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A Tradeoff Between Accuracy and Flexibility in a Working Memory Circuit Endowed with Slow Feedback Mechanisms.

ABSTRACT: Recent studies have shown that reverberation underlying mnemonic persistent activity must be slow, to ensure the stability of a working memory system and to give rise to long neural transients capable of accumulation of information over time. Is the slower the underlying process, the better? To address this question, we investigated 3 slow biophysical mechanisms that are activity-dependent and prominently present in the prefrontal cortex: Depolarization-induced suppression of inhibition (DSI), calcium-dependent nonspecific cationic current (ICAN), and short-term facilitation. Using a spiking network model for spatial working memory, we found that these processes enhance the memory accuracy by counteracting noise-induced drifts, heterogeneity-induced biases, and distractors. Furthermore, the incorporation of DSI and ICAN enlarges the range of network's parameter values required for working memory function. However, when a progressively slower process dominates the network, it becomes increasingly more difficult to erase a memory trace. We demonstrate this accuracy-flexibility tradeoff quantitatively and interpret it using a state-space analysis. Our results supports the scenario where N-methyl-d-aspartate receptor-dependent recurrent excitation is the workhorse for the maintenance of persistent activity, whereas slow synaptic or cellular processes contribute to the robustness of mnemonic function in a tradeoff that potentially can be adjusted according to behavioral demands.

SUBMITTER: Pereira J

PROVIDER: S-EPMC4585505 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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A Tradeoff Between Accuracy and Flexibility in a Working Memory Circuit Endowed with Slow Feedback Mechanisms.

Pereira Jacinto J Wang Xiao-Jing XJ

Cerebral cortex (New York, N.Y. : 1991) 20140924 10

Recent studies have shown that reverberation underlying mnemonic persistent activity must be slow, to ensure the stability of a working memory system and to give rise to long neural transients capable of accumulation of information over time. Is the slower the underlying process, the better? To address this question, we investigated 3 slow biophysical mechanisms that are activity-dependent and prominently present in the prefrontal cortex: Depolarization-induced suppression of inhibition (DSI), c ...[more]

PMID: 25253801

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Project description:Uncovering the underlying biophysical principles of emergent collective computational abilities, such as working memory, in neural circuits is one of the most essential concerns in modern neuroscience. Working memory system is often desired to be robust against noises. Such systems can be highly flexible for adapting environmental demands. How neural circuits reconfigure themselves according to the cognitive task requirement remains unclear. Previous studies explored the robustness and the flexibility in working memory by tracing individual dynamical trajectories in a limited time scale, where the accuracy of the results depends on the volume of the collected statistical data. Inspired by thermodynamics and statistical mechanics in physical systems, we developed a non-equilibrium landscape and flux framework for studying the neural network dynamics. Applying this approach to a biophysically based working memory model, we investigated how changes in the recurrent excitation mediated by slow NMDA receptors within a selective population and mutual inhibition mediated by GABAergic interneurons between populations affect the robustness against noises. This is realized through quantifying the underlying non-equilibrium potential landscape topography and the kinetics of state switching. We found that an optimal compromise for a working memory circuit between the robustness and the flexibility can be achieved through the emergence of an intermediate state between the working memory states. An optimal combination of both increased self-excitation and inhibition can enhance the flexibility to external signals without significantly reducing the robustness to the random fluctuations. Furthermore, we found that the enhanced performance in working memory is supported by larger energy consumption. Our approach can facilitate the design of new network structure for cognitive functions with the optimal balance between performance and cost. Our work also provides a new paradigm for exploring the underlying mechanisms of many cognitive functions based on non-equilibrium physics.

Project description:Visual working memory capacity is estimated to be around 3-4 items, but on some trials participants fail to correctly report even a single item from the memory array. Such failures of working memory performance are surprisingly common, and participants have poor self-awareness of them. Previous work has shown that behavioral feedback can reduce the frequency of working memory failures, but the benefits of feedback disappeared immediately after it was taken away. Here, we tested whether extended practice with or without trial-by-trial feedback would lead to persistent improvements in working memory performance. Participants were assigned to one of four groups: (1) Working memory practice with feedback (2) Working memory practice without feedback (3) Crossword puzzle active control (4) No-contact control. Consistent with previous work, simple practice with a visual working memory task robustly improved working memory performance across practice sessions. However, we found only partial support for the efficacy of feedback in improving working memory performance. Practicing with feedback improved working memory performance relative to a no-feedback group for some practice sessions. However, the feedback benefits did not persist across all training sessions and did not transfer to a final test session without the feedback. Thus, the benefits of performance feedback did not persist over time. Further, we found only stimulus-specific transfer of visual working memory practice benefits. We also found that participants' metaknowledge improved with practice, but that receiving feedback about task accuracy actually slightly harmed the accuracy of concurrent metaknowledge ratings. Finally, we discuss important design considerations for future work in this area (e.g. power, expectations, and "spacing effects"). For example, we found that achieved statistical power to detect a between-groups effect declined with practice. This finding has potentially critical implications for any study using a 1-session study to calculate power for a planned multi-session study.

Dataset Information

A Tradeoff Between Accuracy and Flexibility in a Working Memory Circuit Endowed with Slow Feedback Mechanisms.

Publications

A Tradeoff Between Accuracy and Flexibility in a Working Memory Circuit Endowed with Slow Feedback Mechanisms.

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