{ "fetched_at": "2026-10-18T13:57:24Z", "source_url": "https://www.kaggle.com/competitions/brain-to-text-25/data", "pages": [ { "name": "data-description", "content": "## Overview\nThe [dataset](https://doi.org/10.5061/dryad.dncjsxm85) used in this competition consists of 10,948 sentences spoken by a single research participant as described in [Card et al. “An Accurate and Rapidly Calibrating Speech Neuroprosthesis” (2024) *New England Journal of Medicine*](https://www.nejm.org/doi/full/10.1056/NEJMoa2314132). For each sentence, we provide the transcript of what the participant was attempting to say, along with the corresponding time series of neural spiking activity recorded from 256 microelectrodes in speech motor cortex. The dataset contains predefined *train*, *val*, and *test* partitions. The train and val partitions include the sentence labels, and you may repartition them if desired. The *test* partition does not include sentence labels and will be used for competition evaluation. Your goal will be to train a model to predict spoken words from neural data using the *train* and *val* data splits, and then use that model to predict the words being spoken during each *test* trial.\n\nThe dataset contains a mixture of speaking strategies and sentence corpuses (see table, below) on a block-by-block basis. A description of which blocks correspond to which corpuses and data splits can be found [here](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/blob/main/data/t15_copyTaskData_description.csv). To make the competition more challenging and better approximate real-world use, we do not provide labels as to the speaking strategy for each block.\n\n## Differences from Brain-to-Text '24\nThere are some notable differences between this dataset and the one used in the Brain-to-Text 2024 challenge:\n| | Brain-to-Text '24 | Brain-to-Text '25 |\n| --- | --- | --- |\n| **Participant** | 'T12' | 'T15' |\n| **Neural recordings** | 128 intracortical electrodes in speech motor cortex, 128 intracortical electrodes in inferior frontal gyrus | 256 intracortical recording electrodes in speech motor cortex |\n| **Dataset period** | 25 sessions spanning 4 months | 45 sessions spanning 20 months |\n| **Number of Sentences** | 12,100 | 10,948 |\n| **Sentence corpus** | Switchboard | 50-word vocabulary, Switchboard, Openwebtext2, Harvard sentences, custom high-frequency word sentences, random word sentences |\n| **Speaking strategy** | Attempted vocalized | Attempted vocalized or attempted silent |\n| **Speaking rate** | ~62 words per minute | ~30 words per minute (attempted vocalized) or ~50 words per minute (attempted silent) |\n\n## Data format\nThe dataset can be downloaded either from this Kaggle competition page (see below) or from [Dryad](https://doi.org/10.5061/dryad.dncjsxm85). There are 10,948 sentences from 45 sessions spanning 20 months. Data is stored in `.hdf5` files. **An example of how to load this data using the Python `h5py` library is provided on our GitHub repository, [here](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/blob/main/model_training/evaluate_model_helpers.py#L29)**.\n\nEach trial of data includes: \n- The session date, block number, and trial number\n- 512 neural features (2 features [-4.5 RMS threshold crossings and spike band power] per electrode, 256 electrodes), binned at 20 ms resolution. The data were recorded from the speech motor cortex via four high-density microelectrode arrays (64 electrodes each). The 512 features are ordered as follows in all data files: \n - 0-64: ventral 6v threshold crossings\n - 65-128: area 4 threshold crossings\n - 129-192: 55b threshold crossings\n - 193-256: dorsal 6v threshold crossings\n - 257-320: ventral 6v spike band power\n - 321-384: area 4 spike band power\n - 385-448: 55b spike band power\n - 449-512: dorsal 6v spike band power\n- The ground truth sentence label (for train and val splits)\n- The ground truth phoneme sequence label (for train and val splits)\n\n## Loading the data in Python\n\nYou can load the data using the `h5py` Python library. See example code below, and also on our GitHub repository, [here](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/blob/main/model_training/evaluate_model_helpers.py#L29).\n\n```python\nimport h5py\n\ndef load_h5py_file(file_path):\n data = {\n 'neural_features': [],\n 'n_time_steps': [],\n 'seq_class_ids': [],\n 'seq_len': [],\n 'transcriptions': [],\n 'sentence_label': [],\n 'session': [],\n 'block_num': [],\n 'trial_num': [],\n }\n # Open the hdf5 file for that day\n with h5py.File(file_path, 'r') as f:\n\n keys = list(f.keys())\n\n # For each trial in the selected trials in that day\n for key in keys:\n g = f[key]\n\n neural_features = g['input_features'][:]\n n_time_steps = g.attrs['n_time_steps']\n seq_class_ids = g['seq_class_ids'][:] if 'seq_class_ids' in g else None\n seq_len = g.attrs['seq_len'] if 'seq_len' in g.attrs else None\n transcription = g['transcription'][:] if 'transcription' in g else None\n sentence_label = g.attrs['sentence_label'][:] if 'sentence_label' in g.attrs else None\n session = g.attrs['session']\n block_num = g.attrs['block_num']\n trial_num = g.attrs['trial_num']\n\n data['neural_features'].append(neural_features)\n data['n_time_steps'].append(n_time_steps)\n data['seq_class_ids'].append(seq_class_ids)\n data['seq_len'].append(seq_len)\n data['transcriptions'].append(transcription)\n data['sentence_label'].append(sentence_label)\n data['session'].append(session)\n data['block_num'].append(block_num)\n data['trial_num'].append(trial_num)\n return data\n```\n\n## Data fields\n- `neural_features`: Temporally binned (20 ms) neural features for each trial (512 X T).