Brain fingerprinting: a comprehensive tutorial review of detection of concealed information with event-related brain potentials

Inferring Mental States from Brain Data: Ethico-legal Questions about Social Uses of Brain Data

Neurotechnologies that collect and interpret data about brain activity are already in use for medical and nonmedical applications. Refinements of existing noninvasive techniques and the discovery of new ones will likely encourage broader uptake. The increased collection and use of brain data and, in particular, their use to infer the existence of mental states have led to questions about whether mental privacy may be threatened. It may be threatened if the brain data actually support inferences about the mind or if decisions are made about a person in the belief that the inferences are justified. This article considers the chain of inferences lying between data about neural activity and a particular mental state as well as the ethico-legal issues raised by making these inferences, focusing here on what the threshold of reliability should be for using brain data to infer mental states.

Psychology and the lie detector industry: A fifty-year perspective

Fifty years ago, in a trenchant analysis that challenged applied lie detection theory and science, David Lykken (1974) brought polygraphic interrogation methods to the attention of academia with the hope that these techniques would come under the purview of psychology and psychophysiology. In this perspective, I examine how this application of psychophysiology has evolved over the last half century and how its status has changed for 1) the comparison (control) question test (CQT), used in forensic applications; 2) polygraph screening tests, used to evaluate examinee integrity; and 3) the concealed information technique (CIT), used to assess recognition memory of crime details. The criticisms of the CQT and screening tests advanced by Lykken have been amplified and focused by the academic community over the last half century. However, this has had little effect on how these methods are practiced and has not curtailed their use. Although most private sector employee screening tests are now prohibited, personnel screening of government employees has increased, and screening tests of sex offenders are now commonplace. Even though the CIT has captured the interest of psychophysiologists as a scientifically defensible technique, its field use is negligible. A primary purpose of polygraphic interrogations continues to be the extraction of admissions and confessions. The lack of change in the polygraph testing status quo stems in large part from unwavering government support for the use of these methods. As a result, polygraph theory and research support continues to rest on shaky ground while practice continues unfettered by valid criticism.

The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device

In recent years, brainprint recognition has emerged as a novel method of personal identity verification. Although studies have demonstrated the feasibility of this technology, some limitations hinder its further development into the society, such as insufficient efficiency (extended wear time for multi-channel EEG cap), complex experimental paradigms (more time in learning and completing experiments), and unclear neurobiological characteristics (lack of intuitive biomarkers and an inability to eliminate the impact of noise on individual differences). Overall, these limitations are due to the incomplete understanding of the underlying neural mechanisms. Therefore, this study aims to investigate the neural mechanisms behind brainwave recognition and simplify the operation process. We recorded prefrontal resting-state EEG data from 40 participants, which is followed up over nine months using a single-channel portable brainwave device. We found that portable devices can effectively and stably capture the characteristics of different subjects in the alpha band (8-13Hz) over long periods, as well as capturing their individual differences (no alpha peak, 1 alpha peak, or 2 alpha peaks). Through correlation analysis, alpha-band activity can reveal the uniqueness of the subjects compared to others within one minute. We further used a descriptive model to dissect the oscillatory and non-oscillatory components in the alpha band, demonstrating the different contributions of fine oscillatory features to individual differences (especially amplitude and bandwidth). Our study validated the feasibility of portable brainwave devices in brainwave recognition and the underlying neural oscillation mechanisms. The fine characteristics of various alpha oscillations will contribute to the accuracy of brainwave recognition, providing new insights for the development of future brainwave recognition technology.

Unique Brain Network Identification Number for Parkinson's and Healthy Individuals Using Structural MRI

