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A quasi-comprehensive exploration of the mechanisms of spatial working memory

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Why do some spatial patterns stick in our memory more than others? Liqiang Huang delves into the intricate mechanisms behind spatial working memory by integrating multiple theories into a single conceptual model.

Image courtesy of interviewee. October 4, 2024

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This video discusses the concept of spatial working memory, which refers to our ability to remember spatial patterns and visual information at a given moment. It highlights that working memory can be divided into two components: one for visual information (like colors and locations) and another for verbal information. The speaker is studying cognitive factors influencing how well we can remember different objects and patterns, emphasizing the importance of regularity and organization.

The speaker aims to create an overarching framework to integrate various mechanisms discovered in past studies. They express frustration over the fragmented nature of psychology research, where new findings often overshadow older ones without forming a cohesive understanding. To address this, the speaker built an online platform to conduct large-scale experiments disguised as games, allowing data collection from a broader audience.

During the COVID pandemic, a collaboration with a game company helped enhance data collection significantly. The experiments involve presenting participants with visual memory tasks, where they must recall the locations of dots after a brief presentation.

The speaker believes that traditional methods in psychology could benefit from insights drawn from artificial intelligence, particularly using neural networks to better model and explain working memory processes. They discuss ongoing collaborative research into understanding emotions and visual perception, aiming to improve the breadth and applicability of psychological studies.

The overall goal is to produce more relevant, real-world applications based on comprehensive, high-quality data, addressing key questions in psychology that remain unresolved due to a lack of adequate research frameworks.

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Here are five key points from the video regarding spatial working memory and its study in psychology:

1. **Definition and Components of Working Memory**:
Spatial working memory is a form of working memory that focuses on visual and spatial information, such as remembering locations and patterns. Working memory generally has two parts: one for visual information and another for verbal information. Spatial working memory specifically relates to the visual aspect.

2. **Mechanisms of Memory and Cognitive Factors**:
The study of spatial working memory encompasses various mechanisms of remembering, such as chunking and categorization. The video highlights the fragmented nature of psychological research, which often focuses on isolated factors instead of an integrated framework for understanding memory.

3. **Challenges in Psychological Research**:
There is a lack of consensus in the psychological community regarding a comprehensive framework for memory. Despite numerous studies, the author notes the difficulty of synthesizing findings into a coherent model to guide practical applications, such as teaching techniques for better memory retention.

4. **Innovative Data Collection via Gaming**:
The author describes an innovative approach to data collection through a partnership with a game company, allowing for the collection of significant amounts of data during the COVID-19 pandemic. This method attracted many participants and extensive data for analyzing spatial working memory tasks.

5. **Combining Cognitive Models with Neural Networks**:
The ongoing research aims to develop a more complex and holistic cognitive model by integrating insights from artificial intelligence, particularly neural networks. The author believes that modern psychology can benefit from a better understanding of various cognitive processes to create an overarching framework, moving beyond the fragmented nature of current studies.

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Here are some key quotes and concepts extracted from the video:

1. **Definition of Spatial Working Memory**:
- "Spatial working memory is basically what we remember at this moment, like a spatial pattern or something in front of you."

2. **Components of Working Memory**:
- "Working memory is normally assumed to include two parts: one part for visual information... and another part for verbal information."

3. **Nature of Cognitive Studies**:
- "In psychology studies, unlike physics, things tend to be fragmented."

4. **Framework Challenge**:
- "Unfortunately, there is no overall framework or at least there's no overall framework that everyone agrees with."

5. **Research Approach**:
- "The particular study I'm trying to... is to try to build up an overall framework."

6. **Experimental Psychology Standards**:
- "In experimental psychology, we normally only need a few, or like, tens of participants and each participating for one hour."

7. **Data Collection Strategy**:
- "I spent some time to try to build up an online platform to package those experiments as games and attract people to play those games."

8. **Collaboration with Gaming Industry**:
- "...some guy approached me... I work for this game company... maybe they want to make a friend and then they offer to implement my experiment as one component in their game."

