Sensorimotor control is an integral part of our daily life and the essential prerequisite to interact with one’s environment, i.e. the internal and external milieu. Thus, the convergence and integration of both intero- and exteroceptive stimuli in the human brain is fundamental to allow for a comprehensive environmental picture (Berlucchi & Aglioti, 2010
). In most functional neuroimaging experiments the selection of the adequate behavioral response is based on only a limited number of stimuli, i.e. the brain has to evaluate which stimuli are crucial to meet the task (Bays et al., 2010
). This subset of bottom-up (sensory) input is subsequently weighted against top-down information such as contextual rules and goals. Fundamentally, top-down signals represent feedback from ‘higher’ (usually multimodal) brain regions to unimodal sensory or motor areas. Anatomically, such top-down feedback is implemented by diffuse connectivity into (primarily) dendritic terminals in cortical layers II-III, whereas bottom-up (feed-forward) connections primarily terminate in layer IV of a more circumscribed patch of the cortex. The result of this complex procedure consists of highly integrated data and constitutes the basis upon which the respective movements are planned. In the following, the term ‘contextual integration’ is used to denote the top-down modulation of sensorimotor processing by context-specific a-priori information. Context is here defined as any information affecting actions that is not provided by the given response stimulus itself but by the environment, ranging from explicit instructions about stimulus–response mappings to implicit expectations extracted from regularities in the stimulation sequence. The first aim of our study was to identify regions that are consistently (i.e. across different studies) activated by context-dependent sensorimotor control.
So far, we have only considered task-induced integration processes. However, the human brain is assumed to operate along a continuum between task-related performance and ‘mental rest’, i.e. ‘unconstrained’ cognition (Schilbach et al., 2008
). This presumption is in line with several studies (Smith et al., 2009
; Fox and Raichle, 2007
) demonstrating that ‘physiological rest’ does not equate ‘mental rest’. Rather, it has been hypothesized (Schilbach et al., 2008
) that the absence of an externally structured task entails a re-allocation of resources towards internally oriented, i.e. ‘conceptual’ (Binder et al., 1999
), operations resulting in ‘mind-wandering’ (cf. Smallwood & Schooler, 2006
). Thus, the second aim of our study was to assess the functional connectivity of the above-mentioned areas in both task-dependent and task-independent mental states. The third aim was to test for commonalities and differences in the functional connectivity pattern of these two fundamental states of brain function.
To date, a large number of functional neuroimaging studies have adopted task-based experimental designs to investigate the neural correlates of stimulus-response associations in humans (Egner, 2007
) and non-human primates (Connolly et al., 2009
). Despite the differences in experimental designs several studies have provided consistent evidence for an implementation of these processes in a bilateral fronto-parietal network. In line with data from single-cell recordings in non-human primates (Gottlieb & Snyder, 2010
), the inferior parietal lobe (IPL) and adjacent intraparietal sulcus are conceptualized to evaluate and integrate incoming sensory input from different modalities. In this context, Spence & Driver (2004)
claimed that the posterior parietal cortex plays a critical role in mediating the integration of spatial aspects of multimodal stimuli (e.g. visual, auditory or tactile) and their transformation into action-based representations. This is well in line with the presumption of IPL/IPS acting as a heteromodal integrative ‘hub’ committed to multi-sensory processing (Gottlieb, 2007
, Toni et al., 2002
). Such multimodal integration processes, however, may not be restricted to the posterior parietal cortex. Rather, there is evidence that multi-modal integration is also supported by regions within the (pre-)frontal and temporal cortex (Calvert et al., 2004
, Driver & Noesselt, 2008
). In particular, contextual information from the (pre-)frontal cortex enriches these integrative processes and permits a bidirectional coupling between stimulus and contextual framework (Koechlin & Jubault, 2006
). Moreover, the function of (pre-)frontal areas in the system of sensorimotor control also comprises the exertion of ‘executive control’ on the (pre-) motor system (Koechlin & Summerfield, 2007
). In particular, these regions were found to be involved in rule-based adjustment of motor plans, movement timing and action monitoring. Finally, the (pre-)motor areas are thought to select, initiate and execute the adequate motor program based on the highly integrated information from the parietal and (pre-)frontal cortex (Picard & Strick, 1996
, Rizzolatti et al., 1998
). Sensorimotor control thus depends on the integration of cognitive aspects with the monitoring of the internal and external milieu and the selection of appropriate responses based on these information.
In this context, the question arises as to which regions are consistently activated during the implementation of sensorimotor control, i.e. the association of a given stimulus with an arbitrary (instructed) response. Three recently published functional neuroimaging studies (Jakobs et al., 2009
, Cieslik et al., 2010
, Eickhoff et al., 2011
) applied variations of a manual two-choice reaction time task with graduated levels of difficulty in stimulus-response mapping. Testing for neural effects of increasing demands on stimulus-response association in each study revealed a similar bilateral, though right-hemispherically dominant, fronto-parietal network. In order to statistically validate this prima facie evidence, i.e. to detect regions featuring a significant overlap across the abovementioned studies, we applied an image-based meta-analysis (IBMA) technique to investigate the multi-study conjunction of results. In this context, regions consistently activated across studies are assumed to implement higher-order processes in the cascade of stimulusresponse association.
However, even the common evidence provided by three studies might still reflect design-specific effects to a degree that precludes broad generalizations about this fundamental network. Thus, in the second part of the current study, we used meta-analytic connectivity modeling (MACM) to delineate the functional connectivity (FC) pattern of higher-order sensorimotor regions (i.e. consistently activated clusters observed in the IBMA) in the presence of an externally structured task. The basic idea behind this approach is to assess which brain regions are co-activated above chance with particular seed regions in functional neuroimaging experiments. Here, we used the BrainMap database (Laird et al., 2009a
) to identify co-activations with our seed regions (i.e. the results of the above-mentioned IBMA) across all studies listed in this database and subsequently performed an ALE (activation likelihood estimation) meta-analysis on these studies (Laird et al., 2009a
; Eickhoff et al., 2009
As mentioned above, regions participating in stimulus–context integration are also engaged in task-free brain states. Thus, it may be speculated that a shared procedure is based upon a subset of regions, which are activated irrespective of the current mental state. To test this hypothesis, we investigated ‘resting-state’ FC using functional imaging data from 100 healthy volunteers. The time-series of each seed region was cross-correlated with the time-series of all other gray-matter voxels in the brain. Consistent functional coupling across mental states (i.e. overlap of regions co-activated across studies with our seed and regions with significant intrinsic connectivity to our seed) would indicate that the seed and target regions participate in very much the same networks during task-dependent stimulus–context integration and task-free, unstructured processing. In contrast, divergent results would delineate networks that depend on the mental state and thus allow for a differentiation of internally and externally driven FC networks (Eickhoff & Grefkes, 2011