{
  "id": "AIBD-0004",
  "title": "Intracortical speech neuroprosthesis decodes attempted speech at 62 words per minute for a woman with ALS (Stanford)",
  "summary": "Four 64-electrode microelectrode arrays and an RNN with a 125,000-word language model let Pat Bennett (ALS) produce text at 62 wpm, 23.8% word error rate",
  "date_observed": "2022-08-01",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "At Stanford University, a participant with bulbar-onset amyotrophic lateral sclerosis (identified in news reports as Pat Bennett, 68) had four 64-electrode arrays implanted. They went into ventral premotor cortex (area 6v) and area 44 under the BrainGate2 trial. Stanford's release dates the surgery to 29 March 2022. A recurrent neural network (RNN) converted her neural activity into phoneme probabilities and a 125,000-word language model assembled sentences. She produced text at 62 words per minute (Willett et al., Nature, 23 August 2023). The word error rate was 9.1% on a 50-word vocabulary and 23.8% on the full vocabulary. The work was described as a proof of concept in research sessions. The paper dates sessions by post-implant day (119, 136 and 141 for the reported data), not calendar date. The Stanford release says research sessions began about a month after the 29 March 2022 surgery. It says 62 words per minute came after four months. That places the result in about August 2022, so 1 August 2022 is used as the observation date.",
  "category": "benefit created",
  "unexpected": false,
  "purpose": "Built to restore communication by decoding attempted speech from intracortical recordings into text; large-vocabulary text communication was the intended benefit and is what occurred.",
  "system": "Stanford intracortical speech neuroprosthesis (BrainGate2 trial)",
  "model_version": "Four 64-electrode microelectrode arrays in area 6v and area 44; five-layer gated recurrent-unit RNN with a 125,000-word trigram language model",
  "developer": "Stanford Neural Prosthetics Translational Laboratory (Willett, Henderson, Shenoy) with the BrainGate consortium",
  "deployer": "Stanford Medicine",
  "location": "Stanford, United States",
  "domain": "Healthcare / assistive communication",
  "segment": "ALS with loss of intelligible speech",
  "benefit_type": "Improved Accessibility",
  "taxonomy_note": null,
  "registry_ids": {},
  "ratings": [
    {
      "group": "personal",
      "depth": 2,
      "reason": "Material benefit to one identifiable person: large-vocabulary communication at conversational pace in research sessions. The team itself called it a proof of concept rather than an everyday device."
    }
  ],
  "ai_role": {
    "status": "assessed",
    "statement": "An RNN decoder plus an n-gram language model is the mechanism translating neural activity into text. The Stanford neurosurgeon describes the language model as “a sophisticated auto-correct”. The benefit is attributable to the decoding system."
  },
  "evidence": [
    {
      "kind": "peer-reviewed study",
      "citation": "Willett FR, Kunz EM, Fan C, et al. (2023). A high-performance speech neuroprosthesis. Nature.",
      "title": "A high-performance speech neuroprosthesis",
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/",
      "date": "2023-08-23",
      "written_by": "makers",
      "quote": "T12 spoke at an average pace of 62 words per minute, which more than triples the speed of the previous state of the art for any type of BCI (18 words per minute for a handwriting BCI)."
    },
    {
      "kind": "news report",
      "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).",
      "title": "These experimental brain implants can restore speech to paralyzed patients",
      "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients",
      "date": "2023-08-23",
      "written_by": "independent",
      "quote": "For Pat Bennett, 68, every spoken word is a struggle."
    },
    {
      "kind": "press release",
      "citation": "Goldman B (2023). Brain implants, software guide speech-disabled person's intended words to computer screen. Stanford Medicine News (developer institution release).",
      "title": "Brain implants, software guide speech-disabled person's intended words to computer screen",
      "url": "https://med.stanford.edu/news/all-news/2023/08/brain-implant-speech-als.html",
      "date": "2023-08-23",
      "written_by": "makers",
      "quote": "On March 29, 2022, a Stanford Medicine neurosurgeon placed two tiny sensors apiece in two separate regions - both implicated in speech production - along the surface of Bennett's brain."