\n- `n_time_steps`: Number of time steps per trial.\n- `seq_class_ids`: Integer phoneme sequence labels for each trial. Integers correspond to phonemes using the following mapping:\n```python\nLOGIT_TO_PHONEME = [\n'BLANK', # \"BLANK\" = CTC blank symbol\n'AA', 'AE', 'AH', 'AO', 'AW',\n'AY', 'B', 'CH', 'D', 'DH',\n'EH', 'ER', 'EY', 'F', 'G',\n'HH', 'IH', 'IY', 'JH', 'K',\n'L', 'M', 'N', 'NG', 'OW',\n'OY', 'P', 'R', 'S', 'SH',\n'T', 'TH', 'UH', 'UW', 'V',\n'W', 'Y', 'Z', 'ZH',\n' | ', # \"|\" = silence token\n]\n```\n- `seq_len`: Number of phoneme labels per trial.\n- `transcriptions`: ASCII representation of sentence label for each trial.\n- `sentence_label`: Raw text sentence label for each trial.\n- `session`: Date that the trial's data was collected. Each date has a number of blocks, each block has a number of trials.\n- `block_num`: Research block number that the trial is sourced from.\n- `trial_num`: Trial number that the trial is sourced from.\n\n## More examples\nYou can refer to our [GitHub repository](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text) for thorough examples on how to download and unzip the data, where to put it, and how to train and evaluate a baseline RNN model with it.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Description", "content": "## Computational problem\n\nThe decoding problem consists of mapping a variable-length time series of neural activity to text with no ground-truth alignment between the two. We provide a [baseline algorithm](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text) that first decodes neural activity into phoneme probabilities and then uses an n-gram language model plus LLM rescoring to decode the phoneme probabilities into text (see the diagram below). Our baseline algorithm achieves a 6.70% word error rate on the held-out *test* set. We may provide additional example approaches as the competition progresses, based on our own ideas as well as the lessons learned from the [Brain-to-Text '24 challenge](https://eval.ai/web/challenges/challenge-page/2099).\n\n![Speech neuroprosthesis overview](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/raw/main/b2txt_methods_overview.png)\n\nSome potential avenues for improvement beyond the baseline algorithm include:\n- Data augmentation (e.g., temporal masking)\n- Model architecture (e.g., transformer, end-to-end)\n- Different loss function (e.g., transducer)\n- Using different language models for sentences from [different corpora](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/blob/main/data/t15_copyTaskData_description.csv) (e.g., perhaps a 1-gram language model would do better than a 5gram model on the \"random word\" sentences)\n - Keep in mind that, with the goal of generalization in mind, you ***cannot*** tell your model what corpus to use at test-time. If your model can automatically detect which corpus to use, that's fine. The intention is for models to generalize to all types of speech during real-world BCI usage. Submissions that violate this rule are not eligible for prize money.\n- Different language modeling approach (e.g., neural LM instead of ngram)\n- Model ensembling\n- Test time augmentation\n- Test time adaptation (i.e., continuous finetuning)\n- Different tokenization strategies (e.g., syllables or BPE instead of phonemes)\n- Transfer learning from other datasets (e.g., ASR datasets or the [Brain-to-Text '24](https://eval.ai/web/challenges/challenge-page/2099) T12 neural dataset)\n\n## Dataset\n\nThe dataset used in this competition consists of 10,948 sentences spoken by a single research participant as described in [Card et al. “An Accurate and Rapidly Calibrating Speech Neuroprosthesis” (2024) *New England Journal of Medicine*](https://www.nejm.org/doi/full/10.1056/NEJMoa2314132). For each sentence, we provide the transcript of what the participant was attempting to say, along with the corresponding time series of neural spiking activity recorded from 256 microelectrodes in speech motor cortex. The dataset contains predefined “*train*”, “*val*”, and “*test*” partitions. The train and val partitions include the sentence labels, and you may repartition them if desired. The “*test*” partition does not include sentence labels and will be used for competition evaluation. The dataset can be downloaded either from this Kaggle competition page (see `Data` tab) or from [Dryad](https://doi.org/10.5061/dryad.dncjsxm85).\n\nThe dataset contains a mixture of speaking strategies and sentence corpuses (see table, below) on a block-by-block basis. A description of which blocks correspond to which corpuses and data splits can be found [here](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/blob/main/data/t15_copyTaskData_description.csv). To make the competition more challenging and better approximate real-world use, we do not provide labels as to the speaking strategy for each block.