Persistent activity during working memory maintenance predicts long-term memory formation in the human hippocampus.

Working Memory (WM) and Long-Term Memory (LTM) are often viewed as separate cognitive systems. Little is known about how these systems interact when forming memories. We recorded single neurons in the human medial temporal lobe while patients maintained novel items in WM and a subsequent recognition memory test for the same items. In the hippocampus but not the amygdala, the level of WM content-selective persist activity during WM maintenance was predictive of whether the item was later recognized with high confidence or forgotten. In contrast, visually evoked activity in the same cells was not predictive of LTM formation. During LTM retrieval, memory-selective neurons responded more strongly to familiar stimuli for which persistent activity was high while they were maintained in WM. Our study suggests that hippocampal persistent activity of the same cell supports both WM maintenance and LTM encoding, thereby revealing a common single-neuron component of these two memory systems.

Characterizing the safety profile of vagus nerve stimulation devices for epilepsy from 21,448 manufacturer and user reports.

OBJECTIVE: This study summarizes medical device reports (MDRs) associated with adverse events for vagus nerve stimulation (VNS) devices indicated for epilepsy as reported by the Manufacturer and User Facility Device Experience (MAUDE) database of the US Food and Drug Administration. METHODS: The MAUDE database was surveyed for MDRs from November 2013 to September 2022 regarding VNS devices for epilepsy. Event descriptions, device problems, correlated patient consequences, and device models were grouped and analyzed in Python. Based on event description, revision surgeries and other unique events were identified. Revenue from VNS device sales was used to approximate growth in their use over time. RESULTS: A total of 21,448 MDRs met the inclusion criteria. High VNS impedance, the most prevalent device malfunction overall (17.0% of MDRs), was the most common factor for 18 of the 102 encountered patient problems and led to 1001 revision surgeries (3371 total revisions). Included in those 18 device malfunctions were 3 of the top 6 occurring patient problems: seizure recurrence (9.9% associated with high impedance; encompassed focal, absence, and grand mal subtypes), death (1.3%), and generalized pain (7.9%). The next 4 top cited device malfunctions-lead fracture (13.7% of MDRs), operational issue (6.6%), battery problem holding charge (4.2%), and premature end-of-life indicator (2.9%)-differed widely in their percentage of cases that did not impact patients (77.4%, 57.3%, 48.9%, and 92.2%, respectively), highlighting differing malfunction severities. Seizure recurrence, the most prevalent patient impact, was the outcome most associated with 32 of the 68 encountered device problems, including high impedance (12.8%), lead fracture (12.2%), operational issue (18.4%), battery problem holding charge (31.2%), and premature end-of-life indicator (8.9%), which comprised the top 5 occurring device problems. In general, MDRs spanned a diverse range including device age, hardware, software, and surgeon or manufacturer error. Trends were seen over time with declining annual MDRs coupled with a rise in the use of VNS devices as gauged by revenue growth. Shifting device and patient problem profiles were also seen in successive models, reflecting engineering updates. CONCLUSIONS: This study characterizes the most common and consequential side effects of VNS devices for epilepsy while clarifying likely causes. In addition, the outcomes of 68 distinct device malfunctions were identified, including many not ubiquitously present in literature, lending critical perspective to clinical practice.

Online speech synthesis using a chronically implanted brain-computer interface in an individual with ALS.

Brain-computer interfaces (BCIs) that reconstruct and synthesize speech using brain activity recorded with intracranial electrodes may pave the way toward novel communication interfaces for people who have lost their ability to speak, or who are at high risk of losing this ability, due to neurological disorders. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a man with impaired articulation due to ALS, participating in a clinical trial (ClinicalTrials.gov, NCT03567213) exploring different strategies for BCI communication. The 3-stage approach reported here relies on recurrent neural networks to identify, decode and synthesize speech from electrocorticographic (ECoG) signals acquired across motor, premotor and somatosensory cortices. We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the participant from a vocabulary of 6 keywords previously used for decoding commands to control a communication board. Evaluation of the intelligibility of the synthesized speech indicates that 80% of the words can be correctly recognized by human listeners. Our results show that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words while preserving the participant's voice profile, and provide further evidence for the stability of ECoG for speech-based BCIs.

