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Periventricular nodular heterotopias (PVNH) are areas of neurons abnormally located in the white matter that might be involved in physiological cortical functions. Autoscopic hallucinations are changes in self-consciousness determined by a mismatch in integration of multiple sensory inputs. Our goal is to highlight the brain network involved in generation of autoscopic hallucination elicited by electrical stimulation of a PVNH in a drug resistant epilepsy patient. Our patient was explored using stereo-electroencephalography with electrodes covering the right posterior temporal PVNH and the adjacent cortex. Direct electrical high frequency stimulation of the PVNH elicited autoscopic hallucinations mainly involving the face and upper trunk. We then used multiple modalities to determine brain connectivity: single pulse electrical stimulation of the PVNH and stimulation-evoked potentials were used to highlight resting state effective connectivity. High-frequency stimulation using alternating polarity pulses enabled us to identify the network involved, time-locked to the clinical effect and to map symptom-related effective connectivity. Functional connectivity using a non-linear regression method was used to determine dependencies between different cortical regions following the stimulation. Finally, structural connectivity was highlighted using deterministic fiber tracking. Multi-modal connectivity analysis identified a network involving the PVNH, occipital and temporal neocortex, fusiform gyrus and parietal cortex.

OBJECTIVE: Sleep is an active process with an important role in memory. Epilepsy patients often display a disturbed sleep architecture, with consequences on cognition. We aimed to investigate the effect of sleep on cortical networks' organization.METHODS: We analyzed cortico-cortical evoked responses elicited by single pulse electrical stimulation (SPES) using intracranial depth electrodes in 25 patients with drug-resistant focal epilepsy explored using stereo-EEG. We applied the SPES protocol during wakefulness and NREM - N2 sleep. We analyzed 31,710 significant responses elicited by 799 stimulations covering most brain structures, epileptogenic or non-epileptogenic. We analyzed effective connectivity between structures using a graph-theory approach.RESULTS: Sleep increases excitability in the brain, regardless of epileptogenicity. Local and distant connections are differently modulated by sleep, depending on the tissue epileptogenicity. In non-epileptogenic areas, frontal lobe connectivity is enhanced during sleep. There is increased connectivity between the hippocampus and temporal neocortex, while perisylvian structures are disconnected from the temporal lobe. In epileptogenic areas, we found a clear interhemispheric difference, with decreased connectivity in the right hemisphere during sleep.CONCLUSIONS: Sleep modulates brain excitability and reconfigures functional brain networks, depending on tissue epileptogenicity.SIGNIFICANCE: We found specific patterns of information flow during sleep in physiologic and pathologic structures, with possible implications for cognition.

The operculum, defined as the cortex adjacent to the insula, is a large structure encompassing three lobes, with a recognized role in a variety of neurologic and psychiatric conditions. Its complex functions include sensory, motor, autonomic and cognitive processing. In humans, these are extended with the addition of language. These functions are implemented by highly specialized neuronal populations and their widespread connections, which our study aims at mapping in detail. We studied a group of 31 patients that were explored with intracranial electrodes during the pre-surgical workup for drug-resistant epilepsy. We have selected the subset of contacts implanted in non-epileptogenic opercular cortex and we analyzed the neurophysiological and behavioral responses to direct electrical stimulation. The functional mapping was performed by applying 1 Hz and 50 Hz electrical stimulation on 252 contact pairs and recording the threshold for evoking clinical effects. The effective connectivity was assessed using cortico-cortical evoked potentials elicited by single-pulse electrical stimulation in a subset of 19 patients. The locations of the effects grouped in twelve distinct semiological classes were analyzed. The most frequent effects evoked by stimulation of the frontal operculum were language related (29%). The Rolandic area produced most often oropharyngeal symptoms (47%), the parietal operculum produced somatosensory effects (67%), while the temporal evoked auditory (58%) semiology. The connectivity pattern was complex, with these structures having widespread ipsilateral and contralateral projections. The local connections between the opercular subregions and with the insula, as well as with more distant areas like the cingulate gyrus, were distinguished by strength and between-subjects consistency. In conclusion, we demonstrate specific opercular functionality, distinct from the one of the insular cortex. The study is complemented by a literature review on the opercular functional connectome in human and non-human primates.

