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Online neurostimulation optimization means in vivo trial-and-error tuning of a neural interface, where decisions involve selecting from a large number of parameter options, and the constantly evolving environment induces both noise and non-stationarity in the response.", "key": "MNqWDKhSPM"}], "key": "DZDRD262lZ"}, {"type": "paragraph", "position": {"start": {"line": 41, "column": 1}, "end": {"line": 41, "column": 1}}, "children": [{"type": "text", "value": "To date, real-time neurostimulation optimization in clinical studies is performed by adaptive stimulation ", "position": {"start": {"line": 41, "column": 1}, "end": {"line": 41, "column": 1}}, "key": "cVSqlayrpL"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 1}, "end": {"line": 41, "column": 1}}, "children": [{"type": "cite", "identifier": "arlotti2018eight", "label": "arlotti2018eight", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 108}, "end": {"line": 41, "column": 125}}, "children": [{"type": "text", "value": "Arlotti ", "key": "h45jBW0QbB"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "kKyDp3OoM4"}], "key": "zqSOMPH89O"}, {"type": "text", "value": ", 2018", "key": "zd3wCBZBdW"}], "enumerator": "17", "key": "m6r7eALjnb"}, {"type": "cite", "identifier": "rosa2015adaptive", "label": "rosa2015adaptive", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 126}, "end": {"line": 41, "column": 143}}, "children": [{"type": "text", "value": "Rosa ", "key": "HYSGD9YM9o"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "Qni9xNbxol"}], "key": "XNFX8SbgFk"}, {"type": "text", "value": ", 2015", "key": "ZKRRElBssI"}], "enumerator": "18", "key": "Qcd7J2kRD9"}, {"type": "cite", "identifier": "swann2018adaptive", "label": "swann2018adaptive", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 144}, "end": {"line": 41, "column": 162}}, "children": [{"type": "text", "value": "Swann ", "key": "WAT14goT2I"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "KCEVk1L7zG"}], "key": "Ae9e5Sk8uo"}, {"type": "text", "value": ", 2018", "key": "IbnVaqvopg"}], "enumerator": "19", "key": "W5oZCmNlpV"}], "key": "bM50iVJxMy"}, {"type": "text", "value": ". This closed-loop method traditionally relies on turning on and off ", "key": "eBOwu96Now"}, {"type": "abbreviation", "title": "Deep Brain Stimulation", "children": [{"type": "text", "value": "DBS", "key": "CtAgYhVwVA"}], "key": "NAvKfRkrqC"}, {"type": "text", "value": " and varying the amplitude based on neurophysiological feedback, but this approach is not tailored for a complex multivariate problem such as selecting what specific stimulation pattern to activate, among an immense number of options for varying contact, frequency, current amplitude and pulse width. To offer a solution adapted to optimization of multi parameters, some studies focus on a class of algorithms that does not require training and that relies on parametric models of stimulation properties. Bayesian Optimization based on Gaussian Process (GPBO) can offer an effective solution ", "key": "Ovks37i9wl"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 1}, "end": {"line": 41, "column": 1}}, "children": [{"type": "cite", "identifier": "bonizzato2023autonomous", "label": "bonizzato2023autonomous", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 828}, "end": {"line": 41, "column": 852}}, "children": [{"type": "text", "value": "Bonizzato ", "key": "cQnhptoZFc"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "sFJKwv3CDU"}], "key": "MQy2xLDdSr"}, {"type": "text", "value": ", 2023", "key": "qgHrlIWG2f"}], "enumerator": "20", "key": "CPoabiidFZ"}, {"type": "cite", "identifier": "choiniere2024gaussian", "label": "choiniere2024gaussian", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 853}, "end": {"line": 41, "column": 875}}, "children": [{"type": "text", "value": "Choini\u00e8re ", "key": "YrKNRcWio1"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "YRU1oQRJ2C"}], "key": "ebfXcT2Ouj"}, {"type": "text", "value": ", 2024", "key": "fEDMbt9ooq"}], "enumerator": "21", "key": "rjuX22QzX1"}, {"type": "cite", "identifier": "laferriere2020hierarchical", "label": "laferriere2020hierarchical", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 876}, "end": {"line": 41, "column": 903}}, "children": [{"type": "text", "value": "Laferriere ", "key": "T1e4aWPoIE"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "pZAYJdPorp"}], "key": "eK6Rvk3lcq"}, {"type": "text", "value": ", 2020", "key": "RrOosKH16P"}], "enumerator": "22", "key": "Y1Rp2EiQfa"}, {"type": "cite", "identifier": "sarikhani2022automated", "label": "sarikhani2022automated", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 904}, "end": {"line": 41, "column": 927}}, "children": [{"type": "text", "value": "Sarikhani ", "key": "q6eQOIPjbB"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "Yjb0GsTIiz"}], "key": "grnSCBtRpe"}, {"type": "text", "value": ", 2022", "key": "pzY0Hp3LYS"}], "enumerator": "23", "key": "DYJu6711Qh"}, {"type": "cite", "identifier": "aiello2023recalibration", "label": "aiello2023recalibration", "kind": "parenthetical", "position": {"start": {"line": 41, "column": 928}, "end": {"line": 41, "column": 952}}, "children": [{"type": "text", "value": "Aiello ", "key": "I4tCrodAxY"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "OCwnyv9KRu"}], "key": "N1xqZRlPGu"}, {"type": "text", "value": ", 2023", "key": "FH0ihut6Zh"}], "enumerator": "24", "key": "RovHObbucy"}], "key": "om7RMbKEQS"}, {"type": "text", "value": ". GPBO tests single-input parameter combinations (\u201cqueries\u201d), leveraging responses to build an evidence-based approximation (\u201csurrogate\u201d function) that models how stimulus choices affect the desired output. This approach allows to efficiently explore high dimensional spaces in a small number of iterations.", "position": {"start": {"line": 41, "column": 1}, "end": {"line": 41, "column": 1}}, "key": "dOYxoAnfo6"}], "key": "v1RWhSmynq"}, {"type": "heading", "depth": 3, "position": {"start": {"line": 44, "column": 1}, "end": {"line": 44, "column": 1}}, "children": [{"type": "text", "value": "Optimizing stimulation for movement disorders", "position": {"start": {"line": 44, "column": 1}, "end": {"line": 44, "column": 1}}, "key": "fH11NEjLrm"}], "identifier": "optimizing-stimulation-for-movement-disorders", "label": "Optimizing stimulation for movement disorders", "html_id": "optimizing-stimulation-for-movement-disorders", "implicit": true, "enumerator": "1.2", "key": "F7DikSqn2a"}, {"type": "paragraph", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "children": [{"type": "text", "value": "Restoring motor control after neurotrauma or in disease is a very complex neuromodulation challenge since the movement is controlled by distributed brain and spinal networks with variable dynamic states and outputs. Promising studies already show how advanced optimization methods can enhance mobility ", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "key": "dRAyrrfBeW"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "children": [{"type": "cite", "identifier": "bonizzato2023autonomous", "label": "bonizzato2023autonomous", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 304}, "end": {"line": 46, "column": 328}}, "children": [{"type": "text", "value": "Bonizzato ", "key": "MZSPUve9HK"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "CsdUklAVkj"}], "key": "dSCWihVfmF"}, {"type": "text", "value": ", 2023", "key": "JQgbcO6AF7"}], "enumerator": "20", "key": "gBikjdYx5L"}, {"type": "cite", "identifier": "grahn2014restoration", "label": "grahn2014restoration", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 329}, "end": {"line": 46, "column": 350}}, "children": [{"type": "text", "value": "Grahn ", "key": "hDLiimbjtj"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "WfUQkoKbyf"}], "key": "YcTNTcXvPB"}, {"type": "text", "value": ", 2014", "key": "s9VceBngiR"}], "enumerator": "25", "key": "oGpCiT7acV"}], "key": "N4jHpKsJEZ"}, {"type": "text", "value": ", ", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "key": "aB5lNDE5oi"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "children": [{"type": "cite", "identifier": "losanno2021bayesian", "label": "losanno2021bayesian", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 354}, "end": {"line": 46, "column": 374}}, "children": [{"type": "text", "value": "Losanno ", "key": "IWYosM2amQ"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "PL4ol7MCiS"}], "key": "LjkJfWqtix"}, {"type": "text", "value": ", 2021", "key": "EExCVwviSt"}], "enumerator": "26", "key": "gLIBco5Lwz"}], "key": "k3xoo9eAdA"}, {"type": "text", "value": ", but the field of motor neuroprosthetics is still young. Novel exciting demonstrations of motor control restoration feature complex neuroprosthetic systems, with a high degree of control complexity ", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "key": "cFNqqfiQZL"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "children": [{"type": "cite", "identifier": "rowald2022activity", "label": "rowald2022activity", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 575}, "end": {"line": 46, "column": 594}}, "children": [{"type": "text", "value": "Rowald ", "key": "J3uXeMQvha"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "bLRlMFSz8D"}], "key": "F7vYEaCa4l"}, {"type": "text", "value": ", 2022", "key": "mEK0wMQq6g"}], "enumerator": "27", "key": "AitujQhyZT"}, {"type": "cite", "identifier": "wagner2018targeted", "label": "wagner2018targeted", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 595}, "end": {"line": 46, "column": 614}}, "children": [{"type": "text", "value": "Wagner ", "key": "LO7QdoEN56"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "MQo7Kuppet"}], "key": "eBFk0IfFdL"}, {"type": "text", "value": ", 2018", "key": "SeibVZJ06t"}], "enumerator": "28", "key": "rayyQEJVqo"}], "key": "kNQQpvp7e3"}, {"type": "text", "value": ". Research to develop optimization agents to fine-tune such systems once they are implanted largely benefits from offline modeling and simulation ", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "key": "IZs2euqKvd"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "children": [{"type": "cite", "identifier": "capogrosso2013computational", "label": "capogrosso2013computational", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 762}, "end": {"line": 46, "column": 790}}, "children": [{"type": "text", "value": "Capogrosso ", "key": "hOCRNpFcwL"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "uFxAngmkCa"}], "key": "edxrUagi19"}, {"type": "text", "value": ", 2013", "key": "AmGA4xM1PC"}], "enumerator": "29", "key": "VzB3MSYomh"}, {"type": "cite", "identifier": "rowald2022activity", "label": "rowald2022activity", "kind": "parenthetical", "position": {"start": {"line": 46, "column": 791}, "end": {"line": 