activity during pursuit eye movement control

NeuroImage 63 (2012) 339–347

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Direct recordings in human cortex reveal the dynamics of gamma-band [50–150 Hz] activity during pursuit eye movement control Julien Bastin a, b, c,⁎, Pierre Lebranchu a, Karim Jerbi d, Philippe Kahane b, c, e, Guy Orban f, Jean-Philippe Lachaux d, Alain Berthoz a a

UMR 7152, CNRS-Collège de France, Laboratoire de Physiologie de la Perception et de l'Action, Paris, France Université Joseph Fourier, Fonctions Cérébrales et Neuromodulation, Grenoble, France INSERM, U836, Grenoble Institut des Neurosciences, Grenoble, France d INSERM, U821, Brain Dynamics and Cognition, Université Claude Bernard, Lyon 1, Lyon, France e Epilepsy Surgery Unit, CHU Michallon, Grenoble, France f Laboratorium voor neuro-en psychofysiologie, K.U. Leuven Medical School, Leuven, Belgium b c

a r t i c l e

i n f o

Article history: Accepted 8 July 2012 Available online 20 July 2012 Keywords: Anticipation Frontal eye field Invasive electroencephalography (iEEG) Prediction Motor inhibition Saccades

a b s t r a c t The time course of neural activity in human brain regions involved in mediating pursuit eye movements is unclear. To address this question, we recorded intracerebral electroencephalography activity in eight epileptic patients while they performed a pursuit task that dissociates reactive, predictive and inhibited pursuits. A sustained gamma band (50–150 Hz) activity corresponding to pursuit maintenance was observed in the pursuit (and not saccade) area of the frontal eye field (FEF), in the ventral intraparietal sulcus (VIPS) and in occipital areas. The latency of gamma increase was found to precede target onset in FEF and VIPS, suggesting that those areas could also be involved during pursuit preparation/initiation. During pursuit inhibition, a sustained gamma band response was observed within prefrontal areas (pre-supplementary-motor-area, dorso-lateral prefrontal and frontopolar cortex). This study describes for the first time the dynamics of the neural activity in four areas of the pursuit system, not previously available in humans. These findings provide novel timing constraints to current models of the human pursuit system and establish the relevance of direct recordings to precisely relate eye movement behavior with neural activity in humans. © 2012 Elsevier Inc. All rights reserved.

Introduction The ability to track a moving object and maintain its image stationary on the fovea relies on pursuit eye movements. Predictive mechanisms are necessary to perform accurate pursuit, because delays involved between retinal signals processing and eye velocity commands generation have to be compensated. Hence, predictive pursuit can be transiently observed in the absence of visual stimulus (Becker and Fuchs, 1985; Bennett and Barnes, 2003) and its control relies on extraretinal signals specifying expected target velocity (Newsome et al., 1988). Prediction can also be isolated by asking subjects to pursue a target moving repetitively and predictably (Barnes and Asselman, 1991). In that case, the first unpredictable pursuit cannot match precisely target velocity because of visuo-motor delays (reactive pursuits, RP), since RP is primary controlled by retinal information specifying target velocity (Lisberger and Westbrook, 1985). If the pursuit stimulus is repeated, pursuit

⁎ Corresponding author at: Inserm U.836, Grenoble Institute of Neuroscience, Bâtiment Edmond J. Safra des Neurosciences, Chemin Fotuné Ferrini, Université Joseph Fourier, Site Santé La Tronche, BP 170 38042 Grenoble Cedex 9, France. Fax: +33 4 56 52 05 98. E-mail address: [email protected] (J. Bastin). 1053-8119/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2012.07.011

