Protocol for combined N-of-1 trials to assess cerebellar neurostimulation for movement disorders in children and young adults with dyskinetic cerebral palsy.

Background: Movement and tone disorders in children and young adults with cerebral palsy are a great source of disability. Deep brain stimulation (DBS) of basal ganglia targets has a major role in the treatment of isolated dystonias, but its efficacy in dyskinetic cerebral palsy (DCP) is lower, due to structural basal ganglia and thalamic damage and lack of improvement of comorbid choreoathetosis and spasticity. The cerebellum is an attractive target for DBS in DCP since it is frequently spared from hypoxic ischemic damage, it has a significant role in dystonia network models, and small studies have shown promise of dentate stimulation in improving CP-related movement and tone disorders. Methods: Ten children and young adults with DCP and disabling movement disorders with or without spasticity will undergo bilateral DBS in the dorsal dentate nucleus, with the most distal contact ending in the superior cerebellar peduncle. We will implant Medtronic Percept, a bidirectional neurostimulator that can sense and store brain activity and deliver DBS therapy. The efficacy of cerebellar DBS in improving quality of life and motor outcomes will be tested by a series of N-of-1 clinical trials. Each N-of-1 trial will consist of three blocks, each consisting of one month of effective stimulation and one month of sham stimulation in a random order with weekly motor and quality of life scales as primary and secondary outcomes. In addition, we will characterize abnormal patterns of cerebellar oscillatory activity measured by local field potentials from the intracranial electrodes related to clinical assessments and wearable monitors. Pre- and 12-month postoperative volumetric structural and functional MRI and diffusion tensor imaging will be used to identify candidate imaging markers of baseline disease severity and response to DBS. Discussion: Our goal is to test a cerebellar neuromodulation therapy that produces meaningful changes in function and well-being for people with CP, obtain a mechanistic understanding of the underlying brain network disorder, and identify physiological and imaging-based predictors of outcomes useful in planning further studies. Trial registration: ClinicalTrials.gov NCT06122675, first registered November 7, 2023.

Theta frequency deep brain stimulation in the subthalamic nucleus improves working memory in Parkinson's disease.

Most research in Parkinson's disease focuses on improving motor symptoms. Yet, up to 80% of patients present with non-motor symptoms that often have a large impact on patients' quality of life. Impairment in working memory, a fundamental cognitive process, is common in Parkinson's disease. While deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms in Parkinson's disease, its impact on cognitive functions is less well studied. Here, we examine the effect of DBS in the theta, beta, low and high gamma frequency on working memory in 20 Parkinson's disease patients with bilateral STN-DBS. A linear mixed effects model demonstrates that STN-DBS in the theta frequency improves working memory performance. This effect is frequency-specific and was absent for beta and gamma frequency stimulation. Further, this effect is specific to cognitive performance, as theta frequency DBS did not affect motor function. A non-parametric cluster-based permutation analysis of whole-brain normative structural connectivity shows that working memory enhancement by theta frequency stimulation is associated with higher connectivity between the stimulated subthalamic area and the right middle frontal gyrus. Again, this association is frequency- and task-specific. These findings highlight the potential of theta frequency STN-DBS as a targeted intervention to improve working memory in patients with Parkinson's disease.

Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in Parkinson's disease.

Deep brain stimulation is a widely used therapy for Parkinson's disease (PD) but currently lacks dynamic responsiveness to changing clinical and neural states. Feedback control has the potential to improve therapeutic effectiveness, but optimal control strategy and additional benefits of "adaptive" neurostimulation are unclear. We implemented adaptive subthalamic nucleus stimulation, controlled by subthalamic or cortical signals, in three PD patients (five hemispheres) during normal daily life. We identified neurophysiological biomarkers of residual motor fluctuations using data-driven analyses of field potentials over a wide frequency range and varying stimulation amplitudes. Narrowband gamma oscillations (65-70 Hz) at either site emerged as the best control signal for sensing during stimulation. A blinded, randomized trial demonstrated improved motor symptoms and quality of life compared to clinically optimized standard stimulation. Our approach highlights the promise of personalized adaptive neurostimulation based on data-driven selection of control signals and may be applied to other neurological disorders.

Binaural acoustic stimulation in patients with Parkinson's disease.

