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.

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.

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.

Periodic attention deficits after frontoparietal lesions provide causal evidence for rhythmic attentional sampling.

Contemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time, even in states of presumed "sustained" attention. Recent evidence has suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results revealed that frontoparietal lesions introduce periodic attention deficits, i.e., temporally specific behavioral deficits that are aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with that of healthy controls during optimal phases but was attenuated during the less excitable sub-cycles. Theta-dependent sampling (3-8 Hz) was causally dependent on the prefrontal cortex, while high-alpha/low-beta sampling (8-14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high-amplitude, low-frequency brain activity is not epiphenomenal but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.

Decision and response monitoring during working memory are sequentially represented in the human insula.

Emerging research supports a role of the insula in human cognition. Here, we used intracranial EEG to investigate the spatiotemporal dynamics in the insula during a verbal working memory (vWM) task. We found robust effects for theta, beta, and high frequency activity (HFA) during probe presentation requiring a decision. Theta band activity showed differential involvement across left and right insulae while sequential HFA modulations were observed along the anteroposterior axis. HFA in anterior insula tracked decision making and subsequent HFA was observed in posterior insula after the behavioral response. Our results provide electrophysiological evidence of engagement of different insula subregions in both decision-making and response monitoring during vWM and expand our knowledge of the role of the insula in complex human behavior.

Executive functioning as a moderator of flossing behaviour among young adults: a temporal self-regulation theory perspective.

Background: Flossing among young adults is often infrequent and barriers not completely understood. One explanation concerns the capacity for executive functioning (EF) during the self-regulation of behaviour. Methods: Using Temporal Self-Regulation Theory (TST) as a framework to explore EF, young adults from Norwegian universities completed a survey that measured monthly flossing frequency, flossing-related intentions and behavioural prepotency (BP), and EF using the Behaviour Rating Inventory of Executive Function - Adult Version (BRIEF-A). Results: Data from 362 participants were analysed. The TST-model explained a substantial proportion of variance in monthly flossing (R2 = 0.74), and flossing was associated directly with intention and BP, and interactions between intention and both BP and global-EF. Sub-domains of EF were explored using the same model, revealing that behavioural regulation processes, specifically those related to emotional control and shifting between tasks, offered better fit. Simple slopes revealed that moderation effects were only present at lower levels of BP. Conclusion: EF plays a role in moderating the translation of intentions into flossing behaviour. Specifically, emotional control and task-shifting appear to be influential, and this influence increases when habitual and environmental support (i.e. BP) is reduced. Overcoming EF-barriers may represent a key step in establishing flossing behaviours.

Subspace partitioning in the human prefrontal cortex resolves cognitive interference.

The human prefrontal cortex (PFC) constitutes the structural basis underlying flexible cognitive control, where mixed-selective neural populations encode multiple task features to guide subsequent behavior. The mechanisms by which the brain simultaneously encodes multiple task-relevant variables while minimizing interference from task-irrelevant features remain unknown. Leveraging intracranial recordings from the human PFC, we first demonstrate that competition between coexisting representations of past and present task variables incurs a behavioral switch cost. Our results reveal that this interference between past and present states in the PFC is resolved through coding partitioning into distinct low-dimensional neural states; thereby strongly attenuating behavioral switch costs. In sum, these findings uncover a fundamental coding mechanism that constitutes a central building block of flexible cognitive control.

Quantifying evoked responses through information-theoretical measures.

Information theory is a viable candidate to advance our understanding of how the brain processes information generated in the internal or external environment. With its universal applicability, information theory enables the analysis of complex data sets, is free of requirements about the data structure, and can help infer the underlying brain mechanisms. Information-theoretical metrics such as Entropy or Mutual Information have been highly beneficial for analyzing neurophysiological recordings. However, a direct comparison of the performance of these methods with well-established metrics, such as the t-test, is rare. Here, such a comparison is carried out by evaluating the novel method of Encoded Information with Mutual Information, Gaussian Copula Mutual Information, Neural Frequency Tagging, and t-test. We do so by applying each method to event-related potentials and event-related activity in different frequency bands originating from intracranial electroencephalography recordings of humans and marmoset monkeys. Encoded Information is a novel procedure that assesses the similarity of brain responses across experimental conditions by compressing the respective signals. Such an information-based encoding is attractive whenever one is interested in detecting where in the brain condition effects are present.

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.

Modeling intracranial electrodes. A simulation platform for the evaluation of localization algorithms.

