Altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex.

Orbitofrontal cortex (OFC) is classically linked to inhibitory control, emotion regulation, and reward processing. Recent perspectives propose that the OFC also generates predictions about perceptual events, actions, and their outcomes. We tested the role of the OFC in detecting violations of prediction at two levels of abstraction (i.e., hierarchical predictive processing) by studying the event-related potentials (ERPs) of patients with focal OFC lesions (n = 12) and healthy controls (n = 14) while they detected deviant sequences of tones in a local-global paradigm. The structural regularities of the tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) and at a global (i.e., between sequences) level. In OFC patients, ERPs elicited by standard tones were unaffected at both local and global levels compared to controls. However, patients showed an attenuated mismatch negativity (MMN) and P3a to local prediction violation, as well as a diminished MMN followed by a delayed P3a to the combined local and global level prediction violation. The subsequent P3b component to conditions involving violations of prediction at the level of global rules was preserved in the OFC group. Comparable effects were absent in patients with lesions restricted to the lateral PFC, which lends a degree of anatomical specificity to the altered predictive processing resulting from OFC lesion. Overall, the altered magnitudes and time courses of MMN/P3a responses after lesions to the OFC indicate that the neural correlates of detection of auditory regularity violation are impacted at two hierarchical levels of rule abstraction.

Ramping dynamics and theta oscillations reflect dissociable signatures during rule-guided human behavior.

Contextual cues and prior evidence guide human goal-directed behavior. The neurophysiological mechanisms that implement contextual priors to guide subsequent actions in the human brain remain unclear. Using intracranial electroencephalography (iEEG), we demonstrate that increasing uncertainty introduces a shift from a purely oscillatory to a mixed processing regime with an additional ramping component. Oscillatory and ramping dynamics reflect dissociable signatures, which likely differentially contribute to the encoding and transfer of different cognitive variables in a cue-guided motor task. The results support the idea that prefrontal activity encodes rules and ensuing actions in distinct coding subspaces, while theta oscillations synchronize the prefrontal-motor network, possibly to guide action execution. Collectively, our results reveal how two key features of large-scale neural population activity, namely continuous ramping dynamics and oscillatory synchrony, jointly support rule-guided human behavior.

Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods.

BACKGROUND: Intracranial electrodes are typically localized from post-implantation CT artifacts. Automatic algorithms localizing low signal-to-noise ratio artifacts and high-density electrode arrays are missing. Additionally, implantation of grids/strips introduces brain deformations, resulting in registration errors when fusing post-implantation CT and pre-implantation MR images. Brain-shift compensation methods project electrode coordinates to cortex, but either fail to produce smooth solutions or do not account for brain deformations. NEW METHODS: We first introduce GridFit, a model-based fitting approach that simultaneously localizes all electrodes' CT artifacts in grids, strips, or depth arrays. Second, we present CEPA, a brain-shift compensation algorithm combining orthogonal-based projections, spring-mesh models, and spatial regularization constraints. RESULTS: We tested GridFit on ∼6000 simulated scenarios. The localization of CT artifacts showed robust performance under difficult scenarios, such as noise, overlaps, and high-density implants (<1 mm errors). Validation with data from 20 challenging patients showed 99% accurate localization of the electrodes (3160/3192). We tested CEPA brain-shift compensation with data from 15 patients. Projections accounted for simple mechanical deformation principles with < 0.4 mm errors. The inter-electrode distances smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. COMPARISON WITH EXISTING METHODS: GridFit succeeded in difficult scenarios that challenged available methods and outperformed visual localization by preserving the inter-electrode distance. CEPA registration errors were smaller than those obtained for well-established alternatives. Additionally, modeling resting-state high-frequency activity in five patients further supported CEPA. CONCLUSION: GridFit and CEPA are versatile tools for registering intracranial electrode coordinates, providing highly accurate results even in the most challenging implantation scenarios. The methods are implemented in the iElectrodes open-source toolbox.

MGMT methylation pattern of long-term and short-term survivors of glioblastoma reveals CpGs of the enhancer region to be of high prognostic value.