Phase-amplitude coupling detection and analysis of human 2-dimensional neural cultures in multi-well microelectrode array in vitro.

BACKGROUND: Human induced pluripotent stem cell (hiPSC)- derived neurons offer the possibility of studying human-specific neuronal behaviors in physiologic and pathologic states in vitro. It is unclear whether cultured neurons can achieve the fundamental network behaviors required to process information in the brain. Investigating neuronal oscillations and their interactions, as occurs in cross-frequency coupling (CFC), addresses this question. NEW METHODS: We examined whether networks of two-dimensional (2D) cultured hiPSC-derived cortical neurons grown with hiPSC-derived astrocytes on microelectrode array plates recapitulate the CFC that is present in vivo. We employed the modulation index method for detecting phase-amplitude coupling (PAC) and used offline spike sorting to analyze the contribution of single neuron spiking to network behavior. RESULTS: We found that PAC is present, the degree of PAC is specific to network structure, and it is modulated by external stimulation with bicuculline administration. Modulation of PAC is not driven by single neurons, but by network-level interactions. COMPARISON WITH EXISTING METHODS: PAC has been demonstrated in multiple regions of the human cortex as well as in organoids. This is the first report of analysis demonstrating the presence of coupling in 2D cultures. CONCLUSION: CFC in the form of PAC analysis explores communication and integration between groups of neurons and dynamical changes across networks. In vitro PAC analysis has the potential to elucidate the underlying mechanisms as well as capture the effects of chemical, electrical, or ultrasound stimulation; providing insight into modulation of neural networks to treat nervous system disorders in vivo.

Control of working memory by phase-amplitude coupling of human hippocampal neurons.

Retaining information in working memory is a demanding process that relies on cognitive control to protect memoranda-specific persistent activity from interference1,2. However, how cognitive control regulates working memory storage is unclear. Here we show that interactions of frontal control and hippocampal persistent activity are coordinated by theta-gamma phase-amplitude coupling (TG-PAC). We recorded single neurons in the human medial temporal and frontal lobe while patients maintained multiple items in their working memory. In the hippocampus, TG-PAC was indicative of working memory load and quality. We identified cells that selectively spiked during nonlinear interactions of theta phase and gamma amplitude. The spike timing of these PAC neurons was coordinated with frontal theta activity when cognitive control demand was high. By introducing noise correlations with persistently active neurons in the hippocampus, PAC neurons shaped the geometry of the population code. This led to higher-fidelity representations of working memory content that were associated with improved behaviour. Our results support a multicomponent architecture of working memory1,2, with frontal control managing maintenance of working memory content in storage-related areas3-5. Within this framework, hippocampal TG-PAC integrates cognitive control and working memory storage across brain areas, thereby suggesting a potential mechanism for top-down control over sensory-driven processes.

Risk of Subdural Hematoma Expansion in Patients With End-Stage Renal Disease: Continuous Venovenous Hemodialysis Versus Intermittent Hemodialysis.

BACKGROUND AND OBJECTIVES: Subdural hematoma (SDH) patients with end-stage renal disease (ESRD) require renal replacement therapy in addition to neurological management. We sought to determine whether continuous venovenous hemodialysis (CVVHD) or intermittent hemodialysis (iHD) is associated with higher rates of SDH re-expansion as well as morbidity and mortality. METHODS: Hemodialysis-dependent patients with ESRD who were discovered to have an SDH were retrospectively identified from 2016 to 2022. Rates of SDH expansion during CVVHD vs iHD were compared. Hemodialysis mode was included in a multivariate logistic regression model to test for independent association with SDH expansion and mortality. RESULTS: A total of 123 hemodialysis-dependent patients with ESRD were discovered to have a concomitant SDH during the period of study. Patients who received CVVHD were on average 10.2 years younger ( P < .001), more likely to have traumatic SDH (47.7% vs 19.0%, P < .001), and more likely to have cirrhosis (25.0% vs 10.1%, P = .029). SDH expansion affecting neurological function occurred more frequently during iHD compared with CVVHD (29.7% vs 12.0%, P = .013). Multivariate logistic regression analysis found that CVVHD was independently associated with decreased risk of SDH affecting neurological function (odds ratio 0.25, 95% CI 0.08-0.65). Among patients who experienced in-hospital mortality or were discharged to hospice, 5% suffered a neurologically devastating SDH expansion while on CVVHD compared with 35% on iHD. CONCLUSION: CVVHD was independently associated with decreased risk of neurologically significant SDH expansion. Therefore, receiving renal replacement therapy through a course of CVVHD may increase SDH stability in patients with ESRD.