accuracy improves with few pursuit repetitions and delays are compensated (predictive pursuits, PP). Predictive pursuits are controlled via a combination of retinal and extraretinal signals (Kao and Morrow, 1994). Predictive mechanisms are distributed in frontal and temporal pursuit areas. In monkeys, neuronal activity in the ventral part of medial superior temporal areas (MSTv) is modulated by anticipatory mechanisms, as MSTv activity continues during pursuit when part of the target trajectory is masked (Newsome et al., 1988). In monkeys’ frontal and supplementary eye fields (FEF and SEF), neurons were also shown to play a critical role during predictive pursuits (Fukushima et al., 2002a; Heinen, 1995; Missal and Heinen, 2004; Shichinohe et al., 2009). In humans, the functional anatomy of reactive and predictive pursuit processes have been extensively examined using functional magnetic resonance imaging (fMRI) (Burke and Barnes, 2008; Ding et al., 2009; Lebranchu et al., 2010; Lencer et al., 2004; Nagel et al., 2006, 2008; Schmid et al., 2001), but surprisingly little is known about the time course of neural activity in the human pursuit system, despite its critical functional relevance. Previous neuroimaging studies of the human pursuit system could not investigate the time course of neural activity because of the limited temporal resolution of fMRI. Therefore the relationship between cortical activity and pursuit behavior remains unclear in humans. To address this issue, we recorded intracranial

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J. Bastin et al. / NeuroImage 63 (2012) 339–347

electroencephalographic signals (iEEG) in 8 epileptic patients while they performed a modified version of the remembered pursuit task (Barnes and Donelan, 1999). Materials and methods Patients and recordings Eight patients suffering from drug-resistant partial epilepsy participated in this study. They all gave an informed consent and the study was approved by the Grenoble hospital ethical committee. Patients had normal vision without corrective glasses. Table S1 summarizes patients’ demographics and clinical information. To identify the epileptic focus, patients underwent intracerebral recordings by means of stereotactically implanted (Lachaux et al., 2003) multilead depth electrodes (sEEG). For each patient, 13 to 17 semi-rigid electrodes were implanted depending on the patient; each electrode had a diameter of 0.8 mm and comprised 6 to 18 leads of 2 mm, 1.5 mm apart (Dixi, Besançon, France), depending on the target region. The electrode contacts were identified on each individual stereotactic scheme, and then anatomically localized using the proportional atlas of Talairach and Tournoux (1988) after a linear-scale adjustment used to correct for size differences between the patient's brain and the brain in the Talairach atlas. Electrode positions were visualized with respect to each patient brain anatomy (Activis, Lyon, France and Brainvisa, http://brainvisa.info). Neuronal recordings were conducted using an audio–video-EEG monitoring system (Micromed, Treviso, Italy), which allowed the simultaneous recording of 128 depth-EEG channels sampled at 512 Hz [0.1–200 Hz bandwidth]. One of the contact sites in the white matter was chosen as a reference. Before analysis, all signals were re-referenced to their nearest neighbor on the same electrode, 3.5 mm away, yielding a bipolar montage. The patients were seated in a dark electrically shielded and sound attenuated room. Eye movements were monitored at 512 Hz by an infrared limbus tracking technique (IRIS Skalar Medical, Delft, Netherlands) for 6 patients and 2 patients’ eye movements were monitored with an electro-oculogram. Eye signals were calibrated at the beginning and end of each block of trials. Patients were shortly trained before electrophysiological recordings to ensure correct task execution. Experimental tasks All stimuli were displayed using Presentation (Neurobehavioral Systems, Albany, CA) on a 17″ CRT monitor at 85 Hz. The timing of stimulus delivery was controlled via a TTL pulse that was sent by the stimulation PC to the EEG acquisition PC and to the eye-tracking acquisition PC to synchronize all acquisition systems. The experiment consisted of 10 blocks of pursuit trials followed by 1 block of saccade trials. Pursuit trials The pursuit paradigm (Fig. 1A) was adapted from the remembered pursuit task (Barnes et al., 2000). Patients were required to repeatedly pursue a visual target (subtending 1°) that was textured by a grid of black and white squares, so that target average luminance was identical to background luminance. In addition, two fixation cues subtending 1° of visual angle were placed 3° above and below the screen centre and were always visible during pursuit trials. The target to pursue was horizontally displaced and its velocity profile followed a single cycle sinusoidal law of motion constrained to start at zero. Sinusoidal waveforms were chosen because computational modeling suggests that target dynamics knowledge is necessary for predictive control of pursuit for sinusoidal targets, in contrast to linear pursuit (Shibata et al., 2005). The period was fixed (1500 ms) and amplitude

