Binaural beats utilize a phenomenon that occurs within the cortex when two different frequencies are presented separately to each ear. This procedure produces a third phantom binaural beat, whose frequency is equal to the difference of the two presented tones and which can be manipulated for non-invasive brain stimulation. The effects of binaural beats on working memory, the system in control of temporary retention and online organization of thoughts for successful goal directed behavior, have not been well studied. Furthermore, no studies have evaluated the effects of binaural beats on brain connectivity during working memory tasks. In this study, we determined the effects of different acoustic stimulation conditions on participant response accuracy and cortical network topology, as measured by EEG recordings, during a visuospatial working memory task. Three acoustic stimulation control conditions and three binaural beat stimulation conditions were used: None, Pure Tone, Classical Music, 5Hz binaural beats, 10Hz binaural beats, and 15Hz binaural beats. We found that listening to 15Hz binaural beats during a visuospatial working memory task not only increased the response accuracy, but also modified the strengths of the cortical networks during the task. The three auditory control conditions and the 5Hz and 10Hz binaural beats all decreased accuracy. Based on graphical network analyses, the cortical activity during 15Hz binaural beats produced networks characteristic of high information transfer with consistent connection strengths throughout the visuospatial working memory task.

Funding: The research leading to these results has received funding from the General & Age Related Disabilities Engineering (GARDE) program through the National Science Foundation (Award Numbers: 1055315 and 1604279). NSF had no role in the design of the study, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2016 Beauchene et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Introduction

Findings from the cognitive neuroimaging literature show that the integration of regional neuronal activity, in the form of coordinated network processing, is required for complex cognition (e.g. memory tasks involve prefrontal, temporal, and sensory processes). In memory tasks, for example, these interactions across regions are thought to be reflected in the coupling across multiple EEG oscillatory bands, particularly at theta (4Hz-8Hz) and gamma (25Hz-40Hz) frequencies [1–4]. Networks describing the interconnections between these cortical regions exhibit a high degree of randomness and modularity, but relatively low heterogeneity. The network properties, which are conserved over all scales, include small world degree distributions, short path lengths, modularity, hierarchy, hub nodes, and robustness [5]. While the native networks associated with memory have been explored, their response to noninvasive stimulation remains to be fully characterized. The study presented here examines the network properties of brain regions involved in working memory with the goal of understanding how environmental stimuli, in this case acoustic stimulation with specific oscillatory synchrony, can modulate cognitive processing.

Working memory is the system in control of online processing and organization of information for successful reasoning, comprehension, and goal directed behavior [6, 7]. Individuals exhibit a capacity limit on the number of items that can be simultaneously retained in working memory. Neuroanatomically, the network governing working memory is distributed over a large part of the brain. In particular, working memory tasks involving visuospatial information activate areas of the prefrontal cortex (PFC) and are often right lateralized [8, 9]. In addition, throughout working memory maintenance, the prefrontal and parietal neuronal ensembles are activated simultaneously [10–12]. Increased difficulty on a working memory task is associated with increased connectivity between prefrontal and parietal areas [13].

Cortical activity can be noninvasively recorded from the scalp using EEG. Since EEG is noisy, non-linear, and non-stationary, phase synchronization is well suited for cortical network determination. Phase synchronization is a statistical method to measure the interdependence of two oscillators and it has been applied in the fields of nonlinear dynamics and chaotic systems [14–16]. Short-range, or local, phase synchronization within the brain can be interpreted as creating regional “perceptual binding” [17]. Long-range phase synchronization, between regions, is thought to sub-serve motor planning [18, 19], emotion [20, 21], and memory [22–25].

Previous research has shown that an increase in electrocortical phase synchronization across the cortex facilitates neural communication, promotes neural plasticity, and supports working memory [25]. Synchronized firing of presynaptic neurons increases the firing rate of the postsynaptic neuron because multiple simultaneous inputs sum to increase the likelihood that the postsynaptic neuron’s threshold will be reached [26]. Synchronous gamma oscillations are confined to local neuronal areas, whereas theta synchronization is effective across long distances (i.e. disparate regions of the brain) [27–29]. Successful encoding of information during a memory task requires increased phase synchronization [22, 30–36]. The phase synchronization, within the theta band, between prefrontal and parietal regions during a working memory task is sustained during encoding, maintenance, and retrieval and this synchrony increases with memory load [28, 37]. Stimulation-induced beta and gamma synchronization produces increased coherence between frontal and parietal areas during working memory maintenance [38, 39].

Synchronization can be induced noninvasively via presentation of specific auditory stimuli, called binaural beats (BB). Binaural beats requires the presentation of two different tones to the ears [40]. This procedure causes a third phantom binaural beat, whose frequency is equal to the difference of the two presented tones, to be produced within the Inferior Colliculus (IC) located in the auditory pathway [41–44]. The overall phase difference is preserved from the IC to the auditory cortex by periodic neural firing at the binaural beat frequency [45]. The highest amount of synchronization in the auditory cortex due to binaural beats occurs within the beta band at 16Hz [42].

Previous work has demonstrated that binaural beats can affect cortical responses across frequency bands. Within the gamma band, the largest EEG steady state responses occurred with a binaural beat of 40Hz and primarily activated the frontal and parietal lobes [46–49]. In addition, binaural beat stimulation in the beta band at 18.5Hz increased EEG magnitude by 21% [50]. Areas of the cortex entrained by theta band binaural beats include parietal, frontal, and temporal areas [51–54]. However, binaural beats can influence activity outside their respective frequency band and this effect is not well characterized. For example, Gao et al. reported that, during either delta or alpha binaural beat stimulation, the EEG power increased in their respective band. However, in addition to the stimulated band, the relative EEG power increased in the theta and alpha bands as well [55].

A previous study, by Ioannou et al., investigated the impact of binaural beats on phase synchrony measures in both musicians and non-musicians. They found that binaural beat stimulation in the alpha band created the highest steady state responses in both groups. In addition, they determined that listening to low frequency binaural beats had a significant impact on the structure of the cortical connectivity network in the alpha band [56]. This work suggests that binaural beats will be able to significantly impact the network topology for improving memory.

Although binaural beats offer a noninvasive and easily administered stimulus, their effect on working memory has been explored in only a small number of studies. Kennerly investigated the effect of binaural beats on performance during memory span tasks [57]. The author concluded that the binaural beat groups performed significantly better when compared to the control group. Fernandez et al. tested the effects of binaural beats on verbal working memory [58]. Participants performed significantly better on a word recall task when listening to 5Hz binaural beat when compared to 13Hz. Lane et al. tested participant performance during a 1-back working memory test while listening to either theta or beta range binaural beats [59]. While listening to binaural beats in the beta frequency range, participants showed improvement in target detection, and decreased false alarms, task-related confusion, and fatigue. Although previous studies suggest that binaural beats offer noninvasive manipulation of brain activity that produces behavioral changes in working memory performance, prior studies have not investigated the neural mechanisms that drive the behavioral changes.

The goal of this study is to determine the effect of binaural beats on cortical connectivity and associate any changes in cortical network properties with behavioral performance during a visuospatial working memory task. In particular, we will use graph theory approaches to compare properties of functional networks built with EEG and link the observed behavioral data to those networks