    }
  ],
  "replication": {
    "produced_by": [
      "Preserved articulatory code for phonemes in ventral premotor cortex years after loss of speech",
      "Four intracortical arrays in speech-related cortex",
      "RNN decoder plus large-vocabulary language model trained on the participant's attempted speech",
      "Regulated trial setting (BrainGate2) with research support"
    ],
    "must_hold": [
      "Array signal quality remains adequate",
      "Participant can attempt speech and tolerate recording sessions",
      "Decoder retraining available across sessions"
    ],
    "echoes": [
      {
        "date": "2024-08-15",
        "setting": "UC Davis, a different participant (45-year-old man with ALS), same intracortical phoneme-decoding approach with Willett as co-author; 97.5% accuracy over 248 hours of conversation",
        "model_version": "256 electrodes; phoneme decoder with 125,000-word language models",
        "outcome": "recurred",
        "source": "Card NS, et al. (2024). An Accurate and Rapidly Calibrating Speech Neuroprosthesis. N Engl J Med. https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/"
      }
    ]
  },
  "paired_incident": {
    "database": "AI Incident Database",
    "identifier": "732",
    "title": "Whisper Speech-to-Text AI Reportedly Found to Create Violent Hallucinations",
    "url": "https://incidentdatabase.ai/cite/732",
    "severity": null,
    "group": "personal",
    "basis": "Both decode speech for people with impaired speech; Whisper fabricated words and violent phrases when transcribing impaired speech."
  },
  "headline": "Stanford neuroprosthesis decodes Pat Bennett's speech at 62 wpm",
  "metric": "produce text at 62 wpm, 23.8% word error rate",
  "comparator": {
    "against": "the previous state-of-the-art BCI (a handwriting BCI)",
    "before": "18 words per minute for a handwriting BCI",
    "after": "62 words per minute",
    "basis": "measured",
    "quote": "These accuracies were achieved at high speeds: T12 spoke at an average pace of 62 words per minute, which more than triples the speed of the previous state of the art for any type of BCI (18 words per minute for a handwriting BCI).",
    "url": "https://europepmc.org/article/PMC/PMC10468393"
  },
  "later": {
    "status": "unknown",
    "date": null,
    "note": "No dated development for this participant after the Nature report was found in the cited sources.",
    "quote": null,
    "url": null
  },
  "value": null,
  "developer_country": "United States",
  "deployer_country": "United States",
  "unrated_because": null,
  "brief_notes": null,
  "brief": null,
  "revisions": [
    {
      "date": "2026-10-20",
      "change": "Record drafted from the cited sources.",
      "source": null,
      "editor": "AIBD"
    },
    {
      "date": "2026-10-20",
      "change": "Paired with AI Incident Database incident 732 (medium confidence); severity not given by the source.",
      "source": "https://incidentdatabase.ai/cite/732",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-20",
      "change": "Moved the date observed from the publication date to August 2022, where the paper's post-implant-day sessions fall given the 29 March 2022 surgery date in the Stanford release, replaced “Utah arrays” with the sources' “64-electrode microelectrode arrays”, extended two truncated quotes to full sentences, corrected the NEJM echo date to the 15 August 2024 issue date, and added a taxonomy note on why a proof-of-concept demonstration is filed as a benefit created or restored.",
      "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/; https://med.stanford.edu/news/all-news/2023/08/brain-implant-speech-als.html; https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Added what the benefit is measured against from the cited sources.",
      "source": "https://europepmc.org/article/PMC/PMC10468393",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
      "source": "https://nptl.stanford.edu/; https://en.wikipedia.org/wiki/Stanford_University_School_of_Medicine",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
      "source": null,
      "editor": "AIBD"
    }
  ],
  "confidence": "reported",
  "shade": "medium",
  "claim_status": "Independently reported",
  "claim_basis": "Sources: one independent news report, the makers' peer-reviewed study and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.",
  "profile": {
    "case_id": "AIBD-0004",
    "catalog_version": "1.0.0",
    "source_fingerprint": "9faa389e1dc7813970aa77e80fe1a8cc1517cf5f30fd77ec735e588b98695403",
    "collection_refs": [
      {
        "collection_id": "aibd",
        "version": "snapshot-8bf7cfec9cb185aa"
      },
      {
        "collection_id": "aibd",
        "version": "2026-10-25"
      }
    ],
    "source_ids": [
      "AIBD-0004-source-0001",
      "AIBD-0004-source-0002",
      "AIBD-0004-source-0003"
    ],
    "families": {
      "strategic assessments": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "record_ids": []
      },
      "evaluations": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "record_ids": []
      },
      "monetary observations": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "record_ids": []
      },
      "institutional decisions": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "record_ids": []
      }
    },
    "fields": {
      "actors[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "developer": "Stanford Neural Prosthetics Translational Laboratory (Willett, Henderson, Shenoy) with the BrainGate consortium",
            "deployer": "Stanford Medicine"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "developer",
            "deployer"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "actors[].ownership_control": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "ai_contribution": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "ai_role": {
              "status": "assessed",
              "statement": "An RNN decoder plus an n-gram language model is the mechanism translating neural activity into text. The Stanford neurosurgeon describes the language model as “a sophisticated auto-correct”. The benefit is attributable to the decoding system."