9. **Neural Networks**:
- "We want to use this neural network...to combine different mechanisms... we build a neural network to do that and then train the neural network to predict people's working memory on different patterns."

10. **Psychology's Fragmentation Issues**:
- "I have this idea or belief now that there is something wrong... with the way how psychology has been studying things because mainly because it's fragmented."

11. **Aim for Comprehensive Models**:
- "We never evolve into an overall framework... maybe we can borrow this insight from Artificial Intelligence and try to build something that's more complex and more complete."

12. **Exploration of Emotions**:
- "In psychology, there is this model on emotion... we tend to believe that neither of those are complete."

These quotes highlight the speaker's exploration of spatial working memory, the need for a unified framework in psychology, the importance of large-scale studies, and the integration of technology like neural networks into psychological research.

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Here are some similar articles that discuss concepts related to working memory, cognitive psychology, and the integration of behavioral data with technology:

1. **Working Memory and Its Components**
- This article provides an overview of working memory, detailing its subdivisions into visual-spatial and verbal systems, and explores how these components interact to influence learning and memory retention.

2. **Cognitive Models of Memory: A Review**
- This literature review examines various cognitive models of memory and the fragmentation within the field. It discusses the potential for a unified model that integrates previous findings from diverse studies.

3. **The Role of Chunking in Memory Recall**
- An analysis of how chunking strategies enhance working memory capacity. The article discusses experimental results that support the efficacy of chunking in improving recall performance across different convideos.

4. **Harnessing Gamification for Psychological Research**
- This piece explores how video games can be used as tools for collecting psychological data. It discusses the utilization of game mechanics to engage participants and gather meaningful data for cognitive experiments.

5. **Neural Networks in Cognitive Psychology: A New Frontier**
- An exploration of how neural networks are being applied in cognitive psychology to model complex processes such as memory. The article reviews recent findings and proposes frameworks for combining neural networks with traditional psychological theories.

6. **Spatial Memory: The Science Behind Navigating Spaces**
- This article delves into spatial memory and the ways in which individuals remember locations. It explores theories and models that explain how people navigate and recall spatial information.

7. **Challenges in the Psychology of Emotions**
- A critical review of existing models of emotions in psychology. The article addresses the limitations of current frameworks and suggests directions for future research using large-scale data to develop more holistic models of emotional experience.

8. **The Intersection of Artificial Intelligence and Cognitive Research**
- An overview of how AI technologies are being integrated into cognitive research to enhance data analysis and experimental design, with a focus on applications in understanding human memory and cognition.

9. **Understanding Visual Cognition: Memory and Perception**
- A comprehensive review of the intersections between visual memory and perception, discussing various mechanisms that influence how we remember and interpret visual stimuli.

10. **Building a Unified Framework for Memory Research**
- A proposal for a comprehensive framework to consolidate various aspects of memory research, highlighting the need for collaboration and integration of findings from multiple studies.

These articles collectively cover the theoretical underpinnings of working memory, the application of technology in psychological research, and the ongoing attempts to unify fragmented strands of cognitive psychology.

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Spatial working memory is basically what we

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remember at at this moment.

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Um, like a spatial pattern or something in front of you.

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Um, in psychology there is, working memory,

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the basic concept,

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but, working memory, is normally assumed to,

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include two parts.

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One part for visual information, like you remember,

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remember colors or remember a lot of loca.

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Um, a few locations, like if I like po, point a few

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locations and you can remember that.

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And another part is for verbal information.

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Like I, speak something a KCY,

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you can remember those letters.

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And, that's the two parts of working memory.

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And the, special working memory is one part of the

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visual, part of working memory.

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Like the, what we remember about the special information,

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what I'm studying is, cognitive factors,

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basically the stimuli side.

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So what, kind of objects can we remember better?

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And, in what way do we remember them?

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So for example,

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if I present a few things in front of you

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and they're very regular,

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you can remember those more easily than a

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few scattered thing.

