The Enigma Of Working Memory: Changing Views Part 2

Revealing Hidden Neural Networks in Working Memory

It is much more challenging to investigate the hypothesis that dynamically coupled, electrically silent neural networks underlie working memory, because physiological techniques, such as EEG, fMRI, and electrophysiology, monitor neuronal activity. Building on the TMS studies by Rose and others (2016), Wolff and others (2017) devised a unique approach to test for the presence of an electrically silent neural network maintaining unattended working memory (Fig. 1A).

In recent years, an increasing number of studies have shown that there is a close relationship between dynamic coupling and memory. Dynamic coupling refers to the coordination and synchronization between different areas in the human brain, while memory is the human brain's ability to store, process, and recall information.

Research has found that dynamic coupling can promote information transmission and integration between neurons in the human brain, improving human cognition and executive functions. At the same time, good dynamic coupling also helps promote people's learning and memory abilities. For example, when a person learns new knowledge, the coordination and synchronization between different areas will gradually strengthen, which will promote the storage and processing of new knowledge and facilitate the consolidation and improvement of memory.

Beyond this, research has found that different types of memory are associated with different dynamic couplings. For example, short-term memory is closely related to the degree of dynamic coupling between certain areas in the brain; long-term memory involves a wider range of areas in the brain and the dynamic coupling between them. Therefore, maintaining good dynamic coupling will help promote the improvement of people's different types of memory abilities.

Taken together, there is a positive link between dynamic coupling and memory. By strengthening dynamic coupling, people can improve cognitive and executive functions and promote learning and memory abilities. Therefore, we should actively explore and maintain good dynamic coupling to improve our memory and learning abilities and improve our quality of life. It can be seen that we need to improve memory, and Cistanche deserticola can significantly improve memory because Cistanche deserticola is a traditional Chinese medicinal material that has many unique effects, one of which is to improve memory. The efficacy of minced meat comes from the various active ingredients it contains, including acid, polysaccharides, flavonoids, etc. These ingredients can promote brain health in various ways.

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The investigators reasoned that if an electrically silent neural network had formed and was retained for the duration of working memory, then the response of the network at a systems level should differ from the response had this silent network not formed. 

Rather than apply a TMS pulse, the researchers provided an unrelated visual stimulus (target-shaped circles) to reactivate neural networks related to the visual working memory task. If synaptic plasticity had driven dynamic changes in connectivity in the working memory task, then probing these networks with a different stimulus should yield a different neural response than if the network had not been altered. 

The authors refer to this as “pinging” the neural networks to assess their response. Moreover, the nonspecific visual stimulus could, in theory, reactivate activity in the synaptically coupled silent neural networks encoding the memory, similar to TMS. This would appear as a reactivation of EEG responses that are evoked when the object is recalled from memory.

In preparation for the studies using the unrelated target-shaped image to “ping” the neural networks, participants viewed a screen displaying two objects adjacent to each other, and they were instructed to remember both items. After a short delay, an arrow pointed left or right to cue the observer as to which object should be remembered for a subsequent test. 

This object would then be retained in attended working memory, while the other object would be forgotten or retained in unattended (nonconscious) memory. The objects to remember were two stripe-filled circles that were rotated so that the stripes on each had different orientations. After a delay, a striped circle was displayed, and participants were required to indicate if that “probe” object had been rotated clockwise or counterclockwise from the striped circle they were keeping in working memory.

The results showed increased activity in the alpha band at appropriate electrode recording sites for objects in visual working memory corresponded to how much the probe object differed in rotation from the object in memory. If the orientation of the object in working memory had been forgotten, this discriminating EEG response would not have appeared, and the accuracy of the subjects’ reported responses would have dropped to chance. 

Second, the EEG response indicative of the degree of rotation of the probe image relative to the image in memory would decline with time, as working memory is sustained for only a matter of several seconds. The results showed that this EEG activity increased after the arrow cue and was sustained until the image was presented to test recall, but the activity slowly returned to baseline with time for the object in unattended memory (Fig. 1B). This supports the hypothesis that there are different mechanisms sustaining unattended and attended working memories, with persistent neural activity associated with attended but not unattended memories.

