Abstract
This study examines the relative influence of visual and auditory sensory modalities on working memory (WM) within an evolutionary and cognitive neuroscience framework. Drawing from evolutionary theory and neuroanatomical evidence, it was hypothesized that the visual system would exert a stronger effect on WM due to its earlier phylogenetic development and greater cortical representation. A within-subjects design was employed using archival data from the Online Psychology Lab (N = 134), comparing participant performance on visual and auditory digit span tasks. A paired samples t-test revealed a statistically significant advantage in auditory WM performance, t(133) = 2.017, p = .046, d = 0.174, though with a small effect size. These results contradict earlier findings favoring visual dominance and may indicate a cognitive adaptation linked to increased auditory stimulus exposure in contemporary environments. Methodological limitations include age and gender sampling bias. Findings underscore the need for multimodal, cross-generational research to assess emerging trends in WM processing and their evolutionary implications.
Keywords: working memory, visual memory, auditory memory, evolutionary psychology, digit span, cognitive neuroscience, sensory modalities
Humans have evolved unique abilities both physically and cognitively since they branched from chimpanzees approximately 6 million years ago. Some of these unique abilities include walking and running upright (bipedalism), crafting tools, cooking food, as well as communicating and cooperating with one another, among other things. These features coincided with the development of larger brains, especially that of the neocortex wherein complex thinking, abstract reasoning, and memory formation transpire (Chin et al., 2023). The latter of these features of the neocortex has been of intrigue among researchers over the past century or more.
Furthermore, some of the earliest work on memory being conducted by Hermann Ebbinghaus in the late 19th century. His experiments consisted of an individual (including himself) learning nonsense syllable and then reciting these syllables from memory. The results revealed that 7 syllables were the ideal ratio for an exact recitation from memory, and the higher the number of syllables the lower the accuracy of recitation (Roediger & Yamashiro, 2019). These results were later proved to be related to short-term memory or working memory (Bajaffer et al., 2021). Several decades later, studies conducted by George A. Miller published in 1956 provided similar results with short-term/working memory with a 7 plus or minus 2 regarding bits of information result for an average person’s memory threshold.
Since the time of Ebbinghaus and Miller, hundreds of experiments have been conducted and published pertaining to memory and with these studies an improved understanding of both the functionality and composition of memory. For instance, according to Amal Bajaffer and colleagues (2021), researchers have now divided the functionality of memory into three distinct linear phases that include encoding, storage, and retrieval of information. Furthermore, memory has been categorized into three distinct categories: sensory memory, working memory, and long-term memory. Sensory memory (SM) is short in duration and possesses a large storage capacity, and it involves utilizing the bodily senses (touch, taste, smell, sight, and hearing) in the detection of information that is directly stored in the nervous system. Working memory (WM) is directly linked to short-term memory wherein the information acquired is held for a short period of time, approximately 30 secs, and it has a storage capacity of approximately 4 chunks of information. Finally, long-term memory involves information that is stored for exceptional amounts of time, including months and even years (Bajaffer et al., 2021).
According to Peter Carruthers in his book “In Light of Evolution: The Human Mental Machinery (2014),” WM in particular has been perceived as a fundamental aspect of human survival and flourishing throughout the evolutionary past up to today. This specific feature of memory is involved in multiple processes that are essential to life, including learning, speech, comprehension, and future planning abilities. Moreover, it has been postulated through research that WM is a feature of executive functioning that is distributed throughout the frontal lobes of the brain. Here, WM is thought to collaborate with sensory cortical regions of the brain that interact through attentional processes. It is further speculated that it is through the executive control of attention that sensory information is allowed access into WM (Carruthers, 2014).
However, the most significant and efficient means by which these sensory information interactions have on memory have been of interest to researchers since the induction of memory studies. As mentioned previously by Amal Bajaffer and colleagues (2021), the sensory input in the environment is predicated upon the interaction with the five senses, including smell, sight, hearing, taste, and touch. The two predominantly studied senses pertaining to memory that have the most significant impact include auditory and visual (Linder et al., 2009). Which sensory system impacts memory the most has been of debate, and from an evolutionary perspective, this begs the question, did humans evolve with an acuity for visual memory or auditory memory? The next section will explore the evidence pertaining to visual memory and auditory memory.
