scholarly journals Weakly Modulated Spike Trains: Significance, Precision, and Correction for Sample Size

2002 ◽  
Vol 87 (5) ◽  
pp. 2542-2554 ◽  
Author(s):  
Chou P. Hung ◽  
Benjamin M. Ramsden ◽  
Anna Wang Roe
Keyword(s):  
Single Unit ◽  
Statistical Tests ◽  
Strong Dependence ◽  
Spike Trains ◽  
Correction Function ◽  
Natural Scenes ◽  
Electrophysiological Studies ◽  
Spike Number ◽  
Areas 17 And 18 ◽  
Using Data

Many single-unit electrophysiological studies of visual cortex have investigated strong evoked responses to simple stimuli such as oriented gratings. Experiments involving other types of stimuli, such as natural scenes, higher-order features, and surface brightness, produce single-unit responses that are more difficult to interpret. Experiments with brightness, in particular, evoke single-unit responses that are typically weakly modulated. When the brightness is generated by a visual illusion such as the Cornsweet illusion, statistical tests are often necessary to distinguish true responses from baseline fluctuations. Here, using data collected from cat Areas 17 and 18 in response to real and illusory brightness stimuli, we provide a method for detecting and quantifying weak but significant periodic responses. By randomizing spike trains (via bootstrap methods), we provide confidence levels for response significance, permitting the evaluation of both weak and strong responses. We show that because of a strong dependence on total spike number, response significance can only be appropriately determined with randomized spike trains of similar spike number. Such randomizations can be performed for both stimulus-elicited and spontaneously occurring spike trains. By developing a method for generating randomized modulated spike trains (phase-restricted randomization) from actual recordings, we calculate upper and lower confidence limits of modulated spike trains and describe how measurement precision varies as a function of total spike count. Finally, using this randomization method, we describe how a correction function can be determined to correct for measurement bias introduced at low spike counts. These methods may also be useful in the study of small but potentially significant responses in other systems.

scholarly journals Parametric Assessment of Trend Test Power in a Changing Environment

2020 ◽  
Vol 12 (9) ◽  
pp. 3889
Author(s):  
Andrea Gioia ◽  
Maria Francesca Bruno ◽  
Vincenzo Totaro ◽  
Vito Iacobellis
Keyword(s):  
Statistical Tests ◽  
Statistical Significance ◽  
Strong Dependence ◽  
Generalized Extreme Value Distribution ◽  
Monte Carlo Experiment ◽  
Data Series ◽  
Test Power ◽  
Special Cases ◽  
Wide Range ◽  
Position Parameter

In the context of climate and environmental change assessment, the use of probabilistic models in which the parameters of a given distribution may vary in accordance with time has reinforced the need for appropriate procedures to recognize the “statistical significance” of trends in data series arising from stochastic processes. This paper introduces a parametric methodology, which exploits a measure based on the Akaike Information Criterion (AICΔ), and a Rescaled version of the Generalized Extreme Value distribution, in which a linear deterministic trend in the position parameter is accounted for. A Monte Carlo experiment was set up with the generation of nonstationary synthetic series characterized by different sample lengths and covering a wide range of the shape and scale parameters. The performances of statistical tests based on the parametric AICΔ and the non-parametric Mann-Kendall measures were evaluated and compared with reference to observed ranges of annual maxima of precipitation, peak flow, and wind speed. Results allow for sensitivity analysis of the test power and show a strong dependence on the trend coefficient and the L-Coefficient of Variation of the parent distribution from the upper-bounded to the heavy-tailed special cases. An analysis of the sample variability of the position parameter is also presented, based on the same generation sets.

scholarly journals NotchPUF: Printed Circuit Board PUF Based on Microstrip Notch Filter

Cryptography ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 11
Author(s):  
Mitchell Martin ◽  
Jim Plusquellic
Keyword(s):  
Printed Circuit Boards ◽  
Printed Circuit Board ◽  
Statistical Tests ◽  
Notch Filter ◽  
Circuit Board ◽  
Circuit Boards ◽  
Printed Circuit ◽  
In Series ◽  
Commercial Off The Shelf ◽  
Using Data