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "ai_relationship": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "category": "benefit created",
            "ai_role": {
              "status": "assessed",
              "statement": "An RNN decoder plus an n-gram language model is the mechanism translating neural activity into text. The Stanford neurosurgeon describes the language model as “a sophisticated auto-correct”. The benefit is attributable to the decoding system."
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "ai_role",
            "category"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "assessments[].alternatives": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "assessments[].assessor_date": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "assessments[].depth": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "ratings": [
              {
                "group": "personal",
                "depth": 2,
                "reason": "Material benefit to one identifiable person: large-vocabulary communication at conversational pace in research sessions. The team itself called it a proof of concept rather than an everyday device."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "ratings"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "assessments[].display_confidence": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "confidence": "medium",
            "evidence_word": "reported",
            "claim_status": "Independently reported",
            "basis": "Sources: one independent news report, the makers' peer-reviewed study and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.",
            "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review."
          }
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Derived from the existing case display properties; not a new evidentiary judgment.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "assessments[].rationale": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "ratings": [
              {
                "group": "personal",
                "depth": 2,
                "reason": "Material benefit to one identifiable person: large-vocabulary communication at conversational pace in research sessions. The team itself called it a proof of concept rather than an everyday device."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "ratings"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "assessments[].rubric_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "assessments[].status_basis": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "assessments[].target": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "ratings": [
              {
                "group": "personal",
                "depth": 2,
                "reason": "Material benefit to one identifiable person: large-vocabulary communication at conversational pace in research sessions. The team itself called it a proof of concept rather than an everyday device."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "ratings"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "availability": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "brief": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "case_kind": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "case_links[]": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "answer": "Both decode speech for people with impaired speech; Whisper fabricated words and violent phrases when transcribing impaired speech.",
            "links": [
              {
                "database": "AI Incident Database",
                "identifier": "732",
                "title": "Whisper Speech-to-Text AI Reportedly Found to Create Violent Hallucinations",
                "url": "https://incidentdatabase.ai/cite/732",
                "group": "personal",
                "basis": "Both decode speech for people with impaired speech; Whisper fabricated words and violent phrases when transcribing impaired speech.",
                "relation": "comparable_harm"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Existing paired_incident classification; no new source review.",
          "record_fields": [
            "paired_incident"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "claims[].evidence_links": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "claims[].evidence_strength": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "claims[].missingness": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "claims[].proposition": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "cross_border_flows[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "decisions[].action_outcome": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "institutional decisions"
      },
      "decisions[].grounds": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "institutional decisions"
      },
      "decisions[].institution_task": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "institutional decisions"
      },
      "decisions[].success_criterion": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "institutional decisions"
      },
      "deployment_stage": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "economics[].amount": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].costs[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].counterfactual": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].currency_price_basis": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].gross_net": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].measure_type": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].period_unit": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].realization": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].recipient_payer": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].return_payback": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "economics[].valuation_method": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "monetary observations"
      },
      "evaluations[].ai_uplift": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].comparator": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].design": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].effect": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].exposure": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].id": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].measurement_method": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].metric": {
        "state": "not_assessed",
        "provenance": {
          "kind": "legacy_record",
          "basis": "Mapped from the existing case description without a new external source review.",
          "record_fields": [
            "metric"
          ],
          "source_refs": []
        },
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations",
        "display": {
          "answer": "produce text at 62 wpm, 23.8% word error rate",
          "editor_note": ""
        }
      },
      "evaluations[].reproduction_materials": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].setting_sample": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "evaluations[].uncertainty_limitations": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "evaluations"
      },
      "external_references[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "paired_incident": {
              "database": "AI Incident Database",
              "identifier": "732",
              "title": "Whisper Speech-to-Text AI Reportedly Found to Create Violent Hallucinations",
              "url": "https://incidentdatabase.ai/cite/732",
              "group": "personal",
              "basis": "Both decode speech for people with impaired speech; Whisper fabricated words and violent phrases when transcribing impaired speech."
