative to single target tracking at slow speed (t(11)=2.25, p=0.046,  2 =0.32), but did not differ from single target tracking at the matched speed (i.e., fast; p=0.380,  2 =0.07).

---------Insert Figure 3 about here ---------In the second analysis, we compared attentional modulation of each targetdistractor pair separately when participants tracked one or two targets at the same speed. As shown in Figure 3B, the magnitude of attentional modulation (targetminus-distractor) was significantly reduced for both target-distractor pairs when participants tracked two targets within the samehemifield, relative to when they only tracked one target at the same speed (F(2, 22)=9.16, p = 0.005,  2 =0.45).

Pairwise-comparisons confirmed that the attention effect was reduced for the target-distractor pair in the top-right quadrant (t(11)=2.95, p=0.013,  2 =0.44), and also for the bottom-right quadrant (t(11)=2.42, p=0.034,  2 =0.34), relative to when participants tracked a single target in the bottom-right quadrant (Figure 3B, left). In contrast, there were no reliable differences in the magnitude of the attention effects for either target-distractor pair when participants tracked two targets that appeared in separate hemifields (at fast speed) compared to when they tracked one target at the same speed (bottom-left vs. single target: t(11)=0.695, p=0.502,  2 =0.04; bottom-right vs. single target: t(11)=0.908, p=0.384,  2 =0.06). Note that sensory input wasmatched when comparing the SSVEP amplitudes elicited by the target-distractor pair in the bottom-right quadrant. Thus, any differences in SSVEP amplitudes must be attributed to differences in attentional processes.

Later processing stages: Test probes on targets elicited a larger P3component than test probes on distractors across all conditions (F(1, 11) = 10.76, p = 0.03,  2 = 0.16), showing that targets were effectively discriminated from distractorsby later processing stages (Figure 4). No effect of tracking condition and no interactionswere observed, indicating that any across-hemifield advantage was not evident at these later processing stages, as might be expected given the similar values of tracking accuracy imposed across conditions.

---------Insert Figure 4 about here ---------

Discussion

It is easier to select multiple targets when they appear in separate visual fields, compared to when targets appear in the same visual hemifield (Alvarez & Cavanagh, 2005;[START_REF] Alvarez | Anatomical constraints on attention: Hemifield independence is a signature of multifocal spatial selection[END_REF]Awh&Pashler, 2000). In the present study we measured early attentional selection of multiple targets by tagging moving targets and distractors with distinct frequencies, and examined the SSVEP amplitudes elicited by these stimuli. When observers tracked two targets in separate visual fields (i.e., bottom-left and bottom-right), SSVEP amplitudes for each target were larger compared to the corresponding distractor, and not different from when tracking a single target at the same speed. In contrast, the SSVEP correlates of visual processing for targets and distractors were indistinguishable when observers tracked two targets in the same hemifield (i.e., bottom-right and top-right). These results are consistent with the possibility that the across-hemifield advantage arises at an early sensory processing level; namely, during stimulus processing itself. These results could not be explained by differences in task accuracy, which was controlled by manipulating target speed, or by differences in target speed, which alone had no effect on SSVEP modulation.

Previous studies have shown that attention can facilitate inputs from multiple separate locations at the level of the extrastriate occipital pathways [START_REF] Müller | Sustained division of the attentional spotlight[END_REF]Störmer et al., 2013). Here, we demonstrate that these early facilitatoryeffects of sustained multifocal attention are influenced by hemifield boundaries. A recent fMRI study showed two distinct peaks of retinotopically specific activation in primary visual cortex when participants divided attention across separate visual fields and within the same hemifield, suggestive of two distinct attentional "spotlights". When participants divided attention within a hemifield, however, there was also some attentional modulation in the intervening region, suggesting that attention was divided less effectively within a hemifield (MacMains& Somers, 2004). The present studyshowsa much more dramatic decrease in attentionalmodulation for targets within the samehemifield, with no measurable difference between targets and distractors,even when task performance is adjusted so that two targets could be tracked successfully.This implies that early target enhancement may not be obligatory for selecting and tracking multiple targets, but appears to make it more effective (Störmer et al., 2013).

Another recent paper showed attenuated target responses indexed by

SSVEPsfor stimuli appearing within the same visual hemifield relative to stimuli appearing in separate hemifields (Walter, et al., in press). In that study, participants were asked to detect luminance increments of flashing light-emitting diodes in the same or in opposite visual hemifields. Detection performance was slightly better across hemifields than within a hemifield, although these behavioral differences(9.5% across-hemifield advantage)were much smaller than the effectin our tracking task(230% across-hemifield advantage), consistent with theories suggesting that hemifield effects arise primarily when filtering targets from among same-hemifielddistractors using spatial attention [START_REF] Alvarez | Anatomical constraints on attention: Hemifield independence is a signature of multifocal spatial selection[END_REF][START_REF] Franconeri | Flexible cognitive resources: competitive contnt maps for attention and memory[END_REF]. Correspondingly, the SSVEP responses in their studyshow a hemifield effect of smaller magnitude (133% to 300%) than that found in the present study (523%).Importantly, in Walter et al. (in press), this hemifield difference reflects target processing alone, and not the differential processing of targets relative to same-hemifielddistractors; thus, the difference in SSVEP amplitudes could reflect a general increase in visual processing across hemifields, or, since behavior was not matched across the conditions, could be related to the lower task performance on within-hemifield trials.