Physical Unclonable Functions (PUFs) are primitives that are designed to leverage naturally occurring variations to produce a random bitstring. Current PUF designs are typically implemented in silicon or utilize variations found in commercial off-the-shelf (COTS) parts. Because of this, existing designs are insufficient for the authentication of Printed Circuit Boards (PCBs). In this paper, we propose a novel PUF design that leverages board variations in a manufactured PCB to generate unique and stable IDs for each PCB. In particular, a single copper trace is used as a source of randomness for bitstring generation. The trace connects three notch filter structures in series, each of which is designed to reject specific but separate frequencies. The bitstrings generated using data measured from a set of PCBs are analyzed using statistical tests to illustrate that high levels of uniqueness and randomness are achievable.

scholarly journals Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē–Atbara river basin, Ethiopia

2017 ◽  
Vol 21 (4) ◽  
pp. 2127-2142 ◽  
Author(s):  
Tesfay G. Gebremicael ◽  
Yasir A. Mohamed ◽  
Pieter v. Zaag ◽  
Eyasu Y. Hagos
Keyword(s):  
Change Point ◽  
Statistical Tests ◽  
Catchment Management ◽  
Trend Analyses ◽  
Temporal And Spatial Variability ◽  
Spatial Changes ◽  
Changing Patterns ◽  
Temporal And Spatial ◽  
Using Data ◽  
Streamflow Trends

Abstract. The Upper Tekezē–Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann–Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.

Improvements to the Sensitivity of Gravitational Clustering for Multiple Neuron Recordings

2000 ◽  
Vol 12 (11) ◽  
pp. 2597-2620 ◽  
Author(s):  
Stuart N. Baker ◽  
George L. Gerstein
Keyword(s):  
Interspike Interval ◽  
Simulation Method ◽  
Spike Trains ◽  
The Novel ◽  
Limited Data ◽  
Neuronal Synchrony ◽  
Gravitational Clustering ◽  
Using Data ◽  
Interspike Interval Distribution ◽  
Interval Distribution

We outline two improvements to the technique of gravitational clustering for detection of neuronal synchrony, which are capable of improving the method's detection of weak synchrony with limited data. The advantages of the enhancements are illustrated using data with known levels of synchrony and different interspike interval distributions. The novel simulation method described can easily generate such test data. An important dependence of the sensitivity of gravitational clustering to the interspike interval distribution of the analysed spike trains is described.

Statistical power to detect main and interactive effects on the attributes of small-mammal populations

1999 ◽  
Vol 77 (1) ◽  
pp. 68-73 ◽  
Author(s):  
Eric M Schauber ◽  
W Daniel Edge
Keyword(s):  
Statistical Power ◽  
Statistical Tests ◽  
Interactive Effects ◽  
Natural Systems ◽  
Real Effects ◽  
Treatment Variation ◽  
Higher Power ◽  
Using Data ◽  
Main Effects ◽  
Response Variables

Statistical power is an important consideration in the design of experiments, because resources invested in an experiment may be wasted if it is unlikely to produce statistically significant results when real effects or differences exist. Using data from toxicological experiments on seminatural populations of small mammals, we examined the power of statistical tests for main and interactive effects. Our objectives were to evaluate the efficacy of actively reducing within-treatment variation in order to increase power and compare the power provided by several response variables commonly measured in population studies. Controlling population size (N) before treatment increased power to detect effects on N but decreased power to detect effects on population growth (r). For a specified reduction in N, r provided higher power than N. Fractional measures of recruitment generally provided low power, especially when N was low (<20 animals). Power to detect an interaction of two adverse treatments depended on the magnitudes of their main effects, as well as the magnitude of interactive effects. Estimating or predicting effect size is more complex and difficult for interactive effects than for main effects. We conclude that researchers can increase the probability of detecting real effects by choosing response variables with relatively low inherent variability. However, efforts to actively reduce within-treatment variation may have unanticipated repercussions in natural systems.

