Fuzzy-defined entities: A key concept to strengthen forensic science foundations?

According to the Sydney Declaration, "Forensic science is [… an] endeavour to study traces […] through their detection, recognition, recovery, examination and interpretation to understand anomalous events of public interest (e.g., crimes, security incidents)." This science is focused on establishing the nature and relationships among entities related to events having a potential legal impact. Entities can be (groups of) persons, objects, activities and their corresponding sources, events and traces. Although uniqueness of an entity has been traditionally accepted as a principle of forensic science, this paper argues and illustrates that such uniqueness is illusory: Not only can an entity evolve spatially and temporally, but at any specific instant, it differs from itself according to the level of precision at which it is considered. Its characteristics vary based on when, how and by whom it is perceived. We introduce the concept of fuzzy entities - defined to formally include some essential uncertainty or imprecision. The essential impreciseness and subjectivity of an entity gives a new perspective that allows us to revisit Kirk's principle of individuality and to propose to replace it with a new principle of fuzzy unicity. We believe that this new perspective has the potential to strengthen forensic science foundations and bring closer its disciplines, which is an important step towards a harmonized forensic science.

SEEG electrode shaft affects amplitude and latency of potentials evoked with single pulse electrical stimulation.

BACKGROUND: Long and thin shaft electrodes are implanted intracerebrally for stereoelectroencephalography (SEEG) in patients with pharmacoresistant focal epilepsies. Two adjacent contacts of one of such electrodes can deliver a train of single pulse electrical stimulations (SPES), and evoked potentials (EPs) are recorded on other contacts. In this study we assess if stimulating and recording on the same shaft, as opposed to different shafts, has an impact on common EP features. NEW METHOD: We leverage the large volume of SEEG data gathered in the F-TRACT database and analyze data from nearly one thousand SEEG implantations in order to verify whether stimulation and recording from the same shaft influence the EP pattern. RESULTS: We found that when the stimulated and the recording contacts were located on the same shaft, the mean and median amplitudes of an EP are greater, and its mean and median latencies are smaller than when the contacts were located on different shafts. This effect is small (Cohen's d ∼ 0.1), but robust (p-value < 10-3) across the SEEG database. COMPARISON WITH EXISTING METHOD(S): Our study is the first one to address this question. Due to the choice of commonly used EP features, our method is congruent with other studies. CONCLUSIONS: The magnitude of the reported effect does not obligate all standard analyses to correct for it, unless they aim at high precision. The source of the effect is not clear. Manufacturers of SEEG electrodes could examine it and potentially minimize the effect in their future products.

EEG-fMRI in awake rat and whole-brain simulations show decreased brain responsiveness to sensory stimulations during absence seizures.

In patients suffering absence epilepsy, recurring seizures can significantly decrease their quality of life and lead to yet untreatable comorbidities. Absence seizures are characterized by spike-and-wave discharges on the electroencephalogram associated with a transient alteration of consciousness. However, it is still unknown how the brain responds to external stimuli during and outside of seizures. This study aimed to investigate responsiveness to visual and somatosensory stimulation in Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established rat model for absence epilepsy. Animals were imaged under non-curarized awake state using a quiet, zero echo time, functional magnetic resonance imaging (fMRI) sequence. Sensory stimulations were applied during interictal and ictal periods. Whole-brain hemodynamic responses were compared between these two states. Additionally, a mean-field simulation model was used to explain the changes of neural responsiveness to visual stimulation between states. During a seizure, whole-brain responses to both sensory stimulations were suppressed and spatially hindered. In the cortex, hemodynamic responses were negatively polarized during seizures, despite the application of a stimulus. The mean-field simulation revealed restricted propagation of activity due to stimulation and agreed well with fMRI findings. Results suggest that sensory processing is hindered or even suppressed by the occurrence of an absence seizure, potentially contributing to decreased responsiveness during this absence epileptic process.

Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity.

Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.

Dynamic Causal Models and Autopoietic Systems

Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated.