International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering最新文献

{"title":"A Low-Cost, Open-Source Wireless Platform for Real-Time Tremor Monitoring in Parkinson's Disease.","authors":"Hossein Heydari, Ebubekir E Arslan, Jhan L Okkabaz, Luciano R F Branco, Matthew J Hall, Chandra Prakash Swamy, Bryan T Klassen, Rushna P Ali, Kai J Miller, Ashwin Viswanathan, Nuri F Ince","doi":"10.1109/ner61569.2025.11589100","DOIUrl":"https://doi.org/10.1109/ner61569.2025.11589100","url":null,"abstract":"<p><p>We present a low-cost, open-source, wireless hardware platform dedicated to real-time tremor monitoring in Parkinson's disease (PD). The system is built on the ESP32-C6 microcontroller integrated with a 3-axis accelerometer and tilt sensor and employs ESP-NOW for wireless communication and multi-device synchronization. It supports up to five synchronized accelerometer nodes for assessing tremor and postural changes at the upper and lower limbs, as well as the jaw or chest. In this study, we demonstrate its application for intraoperative tracking of resting tremor and voluntary hand movements during brain stimulation (DBS) surgery, synchronized with neural recordings, while providing real-time feedback to the clinical team. Benchmarking tests confirmed sub-25 ms latency and robust synchronization between accelerometer nodes, underscoring its potential as a reliable tool for objective, real-time tremor quantification in both surgical and postoperative settings.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2025 ","pages":"587-591"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13488414/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148802594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Spatial-Temporal Channel Reliability with AI for Robust High-Frequency Oscillation Detection in Intracranial EEG.","authors":"Behrang Fazli Besheli, Amir Hossein Ayyoubi, Chandra Prakash Swamy, Bobby Mohan, Kai J Miller, Jonathan J Parker, Gregory A Worrell, Nuri F Ince","doi":"10.1109/ner61569.2025.11588994","DOIUrl":"10.1109/ner61569.2025.11588994","url":null,"abstract":"<p><strong>Objective: </strong>Reliable detection of high-frequency oscillations (HFOs) in intracranial EEG (iEEG) is critical for localizing the seizure onset zone (SOZ). However, artifact contamination severely impairs detection specificity and contributes to false positives.</p><p><strong>Methods: </strong>We developed a reliability guided HFO analysis pipeline that targets artifact elimination through a multi-level strategy, including event level denoising, channel signal quality assessment, and segment level temporal reliability analysis. The classifier was trained on 22 subjects using manual annotations of reliable versus unreliable data and validated using leave-one-subject-out cross-validation (LOSO-CV).</p><p><strong>Results: </strong>The final pipeline was further applied to an additional cohort of 8 independent subjects to evaluate generalizability and clinical utility. SOZ localization accuracy based on HFOs retained after event-level denoising improved from 66% (baseline) to 82%, and further to 93% after applying channel and segment reliability filters. ROC analysis confirmed that reliability-based filtering enhanced separation between SOZ and non-SOZ channels, improving clinical specificity.</p><p><strong>Conclusion: </strong>Incorporating spatial and temporal contextual information, specifically by evaluating signal quality across neighboring channels and consistency across adjacent time windows, significantly enhances the ability to distinguish true HFOs from artifacts. This approach improves both the robustness and clinical accuracy of HFO-based SOZ localization.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2025 ","pages":"511-516"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148868209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corticomuscular Connectivity and Brain Reorganization Post-Stroke.","authors":"Mahmood Rajabtabar, Joohwan Sung, Beni Mulyana, Rita Huan-Ting Peng, Xiaoxi Chen, Bethany Marshall, Yuan Yang","doi":"10.1109/NER61569.2025.11589015","DOIUrl":"10.1109/NER61569.2025.11589015","url":null,"abstract":"<p><p>Stroke often causes damage to the motor descending pathways in the lesioned hemisphere, resulting in compensatory recruitment of contralesional motor resources. This proof-of-concept study examines how motor task demand affects brain-muscle communication in individuals with chronic stroke, which represents motor system remodeling after the injury. Coherence between EEG and deltoid EMG was estimated during an isometric shoulder abduction task, and