Objective To perform a side-by-side comparison of two epileptogenicity biomarkers, high frequency oscillations (HFOs) and delayed responses (DRs), as a result of single-pulse electrical stimulation. Methods We have recorded stimulation-evoked HFOs and DRs in 16 epileptic patients undergoing presurgical evaluation using the stereoelectroencephalographic method. To evaluate converging and complementary information provided by the biomarkers, we analyzed them individually and for logical “and”/“or” combinations between them. 3D maps of the biomarkers’ distributions by recording location (inbound maps) and by stimulation location (outbound maps) were created to analyze their relationship with the epileptogenic structures. Results HFOs occur less frequently than DRs, by 18.7%, when counting by recording contacts, and more frequently, by 7.4%, when counting by stimulation contacts. 40.6% of the contacts exhibiting HFOs also exhibit DRs, and 44.1% of the contacts exhibiting DRs also exhibit HFOs. When combining biomarkers, there was a tradeoff between increased seizure onset zone (SOZ) sensitivity, from 21.3% to 73%, and decreased specificity, from 87.2% to 34.3%. Conclusions There is a moderate similarity in the information provided by the DRs and HFOs. Significance The biomarkers complement each other, but there is a tradeoff between different metrics for SOZ localization.

OBJECTIVE: To investigate functional coupling between brain networks using spectral changes induced by single-pulse electric stimulation (SPES).METHOD: We analyzed 20 patients with focal epilepsy, implanted with depth electrodes. SPES was applied to each pair of adjacent contacts, and responses were recorded from all other contacts. The mean response amplitude value was quantified in three time-periods after stimulation (10-60, 60-255, 255-500ms) for three frequency-ranges (Gamma, Ripples, Fast-Ripples), and compared to baseline. A total of 30,755 responses were analyzed, taking into consideration three dichotomous pairs: stimulating in primary sensory areas (S1-V1) vs. outside them, to test the interaction in physiologic networks; stimulating in seizure onset zone (SOZ) vs. non-SOZ, to test pathologic interactions; recording in default mode network (DMN) vs. non-DMN.RESULTS: Overall, we observed an early excitation (10-60ms) and a delayed inhibition (60-500ms). More specifically, in the delayed period, stimulation in S1-V1 produced a higher gamma-inhibition in the DMN, while stimulation in the SOZ induced a higher inhibition in the epilepsy-related higher frequencies (Ripples and Fast-Ripples).CONCLUSION: Physiologic and pathologic interactions can be assessed using spectral changes induced by SPES.SIGNIFICANCE: This is a promising method for connectivity studies in patients with drug-resistant focal epilepsy.

The cingulate cortex is part of the limbic system. Its function and connectivity are organized in a rostro-caudal and ventral-dorsal manner which was addressed by various other studies using rather coarse cortical parcellations. In this study, we aim at describing its function and connectivity using invasive recordings from patients explored for focal drug-resistant epilepsy. We included patients that underwent stereo-electroencephalographic recordings using intracranial electrodes in the University Emergency Hospital Bucharest between 2012 and 2019. We reviewed all high frequency stimulations (50 ​Hz) performed for functional mapping of the cingulate cortex. We used two methods to characterize brain connectivity. Effective connectivity was inferred based on the analysis of cortico-cortical potentials (CCEPs) evoked by single pulse electrical stimulation (SPES) (15 ​s inter-pulse interval). Functional connectivity was estimated using the non-linear regression method applied to 60 ​s spontaneous electrical brain signal intervals. The effective (stimulation-evoked) and functional (non-evoked) connectivity analyses highlight brain networks in a different way. While non-evoked connectivity evidences areas having related activity, often in close proximity to each other, evoked connectivity highlights spatially extended networks. To highlight in a comprehensive way the cingulate cortex’s network, we have performed a bi-modal connectivity analysis that combines the resting-state broadband h2 non-linear correlation with cortico-cortical evoked potentials. We co-registered the patient’s anatomy with the fsaverage FreeSurfer template to perform the automatic labeling based on HCP-MMP parcellation. At a group level, connectivity was estimated by averaging responses over stimulated/recorded or recorded sites in each pair of parcels. Finally, for multiple regions that evoked a clinical response during high frequency stimulation, we combined the connectivity of individual pairs using maximum intensity projection. Connectivity was assessed by applying SPES on 2094 contact pairs and recording CCEPs on 3580 contacts out of 8582 contacts of 660 electrodes implanted in 47 patients. Clinical responses elicited by high frequency stimulations in 107 sites (pairs of contacts) located in the cingulate cortex were divided in 10 groups: affective, motor behavior, motor elementary, versive, speech, vestibular, autonomic, somatosensory, visual and changes in body perception. Anterior cingulate cortex was shown to be connected to the mesial temporal, orbitofrontal and prefrontal cortex. In the middle cingulate cortex, we located affective, motor behavior in the anterior region, and elementary motor and somatosensory in the posterior part. This region is connected to the prefrontal, premotor and primary motor network. Finally, the posterior cingulate was shown to be connected with the visual areas, mesial and lateral parietal and temporal cortex.

High-frequency oscillations >80 Hz (HFOs) have unique features distinguishing them from spikes and artifactual components that can be well-evidenced in the time-frequency representations. We introduce an unsupervised HFO detector that uses computer-vision algorithms to detect HFO landmarks on two-dimensional (2D) time-frequency maps. To validate the detector, we introduce an analytical model of the HFO based on a sinewave having a Gaussian envelope, for which analytical equations in time-frequency space can be derived, allowing us to establish a direct correspondence between common HFO detection criteria in the time domain with the ones in the frequency domain, used by the computer-vision detection algorithm. The detector identifies potential HFO events on the time-frequency representation, which are classified as true HFOs if criteria regarding the HFO's frequency, amplitude, and duration are met. The detector is validated on simulated HFOs according to the analytical model, in the presence of noise, with different signal-to-noise ratios (SNRs) ranging from −9 to 0 dB. The detector's sensitivity was 0.64 at an SNR of −9 dB, 0.98 at −6 dB, and >0.99 at −3 dB and 0 dB, while its positive prediction value was >0.95, regardless of the SNR. Using the same simulation dataset, our detector is benchmarked against four previously published HFO detectors. The F-measure, a combined metric that takes into account both sensitivity and positive prediction value, was used to compare detection algorithms. Our detector surpassed the other detectors at −6, −3, and 0 dB and had the second best F-score at −9 dB SNR after the MNI detector (0.77 vs. 0.83). The ability to detect HFOs in clinical recordings has been tested on a set of 36 intracranial electroencephalogram (EEG) channels in six patients, with 89% of the detections being validated by two independent reviewers. The results demonstrate that the unsupervised detection of HFOs based on their 2D features in time-frequency maps is feasible and has a performance comparable or better than the most used HFO detectors.

Background Initial subthalamic nucleus (STN) localization is based on MRI and an anatomical atlas and then refined intraoperatively using electrophysiological mapping with microelectrode recordings (IOA – intraoperative multi-unit activity) during deep brain stimulation (DBS) in Parkinson's disease (PD). IOA is time consuming and subjective. The purpose of this study was to assess the value of high frequency multi-unit background activity (MUA, frequency > 500 Hz), and local field potentials (LFP, frequency 5–500 Hz) in detection of the STN borders. Methods This was a retrospective, single center study. 18 leads in ten PD patients that underwent STN DBS surgery were evaluated. IOA, MUA and LFP have been compared in detection of the STN. IOA using single train spikes analysis have been used as a gold standard. Results Both LFP in beta range (20–35 Hz) and MUA increased as the microelectrode entered the STN and their increase correlated with dorsal/ventral STN borders. The differences (mean ± sd) were: between IOA and MUA of the dorsal/ventral border 0.20 ± 0.76/0.28 ± 0.30 mm; between IOA and LFP of the dorsal/ventral border 0.08 ± 0.94/0.05 ± 0.53 mm. Using Bland–Altman statistics, only 2 / 36 (5.6%) differences between IOA and MUA and also 2 / 36 differences between IOA and LFP (one for the dorsal border and one for the ventral border) were out of ± 1.96 SD line of measurement differences. Correlation between dorsal border/ventral border positions obtained by IOA and MUA was 0.86, p Conclusions Both MUA and LFP are characteristically elevated in the STN compared to neighboring structures. They may provide fast, real-time, objective and reliable markers of STN borders.