and direction of target displacement was varied between trials (±3, 5, 7°). Each pursuit trial was composed of three to five successive presentations of identical target displacement. Fixation duration (i.e., the inter stimulus interval, ISI) was randomly adjusted in the 800–1200 ms range. The time course of a typical pursuit trial is illustrated in Fig. 1 (see also Supplemental video 1). A pursuit trial began by a black screen that signaled the onset of a new trial. This was necessary because patients were required to hold fixation during the first target motion (Pursuit Inhibition trials, PI). Note that the direction and/or amplitude of this first target displacement always differed during PI compared to the following target motion stimuli so that sensory signals during PI were not relevant relative to the following pursuits (Barnes et al., 2000). To reinforce the build-up of anticipation, target presentation was always preceded (500 ms) by an audio warning signal (80 ms duration, 500 Hz tone) and a 500 Hz audio cue was given during target displacement (500 Hz, 1500 ms). Target was extinguished as soon as its movement ended. Finally, for some trials (66%), a catch target presentation was introduced. During these catch presentations, audio cues were given but visual target was not displayed. To maintain a maximal level of target expectation, catch presentation could occur after the third (33% trials, Fig. 1), fourth (33% trials) target presentation, or not at all (33% trials). Saccade trials The saccade task was designed to be as similar as possible to the pursuit task: target eccentricities (±3, 5, 7°) and audio cues (pre-cue 500 ms before target onset and audio cue during 1500 ms) were identical to those used in the pursuit task. During saccade trials (SA), patients were instructed to perform saccades as fast and as accurately as they could. Targets were displayed during 1500 ms. Behavioral analyses Eye movements were analyzed using Matlab (Matworks Natick, MA). For 7 out of 8 patients, the quality of the eye movement recordings allowed us to quantify the frequency saccades during pursuit trials. Saccades characteristics were extracted and the fast phase components were removed from eye velocity trace using a combined acceleration and velocity thresholds procedure (Barnes, 1982; Bennett and Barnes, 2003). Gaps were joined using linear interpolation. Once saccades were detected, their characteristics were stored for further analyses and eye movement velocity trace was low-pass filtered at 30 Hz using a zero-phase digital filter (Butterworth, order 2). Eye movement onset in pursuit trials was determined using the following two procedures. First, we detected the point at which eye velocity reached 10% the peak eye velocity during the first half-cycle and pursuit latency was determined by performing a linear regression back to the abscissa from a segment of 200 ms of eye velocity starting at this 10% point (Burke and Barnes, 2008; Krauzlis and Miles, 1996). Secondly, we tested saccade occurrence within the beginning of the trial and computed the latency relative to target onset of this first catch-up saccade (catch-up latency). These two eye movement onsets were computed for all pursuit trials and visually inspected after automatic detection. Trials showing invalid eye onset were discarded for further behavioral analyses. The earlier of the two eye movement onsets was chosen to quantify eye movement latency. Paired t-tests were used to compare behavioral data during RP and PP. Electrophysiological analyses EEG signals were evaluated with the software package for electrophysiological analysis (ELAN-Pack) developed in the laboratory (INSERM U1028, Lyon, France) and Matlab algorithms. For each single trial, bipolar derivations were computed between adjacent electrode


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Fig. 1. Experimental stimuli and task. (A) Schematic illustration of stimuli and their timing during pursuit trials. The percentage of pursuit trials that ended with a pursuit or a catch are indicated on the right; (B) Representative sample of eye position trace in a pursuit trial (Patient 7, trial 1). Dark line: eye position; grey curve: target position; Dashed grey curve indicates expected target displacement (during catch trial, visual cues are absent and only auditory cues are delivered to subjects); Gray bars indicate beginning and end of audio cues. Dashed vertical lines indicate beginning and end of target motion. FIX, fixation; PI, pursuit inhibition; RP, reactive pursuit; PP, predictive pursuits; CA, catch trial.