hemisphere dominance was evaluated using a Laterality Index (LI) in five stroke survivors and five healthy controls during isometric shoulder abduction at 20% and 40% of maximal voluntary contraction. Compared to controls, stroke participants exhibited a significantly reduced beta-band corticomuscular connectivity (CMC) at the lesioned hemisphere, with enhanced contralesional CMC. This was accompanied by an increase in motor demand, which amplified contralesional cortical involvement and revealed a pronounced shift in the Laterality Index (LI) toward contralesional dominance. This shift is indicative of maladaptive neural reorganization and diminished reliance on the ipsilesional hemisphere. The potential of beta-band CMC and LI as sensitive neurophysiological biomarkers for evaluating motor impairment and guiding individualized neurorehabilitation strategies that account for cortical plasticity and load-dependent recruitment patterns in stroke recovery is underscored by these task-dependent alterations in coherence and hemispheric dominance.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2025 ","pages":"890-895"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13536468/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148882810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-Driven Hyperparameter Tuning of High-Frequency Oscillation Detection for Seizure-Onset Zone Localization.","authors":"Valentina Hrtonova, Martina Kolajova, Behrang Fazli Besheli, Amir Hossein Ayyoubi, Jhan L Okkabaz, Chandra Prakash Swamy, Kai J Miller, Gregory A Worrell, Nuri F Ince","doi":"10.1109/ner61569.2025.11588923","DOIUrl":"https://doi.org/10.1109/ner61569.2025.11588923","url":null,"abstract":"<p><p>High-frequency oscillations (HFOs) are promising biomarkers for localizing the seizure onset zone (SOZ) in drug-resistant epilepsy. Automatic HFO detectors often depend on specific parameter choices, limiting effectiveness across diverse datasets. This study optimizes a published amplitude-threshold-based detector using a data-driven approach on intracranial EEG recordings from 20 patients at four epilepsy centers. We use the Tree-structured Parzen Estimator (TPE) to efficiently search the parameter space, guided by a new objective function, the SOZ Detection Quality (SDQ) score, which balances SOZ localization precision with the number of detected events in the SOZ. In the training cohort, the optimized detector increased the proportion of detections in SOZ channels from 49% to 61% and improved AUROC from 0.78 to 0.89 while largely preserving the SOZ detection counts. Similar improvements were observed in the test cohort, where detections in SOZ rose from 45% to 62%, and AUROC increased from 0.92 to 0.95. In both cohorts, detections outside the SOZ were significantly reduced, enhancing spatial specificity without compromising sensitivity. Theoretically, our TPE-based optimization achieved over 2,958×speedup over a grid search. These results show an effective data-driven parameter tuning approach that improves HFO biomarker reliability and supports their use in clinical planning for epilepsy surgery.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2025 ","pages":"64-69"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13491750/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148802570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Miniature Wireless Device for Closed-Loop Auditory Sleep Modulation.","authors":"William Lee, Savanna Blade, Yuhan Hou, Amelia McIver, Runtian Yang, Xilin Liu, Andrew G Richardson","doi":"10.1109/ner61569.2025.11588949","DOIUrl":"10.1109/ner61569.2025.11588949","url":null,"abstract":"<p><p>Both sleep research and treatment of common sleep disorders can benefit from targeted modulation of sleep circuits. Noninvasive stimulation through the auditory pathway has proven to be an effective method for neuromodulation during sleep, particularly when timed to ongoing rhythms using a closed-loop system. However, such systems are not widely available to the research or clinical communities. Technical demands include real-time sleep scoring, phase estimation, and low-latency auditory feedback. Our goal is to develop a robust, easy-to-use, wireless, programmable, closed-loop sleep modulation device suitable for subjects ranging from mice to humans and for use outside of a sleep lab environment. Here, we present a prototype: a battery-powered, flex-rigid printed-circuit board with off-the-shelf components for polysomnography data acquisition and wireless transmission, as well as configurable closed-loop control through a Python graphical user interface. Performance was quantified through a series of experiments in freely behaving rats.