Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A cognitive fingerprint in human random number generation.

ABSTRACT: Is the cognitive process of random number generation implemented via person-specific strategies corresponding to highly individual random generation behaviour? We examined random number sequences of 115 healthy participants and developed a method to quantify the similarity between two number sequences on the basis of Damerau and Levenshtein's edit distance. "Same-author" and "different author" sequence pairs could be distinguished (96.5% AUC) based on 300 pseudo-random digits alone. We show that this phenomenon is driven by individual preference and inhibition of patterns and stays constant over a period of 1 week, forming a cognitive fingerprint.

SUBMITTER: Schulz MA

PROVIDER: S-EPMC8511021 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A cognitive fingerprint in human random number generation.

Schulz Marc-André MA Baier Sebastian S Timmermann Benjamin B Bzdok Danilo D Witt Karsten K

Scientific reports 20211012 1

Is the cognitive process of random number generation implemented via person-specific strategies corresponding to highly individual random generation behaviour? We examined random number sequences of 115 healthy participants and developed a method to quantify the similarity between two number sequences on the basis of Damerau and Levenshtein's edit distance. "Same-author" and "different author" sequence pairs could be distinguished (96.5% AUC) based on 300 pseudo-random digits alone. We show that ...[more]

PMID: 34642344

Similar Datasets

DNA synthesis for true random number generation.

Project description:The volume of securely encrypted data transmission required by today's network complexity of people, transactions and interactions increases continuously. To guarantee security of encryption and decryption schemes for exchanging sensitive information, large volumes of true random numbers are required. Here we present a method to exploit the stochastic nature of chemistry by synthesizing DNA strands composed of random nucleotides. We compare three commercial random DNA syntheses giving a measure for robustness and synthesis distribution of nucleotides and show that using DNA for random number generation, we can obtain 7 million GB of randomness from one synthesis run, which can be read out using state-of-the-art sequencing technologies at rates of ca. 300 kB/s. Using the von Neumann algorithm for data compression, we remove bias introduced from human or technological sources and assess randomness using NIST's statistical test suite.

| S-EPMC7675991 | biostudies-literature

One-sided device-independent random number generation through fiber channels.

Project description:Randomness is an essential resource and plays important roles in various applications ranging from cryptography to simulation of complex systems. Certified randomness from quantum process is ensured to have the element of privacy but usually relies on the device's behavior. To certify randomness without the characterization for device, it is crucial to realize the one-sided device-independent random number generation based on quantum steering, which guarantees security of randomness and relaxes the demands of one party's device. Here, we distribute quantum steering between two distant users through a 2 km fiber channel and generate quantum random numbers at the remote station with untrustworthy device. We certify the steering-based randomness by reconstructing covariance matrix of the Gaussian entangled state shared between distant parties. Then, the quantum random numbers with a generation rate of 7.06 Mbits/s are extracted from the measured amplitude quadrature fluctuation of the state owned by the remote party. Our results demonstrate the first realization of steering-based random numbers extraction in a practical fiber channel, which paves the way to the quantum random numbers generation in asymmetric networks.

| S-EPMC11696713 | biostudies-literature

On speeding up stochastic simulations by parallelization of random number generation.

Project description:This paper adds to the tool kit of stochastic simulations based on a very simple idea. Applicable to both SSA and Tau-leap algorithms, it can notably reduce computational times. Stochastic simulations are based on computing sample paths based on the generation of random numbers with either exactly stipulated distribution functions as in SSA (Gillespie, 1977) or in the method of interval of quiescence (Shah et al., 1977) or distribution functions featuring approximations designed to promote efficiency (as in Tau-leap algorithms (Cao et al., 2006; Tian and Burrage, 2004; Peng et al., 2007; Gillespie, 2001; Ramkrishna et al., 2014) where a leap condition with the parameter epsilon is used). The usual strategy involves sequential computation of a large number of sample paths over a bounded time interval which is covered by a set of discrete time subintervals obtained by random number generation. The strategy here departs from the foregoing by parallelizing the generation of random subintervals for the set of sample paths until all sample paths have been computed for the stated time interval. The advantage of this procedure lies in the fact that the time for initiation of the random number generator has been notably reduced. Many examples are demonstrated from SSA as well as Tau-leap algorithms to establish that the advantage of the approach is much more than conceptual.

| S-EPMC4562036 | biostudies-literature

Chaotic microlasers caused by internal mode interaction for random number generation.

Project description:Chaotic semiconductor lasers have been widely investigated for generating unpredictable random numbers, especially for lasers with external optical feedback. Nevertheless, chaotic lasers under external feedback are hindered by external feedback loop time, which causes correlation peaks for chaotic output. Here, we demonstrate the first self-chaotic microlaser based on internal mode interaction for a dual-mode microcavity laser, and realize random number generation using the self-chaotic laser output. By adjusting mode frequency interval close to the intrinsic relaxation oscillation frequency, nonlinear dynamics including self-chaos and period-oscillations are predicted and realized numerically and experimentally due to internal mode interaction. The internal mode interaction and corresponding carrier spatial oscillations pave the way of mode engineering for nonlinear dynamics in a solitary laser. Our findings provide a novel and easy method to create controllable and robust optical chaos for high-speed random number generation.

| S-EPMC9209477 | biostudies-literature

Multi-bit quantum random number generation from a single qubit quantum walk.