WarpDrive: Improving spatial normalization using manual refinements.

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Anatomical substrates and connectivity for bradykinesia motor features in Parkinson's disease after subthalamic nucleus deep brain stimulation.

Parkinsonian bradykinesia is rated using a composite scale incorporating the slowed frequency of repetitive movements, decrement amplitude and arrhythmicity. Differential localization of these movement components within the basal ganglia will drive the development of more personalized network-targeted symptomatic therapies. In this study, using an optical motion sensor, we evaluated the amplitude and frequency of hand movements during a grasping task with subthalamic nucleus deep brain stimulation 'on' or 'off' in 15 patients with Parkinson's disease. The severity of bradykinesia was assessed blindly using the Unified Parkinson's Disease Rating Part III scale. The volumes of activated tissue of each subject were estimated where changes in amplitude and frequency were mapped to identify distinct anatomical substrates of each component in the subthalamic nucleus. The volumes of activated tissue were used to seed a normative functional connectome to generate connectivity maps associated with amplitude and frequency changes. Deep brain stimulation-induced change in amplitude was negatively correlated with a change in Unified Parkinson's Disease Rating Part III scale for right (r = -0.65, P < 0.05) and left hand grasping scores (r = -0.63, P < 0.05). The change in frequency was negatively correlated with amplitude for both right (r = -0.63, P < 0.05) and left hands (r = -0.57, P < 0.05). The amplitude and frequency changes were represented as a spatial gradient with overlapping and non-overlapping regions spanning the anteromedial-posterolateral axis of the subthalamic nucleus. Whole-brain correlation maps between functional connectivity and motor changes were also inverted between amplitude and frequency changes. Deep brain stimulation-associated changes in frequency and amplitude were topographically and distinctly represented both locally in the subthalamic nucleus and in whole-brain functional connectivity.

Stable Decoding from a Speech BCI Enables Control for an Individual with ALS without Recalibration for 3 Months.

Brain-computer interfaces (BCIs) can be used to control assistive devices by patients with neurological disorders like amyotrophic lateral sclerosis (ALS) that limit speech and movement. For assistive control, it is desirable for BCI systems to be accurate and reliable, preferably with minimal setup time. In this study, a participant with severe dysarthria due to ALS operates computer applications with six intuitive speech commands via a chronic electrocorticographic (ECoG) implant over the ventral sensorimotor cortex. Speech commands are accurately detected and decoded (median accuracy: 90.59%) throughout a 3-month study period without model retraining or recalibration. Use of the BCI does not require exogenous timing cues, enabling the participant to issue self-paced commands at will. These results demonstrate that a chronically implanted ECoG-based speech BCI can reliably control assistive devices over long time periods with only initial model training and calibration, supporting the feasibility of unassisted home use.

Online speech synthesis using a chronically implanted brain-computer interface in an individual with ALS.

Recent studies have shown that speech can be reconstructed and synthesized using only brain activity recorded with intracranial electrodes, but until now this has only been done using retrospective analyses of recordings from able-bodied patients temporarily implanted with electrodes for epilepsy surgery. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a clinical trial participant (ClinicalTrials.gov, NCT03567213) with dysarthria due to amyotrophic lateral sclerosis (ALS). We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the user from a vocabulary of 6 keywords originally designed to allow intuitive selection of items on a communication board. Our results show for the first time that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words that are intelligible to human listeners while preserving the participants voice profile.

Phase-Amplitude Coupling Detection and Analysis of Human 2-Dimensional Neural Cultures in Multi-well Microelectrode Array in Vitro.

