Dynamic hidden states underlying working-memory-guided behavior
Recent theoretical models propose that working memory is mediated by rapid transitions in 'activity-silent' neural states (for example, short-term synaptic plasticity). According to the dynamic coding framework, such hidden state transitions flexibly configure memory networks for memory-gu...
| Main Authors: | , , , |
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| Format: | Journal article |
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Springer Nature
2017
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| _version_ | 1797097047860445184 |
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| author | Wolff, M Jochim, J Akyürek, E Stokes, M |
| author_facet | Wolff, M Jochim, J Akyürek, E Stokes, M |
| author_sort | Wolff, M |
| collection | OXFORD |
| description | Recent theoretical models propose that working memory is mediated by rapid transitions in 'activity-silent' neural states (for example, short-term synaptic plasticity). According to the dynamic coding framework, such hidden state transitions flexibly configure memory networks for memory-guided behavior and dissolve them equally fast to allow forgetting. We developed a perturbation approach to measure mnemonic hidden states in an electroencephalogram. By 'pinging' the brain during maintenance, we show that memory-item-specific information is decodable from the impulse response, even in the absence of attention and lingering delay activity. Moreover, hidden memories are remarkably flexible: an instruction cue that directs people to forget one item is sufficient to wipe the corresponding trace from the hidden state. In contrast, temporarily unattended items remain robustly coded in the hidden state, decoupling attentional focus from cue-directed forgetting. Finally, the strength of hidden-state coding predicts the accuracy of working-memory-guided behavior, including memory precision. |
| first_indexed | 2024-03-07T04:50:07Z |
| format | Journal article |
| id | oxford-uuid:d4a8d11d-b8de-4e4b-8259-73f2a08cda4f |
| institution | University of Oxford |
| last_indexed | 2024-03-07T04:50:07Z |
| publishDate | 2017 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:d4a8d11d-b8de-4e4b-8259-73f2a08cda4f2022-03-27T08:20:20ZDynamic hidden states underlying working-memory-guided behaviorJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d4a8d11d-b8de-4e4b-8259-73f2a08cda4fSymplectic Elements at OxfordSpringer Nature2017Wolff, MJochim, JAkyürek, EStokes, MRecent theoretical models propose that working memory is mediated by rapid transitions in 'activity-silent' neural states (for example, short-term synaptic plasticity). According to the dynamic coding framework, such hidden state transitions flexibly configure memory networks for memory-guided behavior and dissolve them equally fast to allow forgetting. We developed a perturbation approach to measure mnemonic hidden states in an electroencephalogram. By 'pinging' the brain during maintenance, we show that memory-item-specific information is decodable from the impulse response, even in the absence of attention and lingering delay activity. Moreover, hidden memories are remarkably flexible: an instruction cue that directs people to forget one item is sufficient to wipe the corresponding trace from the hidden state. In contrast, temporarily unattended items remain robustly coded in the hidden state, decoupling attentional focus from cue-directed forgetting. Finally, the strength of hidden-state coding predicts the accuracy of working-memory-guided behavior, including memory precision. |
| spellingShingle | Wolff, M Jochim, J Akyürek, E Stokes, M Dynamic hidden states underlying working-memory-guided behavior |
| title | Dynamic hidden states underlying working-memory-guided behavior |
| title_full | Dynamic hidden states underlying working-memory-guided behavior |
| title_fullStr | Dynamic hidden states underlying working-memory-guided behavior |
| title_full_unstemmed | Dynamic hidden states underlying working-memory-guided behavior |
| title_short | Dynamic hidden states underlying working-memory-guided behavior |
| title_sort | dynamic hidden states underlying working memory guided behavior |
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