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In. In this study, I'm trying to combine things like,

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there are about, 10 to 15 different mechanisms

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that has been dec discovered in previous studies.

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Uh, like what I just mentioned about regularity.

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That's one thing, like chunking

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and of, of course, the other factors, like, like,

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categorical information or like base integration.

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Uh, there are all those fancy terms,

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but, for our purpose,

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the important thing

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that they're all different from each other.

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And, so, as you may

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or may not be aware, in the psychology studies,

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unlike physics, things tends to be fragmented.

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Like people discuss, discover one thing

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and they discover another thing.

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So it's more always, in those topics related to

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like, other things,

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but it also applies to working memory.

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For example, my wife, always ask me like,

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you study memory, so how do we like teach our child

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so they can remember things better?

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And I told her they all kind of different studies,

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and this and that,

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but unfortunately there is no overall like a framework

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or at least there's no overall framework

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that everyone agree with.

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So the ca the particular study I'm trying to,

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I have done recently, and I'm trying to do,

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more things on this, is to try to build up,

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overall framework.

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So to combine things together and experimental psychology.

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Uh, the typical standard is we run,

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participant for something from 10 to 20,

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sometimes maybe 40, 50.

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But, normally we don't need to go more than like,

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like a hundred to establish a point,

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unlike some other area, like, they need larger study.

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But in experimental, psychology,

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we normally only need a few,

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or like, tens of participants

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and each participating for one hour.

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And, so as you know, like, when we want to

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explicit a complex pattern, we need a lot

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of statistical power, a lot

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of information to figure things out.

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That's why we need a large scale experiment.

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So I spent, some time to try

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to build up a online platform to like,

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packages those, experiment as games

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and attract people to play those games.

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And, interesting, thing is that this doesn't work

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very well at first

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because, it takes a long time to attract people.

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And, but at some point, some guy approached me

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and, say, what are you exactly trying

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to do with this?

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Uh, those

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and then,

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really look like real games not so interesting.

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And, but,

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and obviously you're not gonna make money out of it.

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And why, why are you doing this? And I just told him.

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And then he told me, okay, I work

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for this game company, real game company.

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So maybe like, as a,

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because many of the, zen are also interested,

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in psychology.

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So maybe they want to make a friend

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and then they offer to implement

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my experiment are one component in their game,

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actually popular game, like,

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and then they did it, it actually cost me nothing

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to collect data for like, let me see how to,

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hundred of thousand of hours.

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And, like, of course not regular hours

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because some just play for a few like a minute

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and then left some play for longer.

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But, all come together like, hundreds of thousands

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of like hours.

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And then I got that data and then analyze that.

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And so do this task.

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I present, a few dots in, like a

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six by six array.

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And then, they

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Disappear within a second or so.

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And then, like,

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after another second, the participant have to point out

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where are those locations they have seen,

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it's a standard working memory task.

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So because, by the time we did that,

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the game company helped me to do that,

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it was in the covid time.

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So they, they, like, they have this game related to covid,

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so they, okay, so maybe they package that

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as a one little component in their game.

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And, like you are catching those wires, like,

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something like that.

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The reason why we want to use this neural network is

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because when we want to combine different mechanisms,

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we don't know what we are expecting

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because that's a different perspective from the traditional

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experimental psychology in which you like, just,

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test a hypothesis

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and you say, okay, hypothesis is significant,

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and then you establish a point.

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But now what I'm trying to do, I want to build a model

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to explain the data as much as possible.

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So there's no always benchmark on

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how good is good enough.

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Obviously you will not be able to explain everything.

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Um, and, you'll always be able to explain something.

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So what, how good is good is,

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quite weak, quite ambiguous.

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So I think, okay, maybe,

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nowadays neural network is like,

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a good standard, good standard for like,

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almost everything.

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And then maybe we build a neural network to do that

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and then train neur neural network to predict like, the,

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like, people's working memory on different patterns

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and see how much can the,

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can the neural network explain the data?