\n\nThere are some notable differences between this dataset and the one used in the Brain-to-Text 2024 challenge:\n| | Brain-to-Text '24 | Brain-to-Text '25 |\n| --- | --- | --- |\n| **Participant** | 'T12' | 'T15' |\n| **Neural recordings** | 128 intracortical electrodes in speech motor cortex, 128 intracortical electrodes in inferior frontal gyrus | 256 intracortical recording electrodes in speech motor cortex |\n| **Dataset period** | 25 sessions spanning 4 months | 45 sessions spanning 20 months |\n| **Number of Sentences** | 12,100 | 10,948 |\n| **Sentence corpus** | Switchboard | 50-word vocabulary, Switchboard, Openwebtext2, Harvard sentences, custom high-frequency word sentences, random word sentences |\n| **Speaking strategy** | Attempted vocalized | Attempted vocalized or attempted silent |\n| **Speaking rate** | ~62 words per minute | ~30 words per minute (attempted vocalized) or ~50 words per minute (attempted silent) |\n\n## Competition Timeline\n\nCompetitors may submit their submission `.csv` files until the competition ends on December 31st, 2025 at 11:59 pm (Pacific Standard Time). After the competition ends, entrants who would like to be considered for the cash prize will have until January 31st, 2026, to submit their one-page summary and code. Details on how to submit this information will be provided at a later date. Winners will be chosen and then announced in February 2026.\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Evaluation", "content": "The aggregate [word error rate](https://en.wikipedia.org/wiki/Word_error_rate) metric will be used to evaluate decoding performance across the 1,450 held-out test sentences contained in this dataset (specifically, the `data_test.hdf5` files for each session). Word error rate is the \"edit distance\" between the decoded sentence and the actual sentence, computed over words (i.e., the number of substitutions, insertions and deletions of words needed to make the decoded sentence match the true sentence). The aggregate word error rate across all sentences is equal to the summed edit distance over all sentences, divided by the total number of words across all true transcriptions. \"Words\" are sequences of characters separated by spaces. To be counted as correct, all characters in the decoded word must match the true word (including apostrophes for contractions like \"don't\"). Punctuation marks (such as periods, question marks and commas) are not evaluated and should not be included in the decoded transcripts. \n\nThe test set consists of 1,450 sentences. Not that all sessions do not include *val* or *test* partitions. 1/3 of the *test* sentences will be used for the public leaderboard and the remaining 2/3rds will be used for the private leaderboard. The public leaderboard will be visible throughout the competition, but the private leaderboard will only be revealed after the competition ends on December 31, 2025. Prizes will be based on the private leaderboard.\n\nYour submission file should be a `.csv` file with an `id` and a `text` column. Sentences should appear in chronological order (by session date, block, and trial number) from the *test* partition, with `id` incrementing from 0 to 1449. For example, your `.csv` submission file should first have the held out *test* trials from session `t15.2023.08.13`, followed by `t15.2023.08.18`, then `t15.2023.08.20`, and so on.\n\nSee our [example evaluation script](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/blob/main/model_training/evaluate_model.py) for how to load data, do inference with pretrained models, and create a correctly-formatted submission file. See our [example baseline submission file](https://github.com/Neuroprosthetics-Lab/nejm-brain-to-text/blob/main/model_training/rnn_baseline_submission_file_valsplit.csv) for what your decoded transcripts should look like (note that the linked example submission file corresponds to the *val* partition, not the *test* partition).\n\nPlease feel free to discuss decoding strategies and questions on the *Discussion* tab of this Kaggle competition.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "rules", "content": "## Fine Print\n\n- To be considered eligible for cash prizes, competitors must (privately) submit a one-page summary of their approach as well as the code required to reproduce it (see competition timeline on the Overview tab). Submitted summaries and code will be kept private by the competition organizers, although entrants are free to publicly share and/or publish their approaches if they want to. Prizes will be fully administered and paid out by Blackrock Neurotech, subject to applicable laws, rules, and conditions. We (the academic organizers of this competition) are not directly involved in the prize but will provide Blackrock with the names and contact information of the winners.\n- The decoding should be based solely on code/algorithms that would not rely on human intervention and can be expected to generalize to new text. For example, if your method involves reading the predicted transcript and then using your own (human) intuition as to what the full sentence would be (or trying to find a match in existing speech corpora), this is not in the spirit of the competition and will not be added to the leaderboard or be eligible to win. The same prohibition applies to e.g., trying to reverse engineer the algorithm and random seed for random word lists. Basically, do not try to cheat.\n- Models cannot be trained in any way on the *test* dataset ahead of inference time.\n- Attempting to bypass the daily submission limit (e.g., by creating additional Kaggle accounts) will disqualify entrants from prize eligibility, and these entries will be nullified and hidden from the leaderboard.\n- Similar to the above, we reserve the right to disqualify entrants that we feel are exploiting gray area loopholes that we may have not thought of yet. If you have an idea that you think is borderline, feel free to contact us to ask.