Human induced pluripotent stem cell (hiPSC) - derived neurons offer the possibility of studying human-specific neuronal behaviors in physiologic and pathologic states in vitro . However, it is unclear whether these cultured neurons can achieve the fundamental network behaviors that are required to process information in the human brain. Investigating neuronal oscillations and their interactions, as occurs in cross-frequency coupling (CFC), is potentially a relevant approach. Microelectrode array culture plates provide a controlled framework to study populations of hiPSC-derived cortical neurons (hiPSC-CNs) and their electrical activity. Here, we examined whether networks of two-dimensional cultured hiPSC-CNs recapitulate the CFC that is present in networks in vivo . We analyzed the electrical activity recorded from hiPSC-CNs grown in culture with hiPSC-derived astrocytes. We employed the modulation index method for detecting phase-amplitude coupling (PAC) and used an offline spike sorting method to analyze the contribution of a single neuron's spiking activities to network behavior. Our analysis demonstrates that the degree of PAC is specific to network structure and is modulated by external stimulation, such as bicuculine administration. Additionally, the shift in PAC is not driven by a single neuron's properties but by network-level interactions. CFC analysis in the form of PAC explores communication and integration between groups of nearby neurons and dynamical changes across the entire network. In vitro , it has the potential to capture the effects of chemical agents and electrical or ultrasound stimulation on these interactions and may provide valuable information for the modulation of neural networks to treat nervous system disorders in vivo . Significance: Phase amplitude coupling (PAC) analysis demonstrates that the complex interactions that occur between neurons and network oscillations in the human brain, in vivo , are present in 2-dimensional human cultures. This coupling is implicated in normal cognitive function as well as disease states. Its presence in vitro suggests that PAC is a fundamental property of neural networks. These findings offer the possibility of a model to understand the mechanisms and of PAC more completely and ultimately allow us to understand how it can be modulated in vivo to treat neurologic disease.

Postsurgical morbidity and mortality favorably informs deep brain stimulation for new indications including schizophrenia and schizoaffective disorder.

Background: Deep brain stimulation (DBS) shows promise for new indications like treatment-refractory schizophrenia in early clinical trials. In the first DBS clinical trial for treatment refractory schizophrenia, despite promising results in treating psychosis, one of the eight subjects experienced both a symptomatic hemorrhage and an infection requiring device removal. Now, ethical concerns about higher surgical risk in schizophrenia/schizoaffective disorder (SZ/SAD) are impacting clinical trial progress. However, insufficient cases preclude conclusions regarding DBS risk in SZ/SAD. Therefore, we directly compare adverse surgical outcomes for all surgical procedures between SZ/SAD and Parkinson's disease (PD) cases to infer relative surgical risk relevant to gauging DBS risks in subjects with SZ/SAD. Design: In the primary analysis, we used browser-based statistical analysis software, TriNetX Live (trinetx.com TriNetX LLC, Cambridge, MA), for Measures of Association using the Z-test. Postsurgical morbidity and mortality after matching for ethnicity, over 39 risk factors, and 19 CPT 1003143 coded surgical procedures from over 35,000 electronic medical records, over 19 years, from 48 United States health care organizations (HCOs) through the TriNetX Research Network™. TriNetXis a global, federated, web-based health research network providing access and statistical analysis of aggregate counts of deidentified EMR data. Diagnoses were based on ICD-10 codes. In the final analysis, logistic regression was used to determine relative frequencies of outcomes among 21 diagnostic groups/cohorts being treated with or considered for DBS and 3 control cohorts. Results: Postsurgical mortality was 1.01-4.11% lower in SZ/SAD compared to the matched PD cohort at 1 month and 1 year after any surgery, while morbidity was 1.91-2.73% higher and associated with postsurgical noncompliance with medical treatment. Hemorrhages and infections were not increased. Across the 21 cohorts compared, PD and SZ/SAD were among eight cohorts with fewer surgeries, nine cohorts with higher postsurgical morbidity, and fifteen cohorts within the control-group range for 1-month postsurgical mortality. Conclusions: Given that the subjects with SZ or SAD, along with most other diagnostic groups examined, had lower postsurgical mortality than PD subjects, it is reasonable to apply existing ethical and clinical guidelines to identify appropriate surgical candidates for inclusion of these patient populations in DBS clinical trials.

Use of the Globus ExcelsiusGPS System for Robotic Stereoelectroencephalography: An Initial Experience.

