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\b[<Delay-period activity> explains important properties of <working memory> when its information content and dynamics predict behavior; elevated activity alone is not a complete storage mechanism.] An explanation must account for maintaining an absent stimulus, limited <working memory capacity>, variable precision, interference and flexible prioritization. Different measurements reveal different aspects: <extracellular single-unit recording> measures individual <neurons>, <electroencephalography> measures aggregated electrical signals, and <functional magnetic resonance imaging> measures a slower hemodynamic response. None directly reads a unitary store.
The classic case for <persistent neural activity> came from delayed-response tasks. In <Shintaro Funahashi> and colleagues' 1989 experiment, monkeys maintained fixation after a briefly presented peripheral cue and later made a memory-guided <saccade>. <Dorsolateral prefrontal cortex> <neurons> could maintain location-selective firing during the intervening blank interval; <delay-period activity> was reduced or absent on some error trials. This connects a maintained code to a remembered location rather than merely to stimulus presence. It also supplies a plausible bridge between a short-lived sensory event and a later response. However, the remembered location and intended eye movement covaried, so the experiment does not isolate human mnemonic storage from prospective action coding.<Mnemonic Coding of Visual Space in the Monkey's Dorsolateral Prefrontal Cortex by Shintaro Funahashi and others>[1989, Summary and Conclusions; oculomotor delayed-response task]{ref}
More explanatory leverage comes from linking population dynamics to the \i[pattern] of errors. A <bump attractor> maintains a localized pattern through recurrent excitation and inhibition. Noise can move its center while leaving a memory trace present, predicting increasing uncertainty and trial-specific directional errors. <Klaus Wimmer> and colleagues tested such predictions against monkey prefrontal recordings and memory-guided eye movements: neural variability was related to fine-grained response errors in ways predicted by a diffusing representation. This is stronger than a generic activation–accuracy association because competing models need to explain that structured relationship. Nevertheless, it is evidence from a trained spatial task in monkeys; it does not by itself explain verbal rehearsal, binding errors or every source of human forgetting.<Bump attractor dynamics in prefrontal cortex explains behavioral precision in spatial working memory by Klaus Wimmer and others>[2014, abstract and tests of model-predicted neural–behavioral relationships]{ref}
Human recordings link delay signals to <working memory capacity>. In <Edward K. Vogel> and colleagues' visual-memory experiments, people remembered arrays on one side of fixation while ignoring the other. The <contralateral delay activity> increased with memory load and approached an asymptote associated with each person's behavioral <working memory capacity>. Its usefulness is the relation between a physiological load function and an independently estimated behavioral limit. It does not prove that the <brain> has exactly a fixed number of universal slots: stimulus complexity, filtering, allocation and the measurement's sensitivity can influence the signal. A plateau is evidence constraining a <working memory capacity> mechanism, not the mechanism itself.<Neural activity predicts individual differences in visual working memory capacity by Edward K. Vogel and others>[2004, load-dependent electrophysiology and individual capacity differences]{ref}
<Delay-period activity> also contains specific sensory information. <Stephenie A. Harrison> and <Frank Tong> presented oriented patterns and cued which orientation to remember. <Multivariate pattern analysis> of early <visual cortex> <functional magnetic resonance imaging> could identify the remembered orientation during the delay, even when mean activation was weak. This supports <sensory recruitment> and helps explain why visual memories retain feature-specific detail and may compete with new sensory input. Decoding establishes accessible information, however, not necessarily a local storage site: top-down feedback, <attention> or task preparation could generate a decodable pattern. Its slow hemodynamics cannot establish uninterrupted moment-to-moment firing.<Decoding reveals the contents of visual working memory in early visual areas by Stephenie A. Harrison and Frank Tong>[2009, orientation-memory task and delay-period decoding]{ref}
The temporal and priority structure of <working memory> challenges an exclusively tonic account. <Mikael Lundqvist> and colleagues recorded monkey prefrontal spiking and <local field potentials> and found brief <gamma oscillation> and <beta oscillation> bursts rather than uniformly sustained oscillatory activity. A smooth trial average can conceal intermittent events. This finding qualifies the interpretation of averaged persistence; it does not show that every <neuron> becomes silent between bursts, or that recurrent activity is irrelevant.<Gamma and Beta Bursts Underlie Working Memory by Mikael Lundqvist and others>[2016, abstract; trial-level prefrontal bursts and sensory reactivation]{ref}
Human perturbation experiments distinguish current priority from continued retention. In <Nathan S. Rose> and colleagues' task, a temporarily unattended item could cease to be decodable yet remain relevant for a later probe. A <transcranial magnetic stimulation> pulse reinstated a detectable representation under appropriate relevance conditions. In <Michael J. Wolff> and colleagues' experiment, a neutral visual impulse during the delay evoked an <electroencephalography> response carrying information about remembered items, including temporarily unattended ones; instructed forgetting and temporary inattention had different consequences, and the hidden-state measure related to <working memory precision>. These results explain how an item may remain available without occupying the same active state as the current focus of <attention>.<Reactivation of latent working memories with transcranial magnetic stimulation by Nathan S. Rose and others>[2016, retrocue and perturbation experiments]{ref}<Dynamic hidden states underlying working-memory-guided behavior by Michael J. Wolff and others>[2017, impulse-response decoding, instructed forgetting and behavioral precision]{ref}
An <activity-silent working memory> interpretation proposes temporarily altered network responsiveness, potentially involving <short-term synaptic plasticity>. Neither an absent decoding result nor a successful perturbation identifies that molecular mechanism uniquely: weak or recoded activity can evade a particular measurement, and perturbation can recruit distributed networks. The strongest conclusion is therefore pluralistic. <Persistent neural activity> offers a plausible mechanism for some maintenance and precision effects, while intermittent and latent states help explain prioritization and retained but unattended information. A successful theory must jointly predict errors, load effects and perturbation consequences at the appropriate time scale. \b[<Delay-period activity> provides substantial mechanistic constraints, but human <working memory> is better explained by interacting representations and control states than by equating storage with continuously elevated firing.]
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