Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networks Article Swipe
S Liebe
,
Johannes Niediek
,
Matthijs Pals
,
Thomas P. Reber
,
Jennifer Faber
,
Jan Boström
,
Christian E. Elger
,
Jakob H. Macke
,
Florian Mormann
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41593-025-01893-7
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41593-025-01893-7
The temporal order of a sequence of events has been thought to be reflected in the ordered firing of neurons at different phases of theta oscillations. Here we assess this by measuring single neuron activity (1,420 neurons) and local field potentials (921 channels) in the medial temporal lobe of 16 patients with epilepsy performing a working-memory task for temporal order. During memory maintenance, we observe theta oscillations, preferential firing of single neurons to theta phase and a close relationship between phase of firing and item position. However, the firing order did not match item order. Training recurrent neural networks to perform an analogous task, we also show the generation of theta oscillations, theta phase-dependent firing related to item position and, again, no match between firing and item order. Rather, our results suggest a mechanistic link between phase order, stimulus timing and oscillation frequency. In both biological and artificial neural networks, we provide evidence supporting the role of phase of firing in working-memory processing.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41593-025-01893-7
- https://www.nature.com/articles/s41593-025-01893-7.pdf
- OA Status
- hybrid
- Cited By
- 9
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408770902
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- OpenAlex ID
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https://openalex.org/W4408770902Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41593-025-01893-7Digital Object Identifier
- Title
-
Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networksWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-03-24Full publication date if available
- Authors
-
S Liebe, Johannes Niediek, Matthijs Pals, Thomas P. Reber, Jennifer Faber, Jan Boström, Christian E. Elger, Jakob H. Macke, Florian MormannList of authors in order
- Landing page
-
https://doi.org/10.1038/s41593-025-01893-7Publisher landing page
- PDF URL
-
https://www.nature.com/articles/s41593-025-01893-7.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
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https://www.nature.com/articles/s41593-025-01893-7.pdfDirect OA link when available
- Concepts
-
Neuroscience, Local field potential, Stimulus (psychology), Temporal lobe, Artificial neural network, Working memory, Neuron, Psychology, Neural ensemble, Oscillation (cell signaling), Computer science, Artificial intelligence, Epilepsy, Cognitive psychology, Biology, Cognition, GeneticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
- Citations by year (recent)
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2025: 9Per-year citation counts (last 5 years)
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43Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.with | 52 |
| abstract_inverted_index.close | 78 |
| abstract_inverted_index.field | 40 |
| abstract_inverted_index.local | 39 |
| abstract_inverted_index.match | 93, 123 |
| abstract_inverted_index.order | 3, 90 |
| abstract_inverted_index.phase | 75, 81, 137, 158 |
| abstract_inverted_index.task, | 104 |
| abstract_inverted_index.theta | 25, 66, 74, 111, 113 |
| abstract_inverted_index.(1,420 | 36 |
| abstract_inverted_index.During | 61 |
| abstract_inverted_index.again, | 121 |
| abstract_inverted_index.assess | 29 |
| abstract_inverted_index.events | 8 |
| abstract_inverted_index.firing | 18, 69, 83, 89, 115, 125, 160 |
| abstract_inverted_index.medial | 46 |
| abstract_inverted_index.memory | 62 |
| abstract_inverted_index.neural | 98, 149 |
| abstract_inverted_index.neuron | 34 |
| abstract_inverted_index.order, | 138 |
| abstract_inverted_index.order. | 60, 95, 128 |
| abstract_inverted_index.phases | 23 |
| abstract_inverted_index.single | 33, 71 |
| abstract_inverted_index.timing | 140 |
| abstract_inverted_index.Rather, | 129 |
| abstract_inverted_index.between | 80, 124, 136 |
| abstract_inverted_index.neurons | 20, 72 |
| abstract_inverted_index.observe | 65 |
| abstract_inverted_index.ordered | 17 |
| abstract_inverted_index.perform | 101 |
| abstract_inverted_index.provide | 152 |
| abstract_inverted_index.related | 116 |
| abstract_inverted_index.results | 131 |
| abstract_inverted_index.suggest | 132 |
| abstract_inverted_index.thought | 11 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 87 |
| abstract_inverted_index.Training | 96 |
| abstract_inverted_index.activity | 35 |
| abstract_inverted_index.epilepsy | 53 |
| abstract_inverted_index.evidence | 153 |
| abstract_inverted_index.networks | 99 |
| abstract_inverted_index.neurons) | 37 |
| abstract_inverted_index.patients | 51 |
| abstract_inverted_index.position | 119 |
| abstract_inverted_index.sequence | 6 |
| abstract_inverted_index.stimulus | 139 |
| abstract_inverted_index.temporal | 2, 47, 59 |
| abstract_inverted_index.analogous | 103 |
| abstract_inverted_index.channels) | 43 |
| abstract_inverted_index.different | 22 |
| abstract_inverted_index.measuring | 32 |
| abstract_inverted_index.networks, | 150 |
| abstract_inverted_index.position. | 86 |
| abstract_inverted_index.recurrent | 97 |
| abstract_inverted_index.reflected | 14 |
| abstract_inverted_index.artificial | 148 |
| abstract_inverted_index.biological | 146 |
| abstract_inverted_index.frequency. | 143 |
| abstract_inverted_index.generation | 109 |
| abstract_inverted_index.performing | 54 |
| abstract_inverted_index.potentials | 41 |
| abstract_inverted_index.supporting | 154 |
| abstract_inverted_index.mechanistic | 134 |
| abstract_inverted_index.oscillation | 142 |
| abstract_inverted_index.processing. | 163 |
| abstract_inverted_index.maintenance, | 63 |
| abstract_inverted_index.preferential | 68 |
| abstract_inverted_index.relationship | 79 |
| abstract_inverted_index.oscillations, | 67, 112 |
| abstract_inverted_index.oscillations. | 26 |
| abstract_inverted_index.working-memory | 56, 162 |
| abstract_inverted_index.phase-dependent | 114 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| corresponding_author_ids | https://openalex.org/A5036330569 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I135140700, https://openalex.org/I4210125796 |
| citation_normalized_percentile.value | 0.99515674 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |