Games are fundamentally human-centered. When we design games, we design systems that are coherent to our reasoning systems. We are natural primates that have a belief making system, rationalizing and making sense of the world around us, and therefore design tools that make sense to our own human design. Therefore, when we games, we must rules, interaction, and sysstem that are algined to how we think, feel, and behave.

Cognitive Science: An Introduction to the Study of Mind by Fridenberg et al. discusses Cognitive Science as an interdisciplinary field that discusses and connect the scientific study of the mind and its processes, drawing on: psychology, neuroscience, philosophy, linguistics, anthropology, artificial intelligence, etc. It seeks to understand how intelligent behavior is represented, computed, embodied, and socially situated. Thus, with such knowledge of how the mind works, we can begin to structure our design with human-intent.

Games, as interactive experiences, are deeply tied to cognitive structures—from perception and attention to memory, decision-making, and even affective (emotional) states. We can create experiences that resonate, challenge, intuitive, and bring humans into flow naturally.

Memory,Problem Solving, Imagery, and Concepts

Fridenberg dissects cognition through high-level cognitive processes, which are internal representations that are deeply functional and structural components of human thinking. It is the ideal framework for understanding how humans learn, imagine, solve, and experience games

Fridenberg et al. begins by identifying memory as a multifunctional system critical to learning—whether in humans or machines. It distinguishes between three types of memory: Sensory Memory: A brief storage system for raw sensory data (e.g., iconic memory for visuals and echoic memory for sounds), Working Memory: Where active cognitive tasks like reasoning and gameplay decision-making happen. It holds only 7 ± 2 items and operates across visual, auditory, and semantic codes, and Long-Term Memory: This is subdivided into implicit memory (procedural knowledge like how to double-jump or wall-climb) and explicit memory (semantic knowledge like lore and episodic memories of past in-game events). Thus, in our game design, working memory is especially important: it helps determine how much information players can manage on screen—menus, HUD elements, spatial layouts, dialogue. If a game overloads working memory, it leads to cognitive fatigue. Hence, designing for chunking, tutorial pacing, and progressive disclosure becomes essential.

A game can also be represented as a problem-solving experience. Every genre—whether it’s a puzzle game like The Witness, an action-adventure like Zelda, or a real-time strategy game like StarCraft—it invite players to navigate problems under specific constraints. Fridenberg et al. emphasizes this dimension of cognition by exploring models of human problem-solving and we can map these models elegantly onto our design process and game structures. Fridenberg et al. introduces the General Problem Solver (GPS) model by Newell and Simon, which frames problem-solving as navigating a structured problem space: beginning with an initial state, moving through intermediate states, and reaching a goal state by applying a series of operators (actions), often guided by subgoals. This mirrors how players engage with games: when they enter a level, encounter an obstacle, and use in-game tools or mechanics to progress toward completion. Designers create these spaces intentionally—by laying out levels, rules, and affordances that encourage exploration, experimentation, and learning. Naturall, the GPS framework helps us reason that games can be transformed into a formalized learning systems. When a game introduces new mechanics, puzzles, or enemies, it’s effectively teaching players a new language of problem-solving. Players develop internal models (cognitive schemas) of the game world, adapt through trial and error, and gradually master challenges. Each gameplay loop—whether it's unlocking a door, timing a jump, optimizing a resource economy, or outwitting an opponent—represents a structured cognitive task.

Fridenberg et al. discusses SOAR, a more dynamic architecture that builds on GPS, highlighting how human problem-solving involves subgoaling, chunking, and the creation of production rules based on experience. Applied to game design, this suggests that good games scaffold complexity: they give players just enough information to proceed, while prompting them to form internal rules, patterns, and strategies. This is especially visible in puzzle games, where players must infer systems (e.g., Baba is You or Stephen’s Sausage Roll), but it's equally applicable in action combat or survival games, where strategies emerge from repeated play and evolving difficulty.

Visual Imagery is anchored in the Kosslyn and Schwartz theory, which proposes that visual images are isomorphic to real-world perception—they maintain spatial relationships and are manipulable internally. Game designers benefit by aligning spatial puzzles or maps with how players mentally model space. Good level design uses mental scaffolds, such as landmarks or symmetrical patterns, that align with these internal visualizations. Portal and Superliminal are examples of games built on the player's capacity for spatial imagination.