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "paired_incident"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "follow_up[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "later": {
              "status": "unknown",
              "note": "No dated development for this participant after the Nature report was found in the cited sources."
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "later"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "human_oversight": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "id": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "id": "AIBD-0004"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "id"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "infrastructure_dependencies[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].beneficiaries": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].beneficiary_count": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].benefit_type": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "benefit_type": "Improved Accessibility"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "benefit_type"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "outcomes[].claim": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "At Stanford University, a participant with bulbar-onset amyotrophic lateral sclerosis (identified in news reports as Pat Bennett, 68) had four 64-electrode arrays implanted. They went into ventral premotor cortex (area 6v) and area 44 under the BrainGate2 trial. Stanford's release dates the surgery to 29 March 2022. A recurrent neural network (RNN) converted her neural activity into phoneme probabilities and a 125,000-word language model assembled sentences. She produced text at 62 words per minute (Willett et al., Nature, 23 August 2023). The word error rate was 9.1% on a 50-word vocabulary and 23.8% on the full vocabulary. The work was described as a proof of concept in research sessions. The paper dates sessions by post-implant day (119, 136 and 141 for the reported data), not calendar date. The Stanford release says research sessions began about a month after the 29 March 2022 surgery. It says 62 words per minute came after four months. That places the result in about August 2022, so 1 August 2022 is used as the observation date.",
            "benefit_type": "Improved Accessibility"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "account",
            "benefit_type"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "outcomes[].distribution": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].duration": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].id": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].stakeholder_group": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "ratings": [
              {
                "group": "personal",
                "depth": 2,
                "reason": "Material benefit to one identifiable person: large-vocabulary communication at conversational pace in research sessions. The team itself called it a proof of concept rather than an everyday device."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "ratings"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "outcomes[].status": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].tradeoffs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].unexpected": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "unexpected": false,
            "purpose": "Built to restore communication by decoding attempted speech from intracortical recordings into text; large-vocabulary text communication was the intended benefit and is what occurred."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "unexpected",
            "purpose"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "places[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "location": "Stanford, United States",
            "developer_country": "United States",
            "deployer_country": "United States"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "location",
            "developer_country",
            "deployer_country"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "purpose": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "purpose": "Built to restore communication by decoding attempted speech from intracortical recordings into text; large-vocabulary text communication was the intended benefit and is what occurred."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "purpose"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "record_dates": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "date_observed": "2022-08-01",
            "revisions": [
              {
                "date": "2026-10-20",
                "change": "Record drafted from the cited sources.",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-20",
                "change": "Paired with AI Incident Database incident 732 (medium confidence); severity not given by the source.",
                "source": "https://incidentdatabase.ai/cite/732",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-20",
                "change": "Moved the date observed from the publication date to August 2022, where the paper's post-implant-day sessions fall given the 29 March 2022 surgery date in the Stanford release, replaced “Utah arrays” with the sources' “64-electrode microelectrode arrays”, extended two truncated quotes to full sentences, corrected the NEJM echo date to the 15 August 2024 issue date, and added a taxonomy note on why a proof-of-concept demonstration is filed as a benefit created or restored.",
                "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/; https://med.stanford.edu/news/all-news/2023/08/brain-implant-speech-als.html; https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Added what the benefit is measured against from the cited sources.",
                "source": "https://europepmc.org/article/PMC/PMC10468393",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
