There's a whole field called neuromarketing that focuses on neural processes and emotions, such as fear, anger, happiness, and sadness. The purpose? To sell you items! And to convince you to do/believe/think in a variety of desired ways: agitation, fervor, complacency, etc. Market research has come a long way from relying on focus groups and telephone surveys.
The neural-investigation devices used in scientists' studies are quite small and wearable these days. Think cellphone- and smartwatch- small. They need to be able to measure blood oxygenation, which is cheaply done. Nowadays, one can buy an oximeter for under $8 on Amazon, including shipping.
Have you ever wondered how Facebook gets you to keep scrolling and knows what algorithms to deploy on you to keep you engaged? Your cellphone camera(s) can track your eye movement, which indicates what you are interested in.
The neuromarketing technology has gotten so good that it can read your unconscious preferences. For example, it can predict what people will do with respect to stock transactions even before people have consciously come to a decision.
This is impressive, world-altering technology, and we too often are oblivious that is available to marketers and influence-sellers. There is a reason that data analysts are so highly paid. There is a lot of data out there to analyze.
Here are some studies to back up the above claims:
1) Cherubino P, Martinez-Levy AC, Caratù M, Cartocci G, Di Flumeri G, Modica E, Rossi D, Mancini M, Trettel A. Consumer Behaviour through the Eyes of Neurophysiological Measures: State-of-the-Art and Future Trends. Comput Intell Neurosci. 2019 Sep 18;2019:1976847. doi: 10.1155/2019/1976847. PMID: 31641346; PMCID: PMC6766676. Online at https://pmc.ncbi.nlm.nih.gov/articles/PMC6766676/
[F]irstly, we will describe the historical development of neuromarketing and its main applications in assessing the sensory perceptions of some marketing and advertising stimuli. Then, we will describe the main neuroscientific tools available for such kind of investigations (e.g., measuring the cerebral electrical or hemodynamic activity, the eye movements, and the psychometric responses). Also, this review will present different brain measurement techniques, along with their pros and cons, and the main cerebral indexes linked to the specific mental states of interest (used in most of the neuromarketing research). Such indexes have been supported by adequate validations from the scientific community and are largely employed in neuromarketing research.
2) Rawnaque FS, Rahman KM, Anwar SF, Vaidyanathan R, Chau T, Sarker F, Mamun KAA. Technological advancements and opportunities in Neuromarketing: a systematic review. Brain Inform. 2020 Sep 21;7(1):10. doi: 10.1186/s40708-020-00109-x. PMID: 32955675; PMCID: PMC7505913. Online at https://pubmed.ncbi.nlm.nih.gov/32955675/
Physiological response measuring techniques such as eye tracking, skin conductance recording, heart rate monitoring, and facial mapping have also been found in these empirical studies exclusively or in parallel with brain recordings.
3) Rigby D, Vass C, Payne K. Opening the 'Black Box': An Overview of Methods to Investigate the Decision-Making Process in Choice-Based Surveys. Patient. 2020 Feb;13(1):31-41. doi: 10.1007/s40271-019-00385-8. PMID: 31486021. Online at https://pubmed.ncbi.nlm.nih.gov/31486021/
A variety of methods of pre-choice process analysis have been developed to investigate how and why people make their decisions in such experiments and surveys. These techniques have been developed to investigate how people acquire and process information and make choices. These techniques offer the potential to test and improve theories of choice and/or associated empirical models. This paper provides an overview of such methods, with the focus on their use in stated choice-based healthcare studies. The methods reviewed are eye tracking, mouse tracing, brain imaging, deliberation time analysis and think aloud. For each method, we summarise the rationale, implementation, type of results generated and associated challenges, along with a discussion of possible future developments.
4) Colomer Granero A, Fuentes-Hurtado F, Naranjo Ornedo V, Guixeres Provinciale J, Ausín JM, Alcañiz Raya M. A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents. Front Comput Neurosci. 2016 Jul 15;10:74. doi: 10.3389/fncom.2016.00074. PMID: 27471462; PMCID: PMC4945646. Online at https://pmc.ncbi.nlm.nih.gov/articles/PMC4945646/
Estimation of emotional states is a powerful tool in the marketing field. Efficient monitoring of human emotional states may provide important and useful information for marketing purposes (Frantzidis et al., 2010a). Such monitoring could follow either subjective or objective methods. Subjective methods (psychology-oriented approach) are based on qualitative behavior assessment or by means of questionnaires and interviews, whilst objective methods (neuropsychology-oriented approach) consist on monitoring and analyzing the subject biosignals (Frantzidis et al., 2010a).