Acoustic stimulation can improve motor symptoms in Parkinson's disease (PD) and might therefore represent a potential non-invasive treatment option. Scalp electroencephalography studies in healthy subjects indicate that specifically binaural beat stimulation (BBS) in the gamma frequency range is associated with synchronized cortical oscillations at 40 Hertz (Hz). Several studies suggest that oscillations in the gamma-frequency range (>30 Hz) serve a prokinetic function in PD. In this double-blind, randomized study, 25 PD patients were recruited. The study was conducted with (ON) and without dopaminergic medication (OFF). Each drug condition consisted of two phases (no stimulation and acoustic stimulation). The acoustic stimulation phase was divided into two blocks including BBS and conventional acoustic stimulation (CAS) as a control condition. For BBS, a modulated frequency of 35 Hz was used (left: 320 Hz; right: 355 Hz) and for CAS 340 Hz on both sides. We assessed effects on motor performance using Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and two validated commercially available portable devices (Kinesia ONE™ and Kinesia 360™) measuring motor symptoms such as dyskinesia, bradykinesia, and tremor. Repeated measures ANOVA revealed that BBS improved resting tremor on the side of the more affected limb in the OFF condition, as measured by wearables (F(2,48) = 3.61, p = 0.035). However, BBS did not exert a general positive effect on motor symptoms as assessed via MDS-UPDRS (F(2,48) = 1.00, p = 0.327). For CAS, we did not observe an improvement in specific symptoms but rather an overall beneficial effect on motor performance (MDS-UPDRS total score OFF medication: F(2,48) = 4.17, p = 0.021; wearable scores: F(2,48) = 2.46, p = 0.097). In this study, we found an improvement of resting tremor when applying BBS in the gamma frequency band OFF medication. Moreover, the positive effects of CAS underline the general positive potential for improvement of motor function by acoustically supported therapeutic approaches. However, more studies are needed to fully characterize the clinical relevance of BBS and to further optimize its ameliorating effects.

Aversive memory formation in humans involves an amygdala-hippocampus phase code.

Memory for aversive events is central to survival but can become maladaptive in psychiatric disorders. Memory enhancement for emotional events is thought to depend on amygdala modulation of hippocampal activity. However, the neural dynamics of amygdala-hippocampal communication during emotional memory encoding remain unknown. Using simultaneous intracranial recordings from both structures in human patients, here we show that successful emotional memory encoding depends on the amygdala theta phase to which hippocampal gamma activity and neuronal firing couple. The phase difference between subsequently remembered vs. not-remembered emotional stimuli translates to a time period that enables lagged coherence between amygdala and downstream hippocampal gamma. These results reveal a mechanism whereby amygdala theta phase coordinates transient amygdala -hippocampal gamma coherence to facilitate aversive memory encoding. Pacing of lagged gamma coherence via amygdala theta phase may represent a general mechanism through which the amygdala relays emotional content to distant brain regions to modulate other aspects of cognition, such as attention and decision-making.

NoLiTiA: An Open-Source Toolbox for Non-linear Time Series Analysis.

In many scientific fields including neuroscience, climatology or physics, complex relationships can be described most parsimoniously by non-linear mechanics. Despite their relevance, many neuroscientists still apply linear estimates in order to evaluate complex interactions. This is partially due to the lack of a comprehensive compilation of non-linear methods. Available packages mostly specialize in only one aspect of non-linear time-series analysis and most often require some coding proficiency to use. Here, we introduce NoLiTiA, a free open-source MATLAB toolbox for non-linear time series analysis. In comparison to other currently available non-linear packages, NoLiTiA offers (1) an implementation of a broad range of classic and recently developed methods, (2) an implementation of newly proposed spatially and time-resolved recurrence amplitude analysis and (3) an intuitive environment accessible even to users with little coding experience due to a graphical user interface and batch-editor. The core methodology derives from three distinct fields of complex systems theory, including dynamical systems theory, recurrence quantification analysis and information theory. Besides established methodology including estimation of dynamic invariants like Lyapunov exponents and entropy-based measures, such as active information storage, we include recent developments of quantifying time-resolved aperiodic oscillations. In general, the toolbox will make non-linear methods accessible to the broad neuroscientific community engaged in time series processing.

Microstructural alterations predict impaired bimanual control in Parkinson's disease.

