Education: Categories of Neurotechnology

Categories of Neurotechnology

A wide variety of brain biofeedback and brain stimulation techniques have been developed to date. For clarifications about stimulatory techniques and their labels, consult 2019 Bikson et al [3]’s Transcranial Electrical Stimulation Nomenclature. Various applications are able to induce affective, emotional, and mood adjustments in addition to devices attempting cognitive alterations. Devices used in educational context address focus, attention, and cognitive activities such as mental workload (Kutafina et al., 2021) [4], physiological and learning ability of student (Babini, Kulish, &Namazi, 2020)[5], and group interaction & synchronicity in classroom setting  (Dikker et al., 2017)[6]. Combinations of targets among mental processes and psychological states are becoming the norm, rather than the exception. This means that instead of focusing on a single aspect of brain function, such as improving memory or reducing anxiety, modern brain stimulation and biofeedback techniques are designed to address multiple aspects simultaneously. That combinatory and holistic approach makes a good fit with psychologies and philosophies of instruction and education that view the entire individual as the learner, rather than targeting, in a modular manner, one specific part of the brain.

This document discusses only head wearables and transcranial techniques. Brain-computing implants (BCI) are currently too invasive for non-therapeutic applications in the near term to be a viable option within educational settings. Similarly, interventions/applications for attention-deficit disorders and other learning disabilities/differences fall under the remit of a medical intervention more than an educational one.

In the last twenty years of research in the neuroscience arena, evidence has accumulated that biofeedback, Transcranial Electrical Stimulation (TES), and similar non-invasive modalities can improve attention, focus, working memory, and other factors conducive to learning. TES modulates neural states through low direct current placed on the head. TES techniques were first developed for treating patients with major mental health disorders, but broader clinical and supplemental usages have proven possible. A common mode of TES is tDCS (transcranial direct current stimulation). Cranial electrotherapy stimulation (CES), which has FDA approval as a Class III device for treating psychiatric conditions such as depression, administers low intensity electrical current by way of connections at bilateral head locations, such as the earlobes and temples, to cause neuromodulatory effects at subthreshold levels. These have been listed as potential future use and specialized context. Transcranial stimulation is unlikely to be used in a pre-university educational setting or even Higher Education due to surgical requirements for these neurotechnologies.

Another form of neurotechnology that has transitioned from clinical and research use to consumer market availability is Electroencephalography (EEG). This non-invasive neuroelectric monitoring method permits bio-neurofeedback techniques to record and display levels of cortical activity to regulate desirable mental states conducive to learning. For example, it is possible to decode particular cognitive states from EEG activity, such as low level of attention or drowsiness, and in that case alert the user to this state to increase attention (KosKaushik et al, 2022) [7].

Many neurotechnological devices designed for scientific and clinical investigations are commercially available for approved human subject research. The field of educational research is beginning to be enlivened by studies of cognitive activity and learning performance under various conditions and settings. (Davidescu et al., 2021) [8]. By cognitive activity we refer to the field of research that associates theoretically well-defined cognitive functions with typical brain activity patterns in the brain. This field is rapidly shifting to machine-learning based decoding approaches that aim to ‘read out’ particular cognitive states from brain activity patterns. Learning performance can be defined as students’ self-evaluation of acquired knowledge, understanding and skills developed, and their desire to learn more (Young, Klemz, & Murphy, 2003) [9]

Consumer devices arriving on the market are starting to combine EEG sensing with fNIRS (functional near-infrared spectroscopy). fNIRS is a head-mounted method that measures real-time changes in blood flow and oxygenation levels in the cortex. fNIRS uses focused light (lasers or LEDs) that passes through the skull and is reflected back from brain blood vessels to be detected by the device from the differences detected between the device optodes. Because EEG has better temporal resolution, collects more data points per second, some new devices are combining EEG with fNIRS to record details about longer-lasting brain states and hence general mental conditions. See Table A2 below for specific devices already applied for potential educational use.

Additional neurotechnologies currently under exploration include transcranial magnetic stimulation, transcranial direct current stimulation, and optogenetics. Their effects on cognitive operations and outcomes are poorly understood within education at present. Optogenics, which combines light sensitivity with genetic engineering for brain stimulation, and brain implants might be the most likely examples of anticipated technologies in this field. Both promising results provided by research and industry-supported initiatives indicate that one day, they might transfer from animal models to human applications, but their translation into education will be challenging. For optogenetics, a few early protocols have been implemented in humans to, for example, successfully aid in vision restoration (Sahel et al, 2021) [10]. However, the use of optogenetics is accompanied by significant ethical concerns that will very likely limit its application to a restricted number of clinical cases (Harris and Gilbert, 2022) [11]. Research participants have had neural implants in their motor and sensory cortex, although their use for education purposes remains speculative.

Table A2 lists examples of noninvasive neurotechnology devices, area of focus of the device and link. The table mainly focuses on commercial products due their cost, and prior use in academic educational studies.

Table A2. Examples of existing neurotechnology devices relevant to cognition and learning (curated by Education Sub-committee)

The Future of the Smart Classroom illustrates article  [14, pg2] how EEG-based neurotechnology for learning can be integrated with real-time computer monitoring and instructor guidance into a systemic approach to educational methodology.   Future Smart Classroom concept leveraging wearable neurotechnology to enhance personalized learning. In this setup, both in-person and remote students wear sensors that monitor cognitive load, stress, focus, sleep quality, and information assimilation. This data is processed in real-time via cloud-based systems, and adaptation algorithms provide personalized feedback and recommendations to both students and teachers. Teachers receive insights to adjust instructional materials dynamically, including pacing, ordering, and additional content, as well as recommendations for group work to optimize coherence and performance. This approach aims to improve student engagement and performance by creating a responsive and adaptive learning environment, benefiting from real-time data monitoring and cloud integration​.