Evidence
The evolutionary components of visual and auditory systems is a fine place to begin in the analysis of their impact on WM. First, according to Dan-Eric Nilsson (2022), the visual system is much more primitive in its origins as evidenced in fossils of ancient fish dating back approximately 550 million years ago during the Cambrian explosion. For ancient species, this revolutionary feature of evolution allowed for a novel interaction with reality with newfound abilities such as object recognition and discrimination, motion detection, and enhanced navigational skills (Nilsson, 2022). Next, Marcela Lipovsek and colleagues (2023) have revealed that the evolutionary process of the auditory system occurred at a much earlier date at approximately 350 million years ago during the Carboniferous period, which was a period of the transference from water to land. This evolutionary process was gradual with a low-frequency sound acquisition to high-frequency sound sensitivity (Lipovsek et al., 2023).
As humans evolved from chimpanzees 6 million years ago, both their hearing and vision continued to improve. This feat was accomplished through the evolving process of the brain wherein not only did features pertaining to the neocortex increase and improve, but areas pertaining to vision and hearing increased in size and improved in efficiency as well (Kaas, 2013). However, vision appears to be the most ancient and well developed among the senses which could be indicative of a more influential role in memory compared to hearing.
To help further shed light on this issue, navigational and identification skills of humans both past and present must be analyzed. First, during human’s evolutionary past, navigational skills were of essential value for survival, especially as they began to emerge out of Africa over 100,000 years ago (Stewart & Stringer, 2012). A recent review by Pablo Fernandez-Velasco and Hugo J. Spiers (2024) analyzing the navigational skills of traditional cultures discovered that their navigational skills were predicated upon the identification of patterns in nature that aided in learning and the memorization of terrains. This feat allows them to better navigate their terrain during times of hunting and gathering, and thus mimics conditions of which human ancestors would have contended with (Fernandez-Velasco & Spiers, 2024). Next, according to Maurice Ptito and colleagues (2021), this navigational ability provided by the visual system also provided humans with the necessary ability to better adapt to their environment which enabled them to also identify and remember foods worth foraging and prey valued for hunting. A keen eye for detail and patterns was necessary for the survival and success of the homo species, which was thus translated into the memory of the individual and their descendants (Ptito et al., 2021).
Following this evolutionary trend into the modern work of neuroscience is the recent work conducted by Martin Seeber and colleagues (2025) wherein they analyzed the neuroanatomical effects of navigational skills in action. What they discovered was that both real-world navigation and virtual navigation relied on and influenced memory formation in significant ways. Their study highlighted the essential component of the visual system and memory formation in humans within the confines of navigating one’s current landscape, which was a necessity in the insurance of the survival of evolving humans in the past (Seeber et al., 2025). Furthermore, research conducted by Fabian Hutmacher in 2019 noted the dominant feature of the human visual system wherein it constitutes a large portion of the neocortex, substantially more so than any other sense. This increased area space of the visual system within the brain also indicates a larger amount of energy being supplied to this sensory component of the human body compared to other senses, as well as evidence for a substantial portion of selection pressure placed on vision compared to other senses within the confines of evolution (Hutmacher, 2019).
Finally, a recent international review by Tian-Ya Hou and Wen-Peng Cai in 2022 revealed how emotions impact WM for both better and worse depending on which emotions are elicited. Furthermore, vision and emotions appear to be intricately connected to each other which results in the formation of schematic perceptual frameworks that help one navigate and attend to the world around them (Hou & Cai, 2022). This connection between vision and emotions was researched by Philip A. Kragel and colleagues in 2019, and they discovered how emotionally embedded images are processed through the visual cortex where these images are encoded and decoded within multiple distinct emotional-categorical models that are embedded within memory. These models help with the derivation of meaning, and it has a direct effect in decision making processes and attention (Kragel et al., 2019). These pieces of evidence further help reveal the importance of vision’s impact on working memory; however, whether vision impacts WM more than hearing will be examined next.
Current Working Memory Research
The current literature is abundant on visual and auditory memory; however, an examination of a few bits of relevant research will be achieved here. First, a study examining the differences between visual and auditory working memory conducted by Katie Lindner and colleagues in 2009 discovered that visual memory was superior to auditory memory. In this study, researchers had 49 college student participants divided up into four distinct groups with two of the groups being designated auditory and the other two being visual. These groups were further divided into immediate post-test groups and delayed post-test groups. The results from the study found that the visual groups outperformed the auditory groups in both immediate and delayed post-testing and thus concluded that visual processing effects were more impactful on both working memory and long-term memory (Lindner et al., 2009). Another study from 2009 conducted by Michael A. Cohen and colleagues that focused on the impacts of visual and auditory effects on WM found similar results as Lindner’s team wherein they concluded that auditory processes were inferior to visual processes in terms of WM.
