Evidence map›Paper›PMID 39437730›Full record

ArticleCurrent biology : CB2024

Predictive coding: A distinction - without a difference.

Adam S Lowet, Naoshige Uchida

Abstract read
In one paragraph

Article in Current biology : CB, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Adam S LowetDepartment of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA.
Naoshige UchidaDepartment of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA. Electronic address: uchida@mcb.harvard.edu.

Funding

Towards a Unified Framework for Dopamine Signaling in the StriatumU19NS113201 · NINDS · HARVARD MEDICAL SCHOOL · PI ASSAD, JOHN · 2019 to 2023
$18.7M
Distributional Reinforcement Learning in the BrainR01NS116753 · NINDS · HARVARD UNIVERSITY · PI DRUGOWITSCH, JAN, UCHIDA, NAOSHIGE · 2020 to 2024
$2.9M
NINDS NIH HHS R01 NS116753NINDS NIH HHS U19 NS113201
6 · The paper itself

Abstract

Influential models hold that neurons in the cerebral cortex signal the difference between actual and expected inputs. A new study instead finds that cortical prediction errors reflect not subtraction but rather stimulus-specific amplification of unexpected inputs.

Indexed as

Cerebral CortexNeuronsAnimalsHumansModels, Neurological

Identifiers

PMID39437730
PMCPMC12221311

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.