BACKGROUND: Stereoelectroencephalography (SEEG) is a critical tool used in the identification of epileptogenic zones. Although stereotactic frame-based SEEG procedures have been performed traditionally, newer robotic-assisted SEEG procedures have become increasingly common. In this study, we evaluate the accuracy, efficacy of the ExcelsiusGPS robot (Globus Medica, Audubon, PA) in SEEG procedures. METHODS: Five consecutive adult patients with drug resistant epilepsy were identified as SEEG candidates via a multidisciplinary epilepsy surgery committee. Preoperative scans were merged onto the robot to plan electrode placement. With the use of a camera system, dynamic reference base, and surveillance markers, the robotic arm was used to establish the trajectory of the electrodes. Postoperative computed tomography (CT) scans were merged onto the preoperatively planned trajectory and the radial, depth, and entry errors were calculated. Fiducial registration error was calculated for 4 cases to determine error between the patient and intraoperative CT merge. RESULTS: A total of 59 electrodes were placed. The mean age at surgery was 41.6 ± 15.1 years. Mean operating room time, anesthesia time, and surgical time was 301.6 ± 44.4 min, 261.6 ± 50.2 min, and 155.8 ± 48.8 min, respectively. The overall mean depth, radial, and entry errors were 2.5 ± 1.9 mm, 1.9 ± 1.5 mm, and 1.6 ± 1.2 mm. Mean fiducial registration error retrospectively calculated for 4 of 5 cases was 0.13 ± 0.04 mm. There were no perioperative complications. CONCLUSIONS: The initial performance of the ExcelsiusGPS robotic system yielded comparable results to other systems currently in use for adult SEEG procedures.

Customized External Cranioplasty for Management of Syndrome of Trephined in Nonsurgical Candidates.

BACKGROUND: Craniectomies represent a lifesaving neurosurgical procedure for many severe neurological conditions, such as traumatic brain injury. Syndrome of trephined (SoT) is an important complication of decompressive craniectomy, and cranial reconstruction is the definitive treatment. However, many patients cannot undergo surgical intervention because of neurological status, healing of the primary surgical wound, or the presence of concurrent infection, which may prevent cranioplasty. OBJECTIVE: To offer a customized external cranioplasty option for managing skull deformities for patients who could not undergo surgical intervention for definitive cranioplasty. METHODS: We describe the design and clinical application of an external cranioplasty for a patient with a medical history of intractable epilepsy, for which she underwent multiple right cerebral resections with a large resultant skull defect and SoT. RESULTS: The patient had resolution of symptoms and restoration of a symmetrical skull contour with no complication at 17 months. CONCLUSION: Customized external cranioplasty can improve symptoms associated with SoT for patients who cannot undergo a definitive cranioplasty. In addition, inset monitoring options, such as electroencephalography or telemetric intracranial pressure sensors, could be incorporated in the future for comprehensive monitoring of the patient's neurological condition.

Combining physics-based models with deep learning image synthesis and uncertainty in intraoperative cone-beam CT of the brain.