Treatment with the alkylating agent temozolomide is known to be prognostically beneficial in a subset of glioblastoma patients. Response to such chemotherapeutic treatment and the prognostic benefit have been linked to the methylation status of O6-methylguanine-DNA methyltransferase (MGMT). To date, it has not been entirely resolved which methylation pattern of MGMT is most relevant to predict response to temozolomide treatment and outcome. In this retrospective study, we compared the methylation patterns, analyzed by Sanger sequencing, of 27 isocitrate dehydrogenase (IDH)-wildtype glioblastoma patients that survived more than 3 years (long-term survivors) with those of 24 patients who survived less than a year after initial surgery (short-term survivors). Random Forest-, Correlation-, and ROC-curve analyses were performed. The data showed that MGMT is typically methylated in long-term survivors, whereas no prominent methylation is observed in short-term survivors. The methylation status of CpGs, especially in the promoter and exon1/enhancer region correlated highly with outcome. In addition, age and temozolomide treatment were strongly associated with overall survival. Some CpGs in the enhancer region, in particular CpG 86 (bp + 154), demonstrated high values associated with overall survival in the Random Forest analysis. Our data confirm previously published prognostic factors in IDH-wildtype glioblastoma patients, including age and temozolomide treatment as well as the global MGMT methylation status. The area frequently used for decision making to administer temozolomide at the end of exon1 of MGMT, was associated with outcome. However, our data also suggest that the enhancer region, especially CpG 86 (bp + 154) is of strong prognostic value. Therefore, we propose further investigation of the enhancer region in a large prospective study in order to confirm our findings, which might result in an optimized prediction of survival in glioblastoma patients, likely linked to response to temozolomide treatment.

Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods.

Precise electrode localization is important for maximizing the utility of intracranial EEG data. Electrodes are typically localized from post-implantation CT artifacts, but algorithms can fail due to low signal-to-noise ratio, unrelated artifacts, or high-density electrode arrays. Minimizing these errors usually requires time-consuming visual localization and can still result in inaccurate localizations. In addition, surgical implantation of grids and strips typically introduces non-linear brain deformations, which result in anatomical registration errors when post-implantation CT images are fused with the pre-implantation MRI images. Several projection methods are currently available, but they either fail to produce smooth solutions or do not account for brain deformations. To address these shortcomings, we propose two novel algorithms for the anatomical registration of intracranial electrodes that are almost fully automatic and provide highly accurate results. We first present GridFit, an algorithm that simultaneously localizes all contacts in grids, strips, or depth arrays by fitting flexible models to the electrodes' CT artifacts. We observed localization errors of less than one millimeter (below 8% relative to the inter-electrode distance) and robust performance under the presence of noise, unrelated artifacts, and high-density implants when we ran ~6000 simulated scenarios. Furthermore, we validated the method with real data from 20 intracranial patients. As a second registration step, we introduce CEPA, a brain-shift compensation algorithm that combines orthogonal-based projections, spring-mesh models, and spatial regularization constraints. When tested with real data from 15 patients, anatomical registration errors were smaller than those obtained for well-established alternatives. Additionally, CEPA accounted simultaneously for simple mechanical deformation principles, which is not possible with other available methods. Inter-electrode distances of projected coordinates smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. Moreover, in an additional validation procedure, we found that modeling resting-state high-frequency activity (75-145 Hz ) in five patients further supported our new algorithm. Together, GridFit and CEPA constitute a versatile set of tools for the registration of subdural grid, strip, and depth electrode coordinates that provide highly accurate results even in the most challenging implantation scenarios. The methods presented here are implemented in the iElectrodes open-source toolbox, making their use simple, accessible, and straightforward to integrate with other popular toolboxes used for analyzing electrophysiological data.

Attentional modulation of beta-power aligns with the timing of behaviorally relevant rhythmic sounds.

