Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain-computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to "decode" different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

Human object recognition is remarkably efficient. In recent years, significant advancements have been made in our understanding of how the brain represents visual objects and organizes them into categories. Recent studies using pattern analyses methods have characterized a representational space of objects in human and primate inferior temporal cortex in which object exemplars are discriminable and cluster according to category (e.g., faces and bodies). In the present study we examined how category structure in object representations emerges in the first 1000 ms of visual processing. In the study, participants viewed 24 object exemplars with a planned categorical structure comprised of four levels ranging from highly specific (individual exemplars) to highly abstract (animate vs. inanimate), while their brain activity was recorded with magnetoencephalography (MEG). We used a sliding time window decoding approach to decode the exemplar and the exemplar's category that participants were viewing on a moment-to-moment basis. We found exemplar and category membership could be decoded from the neuromagnetic recordings shortly after stimulus onset (<100 ms) with peak decodability following thereafter. Latencies for peak decodability varied systematically with the level of category abstraction with more abstract categories emerging later, indicating that the brain hierarchically constructs category representations. In addition, we examined the stationarity of patterns of activity in the brain that encode object category information and show these patterns vary over time, suggesting the brain might use flexible time varying codes to represent visual object categories.

Increasing evidence suggests that attention can concurrently select multiple locations; yet it is not clear whether this ability relies on continuous allocation of attention to the different targets (a ''parallel'' strategy) or whether attention switches rapidly between the targets (a periodic ''sampling'' strategy). Here, we propose a method to distinguish between these two alternatives. The human psychometric function for detection of a single target as a function of its duration can be used to predict the corresponding function for two or more attended targets. Importantly, the predicted curves differ, depending on whether a parallel or sampling strategy is assumed. For a challenging detection task, we found that human performance was best reflected by a sampling model, indicating that multiple items of interest were processed in series at a rate of approximately seven items per second. Surprisingly, the data suggested that attention operated in this periodic regime, even when it was focused on a single target. That is, attention might rely on an intrinsically periodic process.oscillation ͉ parallel vs. serial S elective attention denotes the ability to enhance processing of a particular location or object. In recent years a number of studies have suggested that multiple locations can be concurrently attended (1-6). In most of these cases, however, it is difficult to distinguish a true (i.e., sustained) division of the attentional spotlight, from a strategy in which a single attentional focus would switch rapidly between the different targets. Indeed, both strategies could explain the occurrence of classic ''set size effects'' (i.e., decreases of performance with increasing number of attended items) either because attention is a limited resource (''parallel'' strategy), or because the effective time that attention samples each object decreases when several objects must be attended (''sampling'' strategy). With respect to visual search tasks, in which a single target must be detected among a variable number of elements, this debate has divided the community for quite some time, with no accepted conclusion [Sternberg S (1973) in Annual Meeting of the Psychonomics Society in St. Louis, MO,. A similarly unresolved argument has been made regarding multiple-object tracking paradigms (15)(16)(17)(18).Here, we propose a quantitative strategy for distinguishing between these alternatives: The psychometric function for detection of a single target as a function of its duration can be used to predict the expected psychometric function for multiple targets, and the predicted shape is quite different for parallel and sequential strategies. We can thus determine which strategy best describes the performance of human observers with multiple attended items. The mathematical details of this method are given in supporting information (SI) Appendix, but the underlying idea can also be understood in simple terms. A ''probe'' event of variable duration must be detected by the observer (Fig. 1). When only a single location is cu...

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The photoelectron spectra of some 40 transition metal compounds have been measured using AlKα(1487 eV) and MgKα(1254 eV) x-rays. The compounds included both simple salts (halides and chalcogenides) and hexacoordinated complexes (cyano- and fluoro-) of Cr(III), Mn(II, III), Fe(II, III), and Co(III). From these data we have determined the chemical shifts of the core electrons and related these results to a calculated charge based on Pauling's electronegativities. In addition, multiplet splitting has been obtained for photoionization in the 3s shell and is discussed in terms of the exchange interaction between the partially filled 3s and 3d orbitals. To help in this explanation, calculations were made using both (1) Hartree-Fock solutions of the wavefunctions for free ions and (2) a qualitative evaluation of the behavior of the exchange integral. The value of using x-ray photoelectron spectroscopy for studying chemical bonding for transition metal compounds is amply illustrated.

Object perception has been a subject of extensive fMRI studies in recent years. Yet the nature of the cortical representation of objects in the human brain remains controversial. Analyses of fMRI data have traditionally focused on the activation of individual voxels associated with presentation of various stimuli. The current analysis approaches functional imaging data as collective information about the stimulus. Linking activity in the brain to a stimulus is treated as a pattern-classification problem. Linear discriminant analysis was used to reanalyze a set of data originally published by Ishai et al. (2000), available from the fMRIDC (accession no. 2-2000-1113D). Results of the new analysis reveal that patterns of activity that distinguish one category of objects from other categories are largely independent of one another, both in terms of the activity and spatial overlap. The information used to detect objects from phase-scrambled control stimuli is not essential in distinguishing one object category from another. Furthermore, performing an object-matching task during the scan significantly improved the ability to predict objects from controls, but had minimal effect on object classification, suggesting that the task-based attentional benefit was non-specific to object categories.

Relative abundances of differently charged ions were measured following the x irradiation of Xe, and, in separate experiments, of Hg. These studies were carried out for a variety of x-ray energies in order to obtain data as a function of the initial inner-shell vacancies. From the data we have derived charge spectra that result from producing an initial vacancy in each of the following shells: the K, L\, Xii,iu, M\, -M"II,III, Miv,v, and N shells of Xe; and the L, M, N, and 0 shells of Hg. These data are correlated with earlier measurements on He, Ne, Ar, and Kr; and empirical rules are set up whereby one may estimate the average charge resulting from the atomic readjustment to a vacancy in any shell of any atom. 42 CARLSON,HUNT, AND KRAUSE