\n- The determination of “Most Innovative Approach” will be based on the judgement of the competition organizers within the BrainGate consortium. The spirit of this award category is to reward out-of-the-box thinking that is not just an iteration or optimization of standard methods. As one hypothetical scenario, consider if the best 2 performing entrants used a well-known machine learning architecture with large-scale ensembling (in effect, “just throwing compute at it”). While this is valid, it is (frankly) a bit boring and probably doesn’t move the field forward much. If there was another entrant who used a creative architecture that’s more efficient but didn’t quite have the same absolute performance, this would be a strong candidate for the Most Innovative Approach designation.\n- Individuals who are in BrainGate-affiliated labs (or collaborators) and could potentially have access to the test data or other data from this participant are not eligible to win the competition. However, if they play by the rules they can contribute baselines to the leaderboard.\n\n## Data License\nThe [data](https://doi.org/10.5061/dryad.dncjsxm85) is licensed under a CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license. Please cite [Card et al. “An Accurate and Rapidly Calibrating Speech Neuroprosthesis” (2024) *New England Journal of Medicine*](https://www.nejm.org/doi/full/10.1056/NEJMoa2314132) in any work that uses the data.\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "abstract", "content": "People with ALS or brainstem stroke can lose the ability to move and speak. Speech brain-computer interfaces (BCIs) can restore communication by decoding what someone is trying to say directly from their brain activity. Once decoded, the person’s intended message can be spoken for them or typed as text on a computer. Following up on prior speech decoding work, we [recently](https://www.nejm.org/doi/full/10.1056/NEJMoa2314132) demonstrated that a “brain-to-text” speech BCI can decode the attempted speech of a man with ALS and severe dysarthria into words with 97.5% accuracy.\n\nThe goal of this competition is to foster the development of new and improved algorithms for decoding speech from brain activity. Improved accuracies will make it more likely that a speech BCI can be clinically translated, improving the lives of those with vocal tract paralysis. We hope that this competition can also serve as an indicator of progress in the field and provide a standardized way to compare algorithm performance.\n\nIn the prior [Brain-to-Text '24 challenge](https://eval.ai/web/challenges/challenge-page/2099/evaluation), competitors successfully developed improved speech decoding algorithms, reducing the word error rate from 11.06% to as low as 5.77%. Here, we present a similar challenge but with a new dataset from a different research participant collected by the [UC Davis Neuroprosthetics Lab](https://neuroprosthetics.science/).", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "This challenge has a cash prize associated with it, generously provided by [Blackrock Neurotech](https://blackrockneurotech.com/):\n- **1st Place** - $5,000\n- **2nd Place** - $3,000\n- **Most Innovative Approach** - $1,000\n\nTo be considered eligible for cash prizes, competitors must submit a one-page summary of their approach as well as the code required to reproduce it (see competition timeline, below). The prize will be fully administered and paid out by Blackrock Neurotech, subject to applicable laws, rules, and conditions. We (the academic organizers of this competition) are not directly involved in the prize but will provide Blackrock with the names and contact information of the winners.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "foundational-rules", "content": "The following Kaggle Competition Foundational Rules (“ Foundational Rules ”) apply to every competition regardless of whether the Sponsor creates competition-specific rules. Any competition-specific rules provided by the Sponsor are in addition to these rules, and in the case of any conflict or inconsistency, these Foundational Rules control and nullify contrary competition-specific rules.\n###GENERAL COMPETITION RULES - BINDING AGREEMENT\n####1. ELIGIBILITY\na. To be eligible to enter the Competition, you must be:\n1. a registered account holder at Kaggle.com; \n2. the older of 18 years old or the age of majority in your jurisdiction of residence (unless otherwise agreed to by Competition Sponsor and appropriate parental/guardian consents have been obtained by Competition Sponsor); \n3. not a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, or North Korea; and\n4. not a person or representative of an entity under U.S. export controls or sanctions (see: [https://www.treasury.gov/resourcecenter/sanctions/Programs/Pages/Programs.aspx][1]).\n\nb. Competitions are open to residents of the United States and worldwide, except that if you are a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, North Korea, or are subject to U.S. export controls or sanctions, you may not enter the Competition. Other local rules and regulations may apply to you, so please check your local laws to ensure that you are eligible to participate in skills-based competitions. The Competition Host reserves the right to forego or award alternative Prizes where needed to comply with local laws. If a winner is located in a country where prizes cannot be awarded, then they are not eligible to receive a prize.