BACKGROUND: Image-guided neurosurgery requires high localization and registration accuracy to enable effective treatment and avoid complications. However, accurate neuronavigation based on preoperative magnetic resonance (MR) or computed tomography (CT) images is challenged by brain deformation occurring during the surgical intervention. PURPOSE: To facilitate intraoperative visualization of brain tissues and deformable registration with preoperative images, a 3D deep learning (DL) reconstruction framework (termed DL-Recon) was proposed for improved intraoperative cone-beam CT (CBCT) image quality. METHODS: The DL-Recon framework combines physics-based models with deep learning CT synthesis and leverages uncertainty information to promote robustness to unseen features. A 3D generative adversarial network (GAN) with a conditional loss function modulated by aleatoric uncertainty was developed for CBCT-to-CT synthesis. Epistemic uncertainty of the synthesis model was estimated via Monte Carlo (MC) dropout. Using spatially varying weights derived from epistemic uncertainty, the DL-Recon image combines the synthetic CT with an artifact-corrected filtered back-projection (FBP) reconstruction. In regions of high epistemic uncertainty, DL-Recon includes greater contribution from the FBP image. Twenty paired real CT and simulated CBCT images of the head were used for network training and validation, and experiments evaluated the performance of DL-Recon on CBCT images containing simulated and real brain lesions not present in the training data. Performance among learning- and physics-based methods was quantified in terms of structural similarity (SSIM) of the resulting image to diagnostic CT and Dice similarity metric (DSC) in lesion segmentation compared to ground truth. A pilot study was conducted involving seven subjects with CBCT images acquired during neurosurgery to assess the feasibility of DL-Recon in clinical data. RESULTS: CBCT images reconstructed via FBP with physics-based corrections exhibited the usual challenges to soft-tissue contrast resolution due to image non-uniformity, noise, and residual artifacts. GAN synthesis improved image uniformity and soft-tissue visibility but was subject to error in the shape and contrast of simulated lesions that were unseen in training. Incorporation of aleatoric uncertainty in synthesis loss improved estimation of epistemic uncertainty, with variable brain structures and unseen lesions exhibiting higher epistemic uncertainty. The DL-Recon approach mitigated synthesis errors while maintaining improvement in image quality, yielding 15%-22% increase in SSIM (image appearance compared to diagnostic CT) and up to 25% increase in DSC in lesion segmentation compared to FBP. Clear gains in visual image quality were also observed in real brain lesions and in clinical CBCT images. CONCLUSIONS: DL-Recon leveraged uncertainty estimation to combine the strengths of DL and physics-based reconstruction and demonstrated substantial improvements in the accuracy and quality of intraoperative CBCT. The improved soft-tissue contrast resolution could facilitate visualization of brain structures and support deformable registration with preoperative images, further extending the utility of intraoperative CBCT in image-guided neurosurgery.

Anatomical Substrates and Connectivity for Parkinson's Disease Bradykinesia Components after STN-DBS.

Background: Parkinsonian bradykinesia is rated using a composite scale incorporating slowed frequency of repetitive movements, decrement amplitude, and arrhythmicity. Differential localization of these movement components within basal ganglia would drive the development of more personalized network-targeted symptomatic therapies. Methods: Using an optical motion sensor, amplitude and frequency of hand movements during grasping task were evaluated with subthalamic nucleus (STN)-Deep Brain Stimulation (DBS) "on" or "off" in 15 patients with Parkinson's disease (PD). The severity of bradykinesia was assessed blindly using the MDS-UPDRS Part-III scale. Volumes of activated tissue (VAT) of each subject were estimated where changes in amplitude and frequency were mapped to identify distinct anatomical substrates of each component in the STN. VATs were used to seed a normative functional connectome to generate connectivity maps associated with amplitude and frequency changes. Results: STN-DBS-induced change in amplitude was negatively correlated with change in MDS-UPDRS-III right (r = -0.65, p < 0.05) and left hand grasping scores (r = -0.63, p < 0.05). The change in frequency was negatively correlated with amplitude for both right (r = -0.63, p < 0.05) and left hand (r = -0.57, p < 0.05). The amplitude and frequency changes were represented as a spatial gradient with overlapping and non-overlapping regions spanning the dorsolateral-ventromedial axis of the STN. Whole-brain correlation maps between functional connectivity and motor changes were also inverted between amplitude and frequency changes. Conclusion: DBS-associated changes in frequency and amplitude were topographically and distinctly represented both locally in STN and in whole-brain functional connectivity.

Cross-task specificity and within-task invariance of cognitive control processes.

Cognitive control involves flexibly combining multiple sensory inputs with task-dependent goals during decision making. Several tasks involving conflicting sensory inputs and motor outputs have been proposed to examine cognitive control, including the Stroop, Flanker, and multi-source interference task. Because these tasks have been studied independently, it remains unclear whether the neural signatures of cognitive control reflect abstract control mechanisms or specific combinations of sensory and behavioral aspects of each task. To address these questions, we record invasive neurophysiological signals from 16 patients with pharmacologically intractable epilepsy and compare neural responses within and between tasks. Neural signals differ between incongruent and congruent conditions, showing strong modulation by conflicting task demands. These neural signals are mostly specific to each task, generalizing within a task but not across tasks. These results highlight the complex interplay between sensory inputs, motor outputs, and task demands underlying cognitive control processes.