It is largely unknown how attention adapts to the timing of acoustic stimuli. To address this, we investigated how hemispheric lateralization of alpha (7-13 Hz) and beta (14-24 Hz) oscillations, reflecting voluntary allocation of auditory spatial attention, is influenced by tempo and predictability of sounds. We recorded electroencephalography while healthy adults listened to rhythmic sound streams with different tempos that were presented dichotically to separate ears, thus permitting manipulation of spatial-temporal attention. Participants responded to stimulus-onset-asynchrony (SOA) deviants (-90 ms) for given tones in the attended rhythm. Rhythm predictability was controlled via the probability of SOA deviants per block. First, the results revealed hemispheric lateralization of beta-power according to attention direction, reflected as ipsilateral enhancement and contralateral suppression, which was amplified in high- relative to low-predictability conditions. Second, fluctuations in the time-resolved beta-lateralization aligned more strongly with the attended than the unattended tempo. Finally, a trend-level association was found between the degree of beta-lateralization and improved ability to distinguish between SOA-deviants in the attended versus unattended ear. Differently from previous studies, we presented continuous rhythms in which task-relevant and irrelevant stimuli had different tempo, thereby demonstrating that temporal alignment of beta-lateralization with attended sounds reflects top-down attention to sound timing.

Monitoring of Self-Paced Action Timing and Sensory Outcomes After Lesions to the Orbitofrontal Cortex.

Anticipation, monitoring, and evaluation of the outcome of one's actions are at the core of proactive control. Individuals with lesions to OFC often demonstrate behaviors that indicate a lack of recognition or concern for the negative effects of their actions. Altered action timing has also been reported in these patients. We investigated the role of OFC in predicting and monitoring the sensory outcomes of self-paced actions. We studied patients with focal OFC lesions (n = 15) and healthy controls (n = 20) while they produced actions that infrequently evoked unexpected outcomes. Participants performed a self-paced, random generation task where they repeatedly pressed right and left buttons that were associated with specific sensory outcomes: a 1- and 2-kHz tone, respectively. Occasional unexpected action outcomes occurred (mismatch) that inverted the learned button-tone association (match). We analyzed ERPs to the expected and unexpected outcomes as well as action timing. Neither group showed post-mismatch slowing of button presses, but OFC patients had a higher number of fast button presses, indicating that they were inferior to controls at producing regularly timed actions. Mismatch trials elicited enhanced N2b-P3a responses across groups as indicated by the significant main effect of task condition. Planned within-group analyses showed, however, that patients did not have a significant condition effect, suggesting that the result of the omnibus analysis was driven primarily by the controls. Altogether, our findings indicate that monitoring of action timing and the sensory outcomes of self-paced actions as indexed by ERPs is impacted by OFC damage.

Reducing power line noise in EEG and MEG data via spectrum interpolation.

Electroencephalographic (EEG) and magnetoencephalographic (MEG) signals can often be exposed to strong power line interference at 50 or 60 Hz. A widely used method to remove line noise is the notch filter, but it comes with the risk of potentially severe signal distortions. Among other approaches, the Discrete Fourier Transform (DFT) filter and CleanLine have been developed as alternatives, but they may fail to remove power line noise of highly fluctuating amplitude. Here we introduce spectrum interpolation as a new method to remove line noise in the EEG and MEG signal. This approach had been developed for electromyographic (EMG) signals, and combines the advantages of a notch filter, while synthetic test signals indicate that it introduces less distortion in the time domain. The effectiveness of this method is compared to CleanLine, the notch (Butterworth) and DFT filter. In order to quantify the performance of these three methods, we used synthetic test signals and simulated power line noise with fluctuating amplitude and abrupt on- and offsets that were added to an MEG dataset free of line noise. In addition, all methods were applied to EEG data with massive power line noise due to acquisition in unshielded settings. We show that spectrum interpolation outperforms the DFT filter and CleanLine, when power line noise is nonstationary. At the same time, spectrum interpolation performs equally well as the notch filter in removing line noise artifacts, but shows less distortions in the time domain in many common situations.

Preservation of Interference Effects in Working Memory After Orbitofrontal Damage.