Concepts, as explored by Fridenberg et al., represent another vital layer of cognition that plays a central role in how players understand and assign meaning within a game. A “power-up,” a “checkpoint,” or even a “boss fight” can be more than just mechanical features—they are cognitive constructs. Fridenberg et al. outlines two models of how concepts are formed: feature-based theories, which treat concepts as bundles of definable properties, and Barsalou’s Perceptual Simulation Theory, which argues that concepts are constructed dynamically using perceptual experiences. The latter is particularly useful for game design, as it encourages designers to think of concepts not as static labels but as embodied experiences. For instance, a “lava pit” is not just labeled dangerous—it feels dangerous through glowing visuals, heat shimmer, crackling audio, and damage feedback. This aligns directly with the principle of ludonarrative consonance, where a game’s mechanics and systems tell the story just as much as its dialogue or cutscenes. When sensory design and mechanics align with the thematic meaning, players are not just told what something is—they experience what it is. Designers can thus build deeper immersion and meaning by ensuring that in-game items, actions, and environments resonate with the sensorimotor and emotional systems of the player, creating games that speak to players on both cognitive and narrative levels, a signal to Game Feel as discussed in the previous essay.

The act of play is a stimulant of human reasoning, wrapped in systems carefully engineered to evoke learning, mastery, and immersion. As Fridenberg et al. show, the cognitive pillars of memory, problem-solving, imagery, and concepts are not abstract processes—they are the foundation of how players engage with games. These systems directly inform key aspects of game design: onboarding and tutorials rely on working memory limits and chunking; puzzle and progression systems mirror structured problem spaces and subgoals; level and UI design benefit from spatial imagery and cognitive scaffolds; and the semantic design of items and environments draws from perceptual simulation, reinforcing meaning through multisensory feedback. Game design, then, is cognitive design—an architecture of thought and experience, built to not only to entertain but to harmonize with our natural traits of learning, reasoning, and making meaning as human beings.

The Neuroscience Approach — Mind as Brain

Neurosciences analyze the physical, empirical effects of our brain itself, and goes into core concepts—such as attention systems, executive control, reward circuits, and memory encoding. Thus, can be integrated into game design. While neuroscience often focuses on brain anatomy and function, it also provides game designers with foundational insights into how players actually process, react to, and learn from gameplay experiences. These mechanisms are vital for crafting satisfying mechanics, motivating feedback systems, and cognitively-aligned challenges.

Neuroscience breaks attention into automatic and controlled systems. Automatic attention arises from habitual, well-learned stimuli, while controlled attention requires conscious effort and is activated by novelty or difficulty​. Games can use this duality by: Tutorials and onboarding, Use controlled attention early in the game by presenting new mechanics gradually. Players must focus more actively at this stage, Dynamic camera framing and lighting, Exploit bottom-up (automatic) attention by highlighting critical objects, enemies, or puzzles with motion, brightness, or contrast, and Environmental cues - controlled attention is used when the player has to search (e.g., a puzzle room in The Witness), but automatic attention helps when cues like flickering lights guide focus (e.g., Dead Space) .Moreover, attention can be hijacked or divided. Avoid excessive simultaneous UI updates, or time critical decisions poorly, especially in cognitively demanding gameplay phases.

In game design, understanding the brain’s reward circuitry—particularly the dopaminergic system—can guide how we structure feedback and motivation loops. Reward scheduling, for instance, involves varying the timing and magnitude of success to keep the brain engaged. A critical hit in an RPG or an unexpected item drop during gameplay can create emotional spikes that enhance both retention and satisfaction. Progress indicators such as XP bars, level-ups, and combo meters are particularly effective because they offer visible, immediate reinforcement that activates reward pathways. The clarity and frequency of this feedback—through audiovisual effects like chimes, flashes, or celebratory animations—help players feel a sense of growth, even in games that involve repetition or grinding. Beyond mechanics, narrative payoffs play a crucial role in triggering deep emotional reward, such as the moment a player rescues a beloved NPC or completes a character’s redemption arc. These story moments deliver climactic closure that taps into the same neurological reward systems. Conversely, poorly timed or ambiguous feedback can diminish motivation, leaving players uncertain about whether their actions matter. To maintain engagement, it’s essential that players immediately recognize their progress and accomplishments through tightly coupled cause-and-effect feedback.