46, "column": 810}}, "children": [{"type": "text", "value": "Rowald ", "key": "QpFLOgkBub"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "H9EcpsCQSf"}], "key": "EpB6E5q3RJ"}, {"type": "text", "value": ", 2022", "key": "e5S84xcUCH"}], "enumerator": "27", "key": "E8Emb1q75w"}], "key": "fyZ6YWMQjS"}, {"type": "text", "value": ".", "position": {"start": {"line": 46, "column": 1}, "end": {"line": 46, "column": 1}}, "key": "aEYZown2Ja"}], "key": "ioFS8fwjvu"}, {"type": "paragraph", "position": {"start": {"line": 48, "column": 1}, "end": {"line": 48, "column": 1}}, "children": [{"type": "text", "value": "To effectively train and test complex ", "key": "JjPJbDKtYW"}, {"type": "abbreviation", "title": "Machine Learning", "children": [{"type": "text", "value": "ML", "key": "IyjieS1qVV"}], "key": "ArElbmAPOd"}, {"type": "text", "value": " models or simulate online experimental neurostimulation sessions, a diverse range of neurostimulation datasets is essential ", "key": "QqBWSoVoLp"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 48, "column": 1}, "end": {"line": 48, "column": 1}}, "children": [{"type": "cite", "identifier": "wang2023machine", "label": "wang2023machine", "kind": "parenthetical", "position": {"start": {"line": 48, "column": 167}, "end": {"line": 48, "column": 183}}, "children": [{"type": "text", "value": "Wang ", "key": "gWneoPv04a"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "Yy2sJLG8jJ"}], "key": "FlhK5BGRS1"}, {"type": "text", "value": ", 2023", "key": "UiHC1k8RsD"}], "enumerator": "30", "key": "odwWj35c4z"}, {"type": "cite", "identifier": "bonizzato2023autonomous", "label": "bonizzato2023autonomous", "kind": "parenthetical", "position": {"start": {"line": 48, "column": 184}, "end": {"line": 48, "column": 208}}, "children": [{"type": "text", "value": "Bonizzato ", "key": "heGChtwdCC"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "pkSMcqTZYM"}], "key": "MLFZeppHgF"}, {"type": "text", "value": ", 2023", "key": "yW3wd4Q5Oa"}], "enumerator": "20", "key": "TgvG3PHtch"}], "key": "F7i54kwxgv"}, {"type": "text", "value": ". Such datasets must account for variability across subjects, species, and neural interface targets. For example, rodents provide the advantage of generating large datasets due to relatively restrained costs, while ", "key": "XIABt1OYPC"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "SrXiqTNGeM"}], "key": "DEWFflJauZ"}, {"type": "text", "value": "s offer a closer approximation to human brain complexity, making both species invaluable for research. The characteristics of any single dataset can vary widely due to environmental factors and experimental design, leading to significant differences not only between rodent and ", "key": "uIMS3ESbF7"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "zxpjkTZ2fG"}], "key": "Wn4xvtlvmd"}, {"type": "text", "value": " data but also across neural targets such as the spinal cord and cortex; even within subjects of the same species.", "key": "kWkJyg9i6l"}], "key": "oFfkJLsTtG"}, {"type": "paragraph", "position": {"start": {"line": 50, "column": 1}, "end": {"line": 50, "column": 1}}, "children": [{"type": "text", "value": "Although synthetic data can serve as an initial benchmark for algorithm performance, it falls short in addressing the complexities inherent to in vivo data. Many neurophysiological mechanisms, such as the biological variability of motor responses, remain poorly modeled. This variability causes, among other things, inconsistencies in neural output to identical stimulation parameters and is compounded by noise introduced by experimental setups. These challenges make in vivo validation important, not only for assessing algorithm functionality but also for uncovering patterns of responses to neural stimuli and deepening our understanding of neural circuits response dynamics and non-stationarities. However, expanding the collection of neurostimulation datasets faces significant barriers, including high costs, technical complexity, and ethical considerations.", "position": {"start": {"line": 50, "column": 1}, "end": {"line": 50, "column": 1}}, "key": "cnAM2wK5dO"}], "key": "cQWDLrmwXS"}, {"type": "paragraph", "position": {"start": {"line": 52, "column": 1}, "end": {"line": 52, "column": 1}}, "children": [{"type": "text", "value": "The recent surge in optimization algorithms within this field opens new possibilities for neurostimulation applications. To further push the boundaries of AI in neurostimulation, it is essential to broaden the dataset pool, thereby supporting a wider range of innovative use cases.", "position": {"start": {"line": 52, "column": 1}, "end": {"line": 52, "column": 1}}, "key": "mwKrrcCMHg"}], "key": "Npn5q9bLRA"}, {"type": "paragraph", "position": {"start": {"line": 54, "column": 1}, "end": {"line": 54, "column": 1}}, "children": [{"type": "text", "value": "Our goal is to develop ", "key": "SrpHi9qQOB"}, {"type": "abbreviation", "title": "Neurostimulation Multi-scale Open-Source Across Interface, Conditions & Species", "children": [{"type": "text", "value": "NeuroMOSAICS", "key": "yDSq68fPDj"}], "key": "FXkDSJKcn4"}, {"type": "text", "value": " (Neurostimulation Multi-scale Open-Source Across Interface, Conditions & Species), a collection of open-access datasets comprising a wide range of different neurostimulation scenarios: in rats and non-human primates (", "key": "uPaBVgC1lg"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "k4wESqHyrR"}], "key": "jDcwfMAVhg"}, {"type": "text", "value": "), in sedated and awake animals, in intact and injured subjects, in small and large input spaces optimization, and in both cortical and spinal neurostimulation interventions. ", "key": "FnhImb9sFU"}, {"type": "abbreviation", "title": "Neurostimulation Multi-scale Open-Source Across Interface, Conditions & Species", "children": [{"type": "text", "value": "NeuroMOSAICS", "key": "OqubpflLwX"}], "key": "Zz35kgCBU9"}, {"type": "text", "value": " aims to support the development of neurostimulation optimization algorithms. For each dataset, we highlight common challenges that any optimization algorithm must address when applied in this context. Our goal is not only to provide a series of datasets, but also to shed light on these recurring challenges for anyone interested in advancing this field and accelerating the development of related technologies. This collection is an attempt to regroup and valorize all neurostimulation characterization datasets opened by the community. Beyond enabling the training and evaluation of data-demanding algorithms, this collaborative initiative also aims to make valuable knowledge more accessible, thereby encouraging the ", "key": "d9DpsivICy"}, {"type": "abbreviation", "title": "Machine Learning", "children": [{"type": "text", "value": "ML", "key": "dvHlnCg74U"}], "key": "UQKmQH7fwl"}, {"type": "text", "value": " community to design solutions tailored to neurostimulation problems.", "key": "dpplFutwcN"}], "key": "f9qPJ5D5Il"}, {"type": "paragraph", "position": {"start": {"line": 56, "column": 1}, "end": {"line": 56, "column": 1}}, "children": [{"type": "text", "value": "This living white paper intends to evolve in time with new incoming open-source datasets. New datasets will be added as we target additional unmet needs in neurostimulation optimization. Moreover, we aim to incorporate complex datasets that establish benchmarks and open avenues for novel algorithmic solutions. Datasets may also be introduced in response to community demand or as invited contributions. We welcome opportunities to review contributions from groups exploring high-dimensional optimization, to collaboratively grow this evolving body of work.", "position": {"start": {"line": 56, "column": 1}, "end": {"line": 56, "column": 1}}, "key": "yBAnOxrpEZ"}], "key": "ffrwSqKddi"}, {"type": "heading", "depth": 2, "position": {"start": {"line": 58, "column": 1}, "end": {"line": 58, "column": 1}}, "children": [{"type": "text", "value": "Materials and methods", "position": {"start": {"line": 58, "column": 1}, "end": {"line": 58, "column": 1}}, "key": "r83NG1PlyU"}], "identifier": "materials-and-methods", "label": "Materials and methods", "html_id": "materials-and-methods", "implicit": true, "enumerator": "2", "key": "Lr44lrZD9s"}, {"type": "paragraph", "position": {"start": {"line": 60, "column": 1}, "end": {"line": 60, "column": 1}}, "children": [{"type": "text", "value": "In this section we describe how each featured dataset has been collected. We wrote this section with a focus on clarity and a level of readership accessible to those without a background in neuroscience.", "position": {"start": {"line": 60, "column": 1}, "end": {"line": 60, "column": 1}}, "key": "DxO9mN7GD8"}], "key": "FRa9fazZ6X"}, {"type": "heading", "depth": 3, "position": {"start": {"line": 62, "column": 1}, "end": {"line": 62, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1 \u2013 Cortically evoked muscle responses: ", "key": "XlHOR8P7GK"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "ck87DGUeM2"}], "key": "zEcMIGxuCw"}, {"type": "text", "value": " forelimb and rat hindlimb", "key": "RviLxXd9Dn"}], "identifier": "dataset-1-cortically-evoked-muscle-responses-nhp-forelimb-and-rat-hindlimb", "label": "Dataset 1 \u2013 Cortically evoked muscle responses: NHP forelimb and rat hindlimb", "html_id": "dataset-1-cortically-evoked-muscle-responses-nhp-forelimb-and-rat-hindlimb", "implicit": true, "enumerator": "2.1", "key": "bxWH40nqJ1"}, {"type": "admonition", "kind": "important", "children": [{"type": "admonitionTitle", "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 64, "column": 1}, "end": {"line": 64, "column": 1}}, "key": "Dc33ubFU72"}], "key": "tZHIXedNM4"}, {"type": "list", "ordered": false, "spread": false, "position": {"start": {"line": 66, "column": 1}, "end": {"line": 70, "column": 1}}, "children": [{"type": "listItem", "spread": true, "position": {"start": {"line": 66, "column": 1}, "end": {"line": 66, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 66, "column": 1}, "end": {"line": 66, "column": 1}}, "children": [{"type": "text", "value": "Input:", "position": {"start": {"line": 66, "column": 1}, "end": {"line": 66, "column": 1}}, "key": "TFkImU6yAs"}], "key": "J9a9COgVvt"}, {"type": "text", "value": " coordinates of an electrode in a 96-electrode intracortical array for ", "key": "HpnMPUebDC"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "Jtom9wRKkj"}], "key": "LcQyBYUQMr"}, {"type": "text", "value": " and 32-electrode intracortical array for rats.", "key": "mrJMjhOJ2r"}], "key": "XR0y12HFLm"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 67, "column": 1}, "end": {"line": 67, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 67, "column": 1}, "end": {"line": 67, "column": 1}}, "children": [{"type": "text", "value": "Output:", "position": {"start": {"line": 