Experimental Task (Pursuit Trials)

Clinical data:

The two patients(P1, male, 40 years; P2, female, 19 years) were suffering from drug-resistant focal seizures that have started at the age of 15 and 16 years, respectively.Both participants were right-handed, with normal or corrected-to-normal vision.MRI showed a dysembryoplastic tumor in the right anterior cingulate cortex in P1, and bilateral posterior periventricular heterotopias in P2. Based on non-invasive data, sEEG recordings were judged necessary in both cases, on the basis of which the epileptogenic zone proved to be mesial frontal in P1, and involved part of the left posterior heterotopia in P2. After a post-operative follow-up of 2 years, P1 has remained seizure-free, while seizures recurred after 1 year in P2.Patients gave their informed consent before to start experimental procedures, that were approved by the Local Ethical Committee (CPP Sud-Est V no. 09-CHUG-12).At the time of sEEG recordings, P1 was treated with carbamazepine (400 mg/day), and P2 bylevetiracetam (2000 mg/day) and phenobarbital (80 mg/day).Note that the studied contacts (FEF in P1, left precuneus in P2) were outside the epileptogenic brain tissue.

Experimental task (pursuit trials):

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.

The pursuit paradigm (fig e-1) was adapted from the remembered pursuit task (e1). 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. 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 was randomly adjustedin the 800–1200 ms range so that the onset of target displacement was not predictable. The time course of a typical pursuit trial is illustrated in fig e-1. A pursuit trial began by a black screen displayed during 2500 ms that signaled the onset of a new trial (i.e., the interstimulus interval, ISI). 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 (e1). 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). Here, all analyses focus on reactive and Predictive Pursuits (RP and PP) trialsto clarify the role of referential framework in human pursuit coding system. Thus, 318 pursuit trials were analyzed for patient 1 and 368 pursuit trials were analyzed for patient 2.

Electrophysiological analyses:

EEG signals were evaluated with the software package for electrophysiological analysis (ELAN-Pack) developed in the INSERM U280 laboratory and Matlab algorithms. For each single trial, bipolar derivations were computed between adjacent electrode 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 (the intra-contact distance was 1.5 mm).

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., time-varying 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 one 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 account for a bias toward the lower frequencies of the interval that would otherwise occur due to the 1/f drop-off in amplitude.

The onset of gamma power increase relative to fixation was determined as the first time point at which gamma power was above the average power during fixation +1.96 SEM.

Statistical analysis:

Comparisons between experimental conditions were performed separately for each recording site.

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 (e2).

We calculated for each pursuit significant contact (FEF for P1, Cuneusfor P2) the statistical significance of direction-specific signals was estimated by comparing HFA for the appropriate conditions for each 15.625 ms time bin in the [−500 to 1500 ms] time interval, using single-trial responses at each time bin as observations. Thus, one unpaired t-test was performed to contrast HFA during left vs. right craniotopic pursuits across trials, and this procedure was applied every 15.6 ms to determine the time dynamics of the effects. This means that we performed 129 unpaired t-test in the time interval of interest to examine the dynamics if these signals. Therefore, the resulting P-values were corrected for multiple comparisons in the time domain with the FDR algorithm to take into account the 129 tests performed across time. An identical statistical approach was successfully employed previously to quantify the dynamics of HFA during various cognitive protocols (e3-e8). Two statistical control analyses were performed to assess the robustness of the reported effects. In a first control analysis, we ran a bootstrap randomization process (resampling test) that was applied 1000 times by shuffling HFA across trial typesand we repeated this procedure at each time point in the -500 - 1500 ms time interval. The resampling method allowed us to compute a surrogate distribution of t-values in the time interval of interest. If the t value computed from HFA of the original data-set fell outside the 95% confidence interval of the permuted set, HFA was considered to be significantly modulated. The advantage of the bootstrapping approach in that it does not requires any assumption about data distribution and the randomization process effectively control for possible bias inherent to the correlation structure inherent to time-series data. In a second control analysis, we restricted the statistical analysis to two large time windows (the first 750 ms and the last 750 ms, corresponding to the moment at which the target reversal occured, see e-method). Thus, instead of performing 129 unpaired t-test to examine the precise HFA dynamics during pursuit, we conducted a repeated measure analysis of variance with factors pursuit (leftward vs. rightward) and time (first 750 ms vs. last 750 ms), thus avoiding multiple statistical comparisons in the time-domain. Both statistical control analyses revealed identical results and confirmed that HFA was higher in the FEF when the movement of the eye went leftward compared to rightward whatever its hemifield of realization wheread left cuneus revealed a greater activity when the movement was done in the left hemifield compared to the right hemifield, whatever the direction of the eye (all p values<0.05).

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Figure e-1:

Legend: 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 1, 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. ISI, inter-stimulus interval; FIX, fixation; PI, pursuit inhibition; RP, reactive pursuit; PP, predictive pursuits; CA, catch trial.

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