Electrocorticogram Electrodes Research Articles

Soft, conformal PDMS-based ECoG electrode array for long-term in vivo applications

Electrocorticogram (ECoG) electrode arrays based on soft materials, such as polydimethylsiloxane (PDMS), are preferable because they can be implanted with better conformal contact and have physical properties close to biological tissues; thus, the adverse effects on tissues are minimal. However, the realization of electrodes in the micrometer scale on PDMS is challenging. Previously, parylene-treated PDMS was suggested as a solution and proven to be successful in acute in vivo applications. In this study, PDMS-based ECoG electrode arrays fabricated using parylene-treated PDMS (parylene-deposited PDMS and parylene-filled PDMS) are evaluated for the first time in terms of stability and reliability for long-term use. The mechanical and electrochemical properties are investigated over time for up to 8 months through accelerated aging. The ECoG electrode array, implanted in the primary somatosensory area of the brain, can successfully record somatosensory evoked potentials (SEPs) upon mechanical stimulus of the paws with sufficient spatial resolution to distinguish between forepaw and hindpaw stimulations. Finally, the PDMS-based electrodes demonstrate the feasibility of chronic recording for up to 3 months in non-human primates. Based on theses results, it is concluded that they can be used as promising materials and methods to develop various bio-integrated electronic devices that require softness, flexibility, conformability, and robustness over long-term.

NIMG-63. GAMMA-BAND MODULATIONS OF ELECTROCORTICOGRAM (ECOG) INDUCED BY COGNITIVE-LINGUISTIC TASKS DURING AWAKE CRANIOTOMY FOR FEASIBLE FUNCTIONAL LANGUAGE MAPPING

Abstract INTRODUCTION Intraoperative functional language mapping has uncertainty in predicting language function and post-surgical outcomes. We study the feasibility of functional mapping using electrocorticogram (ECoG) gamma-band modulations induced by linguistic tasks having different complexity levels. METHODS Five subjects with left temporal lobe glioma underwent resection involving awake language mapping using a 4x8 ECoG electrode grid. A MATLAB/Simulink based real-time software system was used to map task-induced gamma-band modulations as 2D heat maps. Tasks included verbally responding to single word/tone categorization; object, action, written descriptive and auditory naming respectively. Auditory stimuli were provided during word/tone categorization (duration 300~500ms) and auditory naming tasks ( > 1s). Other tasks provided visual stimuli (line drawings or written phrases). Bipolar DCS (2~6 mA, 60Hz, 2s) was applied at different electrode pairs while repeating the naming tasks. RESULTS Cortical regions activated by word stimuli and the auditory naming task were similar; superior, middle temporal gyri (STG, MTG). Visual naming tasks modulated posterior MTG (pMTG) and STG (written naming). Reproducible speech arrests occurred during different naming tasks while stimulating specific electrode pairs, even though not all electrodes had strong task-specific activations. Considerable inter-personal variability of language areas identified with DCS was observed, despite the similarity of task-specific gamma-band modulated regions across subjects. Post-operative decline in language score was observed in one subject, with resection boundary covering gamma modulated regions during auditory processing tasks but no DCS identified region. CONCLUSION Intraoperative language mapping guided by gamma-band ECoG modulations induced by simple word/tone categorization task exhibited similar patterns to more complex naming tasks, suggesting this task may be a viable approach to localize functional cortex, especially in patients unable to reliably perform more difficult paradigms. Utilizing this method in conjunction with DCS mapping guided by visual naming tasks, eloquent cortical language areas may be better preserved reducing post-operative language deficits.