67, "column": 1}, "end": {"line": 67, "column": 1}}, "key": "SCLBchWIck"}], "key": "CspN4tUkgx"}, {"type": "text", "value": " Motor Evoked Potentials (", "key": "LgehIj2N8x"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "AApnjazEfA"}], "key": "Wc1tfw5gh1"}, {"type": "text", "value": "s) from 4 to 8 muscles, forearm and hand muscles for ", "key": "GitucRupsb"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "cFCE3CQOTA"}], "key": "CIRId3vggB"}, {"type": "text", "value": " and leg muscles for rat.", "key": "IGlnd5OwWH"}], "key": "oX0LQNX2Tu"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 68, "column": 1}, "end": {"line": 68, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 68, "column": 1}, "end": {"line": 68, "column": 1}}, "children": [{"type": "text", "value": "Replicates:", "position": {"start": {"line": 68, "column": 1}, "end": {"line": 68, "column": 1}}, "key": "IgeplZ44zS"}], "key": "RXFY4QB9gU"}, {"type": "text", "value": " Data were collected from N=4 ", "key": "aKqMWSJe4u"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "kKYYDZeICI"}], "key": "DSeqfjLCM2"}, {"type": "text", "value": " and N=6 rats (biological replicate). For each independent muscle, technical replicates ranged from 10 to 28 repetitions.", "key": "RkEZbM6pMO"}], "key": "UsitB5rmEp"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 69, "column": 1}, "end": {"line": 69, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 69, "column": 1}, "end": {"line": 69, "column": 1}}, "children": [{"type": "text", "value": "Depth:", "position": {"start": {"line": 69, "column": 1}, "end": {"line": 69, "column": 1}}, "key": "iYUZ4SokrP"}], "key": "X1Simh7F6Z"}, {"type": "text", "value": " The same neurostimulation is repeated 10 to 28 times per site (muscle) per subject, resulting in an equivalent number of ", "key": "uXRkN7vFsL"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "aP2aFQseug"}], "key": "M91YOe7Fvc"}, {"type": "text", "value": " measurements being collected. Each ", "key": "BxM0RvEHv2"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "bacjoqp4Xw"}], "key": "lRlMl6xARi"}, {"type": "text", "value": " represents the muscle response within a time window of -100 to 200 ms relative to the stimulation delivery (0 ms).", "key": "ilcobLMSF4"}], "key": "vXhXt0iH1a"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 70, "column": 1}, "end": {"line": 70, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 70, "column": 1}, "end": {"line": 70, "column": 1}}, "children": [{"type": "text", "value": "Rationale:", "position": {"start": {"line": 70, "column": 1}, "end": {"line": 70, "column": 1}}, "key": "oNkXm8JPe1"}], "key": "GaqAHLnvO9"}, {"type": "text", "value": " To develop optimization algorithms to efficiently optimize neurostimulation within a set of electrode location options.", "position": {"start": {"line": 70, "column": 1}, "end": {"line": 70, "column": 1}}, "key": "mCoWl5OYUa"}], "key": "iPXqCheoUs"}], "key": "TVLFSOgnca"}], "key": "ePuGvFlOQy"}, {"type": "paragraph", "position": {"start": {"line": 73, "column": 1}, "end": {"line": 73, "column": 1}}, "children": [{"type": "text", "value": "This dataset contains limb EMG responses to cortical stimulation in 4 male ", "key": "JlPcJqQLIO"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "TRxpFfKaap"}], "key": "udqMzwSf21"}, {"type": "text", "value": "s (2 macaques, 2 capuchins) and 6 female rats. The dataset, available on OSF, was collected to develop a Gaussian Process Bayesian Optimization (GPBO) framework, an algorithm designed to optimize neurostimulation parameters for maximizing ", "key": "UoDUNtmCBq"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "NOZwZ2JZcW"}], "key": "aNs7KGhtye"}, {"type": "text", "value": "s. Cross-species data can challenge the robustness and adaptability of optimization algorithms, testing their ability to generalize across scales and from simpler to more complex cortical organizations, that approximate better the human brain.", "key": "JmdJ8x6pKX"}], "key": "LQXsajgHSo"}, {"type": "paragraph", "position": {"start": {"line": 75, "column": 1}, "end": {"line": 76, "column": 1}}, "children": [{"type": "text", "value": "The detailed protocol for surgery and experiment is available on M. Bonizzato et al. ", "position": {"start": {"line": 75, "column": 1}, "end": {"line": 75, "column": 1}}, "key": "iFXWu0tGQv"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 75, "column": 1}, "end": {"line": 75, "column": 1}}, "children": [{"type": "cite", "identifier": "bonizzato2023autonomous", "label": "bonizzato2023autonomous", "kind": "parenthetical", "position": {"start": {"line": 75, "column": 87}, "end": {"line": 75, "column": 111}}, "children": [{"type": "text", "value": "Bonizzato ", "key": "dRbYDvFtZN"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "GHn1kKHa8f"}], "key": "EEHV4C4gyn"}, {"type": "text", "value": ", 2023", "key": "QQ1TXo110l"}], "enumerator": "20", "key": "xz1QLKiJff"}, {"type": "cite", "identifier": "choiniere2024gaussian", "label": "choiniere2024gaussian", "kind": "parenthetical", "position": {"start": {"line": 75, "column": 112}, "end": {"line": 75, "column": 134}}, "children": [{"type": "text", "value": "Choini\u00e8re ", "key": "pG2Xzl1NdO"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "u96jDZPtnG"}], "key": "QZMkRTxik9"}, {"type": "text", "value": ", 2024", "key": "zM5z7KriT0"}], "enumerator": "21", "key": "TkiQqDVCfs"}], "key": "PtifHxX0Fy"}, {"type": "text", "value": ".\nThe rats were implanted with 32-microelectrode arrays in the hindlimb sensorimotor cortex and the ", "key": "x4hTpeZ0zu"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "nnqOegX5vR"}], "key": "kCCJwgD1uu"}, {"type": "text", "value": "s were implanted with 96-electrode arrays implanted in the hand area of the primary motor cortex (M1). For rats, the EMGs were implanted in leg muscles. For ", "key": "mFROtFRFjf"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "R38ZxTQxxb"}], "key": "wDgx7gr7xQ"}, {"type": "text", "value": "s, the EMGs were implanted in hand and finger muscles. When the stimulation protocol was running, the two capuchin ", "key": "JmBuHE2SbG"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "jxUjIfCAIX"}], "key": "kqSAIYzGQr"}, {"type": "text", "value": " were under sedation and the two macaques were awake. In the next sections of this preprint, we will refer to ", "key": "uCvvctR6AY"}, {"type": "strong", "position": {"start": {"line": 75, "column": 1}, "end": {"line": 75, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 75, "column": 1}, "end": {"line": 75, "column": 1}}, "key": "CbDvRvXe2m"}], "key": "jIAFJPB5xw"}, {"type": "text", "value": " as the ", "key": "HRn8wJInyr"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "iujFqscaYh"}], "key": "hD5iEcFMQ2"}, {"type": "text", "value": " results; however, the rat outputs follow the same underlying concept.", "key": "pXjUp7nCgU"}], "key": "K6lvbZka6u"}, {"type": "heading", "depth": 3, "position": {"start": {"line": 78, "column": 1}, "end": {"line": 78, "column": 1}}, "children": [{"type": "text", "value": "Dataset 2 \u2013 Forelimb muscle responses to spinal stimulation in rats", "position": {"start": {"line": 78, "column": 1}, "end": {"line": 78, "column": 1}}, "key": "dFLAN8jN8m"}], "identifier": "dataset-2-forelimb-muscle-responses-to-spinal-stimulation-in-rats", "label": "Dataset 2 \u2013 Forelimb muscle responses to spinal stimulation in rats", "html_id": "dataset-2-forelimb-muscle-responses-to-spinal-stimulation-in-rats", "implicit": true, "enumerator": "2.2", "key": "egrSmy5nMn"}, {"type": "admonition", "kind": "important", "children": [{"type": "admonitionTitle", "children": [{"type": "text", "value": "Dataset 2", "position": {"start": {"line": 80, "column": 1}, "end": {"line": 80, "column": 1}}, "key": "DjWMpq58Ny"}], "key": "ta4BY1nbnP"}, {"type": "list", "ordered": false, "spread": false, "position": {"start": {"line": 81, "column": 1}, "end": {"line": 85, "column": 1}}, "children": [{"type": "listItem", "spread": true, "position": {"start": {"line": 81, "column": 1}, "end": {"line": 81, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 81, "column": 1}, "end": {"line": 81, "column": 1}}, "children": [{"type": "text", "value": "Input:", "position": {"start": {"line": 81, "column": 1}, "end": {"line": 81, "column": 1}}, "key": "DL7A2nrGgQ"}], "key": "bY89yGn7DK"}, {"type": "text", "value": " coordinates of an electrode in an epidural 64-electrode array.", "position": {"start": {"line": 81, "column": 1}, "end": {"line": 81, "column": 1}}, "key": "I0lh0jZFtW"}], "key": "Bg5NSdwjVQ"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 82, "column": 1}, "end": {"line": 82, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 82, "column": 1}, "end": {"line": 82, "column": 1}}, "children": [{"type": "text", "value": "Output:", "position": {"start": {"line": 82, "column": 1}, "end": {"line": 82, "column": 1}}, "key": "L2by64M3w9"}], "key": "b6L5PoXhZy"}, {"type": "text", "value": " motor evoked potentials from 8 to 10 arm muscles.", "position": {"start": {"line": 82, "column": 1}, "end": {"line": 82, "column": 1}}, "key": "Ew1lXKJ1VA"}], "key": "XBohqCUvlz"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 83, "column": 1}, "end": {"line": 83, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 83, "column": 1}, "end": {"line": 83, "column": 1}}, "children": [{"type": "text", "value": "Replicates:", "position": {"start": {"line": 83, "column": 1}, "end": {"line": 83, "column": 1}}, "key": "k89X5fVCua"}], "key": "BAciT0JQeK"}, {"type": "text", "value": " Data were collected from N = 9 biological replicates, defined as the number of distinct physical implants performed across 4 rats. Each implant corresponds to a separate array placement on the spinal cord between levels C3 and C6. For each array position, 10 to 15 repetitions of single-pulse stimulation were delivered to each electrode in random order using Tucker-Davis Technologies (TDT) equipment.", "position": {"start": {"line": 83, "column": 1}, "end": {"line": 83, "column": 1}}, "key": "AqKk2ovLIY"}], "key": "cwBoP39Faj"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 84, "column": 1}, "end": {"line": 84, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 84, "column": 1}, "end": {"line": 84, "column": 1}}, "children": [{"type": "text", "value": "Depth:", "position": {"start": {"line": 84, "column": 1}, "end": {"line": 84, "column": 1}}, "key": "ES1YbFX1bQ"}], "key": "TbxaYCkQVp"}, {"type": "text", "value": " The same neurostimulation is repeated 10 to 15 times per site (muscle) per subject, resulting in an equivalent number of ", "key": "kN3aUtvYFe"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "mDf1foB05T"}], "key": "kYZhCqRQ0A"}, {"type": "text", "value": " measurements being collected. Each ", "key": "qTkF8niuKb"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "VcvFUxp9dg"}], "key": "qE9tFJQQgm"}, {"type": "text", "value": " represents the muscle response within a time window of -35 to 40 ms relative to the stimulation delivery (0 ms).", "key": "yzq77pKVey"}], "key": "FDILYDVXLs"}, {"type": "listItem", "spread": true, "position": {"start": {"line": 85, "column": 1}, "end": {"line": 85, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 85, "column": 1}, "end": {"line": 85, "column": 1}}, "children": [{"type": "text", "value": "Rationale:", "position": {"start": {"line": 85, "column": 1}, "end": {"line": 85, "column": 1}}, "key": "w7lL3UXWDM"}], "key": "nzR5lodz26"}, {"type": "text", "value": " To develop optimization algorithms to efficiently optimize neurostimulation within a set of electrode location options and multiple concurrent output muscle objectives (8-10 bilateral and varied agonist/antagonist muscles).", "position": {"start": {"line": 85, "column": 1}, "end": {"line": 85, "column": 1}}, "key": "Ur8rE2Mmsm"}], "key": "Wozxuqnzcq"}], "key": "xYB5afUdPQ"}], "key": "P3kjPDecOY"}, {"type": "paragraph", "position": {"start": {"line": 88, "column": 1}, "end": {"line": 88, "column": 1}}, "children": [{"type": "text", "value": "This dataset contains EMG responses to spinal cord stimulation in the forelimbs of 4 female Long Evans rats. EMG electrodes were implanted bilaterally in the Biceps, Triceps, Flexor Carpi Radialis, Deltoid, and Dorso muscles. Spinal cord stimulation was delivered via a 64-electrode array placed epidurally.", "position": {"start": {"line": 88, "column": 1}, "end": {"line": 88, "column": 1}}, "key": "wppQD9AqLN"}], "key": "ahYHauFIo4"}, {"type": "list", "ordered": false, "spread": false, "position": {"start": {"line": 90, "column": 1}, "end": {"line": 91, "column": 1}}, "children": [{"type": "listItem", "spread": true, "position": {"start": {"line": 90, "column": 1}, "end": {"line": 91, "column": 1}}, "children": [{"type": "text", "value": "Experiment Description", "position": {"start": {"line": 90, "column": 1}, "end": {"line": 90, "column": 1}}, "key": "MVDjtMywhq"}], "key": "cxlhYkBvQH"}], "key": "NjHNu0cBMD"}, {"type": "paragraph", "position": {"start": {"line": 92, "column": 1}, "end": {"line": 92, "column": 1}}, "children": [{"type": "text", "value": "A 64-electrode array was placed epidurally on the cervical spinal cord (C3\u2013C6) in 9 distinct placements across 4 sedated rats. In each animal, up to three array positions were tested within this spinal segment. EMG activity was recorded from muscles in both forelimbs in response to single-pulse stimulation delivered through the array.", "position": {"start": {"line": 92, "column": 1}, "end": {"line": 92, "column": 1}}, "key": "kBom2PtX9y"}], "key": "rMR9IJM8Bm"}, {"type": "list", "ordered": false, "spread": false, "position": {"start": {"line": 94, "column": 1}, "end": {"line": 95, "column": 1}}, "children": [{"type": "listItem", "spread": true, "position": {"start": {"line": 94, "column": 1}, "end": {"line": 95, "column": 1}}, "children": [{"type": "text", "value": "Surgical Procedure", "position": {"start": {"line": 94, "column": 1}, "end": {"line": 94, "column": 1}}, "key": "zQad5ZAq17"}], "key": "LItHsHbyvO"}], "key": "LslC2oL7KH"}, {"type": "paragraph", "position": {"start": {"line": 96, "column": 1}, "end": {"line": 96, "column": 1}}, "children": [{"type": "text", "value": "The experiments were terminal. Rats were anesthetized with urethane (1 g/kg) prior to surgery. After 30 minutes, they were transitioned to isoflurane anesthesia (\u223c2%). Isoflurane was withdrawn prior to stimulation, and the rat maintained under the initial dose of urethane. Vital signs, temperature, and hydration were continuously monitored.", "position": {"start": {"line": 96, "column": 1}, "end": {"line": 96, "column": 1}}, "key": "MoQ3OyFn0v"}], "key": "ljPMxjrRQn"}, {"type": "paragraph", "position": {"start": {"line": 98, "column": 1}, "end": {"line": 99, "column": 1}}, "children": [{"type": "emphasis", "position": {"start": {"line": 98, "column": 1}, "end": {"line": 98, "column": 1}}, "children": [{"type": "text", "value": "EMG Implants", "position": {"start": {"line": 98, "column": 1}, "end": {"line": 98, "column": 1}}, "key": "r9GifL7BEc"}], "key": "YSFbWZbatG"}, {"type": "text", "value": "\nEMG microwires were implanted in the Biceps, Triceps, Flexor Carpi Radialis, Deltoid, and Dorso muscles on both sides. Correct placement was confirmed by electrical stimulation through the wires and observation of evoked movements. Wires were inserted transcutaneously.", "position": {"start": {"line": 98, "column": 1}, "end": {"line": 98, "column": 1}}, "key": "yeaaXiu4Cw"}], "key": "Xn0RfXgBh9"}, {"type": "paragraph", "position": {"start": {"line": 101, "column": 1}, "end": {"line": 102, "column": 1}}, "children": [{"type": "emphasis", "position": {"start": {"line": 101, "column": 1}, "end": {"line": 101, "column": 1}}, "children": [{"type": "text", "value": "Spinal Cord Implants", "position": {"start": {"line": 101, "column": 1}, "end": {"line": 101, "column": 1}}, "key": "MRU36XAYZK"}], "key": "WUs4dlt8rS"}, {"type": "text", "value": "\nThe dura mater was exposed from C3 to C6. Initially, a single electrode was used to determine muscle response thresholds. A 64-electrode array was then placed epidurally at up to three different locations.", "position": {"start": {"line": 101, "column": 1}, "end": {"line": 101, "column": 1}}, "key": "ABrQjX13Q8"}], "key": "PgE6f4jmTM"}, {"type": "list", "ordered": false, "spread": false, "position": {"start": {"line": 104, "column": 1}, "end": {"line": 105, "column": 1}}, "children": [{"type": "listItem", "spread": true, "position": {"start": {"line": 104, "column": 1}, "end": {"line": 105, "column": 1}}, "children": [{"type": "text", "value": "Data Collection", "position": {"start": {"line": 104, "column": 1}, "end": {"line": 104, "column": 1}}, "key": "cod18IfnVI"}], "key": "UTrleItEEP"}], "key": "C0x60P9Ph5"}, {"type": "paragraph", "position": {"start": {"line": 106, "column": 1}, "end": {"line": 106, "column": 1}}, "children": [{"type": "text", "value": "For each placement, 10 repetitions of single-pulse stimulation were delivered to each electrode in random order using Tucker-Davis Technologies (TDT) equipment. Stimulation amplitude was set to the threshold value identified during single-electrode testing.", "position": {"start": {"line": 106, "column": 1}, "end": {"line": 106, "column": 1}}, "key": "GoPZNF2Gpe"}], "key": "R6BHMxTbAH"}, {"type": "heading", "depth": 3, "position": {"start": {"line": 108, "column": 1}, "end": {"line": 108, "column": 1}}, "children": [{"type": "text", "value": "Processing", "position": {"start": {"line": 108, "column": 1}, "end": {"line": 108, "column": 1}}, "key": "YqiV9ima3h"}], "identifier": "processing", "label": "Processing", "html_id": "processing", "implicit": true, "enumerator": "2.3", "key": "JQLDn6NtjM"}, {"type": "paragraph", "position": {"start": {"line": 110, "column": 1}, "end": {"line": 110, "column": 1}}, "children": [{"type": "text", "value": "The raw signals in both datasets have been rectified.", "position": {"start": {"line": 110, "column": 1}, "end": {"line": 110, "column": 1}}, "key": "FLh8TIzmxA"}], "key": "nlj9UcHLct"}, {"type": "admonition", "kind": "important", "children": [{"type": "admonitionTitle", "children": [{"type": "text", "value": "Processing applied in ", "position": {"start": {"line": 112, "column": 1}, "end": {"line": 112, "column": 1}}, "key": "Gwsp1ZvXBs"}, {"type": "strong", "position": {"start": {"line": 112, "column": 1}, "end": {"line": 112, "column": 1}}, "children": [{"type": "text", "value": "Dataset 2", "position": {"start": {"line": 112, "column": 1}, "end": {"line": 112, "column": 1}}, "key": "uUQewiGHAR"}], "key": "lAQnEvMm45"}], "key": "e19pjGNIwH"}, {"type": "paragraph", "position": {"start": {"line": 114, "column": 1}, "end": {"line": 114, "column": 1}}, "children": [{"type": "text", "value": "In addition to the raw data, a filtered version of the signal is provided in this dataset. 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While ", "key": "EuOyGySxN9"}, {"type": "abbreviation", "title": "Neurostimulation Multi-scale Open-Source Across Interface, Conditions & Species", "children": [{"type": "text", "value": "NeuroMOSAICS", "key": "SVlgW0LRX1"}], "key": "tUkMCkYu6O"}, {"type": "text", "value": " open-source datasets include such baseline variations, we applied an additional preprocessing step to the signals shown in the figure to normalize the baseline to zero. To do so, the mean value of a 30 ms pre-stimulation window was computed for each trial and subtracted from the corresponding EMG signal. This normalization ensures consistent baseline levels across channels and reduces the risk of misinterpretation, for instance, mistaking baseline offsets (e.g., ", "key": "AIfDEeuubu"}, {"type": "inlineCode", "value": "2 mV", "position": {"start": {"line": 123, "column": 1}, "end": {"line": 123, "column": 1}}, "key": "O70idGVGZr"}, {"type": "text", "value": " vs. ", "position": {"start": {"line": 123, "column": 1}, "end": {"line": 123, "column": 1}}, "key": "pjvVa7DPCT"}, {"type": "inlineCode", "value": "0.5 mV", "position": {"start": {"line": 123, "column": 1}, "end": {"line": 123, "column": 1}}, "key": "oQIFtmwwn0"}, {"type": "text", "value": ") as differences in signal quality or responsiveness.", "position": {"start": {"line": 123, "column": 1}, "end": {"line": 123, "column": 1}}, "key": "tyzYpCK0MJ"}], "key": "XhthQAonuW"}], "key": "qCs9xKMeTU"}, {"type": "heading", "depth": 2, "position": {"start": {"line": 126, "column": 1}, "end": {"line": 126, "column": 1}}, "children": [{"type": "text", "value": "Results", "position": {"start": {"line": 126, "column": 1}, "end": {"line": 126, "column": 1}}, "key": "tDywhbDB53"}], "identifier": "results", "label": "Results", "html_id": "results", "implicit": true, "enumerator": "3", "key": "UTTey4MINh"}, {"type": "paragraph", "position": {"start": {"line": 128, "column": 1}, "end": {"line": 128, "column": 1}}, "children": [{"type": "text", "value": "In this section, we frequently refer to the heatmaps in each Figure. Each heatmap corresponds to a specific muscle from a subject and displays the average quantification of motor evoked potentials (", "key": "Y33xE3VTKt"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "y5VMFX0L9g"}], "key": "mXvI5yhZsL"}, {"type": "text", "value": "s) across different electrodes. Those electrode arrays allow us to map the topographic organization of the implanted motor region. Typically, the best-performing electrodes cluster spatially. Each query refers to an individual stimulation.", "key": "QU9LuP2wck"}], "key": "evjSGM4BYm"}, {"type": "heading", "depth": 3, "position": {"start": {"line": 130, "column": 1}, "end": {"line": 130, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 130, "column": 1}, "end": {"line": 130, "column": 1}}, "key": "dxlasuXg8L"}], "identifier": "dataset-1", "label": "Dataset 1", "html_id": "dataset-1", "implicit": true, "enumerator": "3.1", "key": "XY0PanJLeZ"}, {"type": "paragraph", "position": {"start": {"line": 132, "column": 1}, "end": {"line": 132, "column": 1}}, "children": [{"type": "strong", "position": {"start": {"line": 132, "column": 1}, "end": {"line": 132, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 132, "column": 1}, "end": {"line": 132, "column": 1}}, "key": "EsVg2ubLgt"}], "key": "h62ua7gnJP"}, {"type": "text", "value": " was collected during in vivo sessions that involved repeated stimulations of electrode locations in M1. These stimulation sessions were initially conducted on sedated capuchins and on awake rats and macaques. The average ", "key": "qULesL9kNc"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "pI4gQFWo92"}], "key": "T52zj2FVKy"}, {"type": "text", "value": " responses across spatial locations show a topographic organization of M1 such that nearby cortical locations have similar ", "key": "W0vqKnK6gU"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "UPWW4sU9BP"}], "key": "MhiiH99WAO"}, {"type": "text", "value": " patterns (Figure ", "key": "aqOhzTW1OB"}, {"type": "crossReference", "position": {"start": {"line": 132, "column": 1}, "end": {"line": 132, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "zbhJzubJvo"}, {"type": "text", "value": "1", "key": "ZeTxAKhvSD"}], "identifier": "fig1label", "label": "fig1label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "1", "resolved": true, "html_id": "fig1label", "key": "XbiqFCb0aa"}, {"type": "text", "value": " A.). While identifying the optimal electrode in this condition may seem straightforward, it presents significant challenges. The heatmaps represent averages of ", "key": "DpXhgL0RCi"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "hKJTvynjf7"}], "key": "VAwVvZUdCI"}, {"type": "text", "value": ", but individual responses are influenced by excitability, noise factors, and possibly non-stationarity, leading to considerable variability. This variability can obscure important details at the single-trial level. In Figure ", "key": "R798Wn6w4t"}, {"type": "crossReference", "position": {"start": {"line": 132, "column": 1}, "end": {"line": 132, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "qfZ4G6OZh7"}, {"type": "text", "value": "1", "key": "Li6rNwEAYn"}], "identifier": "fig1label", "label": "fig1label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "1", "resolved": true, "html_id": "fig1label", "key": "B80A9SefGy"}, {"type": "text", "value": " B., the upper-left panel displays the average response across multiple stimulations delivered through a specific electrode, providing a global overview of the evoked activity. In contrast, the two other panels offer a more detailed perspective : the distribution of peak amplitudes reveals the consistency of responses across trials, while the stack of individual traces allows visualization of how responses evolve over time. Given the goal of minimizing the number of queries, the task becomes finding the right balance between using enough queries for a robust solution and limiting the search to minimize stimulation.", "position": {"start": {"line": 132, "column": 1}, "end": {"line": 132, "column": 1}}, "key": "nNTZKZZSPT"}], "key": "ncfbnwQzqi"}, {"type": "container", "kind": "figure", "children": [{"type": "output", "id": "leCc_Tq6WsqH-b8a1ZNEO", "data": [{"output_type": "display_data", "metadata": {}, "data": {"text/plain": {"content": "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous \u2026", "content_type": "text/plain"}, "image/png": {"content_type": "image/png", "hash": "7953f7816b037e6022e61f94ca1d5789", "path": "/7953f7816b037e6022e61f94ca1d5789.png"}, "text/html": {"content_type": "text/html", "hash": "06145f7a246c2871e36383a31a59f30b", "path": "/06145f7a246c2871e36383a31a59f30b.html"}, "application/vnd.jupyter.widget-view+json": {"content": "{\"version_major\":2,\"version_minor\":0,\"model_id\":\"dff37866723a487ebd0cc47277acb779\"}", "content_type": "application/vnd.jupyter.widget-view+json"}}}, {"output_type": "display_data", "metadata": {}, "data": {"text/plain": {"content": "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous \u2026", "content_type": "text/plain"}, "image/png": {"content_type": "image/png", "hash": "609ae0149cf529c9cb60510e73661805", "path": "/609ae0149cf529c9cb60510e73661805.png"}, "text/html": {"content_type": "text/html", "hash": "0173905b26f353a28223fac9b5560a24", "path": "/0173905b26f353a28223fac9b5560a24.html"}, "application/vnd.jupyter.widget-view+json": {"content": "{\"version_major\":2,\"version_minor\":0,\"model_id\":\"15627e5b81c84466958d7c030eb33501\"}", "content_type": "application/vnd.jupyter.widget-view+json"}}}], "key": "eAPqafcsvv"}, {"type": "caption", "children": [{"type": "paragraph", "position": {"start": {"line": 137, "column": 1}, "end": {"line": 138, "column": 1}}, "children": [{"type": "captionNumber", "kind": "figure", "label": "fig1label", "identifier": "fig1label", "html_id": "fig1label", "enumerator": "1", "children": [{"type": "text", "value": "Figure\u00a0", "key": "zl9iJDqfMo"}, {"type": "text", "value": "1", "key": "zBPuKRG1tT"}, {"type": "text", "value": ":", "key": "bdgFTxC1nZ"}], "template": "Figure\u00a0%s:", "key": "ZdnFFkbRue"}, {"type": "strong", "position": {"start": {"line": 137, "column": 1}, "end": {"line": 137, "column": 1}}, "children": [{"type": "text", "value": "A.  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Red color hilights outliered trials.", "key": "sS1vpA4Eqk"}], "key": "o52QEmou1o"}], "key": "Vj9c4GpXN4"}], "key": "nJfr9DfZVX"}], "label": "fig1label", "identifier": "fig1label", "enumerator": "1", "html_id": "fig1label", "source": {"url": "/neurolibre-00033/figure-cebus", "label": "figCebcell", "kind": "Notebook", "slug": "figure-cebus", "location": "/content/figure_cebus.ipynb"}, "key": "kSsslQw6gf"}, {"type": "paragraph", "position": {"start": {"line": 144, "column": 1}, "end": {"line": 144, "column": 1}}, "children": [{"type": "text", "value": "The clear topographic organization of the responses observed in sedated ", "key": "KWRHNYpLLN"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "PCAbk5D8xs"}], "key": "JaeUCvsmGC"}, {"type": "text", "value": "s become considerably noisier and more selective in awake ", "key": "p1noZXZ7kM"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "of5ogHS1J2"}], "key": "LTwnz6RiBi"}, {"type": "text", "value": "s (see Figure ", "key": "iKuJU7VGQV"}, {"type": "crossReference", "position": {"start": {"line": 144, "column": 1}, "end": {"line": 144, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "Z2jPjkTygx"}, {"type": "text", "value": "2", "key": "tncRJ95DdL"}], "identifier": "fig2label", "label": "fig2label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "2", "resolved": true, "html_id": "fig2label", "key": "fjGBWs98b7"}, {"type": "text", "value": " A.). These ", "key": "O8dX9cKBRj"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "Wahwto03tc"}], "key": "IhooJMuaVs"}, {"type": "text", "value": " implants were older, and the quality of the electrical interface at the EMG wire-muscle contact can degrade over time, potentially contributing to variations in noise levels in the recorded muscle responses across subjects. We can also identify two ranges of electrodes (column ", "key": "dsHNakZYfp"}, {"type": "inlineCode", "value": "8", "position": {"start": {"line": 144, "column": 1}, "end": {"line": 144, "column": 1}}, "key": "TL0dAlWK57"}, {"type": "text", "value": " and ", "position": {"start": {"line": 144, "column": 1}, "end": {"line": 144, "column": 1}}, "key": "fQl3ftV0PL"}, {"type": "inlineCode", "value": "9", "position": {"start": {"line": 144, "column": 1}, "end": {"line": 144, "column": 1}}, "key": "Z7JmMZDAEv"}, {"type": "text", "value": " in Figure ", "position": {"start": {"line": 144, "column": 1}, "end": {"line": 144, "column": 1}}, "key": "B3wNoXiSXn"}, {"type": "crossReference", "position": {"start": {"line": 144, "column": 1}, "end": {"line": 144, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "NkvwXTDyZw"}, {"type": "text", "value": "2", "key": "klCWVChp8h"}], "identifier": "fig2label", "label": "fig2label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "2", "resolved": true, "html_id": "fig2label", "key": "VbCYWH2SqV"}, {"type": "text", "value": " A.) that consistently exhibit very low signal amplitudes across all muscles. This suggests that these portions of the electrode matrix may not have been in full contact with the tissue. Additionally, the ", "key": "adjunJ8jRP"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "NHjJcUf100"}], "key": "WatYOjcCN4"}, {"type": "text", "value": "s were awake, which may have further contaminated ", "key": "LirW8DyjDz"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "trfgaOTjMs"}], "key": "gTA0dTserm"}, {"type": "text", "value": "s with spontaneous muscle activations, which are possibly present even when the condition of no muscle activity pre-stimulation is enforced. Consequently, this dataset provides an opportunity to test optimization approaches on data that differ significantly from the previous dataset.", "key": "SFAfiuxzg3"}], "key": "EWGeYBDOXR"}, {"type": "container", "kind": "figure", "children": [{"type": "output", "id": "tagECBZn8KwuPSM7ykt_l", "data": [{"output_type": "display_data", "metadata": {}, "data": {"text/plain": {"content": "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous \u2026", "content_type": "text/plain"}, "image/png": {"content_type": "image/png", "hash": "67e4edb313621f6981807a513ec25d5b", "path": "/67e4edb313621f6981807a513ec25d5b.png"}, "text/html": {"content_type": "text/html", "hash": "3241ec86eeaa951cc9f463687fa1a9cd", "path": "/3241ec86eeaa951cc9f463687fa1a9cd.html"}, "application/vnd.jupyter.widget-view+json": {"content": "{\"version_major\":2,\"version_minor\":0,\"model_id\":\"8e93dbd862de46d08f6b55821bb05696\"}", "content_type": "application/vnd.jupyter.widget-view+json"}}}, {"output_type": "display_data", "metadata": {}, "data": {"text/plain": {"content": "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous \u2026", "content_type": "text/plain"}, "image/png": {"content_type": "image/png", "hash": "f552a9a30d91955202c6d59cddeea603", "path": "/f552a9a30d91955202c6d59cddeea603.png"}, "text/html": {"content_type": "text/html", "hash": "c62f6518ca8b2cd55038e3c0d277979a", "path": "/c62f6518ca8b2cd55038e3c0d277979a.html"}, "application/vnd.jupyter.widget-view+json": {"content": "{\"version_major\":2,\"version_minor\":0,\"model_id\":\"51fa522e484a4c1fa300d7c63462554c\"}", "content_type": "application/vnd.jupyter.widget-view+json"}}}], "key": "zMh5thZfod"}, {"type": "caption", "children": [{"type": "paragraph", "position": {"start": {"line": 149, "column": 1}, "end": {"line": 150, "column": 1}}, "children": [{"type": "captionNumber", "kind": "figure", "label": "fig2label", "identifier": "fig2label", "html_id": "fig2label", "enumerator": "2", "children": [{"type": "text", "value": "Figure\u00a0", "key": "tvwr6hKOYD"}, {"type": "text", "value": "2", "key": "v5fCIBMny3"}, {"type": "text", "value": ":", "key": "FaalIUanab"}], "template": "Figure\u00a0%s:", "key": "M3ykyfZr3W"}, {"type": "strong", "position": {"start": {"line": 149, "column": 1}, "end": {"line": 149, "column": 1}}, "children": [{"type": "text", "value": "A.  