contacts to suppress contributions from non-local assemblies and assure that the bipolar sEEG signals could be considered as originating from a cortical volume centered within two contacts (Jerbi et al., 2009b). To determine the time course of gamma band amplitude, continuous SEEG signals were first bandpass filtered in multiple successive 10 Hz wide frequency bands (e.g., 11 bands from [50–60 Hz] to [140–150 Hz]) using a zero phase shift noncausal finite impulse filter with 0.5 Hz roll-off. Next, for each bandpass filtered signal we computed the envelope using standard Hilbert transform. The obtained envelope has a sampling rate of 64 Hz (i.e., one time sample every 15.625 ms). Again, for each band this envelope signal (i.e., timevarying amplitude) was divided by its mean across the entire recording session and multiplied by 100. This yields instantaneous envelope values expressed in percentage (%) of the mean. Finally, the envelope signals computed for each consecutive frequency bands (e.g., 11 bands of 10 Hz intervals between 50 and 150 Hz) were averaged together to provide a single time series (the high gamma-band envelope) across the entire session. By construction, the mean value of that time series across the recording session is equal to 100. Note that computing the Hilbert envelopes in 10 Hz sub-bands and normalizing them individually before averaging over the broadband interval allows us to counteract a bias toward the lower frequencies of the interval induced by the 1/f drop-off in amplitude. The onset of gamma power increase relative to fixation (a 500 ms time interval) was determined as the first time point at which gamma power was above the 95% confidence interval measured during fixation (i.e., the average power during fixation across trials + 1.96 SEM). Comparisons between experimental conditions were performed separately for each recording site using Friedman non-parametric tests applied on the gamma band envelope in the [− 500 1500 ms] time window. Friedman tests were followed by post-hoc tests (Tukey–Kramer). A contact-pair was considered selective to pursuit execution if the gamma band response was greater during RP than during PI and fixation. A contact-pair was considered active during pursuit inhibition if gamma band activity was higher during pursuit inhibition than during both reactive pursuit and saccades.

The level of significance was set to 0.05. All p-values were corrected for multiple comparisons across multiple dimensions (number of bipoles for each patient) with a false discovery rate (FDR) procedure (Genovese et al., 2002). Results Oculomotor performance On average, participants performed 101 (±9) reactive pursuit (RP) and 269 (±24) predictive pursuit eye movements (PP). Fig. 1B shows an example pursuit trial, illustrative of the group level behavior. Overall, the participants initiated the pursuit later during RP than during PP (RP: 117±40 ms; PP: 88±29 ms; t=2.55; pb 0.05; df=7). Also, the lag between eye and target motion during the initial phase of the pursuit (time difference between the first velocity peaks) was greater during RP than during PP (RP: 69±52 ms; PP: 44±39 ms; t=4.19; pb 0.05; df=7). Participants performed more catch-up saccades during RP than during PP (RP: 1.25 ± 0.58; PP: 0.86 ± 0.37; t = 3.65; p b 0.05; df = 6) and a larger proportion of RP trials started with a catch-up saccade within the first 300 ms (RP:40% ± 19%; PP: 28% ± 16%; t = 3.03; p b 0.05; df = 6). Overall, reactive pursuit was thus characterized by longer onset latency, larger lag between eye and target motion and a larger number of catch-up saccades. Electrophysiological results Fig. 2A shows the distribution of electrode entry points in this study. Seven patients (P1–P7) had almost all electrodes in the frontal and temporal lobe. Only patient 8 had electrodes in the left occipital-parietal lobe. The general pattern of time-frequency activity in three representative electrode contact-pairs is shown Fig. 3. In the following, we focus on high frequency responses (50–150 Hz). A quantitative analysis of the all patients’ spectrograms revealed that the mean frequency peak in the gamma band across task-sensitive contact-pairs was 83 ± 17.2 Hz and that the bandwidth of gamma

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Fig. 2. A. Electrodes entry points projected upon a 3D reconstruction of the MNI brain. Each dot corresponds to a 1D array penetrating the brain orthogonally to the sagittal plane. B. Anatomical location of electrodes showing a gamma band increase during pursuit, superimposed on statistical parametric maps (SPMs) showing the voxels with a significant activation during pursuit (random effect analysis, FDR, p b 0.05, data from n = 17 control subjects (Lebranchu et al., 2010), projected onto flattened left and right hemispheres (population-averaged landmark and surface-based (PALS) atlas)).

band response was 82.8 ± 22.7 Hz. This confirms that high frequency responses were broadband in all patients. A higher gamma band power increase was observed during reactive pursuit in 25 out of 772 analyzed electrode pairs (reactive pursuit > fixation, Table 1). Pursuit execution elicited a gamma band power increase in 22 out of these 25 contact-pairs (RP > PI), distributed in frontal eye field (FEF, P7, 2 contact-pairs), ventral intraparietal sulcus (VIPS, P8, 2 contact-pairs), middle occipital gyrus (MOG, P8,

Fig. 3. General pattern of time-frequency amplitude modulations averaged across trials during pursuit (left spectrograms) and saccades (right spectrograms) in three representative contact-pairs. Patient 7 (FEF) and Patient 8 data are separated horizontally for clarity purpose. Zero ms indicates target onset in both experimental conditions.

