FORTRAN subroutine for an EEG feedback digital filter

A method of constructing digital filters is outlined and illustrated in an application for research uses of EEG feedback. The method is based on least squares estimation with geometric weighting. Old data in the time series are discounted according to age, as new data arrive. Recurrence relations are used, allowing the computations to be performed in real time. A FORTRAN digital filter is formulated that simultaneously estimates (1) the spectral power in a band centered at a target frequency, (2) the total spectral power, and (3) the dominant frequency.     

Wavelet analysis of neuroelectric waveforms: a conceptual tutorial

This paper presents a nontechnical, conceptually oriented introduction to wavelet analysis and its application to neuroelectric waveforms such as the EEG and event related potentials (ERP). Wavelet analysis refers to a growing class of signal processing techniques and transforms that use wavelets and wavelet packets to decompose and manipulate time-varying, nonstationary signals. Neuroelectric waveforms fall into this category of signals because they typically have frequency content that varies as a function of time and recording site. Wavelet techniques can optimize the analysis of such signals by providing excellent joint time-frequency resolution. The ability of wavelet analysis to accurately resolve neuroelectric waveforms into specific time and frequency components leads to several analysis applications. Some of these applications are time-varying filtering for denoising single trial ERPs, EEG spike and spindle detection, ERP component separation and measurement, hearing-threshold estimation via auditory brainstem evoked response measurements, isolation of specific EEG and ERP rhythms, scale-specific topographic analysis, and dense-sensor array data compression. The present tutorial describes the basic concepts of wavelet analysis that underlie these and other applications. In addition, the application of a recently developed method of custom designing Meyer wavelets to match the waveshapes of particular neuroelectric waveforms is illustrated. Matched wavelets are physiologically sensible pattern analyzers for EEG and ERP waveforms and their superior performance is illustrated with real data examples.     

Estimating the spatial Nyquist of the human EEG

The discrete sampling of the brain’s electrical field at the scalp surface with individual recording sensors is subject to the same sampling error as the discrete sampling of the time series at any one sensor with analog-to-digital conversion. Unlike temporal sampling, spatial sampling is intrinsically discrete, so that the post hoc application of analog anti-aliasing filters is not possible. However, the skull acts as a low-pass spatial filter of the brain’s electrical field, attenuating the high spatial frequency information. Because of the skull’s spatial filtering, a discrete sampling of the spatial field with a reasonable number of scalp electrodes is possible. In this paper, we provide theoretical and experimental evidence that adequately sampling the human electroencephalograph (EEG) across the full surface of the head requires a minimum of 128 sensors. Further studies with each of the major EEG and event-related potential phenomena are required in order to determine the spatial frequency of these phenomena and in order to determine whether additional increases in sensor density beyond 128 channels will improve the spatial resolution of the scalp EEG.     

Processing of visual illusions in the frequency and spatial domains

In the results we report here, complex periodic and aperiodic illusions are revealed by filtering with filters containing one or more straight edges. Positive definite filters are used both in the frequency domain and in the space domain to reveal each illusion. Rotating slit and half-plane filters are used in the frequency domain, while processing is done in the spatial domain by convolution with a rotating slit. These two schemes show similar results in revealing the illusory patterns. The implications for human visual processing are discussed.     

Multiresolution Analysis of Event-Related Potentials by Wavelet Decomposition

Wavelet analysis is presented as a new tool for analyzing event-related potentials (ERPs). The wavelet transform expands ERPs into a time-scale representation, which allows the analyst to zoom in on the small scale, fine structure details of an ERP or zoom out to examine the large scale, global waveshape. The timescale representation is closely related to the more familiar time-frequency representation used in spectrograms of time-varying signals. However, time-scale representations have special properties that make them attractive for many ERP applications. In particular, time-scale representations permit theoretically unlimited time resolution for the detection of short-lived peaks and permit a flexible choice of wavelet basis functions for analyzing different types of ERPs. Generally, time-scale representations offer a formal basis for designing new, specialized filters for various ERP applications. Among recently explored applications of wavelet analysis to ERPs are (a) the precise identification of the time of occurrence of overlapping peaks in the auditory brainstem evoked response; (b) the extraction of single-trial ERPs from background EEG noise; (c) the decomposition of averaged ERP waveforms into orthogonal detail functions that isolate the waveforms experimental behavior in distinct, orthogonal frequency bands; and (d) the use of wavelet transform coefficients to concisely extract important information from ERPs that predicts human signal detection performance. In this tutorial we present an intuitive introduction to wavelets and the wavelet transform, concentrating on the multiresolution approach to wavelet analysis of ERP data. We then illustrate this approach with real data. Finally,we offer some speculations on future applications of wavelet analysis to ERP data.     