                "source": "https://nptl.stanford.edu/; https://en.wikipedia.org/wiki/Stanford_University_School_of_Medicine",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "date_observed",
            "revisions"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "replication.attempts[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "replication": {
              "produced_by": [
                "Preserved articulatory code for phonemes in ventral premotor cortex years after loss of speech",
                "Four intracortical arrays in speech-related cortex",
                "RNN decoder plus large-vocabulary language model trained on the participant's attempted speech",
                "Regulated trial setting (BrainGate2) with research support"
              ],
              "must_hold": [
                "Array signal quality remains adequate",
                "Participant can attempt speech and tolerate recording sessions",
                "Decoder retraining available across sessions"
              ],
              "echoes": [
                {
                  "date": "2024-08-15",
                  "setting": "UC Davis, a different participant (45-year-old man with ALS), same intracortical phoneme-decoding approach with Willett as co-author; 97.5% accuracy over 248 hours of conversation",
                  "model_version": "256 electrodes; phoneme decoder with 125,000-word language models",
                  "outcome": "recurred",
                  "source": "Card NS, et al. (2024). An Accurate and Rapidly Calibrating Speech Neuroprosthesis. N Engl J Med. https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/"
                }
              ]
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "replication.conditions": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "replication": {
              "produced_by": [
                "Preserved articulatory code for phonemes in ventral premotor cortex years after loss of speech",
                "Four intracortical arrays in speech-related cortex",
                "RNN decoder plus large-vocabulary language model trained on the participant's attempted speech",
                "Regulated trial setting (BrainGate2) with research support"
              ],
              "must_hold": [
                "Array signal quality remains adequate",
                "Participant can attempt speech and tolerate recording sessions",
                "Decoder retraining available across sessions"
              ],
              "echoes": [
                {
                  "date": "2024-08-15",
                  "setting": "UC Davis, a different participant (45-year-old man with ALS), same intracortical phoneme-decoding approach with Willett as co-author; 97.5% accuracy over 248 hours of conversation",
                  "model_version": "256 electrodes; phoneme decoder with 125,000-word language models",
                  "outcome": "recurred",
                  "source": "Card NS, et al. (2024). An Accurate and Rapidly Calibrating Speech Neuroprosthesis. N Engl J Med. https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/"
                }
              ]
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "revision_history[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "revisions": [
              {
                "date": "2026-10-20",
                "change": "Record drafted from the cited sources.",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-20",
                "change": "Paired with AI Incident Database incident 732 (medium confidence); severity not given by the source.",
                "source": "https://incidentdatabase.ai/cite/732",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-20",
                "change": "Moved the date observed from the publication date to August 2022, where the paper's post-implant-day sessions fall given the 29 March 2022 surgery date in the Stanford release, replaced “Utah arrays” with the sources' “64-electrode microelectrode arrays”, extended two truncated quotes to full sentences, corrected the NEJM echo date to the 15 August 2024 issue date, and added a taxonomy note on why a proof-of-concept demonstration is filed as a benefit created or restored.",
                "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/; https://med.stanford.edu/news/all-news/2023/08/brain-implant-speech-als.html; https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Added what the benefit is measured against from the cited sources.",
                "source": "https://europepmc.org/article/PMC/PMC10468393",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
                "source": "https://nptl.stanford.edu/; https://en.wikipedia.org/wiki/Stanford_University_School_of_Medicine",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "revisions"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sector": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "domain": "Healthcare / assistive communication",
            "segment": "ALS with loss of intelligible speech"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "domain",
            "segment"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].access_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "sources[].citation_locator": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "evidence": [
              {
                "kind": "peer-reviewed study",
                "citation": "Willett FR, Kunz EM, Fan C, et al. (2023). A high-performance speech neuroprosthesis. Nature.",
                "title": "A high-performance speech neuroprosthesis",
                "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/",
                "date": "2023-08-23",
                "written_by": "makers",
                "quote": "T12 spoke at an average pace of 62 words per minute, which more than triples the speed of the previous state of the art for any type of BCI (18 words per minute for a handwriting BCI)."
