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Electrophysiological … Age? – The Implications of an Observed Age-Induced Decline of Electrophysiological Readability

April 4, 2025

 

Every year, Georgia Tech’s STEMcomm Vertically Integrated Project (VIP), a project group centered around enhancing public understanding and enthusiasm for science through writing, exhibits, and events, partners with organizations like Science ATL and hosts an event at the Atlanta Science Festival, with the 2025 event being the Amazing Race; STEM Edition. With different legs of the race centered around 4 main focus areas in STEM, involving Physics in the Speed of Light, Chemistry in Shocking Conductors, Computer Science in the Cyber Quest, and Neuroscience in the Reflex Relay, groups of participants raced through Georgia Tech’s campus to complete interactive hands-on STEM-related tasks and objectives as quickly as possible.

Focusing in on the Reflex Relay, which involved 2 stations where participants had to successfully perform a ruler drop experiment centered around reaction time and then move into an experiment centered around the electrophysiological activity associated with motor command. At this 2nd station, participants took turns exploring the electrophysiology of the nervous system through the usage of a Backyard Brains Human-Human Interface to “control” each other’s arms. A common neuroscience experiment performed in many intro neuroscience courses and labs, as described by Greg Gage’s Ted Talk, How to Control Someone Else’s Arm with Your Brain, the human-human interface arm control experiment is a fun and interactive way for people to explore neuroscience in a more hands-on fashion through directly participating in the transmittance of information from one person’s arm into another person’s arm using the Human-Human Interface to do so (Backyard Brains, n.d.).

Throughout the race, however, to everyone’s surprise, a major issue arose regarding the Human-Human Interface’s ability to read certain older individuals. This observed age-related decline in electrophysiological readability was especially shocking for many of the neuroscience group members as well as VIP team leads because much of the group in general had prior experience with the kits as well as a neuroscience background and had never experienced or even heard of this issue before. However, this unexpected linkage between electrophysiological readability and age can be described as electrophysical age and is ultimately something that, while not typically even thought of in neuroscience, is a studied topic of interest and is an interesting byproduct of neuronal noise.

Aging in general is typically associated with some form of mental decline and/or detriment on a more cognitive level, and this generally understood age-related decline in cognitive functioning isn’t typically observed until far later in life. However, some niche research related to changes in electrophysiological noise, specifically what is considered 1/f noise, has proven that, similar to many of the neurobiological precursors linked to typical cognitive decline, there are similar electrophysiological precursors associated with age-related cognitive decline. Electrophysiology is the study of electrical properties associated with biological systems, and since the nervous system is bioelectric, electrophysiology is often very heavily intertwined with the discipline. Through data collected by using intracranial electroencephalography (EEG), a technique neuroscientists use to read the electrophysiological activity in the brain, Voytek et al.’s study titled Age-Related Changes in 1/f Neural Electrophysiological Noise done in 2015 ultimately defines characteristics of 1/f neural noise. Neural noise is interesting in that it is a byproduct of the brain’s constant processing of stimuli; however, in being a ‘noisy’ system, the nervous system can sometimes be challenging to record through devices such as EEG. In defining that the frequency of 1/f neural noise can fall rapidly to what can be considered “white noise” due to the reciprocal nature of the function (f), Voytek et al.’s study is really interesting in that it connects and applies mathematical concepts to neurobiological principles. It was also found that even at rest, the 1/f noise mediated many aspects of cortical functioning like memory, which is especially interesting considering that it directly supports the electrophysiologically based neural noise hypothesisc of aging “that the signal-to-noise ratio of the central nervous system degrades during aging, leading to deficits in processing speed”  first proposed by Robert Kail in 1997 (McCormick et al., 2023). Furthermore, neuroelectrophysiological studies have shown that electrophysiological changes that occur due to age happen as a result of decreases in cellular excitability or the rate in wich neurons can communicate with eachother, which in turn constraints intraneuronal communication by limiting the rate at which neurons can commintate with eachother through the alteration of parameters that are integral to neural functioning (Cepeda et al., 1992). Ultimately, these observed electrophysiological changes can contribute to many of the cognitive and behavioral effects that are commonly associated with aging.

Overall, understanding the key neurobiological functions that degrade over time and lead to cognitive decline is a topic that has been continually researched over the past decade, and more often than not, due to complexity, the electrophysiological components associated with these processes are not thoroughly explored within neuroscience. Even though many computational neuroscientists can contextualize these long-standing problems through different models, such as computational models, much of neuroscience in general looks at noise as troublesome, especially regarding the long-standing issues in computational cognitive modeling where noise is typically thought to indicate a deficit within intraneural communication and is therefore filtered out extensively. Ultimately, however, this phenomenon, known as stochastic resonance, may not always be a bad thing as it is a signaling process that naturally occurs with age in non-linear systems (McDonnell & Abbott, 2009). In a dynamic system, such as the nervous system, extra noise can end up playing a somewhat counterintuitive role as systematically, the noise generated can cause deterministic and predictable changes that end up leading to an overall improved quality of neuronal signaling on a microscopic level while making the signals themselves harder to read on a macroscopic level.

Overall, what the Reflex Relay group found, while unexpected, is a great example of the many neural processes that go unrecognized due to the overall complexity of a continuing, evolving, and relatively newer field. Ultimately, this unexpected realization linking age to a decline of electrophysiological readability is just another example of where we may initially perceive something as abnormal or inefficient, but it may, in turn, actually be an unknowing observation of an eloquently nuanced solution not typically considered.

 

 

References

Backyard Brains. (n.d.). Human-human interface. Human-Human Interface. https://backyardbrains.com/products/human-human-interface?srsltid=AfmBOopmTALs9blNPlYVv8nNty1nJUDUmp5rtV5m2wH9T8Tc8lcWJJhC

Cepeda, C., Lee, N., Buchwald, N. A., Radisavljevic, Z., & Levine, M. S. (1992). Age-induced changes in electrophysiological responses of neostriatal neurons recorded in vitro. Neuroscience, 51(2), 411–423. https://doi.org/10.1016/0306-4522(92)90325-v

McCormick, E. M., Cambridge Centre for Ageing and Neuroscience, & Kievit, R. A. (2023). Poorer White Matter Microstructure Predicts Slower and More Variable Reaction Time Performance: Evidence for a Neural Noise Hypothesis in a Large Lifespan Cohort. The Journal of neuroscience: the official journal of the Society for Neuroscience, 43(19), 3557–3566. https://doi.org/10.1523/JNEUROSCI.1042-22.2023

McDonnell, M. D., & Abbott, D. (2009). What is stochastic resonance? Definitions, misconceptions, debates, and its relevance to biology. PLoS computational biology, 5(5), e1000348. https://doi.org/10.1371/journal.pcbi.1000348

TED. (2015, April 28). How to control someone else’s arm with your brain | Greg Gage. YouTube. https://www.youtube.com/watch?v=rSQNi5sAwuc

Voytek, B., Kramer, M. A., Case, J., Lepage, K. Q., Tempesta, Z. R., Knight, R. T., & Gazzaley, A. (2015). Age-Related Changes in 1/f Neural Electrophysiological Noise. The Journal of neuroscience: the official journal of the Society for Neuroscience, 35(38), 13257–13265. https://doi.org/10.1523/JNEUROSCI.2332-14.2015

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.