Ricarda Ines Schubotz

Brain correlates of aesthetic judgment of beauty

Functional MRI was used to investigate the neural correlates of aesthetic judgments of beauty of geometrical shapes. Participants performed evaluative aesthetic judgments (beautiful or not?) and descriptive symmetry judgments (symmetric or not?) on the same stimulus material. Symmetry was employed because aesthetic judgments are known to be often guided by criteria of symmetry. Novel, abstract graphic patterns were presented to minimize influences of attitudes or memory-related processes and to test effects of stimulus symmetry and complexity. Behavioral results confirmed the influence of stimulus symmetry and complexity on aesthetic judgments. Direct contrasts showed specific activations for aesthetic judgments in the frontomedian cortex (BA 9/10), bilateral prefrontal BA 45/47, and posterior cingulate, left temporal pole, and the temporoparietal junction. In contrast, symmetry judgments elicited specific activations in parietal and premotor areas subserving spatial processing. Interestingly, beautiful judgments enhanced BOLD signals not only in the frontomedian cortex, but also in the left intraparietal sulcus of the symmetry network. Moreover, stimulus complexity caused differential effects for each of the two judgment types. Findings indicate aesthetic judgments of beauty to rely on a network partially overlapping with that underlying evaluative judgments on social and moral cues and substantiate the significance of symmetry and complexity for our judgment of beauty.

Time Perception and Motor Timing: A Common Cortical and Subcortical Basis Revealed by fMRI

Though it is well known that humans perceive the temporal features of the environment incessantly, the brain mechanisms underlying temporal processing are relatively unexplored. Functional magnetic resonance imaging was used in this study to identify brain activations during sustained perceptual analysis of auditorally and visually presented temporal patterns (rhythms). Our findings show that the neural network supporting time perception involves the same brain areas that are responsible for the temporal planning and coordination of movements. These results indicate that time perception and motor timing rely on similar cerebral structures.

Prediction, cognition and the brain

The term “predictive brain” depicts one of the most relevant concepts in cognitive neuroscience which emphasizes the importance of “looking into the future”, namely prediction, preparation, anticipation, prospection or expectations in various cognitive domains. Analogously, it has been suggested that predictive processing represents one of the fundamental principles of neural computations and that errors of prediction may be crucial for driving neural and cognitive processes as well as behavior. This review discusses research areas which have recognized the importance of prediction and introduces the relevant terminology and leading theories in the field in an attempt to abstract some generative mechanisms of predictive processing. Furthermore, we discuss the process of testing the validity of postulated expectations by matching these to the realized events and compare the subsequent processing of events which confirm to those which violate the initial predictions. We conclude by suggesting that, although a lot is known about this type of processing, there are still many open issues which need to be resolved before a unified theory of predictive processing can be postulated with regard to both cognitive and neural functioning.

Functional-anatomical concepts of human premotor cortex: evidence from fMRI and PET studies

The premotor cortex (PM) refers to human Brodmann area 6 (BA6), and often anteriorly adjacent areas BA44 and BA8 are also included. The function traditionally attributed to the PM is the preparation and the organization of movements and actions (Wise, 1985). However, with the introduction of imaging methods, which allow the neural correlates of behavioral functions to be measured online, premotor activations have frequently found in nonmotor “cognitive” domains. As these findings were difficult to interpret in light of the classical motor view, they were typically taken to reflect some kind of latent motor processes. As such, they were experimental artifacts of either nonsuppressible or deliberately chosen behavioral strategies, like verbalizing or tapping, or simply movement noise. However, nowadays the exploration of cognitive function of the human premotor cortex has become an independent field of research, supported and also inspired by results from research in the monkey. Hence, currently a diversity of concepts of PM functions coexist, referring partly to the classical motor account, partly to the scope of nonmotor functions. With particular interest in the nonmotor domain, the present paper aims to outline current concepts of human PM functions as have emerged from imaging results. Concepts apply to functional–anatomical dissociations of right vs left, medial vs lateral, rostral vs caudal, and dorsal vs ventral PM. In view of widely missing macroanatomical borders between PM subsections, these labels can serve only as a gross orientation. Moreover, the investigation of cortical architecture in living humans on the microanatomical level using specific MR protocols is still restricted to a resolution of about 500 m (Damasio, 1991). As we lack direct evidence from individual cytoarchitectonic data in conjunction with functional results, any potential correspondences between subsections of the human and the monkey PM are based on functional rather than on anatomical homologies (e.g., Rizzolatti et al., 2002). The scope of the present paper is limited. It focuses on imaging studies (in contrast to other methods in humans and in contrast to monkey studies), on the lateral (in contrast to medial) PM, and on functional trends along the dorsal– ventral axis. Concepts are illustrated by some representative findings only.

Predicting events of varying probability: uncertainty investigated by fMRI

Many everyday life predictions rely on the experience and memory of event frequencies, i.e., natural samplings. We used functional magnetic resonance imaging (fMRI) to investigate the neural substrates of prediction under varying uncertainty based on a natural sampling approach. The study focused particularly on a comparison with other types of externally attributed uncertainty, such as guessing, and on the frontomedian cortex, which is known to be engaged in many types of decisions under uncertainty. On the basis of preceding stimulus cues, participants predicted events that occurred with probabilities ranging from p = 0.6 to p = 1.0. In contrast to certain predictions in a control task, predictions under uncertainty elicited activations within a posterior frontomedian area (mesial BA 8) and within a set of subcortical areas which are known to subserve dopaminergic modulations. The parametric analysis revealed that activation within the mesial BA 8 significantly increased with increasing uncertainty. A comparison with other types of uncertainty indicates that frontomedian correlates of frequency-based prediction appear to be comparable with those induced in long-term stimulus-response adaptation processes such as hypothesis testing, in contrast to those engaged in short-term error processing such as guessing.