NIMG-64. INTRAOPERATIVE LANGUAGE MAPPING USING GAMMA-BAND MODULATIONS OF ELECTROCORTICOGRAM (ECOG) INDUCED BY WORD/SOUND CATEGORIZATION TASK: VALIDATION WITH REPRODUCIBLE SPEECH ARRESTS DURING LINGUISTIC TASKS

Abstract OBJECTIVE Determination of the correlation between gamma-band modulations of electrocorticogram (ECoG) induced by linguistic tasks and reproducible speech arrests caused by bipolar direct cortical stimulations (DCS). METHODS 3 subjects (age 39, 56, 64 years) with left temporal lobe glioma underwent surgery involving awake craniotomy. A 4x8 ECoG electrode grid (2.3mm contact exposure, 1cm contact spacing) was placed above the respective tumor area. A MATLAB-Simulink based real-time software system running on a portable laptop computer was used to map gamma-band modulations as a 2D heat map while the subjects engaged in different linguistic tasks: word/sound categorization by pressing a button, object naming, action naming, written descriptive naming, and auditory descriptive naming. Auditory stimulus was applied during word/sound categorization task (duration 300 – 500ms), auditory descriptive naming ( > 1s); other tasks involved visual stimulus only. The subjects repeated the four naming tasks while bipolar DCS (2/4/6 mA, 60Hz, 2s) was applied at different electrode pairs. RESULTS The electrodes having stronger gamma-band modulations were distinct for different tasks. Reproducible speech arrests occurred during object, action, auditory naming tasks while stimulating specific electrode pairs, even though not all these electrodes had strong activations during these tasks. Across all subjects these electrodes had strong activations consistently during word/sound categorization tasks, starting as early as 250ms and lasting even after the auditory stimuli were terminated (~ 650ms). The longer activations can be associated with word recognition process. The subjects self-reported about having difficulty in comprehension rather than speech production during speech arrests. 3D brain rendering using MRI images showed that the speech arrest electrodes were identically located on the superior temporal gyrus, inferior to central sulcus for all 3 subjects. CONCLUSION Intraoperative language mapping guided by gamma-band ECoG modulations induced by word/sound categorization tasks can be utilized to localize eloquent cortex associated with auditory processing.

An electrocorticographic decoder for arm movement for brain–machine interface using an echo state network and Gaussian readout

Brain–machine interface (BMI) studies typically use an electrocorticogram (ECoG) to record neural signals from the surface of the cortex because of the high spatial and temporal resolution and high signal-to-noise levels of the data obtained. However, in certain medical conditions, it may not be possible to place the ECoG electrodes at the target brain regions for BMI. Consequently, developing an ECoG decoder with suitable feature extraction and selection processes is challenging. This study investigated the possibility of a novel ECoG decoder for arm movement BMI. The ECoG signals were recorded from four individuals with intractable epilepsy while imaging and performing a reach-and-grasp movement. We examined the performance of the ECoG decoder using an echo state network and 24 Gaussian readouts within the classification problem paradigm of the arm movement directions. A genetic algorithm was used to optimize the hyperparameters of the ECoG decoder. The ECoG decoder successfully classified 24 arm movement directions in the x–y, x–z, and y–z planes in execution and imagination tasks. The best hit rates were 90.9 ± 5.3 %, 92.6 ± 3.9, and 92.6 ± 4.2 for the x–y, x–z, and y–z planes, respectively. A robot arm control simulation indicated that a real-time movement BMI system could use the novel ECoG decoder. Thus, the echo state network with Gaussian readouts for classification can be a successful ECoG decoder model for motor BMIs.

The dopamine D2 agonist quinpirole impairs frontal mismatch responses to sound frequency deviations in freely moving rats.

