Beyond Efficiency: The Neuroscience Case for Keeping Handwriting in Digital Age

Post Title Image (Illustration: Preparing to unbox the Remarkable Paper Pro. Image source: Ernest.)

✳️ tl;dr

  • In Ernest PKM 1, I mentioned that I still maintain paper-based notes, along with using digital handwritten notes.
  • Last year, I acquired a reMarkable Paper Pro, which is also handwriting-based.
  • There’s always this feeling that when surrounded by heaps of mixed information, whenever I want to quiet down and clarify the complex cognition at hand,
  • I usually grab a handwriting tool, put on noise-canceling headphones, sit quietly for a few minutes, and then start writing to output, categorize, and compare,
  • I can always sort things out. Even if no clear structure emerges, at least some branches grow.
  • But feelings are just feelings. I always want to find a causal explanation (ah, is this a bad habit? Anyway, it’s a habitual action - the root cause habits formed at TSMC are too deeply ingrained).

  • Searching and searching, I found that Dr. Audrey van der Meer 2 has long been focused on this field,
  • Below are her research results published in 2024-01. 34
  • The study recorded brain electrical activity in 36 university students as they were handwriting with a digital pen and typing on a keyboard.
  • Brain connectivity patterns during handwriting were far more complex and elaborate than during typing.
  • Handwriting produced widespread theta/alpha frequency connectivity patterns, which are crucial for memory formation and learning.

  • Neural processes are not localized and static; the brain organizes in a highly dynamic functional manner.
  • High-density EEG studies of cortical oscillations are considered an indispensable part of contemporary systems neuroscience.
  • Complex interactions at specific frequencies are thought to reflect different cognitive processes.
  • The temporal organization of neuronal firing is crucial for forming long-term memories in the hippocampus.
  • Event-related synchronization (ERS) and event-related desynchronization (ERD) can be observed in EEG recordings.
  • Handwriting involves more complex hand movements and may be more advantageous for learning than typing.

  • 40 university students in their early twenties participated in the study, with data from 36 students being of sufficient quality for analysis.
  • To avoid crossover effects between the two brain hemispheres, only right-handed participants were included in the study.
  • E-prime 2.0 software was used to individually display 15 different Pictionary words on a Microsoft Surface Studio.
  • Participants used a digital pen to write in cursive on a touchscreen or used a keyboard to type the presented words.
  • The experiment comprised 30 trials, with each word appearing in two different conditions in random order.
  • Each trial gave participants 25 seconds to repeatedly handwrite or type words, but EEG was only recorded for the first 5 seconds.
  • To prevent artifacts caused by eye movements, typed words were not displayed on the screen during typing.
  • A Geodesic Sensor Net with 256 evenly distributed electrodes was used to record EEG activity at 500 Hz sampling rate.
  • BESA software was used to analyze EEG data, employing spherical spline interpolation to handle movement artifacts.

  • The mean number of accepted trials was 14.1 (SD = 1.1) for handwriting and 13.3 (SD = 1.3) for typing.
  • Coherence measures were applied, producing symmetric connectivity matrices showing pairwise clusters.
  • Significant differences in connectivity existed between handwriting and typing, mainly in the theta (3.5-7.5 Hz) and alpha (8-12.5 Hz) frequency bands.
  • Widespread theta/alpha connectivity coherence patterns appeared in parietal and central brain regions during handwriting.
  • The connectivity matrix showed extensive connections between parietal right, parietal midline, parietal left, and central right and central left regions.
  • Parietal and central brain regions are associated with attentional mechanisms, cognitive processes in visual perception, and language processing, with strong links to sensorimotor cortex.
  • 32 significant cluster differences were found in the handwriting condition, representing 16 significant connections.
  • Network measures showed that hubs during handwriting had higher degrees of network involvement (≥4 connections).
  • Handwriting showed more widespread theta/alpha connectivity patterns compared to typing, indicating stronger connectivity.

  • Enhanced brain connectivity during handwriting appeared only when writing by hand and not when pressing keys, proving that handwriting promotes learning.
  • Theta/alpha connectivity patterns may indicate that handwriting and typing involve different neural networks.
  • Alpha band connectivity is related to long-term memory performance, while theta connectivity is related to working memory and the ability to comprehend new information.
  • Lower frequencies are particularly suited for facilitating long-distance communication in the brain, and theta oscillations may gate the occurrence of gamma oscillations.
  • Theta synchrony supports information integration during memory formation, and low-frequency synchronization is crucial for cognition.