8 contact-pairs) and cuneus (CUN, P7, 10 contact-pairs, see Table 1). We found that FEF and CUN gamma band responses co-localized well with pursuit areas identified using functional magnetic resonance imaging in control subjects (Fig. 2B). VIPS and MOG contact-pairs were found outside the activated voxels if corrected for multiple comparisons, but using uncorrected p values thresholded at p b 0.01, all electrodes co-localized with pursuit-activated voxels. Thus, the 23 sites that we consider in the next section come from two patients (FEF recordings from patient 7; VIPS, CUN and MOG recordings from patient 8). In these brain areas, we observed a significantly stronger gamma band activity during RP than SA and PI (corrected p b 0.05, Fig. 3). This definition rules out the possibility that the responses reflect solely processes such as saccades, target motion perception or attention, also active in the SA or PI conditions. Gamma band responses were characterized by an initial peak followed by a sustained activity lasting throughout the pursuit process (Fig. 4). The onset of the gamma band response during RP differed across brain regions: it preceded target onset only in the FEF (− 323 ± 26 ms) and VIPS (− 173 ± 15 ms) whereas gamma response onset followed target onset in the MOG (137 ± 84 ms) and CUN (283 ± 35 ms). Thus, FEF and VIPS were the only areas where gamma activity increased before target onset, consistent with a role in pursuit initiation/ preparation. This early activity followed the auditory pre-cue and was not different between RP and PI. The difference between the two conditions only occurred later at the time of motor execution (Table 1). The relatively late gamma onset in MOG and CUN, is incompatible with a role in pursuit initiation. This means that the extra-retinal information extracted by these occipital regions became only available to the pursuit system during the course of the pursuit and may correspond to a re-afferent signal. The sustained component of the gamma band response in FEF, VIPS, CUN and MOG was coincident with the sustained oculomotor behavior characteristic of pursuit maintenance. That sustained component enabled us to dissociate within the FEF between pursuit (m13–12 and m14–13) and saccade (r13–12 and r14–13) FEF subregions (One patient: P7; Fig. 5A, Table 1). Hence, in the saccade FEF, a transient gamma increase was observed during RP and SA whereas in the pursuit FEF a sustained component followed the transient response. Furthermore, in one pursuit FEF site, gamma power was higher during contraversive than during ipsiversive pursuit (Fig. 5B), that is, gamma response was significantly higherwhen the target first moved to the left compared to early rightward movement (in the 200–500 ms post stimulus onset) and accordingly, during return movement to the left gamma activity was higher from 950 to 1100 ms (compared to return movement to the right). In a majority of the four sites, the sustained gamma component was also higher during RP than during PP when participants could predict target motion (Fig. 6; saccade FEF, P7, VIPS, P8, MOG, P8, CUN, P8; the converse was never observed). However, when oculomotor behavior was driven by prediction alone, during catch trials (CA), a transient increase was also observed, mainly in FEF. The increase was always of lower amplitude than in the RP condition and was followed by a return to baseline between 400 and 600 ms (Fig. 6; 630 ± 57 ms in all four FEF contact-pairs observed in one patient; P7; 600 ms in one out of three VIPS site and 420 ms in one out of eight MOG site, observed in one patient; P8). Pursuit inhibition elicited a gamma band power increase in 1.8% of analyzed contact-pairs (14 out of 772 analyzed bipoles across patients). Hence, gamma band power was higher in several prefrontal regions when participants had to inhibit pursuit (PI) than during RP or SA (Fig. 7; dorso-lateral-prefrontal, DLPFC, n = 3 patients, 5 contact-pairs; pre-supplementary-motor-area, pre-SMA, n=3 patients, 3 contact-pairs; frontopolar cortex, Fp, n=3 patients, 4 contact-pairs). This pattern was also observed in a (saccade) FEF and a VIPS bipole (Table 1).