Sequences of Abstract Nonbiological Stimuli Share Ventral Premotor Cortex with Action Observation and Imagery

Activation triggered by either observed or imagined actions suggests that the ventral premotor cortex (PMv) provides an action vocabulary that allows us to detect and anticipate basically invariant perceptual states in observed actions. In the present study, we tested the hypothesis that the same PMv region is also recruited by nonbiological (abstract) stimulus sequences as long as the temporal order of stimuli has to be processed. Using functional magnetic resonance imaging, we instructed participants to assess expected outcomes in observed actions [external biological cues (EB)], motor imagery [internal biological cues (IB)], or geometrical figure sequences [external nonbiological cues (EN)]. As hypothesized, we found that each condition elicited significant activation within PMv [left hemisphere, Brodman Area (BA) 6], in contrast to a sequential target detection control task. In addition, cue-specific activations were identified in areas that were only engaged for biologically (action) cued (EB, IB) and nonbiologically cued (EN) tasks. Biologically cued tasks elicited activations within inferior frontal gyri adjacent to PMv (BA 44/45), in the frontomedian wall, the extrastriate body area, posterior superior temporal sulci, somatosensory cortices, and the amygdala-hippocampal-area, whereas the nonbiologically cued task engaged presupplementary motor area, middle frontal gyri, intraparietal sulci, and caudate nuclei of the basal ganglia. In sum, findings point to a basic premotor contribution to the representation or processing of sequentially structured events, supplemented by different sets of areas in the context of either biological or nonbiological cues.

Predicting Perceptual Events Activates Corresponding Motor Schemes in Lateral Premotor Cortex: An fMRI Study

The ability to recognize sequential patterns of external events enables us to predict their future course and thus to plan and execute actions based on current perceptions and previous experiences. Here we show with functional magnetic resonance imaging that even in the absence of movement the prediction of sequential patterns activates brain areas involved in the representation of specific motor schemas. Particularly, the prediction of size engages premotor areas involved in hand movements (superior part of the ventrolateral premotor cortex), whereas the prediction of pitch engages premotor areas involved in articulation (inferior most ventrolateral premotor cortex). The findings indicate that events are mapped onto somatotopically corresponding motor schemes whenever we predict sequential perceptions.

Hierarchical artificial grammar processing engages Broca's area

The present fMRI study investigates the neural basis of hierarchical processing using two types of artificial grammars: one governed by rules of adjacent dependencies and the other by rules of hierarchical dependencies. The adjacent dependency sequences followed the rule (AB)(n), at which simple transitions between two types of syllable categories were generated (e.g. A(1)B(1)A(2)B(2)). The hierarchical syllable sequences followed the rule A(n)B(n), generating a center-embedded structure (e.g. A(2)A(1)B(1)B(2)) the learning of which required the processing of hierarchical dependencies. When comparing the processing of hierarchical dependencies to adjacent dependencies, significantly higher activations were observed in Brocas area and the adjacent rim of the ventral premotor cortex (BA 44/6) in addition to some several other cortical and sub-cortical regions. These results indicate that Brocas area is part of a neural circuit that is responsible for the processing of hierarchical structures in an artificial grammar.

Premotor cortex in observing erroneous action: an fMRI study

The lateral premotor cortex (PMC) is involved during action observation in monkeys and humans, reflecting a matching process between observed actions and their corresponding motor schemata. In the present study, functional magnetic resonance imaging (fMRI) was used to investigate if paying attention to the two observable action components, objects and movements, modulates premotor activation during the observation of actions. Participants were asked to classify presented movies as showing correct actions, erroneous actions, or senseless movements. Erroneous actions were incorrect either with regard to employed objects, or to performed movements. The experiment yielded two major results: (1) The ventrolateral premotor cortex (vPMC) and the anterior part of the intraparietal sulcus (aIPS) are strongly activated during the observation of actions in humans. Premotor activation was dominantly located within Brodmann Area (BA) 6, and sometimes extended into BA 44. (2) The presentation of object errors and movements errors allowed to disentangle brain activations corresponding to the analysis of movements and objects in observed actions. Left premotor areas were more involved in the analysis of objects, whereas right premotor areas were dominant in the analysis of movements. It is suggested that the analysis of categorical information, like objects, and that of coordinate information, like movements, are pronounced in different hemispheres.

Why am I unsure? Internal and external attributions of uncertainty dissociated by fMRI

Behavioral evidence suggests that the perceived reason of uncertainty causes different coping strategies to be implemented, particularly frequency ratings with externally attributed uncertainty and memory search with internally attributed uncertainty. We used functional magnetic resonance imaging (fMRI) to investigate whether processes related to these different attributions of uncertainty differ also in their neural substrates. Participants had to predict events that were uncertain due to internal factors, that is, insufficient knowledge. Data were compared with a preceding study in which event prediction was uncertain due to external factors, that is, event probabilities. Parametric analyses revealed the posterior frontomedian cortex, that is, mesial Brodmann Area 8 (BA 8) as the common cortical substrate mediating processes related to uncertainty no matter what the cause of uncertainty. However, processes related to the two differently attributed types of uncertainty differed significantly in relation to the brain network that was coactivated. Only processes related to internally attributed uncertainty elicited activation within the mid-dorsolateral and posterior parietal areas known to underlie working memory (WM) functions. Together, findings from both experiments suggest that there is a common cerebral correlate for uncertain predictions but different correlates for coping strategies of uncertainty. Concluding, BA 8 reflects that we are uncertain, coactivated networks what we do to resolve uncertainty.