Orbitofrontal cortex (OFC) is implicated in multiple cognitive processes, including inhibitory control, context memory, recency judgment, and choice behavior. Despite an emerging understanding of the role of OFC in memory and executive control, its necessity for core working memory (WM) operations remains undefined. Here, we assessed the impact of OFC damage on interference effects in WM using a Recent Probes task based on the Sternberg item-recognition task (1966). Subjects were asked to memorize a set of letters and then indicate whether a probe letter was presented in a particular set. Four conditions were created according to the forthcoming response ("yes"/"no") and the recency of the probe (presented in the previous trial set or not). We compared behavioral and electroencephalography (EEG) responses between healthy subjects (n = 14) and patients with bilateral OFC damage (n = 14). Both groups had the same recency pattern of slower reaction time (RT) when the probe was presented in the previous trial but not in the current one, reflecting the proactive interference (PI). The within-group electrophysiological results showed no condition difference during letter encoding and maintenance. In contrast, event-related potentials (ERPs) to probes showed distinct within-group condition effects, and condition by group effects. The response and recency effects for controls occurred within the same time window (300-500 ms after probe onset) and were observed in two distinct spatial groups including right centro-posterior and left frontal electrodes. Both clusters showed ERP differences elicited by the response effect, and one cluster was also sensitive to the recency manipulation. Condition differences for the OFC group involved two different clusters, encompassing only left hemisphere electrodes and occurring during two consecutive time windows (345-463 ms and 565-710 ms). Both clusters were sensitive to the response effect, but no recency effect was found despite the behavioral recency effect. Although the groups had different electrophysiological responses, the maintenance of letters in WM, the evaluation of the context of the probe, and the decision to accept or reject a probed letter were preserved in OFC patients. The results suggest that neural reorganization may contribute to intact recency judgment and response after OFC damage.

The Tactile Window to Consciousness is Characterized by Frequency-Specific Integration and Segregation of the Primary Somatosensory Cortex.

We recently proposed that besides levels of local cortical excitability, also distinct pre-stimulus network states (windows to consciousness) determine whether a near-threshold stimulus will be consciously perceived. In the present magnetoencephalography study, we scrutinised these pre-stimulus network states with a focus on the primary somatosensory cortex. For this purpose participants performed a simple near-threshold tactile detection task. Confirming previous studies, we found reduced alpha and beta power in the somatosensory region contralateral to stimulation prior to correct stimulus detection as compared to undetected stimuli, and stronger event-related responses following successful stimulus detection. As expected, using graph theoretical measures, we also observed modulated pre-stimulus network level integration. Specifically, the right primary somatosensory cortex contralateral to stimulation showed an increased integration in the theta band, and additionally, a decreased integration in the beta band. Overall, these results underline the importance of network states for enabling conscious perception. Moreover, they indicate that also a reduction of irrelevant functional connections contributes to the window to consciousness by tuning pre-stimulus pathways of information flow.

Prestimulus Network Integration of Auditory Cortex Predisposes Near-Threshold Perception Independently of Local Excitability.

An ever-increasing number of studies are pointing to the importance of network properties of the brain for understanding behavior such as conscious perception. However, with regards to the influence of prestimulus brain states on perception, this network perspective has rarely been taken. Our recent framework predicts that brain regions crucial for a conscious percept are coupled prior to stimulus arrival, forming pre-established pathways of information flow and influencing perceptual awareness. Using magnetoencephalography (MEG) and graph theoretical measures, we investigated auditory conscious perception in a near-threshold (NT) task and found strong support for this framework. Relevant auditory regions showed an increased prestimulus interhemispheric connectivity. The left auditory cortex was characterized by a hub-like behavior and an enhanced integration into the brain functional network prior to perceptual awareness. Right auditory regions were decoupled from non-auditory regions, presumably forming an integrated information processing unit with the left auditory cortex. In addition, we show for the first time for the auditory modality that local excitability, measured by decreased alpha power in the auditory cortex, increases prior to conscious percepts. Importantly, we were able to show that connectivity states seem to be largely independent from local excitability states in the context of a NT paradigm.