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Table 1 Anatomical locations of each bipolar contact-pair showing a significant gamma band response during the tasks. For all contact-pairs that displayed a significant response during reactive pursuit as compared to fixation, the onset of gamma band response is indicated. Furthermore, a second test was applied to test whether reactive pursuit and pursuit inhibition conditions significantly differed, so that we also indicate onset and offset of statistical significance for this contrast. Electrode name (contact-pairs)

Reactive pursuit > fixation (RP > FIX) s′3–s′2 s′4–s′3 o′2–o′1 o′3–o′2 o′4–o′3 l′2–l′1 l′3–l′2 l′4–l′3 l′5–l′4 l′6–l′5 s′9–s′8 s′10–s′9 s′11–s′10 s′12–s′11 o′8–o′7 o′9–o′8 o′10–o′9 o′11–o′10 w′6–w′5 w′7–w′6 w′8–w′7 m13–m12 m14–m13 r13–r12 r14–r13

Talairach coordinates

Pat.

Anatomical

Gamma band results

Structure

Onset

Contrast

Onset

Offset

Contrast

320 270 350 300 280 300 270 250 240 250 170 130 140 50 324 105 80 100 −160 −170 −190 −350 −290 −400 −250

RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX RP > FIX

600 400 460 340 156 400 300 270 270 200 800 550 600 ns 320 420 510 220 450 500 150 420 880 370 ns

1200 1400 950 1280 1750 1300 1550 1500 1550 1550 950 750 950 ns 1360 1075 1050 1120 730 650 280 1390 940 550 ns

RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI ns RP > PI RP > PI RP > PI RP > PI RP > PI RP > PI PI > RP RP > PI RP > PI PI > RP ns

200 200 250 240 0 450 60 50 150 550 500 150

500 700 600 650 375 700 580 1300 700 800 1000 300

PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA PI > RP/SA

x

y

z

−9.6 −13 −6.5 −10 −14 −7.5 −11 −15 −18 −22 −31 −34 −38 −42 −29 −32 −36 −40 −19 −23 −26 47 51 48 52

−86 −86 −81 −81 −81 −68 −68 −68 −68 −68 −86 −86 −86 −86 −81 −81 −81 −81 −74 −74 −74 −2 −2 3 3

20 20 10 10 10 16 16 16 16 16 20 20 20 20 10 10 10 10 36 36 36 55 55 44 44

P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P8 P7 P7 P7 P7

CUN CUN CUN CUN CUN CUN CUN CUN CUN CUN MOG MOG MOG MOG MOG MOG MOG MOG VIPS VIPS VIPS FEF FEF FEF FEF

52 54 46 13 25 25 37 36 9.2 11 19 7.2

P5 P2 P6 P1 P1 P2 P2 P7 P2 P3 P3 P6

PRE-SMA PRE-SMA PRE-SMA DLPFC DLPFC DLPFC DLPFC DLPFC FP FP FP FP

Pursuit inhibition > eye movement tasks (RP and SA) m5–m4 17 k2–k1 6.4 mp2–mp1 −7.6 yp8–yp7 −35 ep12–ep11 −44 j13–j12 43 f11–f10 39 f10–f9 35 g′10–g′9 −33 l8–l7 35 f9–f8 37 k′8–k′7 −36