We propose a novel algorithm called Unique Brain Network Identification Number (UBNIN) for encoding the brain networks of individual subjects. To realize this objective, we employed structural MRI on 180 Parkinson's disease (PD) patients and 70 healthy controls (HC) from the National Institute of Mental Health and Neurosciences, India. We parcellated each subject's brain volume and constructed an individual adjacency matrix using the correlation between the gray matter volumes of every pair of regions. The unique code is derived from values representing connections for every node (i), weighted by a factor of 2-(i-1). The numerical representation (UBNIN) was observed to be distinct for each individual brain network, which may also be applied to other neuroimaging modalities. UBNIN ranges observed for PD were 15,360 to 17,768,936,615,460,608, and HC ranges were 12,288 to 17,733,751,438,064,640. This model may be implemented as a neural signature of a person's unique brain connectivity, thereby making it useful for brainprinting applications. Additionally, we segregated the above datasets into five age cohorts: A: ≤32 years (n1 = 4, n2 = 5), B: 33-42 years (n1 = 18, n2 = 14), C: 43-52 years (n1 = 42, n2 = 23), D: 53-62 years (n1 = 69, n2 = 22), and E: ≥63 years (n1 = 46, n2 = 6), where n1 and n2 are the number of individuals in PD and HC, respectively, to study the variation in network topology over age. Sparsity was adopted as the threshold estimate to binarize each age-based correlation matrix. Connectivity metrics were obtained using Brain Connectivity toolbox (Version 2019-03-03)-based MATLAB (R2020a) functions. For each age cohort, a decreasing trend was observed in the mean clustering coefficient with increasing sparsity. Significantly different clustering coefficients were noted in PD between age-cohort B and C (sparsity: 0.63, 0.66), C and E (sparsity: 0.66, 0.69), and in HC between E and B (sparsity: 0.75 and above 0.81), E and C (sparsity above 0.78), E and D (sparsity above 0.84), and C and D (sparsity: 0.9). Our findings suggest network connectivity patterns change with age, indicating network disruption may be due to the underlying neuropathology. Varying clustering coefficients for different cohorts indicate that information transfer between neighboring nodes changes with age. This provides evidence of age-related brain shrinkage and network degeneration. We also discuss limitations and provide an open-access link to software codes and a help file for the entire study.

Brain fingerprinting field study on major, terrorist crimes supports the brain fingerprinting scientific standards hypothesis: classification concealed information test with P300 and P300-MERMER succeeds; comparison CIT fails

We conducted (I) 18 event-related potential (ERP) field tests to detect concealed information regarding major terrorist crimes and other real-world crimes and (II) 5 ERP tests regarding participation in a classified counterterrorism operation. This study is a test of the brain fingerprinting scientific standards hypothesis: that a specific set of methods for event-related potential (ERP) concealed information tests (CIT) known as the brain fingerprinting scientific standards provide the sufficient conditions to produce less than 1% error rate and greater than 95% median statistical confidence for individual determinations of whether the tested information is stored in each subject's brain. All previous published results in all laboratories are compatible with this hypothesis. We recorded P300 and P300-MERMER ERP responses to visual text stimuli of three types: targets contain known information, irrelevants contain unknown/irrelevant information, and probes contain the situation-relevant information to be tested, known only to the perpetrator and investigators. Classification CIT produced significantly better results than comparison CIT, independent of classification criteria. Classification CIT had 0% error rate; comparison CIT had 6% error rate. As in previous studies, classification-CIT median statistical confidences were approximately 99%, whereas comparison CIT statistical confidences were no better than chance for information-absent (IA) subjects (who did not know the tested information). Over half of the comparison-CIT IA determinations were invalid due to a less-than-chance computed probability of being correct. Experiment (I) results for median statistical confidence: Classification CIT, IA subjects: 98.6%; information-present (IP) subjects (who know the tested information): 99.9%; comparison CIT, IA subjects: 48.7%; IP subjects: 99.5%. Experiment (II) results (Classification CIT): error rate 0%, median statistical confidence 96.6%. Countermeasures had no effect on the classification CIT. These results, like all previous results in our laboratory and all others, support the brain fingerprinting scientific standards hypothesis and indicate that the classification CIT is a necessary condition for a reliable, accurate, and valid brainwave-based CIT. The comparison CIT, by contrast, produces high error rates and IA statistical confidences no better than chance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09795-1.

Simultaneous multiple-stimulus auditory brain-computer interface with semi-supervised learning and prior probability distribution tuning