Bimanual coordination is impaired in Parkinson's disease affecting patients' ability to perform activities of daily living and to maintain independence. Conveyance of information between cortical and subcortical areas is essential for bimanual coordination and relies on the integrity of cerebral microstructure. As pathological deposition of alpha-synuclein compromises microstructure in Parkinson's disease, we investigated the relationship between microstructural integrity and bimanual coordination using diffusion-weighted MRI in 23 patients with Parkinson's disease (mean age ± standard deviation: 56.0 ± 6.45 years; 8 female) and 26 older adults (mean age ± standard deviation: 58.5 ± 5.52 years). Whole-brain analysis revealed specific microstructural alterations between patients and healthy controls matched for age, sex, handedness, and cognitive status congruent with the literature and known Parkinson's disease pathology. A general linear model revealed distinct microstructural alterations associated with poor bimanual coordination in Parkinson's disease, corrected for multiple comparisons using a permutation-based approach. Integrating known functional topography, we conclude that distinct changes in microstructure cause an impediment of structures involved in attention, working memory, executive function, motor planning, motor control, and visual processing contributing to impaired bimanual coordination in Parkinson's disease.

Non-invasive vagus nerve stimulation in epilepsy patients enhances cooperative behavior in the prisoner's dilemma task.

The vagus nerve constitutes a key link between the autonomic and the central nervous system. Previous studies provide evidence for the impact of vagal activity on distinct cognitive processes including functions related to social cognition. Recent studies in animals and humans show that vagus nerve stimulation is associated with enhanced reward-seeking and dopamine-release in the brain. Social interaction recruits similar brain circuits to reward processing. We hypothesize that vagus nerve stimulation (VNS) boosts rewarding aspects of social behavior and compare the impact of transcutaneous VNS (tVNS) and sham stimulation on social interaction in 19 epilepsy patients in a double-blind pseudo-randomized study with cross-over design. Using a well-established paradigm, i.e., the prisoner's dilemma, we investigate effects of stimulation on cooperative behavior, as well as interactions of stimulation effects with patient characteristics. A repeated-measures ANOVA and a linear mixed-effects model provide converging evidence that tVNS boosts cooperation. Post-hoc correlations reveal that this effect varies as a function of neuroticism, a personality trait linked to the dopaminergic system. Behavioral modeling indicates that tVNS induces a behavioral starting bias towards cooperation, which is independent of the decision process. This study provides evidence for the causal influence of vagus nerve activity on social interaction.

A Waveform-Independent Measure of Recurrent Neural Activity.

Rhythmic neural activity, so-called oscillations, plays a key role in neural information transmission, processing, and storage. Neural oscillations in distinct frequency bands are central to physiological brain function, and alterations thereof have been associated with several neurological and psychiatric disorders. The most common methods to analyze neural oscillations, e.g., short-time Fourier transform or wavelet analysis, assume that measured neural activity is composed of a series of symmetric prototypical waveforms, e.g., sinusoids. However, usually, the models generating the signal, including waveform shapes of experimentally measured neural activity are unknown. Decomposing asymmetric waveforms of nonlinear origin using these classic methods may result in spurious harmonics visible in the estimated frequency spectra. Here, we introduce a new method for capturing rhythmic brain activity based on recurrences of similar states in phase-space. This method allows for a time-resolved estimation of amplitude fluctuations of recurrent activity irrespective of or specific to waveform shapes. The algorithm is derived from the well-established field of recurrence analysis, which, in comparison to Fourier-based analysis, is still very uncommon in neuroscience. In this paper, we show its advantages and limitations in comparison to short-time Fourier transform and wavelet convolution using periodic signals of different waveform shapes. Furthermore, we demonstrate its application using experimental data, i.e., intracranial and noninvasive electrophysiological recordings from the human motor cortex of one epilepsy patient and one healthy adult, respectively.

Concurrent stimulation and sensing in bi-directional brain interfaces: a multi-site translational experience.