9.8 13 9.7 32 47 27 34 25 37 43 39 48

Discussion

Study limitations

The main result of the present study is that direct recordings of the neural activity in the pursuit network, as quantified by gamma band activity, reveals clear functional dissociations between four regions: FEF, VIPS, MOG and CUN. These areas co-localize with areas activated during pursuit in previous neuroimaging studies (Berman et al., 1999; Burke and Barnes, 2008; Ding et al., 2009; Lencer et al., 2004; Nagel et al., 2008; O'Driscoll et al., 2000; Petit and Haxby, 1999; Rosano et al., 2002; Tanabe et al., 2002). Furthermore, the high temporal precision of iEEG reveals that the pattern of activity leads to functional dissociations between the pursuit areas. We show that FEF and VIPS mainly support initiation, maintenance and prediction processes, consistent with previous electrophysiological studies in monkeys (Burke and Barnes, 2008; Fukushima et al., 2002b; Ilg and Thier, 2008; Lencer and Trillenberg, 2008; Tanaka and Lisberger, 2001), and MOG and CUN are specifically active during pursuit maintenance, perhaps to encode an extraretinal target speed signal (Lebranchu et al., 2010). In addition, pursuit inhibition mostly activated regions within the prefrontal cortex. This is coherent with previous reports showing that movement inhibition is implemented in a subcortical–prefrontal loop (Aron et al., 2007; Burke and Barnes, 2011; Isoda and Hikosaka, 2007; Swann et al., 2009). Before discussing the specific contribution of each of those regions during pursuit, possible limitations of the current study should be considered.

The main limitation of this study is the limited coverage of the brain provided by invasive recordings. However, we showed that electrode contact-pairs co-localized well with some areas that are involved during pursuit, as identified in a previous fMRI study (Lebranchu et al., 2010): gamma-band amplitude modulations during pursuit execution were selectively found only in FEF, VIPS, CUN and MOG. Gamma band responses that were selective to pursuit execution could only be reported in two out of eight patients, one patient had electrodes implanted within FEF (P7) and the other in occipital and VIPS regions (P8). Hence, in this study, inter-individual reproducibility of gamma band results could not be examined and further intracerebral explorations will be necessary to reproduce these results in a larger patient population. Finally, we think that our data cannot reflect eye muscle artefacts because intracerebral recordings have shown to be predominantly immune to such artefacts (excepting depth electrodes located close to the extra-ocular eye muscles, see (Jerbi et al., 2009a)) and because we used a bipolar montage to further minimize this possibility. Frontal eye field Our data provide the first electrophysiological support for the existence of two separate regions within the human FEF, one devoted

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Fig. 4. Time course of gamma activity during reactive pursuits, pursuit inhibition and saccades in FEF, VIPS, MOG and CUN. Left panels illustrate anatomical location (electrode entry point and horizontal MRI slice) on individual patient's anatomy. Right panels show the time course of gamma band percentage of power change as a function of experimental conditions. 0 ms indicates the onset of visual target. Shaded areas represent ±1.96 SEM. Vertical black dotted line indicate onset and offset of audio and visual cues and gray vertical dotted line indicates onset of audio pre-cue. Stars indicate significance. RP = reactive pursuit; PI = pursuit inhibition; SA = saccade.

to saccade control, and the other to pursuit, extending previous fMRI studies (Petit et al., 1997; Rosano et al., 2002). In the same patient, we observed two distinct response patterns in FEF sites. In the pursuit FEF, gamma band activity was higher during RP than during PI, indicative of a role in pursuit maintenance, whereas the saccade FEF was characterized by a transient gamma activity that is consistent with the pattern of gamma activity observed in the two previous FEF direct recordings (Lachaux et al., 2006; Nagasawa et al., 2011). Gamma power was higher during reactive compared to predictive pursuits in saccade FEF, perhaps because during RP, more saccades occurred in this study. The early phase of the FEF response, which anticipates the onset of the target motion, might correspond to the preparation and initiation of the pursuit eye movement. A strikingly similar activity (an increase of firing rate) was observed in the FEF during fixation in monkeys waiting for a target with predictable onset (Fukushima, 2003; Ilg and Thier, 2008). Therefore, the early FEF activity reported in the present study could correspond to a target expectation signal. Alternatively, it might also correspond to a response to the auditory pre-cue, as this region is known to respond to auditory stimuli (Kirchner et al., 2009). However, FEF auditory responses are sharp

and transient (Kirchner et al., 2009), in contrast with the gradual increase of gamma power that we report here. In addition, the FEF might mediate a prediction mechanism to supplement visually-driven initiation of eye movements by the target motion. Indeed, during catch trials, when eye movements occur in the absence of any visual stimulation, neural activity increase transiently in the FEF at movement onset, in line with previous studies showing that FEF is involved in predictive processes underlying pursuit control (Drew and van Donkelaar, 2007; Fukushima et al., 2002a, 2008; Gagnon et al., 2006; Ilg and Thier, 2008; Lencer et al., 2004; Nagel et al., 2006). Finally, we found a clear instance of FEF site more active during pursuit movements towards the controlateral side. This result is consistent with previous stimulation studies in humans (Blanke and Seeck, 2003; Milea et al., 2002) but it contradicts observations reported in monkeys (Gottlieb et al., 1993; Heide et al., 1996). VIPS and occipital areas The anatomical location of VIPS is close (6 mm anterior) to a motion sensitive region of the posterior parietal cortex (Orban et al.,