It is now recognized that making use of standard marketing techniques, such as depth interviews or focus groups, in which customers are exposed to the product in advance of its massive launch or afterwards, provides biased answers due to the respondents cognitive processes activating during the interview and by the influence that the interviewer may have on their recalls (Vecchiato et al., 2014). Furthermore, people are not able to (or might not want) fully express their preferences when they are explicitly asked (Vecchiato et al., 2011a). Therefore, marketing researchers prefer to complement traditional methods with the use of biosignals.
To follow the objective approach, different features of either positive or negative emotions can be extracted from physiological signals, such as electrocardiography (ECG), electroencephalography (EEG), galvanic skin response (GSR) or the breathing response (Frantzidis et al., 2010a). This techniques allow to assess human emotions in terms of it is able to reveal information that is unobtainable employing traditional methods (Vecchiato et al., 2014).
Electroencephalography and the magnetoencephalography (MEG) allow to record on a millisecond basis the brain activity during the exposition to relevant marketing stimuli. However, such imaging brain techniques present one difficulty: the recorded cerebral activity is mainly generated on the cortical structures of the brain. It is almost impossible to acquire the electromagnetic activity yield by deep structures which are often associated with the generation of emotional processing in humans with EEG or MEG sensors. To overcome this problem, high-resolution EEG technology has been developed to enhance the poor spatial information content on the EEG activity. With this technology, brain activity can be detected with a spatial resolution of a squared centimeter on a milliseconds basis, but only in the cerebral cortex.
Furthermore, autonomic activity such as Heart Rate (HR) and Galvanic Skin Response (GSR) are also able to assess the internal emotional state of the subject (Christoforou et al., 2015; Ohme et al., 2011). GSR activity is actually a sensitive and convenient way of measuring indexing changes in sympathetic arousal associated with emotion, cognition and attention (Critchley, 2002). Lang et al. (1993) discovered that the mean value of GSR is related to the level of arousal. Blood pressure and Heart Rate Variability (HRV) also correlate with emotions, since stress may increase blood pressure. Pleasantness of stimuli can increase peak heart rate response, and HRV decreases with fear, sadness and happiness (Soleymani et al., 2008). Respiration has proven to be an adequate emotional indicator. It is possible to distinguish relaxation (slow respiration) and anger or fear (irregular rhythm, quick variations and cessation of respiration). It is possible as well to detect laughing because it introduces high-frequency fluctuations to the HRV signal (Appelhans and Luecken, 2006).
5) Stallen M, Borg N, Knutson B. Brain Activity Foreshadows Stock Price Dynamics. J Neurosci. 2021 Apr 7;41(14):3266-3274. doi: 10.1523/JNEUROSCI.1727-20.2021. Epub 2021 Mar 8. PMID: 33685944; PMCID: PMC8026346. Online at https://pmc.ncbi.nlm.nih.gov/articles/PMC8026346/
Many try but fail to consistently forecast changes in stock prices. New evidence, however, suggests that anticipatory affective brain activity may not only predict individual choice, but also may forecast aggregate choice. Assuming that stock prices index collective choice, we tested whether brain activity sampled during the assessment of stock prices could forecast subsequent changes in the prices of those stocks. In two neuroimaging experiments, a combination of previous stock price movements and brain activity in a region implicated in processing uncertainty and arousal forecast next-day stock price changes—even when behavior did not. These findings challenge traditional assumptions of market efficiency by implying that neuroimaging data might reveal “hidden information” capable of foreshadowing stock price dynamics.