Heatmap of motor responses across a 96-electrode array in M1 of an awaken Macaque :", "position": {"start": {"line": 149, "column": 1}, "end": {"line": 149, "column": 1}}, "key": "cxRS7R3yhh"}], "key": "F8yR8NGS8Y"}, {"type": "text", "value": " This panel displays the mean motor responses for a selected muscle, averaged across repetitions, for each electrode in a 96-electrode array (10x10 grid with 4 unused electrodes). To view data for a specific muscle, select the desired muscle from the list on the right. The available muscles are: First Dorsal Interosseous (", "key": "UfhW7oG4Fz"}, {"type": "abbreviation", "title": "First Dorsal Interosseous", "children": [{"type": "text", "value": "FDI", "key": "F53gIe8uom"}], "key": "K2GJs3uqie"}, {"type": "text", "value": "), Flexor Digitorum Superficialis (", "key": "Yab7bI7LFb"}, {"type": "abbreviation", "title": "Flexor Digitorum Superficialis", "children": [{"type": "text", "value": "FDS", "key": "HpuJtNbOCV"}], "key": "bcWlRqs2YB"}, {"type": "text", "value": "), Extensor Carpi Radialis (", "key": "vXLMBI9goQ"}, {"type": "abbreviation", "title": "Extensor Carpi Radialis", "children": [{"type": "text", "value": "ECR", "key": "o7V8o5zj4s"}], "key": "wIlblIqbWO"}, {"type": "text", "value": "), Extensor Digitorum Communis (", "key": "lP5CjWWaQ9"}, {"type": "abbreviation", "title": "Extensor Digitorum Communis", "children": [{"type": "text", "value": "EDC", "key": "qlWtS4QfKH"}], "key": "WHavCKQF2i"}, {"type": "text", "value": "). The ", "key": "CyxABH2K9S"}, {"type": "abbreviation", "title": "Extensor Digitorum Communis", "children": [{"type": "text", "value": "EDC", "key": "a2akVaNO4d"}], "key": "JdUXmMAQTq"}, {"type": "text", "value": " muscle exhibits only noisy signals and does not contain clear evoked responses. However, it serves as a useful example of how a single stimulation contaminated by an artefact can significantly distort the average response. This highlights the importance of analyzing multiple repetitions of the same stimulation to ensure that the averaged signal accurately reflects true underlying activity rather than artefactual noise.\n", "key": "miT52M0cm1"}, {"type": "strong", "position": {"start": {"line": 149, "column": 1}, "end": {"line": 149, "column": 1}}, "children": [{"type": "text", "value": "B.  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Red color hilights outliered trials.", "key": "M5zr8sfD47"}], "key": "mXXGLp9ZDR"}], "key": "YDAnipSPF7"}], "key": "Vm0MAgNKvf"}], "label": "fig2label", "identifier": "fig2label", "enumerator": "2", "html_id": "fig2label", "source": {"url": "/neurolibre-00033/figure-macaque", "label": "figMcqcell", "kind": "Notebook", "slug": "figure-macaque", "location": "/content/figure_macaque.ipynb"}, "key": "Ss1NGfgWf9"}, {"type": "paragraph", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "children": [{"type": "text", "value": "High selectivity becomes particularly problematic when the search space is expanded (such as by adding additional parameters like stimulation amplitude and frequency) and even more so in noisy conditions. If it makes it harder to identify the best electrode, the global maximum of the function to optimize, and increases the risk of getting stuck in local maxima during optimization. For example, while searching for the electrode that grants maximal response in the First Dorsal Interosseous muscle (see Figure ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "kUJqbIiP4U"}, {"type": "crossReference", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "hudNAizgeI"}, {"type": "text", "value": "2", "key": "jrQROVU7U1"}], "identifier": "fig2label", "label": "fig2label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "2", "resolved": true, "html_id": "fig2label", "key": "BSnUv5NsL9"}, {"type": "text", "value": " A.), one could easily get stuck at coordinates ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "HlQVIfaPwa"}, {"type": "inlineCode", "value": "(7,7)", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "yDc41FaRX7"}, {"type": "text", "value": " on the heatmap. If the algorithm hasn\u2019t yet queried the optimal electrode at coordinates ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "jCodbRZOoq"}, {"type": "inlineCode", "value": "(4,1)", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "qB48NdyJ86"}, {"type": "text", "value": ", and instead queries ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "YXmaoQBOph"}, {"type": "inlineCode", "value": "(7,7)", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "mBoPg3GHRp"}, {"type": "text", "value": "  at a given query q, it will produce the best result thus far. The algorithm would then continue to exploit the local maximum around ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "HHBvhw6nY6"}, {"type": "inlineCode", "value": "(7,7)", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "S54856RX1K"}, {"type": "text", "value": "  without knowing that a better option exists unless it explores very specific electrodes ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "cBbBKD5ige"}, {"type": "inlineCode", "value": "(4,1)", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "UEtY12uhRP"}, {"type": "text", "value": " or ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "OoaT9IXHtH"}, {"type": "inlineCode", "value": "(5,1)", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "KId0Msepqm"}, {"type": "text", "value": " (see Figure ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "YTiFrNqSKB"}, {"type": "crossReference", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "wxHA9jIgR4"}, {"type": "text", "value": "2", "key": "iniPG3iqzt"}], "identifier": "fig2label", "label": "fig2label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "2", "resolved": true, "html_id": "fig2label", "key": "ND3q11maKG"}, {"type": "text", "value": " B.). With around 50 electrodes to query in a limited number of stimulations, the algorithm\u2019s exploration strategy becomes critical to avoid local maxima. This issue of local maxima and high selectivity is also observed in awake rats, as seen in the Left Medial Gastrocnemius available in ", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "RI58QkV4Py"}, {"type": "strong", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 156, "column": 1}, "end": {"line": 156, "column": 1}}, "key": "BXp8Vzeci0"}], "key": "Ganz2hDauP"}, {"type": "text", "value": " on OSF. However, the smaller array (32 electrodes, compared to 96 for ", "key": "sDNz3KBbIJ"}, {"type": "abbreviation", "title": "non-human primates", "children": [{"type": "text", "value": "NHP", "key": "cMgimnc6T4"}], "key": "uJ9zcjbwmE"}, {"type": "text", "value": "s) reduces the complexity of the search.", "key": "OrBTqCDS9C"}], "key": "ZdqxlaSp3C"}, {"type": "paragraph", "position": {"start": {"line": 158, "column": 1}, "end": {"line": 158, "column": 1}}, "children": [{"type": "text", "value": "The temporal aspect of the responses can play an important role in the nature of the response. In any scenario from this dataset, the stronger ", "key": "ubXkq89q75"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "qQFnDoArZn"}], "key": "CyrX1SIhSj"}, {"type": "text", "value": " are peaking at the same time as we can observe in the stacked ", "key": "W4vK0HU5jg"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "X4mjzd3nKj"}], "key": "Arrm7K3qRY"}, {"type": "text", "value": " where deeper blue lines are vertically crossing all the trials.", "key": "NE6BTRsvWO"}], "key": "cDDMHMw024"}, {"type": "paragraph", "position": {"start": {"line": 160, "column": 1}, "end": {"line": 160, "column": 1}}, "children": [{"type": "text", "value": "Considering noise (such as muscle activations unrelated to stimulation), some responses may convey misleading information about the overall response pattern. A clear example is provided by the ", "key": "jLN4N4YIHM"}, {"type": "abbreviation", "title": "Extensor Digitorum Communis", "children": [{"type": "text", "value": "EDC", "key": "pukQJVWM0H"}], "key": "XfiUeMkTlP"}, {"type": "text", "value": " muscle in Figure ", "key": "duzh75U1pq"}, {"type": "crossReference", "position": {"start": {"line": 160, "column": 1}, "end": {"line": 160, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "uZoXPjcSSl"}, {"type": "text", "value": "2", "key": "tqEzy1QIVk"}], "identifier": "fig2label", "label": "fig2label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "2", "resolved": true, "html_id": "fig2label", "key": "ITsNoAkzYE"}, {"type": "text", "value": ". The response map indicates a high activity level for electrode ", "position": {"start": {"line": 160, "column": 1}, "end": {"line": 160, "column": 1}}, "key": "M6LjBLY4b4"}, {"type": "inlineCode", "value": "(0,6)", "position": {"start": {"line": 160, "column": 1}, "end": {"line": 160, "column": 1}}, "key": "AhFbpI56Wu"}, {"type": "text", "value": ". However, upon closer examination of the stacked EMG traces, it becomes evident that this apparent response is driven almost entirely by a single trial, the 18th stimulation, which shows an isolated increase in ", "key": "FpCtZFfFPK"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "gWoRa4NFI7"}], "key": "cMd55fTyuh"}, {"type": "text", "value": " amplitude. Notably, this sharp deflection is also visible in other channels, such as electrode", "key": "Q6bPozbLxP"}, {"type": "inlineCode", "value": "(7,2)", "position": {"start": {"line": 160, "column": 1}, "end": {"line": 160, "column": 1}}, "key": "lvu71P9C8d"}, {"type": "text", "value": ", but occurs at a time (~170 ms post-stimulation) that is unrelated to the actual stimulation event. This suggests the presence of a transient artefact, underscoring the importance of examining individual trials alongside average responses to avoid misinterpretation.", "position": {"start": {"line": 160, "column": 1}, "end": {"line": 160, "column": 1}}, "key": "gspyRUleJt"}], "key": "VnxD2HyWLf"}, {"type": "paragraph", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "children": [{"type": "text", "value": "Identifying these outliers in real time is challenging, but it is valuable to do so afterward as it raises awareness of their potential impact on