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Fig. 6. Time course of gamma activity during reactive pursuits, predictive pursuits and catch trials in FEF, VIPS and MOG. Shaded areas represent ±1.96 SEM. Vertical black dotted line indicate onset and offset of audio and visual cues and gray vertical dotted line indicates onset of audio pre-cue. Stars indicate significance. RP = reactive pursuit; PP = predictive pursuit; CA = catch trial.

Fig. 5. Time course of gamma activity in FEF subregions. (A) Time course of gamma band percentage of power change in pursuit (m13) and saccade (r14) FEF as a function of experimental conditions. (B) Time course of gamma activity in the FEF during pursuits separated in pursuits during which target was initially moving toward the left (controlateral) or toward the right (ipsilateral). Shaded areas represent ±1.96 SEM. Vertical black dotted line indicate onset and offset of audio and visual cues, gray vertical dotted line indicates onset of audio pre-cue and blue vertical dotted line indicates target reversal. Stars indicate significance. RP = reactive pursuit; PI = pursuit inhibition; SA = saccade; TIML = target initially moving leftward; TIMR = target initially moving rightward; TR = target movement reversal.

2006). In this study, we found that VIPS respond to pursuit initiation, maintenance and prediction: the pattern of gamma response was highly similar to FEF activity, with both an early onset before target motion and a sustained component specific to pursuit maintenance. The similarity between FEF and VIPS responses suggest a similar functional role during pursuits, in the initiation, maintenance and predictive processes. VIPS site anatomical location, together with the functional similarity with FEF suggests that this site might correspond to the parietal eye field (Petit et al., 1997). The late onsets of neural activity in MOG and CUN that followed target motion onset, are consistent with a previous report and confirm that occipital activity propagate from lateral to medial occipital sites during pursuit (Nagasawa et al., 2011).

The pattern of neural activity in MOG and CUN is compatible with a role of these areas during pursuit maintenance. A possibility is that those regions could extract an extraretinal target speed signal (Lebranchu et al., 2010), as suggested by the greater gamma activity during RP as compared to PI. This signal could be used by the pursuit system as a re-afferent signal to correct pursuit. Pursuit inhibition modulates prefrontal gamma band amplitude Pursuit inhibition selectively increased gamma activity in the Pre-SMA, DLPFC and frontopolar cortex, extending recent fMRI results obtained during NOGO pursuit trials (Burke and Barnes, 2011). Saccade inhibition strongly activates pre-SMA neurons (Isoda and Hikosaka, 2007), and pre-SMA is specifically involved in successful stopping of a prepared motor response (Sharp et al., 2010). DLPFC is involved in the inhibition of reflexive saccades (Pierrot-Deseilligny et al., 2003) and was recently shown to be selectively involved during pursuit inhibition (Burke and Barnes, 2011). FP activity may correspond to cognitive processes related to successful pursuit inhibition in this task that tap on working memory, higher-order decision making and conflict processing during PI (Koechlin and Hyafil, 2007). In conclusion, we have, for the first time, described the time course of neural activity in four areas of the human pursuit system, thereby specifying the role of these different components. Frontal and parietal eye fields contribute to pursuit initiation, maintenance and prediction, whereas occipital areas (MOG and CUN) are primary

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Fig. 7. Time course of gamma activity during pursuit inhibition, reactive pursuits and catch trials in DLPFC, pre-SMA and FP. Shaded areas represent ±1.96 SEM. Vertical black dotted line indicate onset and offset of audio and visual cues and gray vertical dotted line indicates onset of audio pre-cue. Stars indicate significance. PI = pursuit inhibition; SA = saccade.

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