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And then we compare our cognitive model.

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It's more complex than the typical one,

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but it's still a cognitive model in and fully interpretable.

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Uh, and then compare that to neural network.

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Uh, it's, didn't do as well as neural network,

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but it's get close.

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So that's like, so we think, okay,

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that's good enough because it's already

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close to a neural network.

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I have this, idea

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or belief now that, there is something wrong

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or at least incomplete with the way how,

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psychology has been studying things because mainly

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because it's fragmented and,

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and we're not going anywhere, like

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after 20 years we discover a lot of things

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and then people forget about those older things

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and then keep digging new things.

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We never evolve into overall framework.

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So that's why I think, okay, maybe we can borrow

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this insight from the

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Artificial intelligence and try to build something

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that's more complex and, but more complete.

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So for that purpose, that's why we need,

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large scale experiment.

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We need a lot of data for that purpose.

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So with this general idea, I started

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with the topic I'm more familiar with,

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but now with that in hand now, with a bunch

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of collaborators, we are moving towards something

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that's more real world relevant, like also like,

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using large scale experiment.

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Um, for example, in this one study, we,

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a, a few collaborators, collaborator, collaborators

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and I, we are trying to figure out what is,

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how we actually, represent emotion in our,

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in our ma in our mind.

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Uh, you may have heard that,

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in psychology there is this model, on emotion.

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Some of them is divided into different categories like

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happiness or sadness, et cetera.

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Some of them like,

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map all those different emotions into in A 2D space.

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But, we tend to believe that neither

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of those are complete.

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And the reason why we don't have anything better,

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for this very important question is we don't have a large

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scale, high quality data for us to build a model on it.

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And, that's what we are doing now

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and the few other things on visual beauty

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and also on visual expression.

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And that's what, we like, I I just mentioned.

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And also on like, language understanding

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or the different things.

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So hopefully those will make, like, larger impact

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and hopefully we'll get into some real

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world applications.

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Uh, but we are working on that.

Understanding Spatial Working Memory: A Dual-Faceted Approach

00:00:00 - Spatial working memory is basically what we remember at at this moment. like a spatial pattern or something in front of you. in psychology there is, working memory, the basic concept, but, working memory, is normally assumed to, include two parts. One part for visual information, like you remember, remember colors or remember a lot of loca. a few locations, like if I like po, point a few

00:00:37 - And another part is for verbal information. Like I, speak something a KCY, you can remember those letters. And, that's the two parts of working memory. And the, special working memory is one part of the visual, part of working memory. Like the, what we remember about the special information, what I'm studying is, cognitive factors, basically the stimuli side.

00:01:11 - And, in what way do we remember them? So for example, if I present a few things in front of you and they're very regular, you can remember those more easily than a few scattered thing. In. In this study, I'm trying to combine things like, there are about, 10 to 15 different mechanisms that has been dec discovered in previous studies.

Fragmentation in Psychological Research and the Quest for a Unified Framework

00:01:43 - That's one thing, like chunking and of, of course, the other factors, like, like, categorical information or like base integration. there are all those fancy terms, but, for our purpose, the important thing that they're all different from each other. And, so, as you may or may not be aware, in the psychology studies, unlike physics, things tends to be fragmented.

00:02:16 - and they discover another thing. So it's more always, in those topics related to like, other things, but it also applies to working memory. For example, my wife, always ask me like, you study memory, so how do we like teach our child so they can remember things better? And I told her they all kind of different studies,

00:02:45 - but unfortunately there is no overall like a framework or at least there's no overall framework that everyone agree with. So the ca the particular study I'm trying to, I have done recently, and I'm trying to do, more things on this, is to try to build up, overall framework. So to combine things together and experimental psychology. the typical standard is we run,

