Interconnected neural networks in a brain.

Decoding Your Brain: How Neural Spikes and Information Theory Can Unlock Your Mind's Secrets

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Avery Sinclair in Mind & Education August 2025 • 4 min read.

"Explore the fascinating intersection of neuroscience and information theory to understand how neural spikes shape our thoughts and actions."


Our brains, often likened to intricate computers, process information in ways that continue to fascinate and challenge scientists. Two fundamental ideas dominate this field: the brain as an information processor and the brain as a computer. Both concepts hinge on how neural signals—specifically, neural spikes—are understood. Traditionally, these spikes have been viewed as binary signals, similar to the 0s and 1s that drive digital computers.

But what if this view is too simplistic? Recent evidence suggests that neural spikes are more complex than mere on-off switches. The precise shape and timing of these spikes may carry critical information, challenging the long-held assumption that they function solely as discrete signals. This revelation opens up new questions about how information theory—a field that quantifies information—can be applied to neural systems.

Corey J. Maley's research delves into this complex intersection, questioning whether our current understanding of information theory adequately captures the nuances of neural communication. By exploring the challenges and pitfalls of applying traditional models to these newly discovered complexities, Maley highlights the need for a more refined approach to understanding the brain's intricate processes.

The Intricacies of Neural Information Processing

Interconnected neural networks in a brain.

Information theory, pioneered by Claude Shannon, provides a framework for quantifying information in various systems. However, it's crucial to distinguish Shannon information from other types, such as semantic (meaning-based) or natural (causal) information. While it's tempting to apply information theory broadly, doing so without careful consideration can lead to trivial or misleading results.

In the context of neural spikes, the traditional view treats each spike as a uniform, binary event. This allows researchers to apply information theory to calculate firing rates and information entropy within neural systems. However, this approach overlooks the potential for individual spikes to vary in shape, amplitude, and timing—variations that emerging research suggests are functionally significant. Consider these points:

  • Spike Shape Matters: Recent studies indicate that the precise waveform of a neural spike can influence downstream neurons, challenging the idea that all spikes are identical.
  • Analog-Digital Facilitation: Voltage levels within a neuron can affect the shape of subsequent action potentials, adding another layer of complexity.
  • Synaptic Plasticity: The waveform of a neural spike can alter synaptic behavior, affecting how future signals are processed.
  • Sub-threshold Dynamics: Activity below the neuron's firing threshold can influence the shape and impact of subsequent spikes.
These findings suggest that neural spikes are not merely binary signals but complex, continuously variable events. This challenges the direct application of classic information theory, which struggles to handle continuous variables effectively. The information entropy of a continuous variable, for instance, is technically infinite, requiring new methods for meaningful analysis.

A New Perspective on the Brain's Code

The emerging view of neural spikes as continuously variable signals complicates our understanding of brain function. However, this complexity also presents an opportunity to refine our models and develop more nuanced approaches to studying neural communication. As researchers delve deeper into the intricacies of spike waveforms and their functional significance, we can expect a more complete and accurate picture of how the brain processes information, paving the way for new insights into cognition, behavior, and neurological disorders. The journey toward understanding the brain's code has only just begun, and the closer we look, the more we realize how much there is to discover.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1007/s13164-018-0412-5, Alternate LINK

Title: Continuous Neural Spikes And Information Theory

Subject: Philosophy

Journal: Review of Philosophy and Psychology

Publisher: Springer Science and Business Media LLC

Authors: Corey J. Maley

Published: 2018-07-18

Everything You Need To Know

1

How has the understanding of neural spikes evolved, and what implications does this have for our comprehension of brain function?

Neural spikes are traditionally viewed as binary signals, like 0s and 1s in a computer, but recent research indicates they may be more complex. The shape and timing of neural spikes might carry crucial information, which challenges the idea they are just discrete on-off signals. This complexity suggests our current understanding of how the brain processes information might be too simplistic.

2

What is Shannon information, and why is it important to distinguish it from other types of information when studying the brain?

Shannon information, developed by Claude Shannon, provides a way to measure information in systems. However, it differs from semantic information (meaning-based) and natural information (causal). Applying information theory without considering these differences can lead to trivial or misleading conclusions when studying neural spikes.

3

What specific characteristics of neural spikes suggest they are more complex than simple binary signals?

Recent studies show that the waveform of a neural spike can influence downstream neurons. Voltage levels within a neuron affect the shape of action potentials, and neural spike waveforms can alter synaptic behavior, affecting future signal processing. Furthermore, activity below the neuron's firing threshold can influence the shape and impact of subsequent spikes. These factors indicate that neural spikes are not simple binary signals but complex, continuously variable events.

4

Why does the continuously variable nature of neural spikes complicate our existing models of brain function?

Viewing neural spikes as continuously variable signals complicates our understanding of brain function because classic information theory struggles with continuous variables. For instance, the information entropy of a continuous variable is technically infinite, requiring new methods for analysis. This complexity necessitates refining our models to develop more nuanced approaches to studying neural communication.

5

How might a deeper understanding of neural spikes and information processing impact our approach to understanding and treating neurological disorders?

Understanding neural spikes could revolutionize our approach to neurological disorders by providing a more complete and accurate picture of how the brain processes information. Delving deeper into the intricacies of neural spike waveforms and their functional significance will pave the way for new insights into cognition and behavior. This understanding could lead to better diagnostic tools and treatments for various neurological conditions.

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