optimization processes. The parameter ", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "key": "MHeqMFCjKM"}, {"type": "inlineCode", "value": "is_valid", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "key": "MeYGPQkNCh"}, {"type": "text", "value": " classifies outliers in two categories: those that can be excluded due to excessive EMG activity prior to stimulation and those that cannot be excluded, where no prior EMG activity was observed, but the response amplitude is unusually high (such as the 18th trial of electrode ", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "key": "nxIRdd42li"}, {"type": "inlineCode", "value": "(0,6)", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "key": "cqSW3njqZk"}, {"type": "text", "value": " in ECD muscle, Figure ", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "key": "h34mf1gtRI"}, {"type": "crossReference", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "PevuRjv4cn"}, {"type": "text", "value": "2", "key": "K1P6Ua8Ili"}], "identifier": "fig2label", "label": "fig2label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "2", "resolved": true, "html_id": "fig2label", "key": "MsSCv9h2X2"}, {"type": "text", "value": "). Accurate online processing can easily reject the first of the two classes, while the second is unlikely to be rejected in a real use case. The first category is highlighted in red in the stack ", "key": "VGr6d3ss0R"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "djei98wbCO"}], "key": "KUk4n0P70J"}, {"type": "text", "value": " figures. The mean and standard deviation of responses in ", "key": "qZ18g6ccE6"}, {"type": "strong", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "key": "trN3GWCt4P"}], "key": "NNZ3qqEvSZ"}, {"type": "text", "value": " still include these outliers. A data scientist wishing to remove these spurious responses from the optimization \u201cground truth\u201d, or objective value, must though recalculate the mean responses.", "position": {"start": {"line": 162, "column": 1}, "end": {"line": 162, "column": 1}}, "key": "wLWQReneaI"}], "key": "HjRWSZDWNo"}, {"type": "admonition", "children": [{"type": "admonitionTitle", "children": [{"type": "text", "value": "Funding", "position": {"start": {"line": 164, "column": 1}, "end": {"line": 164, "column": 1}}, "key": "vBAF8YQSSv"}], "key": "x5wglTJOni"}, {"type": "paragraph", "position": {"start": {"line": 166, "column": 1}, "end": {"line": 166, "column": 1}}, "children": [{"type": "text", "value": "The collection of ", "position": {"start": {"line": 166, "column": 1}, "end": {"line": 166, "column": 1}}, "key": "Od1ujNOkCK"}, {"type": "strong", "position": {"start": {"line": 166, "column": 1}, "end": {"line": 166, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 166, "column": 1}, "end": {"line": 166, "column": 1}}, "key": "sE2SASCaSi"}], "key": "aIGFbeyPWd"}, {"type": "text", "value": " was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC; RGPIN-2022-04210).", "position": {"start": {"line": 166, "column": 1}, "end": {"line": 166, "column": 1}}, "key": "L1FbMSnXzh"}], "key": "wfMgPcDIWC"}], "key": "sxSub9Au0c"}, {"type": "heading", "depth": 3, "position": {"start": {"line": 169, "column": 1}, "end": {"line": 169, "column": 1}}, "children": [{"type": "text", "value": "Dataset 2", "position": {"start": {"line": 169, "column": 1}, "end": {"line": 169, "column": 1}}, "key": "tRNol9WNEH"}], "identifier": "dataset-2", "label": "Dataset 2", "html_id": "dataset-2", "implicit": true, "enumerator": "3.2", "key": "c4UfqN0pX8"}, {"type": "paragraph", "position": {"start": {"line": 171, "column": 1}, "end": {"line": 171, "column": 1}}, "children": [{"type": "text", "value": "This dataset was collected from four anesthetized rats, resulting in smooth topographic organization of the spinal cord with high variance for the average responses. Similar to capuchin in ", "position": {"start": {"line": 171, "column": 1}, "end": {"line": 171, "column": 1}}, "key": "k0ht7ljs7v"}, {"type": "strong", "position": {"start": {"line": 171, "column": 1}, "end": {"line": 171, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 171, "column": 1}, "end": {"line": 171, "column": 1}}, "key": "HBkKFD8R8B"}], "key": "TzGWJ7FkoH"}, {"type": "text", "value": ", the relaxed muscle state in sedated animals, with no intention of motor control or reflex interference, contributes to the smooth responses. However, unlike ", "position": {"start": {"line": 171, "column": 1}, "end": {"line": 171, "column": 1}}, "key": "oZ9ueiL2pu"}, {"type": "strong", "position": {"start": {"line": 171, "column": 1}, "end": {"line": 171, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 171, "column": 1}, "end": {"line": 171, "column": 1}}, "key": "VbQkTSgUeB"}], "key": "Gdq8gi2Tm4"}, {"type": "text", "value": ", this dataset involves spinal cord (spinal cord) stimulation, leading to some key differences in the results. One notable distinction is that the high-response electrodes are more widely distributed spatially, which may be attributed to the different spatial recruitment properties of spinal cord stimulation compared to motor cortex stimulation.  Because dorsal spinal cord stimulation is, from a circuit perspective, closer to the muscle target than M1 stimulation, there is less variability in the responses. Indeed, less synapses (and thus less pulses) lead to a higher repeatability of the responses. This very clear repeatability (a straight deep blue line across each trial in stack ", "key": "TNq0HGNYFr"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "kFalrUe3mA"}], "key": "Gg4IyE0vwk"}, {"type": "text", "value": " figures) makes the identification of outliers easier, and they are also listed in a parameter is_valid and highlighted in red in the stack ", "key": "lPHpDnAgbe"}, {"type": "abbreviation", "title": "Motor Evoked Potential", "children": [{"type": "text", "value": "MEP", "key": "Oi7lhlxwsC"}], "key": "lFBKAz9tdH"}, {"type": "text", "value": " figures. In this case, the mean and the standard deviation were computed without those outliers.", "key": "SnYVQ9z71R"}], "key": "s4uxnmVLGR"}, {"type": "container", "kind": "figure", "children": [{"type": "output", "id": "XLDjpJ7vpR3O8p_eq2lnL", "data": [{"output_type": "display_data", "metadata": {}, "data": {"text/plain": {"content": "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous \u2026", "content_type": "text/plain"}, "image/png": {"content_type": "image/png", "hash": "1edfe52aea9cbe0f24a2031956faa204", "path": "/1edfe52aea9cbe0f24a2031956faa204.png"}, "text/html": {"content_type": "text/html", "hash": "9042115d7bc4e6c1170aa9aba6117e3a", "path": "/9042115d7bc4e6c1170aa9aba6117e3a.html"}, "application/vnd.jupyter.widget-view+json": {"content": "{\"version_major\":2,\"version_minor\":0,\"model_id\":\"d9a35a31c4c0435995e3b674af09b8f4\"}", "content_type": "application/vnd.jupyter.widget-view+json"}}}, {"output_type": "display_data", "metadata": {}, "data": {"text/plain": {"content": "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous \u2026", "content_type": "text/plain"}, "image/png": {"content_type": "image/png", "hash": "d2ae14d9b3d5f02204f79eb301e01465", "path": "/d2ae14d9b3d5f02204f79eb301e01465.png"}, "text/html": {"content_type": "text/html", "hash": "5b43c6f833374d0d872a13e161f69a06", "path": "/5b43c6f833374d0d872a13e161f69a06.html"}, "application/vnd.jupyter.widget-view+json": {"content": "{\"version_major\":2,\"version_minor\":0,\"model_id\":\"15ea4c65785244c38c87a3c1452e7231\"}", "content_type": "application/vnd.jupyter.widget-view+json"}}}], "key": "cwIGjdZSwO"}, {"type": "caption", "children": [{"type": "paragraph", "position": {"start": {"line": 176, "column": 1}, "end": {"line": 178, "column": 1}}, "children": [{"type": "captionNumber", "kind": "figure", "label": "fig3label", "identifier": "fig3label", "html_id": "fig3label", "enumerator": "3", "children": [{"type": "text", "value": "Figure\u00a0", "key": "FYJYCot5aD"}, {"type": "text", "value": "3", "key": "XKtjyKb4uZ"}, {"type": "text", "value": ":", "key": "O5uzydLAK2"}], "template": "Figure\u00a0%s:", "key": "ZeRAk0oaNc"}, {"type": "strong", "position": {"start": {"line": 176, "column": 1}, "end": {"line": 176, "column": 1}}, "children": [{"type": "text", "value": "A.  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The available muscles are: Right Triceps (", "key": "kjTu2Sh1J5"}, {"type": "abbreviation", "title": "Right Triceps", "children": [{"type": "text", "value": "R Tr", "key": "lCzVilWGC0"}], "key": "Unkx0MPfbo"}, {"type": "text", "value": "), Right Biceps (", "key": "rdyvKNjTdl"}, {"type": "abbreviation", "title": "Right Biceps", "children": [{"type": "text", "value": "R Bi", "key": "kz4mZUIDNy"}], "key": "VN1bcA5q5X"}, {"type": "text", "value": "), Right Torso (", "key": "sscOwi4aST"}, {"type": "abbreviation", "title": "Right Torso", "children": [{"type": "text", "value": "R Trs", "key": "uOiFMC3Em4"}], "key": "tS9csMIsG8"}, {"type": "text", "value": "), Right Wrist flexor (", "key": "ToikxYTaeP"}, {"type": "abbreviation", "title": "Right Wrist flexor", "children": [{"type": "text", "value": "R WrFlex", "key": "MwpHVbPZ1e"}], "key": "MJXT05VRz0"}, {"type": "text", "value": "), Right Spinal Deltoid (", "key": "wZ4cE9OMEu"}, {"type": "abbreviation", "title": "Right Spinal Deltoid", "children": [{"type": "text", "value": "R SpDel", "key": "ibiKYKli8F"}], "key": "Tcaapdg3jl"}, {"type": "text", "value": "), Left Triceps (", "key": "pkFCD1HyaW"}, {"type": "abbreviation", "title": "Left Triceps", "children": [{"type": "text", "value": "L Tr", "key": "tx4FO769is"}], "key": "WeJYrXTHon"}, {"type": "text", "value": "),\nLeft Biceps (", "key": "aTwicjOphj"}, {"type": "abbreviation", "title": "Left Biceps", "children": [{"type": "text", "value": "L Bi", "key": "xHe12SOwRM"}], "key": "qkTVTSuswa"}, {"type": "text", "value": "), Left Tors (", "key": "drIH59Vm5b"}, {"type": "abbreviation", "title": "Left Tors", "children": [{"type": "text", "value": "L Trs", "key": "rDn7cDXGkz"}], "key": "oyNZM7cNW4"}, {"type": "text", "value": "), Left Wrist flexor (L WrFlex), Left Spinal Deltoid (L SpDel).\n", "key": "FIeTpH12aq"}, {"type": "strong", "position": {"start": {"line": 176, "column": 1}, "end": {"line": 176, "column": 1}}, "children": [{"type": "text", "value": "B.  