AimA reduced mismatch negativity (MMN) response is a promising electrophysiological endophenotype of schizophrenia that reflects neurocognitive impairment. Dopamine dysfunction is associated with symptoms of schizophrenia. However, whether the dopamine system is involved in MMN impairment remains controversial. In this study, we investigated the effects of the dopamine D2‐like receptor agonist quinpirole on mismatch responses to sound frequency changes in an animal model.MethodsEvent‐related potentials were recorded from electrocorticogram electrodes placed on the auditory and frontal cortices of freely moving rats using a frequency oddball paradigm consisting of ascending and equiprobable (ie, many standards) control sequences before and after the subcutaneous administration of quinpirole. To detect mismatch responses, difference waveforms were obtained by subtracting nondeviant control waveforms from deviant waveforms.ResultsHere, we show the significant effects of quinpirole on frontal mismatch responses to sound frequency deviations in rats. Quinpirole delayed the frontal N18 and P30 mismatch responses and reduced the frontal N55 MMN‐like response, which resulted from the reduction in the N55 amplitude to deviant stimuli. Importantly, the magnitude of the N55 amplitude was negatively correlated with the time of the P30 latency in the difference waveforms. In contrast, quinpirole administration did not clearly affect the temporal mismatch responses recorded from the auditory cortex.ConclusionThese results suggest that the disruption of dopamine D2‐like receptor signaling by quinpirole reduces frontal MMN to sound frequency deviations and that delays in early mismatch responses are involved in this MMN impairment.

Comparison of tuning properties of gamma and high-gamma power in local field potential (LFP) versus electrocorticogram (ECoG) in visual cortex

Electrocorticogram (ECoG), obtained from macroelectrodes placed on the cortex, is typically used in drug-resistant epilepsy patients, and is increasingly being used to study cognition in humans. These studies often use power in gamma (30–70 Hz) or high-gamma (>80 Hz) ranges to make inferences about neural processing. However, while the stimulus tuning properties of gamma/high-gamma power have been well characterized in local field potential (LFP; obtained from microelectrodes), analogous characterization has not been done for ECoG. Using a hybrid array containing both micro and ECoG electrodes implanted in the primary visual cortex of two female macaques (for some stimulus conditions, separate ECoG and microelectrode arrays in two additional male macaques were also used), we compared the stimulus tuning preferences of gamma/high-gamma power in LFP versus ECoG in up to four monkeys, and found them to be surprisingly similar. High-gamma power, thought to index the average firing rate around the electrode, was highest for the smallest stimulus (0.3° radius), and decreased with increasing size in both LFP and ECoG, suggesting local origins of both signals. Further, gamma oscillations were similarly tuned in LFP and ECoG to stimulus orientation, contrast and spatial frequency. This tuning was significantly weaker in electroencephalogram (EEG), suggesting that ECoG is more like LFP than EEG. Overall, our results validate the use of ECoG in clinical and basic cognitive research.

Electrocorticogram (ECoG) Is Highly Informative in Primate Visual Cortex.

Neural signals recorded at different scales contain information about environment and behavior and have been used to control Brain Machine Interfaces with varying degrees of success. However, a direct comparison of their efficacy has not been possible due to different recording setups, tasks, species, etc. To address this, we implanted customized arrays having both microelectrodes and electrocorticogram (ECoG) electrodes in the primary visual cortex of 2 female macaque monkeys, and also recorded electroencephalogram (EEG), while they viewed a variety of naturalistic images and parametric gratings. Surprisingly, ECoG had higher information and decodability than all other signals. Combining a few ECoG electrodes allowed more accurate decoding than combining a much larger number of microelectrodes. Control analyses showed that higher decoding accuracy of ECoG compared with local field potential was not because of differences in low-level visual features captured by them but instead because of larger spatial summation of the ECoG. Information was high in the 30-80 Hz range and at lower frequencies. Information in different frequencies and scales was nonredundant. These results have strong implications for Brain Machine Interface applications and for study of population representation of visual stimuli.SIGNIFICANCE STATEMENT Electrophysiological signals captured across scales by different recording electrodes are regularly used for Brain Machine Interfaces, but the information content varies due to electrode size and location. A systematic comparison of their efficiency for Brain Machine Interfaces is important but technically challenging. Here, we recorded simultaneous signals across four scales: spikes, local field potential, electrocorticogram (ECoG), and EEG, and compared their information and decoding accuracy for a large variety of naturalistic stimuli. We found that ECoGs were highly informative and outperformed other signals in information content and decoding accuracy.