The researchers then used a third unrelated visual stimulus to ping the system for changes in neural network function driven by synaptic plasticity that theoretically records working memory. The unrelated stimulus boosted neural activity for the object in attended memory, but not the object held in unattended memory (Fig. 1C). The authors concluded that in contrast to attended working memories, unattended working memories are stored by synaptic plasticity forming dynamically coupled, but electrically silent neural networks, without the requirement for ongoing increases in neural activity.

Reexamining the Data

A recent study reexamined the original data by Wolff and others (2017) and found that the neural response to the object in unattended memory was sustained for the entire duration before recall when the data were analyzed differently. Instead of monitoring the EEG voltage, Barbosa and others (2021) analyzed the power of the alpha band EEG activity. The increased power of EEG activity that was indicative of both the objects in attended and unattended working memory was sustained for the duration before recall (Fig. 1D). 

The responses in terms of alpha power were boosted by the unrelated visual stimulus “pinging” the system, but the fact that an active response was evident for both attended and unattended memories render somewhat moot the effects of eliciting active responses to visual pinging as a method to reveal hidden states storing memory. Moreover, visual pinging could energize activity in neural networks sustained by action potential firing as well as for putative electrically silent networks, so the visual pinging technique cannot clearly distinguish between these two mechanisms of information storage.

Barbosa and others (2021) reason that voltage measurements are subject to greater variance because of baseline drift and variation in the impedance of scalp electrodes, whereas the frequency and power of oscillations are more robust to such technical difficulties. Thus, the ongoing increase in neural activity associated with unattended memory was not detected by Wolff and others (2017) because of signal-to-noise limitations. Moreover, their analysis showed that the power of the statistical analysis of the original data was weak and that a larger sample size would likely have detected increased sustained activity during the delay period for objects in unattended memory. 

A closer analysis also showed wide subject-to-subject variation in responses, and that in many instances sustained increases in EEG voltage were evident accompanying unattended memory, but in other test subjects this was not evident. The increased variance would have undermined efforts to identify a persistent increase in electrical activity sustaining unattended memory.

Conclusions

A reanalysis of the original data overturns the conclusions of the influential study by Wolff and others (2017) that failed to find a signature of working memory in terms of elevated sustained EEG activity, but it does not invalidate the experiments, nor provide evidence that synaptic plasticity does not form dynamic ensembles of neural networks underlying working memory. The reanalysis only demonstrates the truism that “the absence of evidence is not evidence of absence.” The original experiments and the data are valid, but the conclusions change when analyzed differently.

Importantly, these two papers demonstrate the power of collaboration in scientific research, as Wolff and colleagues provided their raw data to Barbosa and colleagues for reanalysis and they are gratefully acknowledged for their helpful discussions. Both groups recognize that it is far more difficult to obtain experimental evidence in support of the synaptic plasticity mechanism for working memory since it is by definition electrically silent. 

This is especially so if such silent mechanisms operate in tandem with active mechanisms that confound their detection. Thus, the axiom regarding “the absence of evidence . . .” pertains even more to dismissing the silent neural network hypothesis based on the current lack of evidence.

Indeed, these two mechanisms may operate together. Studies by Trübutschek and others (2017) show that participants can recall information that they have no conscious awareness of even though there is no active neural response detected by EEG that is sustained during the delay period before testing recall. They suggest that, following a transient encoding phase via active neuronal firing, nonconscious stimuli may be maintained by active short-term changes in synaptic weights without any detectable neural activity, allowing retrieval for several seconds.

How to reveal the existence of a possible electrically silent neural process remains an enigma, but finding ways to explore possible changes in synaptic connectivity that may attend working memory will remain a vigorous endeavor, which will no doubt spark new collaborations and new advances.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest concerning the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by NIH intramural grant no. ZIAHD000713.

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