Brain waves clearing up, symbolizing cognitive clarity.

Unmasking Brain Signals: How to Reduce Noise and Improve Mental Clarity

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

"Discover the groundbreaking research revealing how common signal noise impacts brain wave analysis and what you can do to optimize your cognitive function."

In today's fast-paced world, understanding how our brains communicate is more critical than ever. Neuroscientists are continuously seeking to decipher the complex connections that drive our thoughts, emotions, and behaviors. Functional and effective connectivity analyses have become powerful tools in this quest, allowing researchers to examine the intricate relationships between different brain areas.

However, like any sophisticated instrument, brain analysis techniques are not without their challenges. One persistent issue is the presence of 'common signals'—extraneous noise that can interfere with the clarity of brain wave readings. This noise can arise from various sources, such as electrical activity at the reference electrode or volume conduction from other electrical sources. Understanding how to minimize this noise is key to accurate interpretation.

Groundbreaking research is shedding new light on how common signals affect our understanding of brain connectivity and cognitive function. By identifying and mitigating these sources of noise, we can unlock more precise insights into the workings of the brain, paving the way for interventions that enhance mental clarity and cognitive performance.

What are Common Signals and How Do They Cloud Our Thinking?

Brain waves clearing up, symbolizing cognitive clarity.

Imagine trying to listen to your favorite song on the radio, but there's static and interference. Common signals act like that static, obscuring the true neural activity that researchers are trying to measure. In electrophysiology, these signals can arise from seemingly innocuous sources, like a non-silent reference electrode, which adds a common signal across all recorded data.

This interference can have significant consequences. It adversely affects functional and effective connectivity analysis, which are crucial for understanding how different brain regions communicate. In essence, common signals can distort our perception of brain activity, leading to misinterpretations and flawed conclusions.

Electrical Activity at the Reference Electrode: Even a 'non-silent' reference electrode can introduce unwanted electrical activity.
Volume Conduction: Signals from other electrical sources can bleed into the recordings, creating a noisy environment.
Environmental Noise: External sources of electromagnetic interference.

To address this issue, neuroscientists have been working to develop effective methods for reducing the impact of common signals. A recent study published in Frontiers in Systems Neuroscience provides a comprehensive review of how these signals affect power, coherence, and Granger causality—key measures in brain connectivity analysis.

The Path Forward: Cleaner Signals, Clearer Minds

By understanding the nature of common signals and their impact on brain analysis, researchers are paving the way for more accurate and reliable assessments of brain function. The ultimate goal is to develop techniques that can effectively filter out the noise, revealing the true underlying neural activity. As these methods improve, we can anticipate breakthroughs in our understanding of cognitive processes, leading to new and innovative approaches for enhancing mental clarity and cognitive performance.

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: 10.3389/fnsys.2018.00030, Alternate LINK

Title: The Effect Of Common Signals On Power, Coherence And Granger Causality: Theoretical Review, Simulations, And Empirical Analysis Of Fruit Fly Lfps Data

Subject: Cellular and Molecular Neuroscience

Journal: Frontiers in Systems Neuroscience

Publisher: Frontiers Media SA

Authors: Dror Cohen, Naotsugu Tsuchiya

Published: 2018-07-25

Everything You Need To Know

What are 'common signals' in the context of brain wave analysis, and why are they problematic?

In brain wave analysis, 'common signals' refer to extraneous noise that interferes with the clarity of brain wave readings. They are problematic because they can distort our perception of actual brain activity, leading to misinterpretations and flawed conclusions in functional and effective connectivity analysis. Common signals act like static, obscuring the true neural activity that researchers are trying to measure. These signals can arise from sources like a non-silent reference electrode, volume conduction from other electrical sources, or external electromagnetic interference.

How do common signals specifically affect functional and effective connectivity analyses?

Common signals adversely affect functional and effective connectivity analysis by distorting the relationships between different brain regions. These analyses rely on accurately measuring the communication between different brain areas. If common signals introduce noise, it can lead to misinterpretations of how these regions interact, impacting the validity of conclusions about cognitive functions and neural processes. This can confound measures like power, coherence, and Granger causality, which are key in brain connectivity analysis.

What are some of the primary sources of common signal interference in brain analysis?

The primary sources of common signal interference include electrical activity at the reference electrode, which can add a common signal across all recorded data if the electrode is not truly 'silent'. Volume conduction, where signals from other electrical sources bleed into the recordings, also contributes significantly. Additionally, environmental noise from external electromagnetic interference can introduce unwanted signals.

What is the ultimate goal of research focused on understanding and mitigating common signals in brain analysis, and what breakthroughs might this lead to?

The ultimate goal is to develop techniques that can effectively filter out common signals, revealing the true underlying neural activity. As these methods improve, breakthroughs can be anticipated in understanding cognitive processes. This can lead to innovative approaches for enhancing mental clarity and cognitive performance. Improved signal clarity could also provide more accurate assessments of brain function.

How does the reduction of common signals in brain analysis relate to improvements in overall mental clarity and cognitive performance?

Reducing common signals in brain analysis leads to more accurate and reliable assessments of brain function. This, in turn, can pave the way for interventions that enhance mental clarity and cognitive performance. By filtering out noise and revealing the true underlying neural activity, researchers can gain deeper insights into the workings of the brain. This knowledge can be used to develop targeted strategies for improving cognitive processes and addressing conditions that affect mental clarity.