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2025 ","pages":"842-846"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13502937/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Design of Brainstem Interfaces: Characterisation of Physiological Artefacts and Implications for Closed-loop Algorithms.","authors":"Alceste Deli, Robert Toth, Mayela Zamora, Amir P Divanbeighi Zand, Alexander L Green, Timothy Denison","doi":"10.1109/NER52421.2023.10123850","DOIUrl":"10.1109/NER52421.2023.10123850","url":null,"abstract":"<p><p>Surgical neuromodulation through implantable devices allows for stimulation delivery to subcortical regions, crucial for symptom control in many debilitating neurological conditions. Novel closed-loop algorithms deliver therapy tailor-made to endogenous physiological activity, however rely on precise sensing of signals such as subcortical oscillations. The frequency of such intrinsic activity can vary depending on subcortical target nucleus, while factors such as regional anatomy may also contribute to variability in sensing signals. While artefact parameters have been explored in more 'standard' and commonly used targets (such as the basal ganglia, which are implanted in movement disorders), characterisation in novel candidate nuclei is still under investigation. One such important area is the brainstem, which contains nuclei crucial for arousal and autonomic regulation. The brainstem provides additional implantation targets for treatment indications in disorders of consciousness and sleep, yet poses distinct anatomical challenges compared to central subcortical targets. Here we investigate the region-specific artefacts encountered during activity and rest while streaming data from brainstem implants with a cranially-mounted device in two patients. Such artefacts result from this complex anatomical environment and its interactions with physiological parameters such as head movement and cardiac functions. The implications of the micromotion-induced artefacts, and potential mitigation, are then considered for future closed-loop stimulation methods.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2023 ","pages":"10123850"},"PeriodicalIF":0.0,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9605836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulation of arousal and performance of a healthy non-human primate using closed-loop central thalamic deep brain stimulation.","authors":"Jonathan L Baker, Robert Toth, Alceste Deli, Mayela Zamora, John E Fleming, Moaad Benjaber, Dana Goerzen, Jae-Wook Ryou, Keith P Purpura, Nicholas D Schiff, Timothy Denison","doi":"10.1109/NER52421.2023.10123754","DOIUrl":"10.1109/NER52421.2023.10123754","url":null,"abstract":"<p><p>Application of closed-loop approaches in systems neuroscience and brain-computer interfaces holds great promise for revolutionizing our understanding of the brain and for developing novel neuromodulation strategies to restore lost function. The anterior forebrain mesocircuit (AFM) of the mammalian brain is hypothesized to underlie arousal regulation of the cortex and striatum, and support cognitive functions during wakefulness. Dysfunction of arousal regulation is hypothesized to contribute to cognitive dysfunctions in various neurological disorders, and most prominently in patients following traumatic brain injury (TBI). Several clinical studies have explored the use of daily central thalamic deep brain stimulation (CT-DBS) within the AFM to restore consciousness and executive attention in TBI patients. In this study, we explored the use of closed-loop CT-DBS in order to episodically regulate arousal of the AFM of a healthy non-human primate (NHP) with the goal of restoring behavioral performance. We used pupillometry and near real-time analysis of ECoG signals to episodically initiate closed-loop CT-DBS and here we report on our ability to enhance arousal and restore the animal's performance. The initial computer based approach was then experimentally validated using a customized clinical-grade DBS device, the DyNeuMo-X, a bi-directional research platform used for rapidly testing closed-loop DBS. The successful implementation of the DyNeuMo-X in a healthy NHP supports ongoing clinical trials employing the internal DyNeuMo system (NCT05437393, NCT05197816) and our goal of developing and accelerating the deployment of novel neuromodulation approaches to treat cognitive dysfunction in patients with structural brain injuries and other etiologies.