              },
              {
                "kind": "news report",
                "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).",
                "title": "These experimental brain implants can restore speech to paralyzed patients",
                "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients",
                "date": "2023-08-23",
                "written_by": "independent",
                "quote": "For Pat Bennett, 68, every spoken word is a struggle."
              },
              {
                "kind": "press release",
                "citation": "Goldman B (2023). Brain implants, software guide speech-disabled person's intended words to computer screen. Stanford Medicine News (developer institution release).",
                "title": "Brain implants, software guide speech-disabled person's intended words to computer screen",
                "url": "https://med.stanford.edu/news/all-news/2023/08/brain-implant-speech-als.html",
                "date": "2023-08-23",
                "written_by": "makers",
                "quote": "On March 29, 2022, a Stanford Medicine neurosurgeon placed two tiny sensors apiece in two separate regions - both implicated in speech production - along the surface of Bennett's brain."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "evidence"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].id": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "AIBD-0004-source-0001",
            "AIBD-0004-source-0002",
            "AIBD-0004-source-0003"
          ],
          "role": "Existing evidence items, in their original order"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Stable within the fingerprinted record version; no source content or source review has been added.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "sources[].language": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "sources[].relationship": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "evidence": [
              {
                "kind": "peer-reviewed study",
                "citation": "Willett FR, Kunz EM, Fan C, et al. (2023). A high-performance speech neuroprosthesis. Nature.",
                "title": "A high-performance speech neuroprosthesis",
                "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/",
                "date": "2023-08-23",
                "written_by": "makers",
                "quote": "T12 spoke at an average pace of 62 words per minute, which more than triples the speed of the previous state of the art for any type of BCI (18 words per minute for a handwriting BCI)."
              },
              {
                "kind": "news report",
                "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).",
                "title": "These experimental brain implants can restore speech to paralyzed patients",
                "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients",
                "date": "2023-08-23",
                "written_by": "independent",
                "quote": "For Pat Bennett, 68, every spoken word is a struggle."
              },
              {
                "kind": "press release",
                "citation": "Goldman B (2023). Brain implants, software guide speech-disabled person's intended words to computer screen. Stanford Medicine News (developer institution release).",
                "title": "Brain implants, software guide speech-disabled person's intended words to computer screen",
                "url": "https://med.stanford.edu/news/all-news/2023/08/brain-implant-speech-als.html",
                "date": "2023-08-23",
                "written_by": "makers",
                "quote": "On March 29, 2022, a Stanford Medicine neurosurgeon placed two tiny sensors apiece in two separate regions - both implicated in speech production - along the surface of Bennett's brain."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "evidence"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].upstream_sources": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "strategic_assessments[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "strategic assessments"
      },
      "summary": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "summary": "Four 64-electrode microelectrode arrays and an RNN with a 125,000-word language model let Pat Bennett (ALS) produce text at 62 wpm, 23.8% word error rate",
            "account": "At Stanford University, a participant with bulbar-onset amyotrophic lateral sclerosis (identified in news reports as Pat Bennett, 68) had four 64-electrode arrays implanted. They went into ventral premotor cortex (area 6v) and area 44 under the BrainGate2 trial. Stanford's release dates the surgery to 29 March 2022. A recurrent neural network (RNN) converted her neural activity into phoneme probabilities and a 125,000-word language model assembled sentences. She produced text at 62 words per minute (Willett et al., Nature, 23 August 2023). The word error rate was 9.1% on a 50-word vocabulary and 23.8% on the full vocabulary. The work was described as a proof of concept in research sessions. The paper dates sessions by post-implant day (119, 136 and 141 for the reported data), not calendar date. The Stanford release says research sessions began about a month after the 29 March 2022 surgery. It says 62 words per minute came after four months. That places the result in about August 2022, so 1 August 2022 is used as the observation date."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "summary",
            "account"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].autonomy_permissions": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].component_role": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "The decoder and language model converted neural activity into text."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.",
          "record_fields": [
            "system",
