Falsifiable substitution tests reveal task-structured neural evidence for auditory attention
Ding, Y.
Show abstract
A neural decoder can predict a mental-state label without using information specific to that state. We made auditory-attention attribution falsifiable by requiring candidate evidence to persist in disjoint data, respond to capacity-matched substitutions of physical organization or listener/population template, and remain testable after target-event exclusion or command-identity residualization; two event-related datasets also permitted electrooculography (EOG)-only comparisons. The design drew on Wang and Zahls three-dimensional Kakeya proof strategy: examine the organized family and its concentration, not only the strongest member. Across six EEG datasets, averaging four neural-speech margins improved 5-s decoding relative to the leading margin in three evaluation sets whose rules were fixed before their results were computed (41 participants; study-equal gain, 0.0201; 95% interval, 0.0125-0.0279). A 16-cell scalp-direction-delay representation replicated in a participant-disjoint cohort and exceeded the mean of 15 capacity-matched remappings. Across three continuous-speech datasets (43 participants; 86 directed transfers), listener-matched weights outranked other-listener weights by 0.0969 and wrong mappings by 0.1371, although accuracy did not improve universally. In two hierarchical interfaces, a parent-stream error score retained AUCs of 0.968 and 0.965 after oracle-label exclusion of all target-command events. It depended on the physical command-stream mapping, exceeded an EOG-only comparator, and generalized within listeners after training-only removal of command identity. Eight electrodes retained 59-77% of binding specificity, but one listener-consistency criterion failed. The main contribution is a transferable standard for testing what information supports a decoded psychological construct. Significance StatementInspired by the proof strategy of the three-dimensional Kakeya theorem, we turn "a neural decoder reads auditory attention" from an interpretation of accuracy into a falsifiable test of evidence attribution. Engineering can exploit any stable predictor; science of latent mental constructs must ask whether the proposed construct remains necessary after plausible alternatives are removed or substituted. Across six electroencephalography (EEG) datasets, task-organized scores survived disjoint data and were challenged by matched substitutions of physical mapping or listener template, target-event exclusion, command-identity residualization, and EOG-only comparison. This framework does not prove that attention is the only cause. It offers neuroscience and brain-computer interfaces (BCIs) a standard: evidence should transport, its proposed organization should matter, and credible shortcuts should fail.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Stimulus dependencies---rather than next-word prediction---can explain pre-onset brain encoding during natural listening 93%
- Shared neural underpinnings of multisensory integration and trial-by-trial perceptual recalibration 93%
- Different computations over the same inputs produce selective behavior in algorithmic brain networks 93%
Similar papers in this journal
Similar papers in this journal
- Timing of speech in brain and glottis and the feedback delay problem in motor control 94%
- Dimensionality and ramping: Signatures of sentence integration in the dynamics of brains and deep language models 93%
- Automatic and fast encoding of representational uncertainty underlies probability distortion 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.