The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns.DFG, GRK 1589, Verarbeitung sensorischer Informationen in neuronalen SystemenBMBF, 01GQ1006, Modulation von Bewertungsprozessen beim menschlichen Entscheidungsverhalten: ein neurocomputationaler Ansat

Working memory signals in early visual cortex are present in weak and strong imagers

It has been suggested that visual images are memorized across brief periods of time by vividly imagining them as if they were still there. In line with this, the contents of both working memory and visual imagery are known to be encoded already in early visual cortex. If these signals in early visual areas were indeed to reflect a combined imagery and memory code, one would predict them to be weaker for individuals with reduced visual imagery vividness. Here, we systematically investigated this question in two groups of participants. Strong and weak imagers were asked to remember images across brief delay periods. We were able to reliably reconstruct the memorized stimuli from early visual cortex during the delay. Importantly, in contrast to the prediction, the quality of reconstruction was equally accurate for both strong and weak imagers. The decodable information also closely reflected behavioral precision in both groups, suggesting it could contribute to behavioral performance, even in the extreme case of completely aphantasic individuals. Our data thus suggest that working memory signals in early visual cortex can be present even in the (near) absence of phenomenal imagery.Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Max‐Planck‐Gesellschaft http://dx.doi.org/10.13039/501100004189Peer Reviewe

Valid population inference for information-based imaging: From the second-level t-test to prevalence inference

In multivariate pattern analysis of neuroimaging data, ‘second-level’ inference is often performed by entering classification accuracies into a t-test vs chance level across subjects. We argue that while the random-effects analysis implemented by the t-test does provide population inference if applied to activation differences, it fails to do so in the case of classification accuracy or other ‘information-like’ measures, because the true value of such measures can never be below chance level. This constraint changes the meaning of the population-level null hypothesis being tested, which becomes equivalent to the global null hypothesis that there is no effect in any subject in the population. Consequently, rejecting it only allows to infer that there are some subjects in which there is an information effect, but not that it generalizes, rendering it effectively equivalent to fixed-effects analysis. This statement is supported by theoretical arguments as well as simulations. We review possible alternative approaches to population inference for information-based imaging, converging on the idea that it should not target the mean, but the prevalence of the effect in the population. One method to do so, ‘permutation-based information prevalence inference using the minimum statistic’, is described in detail and applied to empirical data

On Rules and Methods: Neural Representations of Complex Rule Sets and Related Methodological Contributions