However, a more recent study by Michele E. Gloede and colleagues conducted in 2017 found that although visual processes provided a greater influence on working memory, the effects were of longer duration when it came to auditory processes. Their study consisted of 17 participants that were tested four separate times along with auditory training. This training did provide a benefit with an increase in WM capacity in the confines of auditory testing, although the authors mentioned that the differences between visual and auditory effects on working memory do not appear to be related to one’s experience in those domains. Therefore, this could be evidence for the evolutionary case for visual and auditory differentiation on memory. Lastly, they concluded that although visual memory had a larger capacity, auditory memory was sustained longer in duration (Gloede et al., 2017). Another study by Michele E. Gloede, with the assistance of Melissa K. Gregg conducted in 2019, found similar results to Gloede’s 2017 study, wherein same-day memory tasks with auditory and visual processes revealed that although visual memory was superior in the context of the short-term, auditory and visual memory were similar 2-7 days following the tasks (Gloede & Gregg, 2019).
More recent studies found no difference between visual and auditory systems effects on working memory. The first is a study by Dhana Lace Acedilla and colleagues performed in 2022 on 2nd year university students. This study consisted of two groups of 15 participants with one group assigned to visual memory and the other to auditory memory. Both groups were provided with 20 words to memorize in the manner of the group’s articulation orientation and then were tested on the memorization of these words. The results were that both groups performed similarly and thus it was concluded that visual memory and auditory memory were similar in terms of WM (Acedilla et al., 2022). Similar findings were produced by Sanjana Singh S. & Asha Yathiraj in 2024 wherein they assessed visual and auditory memory in young children ages 8-12 years of age. 18 children were tested on their auditory and visual memory performance both on immediate and delayed memory using the Children’s Memory Scale (CMS). The results indicated no significant difference between visual memory and auditory memory on both immediate and delayed testing (Singh S. & Yathiraj, 2024).
These various conflicting results indicate a faulty approach either in older studies, the newer ones, or both. It is also plausible that these results could indicate a possible recent evolutionary phenomenon wherein humans are shifting their attentional abilities as a result of technological advancements that promote a differentiation in lifestyle compared to their ancient counterparts. Examining the various approaches and similarities of the investigated studies could help resolve some of the confusion.
Approaches of Current Research
To address these issues found within the research literature, an examination of similarities and differences in approaches must be considered. These similarities and differences are most evident in the sample sizes, age ranges, and methodologies. In all studies, the sample sizes were relatively small with the upper limit being evidenced only in the earlier study by Lindner et al. in 2009 wherein 49 participants were used while all other studies used sample sizes averaging in the teens. Furthermore, the age ranges used were college students and younger with no consideration for older populations. This emphasis on emerging adulthood and adolescence neglects essential data from an age range that constitutes the majority of the general population. Lastly, the methodological approach was similar in all studies wherein simple visual and auditory methods of memorization and testing were administered. All of these factors are potential limitations that could be affecting the final results and obstructing a comprehensive understanding of visual and auditory memory, and that of WM.
Limitations
The pre-addressment of limitations has already been examined in the previous section; however, an in-depth analysis of these limitations will be accomplished here. First, the sample sizes for all the examined studies in effect are quite small for a proper representation of the general population, and thus a larger sample size is necessary. Next, the age range by which the previous studies utilized was much too narrow of a scope to be able to properly generalize. Moreover, these lower age groups, although they offer their own valuable insights, is a time wherein the brain is not fully developed and therefore does not provide a comprehensive analysis of WM in a fully developed stage. This begs the question of whether what has been witnessed in the inconclusive results is but a gap within the aging brain, or if the results are accurate, if this inconclusion is but a current evolutionary phenomenon transpiring between generations. Finally, the methodological approach needs to be broader and increased in complexity. The narrowed testing provided by previous studies is only unidimensional in essence, and therefore a broader and more complex test approach could help reveal the complex and intricate processes of the brain and memory.