scholarly journals Phylogeny in Phonology: How Tai Sound Systems Encode Their Past

2018 ◽  
Vol 5 ◽  
Author(s):  
Rikker Dockum
Keyword(s):  
Transition Probabilities ◽  
Phylogenetic Signal ◽  
Statistical Tests ◽  
Genetic Relationships ◽  
Comparative Method ◽  
Coarse Grained ◽  
History Of ◽  
Using Data ◽  
Computational Phylogenetics ◽  
Delta Score

The study of sound change is foundational to traditional historical linguistics, particularly the linguistic comparative method. It is well established that the phonology of modern languages encodes useful data for studying the history of those languages, and their genetic relationships to one another. However, phonology has typically been the means to the end, enabling the comparative method, and coding of a comparative lexicon for cognacy. Once coded, the particular sounds involved no longer factor into the analysis. This study examines whether the phoneme inventories and phonotactic profiles of a set of languages themselves contain phylogenetic signal detectable using established statistical tests D statistic (Fritz & Purvis 2010), K (Blomberg et al 2003), and NeighborNet delta score (Holland et al 2002) and Q-residual (Gray et al 2010). This study adds to the growing body of work on the use of phonological traits in computational phylogenetics for linguistics. Using data from 20 Tai lects from the Kra-Dai language family, this study confirms and extends previous findings. This includes detection of strong phylogenetic signal in phoneme frequency and biphone transition probabilities, but also relatively strong phylogenetic signal detected in even coarse-grained phoneme and biphone presence/absence, which previous work was unable to do.

scholarly journals CRITERION FOR COMPARING THE VARIANCE COMPONENT ESTIMATION METHODS USED FOR ADJUSTING HORIZONTAL CONTROL NETWORKS

2012 ◽  
Vol 32 (1) ◽  
pp. 6-13
Author(s):  
Erol Yavuz ◽  
Orhan Baykal
Keyword(s):  
Stochastic Model ◽  
Variance Component ◽  
Statistical Tests ◽  
Estimation Methods ◽  
Variance Component Estimation ◽  
Control Networks ◽  
Component Estimation ◽  
Using Data ◽  
Horizontal Control

Determination of which stochastic model taken in hand for this study is suitable under conditions, when comparing stochastic models, used for adjusting horizontal control networks, is the aim of this study. Some well-known variance component estimation methods like Conventional, Helmert, MTNQUE, AUE, and Förstner, which have been developed to determine the stochastic model, necessary to be formed in a real way for adjusting geodetic nets, have been compared. For comparing the models mentioned above, concrete deciding criteria, using statistical tests, have been defined and the determination of which model is superior has been studied. For comparison of the models, numerical experiment using data, which belong to the part of Istanbul Metropolitan Triangulation Network (Asiatic side of Istanbul), has been performed.

scholarly journals An Analysis of IHC and HCII Publication Titles: Revealing and Comparing the Topics of Interest of their Communities

2021 ◽  
Vol 12 (1) ◽  
pp. 1-20
Author(s):  
Franklin M. da C. Lima ◽  
Gabriel A. M. Vasiljevic ◽  
Leonardo Cunha De Miranda ◽  
M. Cecília C. Baranauskas
Keyword(s):  
Correlation Analysis ◽  
Human Computer Interaction ◽  
Human Factors ◽  
Statistical Tests ◽  
Research Field ◽  
Academic Community ◽  
Computing Systems ◽  
Significant Difference ◽  
Using Data ◽  
Computer Interaction

Analyzing how the conferences of a given research field are evolving contributes to the academic community in that the researchers can better situate their research towards the advancement of knowledge in their area of expertise. Thus, in this work we present the results of a correlation analysis performed within and between-conferences of the field of Human-Computer Interaction, using data from the conference on Human-Computer Interaction International (HCII) and from the Brazilian Symposium on Human Factors in Computing Systems (IHC). More than 209 thousand words from the titles of over 18 thousand publications from both conferences were analyzed in total, using different quantitative, qualitative and visualization methods, including statistical tests. The analysis of words from the tiles of publications from both conferences and the comparison of the ranking of these words indicate, amongst other results, that there is a significant difference in relation to the main and most covered topics for each one of these conferences. 