Early versus late selection mechanisms

It seems surprising that early visual processing of targets and distractors was indistinguishable in the SSVEP responses during within-hemifield tracking, given that observers performed at an accuracy of 80% correct. However, it is important to note that, in order to achieve 80% accuracy, targets had to move more slowly in the within-hemifield condition than in the across-hemifield condition. One integrative interpretation of these results is that later processing stages can support tracking multiple targets, but that they do so less effectively (and thus can succeed only at slower speeds). This interpretation is consistent with the additional finding that, even for within-hemifield tracking of two targets, the targets were just as reliably discriminated from distractors as for across-hemifields tracking at a later processing stage, as reflected in amplitude modulations of the P3 component which was measured over central-parietal cortex. This implies that the differences in target selection at earlier stages, as indexed by the SSVEPs, were successfully compensated for at other higherprocessing levels. However, this only seems to be the case when targets move at slow speeds, but not when targets move at fast speeds. This suggests that higher-level processes cansupport multiple target tracking, but that the rate at which they can update representations is slower, preventing them from consistently tracking multiple fast moving targets.

Hemifield independence

Consistent with previous research (Alvarez & Cavanagh, 2005), we found evidence for independent selection of targets in the left and right visual field. We also showed through direct electrophysiological measures that this independence is reflected in modulations of early visual areas: target modulations measured by SSVEP were just as strong for a single target as for multiple targets across hemifields. Overall, the pattern of data diverges from models that assume a centrally organized attention process that distributes a unified resource equally across targets in the visual field [START_REF] Broadbent | Perception and communication[END_REF][START_REF] Moran | Selective attentiongates visual processing in the extrastriate cortex[END_REF]. Instead, it supports a model in which early target processing is facilitated independently for the left and right visual fields.

What mechanisms give rise to hemifield independence in early visual processing? The attentional modulations observed in early sensory processing pathways are likely governed by top-down bias signals from parietal and frontal brain regions. Previous functional magnetic resonance imaging (fMRI) studies have found load-dependent activation in parietal brain regions during multiple object tracking [START_REF] Culham | Attention response functions: Characterizing brain areas using fMRI activation during parametric variations of attentional load[END_REF]Jovicich et al., 2011;[START_REF] Howe | Using fMRI to distinguish components of the multiple object tracking task[END_REF]. This suggests that activity in parietal brain areas reflects control mechanisms that appoint attentional resources to targets during tracking. This framework suggests two broad categories of explanation for hemifield independence, one relating to competition between representations in early visual maps, and the other related to lateralized control mechanisms. For example, while spatial attention enhances target processing, it simultanously suppresses processing of surrounding irrelevant information [START_REF] Cutzu | The selective tuning model of attention: psychophysical evidence for a suppressive annulus around an attended item[END_REF][START_REF] Mounts | Evidence for suppressive mechanisms in attentional selection: Feature singletons produce inhibitory surrounds[END_REF][START_REF] Müller | The attentional ''spotlight's'' penumbra: Center-surround modulation in striate cortex[END_REF][START_REF] Müller | The attentional field has a Mexican hat distribution[END_REF][START_REF] Hopf | Direct neurophysiological evidence for spatial suppression surrounding the focus of attention in vision[END_REF]. If these suppressive mechanisms relied on lateral connections that are stronger within a hemifield than across hemifields because of separate hemifield representations in lower level visual areas (V1, V2, V3, LO, and MT ; [START_REF] Gardner | Maps of visual space in human occipital cortex are retinotopic, not spatiotopic[END_REF][START_REF] Bullier | Communications between cortical areas of the visual system[END_REF], then suppression zones would overlap more within the same visual field, leading to greater suppression between targets within a hemifield, and thus more confusion of targets and distractors within a hemifield [START_REF] Alvarez | Anatomical constraints on attention: Hemifield independence is a signature of multifocal spatial selection[END_REF][START_REF] Franconeri | Flexible cognitive resources: competitive contnt maps for attention and memory[END_REF][START_REF] Franconeri | The nature and status of visual resources[END_REF], and less distinct SSVEP responses for targets and distractors within a hemifield. Alternatively, it is possible that there exist independent attentional pointers for each hemifield. When targets are presented in separate visual fields, these pointers can reliably allocate resources to each target in parallel, thereby facilitating their processing effectively -just as effectively as for a single target. When targets are presented in the same visual hemifield, however, only one pointer is available that would need to switch back and forth between the targets in a serial manner, leading to less effective modulation of early visual areas. This possibility is consistent with results from transcranial magnetic stimulation (TMS) studies, which show that TMS applied to the parietal lobes impairs tracking in the contralateral hemifield (when multiple objects are tracked; [START_REF] Battelli | The role of the parietal lobe in visual extinction studied with transcranial magnetic stimulation[END_REF].

Both hypotheses are consistent with our finding of reduced attentional facilitation of targets when they appear in the same visual hemifield, and further research will be necessary to determine the extent to which map-based competition versus lateralized attentional control account for hemifield independence.

Conclusion

Our results show that the benefits of dividing attention across separate visual hemifields emerge at an early sensory level, namely during stimulus processing itself. Visual processing of multiple targets as indexed by SSVEP signals is continuously facilitated when attention is divided across the left and right visual field, possibly as effectively as for a single target. However, these early facilatory effects are greatly attenuated when attention is divided within the same visual hemifield. Higher-level identification and discrimination processes, on the other hand, do not seem to be affected by how attention is divided in the visual field, but operate less effectively, possibly reflecting the slow clock-rate of central processing.

