A demonstration of 'broken' visual space

It has long been assumed that there is a distorted mapping between real and ‘perceived’ space, based on demonstrations of systematic errors in judgements of slant, curvature, direction and separation. Here, we have applied a direct test to the notion of a coherent visual space. In an immersive virtual environment, participants judged the relative distance of two squares displayed in separate intervals. On some trials, the virtual scene expanded by a factor of four between intervals although, in line with recent results, participants did not report any noticeable change in the scene. We found that there was no consistent depth ordering of objects that can explain the distance matches participants made in this environment (e.g. A > B > D yet also A < C < D) and hence no single one-to-one mapping between participants’ perceived space and any real 3D environment. Instead, factors that affect pairwise comparisons of distances dictate participants’ performance. These data contradict, more directly than previous experiments, the idea that the visual system builds and uses a coherent 3D internal representation of a scene

Frontostriatal Gating of Tinnitus and Chronic Pain

Tinnitus and chronic pain are sensory-perceptual disorders associated with negative affect and high impact on well-being and behavior. It is now becoming increasingly clear that higher cognitive and affective brain systems are centrally involved in the pathology of both disorders. We propose that the ventromedial prefrontal cortex and the nucleus accumbens are part of a central 'gatekeeping' system in both sensory modalities, a system which evaluates the relevance and affective value of sensory stimuli and controls information flow via descending pathways. If this frontostriatal system is compromised, long-lasting disturbances are the result. Parallels in both systems are striking and mutually informative, and progress in understanding central gating mechanisms might provide a new impetus to the therapy of tinnitus and chronic pain

Impaired cross-modal inhibition in Alzheimer disease.

BackgroundSuccessful cognitive performance depends not only on the activation of specific neuronal networks but also on selective suppression of task-irrelevant modalities, i.e., deactivation of non-required cerebral regions. This ability to suppress the activation of specific brain regions has, to our knowledge, never been systematically evaluated in patients with Alzheimer disease (AD). The aim of the current study was to evaluate both cerebral activation and deactivation in (1) healthy volunteers, (2) patients with mild cognitive impairment (MCI) who are at risk for AD, and (3) patients with moderate AD during active navigation, representing a cognitive task typically affected in AD.Methods and findingsChanges in regional cerebral blood flow (rCBF) were assessed with PET imaging during an active navigation task in a 3D virtual-reality environment. The task was based on visual cues exclusively; no auditory cues were provided. Age-matched groups of healthy individuals, patients with MCI, and patients with AD were examined. Specific differences in the activation patterns were observed in the three groups, with stronger activation of cerebellar portions and visual association cortex in controls and stronger activation of primary visual and frontal cortical areas in patients with MCI and AD. Highly significant bilateral decrease of rCBF in task-irrelevant auditory cortical regions was detected in healthy individuals during performance of the task. This rCBF decrease was interpreted as a cross-modal inhibitory effect. It was diminished in patients with MCI and completely absent in patients with AD. A regression analysis across all individuals revealed a clear positive relation between cognitive status (mini mental state examination score) and the extent of auditory cortical deactivation.ConclusionDuring active navigation, a high level of movement automation and an involvement of higher-order cerebral association functions were observed in healthy controls. Conversely, in patients with MCI and AD, increased cognitive effort and attention towards movement planning, as well as stronger involvement of lower-order cerebral systems, was found. Successful cognitive performance in healthy individuals is associated with deactivation of task-irrelevant cerebral regions, whereas the development of AD appears to be characterized by a progressive impairment of cross-modal cerebral deactivation functions. These changes may cause the generally decreased ability of patients with AD to direct attention primarily to the relevant cognitive modality

Metabolic connectivity mapping reveals effective connectivity in the resting human brain

Directionality of signaling among brain regions provides essential information about human cognition and disease states. Assessing such effective connectivity (EC) across brain states using functional magnetic resonance imaging (fMRI) alone has proven difficult, however. We propose a novel measure of EC, termed metabolic connectivity mapping (MCM), that integrates undirected functional connectivity (FC) with local energy metabolism from fMRI and positron emission tomography (PET) data acquired simultaneously. This method is based on the concept that most energy required for neuronal communication is consumed postsynaptically, i.e., at the target neurons. We investigated MCM and possible changes in EC within the physiological range using eyes open versus eyes closed conditions in healthy subjects. Independent of condition, MCM reliably detected stable and bidirectional communication between early and higher visual regions. Moreover, we found stable top-down signaling from a frontoparietal network including frontal eye fields. In contrast, we found additional top-down signaling from all major clusters of the salience network to early visual cortex only in the eyes open condition. MCM revealed consistent bidirectional and unidirectional signaling across the entire cortex, along with prominent changes in network interactions across two simple brain states. We propose MCM as a novel approach for inferring EC from neuronal energy metabolism that is ideally suited to study signaling hierarchies in the brain and their defects in brain disorders