Theory and Hypothesis
According to evolutionary theory, humans have adapted to their environment through interactive sensory engagements that have wired the connectome of the brain in a way that represents this interactive sensory experience. Moreover, recent research has revealed the mapping of these sensory experiences throughout the brain with vision being the most ancient and widely distributed system followed by the auditory complex (Hutmacher, 2019; Lipovsek et al., 2023; Nilsson, 2022). These experiences also necessitated memory formation to help humans in their adaptive process which required the interaction between sensory input and emotional arousal (Hou & Cai, 2022; Kragel et al., 2019). Regarding the evolving nature of sensory input with vision as the predominant sensory system along with its proximal link with memory formation via emotional arousal, it is hypothesized that the visual system is the predominant sensory system by which WM is evoked. This is further supported through the previously examined research (Cohen et al., 2009; Gloede et al., 2017; Gloede & Gregg, 2019; Lindner et al., 2009); however, some of the most recent research has contended this hypothesis (Acedilla et al., 2022; Singh & Yathiraj, 2024). These contradictory research findings elicit a need for further investigation to help disclose whether the visual system or auditory system is the predominant underlying process by which WM is evoked.
Variables
The independent variable will be the appearance of a given stimulus according to its sensory category (visual/auditory). The dependent variable will be the length of the digit sequence that the research participant can recall (working memory).
Method
I used archival data from the Online Psychology Lab (OPL). The data used was derived from various universities spread throughout the United States and beyond, including Alabama A&M University, Capella University, Indiana University, Miami Regional University, Hong Kong Polytechnic University, University of Colorado Boulder, Western Connecticut State University, and Tokyo Daigaku – Komaba Campus.
The use of both the numerical digit span test and auditory listening digit span test was utilized in this study to help reveal their relationship with WM. I utilized a within-subjects design wherein participants in each group participated in both the auditory and visual numerical test via memorization in a pre-test and post-test format.
The numerical stimulus used were numbers ranging from 0-9 that were presented in random order either in an auditory or visual form depending on the context of the test one was participating in. The task increased in complexity as a participant graduated from each level, and this complexity was increased in the form of an added digit to the sequence of digits to be memorized and recalled. This process continued in its increased frequency until the participant fails, at which time the participant either moved on to the subsequent format of presentation or the experiment was ended.
Participants
The participants I have utilized in this study are derived from several universities that are spread out not only throughout the United States, but throughout the world as well with nationalities consisting of Chinese and Japanese. Total number of participants is 134 with 97 (72.39%) females, 34 (25.37%) males, 2 (1.49%) identifying as other gender, and 1 (0.75%) as a non-conforming. The age range is quite diverse with the youngest participant at the age of 16, and the oldest at 56 years of age with the mean age of 25.321 and standard deviation of 8.243.
Measures
The use of both the numerical digit span test and auditory listening digit span test will be utilized in this study to help reveal their relationship with WM. Throughout the past century, these tests and their relationship to WM have been utilized in research in efforts to better understand the various aspects of cognition, including IQ tests, Aphasia, mathematics performance, among others (Allen et al., 2020; Egeland et al., 2025; Murray et al., 2018; Power, 2017). However, although the use of such tests has been demonstrated through empirical research, this alone does not provide enough evidence for their reliability and validity. Therefore, according to Kexin Liu and Remi Murao (2025), both the numerical and auditory tests for WM have been found to have high internal and external reliability. For instance, both tests revealed strong internal reliability and a moderate to strong test-retest correlation (.70 for numerical; .90 for auditory). Furthermore, the correlation between WM and these tests is substantial and thus helps verify their validity. Both tests revealed strong correlations in the domains of internal and construct validity; however, the numerical test disclosed a non-significant correlation in the domain of context.
Procedure
The one-group pre-test post-test design will be used for this study. This design method will compare scores of participants between pre-test and post-test with no control group assigned (Salkind, 2017). I will have one group wherein each participant will participate in both the auditory and visual memory pre-test and post-test.
Results
A paired samples t-test was performed and found a statistically significant difference between the auditory and visual memory test, t(133)=2.017, p=0.046, d=0.174. Effect size for this study was d=0.174, which is a relatively small effect size. This indicates that although there was a statistically significant difference between the two tests, albeit this difference was not large. However, in comparison to previous studies, these findings point to something significant that should be further explored.