Objective. To provide a design analysis and guidance framework for the implementation of concurrent stimulation and sensing during adaptive deep brain stimulation (aDBS) with particular emphasis on artifact mitigations.Approach. We defined a general architecture of feedback-enabled devices, identified key components in the signal chain which might result in unwanted artifacts and proposed methods that might ultimately enable improved aDBS therapies. We gathered data from research subjects chronically-implanted with an investigational aDBS system, Summit RC + S, to characterize and explore artifact mitigations arising from concurrent stimulation and sensing. We then used a prototype investigational implantable device, DyNeuMo, and a bench-setup that accounts for tissue-electrode properties, to confirm our observations and verify mitigations. The strategies to reduce transient stimulation artifacts and improve performance during aDBS were confirmed in a chronic implant using updated configuration settings.Main results.We derived and validated a 'checklist' of configuration settings to improve system performance and areas for future device improvement. Key considerations for the configuration include (a) active instead of passive recharge, (b) sense-channel blanking in the amplifier, (c) high-pass filter settings, (d) tissue-electrode impedance mismatch management, (e) time-frequency trade-offs in the classifier, (f) algorithm blanking and transition rate limits. Without proper channel configuration, the aDBS algorithm was susceptible to limit-cycles of oscillating stimulation independent of physiological state. By applying the checklist, we could optimize each block's performance characteristics within the overall system. With system-level optimization, a 'fast' aDBS prototype algorithm was demonstrated to be feasible without reentrant loops, and with noise performance suitable for subcortical brain circuits.Significance. We present a framework to study sources and propose mitigations of artifacts in devices that provide chronic aDBS. This work highlights the trade-offs in performance as novel sensing devices translate to the clinic. Finding the appropriate balance of constraints is imperative for successful translation of aDBS therapies.Clinical trial:Institutional Review Board and Investigational Device Exemption numbers: NCT02649166/IRB201501021 (University of Florida), NCT04043403/IRB52548 (Stanford University), NCT03582891/IRB1824454 (University of California San Francisco). IDE #180 097.

German normative data with naming latencies for 283 action pictures and 600 action verbs.

Timed picture naming is a common psycholinguistic paradigm. In this task, participants are asked to label visually depicted objects or actions. Naming performance can be influenced by several picture and verb characteristics which demands fully characterized normative data. In this study, we provide a first German normative data set of picture and verb characteristics associated with a compilation of 283 freely available action pictures and 600 action verbs including naming latencies from 55 participants. We report standard measures for pictures and verbs such as name agreement indices, visual complexity, word frequency, word length, imageability and age of acquisition. In addition, we include less common parameters, such as orthographic Levenshtein distance, transitivity, reflexivity, morphological complexity, and motor content of the pictures and their associated verbs. We use repeated measures correlations in order to investigate associations between picture and word characteristics and linear mixed effects modeling for the prediction of naming latency. Our analyses reveal comparable results to previous studies in other languages, indicating high construct validity. We found that naming latency varied as a function of entropy of responses, word frequency and motor content of pictures and words. In summary, we provide first German normative data for action pictures and their associated verbs and identify variables influencing naming latency.

Proceedings of the 10th annual deep brain stimulation think tank: Advances in cutting edge technologies, artificial intelligence, neuromodulation, neuroethics, interventional psychiatry, and women in neuromodulation.

The deep brain stimulation (DBS) Think Tank X was held on August 17-19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation. Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging DBS technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the "trough of disillusionment." DBS for depression was considered as "re-emerging" and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS.

An engram of intentionally forgotten information.

Successful forgetting of unwanted memories is crucial for goal-directed behavior and mental wellbeing. While memory retention strengthens memory traces, it is unclear what happens to memory traces of events that are actively forgotten. Using intracranial EEG recordings from lateral temporal cortex, we find that memory traces for actively forgotten information are partially preserved and exhibit unique neural signatures. Memory traces of successfully remembered items show stronger encoding-retrieval similarity in gamma frequency patterns. By contrast, encoding-retrieval similarity of item-specific memory traces of actively forgotten items depend on activity at alpha/beta frequencies commonly associated with functional inhibition. Additional analyses revealed selective modification of item-specific patterns of connectivity and top-down information flow from dorsolateral prefrontal cortex to lateral temporal cortex in memory traces of intentionally forgotten items. These results suggest that intentional forgetting relies more on inhibitory top-down connections than intentional remembering, resulting in inhibitory memory traces with unique neural signatures and representational formats.

Increased prefrontal top-down control in older adults predicts motor performance and age-group association.

Bimanual motor control declines during ageing, affecting the ability of older adults to maintain independence. An important underlying factor is cortical atrophy, particularly affecting frontal and parietal areas in older adults. As these regions and their interplay are highly involved in bimanual motor preparation, we investigated age-related connectivity changes between prefrontal and premotor areas of young and older adults during the preparatory phase of complex bimanual movements using high-density electroencephalography. Generative modelling showed that excitatory inter-hemispheric prefrontal to premotor coupling in older adults predicted age-group affiliation and was associated with poor motor-performance. In contrast, excitatory intra-hemispheric prefrontal to premotor coupling enabled older adults to maintain motor-performance at the cost of lower movement speed. Our results disentangle the complex interplay in the prefrontal-premotor network during movement preparation underlying reduced bimanual control and the well-known speed-accuracy trade-off seen in older adults.