In the context of the human brain, the term "connectivity" can refer to structural, functional or effective connectivity. Intracranial electrical stimulation is perhaps the most direct way of investigating the effective connectivity. We propose a method of mapping the effective connectivity, revealed by the electrical stimulation of brain structures, over the structural connectome (SC), obtained through diffusion spectrum imaging (DSI), to form a structural-effective connectome (SEC). A number of 24 patients with refractory epilepsy were implanted with depth electrodes for pre-surgical evaluation. Effective connectivity was assessed by analyzing the responses to single pulse electrical stimulation (SPES). Stimulation pulses having variable amplitude were applied to each pair of adjacent contacts and responses evoked by stimulation were recorded from other contacts located in other brain areas. Early responses (10-110 ms) on the stimulation-activated contacts located outside the epileptogenic zone were averaged for each patient, resulting in a patient-level physiological effective connectome (EC). The population level EC is computed by averaging the connections of the individual ECs, on a structure by structure basis. A fiber activation factor is used to weight the number of fibers connecting a pair of structures in the SC by its corresponding normalized EC value. The resulting number of effectively activated fibers describes the directional connection strength between two structures in the SEC. A physiological SEC comprising directional connections between 70 segmented brain areas in both hemispheres, was obtained by inclusion of structures outside the epileptogenic zone only. Over the entire structure set, the Spearman's correlation coefficient ρ between the number of fibers extracted from the DSI Atlas and the normalized RMS responses to SPES was ρ=0.21 (p0.001), while Kendall's tau coefficients ranged -0.52-0.44 (p0.05). The physiological structural-effective connectomics approach we have introduced can be applied for the creation of a whole-brain connectivity atlas that can be used as a reference tool for differential analysis of altered versus normal brain connectivity in epileptic patients.

Highlights • New method for stimulation artifact removal from cortico-cortical evoked potentials. • The method is based on electrical modeling of tissue-electrode interface. • It allows disambiguation of time-locked physiological responses and artifacts. • Method validation is based on synthetic and experimental data., Background Effective connectivity can be explored using direct electrical stimulations in patients suffering from drug-resistant focal epilepsies and investigated with intracranial electrodes. Responses to brief electrical pulses mimic the physiological propagation of signals and manifest as cortico-cortical evoked potentials (CCEP). The first CCEP component is believed to reflect direct connectivity with the stimulated region but the stimulation artifact, a sharp deflection occurring during a few milliseconds, frequently contaminates it. New method In order to recover the characteristics of early CCEP responses, we developed an artifact correction method based on electrical modeling of the electrode–tissue interface. The biophysically motivated artifact templates are then regressed out of the recorded data as in any classical template-matching removal artifact methods. Results Our approach is able to make the distinction between the physiological responses time-locked to the stimulation pulses and the non-physiological component. We tested the correction on simulated CCEP data in order to quantify its efficiency for different stimulation and recording parameters. We demonstrated the efficiency of the new correction method on simulations of single trial recordings for early responses contaminated with the stimulation artifact. The results highlight the importance of sampling frequency for an accurate analysis of CCEP. We then applied the approach to experimental data. Comparison with existing method The model-based template removal was compared to a correction based on the subtraction of the averaged artifact. Conclusions This new correction method of stimulation artifact will enable investigators to better analyze early CCEP components and infer direct effective connectivity in future CCEP studies.

International audience; Objective: Technology for localizing epileptogenic brain regions plays a central role in surgical planning. Recent improvements in acquisition and electrode technology have revealed that high-frequency oscillations (HFOs) within the 80-500 Hz frequency range provide the neurophysiologist with new information about the extent of the epileptogenic tissue in addition to ictal and interictal lower frequency events. Nevertheless, two decades after their discovery there remain questions about HFOs as biomarkers of epileptogenic brain and there use in clinical practice.Methods: In this review, we provide practical, technical guidance for epileptologists and clinical researchers on recording, evaluation, and interpretation of ripples, fast ripples, and very high-frequency oscillations.Results: We emphasize the importance of low noise recording to minimize artifacts. HFO analysis, either visual or with automatic detection methods, of high fidelity recordings can still be challenging because of various artifacts including muscle, movement, and filtering. Magnetoencephalography and intracranial electroencephalography (iEEG) recordings are subject to the same artifacts.Significance: High-frequency oscillations are promising new biomarkers in epilepsy. This review provides interested researchers and clinicians with a review of current state of the art of recording and identification and potential challenges to clinical translation.

The human brain is an amazingly complex structure whose functionality, including high-order cognitive functions, is determined by intricate connectivity patterns between tens of billions of neurons (Azevedo et al. 2009). The signaling between neurons is deceivingly simple, using binary-like electrical impulses, such that the multitude of brain functions, that are often performed concurrently, are the result of connectivity patterns across various spatial scales (Bullock et al. 1977; Budd and Kisvarday 2012), that implement a mixed sequential, parallel or hierarchical architecture. The brain regulates breathing and heart rate, collects and processes sensory information, and controls all the voluntary and involuntary movements and actions. While some of these functions are performed by well-defined areas of the brain (i.e. visual stimuli are processed solely by the primary visual cortex), some higher level functions (i.e. speech production, problem solving, music performance) can only be accomplished by various brain areas working together in a serial or, more likely, in a parallel or distributed design (Sigman and Dehaene 2008).