  • Handwriting requires fine motor control over the fingers, forcing students to pay attention to what they are doing. 👉 Cognition
  • Typing requires mechanical repetitive movements, trading awareness for speed. 👉 Efficiency

  • The spatiotemporal patterns of visual, motor commands, and proprioceptive feedback produced by handwriting movements are absent in typing.
  • Replacing handwriting with typing in educational environments may have negative impacts on the learning process.

✳️ Knowledge Graph

(More about Knowledge Graph…)

%%{init: {'theme':'default'}}%%
graph LR
    %% Concept Classes in Orange
    Handwriting[Handwriting]:::concept
    Typewriting[Typewriting]:::concept
    BrainConnectivity[Brain Connectivity]:::concept
    NeuralNetworks[Neural Networks]:::concept
    MemoryFormation[Memory Formation]:::concept
    Learning[Learning]:::concept
    SensorimotorIntegration[Sensorimotor Integration]:::concept
    CognitiveProcesses[Cognitive Processes]:::concept
    MotorControl[Motor Control]:::concept
    
    %% Instances in Blue
    HighDensityEEG[High-density EEG]:::instance
    ThetaOscillations[Theta Oscillations 3.5-7.5Hz]:::instance
    AlphaOscillations[Alpha Oscillations 8-12.5Hz]:::instance
    ParietalRegions[Parietal Regions]:::instance
    CentralRegions[Central Regions]:::instance
    NetworkHubs[Network Hubs]:::instance
    NetworkNodes[Network Nodes]:::instance
    DigitalPen[Digital Pen]:::instance
    Keyboard[Keyboard]:::instance
    WorkingMemory[Working Memory]:::instance
    LongTermMemory[Long-term Memory]:::instance
    Coherence[Coherence Measure]:::instance
    VisualMotorCoordination[Visual-Motor Coordination]:::instance
    ProprioceptiveFeedback[Proprioceptive Feedback]:::instance
    
    %% Handwriting relationships
    Handwriting -->|requires| MotorControl
    Handwriting -->|activates| SensorimotorIntegration
    Handwriting -->|enhances| BrainConnectivity
    Handwriting -->|uses| DigitalPen
    Handwriting -->|produces| VisualMotorCoordination
    
    %% Typewriting relationships
    Typewriting -->|uses| Keyboard
    Typewriting -->|involves| MotorControl
    Typewriting -->|produces limited| BrainConnectivity
    
    %% Brain Connectivity relationships
    BrainConnectivity -->|measured by| HighDensityEEG
    BrainConnectivity -->|assessed via| Coherence
    BrainConnectivity -->|forms| NeuralNetworks
    BrainConnectivity -->|facilitates| MemoryFormation
    BrainConnectivity -->|involves| ThetaOscillations
    BrainConnectivity -->|involves| AlphaOscillations
    
    %% Neural Networks relationships
    NeuralNetworks -->|contain| NetworkHubs
    NeuralNetworks -->|contain| NetworkNodes
    NeuralNetworks -->|located in| ParietalRegions
    NeuralNetworks -->|located in| CentralRegions
    
    %% EEG measurements
    HighDensityEEG -->|detects| ThetaOscillations
    HighDensityEEG -->|detects| AlphaOscillations
    HighDensityEEG -->|records from| ParietalRegions
    HighDensityEEG -->|records from| CentralRegions
    
    %% Oscillations and Memory
    ThetaOscillations -->|supports| WorkingMemory
    AlphaOscillations -->|correlates with| LongTermMemory
    
    %% Memory and Learning
    MemoryFormation -->|enables| Learning
    WorkingMemory -->|contributes to| MemoryFormation
    LongTermMemory -->|results from| MemoryFormation
    
    %% Sensorimotor Integration
    SensorimotorIntegration -->|requires| VisualMotorCoordination
    SensorimotorIntegration -->|depends on| ProprioceptiveFeedback
    SensorimotorIntegration -->|engages| CognitiveProcesses
    
    %% Cognitive Processes
    CognitiveProcesses -->|support| Learning
    CognitiveProcesses -->|reflected in| ThetaOscillations
    CognitiveProcesses -->|reflected in| AlphaOscillations
    
    %% Motor Control
    MotorControl -->|involves| VisualMotorCoordination
    MotorControl -->|generates| ProprioceptiveFeedback
    
    %% Styling
    classDef concept fill:#FF8000,stroke:#CC6600,stroke-width:2px,color:#000
    classDef instance fill:#0080FF,stroke:#0060CC,stroke-width:2px,color:#FFF

✳️ Further Reading