Trust your gut: vagal nerve stimulation in humans improves reinforcement learning.

Whereas the effect of vagal nerve stimulation on emotional states is well established, its effect on cognitive functions is still unclear. Recent rodent studies show that vagal activation enhances reinforcement learning and neuronal dopamine release. The influence of vagal nerve stimulation on reinforcement learning in humans is still unknown. Here, we studied the effect of transcutaneous vagal nerve stimulation on reinforcement learning in eight long-standing seizure-free epilepsy patients, using a well-established forced-choice reward-based paradigm in a cross-sectional, within-subject study design. We investigated vagal nerve stimulation effects on overall accuracy using non-parametric cluster-based permutation tests. Furthermore, we modelled sub-components of the decision process using drift-diffusion modelling. We found higher accuracies in the vagal nerve stimulation condition compared to sham stimulation. Modelling suggests a stimulation-dependent increase in reward sensitivity and shift of accuracy-speed trade-offs towards maximizing rewards. Moreover, vagal nerve stimulation was associated with increased non-decision times suggesting enhanced sensory or attentional processes. No differences of starting bias were detected for both conditions. Accuracies in the extinction phase were higher in later trials of the vagal nerve stimulation condition, suggesting a perseverative effect compared to sham. Together, our results provide first evidence of causal vagal influence on human reinforcement learning and might have clinical implications for the usage of vagal stimulation in learning deficiency.

Schizotypy in Parkinson's disease predicts dopamine-associated psychosis.

Psychosis is the most common neuropsychiatric side-effect of dopaminergic therapy in Parkinson's disease (PD). It is still unknown which factors determine individual proneness to psychotic symptoms. Schizotypy is a multifaceted personality trait related to psychosis-proneness and dopaminergic neurotransmission in healthy subjects. We investigated whether (1) PD patients exhibit lower schizotypy than controls and (2) dopamine-related neuropsychiatric side-effects can be predicted by higher schizotypy. In this cross-sectional study, we used the Oxford-Liverpool Inventory of Feelings and Experiences in 56 PD patients (12 women, mean ± sd age: 61 ± 11 years) receiving their usual dopaminergic medication and 32 age-matched healthy controls (n = 32; 18 women, mean ± sd age: 57 ± 6 years). We further compared schizotypy scores of patients with (n = 18, 32.1%) and without previously experienced psychosis. We found that patients exhibited lower schizotypy than controls. Further, patients with a history of psychosis exhibited higher schizotypy than patients without these symptoms. Using an information theoretic measure and a machine learning approach, we show that schizotypy yields the greatest predictive value for dopamine-associated hallucinations compared to other patient characteristics and disease related factors. Our results indicate an overlap between neural networks associated with schizotypy and the pathophysiology of PD and a relationship between schizotypy and psychotic side-effects of dopaminergic medication.

Probabilistic sweet spots predict motor outcome for deep brain stimulation in Parkinson disease.

OBJECTIVE: To investigate whether functional sweet spots of deep brain stimulation (DBS) in the subthalamic nucleus (STN) can predict motor improvement in Parkinson disease (PD) patients. METHODS: Stimulation effects of 449 DBS settings in 21 PD patients were clinically and quantitatively assessed through standardized monopolar reviews and mapped into standard space. A sweet spot for best motor outcome was determined using voxelwise and nonparametric permutation statistics. Two independent cohorts were used to investigate whether stimulation overlap with the sweet spot could predict acute motor outcome (10 patients, 163 settings) and long-term overall Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) improvement (63 patients). RESULTS: Significant clusters for suppression of rigidity and akinesia, as well as for overall motor improvement, resided around the dorsolateral border of the STN. Overlap of the volume of tissue activated with the sweet spot for overall motor improvement explained R2 = 37% of the variance in acute motor improvement, more than triple what was explained by overlap with the STN (R2 = 9%) and its sensorimotor subpart (R2 = 10%). In the second independent cohort, sweet spot overlap explained R2 = 20% of the variance in long-term UPDRS-III improvement, which was equivalent to the variance explained by overlap with the STN (R2 = 21%) and sensorimotor STN (R2 = 19%). INTERPRETATION: This study is the first to predict clinical improvement of parkinsonian motor symptoms across cohorts based on local DBS effects only. The new approach revealed a distinct sweet spot for STN DBS in PD. Stimulation overlap with the sweet spot can predict short- and long-term motor outcome and may be used to guide DBS programming. ANN NEUROL 2019;86:527-538.

