Carsten Bogler

The extended language network: A meta-analysis of neuroimaging studies on text comprehension

Language processing in context requires more than merely comprehending words and sentences. Important subprocesses are inferences for bridging successive utterances, the use of background knowledge and discourse context, and pragmatic interpretations. The functional neuroanatomy of these text comprehension processes has only recently been investigated. Although there is evidence for right‐hemisphere contributions, reviews have implicated the left lateral prefrontal cortex, left temporal regions beyond Wernickes area, and the left dorso‐medial prefrontal cortex (dmPFC) for text comprehension. To objectively confirm this extended language network and to evaluate the respective contribution of right hemisphere regions, meta‐analyses of 23 neuroimaging studies are reported here. The analyses used replicator dynamics based on activation likelihood estimates. Independent of the baseline, the anterior temporal lobes (aTL) were active bilaterally. In addition, processing of coherent compared with incoherent text engaged the dmPFC and the posterior cingulate cortex. Right hemisphere activations were seen most notably in the analysis of contrasts testing specific subprocesses, such as metaphor comprehension. These results suggest task dependent contributions for the lateral PFC and the right hemisphere. Most importantly, they confirm the role of the aTL and the fronto‐medial cortex for language processing in context. Hum Brain Mapp 2008.

Decoding Successive Computational Stages of Saliency Processing

An important requirement for vision is to identify interesting and relevant regions of the environment for further processing. Some models assume that salient locations from a visual scene are encoded in a dedicated spatial saliency map [1, 2]. Then, a winner-take-all (WTA) mechanism [1, 2] is often believed to threshold the graded saliency representation and identify the most salient position in the visual field. Here we aimed to assess whether neural representations of graded saliency and the subsequent WTA mechanism can be dissociated. We presented images of natural scenes while subjects were in a scanner performing a demanding fixation task, and thus their attention was directed away. Signals in early visual cortex and posterior intraparietal sulcus (IPS) correlated with graded saliency as defined by a computational saliency model. Multivariate pattern classification [3, 4] revealed that the most salient position in the visual field was encoded in anterior IPS and frontal eye fields (FEF), thus reflecting a potential WTA stage. Our results thus confirm that graded saliency and WTA-thresholded saliency are encoded in distinct neural structures. This could provide the neural representation required for rapid and automatic orientation toward salient events in natural environments.

The neural encoding of guesses in the human brain.

Human perception depends heavily on the quality of sensory information. When objects are hard to see we often believe ourselves to be purely guessing. Here we investigated whether such guesses use brain networks involved in perceptual decision making or independent networks. We used a combination of fMRI and pattern classification to test how visibility affects the signals, which determine choices. We found that decisions regarding clearly visible objects are predicted by signals in sensory brain regions, whereas different regions in parietal cortex became predictive when subjects were shown invisible objects and believed themselves to be purely guessing. This parietal network was highly overlapping with regions, which have previously been shown to encode free decisions. Thus, the brain might use a dedicated network for determining choices when insufficient sensory information is available.

Similar neural mechanisms for perceptual guesses and free decisions.

When facing perceptual choices under challenging conditions we might believe to be purely guessing. But which brain regions determine the outcome of our guesses? One possibility is that higher-level, domain-general brain regions might help break the symmetry between equal-appearing choices. Here we directly investigated whether perceptual guesses share brain networks with other types of free decisions. We trained an fMRI-based pattern classifier to distinguish between two perceptual guesses and tested whether it was able to predict the outcome of similar non-perceptual choices, as in conventional free choice tasks. Activation patterns in the medial posterior parietal cortex cross-predicted free decisions from perceptual guesses and vice versa. This inter-changeability strongly speaks for a similar neural code for both types of decisions. The posterior parietal cortex might be part of a domain-general system that helps resolve decision conflicts when no choice option is more or less likely or valuable, thus preventing behavioural stalemate.