Effective game design aligns attention, memory, and reward systems into a cohesive experience that resonates with the brain’s natural learning architecture. Neuroscience shows that focused attention enhances memory encoding, while dopaminergic reward signals strengthen learning pathways through reinforcement. In flow-based games like *Hades* or *DOOM Eternal*, designers harness this synergy by locking player attention through tightly controlled enemy behavior, arena layouts, and rapid pacing. These games provide fast, clear feedback—such as hit sparks, sound cues, or combo counters—that immediately reward precision and accuracy, engaging the brain’s reward circuits. At the same time, they promote gradual mastery through repeated patterns that reinforce procedural memory, enabling players to develop skill without conscious effort. Together, these elements construct what can be described as the “neuroarchitecture” of flow—a gameplay structure that sustains engagement, enhances learning, and fosters intrinsic motivation by speaking directly to how the brain processes, remembers, and rewards action.

The Emotional Approach — Mind as Emotion

Fridenberg et al. frame emotion not as a secondary reaction, but as a primary system that shapes perception, memory, decision-making, and learning. Emotions are cognitive signals that highlight what matters—what to notice, remember, or act upon—making them an indispensable design tool in games. Video games themselves are already affective computational systems, designed to evoke emotional responses through structure, interaction, and feedback within software. In game design, emotional modeling can guide the pacing of narrative arcs, the stakes of decision-making systems, the satisfaction of reward loops, and the tension or release embedded in aesthetic moments.

One of the most valuable takeaways from this chapter is the idea that emotions are not separable from cognition but are integral to it. Emotion and cognition are “hot and cold” modes of reasoning that work in concert, influencing everything from how we filter perception to how we make choices under uncertainty​ . For example, the threat-superiority effect suggests that emotionally charged stimuli—like angry faces—are detected faster than neutral ones​ . This has immediate design implications: UI elements signaling danger (low health, enemy alerts, time pressure) should leverage these visual cues to command player attention intuitively. In horror or survival games, these design tricks aren’t just functional—they work because our neural systems are tuned to them.

Memory is also highly sensitive to emotional input. Research has shown that emotional events are remembered more vividly than neutral ones, particularly negative or arousing stimuli​ . In narrative-driven games, designers can strategically use emotional beats (loss, surprise, awe) to increase player retention and remeberance events. The emotional arc of Journey or The Last of Us, for instance, is an exemplar of cognitively sticky. The vividness of these memories shows us how emotion modulates the underlying memory systems, allowing players to have a strong response when recalling games from memory, mapping its respective emotional beats as fond memories, which is great for designing that peak moment in your game, or having a ever-lasting onboarding effect.

Game designers can treat video games themselves as a form of affective computing design. Designers engineer intelligent, reactive systems that enables audiovisual feedback, narrative structure, pacing, and player choice to orchestrate emotion. Thus, emotion becomes the north star to game creation, as it is the hidden language by which systems are felt, not just understood.

Evolutionary Cognition: Why We Think the Way We Do

The evolutionary approach posits that human cognitive architecture evolved to solve problems faced by our ancestors in adaptive environments, such as locating food, avoiding predators, social cooperation, mating, and navigating hierarchies​ . These deep-rooted pressures shaped modules in the brain optimized for pattern recognition, loss aversion, reward seeking, and social reasoning—all of which still influence how players behave in game systems today. Game designers can use this knowledge to create systems that “plug into” these ancient behaviors. For example, resource-gathering loops, territory defense mechanics, or survival simulations (like Don’t Starve or Rust) resonate with our evolutionary instincts to explore, hoard, and secure. Mechanics that trigger risk vs. reward calculations also tap into evolved mechanisms around survival and opportunity.

Fridenberg et al. r discusses how evolved cognitive shortcuts—heuristics—allow humans to make fast decisions under uncertainty, though these shortcuts often result in predictable biases. Far from flaws, these biases are adaptive tools shaped by evolution to help us survive in complex environments. For example, loss aversion makes players more cautious about losing items, progress, or characters than they are excited about gaining new ones, which is why permadeath in XCOM or the tension of losing a rare resource in Don’t Starve can feel so emotionally charged. Status quo bias, where players stick to familiar options even if better ones exist, can be seen when players choose to keep early weapons or abilities—like the starter sword in Zelda—despite unlocking better alternatives, simply because they are accustomed to their behavior. The availability heuristic, which leads people to overestimate vivid or emotionally intense outcomes, influences how players assess threat or failure in games like Darkest Dungeon, where a single brutal encounter may disproportionately affect future choices and risk tolerance. Designers can use these evolved tendencies to shape moment to moment systems and recognize players action and decisions — crafting meaningful choices, perceived risk, and strategic tension that feel intuitive and emotionally resonant. Understanding heuristics helps designers create engaging, instinctively navigable decision spaces, where players feel the weight of their actions without being overwhelmed or misled.