Introduction: Intracranial electrodes are implanted in patients with drug-resistant epilepsy as part of their pre-surgical evaluation. This allows the investigation of normal and pathological brain functions with excellent spatial and temporal resolution. The spatial resolution relies on methods that precisely localize the implanted electrodes in the cerebral cortex, which is critical for drawing valid inferences about the anatomical localization of brain function. Multiple methods have been developed to localize the electrodes, mainly relying on pre-implantation MRI and post-implantation computer tomography (CT) images. However, they are hard to validate because there is no ground truth data to test them and there is no standard approach to systematically quantify their performance. In other words, their validation lacks standardization. Our work aimed to model intracranial electrode arrays and simulate realistic implantation scenarios, thereby providing localization algorithms with new ways to evaluate and optimize their performance. Results: We implemented novel methods to model the coordinates of implanted grids, strips, and depth electrodes, as well as the CT artifacts produced by these. We successfully modeled realistic implantation scenarios, including different sizes, inter-electrode distances, and brain areas. In total, ∼3,300 grids and strips were fitted over the brain surface, and ∼850 depth electrode arrays penetrating the cortical tissue were modeled. Realistic CT artifacts were simulated at the electrode locations under 12 different noise levels. Altogether, ∼50,000 thresholded CT artifact arrays were simulated in these scenarios, and validated with real data from 17 patients regarding the coordinates' spatial deformation, and the CT artifacts' shape, intensity distribution, and noise level. Finally, we provide an example of how the simulation platform is used to characterize the performance of two cluster-based localization methods. Conclusion: We successfully developed the first platform to model implanted intracranial grids, strips, and depth electrodes and realistically simulate thresholded CT artifacts and their noise. These methods provide a basis for developing more complex models, while simulations allow systematic evaluation of the performance of electrode localization techniques. The methods described in this article, and the results obtained from the simulations, are freely available via open repositories. A graphical user interface implementation is also accessible via the open-source iElectrodes toolbox.

Long-term post-concussion symptoms. / Langvarige plager etter hjernerystelse.

Concussion is common and usually resolves without complications. However, persistent symptoms occur in 10-15 % of patients. These post-concussion symptoms are predominantly somatic, cognitive and emotional. The condition is most common in those with previous somatic and mental health issues. The causes underlying long-term post-concussion symptoms are unclear, but a biopsychosocial explanatory model is currently regarded as the most appropriate basis for diagnosis and treatment. This clinical review article is based on key literature and our own clinical experiences with patients who have these long-term post-concussion symptoms.

Complexity-based Encoded Information Quantification in Neurophysiological Recordings.

Brain activity differs vastly between sleep, cognitive tasks, and action. Information theory is an appropriate concept to analytically quantify these brain states. Based on neurophysiological recordings, this concept can handle complex data sets, is free of any requirements about the data structure, and can infer the present underlying brain mechanisms. Specifically, by utilizing algorithmic information theory, it is possible to estimate the absolute information contained in brain responses. While current approaches that apply this theory to neurophysiological recordings can discriminate between different brain states, they are limited in directly quantifying the degree of similarity or encoded information between brain responses. Here, we propose a method grounded in algorithmic information theory that affords direct statements about responses' similarity by estimating the encoded information through a compression-based scheme. We validated this method by applying it to both synthetic and real neurophysiological data and compared its efficiency to the mutual information measure. This proposed procedure is especially suited for task paradigms contrasting different event types because it can precisely quantify the similarity of neuronal responses.

Regional brain volume prior to treatment is linked to outcome after cognitive rehabilitation in traumatic brain injury.

Cognitive rehabilitation is useful for many after traumatic brain injury (TBI), but we lack critical knowledge about which patients benefit the most from different approaches. Advanced neuroimaging techniques have provided important insight into brain pathology and systems plasticity after TBI, and have potential to inform new practices in cognitive rehabilitation. In this study, we aimed to identify candidate structural brain measures with relevance for rehabilitation of cognitive control (executive) function after TBI. Twenty-eight patients (9 female, mean age 40.5 (SD = 13.04) years) with TBI (>21 months since injury) that participated in a randomized controlled cognitive rehabilitation trial (NCT02692352) were included in the analyses. Regional brain volume was extracted from T1-weighted MRI scans before treatment using tensor-based morphometry. Both positive and negative associations between treatment outcome (everyday cognitive control function) and regional brain volume were observed. The most robust associations between regional brain volume and improvement in function were observed in midline fronto-parietal regions, including the anterior and posterior cingulate cortices. The study provides proof of concept and valuable insight for planning future studies focusing on neuroimaging in cognitive rehabilitation after TBI.

Orbitofrontal cortex governs working memory for temporal order.