Default Network Activity Is Associated with Better Performance in a Vigilance Task

When attention has to be maintained over prolonged periods performance slowly fluctuates and errors can occur. It has been shown that lapses of attention are correlated with BOLD signals in frontal and parietal cortex. This raises the question how attentional fluctuations are linked to the fronto-parietal default network. Because the attentional state fluctuates slowly we expect that potential links between attentional fluctuations and brain activity should be observable on longer time scales and importantly also before the execution of the task. In the present study we used fMRI to identify brain activity that is correlated with vigilance, defined as fluctuations of reaction times (RT) during a sustained attention task. We found that brain activity in visual cortex, parietal lobe (PL), inferior and superior frontal gyrus, and supplementary motor area (SMA) was higher when the subject had a relatively long RT. In contrast to our expectations, activity in the default network (DN) was higher when subjects had a relatively short RT, that means when the performance was improved. This modulation in the DN was present already several seconds before the task execution, thus pointing to activity in the DN as a potential cause of performance increases in simple repetitive tasks.

Am I seeing myself, my friend or a stranger? The role of personal familiarity in visual distinction of body identities in the human brain

Several brain regions appear to play a role in representing different body identities. The specific contribution of each of these regions is still unclear, however. Here we investigated which brain areas enable the visual distinction between self and other bodies of different familiarity, and between familiar and unfamiliar other individuals, and moreover, where identity-specific information on the three individuals was encoded. Participants were confronted with standardized headless human body stimuli either showing the participants own, a personally familiar or an unfamiliar other body, while performing a luminance discrimination task. Employing multivariate pattern analysis, we were able to identify areas that allowed for the distinction of self from personal familiar other bodies within the medial prefrontal cortex (mPFC) and posterior cingulate cortex/precuneus. Successful distinction of self from unfamiliar others was possible in the left middle frontal gyrus, the right inferior frontal gyrus, the left pre-supplementary motor area and the right putamen. Personally familiar others could be distinguished from unfamiliar others in the right temporoparietal junction (TPJ). An analysis of identity-specific information revealed a spatial gradient ranging from inferior posterior to superior anterior portions of the mPFC that was associated with encoding identity-related information for self via familiar to unfamiliar other bodies, respectively. Furthermore, several midline and frontal regions encoded information on more than one identity. The TPJs role in deviance detection was underlined, as only identity-specific information on unfamiliar others was encoded here. Together, our findings suggest substantial spatial overlap in neural correlates of self and other body representation and thus, support the hypothesis of a socially-related representation of the self.

Multivariate dekodierung von fMRT-daten: Auf dem weg zu einer inhaltsbasierten kognitiven neurowissenschaft

Zusammenfassung Seit dem Aufkommen der funktionellen Magnetresonanztomografie (fMRT) vor 20 Jahren steht eine neue Methode zur nicht invasiven Messung von Gehirnfunktionen zur Verfügung, welche in den kognitiven Neurowissenschaften inzwischen weit verbreitet ist. Traditionell wurden fMRT-Daten vor allem verwendet, um globale Änderungen der Aktivität in bestimmten Gehirnregionen zu messen, wie sie etwa während einer kognitiven Verarbeitung auftreten. Die Entwicklung neuer Methoden ermöglicht nun einen verfeinerten, inhaltsbasierten Ansatz. Das „multivariate Decoding“ erlaubt es, die kognitive Information zu untersuchen, die in feinkörnigen fMRT-Aktivitätsmustern enthalten ist. Damit lässt sich die Kodierung spezifischer kognitiver Inhalte und Repräsentationen im Gehirn näher bestimmen. Hier wird ein Überblick über verschiedene Entwicklungen des multivariaten Decoding gegeben von der Anwendung in den kognitiven Neurowissenschaften (Wahrnehmung, Aufmerksamkeit, Belohnung, Entscheidungsfindung, emotionale Kommunikation) über neuere methodische Entwicklungen (Informationsfluss, oberflächenbasiertes Searchlight-Decoding) bis hin zur medizinischen Diagnostik gegeben.