This leads us to propose that when attention is divided within a hemifield, higherlevel attentional pointers fail to reliably reach down to early visual areas to facilitate sensory processing of multiple target stimuli. Overall then, our results point to dramatic constraints of attentional selection beginning at an early sensory processing stage. They indicate that the mechanisms of attentional selectionare limited by the architecture of the visual system, and that the capacity of the system to process multiple items at once is determined by the combination of constraintsat multiple levels of processing.

Figure captions

Figure 1 :

 1 Figure 1:Experimental procedure and behavioral results. (A) Illustration of an

Figure 2 .

 2 Figure 2.Grand-average amplitude spectrum across all subjects obtained by Fourier

Acknowledgments

This work was supported by a Marie Curie fellowship(EU Grant PIOF-GA-2012-329920to VSS), an NSF CAREER award (BCS-0953730 to GAA), and NIH EY09258 and a Chaired'Excellence and ERC POSITION (PC). We thank Phillip J. Holcombe at Tufts University for his generosity in providing space and time in his EEG laboratory for pilot experiments on this project.

amplitudes show less clear modulations for targets and distractors during withinhemifield tracking.


Zayna Chaker

Caroline George

Marija Petrovska

Jean-Baptiste Caron

Philippe Lacube

Isabelle Caillé

Martin Holzenberger
email: martin.holzenberger@inserm.fr

Hypothalamic neurogenesis persists in the aging brain and is controlled by energy-sensing IGF-I pathway

Keywords: Adult neurogenesis, IGF-I, Hypothalamus, Tanycyte, GHRH, Conditional mutagenesis

Introduction

The hypothalamus is an important structure of the forebrain that integrates and responds to a variety of hormonal and metabolic signals [START_REF] Williams | The hypothalamus and the regulation of energy homeostasis : lifting the lid on a black box[END_REF][START_REF] Coll | The hypothalamus and metabolism : integrating signals to control energy and glucose homeostasis[END_REF]. The recent discovery that production of new neurons persists in the postnatal hypothalamus has opened promising lines of research, promoting neurogenesis as potential modulator of adult hypothalamic plasticity and function. However, little is known about the extent and regulation of hypothalamic neurogenesis throughout lifespan, as well as on its possible impact on physiology later in life. Recently, proliferating glial-like cells have been detected lining the paraventricular zone of the adult hypothalamus in rodents [START_REF] Xu | Neurogenesis in the ependymal layer of the adult rat 3rd ventricle[END_REF]. Although the cell of origin of adult-born hypothalamic neurons is still a matter of -tanycytes are thought to represent the stem cell--tanycytes, which form a barrier between median eminence (ME) milieu and ventricular cerebrospinal fluid (CSF), show only limited self-renewal [START_REF] Rodríguez | 164 Rojczyk-. Hypothalamic subependymal niche: a novel site of the adult neurogenesis[END_REF][START_REF] Robins | Tanycytes of the adult hypothalamic third ventricle include distinct populations of FGF-responsive neural progenitors[END_REF]. In this study, we used conditional mutagenesis driven by a nestin-CreER T2 transgene [START_REF] Lagace | Dynamic contribution of nestin-expressing stem cells to adult neurogenesis[END_REF] to perform long-term tanycyte lineage tracing in vivo. We detected significant production of new neurons in the hypothalamus between 3 and 16 months of age, contributing to cell replacement in various hypothalamic nuclei. Interestingly, several studies suggest that the postnatal dynamics of hypothalamic neurogenesis impacts feeding regulation, but it remains unclear whether increased or decreased neurogenesis is beneficial for long-term energy balance [START_REF] Lee | Evidence that brain-derived neurotrophic factor is required for basal neurogenesis and mediates, in part, the enhancement of neurogenesis by dietary restriction in the hippocampus of adult mice[END_REF][START_REF] Kokoeva | Neurogenesis in the hypothalamus of adult mice: potential role in energy balance[END_REF][START_REF] Pierce | De novo neurogenesis in adult hypothalamus as a compensatory mechanism to regulate energy balance[END_REF]. Conversely, tanycytes are known to respond to a range of trophic factors and energy-sensing pathways [START_REF] Pérez-Martín | IGF-I stimulates neurogenesis in the hypothalamus of adult rats[END_REF], suggesting that environmental changes in diet or activity may influence neurogenesis. Circulating IGF-I is a major molecular integrator of nutrition and exercise acting on adult neurogenesis [START_REF] Llorens-Martín | Exercise modulates insulin-like growth factor 1-dependent and -independent effects on adult hippocampal neurogenesis and behaviour[END_REF]. Here, we also asked whether somatotropic signaling in adult HySC might be a molecular mechanism coordinating environmental changes and neurogenesis in the hypothalamic niche. To test this hypothesis, we induced conditional knockout of IGF-I receptor (IGF-1R) specifically in adult nestin + cells, an intervention that mimics food scarcity by genetically lowering cell sensitivity to IGF-I, and quantified short-and long-term effects of this mutation on hypothalamic neurogenesis.

M aterial and methods

Mouse models

Experimental protocols were approved by All analyses were performed on males. We backcrossed CAG-tdTomato Experimental groups of KO and control animals were analyzed 1, 6 and 13 months after induction of Cre recombination.