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].deployment_configuration": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "Four arrays, each with 64 electrodes, recorded activity in cortical areas 6v and 44. The language model used a vocabulary of 125,000 words."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.",
          "record_fields": [
            "model_version",
            "system",
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].inputs_outputs": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "The system converted cortical recordings into words."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.",
          "record_fields": [
            "system",
            "ai_role",
            "replication",
            "account"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].model_name": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "A five-layer recurrent neural network with gated recurrent units, combined with a trigram language model."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.",
          "record_fields": [
            "model_version",
            "system",
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].model_version": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "model_version": "Four 64-electrode microelectrode arrays in area 6v and area 44; five-layer gated recurrent-unit RNN with a 125,000-word trigram language model"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "model_version"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial",
        "display": {
          "answer": "Exact release not established.",
          "editor_note": ""
        }
      },
      "systems[].product_name": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "system": "Stanford intracortical speech neuroprosthesis (BrainGate2 trial)"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "system"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].provider": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "application_developer": "Stanford Neural Prosthetics Translational Laboratory (Willett, Henderson, Shenoy) with the BrainGate consortium"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Mapped from the existing case description without a new external source review.",
          "record_fields": [
            "developer"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "taxonomy_crosswalks[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "title": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "title": "Intracortical speech neuroprosthesis decodes attempted speech at 62 words per minute for a woman with ALS (Stanford)",
            "headline": "Stanford neuroprosthesis decodes Pat Bennett's speech at 62 wpm"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "title",
            "headline"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "version": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "9faa389e1dc7813970aa77e80fe1a8cc1517cf5f30fd77ec735e588b98695403"
          ],
          "role": "SHA-256 of normalized original case data"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Deterministic content version assigned by the local migration.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "workflow": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "At Stanford University, a participant with bulbar-onset amyotrophic lateral sclerosis (identified in news reports as Pat Bennett, 68) had four 64-electrode arrays implanted. They went into ventral premotor cortex (area 6v) and area 44 under the BrainGate2 trial. Stanford's release dates the surgery to 29 March 2022. A recurrent neural network (RNN) converted her neural activity into phoneme probabilities and a 125,000-word language model assembled sentences. She produced text at 62 words per minute (Willett et al., Nature, 23 August 2023). The word error rate was 9.1% on a 50-word vocabulary and 23.8% on the full vocabulary. The work was described as a proof of concept in research sessions. The paper dates sessions by post-implant day (119, 136 and 141 for the reported data), not calendar date. The Stanford release says research sessions began about a month after the 29 March 2022 surgery. It says 62 words per minute came after four months. That places the result in about August 2022, so 1 August 2022 is used as the observation date.",
            "replication": {
              "produced_by": [
                "Preserved articulatory code for phonemes in ventral premotor cortex years after loss of speech",
                "Four intracortical arrays in speech-related cortex",
                "RNN decoder plus large-vocabulary language model trained on the participant's attempted speech",
                "Regulated trial setting (BrainGate2) with research support"
              ],
              "must_hold": [
                "Array signal quality remains adequate",
                "Participant can attempt speech and tolerate recording sessions",
                "Decoder retraining available across sessions"
              ],
              "echoes": [
                {
                  "date": "2024-08-15",
                  "setting": "UC Davis, a different participant (45-year-old man with ALS), same intracortical phoneme-decoding approach with Willett as co-author; 97.5% accuracy over 248 hours of conversation",
                  "model_version": "256 electrodes; phoneme decoder with 125,000-word language models",
                  "outcome": "recurred",
                  "source": "Card NS, et al. (2024). An Accurate and Rapidly Calibrating Speech Neuroprosthesis. N Engl J Med. https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/"
                }
              ]
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "account",
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 36,
      "reviewed": 0,
      "record_mapped": 36,
      "not_assessed": 55,
      "complete": false,
      "by_state": {
        "value_present": 36,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 55,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}