Project description:We present a scheme for multi-bit quantum random number generation using a single qubit discrete-time quantum walk in one-dimensional space. Irrespective of the initial state of the qubit, quantum interference and entanglement of particle with the position space in the walk dynamics certifies high randomness in the system. Quantum walk in a position space of dimension 2l + 1 ensures string of (l + 2)-bits of random numbers from a single measurement. Bit commitment with the position space and control over the spread of the probability distribution in position space enable us with options to extract multi-bit random numbers. This highlights the power of one qubit, its practical importance in generating multi-bit string in single measurement and the role it can play in quantum communication and cryptographic protocols. This can be further extended with quantum walks in higher dimensions.

| S-EPMC6707389 | biostudies-literature

On multiplexing in physical random number generation, and conserved total entropy content.

Project description:In the current article, we use a random supercontinuum based on a random Raman distributed feedback laser to investigate the generation of random numbers by spectrally demultiplexing the broad supercontinuum spectrum in parallel channels. By tuning the spectral separation between two independent channels, we test the most typically used statistical tests' abilities to identify the required minimum spectral separation between channels, especially after the use of post-processing steps. Out of all the tests that were investigated, the cross-correlation across channels using the raw data appears to be the most robust. We also demonstrate that the use of post-processing steps, either least significant bits extraction or exclusive-OR operations, hinders the ability of these tests to detect the existing correlations. As such, performing these tests on post-processed data, often reported in literature, is insufficient to properly establish the independence of two parallel channels. We therefore present a methodology, which may be used to confirm the true randomness of parallel random number generation schemes. Finally, we demonstrate that, while tuning a single channel's bandwidth can modify its potential randomness output, it also affects the number of available channels, such that the total random number generation bitrate is conserved.

| S-EPMC10188537 | biostudies-literature

Chaotic oscillation and random-number generation based on nanoscale optical-energy transfer.

Project description:By using nanoscale energy-transfer dynamics and density matrix formalism, we demonstrate theoretically and numerically that chaotic oscillation and random-number generation occur in a nanoscale system. The physical system consists of a pair of quantum dots (QDs), with one QD smaller than the other, between which energy transfers via optical near-field interactions. When the system is pumped by continuous-wave radiation and incorporates a timing delay between two energy transfers within the system, it emits optical pulses. We refer to such QD pairs as nano-optical pulsers (NOPs). Irradiating an NOP with external periodic optical pulses causes the oscillating frequency of the NOP to synchronize with the external stimulus. We find that chaotic oscillation occurs in the NOP population when they are connected by an external time delay. Moreover, by evaluating the time-domain signals by statistical-test suites, we confirm that the signals are sufficiently random to qualify the system as a random-number generator (RNG). This study reveals that even relatively simple nanodevices that interact locally with each other through optical energy transfer at scales far below the wavelength of irradiating light can exhibit complex oscillatory dynamics. These findings are significant for applications such as ultrasmall RNGs.

| S-EPMC4129418 | biostudies-literature

RandseqR: An R Package for Describing Performance on the Random Number Generation Task.

Project description:The Random Number Generation (RNG) task has a long history in neuropsychology as an assessment procedure for executive functioning. In recent years, understanding of human (executive) behavior has gradually changed from reflecting a static to a dynamic process and this shift in thinking about behavior gives a new angle to interpret test results. However, this shift also asks for different methods to process random number sequences. The RNG task is suited for applying non-linear methods needed to uncover the underlying dynamics of random number generation. In the current article we present RandseqR: an R-package that combines the calculation of classic randomization measures and Recurrence Quantification Analysis. RandseqR is an easy to use, flexible and fast way to process random number sequences and readies the RNG task for current scientific and clinical use.

| S-EPMC8129161 | biostudies-literature

An architecturally constrained model of random number generation and its application to modeling the effect of generation rate.

Project description:Random number generation (RNG) is a complex cognitive task for human subjects, requiring deliberative control to avoid production of habitual, stereotyped sequences. Under various manipulations (e.g., speeded responding, transcranial magnetic stimulation, or neurological damage) the performance of human subjects deteriorates, as reflected in a number of qualitatively distinct, dissociable biases. For example, the intrusion of stereotyped behavior (e.g., counting) increases at faster rates of generation. Theoretical accounts of the task postulate that it requires the integrated operation of multiple, computationally heterogeneous cognitive control ("executive") processes. We present a computational model of RNG, within the framework of a novel, neuropsychologically-inspired cognitive architecture, ESPro. Manipulating the rate of sequence generation in the model reproduced a number of key effects observed in empirical studies, including increasing sequence stereotypy at faster rates. Within the model, this was due to time limitations on the interaction of supervisory control processes, namely, task setting, proposal of responses, monitoring, and response inhibition. The model thus supports the fractionation of executive function into multiple, computationally heterogeneous processes.

| S-EPMC4076660 | biostudies-literature

Harnessing Physical Entropy Noise in Structurally Metastable 1T' Molybdenum Ditelluride for True Random Number Generation.

Project description:True random numbers are crucial for various research and engineering problems. Their generation depends upon a robust physical entropy noise. Here, we present true random number generation from the conductance noise probed in structurally metastable 1T' molybdenum ditelluride (MoTe2). The noise, fitting a Poisson process, is proved to be a robust physical entropy noise at low and even cryogenic temperatures. Noise characteristic analyses suggest the noise may originate from the polarization variations of the underlying ferroelectric dipoles in 1T' MoTe2. We demonstrate the noise allows for true random number generation, and this facilitates their use as the seed for generating high-throughput secure random numbers exceeding 1 Mbit/s, appealing for practical applications in, for instance, cryptography where data security is now critical. As an example, we show biometric information safeguarding in neural networks by using the random numbers as the mask, proving a promising data security measure in big data and artificial intelligence.

| S-EPMC11565741 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data