Paired Samples T-Test
| Paired Samples T-Test | |||||||||||||||
| Measure 1 | Measure 2 | t | df | p | Cohen’s d | SE Cohen’s d | |||||||||
| AUD | – | VIS | 2.017 | 133 | 0.046 | 0.174 | 0.103 | ||||||||
| Note. Student’s t-test. | |||||||||||||||
Discussion
The findings indicated a statistically significant difference between the tests administered with a contradictory outcome compared to my initial hypothesis of the predominance of the visual system over the auditory system in its impact on working memory. The significant difference was that participants performed better during auditory memory tests compared to visual memory tests. These results contradict my initial hypothesis that humans evolved keener visual working memory systems compared to auditory working memory systems. Although past evidence did support this hypothesis, more recent studies found contradictory evidence akin to what I have found. The visual system’s predominant effect on working memory was predicted due to the longevity of its evolutionary history in comparison to the auditory system (Hutmacher, 2019; Lipovsek et al., 2023; Nilsson, 2022). However, the results of my study may reflect something else more profound, evolutionary speaking, that may support one of the two hypotheses I suggested that were proposed in the introductory section of this paper. The first hypothesis had a simpler explanation in that the methods and sample sizes used in older studies were inadequate in providing sufficient insight into the complexities of such systems. The second hypothesis was that this dilemma is nested in the grander scheme of human evolution and the impacts of technology and modernization.
The first hypothesis appears to be the least likely of the two as earlier studies sometimes had larger sample sizes than later experiments. Moreover, the method utilized in older studies is akin to the one that I used in this study, and yet the results are drastically different. Therefore, the second hypothesis appears to be the more plausible of the two: however, there are other explanatory factors that could be considered. The rapid increase in technology alongside the other factors that contribute to the overarching dynamics of modernization could in fact be causing an evolutionary shift in how humans are utilizing these sensory systems. For example, the increased use of headphones among younger generations along with handheld devices could be emphasizing auditory systems over visual systems and their impact on memory formation and recall (Alshaikh et al., 2025). However, this is something that future studies should consider.
One key difference between the more recent studies and my study is that the recent studies found no difference between the two sensory systems effect on working memory while mine found a difference that emphasized auditory over visual (Acedilla et al., 2022; Singh & Yathiraj, 2024). When compared with earlier studies wherein researchers discovered visual predominance over auditory (Cohen et al., 2009; Gloede et al., 2017; Gloede & Gregg, 2019; Lindner et al., 2009), mine upends these results with an emphasis on the more recent rather than former. This upending result, again, may reflect an evolutionary phenomenon.
However, another consideration outside of the scope of my two alternative hypotheses is that of the sample population. Although the generalizability of my study is supported through the use of a diverse sample within the confines of ethnicity, age range, gender and cultural background, both the age range and gender limitations must be considered. For instance, the age range, although encompassing a broad range, the predominant age range is 18-24 years of age which limits its generalizability to the general population. Albeit this demographic element does support the second alternative hypothesis I proposed. Furthermore, gender is another consideration as although it does include a diverse range, the predominant gender is female and thus the results may reflect a gender specific sensory modality preference in memory formation, perhaps something that may even be related to evolutionary theory. This gender influence on sensory modality memory is something that future studies should investigate further.
Summary and Conclusion
Evolutionary theory has revealed the antiquity of the visual system compared to the auditory system wherein the visual system predates the evolution of the auditory system by several million years (Hutmacher, 2019; Lipovsek et al., 2023; Nilsson, 2022). Therefore, it seems plausible that the visual system would have a greater impact on working memory in comparison to the auditory system. Earlier studies on sensory modalities and their effect on working memory appeared to support such a hypothesis (Cohen et al., 2009; Gloede et al., 2017; Gloede & Gregg, 2019; Lindner et al., 2009); however, recent studies began to reveal no difference between the effects of these sensory systems and their impact on working memory (Acedilla et al., 2022; Singh & Yathiraj, 2024). This study sought out to test and confirm the antiquated sensory modality and working memory evolutionary hypothesis, albeit the results did not support the hypothesis. Moreover, not only did the results of this study not support the hypothesis, but instead it produced results that contradicted it entirely with the results indicating a predominance of the auditory system over the visual system in their impact on working memory. These results provide future prospective research with information that could be utilized to form new hypothesis to test such as I have suggested previously that may help reveal something more profound, a phenomenon that may be unfolding within the very fabric of the human evolutionary pathway.
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Michael Thacker 