Objective.Auditory brain-computer interfaces (BCIs) enable users to select commands based on the brain activity elicited by auditory stimuli. However, existing auditory BCI paradigms cannot increase the number of available commands without decreasing the selection speed, because each stimulus needs to be presented independently and sequentially under the standard oddball paradigm. To solve this problem, we propose a double-stimulus paradigm that simultaneously presents multiple auditory stimuli.Approach.For addition to an existing auditory BCI paradigm, the best discriminable sound was chosen following a subjective assessment. The new sound was located on the right-hand side and presented simultaneously with an existing sound from the left-hand side. A total of six sounds were used for implementing the auditory BCI with a 6 × 6 letter matrix. We employ semi-supervised learning (SSL) and prior probability distribution tuning to improve the accuracy of the paradigm. The SSL method involved updating of the classifier weights, and their prior probability distributions were adjusted using the following three types of distributions: uniform, empirical, and extended empirical (e-empirical). The performance was evaluated based on the BCI accuracy and information transfer rate (ITR).Main results.The double-stimulus paradigm resulted in a BCI accuracy of 67.89 ± 11.46% and an ITR of 2.67 ± 1.09 bits min^-1, in the absence of SSL and with uniform distribution. The proposed combination of SSL with e-empirical distribution improved the BCI accuracy and ITR to 74.59 ± 12.12% and 3.37 ± 1.27 bits min^-1, respectively. The event-related potential analysis revealed that contralateral and right-hemispheric dominances contributed to the BCI performance improvement.Significance.Our study demonstrated that a BCI based on multiple simultaneous auditory stimuli, incorporating SSL and e-empirical prior distribution, can increase the number of commands without sacrificing typing speed beyond the acceptable level of accuracy.

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.

Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface

A brain-computer interface (BCI) can connect humans and machines directly and has achieved successful applications in the past few decades. Many new BCI paradigms and algorithms have been developed in recent years. Therefore, it is necessary to review new progress in BCIs. This paper summarizes progress for EEG-based BCIs from the perspective of encoding paradigms and decoding algorithms, which are two key elements of BCI systems. Encoding paradigms are grouped by their underlying neural meachanisms, namely sensory- and motor-related, vision-related, cognition-related and hybrid paradigms. Decoding algorithms are reviewed in four categories, namely decomposition algorithms, Riemannian geometry, deep learning and transfer learning. This review will provide a comprehensive overview of both modern primary paradigms and algorithms, making it helpful for those who are developing BCI systems.

Aging reduces EEG markers of recognition despite intact performance: Implications for forensic memory detection

ERP-based forensic memory detection is based on the logic that guilty suspects will hold incriminating knowledge about crimes they have committed, and therefore should show parietal ERP positivities related to recognition when presented with reminders of their crimes. We predicted that such forensic memory detection might however be inaccurate in older adults, because of changes to recognition-related brain activity that occurs with aging. We measured both ERPs and EEG oscillations associated with episodic old/new recognition and forensic memory detection in 30 younger (age < 30) and 30 older (age > 65) adults. EEG oscillations were included as a complementary measure which is less sensitive to temporal variability and component overlap than ERPs. In line with predictions, recognition-related parietal ERP positivities were significantly reduced in the older compared to younger group in both tasks, despite highly similar behavioural performance. We also observed aging-related reductions in oscillatory markers of recognition in the forensic memory detection test, while the oscillatory effects associated with episodic recognition were similar across age groups. This pattern of results suggests that while both forensic memory detection and episodic recognition are accompanied by aging-induced reductions in parietal ERP positivities, these reductions may be caused by non-overlapping mechanisms across the two tasks. Our findings suggest that EEG-based forensic memory detection tests are less valid in older than younger populations, limiting their practical applications.

Fast fronto-parietal cortical dynamics of conflict detection and context updating in a flanker task

Recent research has found that the traditional target P3 consists of a family of P3-like positivities that can be functionally and topographically dissociated from one another. The current study examined target N2 and P3-like subcomponents indexing conflict detection and context updating at low- and high-order levels in the neural hierarchy during cognitive control. Electroencephalographic signals were recorded from 45 young adults while they completed a hybrid go/nogo flanker task, and Residue Iteration Decomposition (RIDE) was applied to functionally dissociate these peaks. Analyses showed a stimulus-locked frontal N2 revealing early detection and fast perceptual categorization of nogo, congruent and incongruent trials, resulting in frontal P3-like activity elicited by nogo trials in the latency-variable RIDE cluster, and by incongruent trials in the response-locked cluster. The congruent trials did not elicit frontal P3-like activity. These findings suggest that behavioral incongruency effects are related to intermediate and later stages of motor response re-programming.