Pre surgical evaluation in drug resistant epilepsy is based also on invasive EEG recordings in order to accurately establish the epileptogenic zone for surgical resection as well as the eloquent cortex that should be spared. During intracranial session we record ictal events and we apply different stimulation protocols to study functional cortex. In our centre we use the stereo-EEG method to identify the epileptogenic networks and mainly high frequency (50 Hz) stimulation for cortical mapping. By modulating the properties of the stimulation waveforms, in conjunction with the nonlinear response of the tissue to electrical stimulation, we were able to recover the physiological responses during the course of the stimulation train. The activation of the networks at stimulation levels evoking a clinical symptom was compared with the below-threshold stimulation, that did not elicit any clinical effects, allowing to evidence a selective recruitment of pathways associated with a particular symptom. The method is used for identification of physiologic networks associated with various somatosensory, motor or language-related symptoms, to investigate the impact of epileptogenic zone to functional cortex as well as to predict a possible post surgical deficit.

Cortical direct electrical stimulation (DES) is a method of brain mapping used during invasive presurgical evaluation of patients with intractable epilepsy. Intellectual auras like intrusive thoughts, also known as forced thinking (FT), have been reported during frontal seizures. However, there are few reports on FT obtained during DES in frontal cortex. We report three cases in which we obtained intrusive thoughts while stimulating the dorsolateral prefrontal cortex and the white matter in the prefrontal region. In order to highlight the effective connectivity that might explain this clinical response, we have analyzed cortico-cortical potentials evoked by single pulse electrical stimulation.

Object Insight may be gained into the physiological mechanisms of deep brain stimulation (DBS) by analyzing local and contralateral subthalamic nucleus (STN) single-unit activity during activation of previously placed DBS electrodes. Special techniques are required to perform such analysis due to the presence of a large stimulus artifact. The purpose of this study was to determine the effects of DBS stimulation on single unit activity acquired from patients undergoing new or revised DBS placements. Methods Subthalamic nucleus single unit activity was acquired from awake patients during activation of a previously implanted STN DBS electrode. Stimulation was contralateral to the recording site in 4 cases and ipsilateral in 3. Data were acquired at stimulation frequencies of 30, 60, and 130 Hz and with other stimulation parameters at clinically effective settings. Cells were included if they showed kinesthetic activity before and after the stimulation paradigm and if their action potential morphology was maintained throughout the experiment. Analysis of single-unit activity acquired before, during, and after stimulation was performed employing a time-domain algorithm to overcome the stimulus artifact. Results Both ipsilateral and contralateral acute stimulation resulted in reversible STN firing rate suppression. The degree of suppression became greater as stimulus frequency increased and was significant at 60 Hz (t-test, p < 0.05) and 130 Hz (p < 0.01). Suppression with ipsilateral 130-Hz stimulation ranged between 52.8% and 99.8%, whereas with similar contralateral STN stimulation, the range was lower (1.9%–50.3%). Return to baseline activity levels typically occurred within seconds after stimulation ended. Conclusions Stimulation of the STN at clinically effective frequencies has an acute suppressive rather than an excitatory effect on STN single-unit activity. The effect is bilateral, even though the degree of suppression is greater on the ipsilateral than the contralateral STN. The authors' algorithm helps reveal this effect in human patients.

Objectives By analyzing the responses to intracranial electrical stimulation we aim at im-proving the localization of the seizure onset zone (SOZ) and the connectivity between different areas. Methods Our center uses a set of traditional and innovative advanced analysis methods for stereo-EEG signals recorded using depth electrodes. We analyze stimulation-evoked activity in time-frequency domain to detect inter-ictal epileptogenicity biomarkers like high-frequency oscillations (HFO, f > 80 Hz) and delayed responses (DR, t > 100 ms). Results of the different quantitative EEG analyses are represented as 3-D maps superimposed with patient’s anatomy, as visible on various imaging modalities, and their evolution in time is shown as movies. Cortico-cortical evoked potentials (CCEP) based on early responses (t = 10–110 ms) to single-pulse intracranial stimulation are used to calculate functional connectivity between cortical areas. Results Biomarker response maps and effective connectomes were calculated in a population of 24 patients undergoing presurgical evaluation for drug-resistant epilepsy. The sensitivity with respect to SOZ of HFOs was higher than the one of the DR by both response and stimulation location, whereas the specificity of the DRs was higher by the lo-cation of the stimulation. Discussion Despite variable sensitivity and specificity of the biomarkers, the positive pre-diction level of these biomarkers is less than 30%, taken separately or in combination. Conclusions Analysis of responses to intracranial electrical stimulation can contribute to the identification of the epileptogenic networks and for delineating the epileptogenic are-as. Significance We illustrate the value of using multiple advanced signal analysis techniques.