Wo und wie werden komplexe Regelsätze im Gehirn repräsentiert? Drei empirische Studien dieser Doktorarbeit untersuchen dies experimentell. Eine weitere methodische Studie liefert Beiträge zur Weiterentwicklung der genutzten empirischen Methode. Die empirischen Studien nutzen multivariate Musteranalyse (MVPA) funktioneller Magnetresonanzdaten (fMRT) gesunder Probanden. Die Fragestellungen der methodischen Studie wurden durch die empirischen Arbeiten inspiriert. Wirkung und Anwendungsbreite der entwickelten Methode gehen jedoch über die Anwendung in den empirischen Studien dieser Arbeit hinaus. Die empirischen Studien bearbeiten Fragen wie: Wo werden Hinweisreize und Regeln repräsentiert, und sind deren Repräsentationen voneinander unabhängig? Wo werden Regeln repräsentiert, die aus mehreren Einzelregeln bestehen, und sind Repräsentationen der zusammengesetzten Regeln Kombinationen der Repräsentationen der Einzelregeln? Wo sind Regeln verschiedener Hierarchieebenen repräsentiert, und gibt es einen hierarchieabhängigen Gradienten im ventrolateralen präfrontalen Kortex (VLPFK)? Wo wird die Reihenfolge der Regelausführung repräsentiert? Alle empirischen Studien verwenden informationsbasiertes funktionales Mapping ("Searchlight"-Ansatz), zur hirnweiten und räumlich Lokalisierung von Repräsentationen verschiedener Elemente komplexer Regelsätze. Kernergebnisse der Arbeit beinhalten: Kompositionalität neuronaler Regelrepräsentationen im VLPFK; keine Evidenz für Regelreihenfolgenrepräsentation im VLPFK, welches gegen VLPFK als generelle Task-Set-Kontrollregion spricht; kein Hinweis auf einen hierarchieabhängigen Gradienten im VLPFK. Die komplementierende methodische Studie präsentiert "The Same Analysis Approach (SAA)", ein Ansatz zur Erkennung und Behebung experimentspezifischer Fehler, besonders solcher, die aus Design–Analyse–Interaktionen entstehen. SAA ist für relevant MVPA, aber auch für anderen Bereichen innerhalb und außerhalb der Neurowissenschaften.Where and how does the brain represent complex rule sets? This thesis presents a series of three empirical studies that decompose representations of complex rule sets to directly address this question. An additional methodological study investigates the employed analysis method and the experimental design. The empirical studies employ multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data from healthy human participants. The methodological study has been inspired by the empirical work. Its impact and application range, however, extend well beyond the empirical studies of this thesis. Questions of the empirical studies (Studies 1-3) include: Where are cues and rules represented, and are these represented independently? Where are compound rules (rules consisting of multiple rules) represented, and are these composed from their single rule representations? Where are rules from different hierarchical levels represented, and is there a hierarchy-dependent functional gradient along ventro-lateral prefrontal cortex (VLPFC)? Where is the order of rule-execution represented, and is it represented as a separate higher-level rule? All empirical studies employ information-based functional mapping ("searchlight" approach) to localise representations of rule set features brain-wide and spatially unbiased. Key findings include: compositional coding of compound rules in VLPFC; no order information in VLPFC, suggesting VLPFC is not a general controller for task set; evidence against the hypothesis of a hierarchy-dependent functional gradient along VLPFC. The methodological study (Study 4) introduces "The Same Analysis Approach (SAA)". SAA allows to detect, avoid, and eliminate confounds and other errors in experimental design and analysis, especially mistakes caused by malicious experiment-specific design-analysis interactions. SAA is relevant for MVPA, but can also be applied in other fields, both within and outside of neuroscience

Kathodolumineszenz (KL) von Schwermineralen

Im Rahmen von vier Fallstudien wurde der Zusammenhang zwischen dem Kathodolumineszenz-Verhalten von Schwermineralen, insbesondere von Zirkon, Disthen, Apatit, und ihrem KL-aktivierungsrelevanten Spurenelementgehalt untersucht. Zunächst wurden Grundtypen und Variationsbreiten erarbeitet, die im Falle von Disthen und Zirkon durch PIXE-Messungen unterstützt wurden. Für Apatit ließen sich, basierend auf den KL-Farben fünf Haupttypen definieren, die sich in zwei bis drei Subtypen aufteilen lassen. Basierend auf den Lumineszenzfarben ließen sich für Disthen vier Haupttypen sowie zwei bis drei Subtypen für eine Unterscheidung heranziehen, wobei in den Subtypen die Verteilung der KL-Farben ausschlaggebend ist. Eine ähnliche Typisierung ließ sich auch für Zirkone aufstellen. Sie läßt sich in fünf Haupttypen aufteilen, wobei eine weitere Unterteilung in zwei bis drei Subtypen möglich wird, die sich nach der Verteilung von hellen und dunklen Bereichen richtet. Die Häufigkeitsverteilungen der Lumineszenzfarben innerhalb einer Probe können sich nutzen lassen, um Rückschlüsse auf den Chemismus des ursprünglichen Ausgangsgesteins zu gewinnen

Multiple imputation using ICE: A simulation study on a binary response

Background: Various methods for multiple imputations of missing values are available in statistical software. They have been shown to work well when small proportions of missings were to be imputed. However, some researchers have started to impute large proportions of missings. Method: We performed a simulation using ICE on datasets of 50/100/200/400 cases and 4/11/25 variables. A varying proportion of data (3–63%) were randomly set missing and subsequently substituted by multiple imputation. Results: (1) It is shown when and how the algorithm breaks down by decreasing n of cases and increasing number of variables in the model. (2) Some unexpected results are demonstrated, e.g. flawed coefficients. (3) Compared to the second program that performs multiple imputations by chained equations, i.e., mice in R, the Stata program, ice, results in a slightly higher precision of the estimates by similar features of the program. Conclusion: The imputation of missings by chained equations is a useful tool for imputing small to moderate proportions of missings. The replacement of larger amounts, however, can be critical.

