Improvements?

How to improve? 

This section mostly consists of my discussions with Chatgtp on if it where in future possible to imporve lying technqiues and if these ideas have already been tried out/ are possible. 

-> What if we stimulated the hippocampus by either deep TMS or TES and at the same time measured the p300 wave? 

Hippocampus and TMS-TES

The hippocampus is crucial for memory formation, particularly for episodic (event-related) and declarative (fact-based) memories. The cognitive load on the hippocampus increases when someone lies, as you must suppress it. If one stimulated with TMS/TES the hippocampus, one could influence how memories are accessed and manipulated, potentially making it harder for individuals to manage the cognitive burden of lying.

• Deep TMS could target the hippocampus to modulate activity during the lie detection process. Stimulating the hippocampus during questioning could increase cognitive load as it would be harder to manipulate memory. TMS could interfere with the liar's ability to recall details of their fabricated story, making inconsistencies or cognitive difficulties more apparent in behaviour or brain activity.

• TES of the hippocampus could subtly alter neural firing patterns related to memory and attention. If stimulation was made, real memories become more accessible, it could increase the cognitive strain on someone trying to suppress them in favor of lying. If in future a region was located for false memory, TES could also inhibit this area, making it more difficult for the individual to maintain a consistent fabricated narrative. 

The P300 event-related potential (ERP) is a well-known EEG signal that occurs when a person detects something meaningful or surprising. In the context of lie detection the P300 wave often indicates recognition of familiar stimuli or information. The appearance of a P300 wave when presented with truth-related stimuli could reveal that the person recognizes these details but is trying to hide or ignore them. P300 signal could also be enhanced when the individual recognizes information that contradicts their fabricated story.

Combination of TMS/TES and EEG

If the hippocampus is stimulated, it could heighten memory recall or create interference when someone attempts to lie, potentially amplifying the P300 signal. 

This may lead to more detectable differences between lying and truth-telling in the P300 response. EEG P300 can be measured in real-time, allowing immediate feedback on whether someone might be lying. Adding TMS/TES could disrupt the person’s cognitive flow while they are lying, making the detection process more dynamic and responsive.

Challenges

Not everyone’s brain responds the same way to TMS/TES, it is still not known if only a certain region is influenced or how it affects nearby regions or other neural networks. Also, the potential that is applied on TMS depends on the M1 cortex, but we do not know if this is enough to also influence other areas. 

Secondly, P300 patterns depend on the subject. This variability could make it difficult to establish universal thresholds for detecting lies. However, each person has an EEG genetic marker, so it would be possible to identify the subject’s P300 by running some tests forehand. 

Feasibility of Combining EEG and fNIRS  

There are already existing prototypes and research studies where hybrid EEG-fNIRS caps are used. These systems require careful design to avoid interference between the sensors and to ensure proper data collection. Advances in wearable neuroimaging technology, like lightweight and flexible sensors, have made this increasingly practical. Combining EEG and fNIRS for lie detection is theoretically promising because:  

1. EEG detects neural activity linked to recognition or decision-making, such as the P300 wave, which can indicate familiarity with stimuli.  

2. fNIRS monitors hemodynamic responses, like those associated with cognitive load and stress, which may vary during deception.  

Challenges  

- Signal Integration: Combining two types of data (electrical and hemodynamic) is computationally complex and requires advanced algorithms.  

- Artifacts: Both EEG and fNIRS are sensitive to motion, and overlapping artifacts can complicate analysis.