Tissue sampling

Mice were anesthetized and perfused transcardially with cold 4% PFA in 0.1 M PBS. Brains were post-fixed overnight at 4°C in 4% PFA, and then incubated in 0.1 M PBS with 30% sucrose until they sank. Brains were snap-frozen in isopentane at -45°C and sectioned into 30 µm slices on a freezing microtome in coronal plane from Bregma -1.22 to -2.54. Coordinates were determined using a mouse brain atlas [START_REF] Paxinos | The mouse brain in stereotaxic coordinates (2nd edition)[END_REF]. Sections were collected in 6 parallel sets of ten, with sections being 180 µm apart. All 6 sets represented comparable samples of the entire ARC and ME region, and each cell type-specific staining was performed on a given set.

Immunohistochemistry

Cell type-specific antibody staining was performed on free-floating sections, and combined with Tom + newborn cell lineage tracing. Antibodies used were: rabbit polyclonal anti-IGFsubunit antibody (sc-713, 1:200, Santa-Cruz Biotechnology), rabbit polyclonal anti-glial fibrillary acidic protein antibody (GFAP, 1:2,000; Dako), anti-nuclear Ki67 antibody (1:250; Millipore), mouse monoclonal anti-neuronal marker antibody (NeuN 1:500; Millipore), rabbit polyclonal anti-P-STAT3 antibody (1:200; Abcam), rabbit polyclonal anti-Neuropeptide Y antibody (1:500; Abcam), mouse monoclonal anti-GABA-B receptor 1 antibody (1:1,000;

Abcam), rabbit polyclonal anti-GHRH antibody (1:200; Abcam), and rabbit polyclonal antiglutamate receptor 1 antibody (AMPA subtype) (1:200; Abcam).

Cell quantification

All tissues used for quantification were imaged using a spinning disc microscope (Yokogawa spinning head, Roper/Leica). Cell densities and absolute number of neurons were measured on Z-stacks composed of 2 to 4 µm optical slices. Cells were manually counted using Z-stack treatment options of FIJI software (http://fiji.sc/F iji). Tanycytes were identified by their highly specific morphology, and based on their anatomical position with respect to the 3 rd ventricle [START_REF] Robins | Tanycytes of the adult hypothalamic third ventricle include distinct populations of FGF-responsive neural progenitors[END_REF]. To assess neuronal morphology, about 20 cells per group were analyzed by acquisition of Z-stacks of 15 to 20 optical sections per neuron at 0.5 µm intervals. 3D-reconstructions of glial cells and neurons were performed using the 3D Project FIJI plug-in.

Statistical analyses

All data are reported as mean ± SEM. The threshold of statistical significance was defined as

P < 0.

Results

Neuro-and gliogenesis occur beyond postnatal periods in the aging hypothalamic niche

To perform long-term tanycyte lineage tracing, we combine the nestin-CreER T2 transgene [START_REF] Lagace | Dynamic contribution of nestin-expressing stem cells to adult neurogenesis[END_REF] with Cre-inducible tdTomato knock-in reporter [START_REF] Madisen | A robust and high-throughput Cre reporting and characterization system for the whole mouse brain[END_REF].

We injected nestin-CreER T2 ;CAG-tdTomato +/0 mice with tamoxifen (Tam) at 3 months of age to exclude all developmental neurogenesis (Fig. 1A). Red fluorescence was efficiently induced in ependymocytes (Fig. 1B), and in --tanycytes (Fig. 1D). This new mouse model allowed cumulative recording of neurogenesis at different time points during adult life and aging. We observed that ependymal cell density increased significantly between 4 and 16 months of age (Fig. 1C; 1,565 ± 387 versus 3,676 ± 476, p < 0.05), indicating ongoing proliferation of these support cells in the aging brain. We also demonstrated for the first time a significant age-related attrition -tanycyte compartment (Fig. 1E; -34%, p = 0.02). In -tanycytes were substantially less abundant -tanycytes, and their number remained unchanged with age (Fig. 1F), corroborating the hypothesis that this cell compartment was rather transitory in the adult neurogenic process. Interestingly, the number of Tom + NeuN + cells (Fig. 1G) increased dramatically between 4 and 9 months, reaching a plateau between 9 and 16 months of age (Fig. 1H; 57 ± 3, 237 ± 39 and 196 ± 35 cells, respectively, p 4mo-9mo = 0.04). This result clearly demonstrates that production of new neurons continues in the adult hypothalamus. As some postnatal gliogenesis has been reported in this region [START_REF] Migaud | Emerging new sites for adult neurogenesis in the mammalian brain: a comparative study between the hypothalamus and the classical neurogenic zones[END_REF], we quantitatively compared neurogenic and gliogenic fate over age. At 9 and 16 months, we found few newborn cells presenting glial morphology (oligodendrocytes, microglia and astrocytes) in the ventromedial and dorsomedial hypothalamus, as compared to the number of newborn neurons (Fig. 1I-J). Importantly, we could not detect any gliogenic activity at 4 months, suggesting that limited gliogenesis developed predominantly during late adult life.