Asymmetry in visual search for targets defined by differences in movement speed.

Perception of motion speed was investigated with the visual search paradigm, using human Ss. When searching for a fast target among slow distractors, reaction time was minimally affected as the number of distractors was increased. In contrast, reaction time to detect a slow target among fast distractors was slow and linearly related to the number of distractors. The effect cannot be attributed to differences in temporal frequency, discriminability, or one type of representation that might result from spatiotemporal filtering. An alternative hypothesis that can account for the asymmetry is that speed detectors operate as high-pass filters in the velocity domain. This hypothesis is in agreement with results obtained in psychophysical studies on motion adaptation as well as data from single-cell recordings in nonhuman species.     

A digitally controlled universal second-order filter block for biosignals with CMOS D/A converters

A universal second-order low-pass filter block with a digitally adjustable cutoff frequency is described. The filter section replaces conventional manually adjustable low-pass filters and is suitable for a wide range of biosignals such as EEG, EMG, and the recording of evoked potentials (ERPs). The advantages of digital control of filter parameters are briefly outlined and construction hints are given for a number of applications. The universal state-variable filter section may be programmed by any laboratory computer and does not require a complex installation procedure.     

The effect of spatial-frequency filtering on the visual processing of global structure

In three experiments we measured reaction times (RTs) and error rates in identifying the global structure of spatially filtered stimuli whose spatial-frequency content was selected by means of three types of 2-D isotropic filters (Butterworth of order 2, Butterworth of order 10, and a filters with total or partial Gaussian spectral profile). In each experiment, low-pass (LP), bandpass (BP), and high-pass (HP) filtered stimuli, with nine centre or cut-off spatial frequencies, were used. Irrespective of the type of filter, the experimental results showed that: (a) RTs to stimuli with low spatial frequencies were shorter than those to stimuli with medium or high spatial frequencies, (b) RTs to LP filtered stimuli were nearly constant, but they increased in a nonmonotonic way with the filter centre spatial frequency in BP filtered stimuli and with the filter cut-off frequency in HP filtered stimuli, and (c) the identification of the global pattern occurred with all visible stimuli used, including BP and HP images without low spatial frequencies. To remove the possible influence of the energy, a fourth experiment was conducted with Gaussian filtered stimuli of equal contrast power (c(rms) = 0.065). Similar results to those described above were found for stimuli with spatial-frequency content higher than 2 cycles deg(-1). A model of isotropic first-order visual channels collecting the stimulus spectral energy in all orientations explains the RT data. A subsequent second-order nonlinear amplitude demodulation process, applied to the output of the most energetic first-order channel, could explain the perception of global structure of each spatially filtered stimulus, including images lacking low spatial frequencies.     

Digital filtering and signal processing

The design, realization, and some of the many uses of digital filters are reviewed. Computer programs coded in FORTRAN are presented for the design of lumped parameter digital and analog filter systems which are simulated on a digital computer. Explanations of the programs are accompanied by examples of their use. There is a discussion of problems arising from errors of roundoff and approximation.     