Objective We aim to study the connections of the posterior insula (pI) and anterior insula (aI) through cortico-cortical evoked potentials (CCEP) by single pulse electrical stimulation (SPES). Method We performed SPES stimulation protocol in a group of 8 refractory epilepsy patients presurgically explored with intracerebral depth electrodes, out of which 6 were operated on and are currently seizure-free. We selected the early responses (ER) obtained from contacts of 24 electrodes that were included in the anterior and posterior insula, when this structure was outside the seizure onset zone (SOZ). Responses were analyzed in terms of amplitude variations during wakefulness and sleep. Effective connectivity betweeen cortical was calculated based on the measured CCEPs. Results The ER amplitudes by SPES stimulation in the insula during wakefulness compared to sleep showed statistically significant ( p 0.05 ) differences in 6 patients. There are constant connections between aI and pI. We identified connectivity of the pI with language-related brain stuctures during wakefulness, and with the temporal mesial structures during sleep, possibly influenced by the SOZ. Right pI stimulation seems to elicit ampler reponses in the rolandic operculum and parietal structures during wakefulness, and in the primary motor and premotor cortex during sleep. Anterior insula has preferential connectivity with anterior cingulate gyrus during wakefulness and with the fusiform gyrus during sleep. Discussions Connectivity of the aI versus pI, as well as right versus left insula during wakefulness and sleep is different, partially supporting previous observations. Conclusion Sleep has been shown to alter the physiological connectivity of the insula. Further investigations are in progress to confirm these results. Significance These findings describe insular connectivity and variability during sleep, with possible implications in epilepsy surgery, sleep disorders understanding and language studies.

Epileptic seizures are characterized by a rich dynamic spectrum consisting of excessive, abnormal and synchronized firing of neuron ensembles. Such abnormal firing has been quantitatively characterized via power laws in neural avalanches. The term “neural avalanche” has been used to illustrate the excessively amplified neural firing patterns that lead to epileptic seizures. The pattern of amplified firing in neural avalanches betrays a modular signature in the spread of activation across cortical minicolumns. According to this modular approach of epilepsy, the excessive amplification of neural firing in a cortical minicolumn results from a defect within the “inhibitory curtain” surrounding the pyramidal cells. The functional basis of this approach provides insights into potential clinical interventions.

The visual responsiveness and spatial tuning of frontal eye field (FEF) neurons were determined using a delayed memory saccade task. Neurons with visual responses were then tested for direction selectivity using moving random dot patterns centered in the visual receptive field. The preferred axis of motion showed a significant tendency to be aligned with the receptive-field location so as to favor motion toward or away from the center of gaze. Centrifugal (outward) motion was preferred over centripetal motion. Motion-sensitive neurons in FEF thus appear to have a direction bias at the population level. This bias may facilitate the detection or discrimination of expanding optic flow patterns. The direction bias is similar to that seen in visual area MT and in posterior parietal cortex, from which FEF receives afferent projections. The outward motion bias may explain asymmetries in saccades made to moving targets. A representation of optic flow in FEF might be useful for planning eye movements during navigation.

Objective To investigate default-mode network (DMN) deactivation in different types of focal epilepsy by single pulse electric stimulation (SPES). Method We analyzed 18 patients with focal epilepsy (8 frontal, 8 temporal, 2 posterior), implanted with depth electrodes. SPES was applied to each pair of adjacent contacts in seiwure onset zone (SOZ), and responses were recorded from the 10 different DMN-hubs; The responses to SPES in Gamma, Ripple (R) and Fast-Ripple (FR) bands were quantified in a 60–250 ms time-window following each stimulation pulse and compared to baseline. Time of propagation was determined based on N1 latency. These responses were compared across the three epilepsy types. Results Overall, we observed a significant deactivation of the DMN in the upper frequency ranges for all epilepsies (75% drop from baseline for gamma and 93% for R and FR). In the gamma band, the stimulation of frontal SOZs deactivated the ipsilateral posterior cingulate and precuneus significantly more than in the other epilepsy-types, with shorter general latencies of 22, 25 and 23 ms, respectively. Discussion Our results might explain why in prefrontal focal epilepsies and in generalized epilepsies, thought to have a frontal generator, the consciousness is preferentially and significantly impaired. Significance This is a promising method for quantifying the engagement of the consciousness processing areas by the epileptic focus. Detailed illustrations and tables for all 10 DMN-hubs, in all 3 high-frequency bands are provided.