Humans evolved in environments that required constant adaptation through reinforcement and feedback, which is echoed in modern game loops. Games that deliver timely rewards or punishments—through sound cues, visual effects, or scoreboards—mimic the dopaminergic feedback systems of our brains. This evolutionary link helps explain why well-designed feedback systems feel so satisfying, the juiceness and feel of the game. Moreover, evolutionary theory shows that we are tuned to learn incrementally and through pattern recognition, not random abstraction. Games like Tetris or Dark Souls are built around this principle—they teach players new rules through repetition and adaptation, aligning with our natural reinforcement learning architecture.

At its core, game design is the architecture of human experience—an interdisciplinary convergence of psychology, neuroscience, affective science, philosophy, and evolutionary theory. From how we direct attention, process memory, and solve problems, to how we feel emotion, make decisions, and adapt through feedback, games are deeply entangled with the fundamental machinery of the mind and brain. As Cognitive Science: An Introduction to the Study of Mind by Fridenberg et al. reveals, these systems are not isolated but deeply interconnected—creating a design space where mechanics, narrative, feedback, and emotion become levers for human understanding. Whether it’s structuring a flow-inducing combat loop, crafting a memorable story beat, guiding player attention, or aligning systems with ancestral heuristics, game design becomes a cognitive craft—one that speaks fluently to how we think, feel, and learn. Designing with this awareness doesn’t just make better games; it makes games that resonate, that teach, that move, and that stay with players long after they’ve set the controller down. Thus, games should be tapping and aligning our inner selfs.

Exercises

1. [🟢 Easy] Identify a Cognitive Mechanic
Pick a game you've played recently. Identify one mechanic (e.g., sprinting, crafting, dialogue choice) and map it to a cognitive domain: memory, attention, problem-solving, or emotional regulation. What does it challenge or reinforce?

2. [🟢 Easy] Spot Attention Systems
Describe a moment in a game where the environment or UI guided your attention. Was it automatic (e.g., flashing light, sound cue) or controlled (e.g., conscious search)? Why did it work?

3. [🟢 Easy] Match Reward to Feedback
Think of a satisfying moment in a game—level up, puzzle solved, boss defeated. What kind of reward was given (visual, audio, narrative)? How fast was the feedback? Why did it feel good?

4. [🔵 Medium] Diagnose Cognitive Load
Choose a complex system from a game—like an inventory menu, skill tree, or map. Was it overwhelming at first? How might it be redesigned to reduce working memory load (e.g., chunking, progressive tutorials)?

5. [🔵 Medium] Analyze Problem-Solving Flow
Select a puzzle, combat scenario, or strategy challenge. Break it down into initial state → intermediate states → goal state. Which game elements supported or hindered your progress through that cognitive path?

6. [🔵 Medium] Emotional Memory Mapping
Think of a memorable emotional moment from a game (joy, loss, awe). What design elements—visuals, music, pacing—amplified this emotion? Why do you think it stuck with you?

7. [🔴 Hard] Restructure a Tutorial
Pick a game with a frustrating or overwhelming tutorial. Reimagine it using principles of neuroscience and cognition: attention scaffolding, memory load, reward timing. What would you change step-by-step?

8. [🔴 Hard] Synthesize a Flow System
Design a small gameplay loop (e.g., gather → craft → survive) that aligns attention, memory, and reward into a smooth experience. How will you guide attention? How will players learn and remember? What feedback closes the loop?

9. [🔴 Hard] Cognitive Design Critique
Select a cognitively complex game (e.g., *Outer Wilds*, *Dwarf Fortress*, *Dark Souls*). Critically analyze how it uses—or misuses—cognitive science principles across memory, problem-solving, emotion, and flow. Where does it succeed? Where does it break down?