Deleterious effects of probe-related versus irrelevant targets on the "CIT effect" in the P300- and RT-based three-stimulus protocol for detection of concealed information

Two groups of participants committed the same mock crime in which one of two items, a watch or a ring, was removed from a drawer and concealed. One group, the crime-familiar group next experienced a three-stimulus protocol (3SP), a Concealed Information Test (CIT), in which they were tested on the stolen (probe) item presented in a random series of five irrelevant (unseen) stimuli from the same jewelry category. A left-hand button press, meaning "I don't recognize" was to follow each of these six items. A right-hand press ("I do recognize") was to follow the one other presented item, the target item, which in the case of the crime-familiar group was the other, not-stolen item in the drawer at the mock crime scene. For the other crime-unfamiliar group, the target was a sixth unseen irrelevant item as in the original P300 CIT. In terms of P300 latency and reaction time (RT), crime-familiar participants processed all stimuli faster than crime-unfamiliar participants. The CIT effects (probe-minus-irrelevant differences) for crime-familiar group members were inferior to those of crime-unfamiliar group members for RT and P300 amplitude measures. Thus, familiar targets negatively impact the 3SP.

Criminal Responsibility and Neuroscience: No Revolution Yet

Since the 1990's, neurolaw is on the rise. At the heart of heated debates lies the recurrent theme of a neuro-revolution of criminal responsibility. However, caution should be observed: the alleged foundations of criminal responsibility (amongst which free will) are often inaccurate and the relative imperviousness of its real foundations to scientific facts often underestimated. Neuroscientific findings may impact on social institutions, but only insofar as they also engage in a political justification of the changes being called for, convince populations, and take into consideration the ensuing consequences. Moreover, the many limits of neuroscientific tools call for increased vigilance when, if ever, using neuroscientific evidence in a courtroom. In this article, we aim at setting the basis for future sound debates on the contribution of neuroscience to criminal law, and in particular to the assessment of criminal responsibility. As such, we provide analytical tools to grasp the political and normative nature of criminal responsibility and review the current or projected use of neuroscience in the law, all the while bearing in mind the highly publicized question: can neuroscience revolutionize criminal responsibility? Answering this question implicitly requires answering a second question: should neuroscience revolutionize the institution of criminal responsibility? Answering both, in turn, requires drawing the line between science and normativity, revolution and dialogue, fantasies and legitimate hopes.

Integrating Brain Science and Law: Neuroscientific Evidence and Legal Perspectives on Protecting Individual Liberties

Advances in neuroscientific techniques have found increasingly broader applications, including in legal neuroscience (or “neurolaw”), where experts in the brain sciences are called to testify in the courtroom. But does the incursion of neuroscience into the legal sphere constitute a threat to individual liberties? And what legal protections are there against such threats? In this paper, we outline individual rights as they interact with neuroscientific methods. We then proceed to examine the current uses of neuroscientific evidence, and ultimately determine whether the rights of the individual are endangered by such approaches. Based on our analysis, we conclude that while federal evidence rules constitute a substantial hurdle for the use of neuroscientific evidence, more ethical safeguards are needed to protect against future violations of fundamental rights. Finally, we assert that it will be increasingly imperative for the legal and neuroscientific communities to work together to better define the limits, capabilities, and intended direction of neuroscientific methods applicable for use in law.

Usage of drip drops as stimuli in an auditory P300 BCI paradigm

Recently, many auditory BCIs are using beeps as auditory stimuli, while beeps sound unnatural and unpleasant for some people. It is proved that natural sounds make people feel comfortable, decrease fatigue, and improve the performance of auditory BCI systems. Drip drop is a kind of natural sounds that makes humans feel relaxed and comfortable. In this work, three kinds of drip drops were used as stimuli in an auditory-based BCI system to improve the user-friendness of the system. This study explored whether drip drops could be used as stimuli in the auditory BCI system. The auditory BCI paradigm with drip-drop stimuli, which was called the drip-drop paradigm (DP), was compared with the auditory paradigm with beep stimuli, also known as the beep paradigm (BP), in items of event-related potential amplitudes, online accuracies and scores on the likability and difficulty to demonstrate the advantages of DP. DP obtained significantly higher online accuracy and information transfer rate than the BP (p < 0.05, Wilcoxon signed test; p < 0.05, Wilcoxon signed test). Besides, DP obtained higher scores on the likability with no significant difference on the difficulty (p < 0.05, Wilcoxon signed test). The results showed that the drip drops were reliable acoustic materials as stimuli in an auditory BCI system.