Objectives We aim to map the function and connectivity of the cingulate gyrus (CG) using cortical direct electrical stimulation. Methods We selected patients explored by SEEG at the Emergency University Hospital Bucharest and at the Strasbourg University Hospital, that had minimum one electrode sampling the CG (anterior-ACG, middle-MCG or posterior-PCG), outside the epileptogenic zone. We systematically reviewed the functional stimulations (bipolar, 50 Hz, 0.25–3 mA). For 17 patients explored in Bucharest, cortico-cortical evoked potentials (CCEPs) elicited by single pulse electrical stimulations (SPES) were used to obtain the effective connectivity at a group level for each part of the CG. Results We included 429 bipolar stimulations from 108 patients. From 151 stimulations in the ACG, 24.5% elicited a clinical response like: emotions (19%), vestibular (13.5%), thoracic sensation (13.5%), smile (11%). There are 135 stimulations in the MCG of which 53.3% elicited clinical responses like: elementary motor (24.94%), proprioception (22.22%), elementary somatosensitive (13.2%), compulsive motor (2.77%). There were 143 stimulations in the PCG and only 18.88% were positive, for example: executive function (11.11%), vestibular (7.4%). CCEPs analysis revealed that ACG is connected with the prefrontal (frontobasal and frontopolar) regions, anterior insula, mesiotemporal regions. MCG is connected with the primary and supplementary motor areas, insulo-perisylvian region and parietal lobe. PCG is connected with the ACG, MCG, prefrontal, parietal and temporal regions. Discussion High frequency stimulations elicit clinical responses as a result of a network effect that we have mapped with CCEPs. Conclusions There is a regional organization of the cingulate gyrus for each part both in function and connectivity. Significance These findings help us understand the functional organization of the cingulate gyrus with possible implications in epilepsy surgery, depression or other mental disorders.

Purpose Design a protocol for probing the plastic nature of the epileptic networks. Methods We selected 3 patients with pharmaco-resistant epilepsy that were explored in the SEEG method. Single pulse electrical stimulations (SPES) (biphasic, 3 ms, 0.25–5 mA) were applied to adjacent contacts. We calculated the early responses in the 10–110 ms interval and considered only connections between contacts having a RMS value within the 3rd quartile of all the responses in an individual patient, correlated with the stimulation current (Spearman‘s rho >0.5, p Sublobar anatomical structures projecting to SOZ (inbound connections), as well as SOZ’s projections to other structures (outbound connections) were systematically assessed and named generically “epileptome”. SOZ‘s contacts were also stimulated in various relevant clinical situations (first, second patient-interictal awake vs. sleep vs. postictal, third-on medication vs. off) to understand the dynamics of the outbound analysis. Results Lack of medication or sleep activated SOZ’s network (mean increase in RMS 6%, 28% to baseline) and introduced new structures in the epileptome (hippocampus in one patient, contralateral basal temporal and precuneus in another). Post-seizure, SOZ lost some nearby connections and gained distant ones, not present interictally. Conclusions Intra-individually the epileptic focus engages in an evolving network configuration that can be accurately described.

Refinement of the subthalamic nucleus (STN) coordinates using intraoperative microelectrode recordings (MER) is routinely performed during deep brain stimulation (DBS) surgeries in Parkinson disease (PD). The commonly used criteria for electrophysiological localization of the STN are qualitative. The goal of this study was to validate quantitative STN detection algorithm (QD) derived from the multi-unit activity in a prospective setting.Ten PD patients underwent STN DBS surgery. The MUA was obtained by removing large spikes close to microelectrode using wavelet method and integrating the 500-2000Hz band in the power spectral density. The qualitative intraoperative mapping of the STN using MER (IOM) versus QD was compared using Bland-Altman and Pearson's correlation analysis.The clinical efficacy was confirmed in all subjects. The mean difference between IOM and QD of the dorsal/ventral border was 0.31±0.84/0.44±0.47mm. Using Bland-Altman statistic, only 2/36 (5.6%) differences (one for the dorsal border and one for the ventral border) were out of ±2 sd line of measurement differences. Correlation between dorsal border/ventral border positions obtained by IOM and QD was 0.79, p0.0001/0.91, p0.0001.Both methods are in reasonable agreement and are strongly correlated. The QD gives objective coordinates of the STN borders at high precision and may be more accurate than IOM. Prospective blinded comparative studies where the DBS leads will be placed using either QD or IOM are warranted.