What it means to be Zen: marked modulations of local and interareal synchronization during open monitoring meditation.

Experienced meditators are able to voluntarily modulate their state of consciousness and attention. In the present study, we took advantage of this ability and studied brain activity related to the shift of mental state. Electrophysiological activity, i.e. EEG, was recorded from 11 subjects with varying degrees of meditation experience during Zen meditation (a form of open monitoring meditation) and during non-meditation rest. On a behavioral level, mindfulness scores were assessed using the Mindfulness Attention and Awareness Scale (MAAS). Analysis of EEG source power revealed the so far unreported finding that MAAS scores significantly correlated with gamma power (30-250Hz), particularly high-frequency gamma (100-245Hz), during meditation. High levels of mindfulness were related to increased high-frequency gamma, for example, in the cingulate cortex and somatosensory cortices. Further, we analyzed the relationship between connectivity during meditation and self-reported mindfulness (MAAS). We found a correlation between graph measures in the 160-170Hz range and MAAS scores. Higher levels of mindfulness were related to lower small worldedness as well as global and local clustering in paracentral, insular, and thalamic regions during meditation. In sum, the present study shows significant relationships of mindfulness and brain activity during meditation indicated by measures of oscillatory power and graph theoretical measures. The most prominent effects occur in brain structures crucially involved in processes of awareness and attention, which also show structural changes in short- and long-term meditators, suggesting continuative alterations in the meditating brain. Overall, our study reveals strong changes in ongoing oscillatory activity as well as connectivity patterns that appear to be sensitive to the psychological state changes induced by Zen meditation.

Listen to Yourself: The Medial Prefrontal Cortex Modulates Auditory Alpha Power During Speech Preparation.

How do we process stimuli that stem from the external world and stimuli that are self-generated? In the case of voice perception it has been shown that evoked activity elicited by self-generated sounds is suppressed compared with the same sounds played-back externally. We here wanted to reveal whether neural excitability of the auditory cortex-putatively reflected in local alpha band power--is modulated already prior to speech onset, and which brain regions may mediate such a top-down preparatory response. In the left auditory cortex we show that the typical alpha suppression found when participants prepare to listen disappears when participants expect a self-spoken sound. This suggests an inhibitory adjustment of auditory cortical activity already before sound onset. As a second main finding we demonstrate that the medial prefrontal cortex, a region known for self-referential processes, mediates these condition-specific alpha power modulations. This provides crucial insights into how higher-order regions prepare the auditory cortex for the processing of self-generated sounds. Furthermore, the mechanism outlined could provide further explanations to self-referential phenomena, such as "tickling yourself". Finally, it has implications for the so-far unsolved question of how auditory alpha power is mediated by higher-order regions in a more general sense.

The strength of alpha and beta oscillations parametrically scale with the strength of an illusory auditory percept.

Studies investigating the role of oscillatory activity in sensory perception are primarily conducted in the visual domain, while the contribution of oscillatory activity to auditory perception is heavily understudied. The objective of the present study was to investigate macroscopic (EEG) oscillatory brain response patterns that contribute to an auditory (Zwicker tone, ZT) illusion. Three different analysis approaches were chosen: 1) a parametric variation of the ZT illusion intensity via three different notch widths of the ZT-inducing noise; 2) contrasts of high-versus-low-intensity ZT illusion trials, excluding physical stimuli differences; 3) a representational similarity analysis to relate source activity patterns to loudness ratings. Depending on the analysis approach, levels of alpha to beta activity (10-20Hz) reflected illusion intensity, mainly defined by reduced power levels co-occurring with stronger percepts. Consistent across all analysis approaches, source level analysis implicated auditory cortices as main generators, providing evidence that the activity level in the alpha and beta range - at least in part - contributes to the strength of the illusory auditory percept. This study corroborates the notion that alpha to beta activity in the auditory cortex is linked to functionally similar states, as has been proposed for visual, somatosensory and motor regions. Furthermore, our study provides certain theoretical implications for pathological auditory conscious perception (tinnitus).