6) Çakar T, Filiz G. Unraveling neural pathways of political engagement: bridging neuromarketing and political science for understanding voter behavior and political leader perception. Front Hum Neurosci. 2023 Dec 21;17:1293173. doi: 10.3389/fnhum.2023.1293173. PMID: 38188505; PMCID: PMC10771297. Online at https://pmc.ncbi.nlm.nih.gov/articles/PMC10771297/
The present investigation used a near-infrared spectroscopy (NIRS) system as primary data collection instrument. The NIRS system utilized in this study is produced by fNIR Devices, model 11001 and is rooted in the research development units of Drexel University (Philadelphia, PA, USA) (Ayaz, 2010). The system consists of three elements: a flexible sensor with 16 optodes (8 light sources and 8 detectors) arranged in a 4 × 4 grid, and which is securely fixed to the participant’s head; the control box with electronic components and analog-to-digital converters; and the system computer, which runs the COBI Studio software and facilitates real-time data monitoring and recording. The sensor, equipped with four distinct light sources, detects oxygenation levels through ten detectors while concurrently recording data streams across sixteen distinct channels (Ayaz et al., 2011). Notably, the sensor is designed so that the light source and the detector are approximately 2.5 centimeters apart, thereby enabling measurements from depths of approximately 1.25 centimeters. This fNIRS system uses two wavelengths (760 nm and 830 nm) to measure the concentration of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (Hb) in the blood. Functionally, the system boasts a data acquisition frequency of 2 samples per second (2 Hz) and is capable of measuring neural activity within the Brodmann areas BA9, BA10, BA44, and BA45 (Ayaz et al., 2011).
The non-invasive and portable nature of the optical brain imaging system is instrumental to its effectiveness.
[Update 2/12/2025: Not only can it "read" our minds, our portable technology can also be used to affect our mental states. Smart phones now usually come with the capability of generating infrared light, which can be used to improve mood and reduce inflammation:
Giménez MC, Luxwolda M, Van Stipriaan EG, Bollen PP, Hoekman RL, Koopmans MA, Arany PR, Krames MR, Berends AC, Hut RA, Gordijn MCM. Effects of Near-Infrared Light on Well-Being and Health in Human Subjects with Mild Sleep-Related Complaints: A Double-Blind, Randomized, Placebo-Controlled Study. Biology (Basel). 2022 Dec 29;12(1):60. doi: 10.3390/biology12010060. PMID: 36671752; PMCID: PMC9855677. Online at https://pmc.ncbi.nlm.nih.gov/articles/PMC9855677/
Therapeutic exposure to doses of red and NIR, known as photobiomodulation (PBM), has been effective for a broad range of conditions. In a double-blind, randomized, placebo-controlled study, we aimed to assess the effects of a PBM home set-up on various aspects of well-being, health, sleep, and circadian rhythms in healthy human subjects with mild sleep complaints. The effects of three NIR light (850 nm) doses (1, 4, or 6.5 J·cm−2) were examined against the placebo. Exposure was presented five days per week between 9:30 am and 12:30 pm for four consecutive weeks. The study was conducted in both summer and winter to include seasonal variation. The results showed PBM treatment only at 6.5 J·cm−2 to have consistent positive benefits on well-being and health, specifically improving mood, reducing drowsiness, reducing IFN-γ, and resting heart rate. This was only observed in winter.
I think that housing people in windowless buildings is a very bad idea, per this study. We need some of this kind of light.]
[Update 2/13/2025: I think the most secretive, well-funded agencies have been working on mind reading capabilities for decades. Last fall, Popular Mechanics reported the military is going to develop mind reading helmets for aircraft pilots, ones that are non-invasive (i.e., not relying on brain implants) and so precise that the military intends to have the pilots use the mind reading capabilites for launching weapons. You don't rely on technology to launch weapons until you're sure it works and works extraordinarily well! Here's a link to the Popular Mechanics story:
https://www.popularmechanics.com/military/a62719626/darpa-n3-ai-helmet/
If mind reading technology is being used on us civilians these days, I think DARPA and other such agencies are obligated under the Constitution, as constructed and understood to be about providing for the common defense, to tell us about it, no matter how many non-disclosure agreements they initially signed back when our society wasn't being run into the ground by unproductive uses of new technologies.]
[Update 2/16/2025: As I look at news headlines, I'm struck with the realization that they make a lot more sense if one hypothesizes that some people are using advanced technology to manipulate politicians and prominent business/entertainment people. Sort of a Sim-City game, but real. Is it plausible?]
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