3.2. Adult neurogenesis produces specific neuronal cell-types in functionally different regions of the hypothalamus Adult neurogenesis in the hypothalamic niche was widespread and concerned multiple nuclei located in the posterior (PH), dorsomedial (DMH), ventromedial (VMH), mediobasal and lateral (LH) hypothalamus (Fig. 2A). At 9 months of age, the vast majority of newborn neurons integrated into dorso-medial hypothalamus (PH, DMH and VMH), while the arcuate nucleus (ARC) and median eminence (ME) also received some Tom + neurons (Fig. 2A; 49% in PH versus 3% in ARC). The long-term integration pattern that we observed differed substantially from the neurogenesis reported from early postnatal periods, confined predominantly to ARC and ME [START_REF] Lee | Tanycytes of the hypothalamic median eminence form a diet-responsive neurogenic niche[END_REF]. Because of this intriguing discrepancy, we aimed at characterizing which types of neuron are born in the aging hypothalamus. We checked whether neurons contributing to the regulation of food satiety were replaced in ARC and VMH, but did not find tangible evidence for colocalization of Tom + cells with neuropeptide Y (Fig. 2B; n = 6 animals, > 250 Tom + cells screened). Similarly, newborn hypothalamic cells were all negative for P-STAT3, indicating that none of them pertained to the populations of leptin-sensitive, orexigenic neuropeptide Y (NPY/AgRP) or to anorexigenic (proopiomelanocortin, POMC) neurons (Fig. 2C; n = 6, > 250 cells screened).

Interestingly, we found that the majority of Tom + adult-born cells in the aging ARC-ME were GHRH producing neurons (Fig. 2D; 68% ± 16, n = 6 animals, 25 cells screened in total). In contrast to the situation in the most ventral hypothalamus, DMH and PH contained a substantial proportion of total newborn neurons. These cells were expressing receptors for either glutamate or GABA, the two most abundant neurotransmitters in the hypothalamus (Fig. 2E-F; 59% were glutamate receptor-positive and 23% GABA receptor-positive, n = 6, > 250 Tom + cells screened). This result suggested that adult-born neurons were able to functionally integrate into pre-existing neurocircuitry, possibly as relay interneurons.

Although the cell of origin and the differentiation steps of newborn hypothalamic neurons are still a matter of debate, the anatomical disposition of Tom + NeuN + cells around the 3 rd ventricle suggested that they were potentially stemming from -tanycytes and progressively migrated into the hypothalamic parenchyma (Fig. 2G).

Suppression of IG F-I signaling in adult HySCs delays age-related decline of hypothalamic neurogenesis

To study the role of IGF-I signaling in hypothalamic neurogenesis, we used conditional gene targeting of IGF-1R. Nestin-CreER T2 ;CAG-tdTomato +/0 ;IGF-1R flox/flox mutants and nestin-CreER T2 ;CAG-tdTomato +/0 control mice were injected with Tam at 3 months of age to induce HySC-specific IGF-1R knockout. This provoked both red fluorescent label and loss of IGF-1R in all tanycytes and tanycyte progeny in mutants, and red fluorescence in the corresponding cells in control mice, allowing quantitative comparison of IGF-1R -/-and IGF-1R wt/wt newborn cell lineages. We confirmed that tanycytes, ependymocytes, and neurons all express high levels of IGF-1R in wild type animals (Fig. 3A-B). In contrast, adult-born Tom + neurons in mutants were completely devoid of IGF-1R (Fig. 3B, right panel).

Using the neuronal marker NeuN, we quantified Tom + newborn mature neurons in the hypothalamic niche over age, and observed significantly increased neuronal production in mutants compared to controls at 4 months (Fig. 3C; 158 ± 23 versus 57 ± 3, p 4mo = 0.04), and at 9 months (Fig. 3C; 468 ± 60 versus 237 ± 39, p 9mo = 0.008). Despite noticeable age-related decline of neurogenesis in both groups between 9 and 16 months (-29% in KO versus -17% in controls), mutants tended to preserve more adult-born neurons at long-term (Fig. 3C; 331 ± 93 versus 196 ± 35 cells, p 16mo = 0.24). Of critical note, complete suppression of IGF-I signaling in adult tanycytes did not affect gliogenesis in the aging hypothalamus (9 mo: 48 ± 11 versus 57 ± 27, and 16 mo: 28 ± 12 versus 31 ± 10, NS). Interestingly, the cumulative integration in mutants (Fig. 3D) was similar in proportion to controls (Fig. 2A), confirming that the absolute number of newborn neurons was significantly increased in KO animals in all hypothalamic nuclei, and also along the antero-posterior axis (Fig. 3E). Of important note, most newborn neurons originating from the 3 rd ventricle seemed to have migrated long distances before integrating into hypothalamic nuclei in KO and control animals (Fig. 3E). These data clearly demonstrate that deletion of IGF-1R in adult HySC dramatically enhance hypothalamic neurogenesis, both at short and at long-term.

In addition to the impact on neurogenesis, IGF-I signaling also affected the morphology of newborn neuron selectively in the ARC-ME region (Fig. 3F-G nerve cells in the ARC-ME region appeared to be conspicuously more tortuous than in controls at 9 and 16 months of age (Fig. 3G). To quantify tortuosity, we defined dendritic linearity index as curvilinear length divided by the straight line connecting the ends of the measured segment [START_REF] Irintchev | Structural and functional aberrations in the cerebral cortex of tenascin-C deficient mice[END_REF]. We found that dendrites of IGF-1R -/-neurons were significantly more tortuous than controls (Fig. 3H; KO: 1.09 ± 0.01 and controls: 1.04 ± 0.01, n = 4-5, p = 0.04). Moreover, IGF-1R null neurons also displayed significantly more dendrites sprouting from the soma (Fig. 3G; 4.6 ± 0.5 versus 2.0 ± 0.2 dendrites per cell, n = 4-5, p = 0.012). These results suggest that outgrowth is strongly dependent on IGF-I signaling also in the adult brain, and that these effects might be specific to neuroendocrine neurons in arcuate nucleus and median eminence.