How do we think about time? Converging lesion and neuroimaging evidence indicates that orbitofrontal cortex (OFC) supports the encoding and retrieval of temporal context in long-term memory1, which may contribute to confabulation in individuals with OFC damage2. Here, we reveal that OFC damage diminishes working memory for temporal order, that is, the ability to disentangle the relative recency of events as they unfold. OFC lesions reduced working memory for temporal order but not spatial position, and individual deficits were commensurate with lesion size. Comparable effects were absent in patients with lesions restricted to lateral prefrontal cortex (PFC). Based on these findings, we propose that OFC supports understanding of the order of events. Well-documented behavioral changes in individuals with OFC damage2 may relate to impaired temporal-order understanding.

Intact Proactive Motor Inhibition after Unilateral Prefrontal Cortex or Basal Ganglia Lesions.

Previous research provided evidence for the critical importance of the PFC and BG for reactive motor inhibition, that is, when actions are cancelled in response to external signals. Less is known about the role of the PFC and BG in proactive motor inhibition, referring to preparation for an upcoming stop signal. In this study, patients with unilateral lesions to the BG or lateral PFC performed in a cued go/no-go task, whereas their EEG was recorded. The paradigm called for cue-based preparation for upcoming, lateralized no-go signals. Based on previous findings, we focused on EEG indices of cognitive control (prefrontal beta), motor preparation (sensorimotor mu/beta, contingent negative variation [CNV]), and preparatory attention (occipital alpha, CNV). On a behavioral level, no differences between patients and controls were found, suggesting an intact ability to proactively prepare for motor inhibition. Patients showed an altered preparatory CNV effect, but no other differences in electrophysiological activity related to proactive and reactive motor inhibition. Our results suggest a context-dependent role of BG and PFC structures in motor inhibition, being critical in reactive, unpredictable contexts, but less so in situations where one can prepare for stopping on a short timescale.

Intracranial Recordings Demonstrate Both Cortical and Medial Temporal Lobe Engagement in Visual Search in Humans.

Visual search is a fundamental human behavior, providing a gateway to understanding other sensory domains as well as the role of search in higher-order cognition. Search has been proposed to include two component processes: inefficient search (Search) and efficient search (Pop-out). According to extant research, these two processes map onto two separable neural systems located in the frontal and parietal association cortices. In this study, we use intracranial recordings from 23 participants to delineate the neural correlates of Search and Pop-out with an unprecedented combination of spatiotemporal resolution and coverage across cortical and subcortical structures. First, we demonstrate a role for the medial temporal lobe in visual search, on par with engagement in frontal and parietal association cortex. Second, we show a gradient of increasing engagement over anatomical space from dorsal to ventral lateral frontal cortex. Third, we confirm previous intracranial work demonstrating nearly complete overlap in neural engagement across cortical regions in Search and Pop-out. We further demonstrate Pop-out selectivity, manifesting as activity increase in Pop-out as compared to Search, in a distributed set of sites including frontal cortex. This result is at odds with the view that Pop-out is implemented in low-level visual cortex or parietal cortex alone. Finally, we affirm a central role for the right lateral frontal cortex in Search.

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.

Patients with Ventromedial Prefrontal Lesions Show an Implicit Approach Bias to Angry Faces.

Damage to the ventromedial PFC (VMPFC) can cause maladaptive social behavior, but the cognitive processes underlying these behavioral changes are still uncertain. Here, we tested whether patients with acquired VMPFC lesions show altered approach-avoidance tendencies to emotional facial expressions. Thirteen patients with focal VMPFC lesions and 31 age- and gender-matched healthy controls performed an implicit approach-avoidance task in which they either pushed or pulled a joystick depending on stimulus color. Whereas controls avoided angry faces, VMPFC patients displayed an incongruent response pattern characterized by both increased approach and reduced avoidance of angry facial expressions. The approach bias was stronger in patients with higher self-reported impulsivity and disinhibition and in those with larger lesions. We further used linear ballistic accumulator modeling to investigate latent parameters underlying approach-avoidance decisions. Controls displayed negative drift rates when approaching angry faces, whereas VMPFC lesions abolished this pattern. In addition, VMPFC patients had weaker response drifts than controls during avoidance. Finally, patients showed reduced drift rate variability and shorter nondecision times, indicating impulsive and rigid decision-making. Our findings thus suggest that VMPFC damage alters the pace of evidence accumulation in response to social signals, eliminating a default, protective avoidant bias and facilitating a dysfunctional approach behavior.

Gender bias in academia: A lifetime problem that needs solutions.

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow, and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in science. Here, we argue that gender bias is not a single problem but manifests as a collection of distinct issues that impact researchers' lives. We disentangle these facets and propose concrete solutions that can be adopted by individuals, academic institutions, and society.