Ablation of apparent diffusion coefficient hyperintensity clusters in mesial temporal lobe epilepsy improves seizure outcomes after laser interstitial thermal therapy.

OBJECTIVE: Laser interstitial thermal therapy (LiTT) is a minimally invasive surgical procedure for intractable mesial temporal epilepsy (mTLE). LiTT is safe and effective, but seizure outcomes are highly variable due to patient variability, suboptimal targeting, and incomplete ablation of the epileptogenic zone. Apparent diffusion coefficient (ADC) is a magnetic resonance imaging (MRI) sequence that can identify potential epileptogenic foci in the mesial temporal lobe to improve ablation and seizure outcomes. The objective of this study was to investigate whether ablation of tissue clusters with high ADC values in the mesial temporal structures is associated with seizure outcome in mTLE after LiTT. METHODS: Twenty-seven patients with mTLE who underwent LiTT at our institution were analyzed. One-year seizure outcome was categorized as complete seizure freedom (International League Against Epilepsy [ILAE] Class I) and residual seizures (ILAE Class II-VI). Volumes of hippocampus and amygdala were segmented from the preoperative T1 MRI sequence. Spatially distinct hyperintensity clusters were identified in the preoperative ADC map. Proportion of cluster volume and number ablated were associated with seizure outcomes. RESULTS: The mean age at surgery was 37.5 years and the mean follow-up duration was 1.9 years. Proportions of hippocampal cluster volume (p = .013) and number (p = .03) ablated were significantly higher in patients with seizure freedom. For amygdala clusters, the proportion of cluster number ablated was significantly associated with seizure outcome (p = .026). In the combined amygdalohippocampal complex, ablation of amygdalohippocampal clusters reliably predicted seizure outcome by their volume ablated (area under the curve [AUC] = 0.7670, p = .02). SIGNIFICANCE: Seizure outcome after LiTT in patients with mTLE was associated significantly with the extent of cluster ablation in the amygdalohippocampal complex. The results suggest that preoperative ADC analysis may help identify high-yield pathological tissue clusters that represent epileptogenic foci. ADC-based cluster analysis can potentially assist ablation targeting and improve seizure outcome after LiTT in mTLE.

Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer's disease.

Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer's Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others. This could be explained by variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we performed a post-hoc analysis on a multi-center cohort of 46 patients with DBS to the fornix (NCT00658125, NCT01608061). Using normative structural and functional connectivity data, we found that stimulation of the circuit of Papez and stria terminalis robustly associated with cognitive improvement (R = 0.53, p < 0.001). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.48, p < 0.001). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.48, p < 0.001). Findings were robust to multiple cross-validation designs and may define an optimal network target that could refine DBS surgery and programming.

Characteristics and stability of sensorimotor activity driven by isolated-muscle group activation in a human with tetraplegia.

Understanding the cortical representations of movements and their stability can shed light on improved brain-machine interface (BMI) approaches to decode these representations without frequent recalibration. Here, we characterize the spatial organization (somatotopy) and stability of the bilateral sensorimotor map of forearm muscles in an incomplete-high spinal-cord injury study participant implanted bilaterally in the primary motor and sensory cortices with Utah microelectrode arrays (MEAs). We built representation maps by recording bilateral multiunit activity (MUA) and surface electromyography (EMG) as the participant executed voluntary contractions of the extensor carpi radialis (ECR), and attempted motions in the flexor carpi radialis (FCR), which was paralytic. To assess stability, we repeatedly mapped and compared left- and right-wrist-extensor-related activity throughout several sessions, comparing somatotopy of active electrodes, as well as neural signals both at the within-electrode (multiunit) and cross-electrode (network) levels. Wrist motions showed significant activation in motor and sensory cortical electrodes. Within electrodes, firing strength stability diminished as the time increased between consecutive measurements (hours within a session, or days across sessions), with higher stability observed in sensory cortex than in motor, and in the contralateral hemisphere than in the ipsilateral. However, we observed no differences at network level, and no evidence of decoding instabilities for wrist EMG, either across timespans of hours or days, or across recording area. While map stability differs between brain area and hemisphere at multiunit/electrode level, these differences are nullified at ensemble level.