Deception Detection by Hybrid-Pair Wireless fNIRS System

Normal fNIRS setting up was limited by superficial physiological noises when applied into the deception detection. We designed a hybrid-pair wireless fNIRS system to improve the detection. The system takes advantages of short-pair channel to suppress the effect of physiological noises, and wireless module to improve the comfortableness of wearing it. We applied the system into a modified Guilty Knowledge Test. The experiment demonstrated that normal metrics might hint different energy consume during lying, while the regional oxygen saturation rSO2, specific in the system, is sensitive to indicate a lying.

An exploration of spatial auditory BCI paradigms with different sounds: music notes versus beeps

Visual brain-computer interfaces (BCIs) are not suitable for people who cannot reliably maintain their eye gaze. Considering that this group usually maintains audition, an auditory based BCI may be a good choice for them. In this paper, we explore two auditory patterns: (1) a pattern utilizing symmetrical spatial cues with multiple frequency beeps [called the high low medium (HLM) pattern], and (2) a pattern utilizing non-symmetrical spatial cues with six tones derived from the diatonic scale [called the diatonic scale (DS) pattern]. These two patterns are compared to each other in terms of accuracy to determine which auditory pattern is better. The HLM pattern uses three different frequency beeps and has a symmetrical spatial distribution. The DS pattern uses six spoken stimuli, which are six notes solmizated as "do", "re", "mi", "fa", "sol" and "la", and derived from the diatonic scale. These six sounds are distributed to six, spatially distributed, speakers. Thus, we compare a BCI paradigm using beeps with another BCI paradigm using tones on the diatonic scale, when the stimuli are spatially distributed. Although no significant differences are found between the ERPs, the HLM pattern performs better than the DS pattern: the online accuracy achieved with the HLM pattern is significantly higher than that achieved with the DS pattern (p = 0.0028).

Historical Techniques of Lie Detection

Since time immemorial, lying has been a part of everyday life. For this reason, it has become a subject of interest in several disciplines, including psychology. The purpose of this article is to provide a general overview of the literature and thinking to date about the evolution of lie detection techniques. The first part explores ancient methods recorded circa 1000 B.C. (e.g., God’s judgment in Europe). The second part describes technical methods based on sciences such as phrenology, polygraph and graphology. This is followed by an outline of more modern-day approaches such as FACS (Facial Action Coding System), functional MRI, and Brain Fingerprinting. Finally, after the familiarization with the historical development of techniques for lie detection, we discuss the scope for new initiatives not only in the area of designing new methods, but also for the research into lie detection itself, such as its motives and regulatory issues related to deception.

Identifying the location of a concealed object through unintentional eye movements

In some investigative and interrogative contexts, the investigator is seeking to identify the location of an object (e.g., implanted bomb) which is known to a given subject (e.g., a terrorist). In this paper, we present a non-intrusive methodology for uncovering the loci of a concealed object by analyzing the subject's eye movements. Using a combination of eye tracking, psychological manipulation and a search algorithm, we have performed two experiments. In the first experiment, we have gained 58% hit rate in identifying the location of the concealed object and in the second experiment 56% hit rate. The pros and cons of the methodology for forensic investigation are discussed.

Brain fingerprinting classification concealed information test detects US Navy military medical information with P300

A classification concealed information test (CIT) used the “brain fingerprinting” method of applying P300 event-related potential (ERP) in detecting information that is (1) acquired in real life and (2) unique to US Navy experts in military medicine. Military medicine experts and non-experts were asked to push buttons in response to three types of text stimuli. Targets contain known information relevant to military medicine, are identified to subjects as relevant, and require pushing one button. Subjects are told to push another button to all other stimuli. Probes contain concealed information relevant to military medicine, and are not identified to subjects. Irrelevants contain equally plausible, but incorrect/irrelevant information. Error rate was 0%. Median and mean statistical confidences for individual determinations were 99.9% with no indeterminates (results lacking sufficiently high statistical confidence to be classified). We compared error rate and statistical confidence for determinations of both information present and information absent produced by classification CIT (Is a probe ERP more similar to a target or to an irrelevant ERP?) vs. comparison CIT (Does a probe produce a larger ERP than an irrelevant?) using P300 plus the late negative component (LNP; together, P300-MERMER). Comparison CIT produced a significantly higher error rate (20%) and lower statistical confidences: mean 67%; information-absent mean was 28.9%, less than chance (50%). We compared analysis using P300 alone with the P300 + LNP. P300 alone produced the same 0% error rate but significantly lower statistical confidences. These findings add to the evidence that the brain fingerprinting methods as described here provide sufficient conditions to produce less than 1% error rate and greater than 95% median statistical confidence in a CIT on information obtained in the course of real life that is characteristic of individuals with specific training, expertise, or organizational affiliation.