\n\nc. If you are entering as a representative of a company, educational institution or other legal entity, or on behalf of your employer, these rules are binding on you, individually, and the entity you represent or where you are an employee. If you are acting within the scope of your employment, or as an agent of another party, you warrant that such party or your employer has full knowledge of your actions and has consented thereto, including your potential receipt of a Prize. You further warrant that your actions do not violate your employer's or entity's policies and procedures. \n\nd. The Competition Sponsor reserves the right to verify eligibility and to adjudicate on any dispute at any time. If you provide any false information relating to the Competition concerning your identity, residency, mailing address, telephone number, email address, ownership of right, or information required for entering the Competition, you may be immediately disqualified from the Competition.\n\n####2. SPONSOR AND HOSTING PLATFORM\n\na. The Competition is sponsored by Competition Sponsor named above. The Competition is hosted on behalf of Competition Sponsor by Kaggle Inc. (\"Kaggle\"). Kaggle is an independent contractor of Competition Sponsor, and is not a party to this or any agreement between you and Competition Sponsor. You understand that Kaggle has no responsibility with respect to selecting the potential Competition winner(s) or awarding any Prizes. Kaggle will perform certain administrative functions relating to hosting the Competition, and you agree to abide by the provisions relating to Kaggle under these Rules. As a Kaggle.com account holder and user of the Kaggle competition platform, remember you have accepted and are subject to the Kaggle Terms of Service at [www.kaggle.com/terms][2] in addition to these Rules.\n\n####3. COMPETITION PERIOD\na. For the purposes of Prizes, the Competition will run from the Start Date and time to the Final Submission Deadline (such duration the “Competition Period”). The Competition Timeline is subject to change, and Competition Sponsor may introduce additional hurdle deadlines during the Competition Period. Any updated or additional deadlines will be publicized on the Competition Website. It is your responsibility to check the Competition Website regularly to stay informed of any deadline changes. YOU ARE RESPONSIBLE FOR DETERMINING THE CORRESPONDING TIME ZONE IN YOUR LOCATION.\n\n####4. COMPETITION ENTRY\na. NO PURCHASE NECESSARY TO ENTER OR WIN. To enter the Competition, you must register on the Competition Website prior to the Entry Deadline, and follow the instructions for developing and entering your Submission through the Competition Website. Your Submissions must be made in the manner and format, and in compliance with all other requirements, stated on the Competition Website (the \"Requirements\"). Submissions must be received before any Submission deadlines stated on the Competition Website. Submissions not received by the stated deadlines will not be eligible to receive a Prize.\nb. Submissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.\nc. If the Competition is a multi-stage competition with temporally separate training and/or test data, one or more valid Submissions may be required during each Competition stage in the manner described on the Competition Website in order for the Submissions to be Prize eligible.\nd. Submissions are void if they are in whole or part illegible, incomplete, damaged, altered, counterfeit, obtained through fraud, or late. Competition Sponsor reserves the right to disqualify any entrant who does not follow these Rules, including making a Submission that does not meet the Requirements. \n\n####5. INDIVIDUALS AND TEAMS\na. Individual Account. You may make Submissions only under one, unique Kaggle.com account. You will be disqualified if you make Submissions through more than one Kaggle account, or attempt to falsify an account to act as your proxy. You may submit up to the maximum number of Submissions per day as specified on the Competition Website. \nb. Teams. If permitted under the Competition Website guidelines, multiple individuals may collaborate as a Team; however, you may join or form only one Team. Each Team member must be a single individual with a separate Kaggle account. You must register individually for the Competition before joining a Team. You must confirm your Team membership to make it official by responding to the Team notification message sent to your Kaggle account. Team membership may not exceed the Maximum Team Size stated on the Competition Website.\nc. Team Merger. Teams may request to merge via the Competition Website. Team mergers may be allowed provided that: (i) the combined Team does not exceed the Maximum Team Size; (ii) the number of Submissions made by the merging Teams does not exceed the number of Submissions permissible for one Team at the date of the merger request; (iii) the merger is completed before the earlier of: any merger deadline or the Competition deadline; and (iv) the proposed combined Team otherwise meets all the requirements of these Rules. \nd. Private Sharing. No private sharing outside of Teams. Privately sharing code or data outside of Teams is not permitted. It's okay to share code if made available to all Participants on the forums.