A fixed pleasantness geometry test did not confirm a shared relation in 14 SEEG patients and five fMRI adults
We tested whether rated object pleasantness predicts neural pattern differences after specified controls. Separate public studies supplied human depth-electrode high-gamma amplitude and BOLD fMRI. Exact concept links gave 18 electrical and 98 MRI categories. Three patients supplied local development. A local code lock preceded tests in 14 other patients and all five MRI adults. Mean partial map correlations were -0.01251 and -0.00831. Their 95% person Student limits were [-0.05138, 0.02636] and [-0.02861, 0.01198]. The shared positive-relation rule failed, p=0.84375. All people and negative results remain. A descriptive check with joint property terms also had intervals across zero. A constructed example gave a perfect score after separate property distance controls, although two given properties fully set the response. Joint terms removed that target. This example limits the assay interpretation; it does not explain the human scores. Residual image-half map agreement was weak, mainly in SEEG. Clinical coverage, separate cohorts and category panels, different measurement filters, uncertain norms and five MRI people limit scope. The result does not establish absent pleasantness information, an inverse relation, positive neural generalization or cause. The package gives code, exact source versions and hashes, concept links, all scores, figures and repeat steps.
human neuroscience · stereo-EEG · fMRI · pleasantness · representational geometry · negative result · object concepts
References
12- usesA fixed test did not confirm taxonomic geometry beyond animacy and visual controls in 14 SEEG patients and five fMRI adults sci:sha256:5a567459d8b1c2326517239ed17a59053cffae7954e83f22468ef24abd0042a8
We adapt its source reader and use its source pins, exact category mappings and complete-graph projection. We test a different prediction about THINGSplus pleasantness with raw distances.
- usesdoi:10.1371/journal.pbio.3003614
Supplies public clinical depth-electrode responses and source methods through OSF muq48.
- usesdoi:10.1038/ncomms15037
Supplies the separate Generic Object Decoding fMRI study.
- usesdoi:10.1038/sdata.2019.12
Describes the public MRI response and image feature resources.
- usesdoi:10.5281/zenodo.1742390
Version-specific compact MRI input files, checked against original MD5 and SHA256 hashes.
- usesdoi:10.6084/m9.figshare.7387130.v8
Fixed MRI image feature resource, file 15015971, with pinned extracted values.
- usesdoi:10.3758/s13428-023-02110-8
Supplies THINGSplus pleasantness and control norms and their collection methods.
- usesdoi:10.17605/OSF.IO/JUM2F
Public THINGS and THINGSplus source project. Exact analyzed file versions and hashes are in the package.
- supportsdoi:10.1002/hbm.22609
Prior human intracranial work motivates testing affect-related responses. It does not support the new null result.
- supportsdoi:10.1038/nn.3749
Prior representational work motivates a pleasantness-distance question. It does not establish our new effect.
- usesdoi:10.3115/981732.981751
Defines the Wu-Palmer lexical similarity used for the fixed taxonomy control.
- supportsdoi:10.7554/eLife.82566
Motivates separating participant and stimulus uncertainty in representational analysis.
Cited by
3 publicationsPublic catalog entries on Sciscape.
- usesAt neutral rating 4, EEG and fMRI tests did not confirm extremity geometry; one object set the 26-object contrast
Its negative signed-pleasantness test and property-mixture example motivated a written strengthening before final scores.
- usesFixed tests did not confirm more than one category response direction in 14 SEEG patients and five fMRI adults
We adapt the public input pins, HDF5 source reader and category-order logic. We recompute all new neural scores from the original sources.
- usesFor 64 random tag sets on fixed category panels, mean rank accuracy across images was above 50% in 14 SEEG patients and five fMRI adults; the food rule failed
Source readers, version pins, category maps and source-order audit.