Somatosensation Evoked by Cortical Surface Stimulation of the Human Primary Somatosensory Cortex.

Electrical stimulation of the primary somatosensory cortex using intracranial electrodes is crucial for the evocation of artificial somatosensations, typically tactile sensations associated with specific regions of the body, in brain-machine interface (BMI) applications. The qualitative characteristics of these artificially evoked somatosensations has been well documented. As of yet, however, the quantitative aspects of these evoked somatosensations, that is to say the quantitative relationship between intensity of electrical stimulation and perceived intensity of the resultant somatosensation remains obscure. This study aimed to explore this quantitative relationship by surface electrical stimulation of the primary somatosensory cortex in two human participants undergoing electrocorticographic monitoring prior to surgical treatment of intractable epilepsy. Electrocorticogram electrodes on the primary somatosensory cortical surface were stimulated with varying current intensities, and a visual analogue scale was employed to provide a quantitative measure of intensity of the evoked sensations. Evoked sensations included those of the thumb, tongue, and hand. A clear linear relationship between current intensity and perceived intensity of sensation was observed. These findings provide novel insight into the quantitative nature of primary somatosensory cortex electrical stimulation-evoked sensation for development of somatosensory neuroprosthetics for clinical use.

Transformation of 2D Planes into 3D Soft and Flexible Structures with Embedded Electrical Functionality

Three-dimensional (3D) structures composed of flexible and soft materials have been in demand for implantable biomedical devices. However, the fabrication of 3D structures using microelectromechanical system (MEMS) techniques has limitations in terms of the materials and the scale of the structures. Here, a technique to selectively bond polydimethylsiloxane (PDMS) and parylene-C by plasma treatment is reported, with which two-dimensional structures that are fabricated using MEMS techniques are turned into 3D structures by the inflation of selectively non-bonded patterns. The bonding strength and the bonding mechanism were analyzed by mechanical tests and chemical analyses, respectively. We fabricated soft and flexible 3D structures with various patterns and dimensions, even with embedded electrical functions, including light emitting diodes and electrocorticogram electrodes. Based on these results, the flexible, soft, and MEMS-capable 3D structures that are obtained by the developed selective bonding technique are promising for applications in a wide range of biomedical applications.

Cortical Electrocorticogram (ECoG) Is a Local Signal.

Electrocorticogram (ECoG), obtained by low-pass filtering the brain signal recorded from a macroelectrode placed on the cortex, is extensively used to find the seizure focus in drug-resistant epilepsy and is of growing importance in cognitive and brain-machine-interfacing studies. To accurately estimate the epileptogenic cortex or to make inferences about cognitive processes, it is important to determine the "spatial spread" of ECoG (i.e., the extent of cortical tissue that contributes to its activity). However, the ECoG spread is currently unknown; even the spread of local field potential (LFP) obtained from microelectrodes is debated, with estimates ranging from a few hundred micrometers to several millimeters. Spatial spread can be estimated by measuring the receptive field (RF) and multiplying by the cortical magnification factor, but this method overestimates the spread because RF size gets inflated due to several factors. This issue can be partially addressed using a model that compares the RFs of two measures, such as LFP and multi-unit activity (MUA). To use this approach for ECoG, we designed a customized array containing both microelectrodes and ECoG electrodes to simultaneously map MUA, LFP, and ECoG RFs from the primary visual cortex of awake monkeys (three female Macaca radiata). The spatial spread of ECoG was surprisingly local (diameter ∼3 mm), only 3 times that of the LFP. Similar results were obtained using a model to simulate ECoG as a sum of LFPs of varying electrode sizes. Our results further validate the use of ECoG in clinical and basic cognitive research.SIGNIFICANCE STATEMENT Brains signals capture different attributes of the neural network depending on the size and location of the recording electrode. Electrocorticogram (ECoG), obtained by placing macroelectrodes (typically 2-3 mm diameter) on the exposed surface of the cortex, is widely used by neurosurgeons to identify the source of seizures in drug-resistant epileptic patients. The brain area responsible for seizures is subsequently surgically removed. Accurate estimation of the epileptogenic cortex and its removal requires the estimation of spatial spread of ECoG. Here, we estimated the spatial spread of ECoG in five behaving monkeys using two different approaches. Our results suggest that ECoG is a local signal (diameter of ∼3 mm), which can provide a useful tool for clinical, cognitive neuroscience, and brain-machine-interfacing applications.