\n\n####6. SUBMISSION CODE REQUIREMENTS\na. Private Code Sharing. Unless otherwise specifically permitted under the Competition Website or Competition Specific Rules above, during the Competition Period, you are not allowed to privately share source or executable code developed in connection with or based upon the Competition Data or other source or executable code relevant to the Competition (“Competition Code”). This prohibition includes sharing Competition Code between separate Teams, unless a Team merger occurs. Any such sharing of Competition Code is a breach of these Competition Rules and may result in disqualification.\nb. Public Code Sharing. You are permitted to publicly share Competition Code, provided that such public sharing does not violate the intellectual property rights of any third party. If you do choose to share Competition Code or other such code, you are required to share it on Kaggle.com on the discussion forum or notebooks associated specifically with the Competition for the benefit of all competitors. By so sharing, you are deemed to have licensed the shared code under an Open Source Initiative-approved license (see [www.opensource.org][3]) that in no event limits commercial use of such Competition Code or model containing or depending on such Competition Code.\nc. Use of Open Source. Unless otherwise stated in the Specific Competition Rules above, if open source code is used in the model to generate the Submission, then you must only use open source code licensed under an Open Source Initiative-approved license (see [www.opensource.org][4]) that in no event limits commercial use of such code or model containing or depending on such code.\n\n####7. DETERMINING WINNERS\na. Each Submission will be scored and ranked by the evaluation metric stated on the Competition Website. During the Competition Period, the current ranking will be visible on the Competition Website's Public Leaderboard. The potential winner(s) are determined solely by the leaderboard ranking on the Private Leaderboard, subject to compliance with these Rules. The Public Leaderboard will be based on the public test set and the Private Leaderboard will be based on the private test set.\nb. In the event of a tie, the Submission that was entered first to the Competition will be the winner. In the event a potential winner is disqualified for any reason, the Submission that received the next highest score rank will be chosen as the potential winner.\n\n####8. NOTIFICATION OF WINNERS & DISQUALIFICATION\na. The potential winner(s) will be notified by email. \nb. If a potential winner (i) does not respond to the notification attempt within one (1) week from the first notification attempt or (ii) notifies Kaggle within one week after the Final Submission Deadline that the potential winner does not want to be nominated as a winner or does not want to receive a Prize, then, in each case (i) and (ii) such potential winner will not receive any Prize, and an alternate potential winner will be selected from among all eligible entries received based on the Competition’s judging criteria.\nc. In case (i) and (ii) above Kaggle may disqualify the Participant. However, in case (ii) above, if requested by Kaggle, such potential winner may provide code and documentation to verify the Participant’s compliance with these Rules. If the potential winner provides code and documentation to the satisfaction of Kaggle, the Participant will not be disqualified pursuant to this paragraph.\nd. Competition Sponsor reserves the right to disqualify any Participant from the Competition if the Competition Sponsor reasonably believes that the Participant has attempted to undermine the legitimate operation of the Competition by cheating, deception, or other unfair playing practices or abuses, threatens or harasses any other Participants, Competition Sponsor or Kaggle.\ne. A disqualified Participant may be removed from the Competition leaderboard, at Kaggle's sole discretion. If a Participant is removed from the Competition Leaderboard, additional winning features associated with the Kaggle competition platform, for example Kaggle points or medals, may also not be awarded.\nf. The final leaderboard list will be publicly displayed at Kaggle.com. Determinations of Competition Sponsor are final and binding.\n\n####9. PRIZES\na. Prize(s) are as described on the Competition Website and are only available for winning during the time period described on the Competition Website. The odds of winning any Prize depends on the number of eligible Submissions received during the Competition Period and the skill of the Participants. \nb. All Prizes are subject to Competition Sponsor's review and verification of the Participant’s eligibility and compliance with these Rules, and the compliance of the winning Submissions with the Submissions Requirements. In the event that the Submission demonstrates non-compliance with these Competition Rules, Competition Sponsor may at its discretion take either of the following actions: (i) disqualify the Submission(s); or (ii) require the potential winner to remediate within one week after notice all issues identified in the Submission(s) (including, without limitation, the resolution of license conflicts, the fulfillment of all obligations required by software licenses, and the removal of any software that violates the software restrictions).\nc. A potential winner may decline to be nominated as a Competition winner in accordance with Section 3.8.