Neural Representations of Hierarchical Rule Sets: The Human Control System Represents Rules Irrespective of the Hierarchical Level to Which They Belong

Humans use rules to organize their actions to achieve specific goals. Although simple rules that link a sensory stimulus to one response may suffice in some situations, often, the application of multiple, hierarchically organized rules is required. Recent theories suggest that progressively higher level rules are encoded along an anterior-to-posterior gradient within PFC. Although some evidence supports the existence of such a functional gradient, other studies argue for a lesser degree of specialization within PFC. We used fMRI to investigate whether rules at different hierarchical levels are represented at distinct locations in the brain or encoded by a single system. Thirty-seven male and female participants represented and applied hierarchical rule sets containing one lower-level stimulus–response rule and one higher-level selection rule. We used multivariate pattern analysis to investigate directly the representation of rules at each hierarchical level in absence of information about rules from other levels or other task-related information, thus providing a clear identification of low- and high-level rule representations. We could decode low- and high-level rules from local patterns of brain activity within a wide frontoparietal network. However, no significant difference existed between regions encoding representations of rules from both levels except for precentral gyrus, which represented only low-level rule information. Our findings show that the brain represents conditional rules regardless of their level in the explored hierarchy, so the human control system did not organize task representation according to this dimension. Our paradigm represents a promising approach to identifying critical principles that shape this control system.Peer Reviewe

A tightly controlled fMRI dataset for receptive field mapping in human visual cortex

Four right-handed, healthy subjects participated in a visual stimulation experiment. Subjects were viewing a dartboard-shaped flickering checkerboard stimulus, divided into 4 rings and 12 segments, defining 48 sectors in the visual field. Local contrast in each sector was continuously varying across four levels and updated every 3 s. To maintain fixation, subjects had to respond to a stimulus at the center of the visual field.During the entire experiment, in which subjects performed 8 runs, each consisting of 100 trials, brain activity was measured with functional magnetic resonance imaging (MRI). Using a 3-T Siemens Trio MRI scanner, 220 echo-planar images were acquired in each run, with a repetition time of 1.5 s and voxel size of 3 x 3 x 3 mm.The dataset is publicly available from OpenNeuro and additionally includes region of interest maps for visual areas V1 to V4, left and right, obtained from another retinotopic mapping experiment. As such, the dataset allows for accurate mapping of receptive fields and their properties across several stages of human visual cortex

Mitigating Modality-Based Interference: Multitasking practice and the distinctiveness of task representation in sensory brain regions

Representational overlap is debated as the neural basis of multitasking costs. Cognitive theories propose that overlapping task representations lead to an unintended exchange of information between tasks (e.g., crosstalk). Recently, modality-based crosstalk was suggested as a source for multitasking costs in multisensory settings. Robust findings of increased costs for certain modality mappings, even when both tasks use non-overlapping stimulus and response modalities, may be explained by crosstalk between the stimulus modality in one task and sensory action consequences in the concurrently performed task. This study (N = 54) employs functional neuroimaging, multivariate pattern analysis, and modality-specific interventions to investigate neural overlap in multitasking, emphasizing modality compatibility. Noteworthy, differences in single-task representations were found in the auditory cortex but not in fronto-parietal regions. Improved auditory decoding accuracy in modality-incompatible tasks predicted dual-task performance gains, eliminating modality-specific costs, exclusively for the modality-incompatible intervention group. This study provides neural evidence for modality-based crosstalk in sensory regions