A graphical user interface for infant ERP analysis

Recording of event-related potentials (ERPs) is one of the best-suited technologies for examining brain function in human infants. Yet the existing software packages are not optimized for the unique requirements of analyzing artifact-prone ERP data from infants. We developed a new graphical user interface that enables an efficient implementation of a two-stage approach to the analysis of infant ERPs. In the first stage, video records of infant behavior are synchronized with ERPs at the level of individual trials to reject epochs with noncompliant behavior and other artifacts. In the second stage, the interface calls MATLAB and EEGLAB (Delorme & Makeig, Journal of Neuroscience Methods 134(1):9–21, 2004) functions for further preprocessing of the ERP signal itself (i.e., filtering, artifact removal, interpolation, and rereferencing). Finally, methods are included for data visualization and analysis by using bootstrapped group averages. Analyses of simulated and real EEG data demonstrated that the proposed approach can be effectively used to establish task compliance, remove various types of artifacts, and perform representative visualizations and statistical comparisons of ERPs. The interface is available for download from http://www.uta.fi/med/icl/methods/eeg.html in a format that is widely applicable to ERP studies with special populations and open for further editing by users.     

“Parts” of perceived visual forms: New evidence

The Pulfrich effect (the illusory displacement of a moving stimulus when it is viewed with an optical filter over one eye) was measured repeatedly during a 20 min period following the initial filtering of the eye. For each of 10 filter densities, the Pulfrich effect always occurred immediately upon filtering the eye, but subsequently increased greatly during the adaptation period. The results indicate that the perceptual latency of the filtered eye is increased by two factors: the reduction in stimulus luminance due to the filter and progressive dark adaptation. Dark adaptation is apparently the more important of these two factors.     

Surfaces with steep variations in depth pose difficulties for orientationally tuned disparity filters

Surfaces possessing steep variations in depth present severe difficulties for orientationally tuned filter models of stereopsis. These difficulties are discussed in connection with a random-dot stereogram depicting a surface with steep horizontal corrugations. As expected on theoretical grounds, we find that a vertical +/- 45 degrees orientationally filtered version of this stereogram cannot be fused. Moreover, it is demonstrated that a horizontal +/- 45 degrees filtered version can be fused only with difficulty and its stereo percept is poor compared to that of the unfiltered original. It is concluded that orientated filters seem ill-designed to mediate the extraction of disparity cues, at least in the cases under consideration.     

The effects of spatial frequency overlap on face recognition

The effects of spatial frequency overlap between pairs of low-pass versus high-pass images on face recognition and matching were examined in 6 experiments. Overlap was defined as the range of spatial frequencies shared by a pair of filtered images. This factor was manipulated by processing image pairs with high-pass/low-pass filter pairs whose 50% cutoff points varied in their separation from one another. The effects of the center frequency of filter pairs were also investigated. In general, performance improved with greater overlap and higher center frequency. In control conditions, the image pairs were processed with identical filters and thus had complete overlap. Even severely filtered low-pass or high-pass images in these conditions produced superior performance. These results suggest that face recognition is more strongly affected by spatial frequency overlap than by the frequency content of the images.     

The role of low-spatial frequencies in lexical decision and masked priming

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch filtered letter strings. In the unprimed experiments, a filtered target was presented for 105 or 400 ms followed by a pattern mask. Sensitivity (d′) was lowest for the low-pass filtered targets at both durations with a bias towards a ‘non-word’ response. Sensitivity was higher in the high-pass and notch filter conditions. In the priming experiments, a forward mask was followed by a filtered prime then an unfiltered target. Primed words, but not non-words, were identified faster than unprimed words in both the low-pass and high-pass filtered conditions. These results do not support a unique role for low-spatial frequency information in either facilitating or making rapid lexical decisions.     

The use of electrophysiology in the study of early development

Electrophysiology is a timely and important tool in the study of early cognitive development. This commentary polishes the definition of event‐related potential (ERP) components; often interpreted as expressions of mental processes. Further, attention is drawn to time‐frequency analysis of the electroencephalogram (EEG) which conveys much more information than the exclusive use of traditional ERP methodology. Several studies have shown that frequency bands of the EEG undergo systematic development in early childhood. EEG frequency analysis has a potential in early risk assessment. 40 Hz gamma range oscillation bursts accompany stimulus feature binding both in infants and in adults, probably indexing grouping and selection of distributed neuronal populations. Methodological concerns are noted and the need for long‐term normative studies is stressed. Copyright © 2005 John Wiley & Sons, Ltd.     