\nd. Potential winners must return all required Prize acceptance documents within two (2) weeks following notification of such required documents, or such potential winner will be deemed to have forfeited the prize and another potential winner will be selected. Prize(s) will be awarded within approximately thirty (30) days after receipt by Competition Sponsor or Kaggle of the required Prize acceptance documents. Transfer or assignment of a Prize is not allowed. \ne. You are not eligible to receive any Prize if you do not meet the Eligibility requirements in Section 2.7 and Section 3.1 above.\nf. If a Team wins a monetary Prize, the Prize money will be allocated in even shares between the eligible Team members, unless the Team unanimously opts for a different Prize split and notifies Kaggle before Prizes are issued.\n\n####10. TAXES\na. ALL TAXES IMPOSED ON PRIZES ARE THE SOLE RESPONSIBILITY OF THE WINNERS. Payments to potential winners are subject to the express requirement that they submit all documentation requested by Competition Sponsor or Kaggle for compliance with applicable state, federal, local and foreign (including provincial) tax reporting and withholding requirements. Prizes will be net of any taxes that Competition Sponsor is required by law to withhold. If a potential winner fails to provide any required documentation or comply with applicable laws, the Prize may be forfeited and Competition Sponsor may select an alternative potential winner. Any winners who are U.S. residents will receive an IRS Form-1099 in the amount of their Prize.\n\n####11. GENERAL CONDITIONS\na. All federal, state, provincial and local laws and regulations apply.\n\n####12. PUBLICITY\na. You agree that Competition Sponsor, Kaggle and its affiliates may use your name and likeness for advertising and promotional purposes without additional compensation, unless prohibited by law.\n\n####13. PRIVACY\na. You acknowledge and agree that Competition Sponsor and Kaggle may collect, store, share and otherwise use personally identifiable information provided by you during the Kaggle account registration process and the Competition, including but not limited to, name, mailing address, phone number, and email address (“Personal Information”). Kaggle acts as an independent controller with regard to its collection, storage, sharing, and other use of this Personal Information, and will use this Personal Information in accordance with its Privacy Policy <[www.kaggle.com/privacy][6]>, including for administering the Competition. As a Kaggle.com account holder, you have the right to request access to, review, rectification, portability or deletion of any personal data held by Kaggle about you by logging into your account and/or contacting Kaggle Support at <[www.kaggle.com/contact][7]>.\nb. As part of Competition Sponsor performing this contract between you and the Competition Sponsor, Kaggle will transfer your Personal Information to Competition Sponsor, which acts as an independent controller with regard to this Personal Information. As a controller of such Personal Information, Competition Sponsor agrees to comply with all U.S. and foreign data protection obligations with regard to your Personal Information. Kaggle will transfer your Personal Information to Competition Sponsor in the country specified in the Competition Sponsor Address listed above, which may be a country outside the country of your residence. Such country may not have privacy laws and regulations similar to those of the country of your residence.\n\n####14. WARRANTY, INDEMNITY AND RELEASE \na. You warrant that your Submission is your own original work and, as such, you are the sole and exclusive owner and rights holder of the Submission, and you have the right to make the Submission and grant all required licenses. You agree not to make any Submission that: (i) infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; or (ii) otherwise violates any applicable U.S. or foreign state or federal law.\nb. To the maximum extent permitted by law, you indemnify and agree to keep indemnified Competition Entities at all times from and against any liability, claims, demands, losses, damages, costs and expenses resulting from any of your acts, defaults or omissions and/or a breach of any warranty set forth herein. To the maximum extent permitted by law, you agree to defend, indemnify and hold harmless the Competition Entities from and against any and all claims, actions, suits or proceedings, as well as any and all losses, liabilities, damages, costs and expenses (including reasonable attorneys fees) arising out of or accruing from: (a) your Submission or other material uploaded or otherwise provided by you that infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; (b) any misrepresentation made by you in connection with the Competition; (c) any non-compliance by you with these Rules or any applicable U.S. or foreign state or federal law; (d) claims brought by persons or entities other than the parties to these Rules arising from or related to your involvement with the Competition; and (e) your acceptance, possession, misuse or use of any Prize, or your participation in the Competition and any Competition-related activity.\nc. You hereby release Competition Entities from any liability associated with: (a) any malfunction or other problem with the Competition Website; (b) any error in the collection, processing, or retention of any Submission; or (c) any typographical or other error in the printing, offering or announcement of any Prize or winners.