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Indeed, the excitability can increase and decrease drastically in a few queries (like for electrode ", "position": {"start": {"line": 185, "column": 1}, "end": {"line": 185, "column": 1}}, "key": "v9yi099zyF"}, {"type": "inlineCode", "value": "(2,4)", "position": {"start": {"line": 185, "column": 1}, "end": {"line": 185, "column": 1}}, "key": "NEMLpJRwZj"}, {"type": "text", "value": " in Left Biceps  (see Figure ", "position": {"start": {"line": 185, "column": 1}, "end": {"line": 185, "column": 1}}, "key": "TwBPJuj5Yu"}, {"type": "crossReference", "position": {"start": {"line": 185, "column": 1}, "end": {"line": 185, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "GCkazR8fIt"}, {"type": "text", "value": "3", "key": "VP4nYvPvTN"}], "identifier": "fig3label", "label": "fig3label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "3", "resolved": true, "html_id": "fig3label", "key": "A4AI2kc41Q"}, {"type": "text", "value": " B.)), and some electrodes are losing contact on half of the process (like in electrode ", "position": {"start": {"line": 185, "column": 1}, "end": {"line": 185, "column": 1}}, "key": "poq1ZhSkvR"}, {"type": "inlineCode", "value": "(4,3)", "position": {"start": {"line": 185, "column": 1}, "end": {"line": 185, "column": 1}}, "key": "kOMHtUPr0I"}, {"type": "text", "value": " in Left Biceps), making it harder to identify a best electrode and to take a decision on the definition of what is the best electrode. This phenomenon suggests potential future use of this dataset to take into account the non-stationarity of the responses.", "position": {"start": {"line": 185, "column": 1}, "end": {"line": 185, "column": 1}}, "key": "dxJ28OmSC8"}], "key": "Ujss19Iiho"}, {"type": "paragraph", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "children": [{"type": "text", "value": "The higher variance in this dataset tends to blur the distinction between the best average solution and its neighboring electrodes. This makes it easy to identify the best location area, but also more challenging to point out the precise optimal electrode. As the variability in the responses increases, it becomes more likely that, at query q, the best electrode yields a lower response than nearby ones. For instance, in the Right Biceps muscle  (see Figure ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "NAkrzjVOtY"}, {"type": "crossReference", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "children": [{"type": "text", "value": "Figure\u00a0", "key": "RoKkVKItbq"}, {"type": "text", "value": "3", "key": "GQ6d50PuEK"}], "identifier": "fig3label", "label": "fig3label", "kind": "figure", "template": "Figure\u00a0%s", "enumerator": "3", "resolved": true, "html_id": "fig3label", "key": "Qy8h9RUhL6"}, {"type": "text", "value": " A.), the peak amplitude distribution from the best electrode (coordinates ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "WQkPhsg4SI"}, {"type": "inlineCode", "value": "(2,5)", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "i43wBuTUUc"}, {"type": "text", "value": ") is centered at ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "CNUxpUxJpE"}, {"type": "inlineCode", "value": "13.1 mV", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "tHA6xa1tm9"}, {"type": "text", "value": ", but there is an outlier stimulation yielding a response of ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "Mirm3aMCES"}, {"type": "inlineCode", "value": "11.2 mV", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "B7JEGNIja2"}, {"type": "text", "value": ". Meanwhile, the electrode at coordinates ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "PyJpGR5BMq"}, {"type": "inlineCode", "value": "(2,4)", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "TieKp1wvv3"}, {"type": "text", "value": " has stimulations with outputs around ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "dyBBzSowKp"}, {"type": "inlineCode", "value": "13.1 mV", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "X3mRGwyR39"}, {"type": "text", "value": ". If an algorithm repeatedly queries electrode ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "GqpyPKeqcq"}, {"type": "inlineCode", "value": "(2,4)", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "UIRyJXiFDI"}, {"type": "text", "value": " and obtains consecutively good motor responses, while a single query of electrode ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "mBoShSGutk"}, {"type": "inlineCode", "value": "(2,5)", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "jLxNh8CNzz"}, {"type": "text", "value": " produces an outlier of ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "GHJOceXPO1"}, {"type": "inlineCode", "value": "11.2 mV", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "zgXTkZHlzG"}, {"type": "text", "value": ", the algorithm might incorrectly infer that electrode ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "nldVgV7yxf"}, {"type": "inlineCode", "value": "(2,4)", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "mmo4a7ANfy"}, {"type": "text", "value": " is superior. Although ", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "BSkjfPe94I"}, {"type": "inlineCode", "value": "(2,4)", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "rdxJiEKE7s"}, {"type": "text", "value": " is not the global maximum, it remains a strong candidate because it provides stable, high-quality responses and is situated within the highest region of the heatmap.", "position": {"start": {"line": 187, "column": 1}, "end": {"line": 187, "column": 1}}, "key": "RNwWGSixnA"}], "key": "NxjHBrm90R"}, {"type": "paragraph", "position": {"start": {"line": 189, "column": 1}, "end": {"line": 189, "column": 1}}, "children": [{"type": "text", "value": "Another key insight from this dataset is the spatial organization of the spinal cord for motor control. There is a clear lateralization, with the right side of the spinal cord predominantly evoking stronger responses in muscles on the right side of the body, and the left side evoking responses in left-side muscles. Additionally, there appears to be spatial clustering in spinal cord sites evoking motor potential in specific muscles. The spatial organization is non-trivial given that the dorsal aspect of the spinal cord, which we stimulated, is associated with afferent pathways, and motor output depends on reflex responses ", "position": {"start": {"line": 189, "column": 1}, "end": {"line": 189, "column": 1}}, "key": "ChJaGJT1JB"}, {"type": "citeGroup", "kind": "parenthetical", "position": {"start": {"line": 189, "column": 1}, "end": {"line": 189, "column": 1}}, "children": [{"type": "cite", "identifier": "capogrosso2013computational", "label": "capogrosso2013computational", "kind": "parenthetical", "position": {"start": {"line": 189, "column": 631}, "end": {"line": 189, "column": 659}}, "children": [{"type": "text", "value": "Capogrosso ", "key": "yl74WxlgD7"}, {"type": "emphasis", "children": [{"type": "text", "value": "et al.", "key": "a2fbuhdxyK"}], "key": "Yy6hC6PXak"}, {"type": "text", "value": ", 2013", "key": "MMtxy0oIM0"}], "enumerator": "29", "key": "FYTGbytiyS"}], "key": "DinrAiJmMC"}, {"type": "text", "value": ". This insight has significant implications for optimization in neuromodulation. The function linking stimulation parameters to motor responses is inherently complex and unknown, posing a \u201cblack-box\u201d optimization problem. 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For example, integrating the knowledge that stimulating the left (or right) dorsal spinal cord enhances motor responses on the corresponding side of the body allows the algorithm to narrow its spatial exploration. 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RGPIN-2023-04370) and New Frontiers in Research Fund Exploration (NFRFE-2022-00394).", "position": {"start": {"line": 214, "column": 1}, "end": {"line": 214, "column": 1}}, "key": "mwaRgGmhuu"}], "key": "laim02kxFy"}, {"type": "heading", "depth": 2, "position": {"start": {"line": 216, "column": 1}, "end": {"line": 216, "column": 1}}, "children": [{"type": "text", "value": "Declaration of competing interest", "position": {"start": {"line": 216, "column": 1}, "end": {"line": 216, "column": 1}}, "key": "MDa5HqWjvu"}], "identifier": "declaration-of-competing-interest", "label": "Declaration of competing interest", "html_id": "declaration-of-competing-interest", "implicit": true, "enumerator": "8", "key": "xIOA7jtfqU"}, {"type": "paragraph", "position": {"start": {"line": 218, "column": 1}, "end": {"line": 218, "column": 1}}, "children": [{"type": "text", "value": "The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.", "position": {"start": {"line": 218, "column": 1}, "end": {"line": 218, "column": 1}}, "key": "v4LmJYjyX0"}], "key": "TSnjBAD60d"}, {"type": "heading", "depth": 2, "position": {"start": {"line": 220, "column": 1}, "end": {"line": 220, "column": 1}}, "children": [{"type": "text", "value": "Acknowledgements", "position": {"start": {"line": 220, "column": 1}, "end": {"line": 220, "column": 1}}, "key": "yRMXkT28YN"}], "identifier": "acknowledgements", "label": "Acknowledgements", "html_id": "acknowledgements", "implicit": true, "enumerator": "9", "key": "rS1nVzpWie"}, {"type": "paragraph", "position": {"start": {"line": 222, "column": 1}, "end": {"line": 222, "column": 1}}, "children": [{"type": "text", "value": "The authors extend their gratitude to all scholars who have openly shared datasets for neurostimulation optimization, fostering the growth of the community. This includes the contributors who released ", "position": {"start": {"line": 222, "column": 1}, "end": {"line": 222, "column": 1}}, "key": "fPZo5iGwUj"}, {"type": "strong", "position": {"start": {"line": 222, "column": 1}, "end": {"line": 222, "column": 1}}, "children": [{"type": "text", "value": "Dataset 1", "position": {"start": {"line": 222, "column": 1}, "end": {"line": 222, "column": 1}}, "key": "fB6MLPCgjE"}], "key": "qug8T79AQn"}, {"type": "text", "value": " in 2021. ", "key": "DzTw3B0txr"}, {"type": "abbreviation", "title": "Neurostimulation Multi-scale Open-Source Across Interface, Conditions & Species", "children": [{"type": "text", "value": "NeuroMOSAICS", "key": "hW2ClatPRv"}], "key": "KsW8mTbBVA"}, {"type": "text", "value": " owes its existence to a steadfast community commitment to open science.", "key": "mtIllX9ekR"}], "key": "BYsC23oZSc"}], "key": "ulJd3r6jnt"}], "key": "lRWSVEPqh6"}, "references": {"cite": {"order": ["ting2021neurostimulation", "james2018neuromodulation", "schupbach2017directional", "anderson2018optimized", "de2021future", "won2020emerging", "jun2017fully", "tsai2017very", "pineau2009treating", "gao2023offline", "gebodh2021novel", "de2021predictive", "shukla2014towards", "shukla2012neural", "medaglia2020personalizing", "yu2021reinforcement", "arlotti2018eight", "rosa2015adaptive", "swann2018adaptive", "bonizzato2023autonomous", "choiniere2024gaussian", "laferriere2020hierarchical", "sarikhani2022automated", "aiello2023recalibration", "grahn2014restoration", "losanno2021bayesian", "rowald2022activity", "wagner2018targeted", "capogrosso2013computational", "wang2023machine", "guay2025robust", "greenhill2020bayesian"], "data": {"ting2021neurostimulation": {"label": "ting2021neurostimulation", "enumerator": "1", "doi": "10.3389/fnins.2021.649459", "html": "Ting, W. 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