Application of digital filters in the processing of eye movement data

Digital filter techniques have been applied to the analysis of eye movement data. Methods were developed to calculate eye velocity and eye acceleration in real-time from an electronystag-mogram (ENG) signal that was recorded using a one-pole RC high-pass filter in the preamplifier. Nonrecursive, finite impulse-response digital filters were designed to remove the effects of the RC high-pass filter and calculate the first and second time derivatives of the ENG signal, as well as remove high-frequency noise. Applying these new techniques to the analysis of vestibular nystagmus enables estimation of the transfer characteristics of the vestibuloocular system.     

Localizing cortical sources of event-related potentials in infants' covert orienting

This study used cortical source analysis to locate potential cortical sources of event-related potentials (ERPs) during covert orienting in infants aged 14 and 20 weeks. The infants were tested in a spatial cueing procedure. The reaction time to localize the target showed response facilitation for valid trials relative to invalid or neutral trials. High-density EEG (126 channels) was recorded during the task, and independent component analysis and equivalent current dipole analysis was used to estimate the cortical sources of the EEG during the task. There was a larger P1 ERP component on the valid trials than the other trials (P1 validity effect). The cortical source analysis suggested that this occurred due to activity in Brodmann's areas 18 and 19. A presaccadic ERP component occurred over the frontal scalp areas (-65 ms) and was larger to a target in a cued location than in uncued locations. A potential cortical source for this ERP component was the superior frontal gyrus on the inferior portion of the prefrontal cortex. Increases from 14 to 20 weeks in amplitude of the P1 validity effect and the presaccadic ERP could be modeled by an increase in activation in the corresponding cortical areas.     

基于Think/No-think范式的动机性遗忘研究:行为与脑机制

想/不想范式(Think/No-think,TNT)是基于go/no-go范式提出来的用于研究动机性遗忘过程的实验范式,主要过程是指个体对于记忆的提取抑制可以导致随后该记忆的遗忘。近年来TNT范式的大量行为学研究都一致性地发现记忆提取抑制可以产生负性控制效应,验证了在实验室情境下对动机性遗忘进行研究的可行性。其中,负性控制效应指的是压抑条件的项目相对于基线条件的项目的回忆量有显著降低。关于动机性遗忘发生的神经机制的探讨已积累了大量的研究证据,总结脑电(EEG)和功能核磁共振(f MRI)两个模态的研究,我们提出了动机性遗忘发生的多模态功能网络模型。最后,在该模型的基础上,我们展望了TNT范式未来的研究方向,其中特别注意到同步EEG-f MRI技术的应用有望为我们揭示出记忆提取抑制导致的动机性遗忘发生的动态过程。     

Error analysis of digital filters using HOL theorem proving

When a digital filter is realized with floating-point or fixed-point arithmetics, errors and constraints due to finite word length are unavoidable. In this paper, we show how these errors can be mechanically analysed using the HOL theorem prover. We first model the ideal real filter specification and the corresponding floating-point and fixed-point implementations as predicates in higher-order logic. We use valuation functions to find the real values of the floating-point and fixed-point filter outputs and define the error as the difference between these values and the corresponding output of the ideal real specification. Fundamental analysis lemmas have been established to derive expressions for the accumulation of roundoff error in parametric Lth-order digital filters, for each of the three canonical forms of realization: direct, parallel, and cascade. The HOL formalization and proofs are found to be in a good agreement with existing theoretical paper-and-pencil counterparts.     

FN400和N400是相同的ERP成分：来自图形材料的证据

本研究通过比较记忆编码阶段语义启动引起的N400效应和提取阶段熟悉性引起的FN400效应的地形图考察图形材料诱发的N400和FN400是否是相同的ERP成分。实验结果发现,语义启动引起的N400效应和熟悉性引起的FN400效应的地形图没有显著差异。这说明图形材料诱发的FN400和N400是相同的ERP成分,两者都反映了语义加工。本研究为FN400效应反映了语义启动而不是熟悉性的观点提供了新的实验证据。