Typing decoding

Name: typing

Category: cognitive decoding

Dataset: Levy2025BrainMeg

Objective Multiclass classification

Split: Leave-sentences-out

Usage

neuralbench meg typing

Show config.yaml

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.

data:
  study:
    source:
      name: Levy2025BrainMeg
    remove_bad_subjects:
      name: QueryEvents
      query: "~subject.isin(['Levy2025BrainMeg/S23', 'Levy2025BrainMeg/S11122024', 'Levy2025BrainMeg/S12122024', 'Levy2025BrainMeg/S26112024', 'Levy2025BrainMeg/S27112024', 'Levy2025BrainMeg/S28112024'])"
    filter_trial_id:
      name: QueryEvents
      query: "~trial_id.isin([0.0, 1.0])"
    split:
      name: SimilaritySplit
      stim_event_type: Keystroke
      valid_split_ratio: 0.2
      test_split_ratio: 0.2
      valid_random_state: 33
      test_random_state: 33
      threshold: 0.7
      use_sklearn_split: true
  neuro:
    name: MegExtractor
    picks: [meg]
    baseline: [0.0, 0.2]
    allow_maxshield: true
  channel_positions:
    include_ref_eeg: false
    layout_or_montage_name: null
  target:
    =replace=: true
    name: LabelEncoder
    event_types: Keystroke
    event_field: button
    predefined_mapping:
      s: 0
      o: 1
      t: 2
      e: 3
      n: 4
      c: 5
      i: 6
      a: 7
      "<space>": 8
      d: 9
      l: 10
      r: 11
      b: 12
      "<special>": 13
      z: 14
      v: 15
      f: 16
      m: 17
      u: 18
      h: 19
      p: 20
      g: 21
      q: 22
      w: 23
      x: 24
      y: 25
      j: 26
      ý: 13
      "\x14": 13
      k: 27
      ü: 13
      û: 13
      "£": 13
      "¤": 13
      "<number>": 28
      "-": 13
      "¿": 13
      "`": 13
      "\u0060": 13
    return_one_hot: true
    aggregation: trigger
  trigger_event_type: Keystroke
  start: -0.2
  duration: 1.0
  summary_columns: [button]
compute_class_weights: true
brain_model_output_size: &brain_model_output_size 29
trainer_config.monitor: val/bal_acc
trainer_config.mode: max
loss:
  name: CrossEntropyLoss
  kwargs:
    label_smoothing: 0.1
metrics: !!python/object/apply:neuralbench.defaults.metrics.get_classification_metric_configs
  - *brain_model_output_size

Description

The typing decoding task involves decoding the characters that were typed on a computer keyboard while MEG was recorded [Levy2025]. In this task, we use the private Levy2025BrainMeg dataset, which contains MEG data recorded while subjects typed back sentences that were shown on a screen.

Dataset Notes

• Train/test splits are created by clustering similar sentences together into the same split to avoid data leakage (see neuralset.splitting.SimilaritySplitter).

References

[Levy2025]

Lévy, Jarod, et al. “Brain-to-text decoding: A non-invasive approach via typing.” arXiv preprint arXiv:2502.17480 (2025).