Brain fingerprinting field studies comparing P300-MERMER and P300 brainwave responses in the detection of concealed information

Brain fingerprinting detects concealed information stored in the brain by measuring brainwave responses. We compared P300 and P300-MERMER event-related brain potentials for error rate/accuracy and statistical confidence in four field/real-life studies. 76 tests detected presence or absence of information regarding (1) real-life events including felony crimes; (2) real crimes with substantial consequences (either a judicial outcome, i.e., evidence admitted in court, or a $100,000 reward for beating the test); (3) knowledge unique to FBI agents; and (4) knowledge unique to explosives (EOD/IED) experts. With both P300 and P300-MERMER, error rate was 0 %: determinations were 100 % accurate, no false negatives or false positives; also no indeterminates. Countermeasures had no effect. Median statistical confidence for determinations was 99.9 % with P300-MERMER and 99.6 % with P300. Brain fingerprinting methods and scientific standards for laboratory and field applications are discussed. Major differences in methods that produce different results are identified. Markedly different methods in other studies have produced over 10 times higher error rates and markedly lower statistical confidences than those of these, our previous studies, and independent replications. Data support the hypothesis that accuracy, reliability, and validity depend on following the brain fingerprinting scientific standards outlined herein.

A comparison study of two P300 speller paradigms for brain-computer interface

In this paper, a comparison of two existing P300 spellers is conducted. In the first speller, the visual stimuli of characters are presented in a single character (SC) paradigm and each button corresponding to a character flashes individually in a random order. The second speller is based on a region-based (RB) paradigm. In the first level, all characters are grouped and each button corresponding to a group flashes individually in a random order. Once a group is selected, the characters in it will appear on the flashing buttons of the second level for the selection of desired character. In a spelling experiment involving 12 subjects, higher online accuracy was obtained on the RB paradigm-based P300 speller than the SC paradigm-based P300 speller. Furthermore, we analyzed P300 detection performance, the P300 waveforms and Fisher ratios using the data collected by the two spellers. It was found that the stimuli display paradigm of the RB speller enhances P300 potential and is more suitable for P300 detection.

A comment on Farwell (2012): brain fingerprinting: a comprehensive tutorial review of detection of concealed information with event-related brain potentials

In a recent issue of Cognitive Neurodynamics Farwell (Cogn Neurodyn 6:115-154, 2012) published a comprehensive tutorial review of the use of Event Related Brain Potentials (ERP) in the detection of concealed information. Farwell's review covered much of his own work employing his "brain fingerprinting" technology. All his work showed a 100 % accuracy rate in detecting concealed information. We argue in this comment that Farwell (Cogn Neurodyn 6:115-154, 2012) is misleading and misrepresents the scientific status of brain fingerprinting technology.

Brain fingerprinting: let's focus on the science-a reply to Meijer, Ben-Shakhar, Verschuere, and Donchin

Farwell in Cogn Neurodyn 6:115-154, (2012) reviewed all research on brainwave-based detection of concealed information published in English, including the author's laboratory and field research. He hypothesized that specific methods are sufficient to obtain less than 1 % error rate and high statistical confidence, and some of them are necessary. Farwell proposed 20 brain fingerprinting scientific standards embodying these methods. He documented the fact that all previous research and data are compatible with these hypotheses and standards. Farwell explained why failure to meet these standards resulted in decrements in performance of other, alternative methods. Meijer et al. criticized Farwell in Cogn Neurodyn 6:115-154, (2012) and Farwell personally. The authors stated their disagreement with Farwell's hypotheses, but did not cite any data that contradict the three hypotheses, nor did they propose alternative hypotheses or standards. Meijer et al. made demonstrable misstatements of fact, including false ad hominem statements about Farwell, and impugned Farwell's motives and character. We provide supporting evidence for Farwell's three hypotheses, clarify several issues, correct Meijer et al.'s misstatements of fact, and propose that the progress of science is best served by practicing science: designing and conducting research to test and as necessary modify the proposed hypotheses and standards that explain the existing data.