3.4. IG F-I signaling controls -tanycyte maintenance by modulating their division pattern over age

We next asked whether enhanced neurogenesis was accompanied by stem/progenitor cell depletion with age. To address this point, we determined --tanycyte density in vicinity of the 3 rd ventricle. Importantly, at 4 months, KO and controls started with the same number of -tanycytes (Fig. 4A). In control animals, we observed a marked attrition of this cell compartment in control animals between 4 and 16 months (-48%). In contrast, mutants maintained and even increased -tanycytes with age (+33%). These differences resulted in twice as many -tanycytes in mutants compared to controls, both at 9 and 16 months of age (Fig. 4A-B; +132% at 9 months, p 9mo = 0.02, and +108% at 16 months, p 16mo < 0.0001). However, we did not observe such age-dependent differences in -tanycyte density comparing KO and controls (Fig. 4C). Starting with the same number of cells at 4 months, mutants tended to have higher -tanycyte density at 9 months of age (+78%, p = 0.24), but this trend disappeared at age 16 months. Similarly, non-neurogenic ependymal cells seemed unaffected by lifelong suppression of IGF-I signaling (Fig. 4D). Thus, inhibition of IGF signaling in adult HySC prevented age-related depletion selectively in -tanycytes.

Intriguingly, mutants maintained the pool of -tanycytes between 9 and 16 months, but produced substantially less neurons at 16 months compared to 9 months. In fact,tanycyte density (Fig. 4A) and number of newborn neurons (Fig. 3C) were no longer correlated in the 16-month-old mutants. To explain this discrepancy, we checked whether proliferation propensity decreased in IGF-1R -/--tanycytes between 9 and 16 months of age.

We found that the proportion of proliferating -tanycytes was similar at both ages in mutants (Fig. 4E), indicating that IGF-1R -/--tanycytes at 16 months were preferentially self-renewing and less differentiating. This result strongly points to a late-life shift in cell fate choice induced by lifelong suppression of IGF-I signaling in HySC. Collectively, these data demonstrate that deletion of IGF-1R from nestin + cells in the adult hypothalamus allows -tanycytes specifically with age, possibly through lifelong control of cell division pattern.

Discussion

Neurogenesis in aging versus early-postnatal hypothalamus

Using a conditional genetic marker, we performed long-term lineage tracing of nestin + neuronal progenitors in the hypothalamus. This allowed recording neurogenesis over extended periods of adult life and revealed for the first time quantitative aspects of neuronal replacement in this adult stem cell niche. Published data on SC-dependent maintenance of other adult tissues shows that these processes generally decline with increasing age.

Therefore, it is very likely that our findings comprise most if not all of adult neurogenesis after 3 months, and that the bulk of this neurogenesis occurred between 3 and 9 months of age. We demonstrated that hypothalamic neurogenesis generated several types of neurons.

Interestingly, identity as well as integration sites of these neurons differed markedly from what has been described for hypothalamic neurons born during postnatal periods. Adult-born neurons mostly integrated into PH, DMH and VMH nuclei, and a smaller proportion was found in the arcuate nucleus and median eminence. Moreover, most of these new neurons were either interneurons receiving GABA and glutamate afferences in posterior hypothalamus, or GHRH neurons in the most ventral regions. We did not find any anorexigenic or orexigenic leptin-sensitive newborn neurons during aging, contrasting with what has been documented for early postnatal hypothalamic neurogenesis [START_REF] Kokoeva | Neurogenesis in the hypothalamus of adult mice: potential role in energy balance[END_REF]Rojczyk-ska et al., 2014). This intriguing observation suggests that early and late adult neurogenesis of the hypothalamus might contribute to different physiological functions. Several reports show that postnatal neurogenesis in the hypothalamus is controlling energy homeostasis during the first two months of adulthood [START_REF] Sousa-Ferreira | Role of hypothalamic neurogenesis in feeding regulation[END_REF], and accordingly concerns NPY, POMC and P-STAT3 neurons. We propose that the here observed late-life hypothalamic neurogenesis is mainly targeting relay interneurons that might be important for tuning the activity of specific neuronal circuits in selected nuclei of the hypothalamus.

Adult-born G HRH-producing neurons

Another surprising observation was that GHRH neurons continued to be produced in the brain throughout adult life. These neurons are important elements in the forward and retroregulation of the somatotropic neuroendocrine axis. Their nerve endings extend to the median eminence, and GHRH secretion eventually induces growth hormone release from the pituitary into the peripheral blood. It is well-documented that GHRH neurons decrease in number with age [START_REF] Kuwahara | Age-related changes in growth hormone (GH) cells in the pituitary gland of male mice are mediated by GH-releasing hormone but not by somatostatin in the hypothalamus[END_REF]. Thus, de novo neurogenesis of specialized neuroendocrine neurons as we demonstrated here may open promising avenues of research for regenerative medicine and novel therapeutic strategies targeting replacement of neuropeptide and hormone-producing cells in the CNS.