High Spatiotemporal Resolution ECoG Recording of Somatosensory Evoked Potentials with Flexible Micro-Electrode Arrays.

Electrocorticogram (ECoG) has great potential as a source signal, especially for clinical BMI. Until recently, ECoG electrodes were commonly used for identifying epileptogenic foci in clinical situations, and such electrodes were low-density and large. Increasing the number and density of recording channels could enable the collection of richer motor/sensory information, and may enhance the precision of decoding and increase opportunities for controlling external devices. Several reports have aimed to increase the number and density of channels. However, few studies have discussed the actual validity of high-density ECoG arrays. In this study, we developed novel high-density flexible ECoG arrays and conducted decoding analyses with monkey somatosensory evoked potentials (SEPs). Using MEMS technology, we made 96-channel Parylene electrode arrays with an inter-electrode distance of 700 μm and recording site area of 350 μm2. The arrays were mainly placed onto the finger representation area in the somatosensory cortex of the macaque, and partially inserted into the central sulcus. With electrical finger stimulation, we successfully recorded and visualized finger SEPs with a high spatiotemporal resolution. We conducted offline analyses in which the stimulated fingers and intensity were predicted from recorded SEPs using a support vector machine. We obtained the following results: (1) Very high accuracy (~98%) was achieved with just a short segment of data (~15 ms from stimulus onset). (2) High accuracy (~96%) was achieved even when only a single channel was used. This result indicated placement optimality for decoding. (3) Higher channel counts generally improved prediction accuracy, but the efficacy was small for predictions with feature vectors that included time-series information. These results suggest that ECoG signals with high spatiotemporal resolution could enable greater decoding precision or external device control.

Comparison of decoding resolution of standard and high-density electrocorticogram electrodes

Objective. Electrocorticography (ECoG)-based brain–computer interface (BCI) is a promising platform for controlling arm prostheses. To restore functional independence, a BCI must be able to control arm prostheses along at least six degrees-of-freedoms (DOFs). Prior studies suggest that standard ECoG grids may be insufficient to decode multi-DOF arm movements. This study compared the ability of standard and high-density (HD) ECoG grids to decode the presence/absence of six elementary arm movements and the type of movement performed. Approach. Three subjects implanted with standard grids (4 mm diameter, 10 mm spacing) and three with HD grids (2 mm diameter, 4 mm spacing) had ECoG signals recorded while performing the following movements: (1) pincer grasp/release, (2) wrist flexion/extension, (3) pronation/supination, (4) elbow flexion/extension, (5) shoulder internal/external rotation, and (6) shoulder forward flexion/extension. Data from the primary motor cortex were used to train a state decoder to detect the presence/absence of movement, and a six-class decoder to distinguish between these movements. Main results. The average performances of the state decoders trained on HD ECoG data were superior (p = 3.05 × 10−5) to those of their standard grid counterparts across all combinations of the μ, β, low-γ, and high-γ frequency bands. The average best decoding error for HD grids was 2.6%, compared to 8.5% of standard grids (chance 50%). The movement decoders trained on HD ECoG data were superior (p = 3.05 × 10−5) to those based on standard ECoG across all band combinations. The average best decoding errors of 11.9% and 33.1% were obtained for HD and standard grids, respectively (chance error 83.3%). These improvements can be attributed to higher electrode density and signal quality of HD grids. Significance. Commonly used ECoG grids are inadequate for multi-DOF BCI arm prostheses. The performance gains by HD grids may eventually lead to independence-restoring BCI arm prosthesis.

