Representations of specific acoustic patterns in the auditory cortex and hippocampus

Previous behavioural studies have shown that repeated presentation of a randomly chosen acoustic pattern leads to the unsupervised learning of some of its specific acoustic features. The objective of our study was to determine the neural substrate for the representation of freshly learnt acoustic patterns. Subjects first performed a behavioural task that resulted in the incidental learning of three different noise-like acoustic patterns. During subsequent high-resolution functional magnetic resonance imaging scanning, subjects were then exposed again to these three learnt patterns and to others that had not been learned. Multi-voxel pattern analysis was used to test if the learnt acoustic patterns could be ‘decoded’ from the patterns of activity in the auditory cortex and medial temporal lobe. We found that activity in planum temporale and the hippocampus reliably distinguished between the learnt acoustic patterns. Our results demonstrate that these structures are involved in the neural representation of specific acoustic patterns after they have been learnt.     

Dysregulated daily rhythmicity of neuronal resting-state networks in MCI patients

In young healthy participants, the degree of daily rhythmicity largely varies across different neuronal resting-state networks (RSNs), while it is to date unknown whether this temporal pattern of activity is conserved in healthy and pathological aging. Twelve healthy elderly (mean age?=?65.1?±?5.7 years) and 12 patients with amnestic mild cognitive impairment (aMCI; mean age?=?69.6?±?6.2 years) underwent four resting-state functional magnetic resonance imaging scans at fixed 2.5?h intervals throughout a day. Time courses of a RSN were extracted by a connectivity strength and a spatial extent approach performed individually for each participant. Highly rhythmic RSNs included a sensorimotor, a cerebellar and a visual network in healthy elderly; the least rhythmic RSNs in this group included a network associated with executive control and an orbitofrontal network. The degree of daily rhythmicity in aMCI patients was reduced and dysregulated. For healthy elderly, the findings are in accordance with results reported for young healthy participants suggesting a comparable distribution of daily rhythmicity across RSNs during healthy aging. In contrast, the reduction and dysregulation of daily rhythmicity observed in aMCI patients is presumably indicative of underlying neurodegenerative processes in this group.     

The Postnatal Development of the Cerebellum— A fMRI and Silver Study

Summary The aim of this study was to evaluate the postnatal development of the cerebella of the pig and to compare this with the activation of the fMRI. The cells in the cerebella were studied by silver technique and the activation of the fMRI in the cerebella was initiated by flexion and extension of the hind paw. Our results showed an increase of the branching of the cells of the cerebellar cortex postnatally, coordinated with registration of fMRI active sites in the cerebella at 6-month postnatal. We concluded that the full maturation of the cerebella was around 6-month postnatal in the pig.     

Traveling EEG slow oscillation along the dorsal attention network initiates spontaneous perceptual switching

An ambiguous figure such as the Necker cube causes spontaneous perceptual switching (SPS). The mechanism of SPS in multistable perception has not yet been determined. Although early psychological studies suggested that SPS may be caused by fatigue or satiation of orientation, the neural mechanism of SPS is still unknown. Functional magnetic resonance imaging (fMRI) has shown that the dorsal attention network (DAN), which mainly controls voluntary attention, is involved in bistable perception of the Necker cube. To determine whether neural dynamics along the DAN cause SPS, we performed simultaneous electroencephalography (EEG) and fMRI during an SPS task with the Necker cube, with every SPS reported by pressing a button. This EEG–fMRI integrated analysis showed that (a) 3–4 Hz spectral EEG power modulation at fronto-central, parietal, and centro-parietal electrode sites sequentially appeared from 750 to 350 ms prior to the button press; and (b) activations correlating with the EEG modulation traveled along the DAN from the frontal to the parietal regions. These findings suggest that slow oscillation initiates SPS through global dynamics along the attentional system such as the DAN.     

Basics of Multivariate Analysis in Neuroimaging Data

Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques^1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.     

Medial prefrontal cortex dissociation between self and others in a referential task: An fMRI study based on word traits

A number of recent neuroimaging studies using self referential tasks have investigated whether self referential processing depends on a unique neural basis that operates specifically in the medial prefrontal cortex. However, these studies have provided contradictory results despite the use of similar methodologies. We hypothesized that these discrepancies are partially related to the task-difficulty that presents dissociations reaction times in the self- and other-referential tasks. We therefore measured brain activity during self and other referential tasks to determine if such activity can be dissociated according to the reaction times (fast versus slow) for the trait words. Activation differed across self and other only in the slow word condition. The self referential condition with slow reaction time produced greater activation in the ventromedial prefrontal cortex, whereas the other referential condition with slow reaction time produced activation of the middle temporal gyrus. Results suggested that the task-difficulty might affect whether or not brain activities within MPFC would be dissociated between self- and other-referential processing.     

Correlation of behavior changes and BOLD signal in Alzheimer-like rat model

Memory impairment is usually the early and most promi-nent clinical manifestation of Alzheimer disease (AD), aprogressive neurodegenerative illness characterized bygradual deposition of neuritic plaques and neurofibrillarytangles in the brain of the patie…