IG F-I signaling, neurogenesis and metabolism

In this study, we demonstrated that hypothalamic neurogenesis continues in the adult and aging brain, which implies that it is controlled by specific molecular pathways throughout lifespan. Previous studies have shown that cell replacement in this new niche is tightly regulated by nutrient-sensing factors, such as brain-derived neurotrophic factor (BDNF), ciliary neurotrophic factor (CNTF) and fibroblast growth factors FGF-2, -10 and -18 [START_REF] Kokoeva | Neurogenesis in the hypothalamus of adult mice: potential role in energy balance[END_REF][START_REF] Robins | Tanycytes of the adult hypothalamic third ventricle include distinct populations of FGF-responsive neural progenitors[END_REF]. Moreover, hypothalamic neurogenesis is known to be highly sensitive to nutritional conditions and metabolic status of the animal. For instance, rodent obesity models display a significant decrease of postnatal neurogenesis in the arcuate nucleus and median eminence [START_REF] Mcnay | Remodeling of the arcuate nucleus energy-balance circuit is inhibited in obese mice[END_REF]. Inversely, inhibiting hypothalamic neurogenesis is sufficient to alter weight and metabolic balance at short-term [START_REF] Lee | Tanycytes of the hypothalamic median eminence form a diet-responsive neurogenic niche[END_REF]. Here, we propose that IGF-I signaling, a potent energy-sensing pathway, could serve as a molecular bridge connecting nutrition and cell replacement during adult life and aging. Down-regulation of IGF-I signaling, which is a genetic intervention mimicking conditions of low environmental energy resources, prolongs individual lifespan and preserves regenerative potential of stem cells [START_REF] Ratajczak | Higher number of stem cells in bone marrow of circulating Igf-1 level low Laron dwarf mice -novel view on Igf-1, stem cells and aging[END_REF]. Intriguingly, mutant mice used for the present study also develop a metabolic phenotype at 16 months of age, becoming leaner and more insulin-sensitive with age (Chaker et al., in press). While mostly explained by important changes in olfactory bulb neurogenesis and olfactory sensory function, this phenotype might also be affected by the increased hypothalamic neurogenesis observed at 4 and 9 months of age in mutants. Collectively, our work suggests that the dynamics of neurogenesis in the hypothalamic niche adapts itself to changes in environmental resources and sensory signals. This plasticity seems to be controlled lifelong by IGF signals, and might in turn exert a feed-forward effect on regulation of individual metabolic homeostasis.

Interestingly, in mutants and controls, the number of tanycytes far exceeded neurons, raising the issue of whether only a subset of tanycytes has the capacity to generate new neurons.

Similarly, as the number of tanycytes was the same in mutants and controls at 4 months, it will be important to parse whether the increase in lineage-traced neurons at all ages in mutant mice stems from increased proliferation rates alone or depends also on increased survival of adult-born neurons.

-tanycyte self-renewal during aging Deletion of IGF--tanycyte division pattern towards more self-renewal at long--tanycyte or ependymal cell number. This selective tanycyte subset is concordant with IGF-I having more dramatic effects on neurogenesis occurring in the medial periventricular region of the niche, as demonstrated at short-term in 8-week-old rats [START_REF] Pérez-Martín | IGF-I stimulates neurogenesis in the hypothalamus of adult rats[END_REF]. One pending question is whether the cellular mechanism by which IGF-I signaling controls neurogenesis in the hypothalamus is cell autonomous or not. Indeed, ependymocytes, which are an important component of the hypothalamic niche, are also knockout for IGF-1R. This could be sufficient to modify neurogenesis independently of direct effects on stem/progenitor cells, as demonstrated for other genes in subependymal cells of the SVZ [START_REF] Lim | Noggin antagonizes BMP signaling to create a niche for adult neurogenesis[END_REF].

Conclusions

This work constitutes first proof that highly specific neurogenesis exists in the aging hypothalamus, and that its dynamics depend on the IGF-I pathway. The discovery of lifelong cellular plasticity provides novel insights and perspectives for neuroendocrinology and for the development of hormone replacement therapies. 3. The data contained in this manuscript have not been previously published, have not been submitted elsewhere and will not be submitted elsewhere while under consideration at Neurobiology of Aging.

4.

Ani .

*Verification

Chaker et al. )#

  ). Whether KO or control, adult-born neurons newly integrated into the ARC-ME had significantly smaller soma than those integrated into VMH, DMH and PH (at 16 months of age, KO: 178 for ARC-ME and n = 18 cells for posterior regions; p < 0.001). Interestingly, extensions of IGF-1R -/-