Implementation of Intraoperative Computed Tomography for Deep Brain Stimulation: Pitfalls and Optimization of Workflow, Accuracy, and Radiation Exposure.

OBJECTIVE: Deep brain stimulation (DBS) is an effective treatment for movement disorders. Stereotactic electrode placement can be guided by intraoperative imaging, which also allows for immediate intraoperative quality control. This article is about implementation and refining a workflow applying intraoperative computed tomography (iCT) for DBS. METHODS: Eighteen patients underwent DBS with bilateral implantation of directional electrodes applying a 32-slice movable computed tomography scanner in combination with microelectrode recording. RESULTS: iCT led to a significant decrease in overall procedural time, despite performing multiple scans. In 3 of the initial 5 cases, iCT caused an adjustment of the final electrodes demonstrating the learning curve and the necessity to integrate road mapping for the exchange of microelectrode to final electrode. Implementation of low-dose computed tomography protocols added microelectrode iCT to the refined workflow, resulting in an intraoperative adjustment of a trajectory in 1 patient. Low-dose protocols lowered the total effective dose to 1.15 mSv, that is, a reduction by a factor of 3.5 compared to a standard non-iCT DBS procedure, despite repeated iCTs. Intraoperative lead detection based on final iCT revealed a radial error of 1.04 ± 0.58 mm and a vector error of 2.28 ± 0.97 mm compared to the preoperative planning, adjusted by the findings of microelectrode recording. CONCLUSIONS: iCT can be easily integrated into the surgical workflow resulting in an overall efficient time-saving procedure. Repeated intraoperative scanning ensures reliable electrode placement, although low-dose scanning protocols prevent extensive radiation exposure. iCT of microelectrodes is feasible and led to the adjustment of 1 electrode.

Direct Electrophysiological Evidence for Prefrontal Control of Hippocampal Processing during Voluntary Forgetting.

Forgetting does not necessarily reflect failure to encode information but can, to some extent, also be voluntarily controlled. Previous studies have suggested that voluntary forgetting relies on active inhibition of encoding processes in the hippocampus by the dorsolateral prefrontal cortex (DLPFC) [1-4]. During attentional and sensorimotor processing, enhanced DLPFC theta power alongside increased alpha/beta oscillations are a neural signature of an inhibitory top-down mechanism, with theta oscillations reflecting prefrontal control and alpha/beta oscillations occurring in areas targeted by inhibition [5-12]. Here, we used intracranial EEG recordings in presurgical epilepsy patients implanted in DLPFC (n = 13) and hippocampus (n = 15) during an item-method directed forgetting paradigm. We found that voluntary forgetting is associated with increased neural oscillations in the low theta band (3-5 Hz) in DLPFC and in a broad theta/alpha/beta (6-18 Hz) frequency range in hippocampus. Combining time-lagged correlation analysis, phase synchronization, and Granger causality in 6 patients with electrodes in both DLPFC and hippocampus, we obtained converging evidence for a top-down control of hippocampal activity by the DLPFC. Together, our results provide strong support for a model in which voluntary forgetting relies on enhanced inhibition of the hippocampus by the DLPFC.

Human Hippocampal Dynamics during Response Conflict.

Besides its relevance for declarative memory functions, hippocampal activation has been observed during disambiguation of uncertainty and conflict. Uncertainty and conflict may arise on various levels. On the perceptual level, the hippocampus has been associated with signaling of contextual deviance and disambiguation of similar items (i.e., pattern separation). Furthermore, conflicts can occur on the response level. Animal experiments showed a role of the hippocampus for inhibition of prevailing response tendencies and suppression of automatic stimulus-response mappings, potentially related to increased theta oscillations (3-8 Hz). In humans, a recent fMRI study demonstrated hippocampal involvement in approach-avoidance conflicts. However, the more general significance of hippocampal activity for dealing with response conflicts also on a cognitive level is still unknown. Here, we investigated the role of the hippocampus for response conflict in the Stroop task by combining intracranial electroencephalography (iEEG) recordings from the hippocampus of epilepsy patients with region of interest-based fMRI in healthy participants. Both methods revealed converging evidence that the hippocampus is recruited in a regionally specific manner during response conflict. Moreover, our iEEG data show that this activation depends on theta oscillations and is relevant for successful response conflict resolution.