Challenges in Conducting Large-Scale Experiments in Psychology

00:03:21 - sometimes maybe 40, 50. But, normally we don't need to go more than like, like a hundred to establish a point, unlike some other area, like, they need larger study. But in experimental, psychology, we normally only need a few, or like, tens of participants and each participating for one hour. And, so as you know, like, when we want to

00:03:57 - of statistical power, a lot of information to figure things out. That's why we need a large scale experiment. So I spent, some time to try to build up a online platform to like, packages those, experiment as games and attract people to play those games. And, interesting, thing is that this doesn't work

00:04:24 - because, it takes a long time to attract people. And, but at some point, some guy approached me and, say, what are you exactly trying to do with this? those and then, really look like real games not so interesting. And, but, and obviously you're not gonna make money out of it. And why, why are you doing this? And I just told him. And then he told me, okay, I work for this game company, real game company.

Leveraging Gaming for Memory Research During COVID

00:04:58 - because many of the, zen are also interested, in psychology. So maybe they want to make a friend and then they offer to implement my experiment are one component in their game, actually popular game, like, and then they did it, it actually cost me nothing to collect data for like, let me see how to, hundred of thousand of hours.

00:05:31 - because some just play for a few like a minute and then left some play for longer. But, all come together like, hundreds of thousands of like hours. And then I got that data and then analyze that. And so do this task. I present, a few dots in, like a six by six array. And then, they

00:05:59 - And then, like, after another second, the participant have to point out where are those locations they have seen, it's a standard working memory task. So because, by the time we did that, the game company helped me to do that, it was in the covid time. So they, they, like, they have this game related to covid, so they, okay, so maybe they package that as a one little component in their game.

Integrating Neural Networks with Working Memory Research

00:06:33 - something like that. The reason why we want to use this neural network is because when we want to combine different mechanisms, we don't know what we are expecting because that's a different perspective from the traditional experimental psychology in which you like, just, test a hypothesis and you say, okay, hypothesis is significant, and then you establish a point.

00:07:02 - to explain the data as much as possible. So there's no always benchmark on how good is good enough. Obviously you will not be able to explain everything. and, you'll always be able to explain something. So what, how good is good is, quite weak, quite ambiguous. So I think, okay, maybe, nowadays neural network is like,

00:07:36 - almost everything. And then maybe we build a neural network to do that and then train neur neural network to predict like, the, like, people's working memory on different patterns and see how much can the, can the neural network explain the data? And then we compare our cognitive model. It's more complex than the typical one, but it's still a cognitive model in and fully interpretable.

Integrating AI Insights into Psychology Research

00:08:07 - it's, didn't do as well as neural network, but it's get close. So that's like, so we think, okay, that's good enough because it's already close to a neural network. I have this, idea or belief now that, there is something wrong or at least incomplete with the way how, psychology has been studying things because mainly because it's fragmented and,

00:08:38 - after 20 years we discover a lot of things and then people forget about those older things and then keep digging new things. We never evolve into overall framework. So that's why I think, okay, maybe we can borrow this insight from the Artificial intelligence and try to build something that's more complex and, but more complete. So for that purpose, that's why we need, large scale experiment.

00:09:09 - So with this general idea, I started with the topic I'm more familiar with, but now with that in hand now, with a bunch of collaborators, we are moving towards something that's more real world relevant, like also like, using large scale experiment. for example, in this one study, we, a, a few collaborators, collaborator, collaborators and I, we are trying to figure out what is,

Advancing Emotional Models in Psychology

00:09:44 - in our ma in our mind. you may have heard that, in psychology there is this model, on emotion. Some of them is divided into different categories like happiness or sadness, et cetera. Some of them like, map all those different emotions into in A 2D space. But, we tend to believe that neither of those are complete. And the reason why we don't have anything better,

00:10:17 - scale, high quality data for us to build a model on it. And, that's what we are doing now and the few other things on visual beauty and also on visual expression. And that's what, we like, I I just mentioned. And also on like, language understanding or the different things. So hopefully those will make, like, larger impact

00:10:50 - world applications. but we are working on that.

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