An internal model for predictive saccades in frontal cortex was investigated by recording neurons in monkey frontal eye field (FEF) during an inferred motion task. Monkeys were trained to make saccades to the extrapolated position of a small moving target that was rendered temporarily invisible and whose trajectory was altered. On approximately two-thirds of the trials, monkeys made multiple saccades while the target was invisible. Primary saccades were correlated with extrapolated target position. Secondary saccades significantly reduced residual errors resulting from imperfect accuracy of the first saccade. These observations suggest that the second saccade was corrective. Because there was no visual feedback, corrective saccades could only be driven by an internally generated error signal. Neuronal activity in the frontal eye field was directionally tuned before both primary and secondary saccades. Separate subpopulations of cells encoded either saccade direction or direction error before the second saccade. These results suggest that FEF neurons encode the error after the first saccade, as well as the direction of the second saccade. Hence, FEF appears to contribute to detecting and correcting movement errors based on internally generated signals.

The purpose of this study was to investigate the interaction between internal representations of invisible moving targets and visual responses of neurons in frontal eye fields (FEFs). Monkeys were trained to make saccades to the extrapolated position of a target that was temporarily rendered invisible for variable durations as if it had passed behind an occluder. Flashed, task-irrelevant visual probe stimuli were used to study the visual responsiveness of FEF neurons during this task. Probes were flashed at various times and locations during the occlusion interval. Net changes in neuronal activity were obtained by comparing the activity on trials with probes with randomly interleaved trials without any probe. Most neurons showed an increase in firing rate in response to the probe, but some showed a decrease. Both types of responses were enhanced when the invisible target moved toward the receptive field (RF) as compared with trials on which the target moved away from the RF. Some neurons showed a spatial shift in the visual response during the occlusion interval. For cells that were excited by the probe, the shift tended to be correlated with the direction of motion of the target, whereas for cells that were inhibited the shift tended to be in the opposite direction. These results suggest that the role of FEF in predicting invisible target motion includes a sensory/perceptual component.

Working memory involves transient storage of information and the ability to manipulate that information for short-range planning and prediction. The computational aspect of working memory can be probed using dynamic sensorimotor behavior requiring complex stimulus-response mappings. Such a transformation occurs when extrapolating the future location of a moving target that is rendered temporarily invisible. Estimating the trajectory of an invisible moving target requires encoding and storing several target features, including the direction and speed of motion. We trained monkeys to make saccades to the estimated position of invisible targets moving at various speeds. The activity of neurons in the frontal eye field (FEF) was consistently modulated according to the speed of target motion. A reconstruction algorithm showed that estimates of target speed based on FEF activity were similar to behavioral speed estimates. FEF may therefore be involved in updating an internal representation of target trajectory for predictive saccades.

To investigate the mechanisms of fixation disengagement and saccade initiation, we electrically stimulated the macaque frontal eye fields (FEF) while monkeys performed a visual fixation task. We tested the effect of introducing a temporal gap between fixation target offset and the onset of the electrical stimulus. We found that the duration of the gap had a pronounced effect on the probability of producing electrically evoked saccades at a given current level. The highest probability was found for gaps of 200 ms duration. There were also effects of gap duration on saccade latency and amplitude for most of the stimulation sites. The increase in saccade probability may be associated with lower current thresholds for evoking saccades.

Spatially selective delay activity in the frontal eye field (FEF) is hypothesized to be part of a mechanism for the transformation of visual signals into instructions for voluntary movements. To understand the linkage between FEF activity and eye movement planning, we recorded neuronal responses of FEF neurons while monkeys performed a memory-saccade task. We then electrically stimulated the same sites during the memory-delay epoch of the task. The stimulation currents used were subthreshold for evoking saccades during a gap-fixation task. Microstimulation resulted in changes in the spatial and temporal components of saccade parameters: an increase in latency, and a shift in amplitude and direction. We performed a vector analysis to determine the relative influence of the visual cue and electrical stimulus on the memory-saccade. In general, the memory-saccade was strongly weighted toward the visual cue direction, yet the electrical stimulus introduced a consistent bias away from the receptive/movement field of the stimulation site. The effects of sub-threshold stimulation were consistent with a combination of vector subtraction and averaging, but not with vector summation. Vector subtraction may play a role in spatial updating of movement plans for memory-guided saccades when eye position changes during the memory period.