\n\n####15. INTERNET\na. Competition Entities are not responsible for any malfunction of the Competition Website or any late, lost, damaged, misdirected, incomplete, illegible, undeliverable, or destroyed Submissions or entry materials due to system errors, failed, incomplete or garbled computer or other telecommunication transmission malfunctions, hardware or software failures of any kind, lost or unavailable network connections, typographical or system/human errors and failures, technical malfunction(s) of any telephone network or lines, cable connections, satellite transmissions, servers or providers, or computer equipment, traffic congestion on the Internet or at the Competition Website, or any combination thereof, which may limit a Participant’s ability to participate.\n\n####16. RIGHT TO CANCEL, MODIFY OR DISQUALIFY\na. If for any reason the Competition is not capable of running as planned, including infection by computer virus, bugs, tampering, unauthorized intervention, fraud, technical failures, or any other causes which corrupt or affect the administration, security, fairness, integrity, or proper conduct of the Competition, Competition Sponsor reserves the right to cancel, terminate, modify or suspend the Competition. Competition Sponsor further reserves the right to disqualify any Participant who tampers with the submission process or any other part of the Competition or Competition Website. Any attempt by a Participant to deliberately damage any website, including the Competition Website, or undermine the legitimate operation of the Competition is a violation of criminal and civil laws. Should such an attempt be made, Competition Sponsor and Kaggle each reserves the right to seek damages from any such Participant to the fullest extent of the applicable law.\n\n####17. NOT AN OFFER OR CONTRACT OF EMPLOYMENT\na. Under no circumstances will the entry of a Submission, the awarding of a Prize, or anything in these Rules be construed as an offer or contract of employment with Competition Sponsor or any of the Competition Entities. You acknowledge that you have submitted your Submission voluntarily and not in confidence or in trust. You acknowledge that no confidential, fiduciary, agency, employment or other similar relationship is created between you and Competition Sponsor or any of the Competition Entities by your acceptance of these Rules or your entry of your Submission.\n\n####18. DEFINITIONS\na. \"Competition Data\" are the data or datasets available from the Competition Website for the purpose of use in the Competition, including any prototype or executable code provided on the Competition Website. The Competition Data will contain private and public test sets. Which data belongs to which set will not be made available to Participants. \nb. An “Entry” is when a Participant has joined, signed up, or accepted the rules of a competition. Entry is required to make a Submission to a competition.\nc. A “Final Submission” is the Submission selected by the user, or automatically selected by Kaggle in the event not selected by the user, that is/are used for final placement on the competition leaderboard.\nd. A “Participant” or “Participant User” is an individual who participates in a competition by entering the competition and making a Submission.\ne. The “Private Leaderboard” is a ranked display of Participants’ Submission scores against the private test set. The Private Leaderboard determines the final standing in the competition.\nf. The “Public Leaderboard” is a ranked display of Participants’ Submission scores against a representative sample of the test data. This leaderboard is visible throughout the competition.\ng. A “Sponsor” is responsible for hosting the competition, which includes but is not limited to providing the data for the competition, determining winners, and enforcing competition rules.\nh. A “Submission” is anything provided by the Participant to the Sponsor to be evaluated for competition purposes and determine leaderboard position. A Submission may be made as a model, notebook, prediction file, or other format as determined by the Sponsor.\ni. A “Team” is one or more Participants participating together in a Kaggle competition, by officially merging together as a Team within the competition platform.\n\n [1]: https://www.treasury.gov/resource-center/sanctions/Programs/Pages/Programs.aspx\n [2]: http://www.kaggle.com/terms\n [3]: http://www.opensource.org\n [4]: http://www.opensource.org\n [5]: https://www.kaggle.com/WinningModelDocumentationGuidelines\n [6]: http://www.kaggle.com/privacy\n [7]: http://www.kaggle.com/contact\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Competition Organizers", "content": "This competition was organized by [Nicholas Card](https://x.com/NS_Card) and the [UC Davis Neuroprosthetics Lab](https://neuroprosthetics.science/), which is part of the [BrainGate consortium](https://www.braingate.org/).\n\nFor questions or comments, please reach out via the discussion board here, or via email, Twitter/X, or LinkedIn:\n- Email: nscard@health.ucdavis.edu\n- Twitter/X: https://x.com/NS_Card\n- LinkedIn: https://www.linkedin.com/in/nicholas-card/", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Terms and Conditions", "content": "The [data](https://doi.org/10.5061/dryad.dncjsxm85) is licensed under a CC0 1.0 Universal (CC0 1.0) Public Domain Dedication license. Please cite [Card et al. “An Accurate and Rapidly Calibrating Speech Neuroprosthesis” (2024) *New England Journal of Medicine*](https://www.nejm.org/doi/full/10.1056/NEJMoa2314132) in any work that uses the data.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false } ] }