Atenolol offers better protection than clonidine against cardiac injury in kainic acid-induced status epilepticus.

Status epilepticus is increasingly associated with cardiac injury in both clinical and animal studies. The current study examined ECG activity for up to 48 h following kainic acid (KA) seizure induction and compared the potential of atenolol and clonidine to attenuate this cardiac pathology. Sprague-Dawley rats (male, 300-350 g) were implanted with ECG and electrocorticogram electrodes to allow simultaneous telemetric recordings of cardiac and cortical responses during and after KA-induced seizures. Animals were randomized into saline controls, and saline vehicle-, clonidine- or atenolol-pretreated KA groups. KA administration in the saline-pretreated group produced an immediate bradycardic response (maximal decrease of 28 ± 6%), coinciding with low-level seizure activity. As high-level seizure behaviours and EEG spiking increased, tachycardia also developed, with a maximum heart rate increase of 38 ± 7% coinciding with QTc prolongation and T wave elevation. Both clonidine and atenolol pretreatment attenuated seizure activity and reduced KA-induced changes in heart rate, QTc interval and T wave amplitude observed during both bradycardic and tachycardic phases in saline-pretreated KA animals. Clonidine, however, failed to reduce the power of EEG frequencies. Atenolol and to a lesser extent clonidine attenuated the cardiac hypercontraction band necrosis, inflammatory infiltration, and oedema at 48 h after KA, relative to the saline-KA group. Severe seizure activity in this model was clearly associated with altered ECG activity and cardiac pathology. We suggest that modulation of sympathetic activity by atenolol provides a promising cardioprotective approach in status epilepticus.

Local spatial correlation analysis of hand flexion/extension using intraoperative high-density ECoG.

We recorded motor cortical activity using highdensity electrocorticogram (ECoG) from three patients during awake craniotomy. Subjects repeatedly executed hand flexion/extension tasks according to auditory instructions. Clear event-related desynchronization (ERD) in beta band (8-32) Hz and event-related synchronization (ERS) in gamma band (60-200) Hz were observed. High frequency band (HFB: 60-200 Hz) activation was found to be more localized compared to low frequency band (LFB: 8-32 Hz) activation in all subjects. Local spatial correlation maps in LFB and HFB were constructed by computing the correlation between channels. Local spatial correlation dropped more in the ERD/ERS areas consistently in two subjects. The results indicate that ERD/ERS patterns are more spatially uncorrelated and denser ECoG electrode is necessary within these areas to map uncorrelated `sources'. High resolution electrodes might improve both clinical functional mapping and brain machine interface outcomes in the near future.

Adaptive shut-down of EEG activity predicts critical acidemia in the near-term ovine fetus.

In fetal sheep, the electrocorticogram (ECOG) recorded directly from the cortex during repetitive heart rate (FHR) decelerations induced by umbilical cord occlusions (UCO) predictably correlates with worsening hypoxic-acidemia. In human fetal monitoring during labor, the equivalent electroencephalogram (EEG) can be recorded noninvasively from the scalp. We tested the hypothesis that combined fetal EEG – FHR monitoring allows for early detection of worsening hypoxic-acidemia similar to that shown for ECOG-FHR monitoring. Near-term fetal sheep (n = 9) were chronically instrumented with arterial and venous catheters, ECG, ECOG, and EEG electrodes and umbilical cord occluder, followed by 4 days of recovery. Repetitive UCOs of 1 min duration and increasing strength (with regard to the degree of reduction in umbilical blood flow) were induced each 2.5 min until pH dropped to <7.00. Repetitive UCOs led to marked acidosis (arterial pH 7.35 ± 0.01 to 7.00 ± 0.03). At pH of 7.22 ± 0.03 (range 7.32–7.07), and 45 ± 9 min (range 1 h 33 min–20 min) prior to attaining pH < 7.00, both ECOG and EEG amplitudes began to decrease ∼fourfold during each FHR deceleration in a synchronized manner. Confirming our hypothesis, these findings support fetal EEG as a useful adjunct to FHR monitoring during human labor for early detection of incipient fetal acidemia.

