Dataset Information

Dynamic hidden states underlying working-memory-guided behavior.

ABSTRACT: 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.

SUBMITTER: Wolff MJ

PROVIDER: S-EPMC5446784 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Publications

Dynamic hidden states underlying working-memory-guided behavior.

Wolff Michael J MJ Jochim Janina J Akyürek Elkan G EG Stokes Mark G MG

Nature neuroscience 20170417 6

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 ...[more]

PMID: 28414333

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Project description:Obstructive sleep apnea (OSA) is characterized by the frequent presence of neuro-cognitive impairment. Recent studies associate cognitive dysfunction with altered resting-state brain connectivity between key nodes of the executive and default-mode networks, two anti-correlated functional networks whose strength of activation increases or decreases with cognitive activity, respectively. To date no study has investigated a relationship between cognitive impairment in OSA and brain connectivity during an active working-memory challenge. We thus investigated the effect of OSA on working-memory performance and underlying brain connectivity. OSA patients and matched healthy controls underwent functional magnetic resonance imaging (fMRI) scanning while performing a 2-back working-memory task. Standard fMRI analyses highlighted the brain regions activated at increasing levels of working-memory load, which were used as seeds in connectivity analyses. The latter were based on a multiregional Psycho-Physiological-Interaction (PPI) approach, to unveil group differences in effective connectivity underlying working-memory performance. Compared with controls, in OSA patients normal working-memory performance reflected in: a) reduced interhemispheric effective connectivity between the frontal "executive" nodes of the working-memory network, and b) increased right-hemispheric connectivity among regions mediating the "salience-based" switch from the default resting-state mode to the effortful cognitive activity associated with the executive network. The strength of such connections was correlated, at increasing task-demands, with executive (Stroop test) and memory (Digit Span test) performance in neuro-cognitive evaluations. The analysis of effective connectivity changes during a working-memory challenge provides a complementary window, compared with resting-state studies, on the mechanisms supporting preserved performance despite functional and structural brain modifications in OSA.

Dataset Information

Dynamic hidden states underlying working-memory-guided behavior.

Publications

Dynamic hidden states underlying working-memory-guided behavior.

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