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2023 ","pages":"10123754"},"PeriodicalIF":0.0,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614571/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9518332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medial Tractography Analysis (MeTA) for White Matter Population Analyses Across Datasets","authors":"Iyad Ba Gari, Abhinaav Ramesh, Shayan Javid, S. Gadewar, Elnaz Nourollahimoghadam, S. Thomopoulos, P. Thompson, T. Nir, N. Jahanshad","doi":"10.1109/ner52421.2023.10123727","DOIUrl":"https://doi.org/10.1109/ner52421.2023.10123727","url":null,"abstract":"","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"43 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82540794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reverse engineering information processing in lateral amygdala during auditory tones.","authors":"Greg Glickert,&nbsp;Ben Latimer,&nbsp;Pankaj Sah,&nbsp;Satish S Nair","doi":"10.1109/ner52421.2023.10123856","DOIUrl":"https://doi.org/10.1109/ner52421.2023.10123856","url":null,"abstract":"<p><p>Learning in the mammalian lateral amygdala (LA) during auditory fear conditioning (tone - foot shock pairing), one form of associative learning, requires N-methyl-D-aspartate (NMDA) receptor-dependent plasticity. Despite this fact being known for more than two decades, the biophysical details related to signal flow and the involvement of the coincidence detector, NMDAR, in this learning, remain unclear. Here we use a 4000-neuron computational model of the LA (containing two types of pyramidal cells, types A and C, and two types of interneurons, fast spiking FSI and low-threshold spiking LTS) to reverse engineer changes in information flow in the amygdala that underpin such learning; with a specific focus on the role of the coincidence detector NMDAR. The model also included a Ca^2s based learning rule for synaptic plasticity. The physiologically constrained model provides insights into the underlying mechanisms that implement habituation to the tone, including the role of NMDARs in generating network activity which engenders synaptic plasticity in specific afferent synapses. Specifically, model runs revealed that NMDARs in tone-FSI synapses were more important during the spontaneous state, although LTS cells also played a role. Training trails with tone only also suggested long term depression in tone-PN as well as tone-FSI synapses, providing possible hypothesis related to underlying mechanisms that might implement the phenomenon of habituation.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2023 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10292606/pdf/nihms-1892243.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9709288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning signatures of decision making from many individuals playing the same game.","authors":"Michael J Mendelson,&nbsp;Mehdi Azabou,&nbsp;Suma Jacob,&nbsp;Nicola Grissom,&nbsp;David Darrow,&nbsp;Becket Ebitz,&nbsp;Alexander Herman,&nbsp;Eva L Dyer","doi":"10.1109/ner52421.2023.10123846","DOIUrl":"10.1109/ner52421.2023.10123846","url":null,"abstract":"<p><p>Human behavior is incredibly complex and the factors that drive decision making-from instinct, to strategy, to biases between individuals-often vary over multiple timescales. In this paper, we design a predictive framework that learns representations to encode an individual's 'behavioral style', i.e. long-term behavioral trends, while simultaneously predicting future actions and choices. The model explicitly separates representations into three latent spaces: the recent past space, the short-term space, and the long-term space where we hope to capture individual differences. To simultaneously extract both global and local variables from complex human behavior, our method combines a multi-scale temporal convolutional network with latent prediction tasks, where we encourage embeddings across the entire sequence, as well as subsets of the sequence, to be mapped to similar points in the latent space. We develop and apply our method to a large-scale behavioral dataset from 1,000 humans playing a 3-armed bandit task, and analyze what our model's resulting embeddings reveal about the human decision making process. In addition to predicting future choices, we show that our model can learn rich representations of human behavior over multiple timescales and provide signatures of differences in individuals.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2023 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10559224/pdf/nihms-1931965.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41171846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}