scholarly journals A decisional space account of saccadic reaction times towards personally familiar faces

2018 ◽  
Author(s):  
Meike Ramon ◽  
Nayla Sokhn ◽  
Roberto Caldara
Keyword(s):  
Visual Processing ◽  
Reaction Times ◽  
Task Demands ◽  
Natural Scenes ◽  
Familiar Face ◽  
Processing Times ◽  
Electrophysiological Studies ◽  
Neurological Patients ◽  
Saccadic Reaction Times ◽  
Time Required

AbstractManual and saccadic reaction times (SRTs) have been used to determine the minimum time required for different types of visual categorizations. Such studies have demonstrated that faces can be detected within natural scenes within as little as 100ms (Crouzet, Kirchner & Thorpe, 2010), while increasingly complex decisions require longer processing times (Besson, Barragan-Jason, Thorpe, Fabre-Thorpe, Puma et al., 2017). Following the notion that facial representations stored in memory facilitate perceptual processing (Ramon & Gobbini, 2018), a recent study reported 180ms as the fastest speed at which “familiar face detection” based on expressed choice saccades (Visconti di Ollegio Castello & Gobbini, 2015). At first glance, these findings seem incompatible with the earliest neural markers of familiarity reported in electrophysiological studies (Barragan-Jason, Cauchoix & Barbeau, 2015; Caharel, Ramon & Rossion, 2014; Huang, Wu, Hu, Wang, Ding & Qu et al., 2017), which should temporally precede any overtly observed behavioral (oculomotor or manual) categorization. Here, we reason that this apparent discrepancy could be accounted for in terms of decisional space constraints, which modulate both manual RTs observed for different levels of visual processing (Besson et al., 2017), as well as saccadic RTs (SRTs) in both healthy observers and neurological patients (Ramon, in press; Ramon, Sokhn, Lao & Caldara, in press). In the present study, over 70 observers completed three different SRT experiments in which decisional space was manipulated through task demands and stimulus probability. Subjects performed a gender categorization task, or one of two familiar face “recognition” tasks, which differed with respect to the number of personally familiar identities presented (3 vs. 7). We observe an inverse relationship between visual categorization proficiency and decisional space. Observers were most accurate for categorization of gender, which could be achieved in as little as 140ms. Categorization of highly predictable targets was more error-prone and required an additional ~100ms processing time. Our findings add to increasing evidence that pre-activation of identity-information can modulate early visual processing in a top-down manner. They also emphasize the importance of considering procedural aspects as well as terminology when aiming to characterize cognitive processes.

Adjustment of Medical Observations Influenced by Emotional State

2018 ◽  
Vol 9 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Firas Zekri ◽  
Afef Samet Ellouze ◽  
Rafik Bouaziz
Keyword(s):  
Decision Support ◽  
Fuzzy Systems ◽  
Emotional State ◽  
Strong Dependence ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Medical Decision ◽  
Medical Decision Support ◽  
Medical Observation ◽  
Using Data

Research in neurophysiology and neuropsychology have established a strong dependence between emotion, subjectivity and decision-making. Otherwise, medical observations are used as one of the main inputs of clinical decision support systems (CDSS) which are designed to support patients with chronic progressive diseases. However, these observations are influenced when confronted with a critical emotional state and they are likely to be subjective. To generate efficient results, CDSS must bring these subjective observations closer to the reality by using data describing the observer's emotional state. To solve this issue, the authors of this article propose to identify the dependency relationship between observations and emotions. Then they provide a solution that moderates the patient and caregivers' observations within a medical decision support system, so that it can generate efficient results. Finally, they propose two fuzzy systems to adjust the influence of emotional state on medical observation. These two systems make the medical observation closer to the current condition of the patient.

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