Morphological and electrochemical properties of an explanted PtIr electrode array after 15 months in vivo.

We investigated the morphological and electrochemical properties of an explanted laser-machined 32 channel electrocorticogram (ECoG) electrode array made of platinum-iridium and silicone rubber. It was connected to a wireless brain-computer interface (BCI) and implanted in a sheep for more than 15 months. Recordings and stimulations of cortical activity were conducted over the whole period on a regularly basis. Currently, this is the longest in vivo study for this type of ECoG electrode array. Results were compared with an unused electrode array of same dimensions, material and production method. Visual inspections revealed no significant material alterations, despite organic residuals which could be easily removed though. Electrochemical impedance measurements also attested proper long-term stability of magnitude and phase, the difference between explanted electrode contacts and those of the unused array were found negligible.

Reconstruction of intracortical whisker-evoked local field potential from electrocorticogram using a model trained for spontaneous activity in the rat barrel cortex

Electrocorticogram (ECoG) has provided neural information from the cortical surfaces, is widely used in clinical applications, and expected to be useful for brain–machine interfaces. Recent studies have defined the relationship between neural activity in deep layers of the cerebral cortex and ECoG. However, it is still unclear whether this relationship is shared across different brain states. In this study, spontaneous activity and whisker-evoked responses in the barrel cortex of anesthetized rats were recorded with a 32-channel ECoG electrode array and 32-channel linear silicon probe electrodes, respectively. Spontaneous local field potentials (LFPs) at various depths could be reconstructed with high accuracy (R>0.9) by a linear weighted summation of spontaneous ECoG. Current source density analysis revealed that the reconstructed LFPs correctly represented laminar profiles of current sinks and sources as well as the raw LFP. Moreover, when we applied the spontaneous activity model to reconstruction of LFP from the whisker-related ECoG, high accuracy of reconstruction could be obtained (R>0.9). Our results suggest that the ECoG carried rich information about synaptic currents in the deep layers of the cortex, and the same reconstruction model can be applied to estimate both spontaneous activity and whisker-evoked responses.

All-or-none activity as a correlate of object awareness in monkey visual cortex

Recurring activity in visual areas has been argued to have an essential role in object aware recognition. However, this has been hard to prove, mainly due to the difficulty in dissociating low-level feature extraction from the actual object recognition activity. Here we used an innovative technique called Semantic Wavelet-Induced Frequency-Tagging (SWIFT), where cyclic wavelet-scrambling allowed us to isolate neural correlates of the semantic extraction from low-level features processing of the image. Electrocorticogram electrodes placed intracranially over ventral visual areas from V2 to TEO allowed us to record neural activity with both high temporal and spatial resolution. One macaque monkey was trained to perform an animal/non-animal categorization task. In each trial a SWIFT sequence containing either a target (an animal) or a distractor (a landscape, object or meaningless texture) was presented. The monkey reported the presence or absence of a target by a go or no-go manual response respectively. In each session, one third of the trials corresponded to new images, making the task quite challenging (about 65% correct responses on targets). Event-related potential (ERP) analysis of local sources revealed two ERP components in ventral visual areas. A first positive (P1) component, representing the feed-forward sweep, peaked around 100 ms; while a second positive (P2) component, likely representing recurring reactivation, appeared from 200 ms after the semantic onset. The P1 component was present either the target was recognized or not and its amplitude was modulated by stimulus category (low amplitude for meaningless texture distractors, medium amplitude for object distractors and high amplitude for animal targets). On the other hand, the P2 component was only present when the target was recognized or when a distractor elicited a false alarm, but totally absent otherwise, either when the target was not recognized or when a distractor was correctly rejected, thus being modulated in an all-or-none fashion by image recognition as a target of the task. Importantly, this P2 modulation was observed when comparing the same images before and after being recognized as a target, demonstrating that the P2 component is a specific feature related to aware image recognition.

Influence of a Silastic ECoG Grid on EEG/ECoG Based Source Analysis

The simultaneous evaluation of the local electrocorticogram (ECoG) and the more broadly distributed electroencephalogram (EEG) from humans undergoing evaluation for epilepsy surgery has been shown to further the understanding of how pathologies give rise to spontaneous seizures. However, a well-known problem is that the disruption of the conducting properties of the brain coverings can render simultaneous scalp and intracranial recordings unrepresentative of the habitual EEG. The ECoG electrodes for measuring the potential on the surface of the cortex are commonly embedded into one or more sheets of a silastic material. These highly resistive silastic sheets influence the volume conduction and might therefore also influence the scalp EEG and ECoG measurements. We carried out a computer simulation study to examine how the scalp EEG and the ECoG, as well as the source reconstruction therefrom, employing equivalent current dipole estimation methods, are affected by the insulating ECoG grids. The finite element method with high quality tetrahedral meshes, generated using a constrained Delaunay tetrahedralization meshing approach, was used to model the volume conductor that incorporates the very thin ECoG sheets. It is shown that the insulating silastic substrate of the ECoG grids can have a large impact on the scalp potential and on source reconstruction from scalp EEG data measured in the presence of the grids. The reconstruction errors are characterized with regard to the location of the source in the brain and the mislocalization tendency. In addition, we found a non-negligible influence of the insulating grids on ECoG based source analysis. We conclude, that the thin insulating ECoG sheets should be taken into account, when performing source analysis of simultaneously measured ECoG and scalp EEG data.

Intrauterine Cerebral Processing of External Vibroacoustic Stimuli

The human and the sheep fetus, the animal model of human pregnancy, respond to external stimuli such as vibrations or noises with behavior state changes from 0.8 gestation onwards. It is not clear yet 1) if the behavior state changes that represent a „subcortical“ arousal are accompanied by a „cortical“ arousal as a condition of conscious perception of the stimuli; 2) to what extent the perception of the stimuli depends on the behavior state and the quality of the stimulus; and 3) if the proprioceptive system is important for perception of the vibratory component of the signal. Via Cesarean section, sheep fetuses were chronically instrumented at 0.8 gestation with ECoG (electrocorticogram) electrodes as well as EOG, EMG and EKG electrodes to define fetal behavior states. After a recovery period of five days, stimuli were presented from the abdominal wall of the ewe during periods of NREM and REM sleep. We tested pure vibratory (30min) and acoustic (5h) stimuli as well as dynamic amplitude and frequency modulated and two static vibroacoustic stimuli (VAS) produced by an electronic artificial larynx (EAL) and a laboratory shaker. ECoG changes were analyzed using linear (power spectral analysis) and non-linear methods. For non-linear analysis we used an algorithm based on the Wolf algorithm (calculation of the leading Lyapunov exponent) which calculates a point prediction error (PE) regarding the course of the time series in the phase space. The vibratory and acoustic stimuli did not induce a cortical arousal. The VAS produced an arousal with similar effectiveness during NREM and REM sleep. The dynamic stimulus induced 100%, the EAL 70% and the laboratory shaker 40–50% responses. The PE showed a high predictability in NREM and a low predictability of the ECoG in REM sleep. Although the power spectrum differed between VAS in NREM (decrease of delta activity) and REM sleep (beta activation), the PE showed that the cortical activation pattern did not depend on the sleep state and the stimulus. Processes of cortical activation and deactivation during spontaneous sleep state changes and VAS were similar in their time courses. Cochlear ablation prevented from arousal, suggesting that stimuli were detected through the auditory rather than the proprioceptive system. The results show that external VAS induce a cortical arousal during the last trimester depending on the stimulus. The time course of cortical activation within 32s suggests an arousal via the ascending activating reticular system rather than via specific fiber systems.