F

  igure L egends F ig. 1. Dynamics of neurogenesis in the aging hypothalamic niche. (A) Schematics of inducible transgenic approach used for in vivo lineage tracing. Administration of Tam activated Cre recombinase in all nestin + cells, inducing intense red label in these cells and their progeny. All mice were injected at 3 months of age and analyzed 1, 6 and 13 months after Tam-induced labeling. (B) Representative micrograph of recombined ependymal cells (red). Sections were counterstained with DAPI (blue). (C) Age-dependent dynamics of ependymocyte population; p = 0.05. (D) Representative micrograph of --tanyctes (red) lining the 3 rd ventricle (3V). Section were counterstained with DAPI (blue). (E and F) Age-dep -tanycytes (E; p tanycytes (F). (G) Sections of dorso-medial hypothalamus stained with neuronal marker NeuN. Arrows indicate adult-born neurons. Scale bars: inset. (H) Age-dependent evolution of neuronal population; p = 0.04. (I) Absolute number of Tom + glial cells detected in the hypothalamic niche at 9 and 16 months. Quantifications were performed on 10 sections per animal and n 4mo = 2, n 9mo = 6, n 16mo = 5 animals per group. (J) 3D Z-projection image representing newborn glial cells (astrocytes co-labeled with GFAP). F ig. 2. Identity of newborn hypothalamic neurons. (A) Left panel: Schematic representation of hypothalamic nuclei showing neurogenesis, namely posterior (PH), dorsomedial (DMH), ventromedial (VMH), lateral (LH) and arcuate nucleus (ARC). Right panel: quantification of the proportion of newborn neurons (% of total Tom + neurons) having integrated into the respective nucleus. (B-F) Double labeling of Tom + neurons in (B) the ARC-ME region with functional marker NPY and (C) VMH-DMH with P-STAT3 marker, showing no colocalization with Tom + cells. (D) GHRH staining colocalizing with a subset of Tom + cells in ARC-ME. Scale bars: 50 , 200 in GHRH inset in merge inset. (E and F) Tissue sections representing DMH nuclei stained using anti-glutamate receptor (E) and anti-GABA receptor (F) antibodies. Scale bars: 1 (G) Representative micrographs of adult-born Tom + NeuN + neurons (arrows) located close to the 3 rd ventricle (3V; delimited with dashed lines). Arrangement of these new neurons relative to Tom + tanycytes is compatible with the supposed neurogenic role of tanycytes. Depicted events could represent successive stages of adult hypothalamic neurogenesis, with new neurons migrating away from the ventricle walls into the brain parenchyma. All analyses were performed on 9-month-old animals. F ig. 3. I G F-I signaling and lifelong regulation of hypothalamic neurogenesis. (A) IGF-1R expression in tanycytes (left) and ependymal cells (right) in the hypothalamic niche. 3 rd ventricle (3V) walls are delimited with dashed lines. Arrows indicate Tom + IGF-1R + . (B) Tom + newborn neurons express IGF-1R in controls (left), while in mutants they do not ; in insets. (C) Number of newborn neurons in the adult hypothalamus over age. n 4mo = 2-3 and n 9mo-16mo = 5-6, p = 0.04 at 4 months, and p = 0.008 at 16 months. (D) Proportion of newborn neurons integrated in each hypothalamic nucleus (% of total Tom + neurons in the niche). (E) Neuronal integration map in controls versus mutants reported on representative coronal sections of the brain, from Bregma -1.22 to -2.54. The map was built by compiling all Tom + cells from 5 animals for each group, using the same number of sections per genotype. (F and G) Representative micrographs of newborn neurons integrated into DMH-VMH-PH (F) and ARC-ME (G) regions of 16-month-old animals (H) Dendrite morphology of ARC-ME neurons at 16 months of age. Scale F ig. 4. I G F--tanycytes throughout lifespan. (A-D) Tanycyte and ependymal cell densities in mutant and control mice over age. (A)tanycyte density; n = 5-6, p 9mo = 0.017, p 16mo < 0.0001. (B) tanycyte abundance in KO versus control animals. Scale bars: 50 (C) -tanycyte density. (D) Ependymal cell density. (E) -tanycytes at 9 and 16 months of age in mutants and controls. VERIFICATION 1. The authors declare they have no conflict of interests. 2. This work was funded by INSERM, UPMC and LECMA. Fellowships were provided by AXA Research Fund and FRM.

  Figure(s)

A cknowledgments

We thank Dr. A.J. Eisch for providing the nestin-CreER T2 mouse. This work was funded by INSERM, UPMC and LECMA. Fellowships were provided by AXA Research Fund and FRM.

Disclosure statement

The authors declare they have no conflict of interests.


Implementation of agronomical and geochemical modules into a 3D groundwater code for assessing nitrate storage and transport through unconfined Chalk aquifer Géraldine Picot-Colbeaux, Nicolas Devau, Dominique Thiéry, Marie Pettenati, Nicolas Surdyk, Marc Parmentier, Nadia Amraoui, François Crastes de Paulet, and Laurent André BRGM, French Geological Survey, Orléans, France (g.picot@brgm.fr) Chalk aquifer is the main water resource for domestic water supply in many parts in northern France. In same basin, groundwater is frequently affected by quality problems concerning nitrates. Often close to or above the drinking water standards, nitrate concentration in groundwater is mainly due to historical agriculture practices, combined with leakage and aquifer recharge through the vadose zone. The complexity of processes occurring into such an environment leads to take into account a lot of knowledge on agronomy, geochemistry and hydrogeology in order to understand, model and predict the spatiotemporal evolution of nitrate content and provide a decision support tool for the water producers and stakeholders. To succeed in this challenge, conceptual and numerical models representing accurately the Chalk aquifer specificity need to be developed. A multidisciplinary approach is developed to simulate storage and transport from the ground surface until groundwater. This involves a new agronomic module "NITRATE" (NItrogen TRansfer for Arable soil to groundwaTEr), a soil-crop model allowing to calculate nitrogen mass balance in arable soil, and the "PHREEQC" numerical code for geochemical calculations, both coupled with the 3D transient groundwater numerical code "MARTHE". Otherwise, new development achieved on MARTHE code allows the use of dual porosity and permeability calculations needed in the fissured Chalk aquifer context. This method concerning the integration of existing multi-disciplinary tools is a real challenge to reduce the number of parameters by selecting the relevant equations and simplifying the equations without altering the signal. The robustness and the validity of these numerical developments are tested step by step with several simulations constrained by climate forcing, land use and nitrogen inputs over several decades. In the first time, simulations are performed in a 1D vertical unsaturated soil column for representing experimental nitrates vertical soil profiles (0-30m depth experimental measurements in Somme region). In the second time, this approach is used to simulate with a 3D model a drinking water catchment area in order to compared nitrate contents time series calculated and measured in the domestic water pumping well since 1995 (field in northern France -Avre Basin region). This numerical tool will help the decision-making in all activities in relation with water uses.