Early excitatory-inhibitory cortical modifications following skill learning are associated with motor memory consolidation and plasticity overnight

Abstract Consolidation of motor memories is vital to offline enhancement of new motor skills and involves short and longer-term offline processes following learning. While emerging evidence link glutamate and GABA dynamics in the primary motor cortex (M1) to online motor skill practice, its relationship with offline consolidation processes in humans is unclear. Using two-day repeated measures of behavioral and multimodal neuroimaging data before and following motor sequence learning, we show that short-term glutamatergic and GABAergic responses in M1 within minutes after learning were associated with longer-term learning-induced functional, structural, and behavioral modifications overnight. Furthermore, Glutamatergic and GABAergic modifications were differentially associated with different facets of motor memory consolidation. Our results point to unique and distinct roles of Glutamate and GABA in motor memory consolidation processes in the human brain across timescales and mechanistic levels, tying short-term changes on the neurochemical level to overnight changes in macroscale structure, function, and behavior

Diminished Auditory Responses during NREM Sleep Correlate with the Hierarchy of Language Processing.

Natural sleep provides a powerful model system for studying the neuronal correlates of awareness and state changes in the human brain. To quantitatively map the nature of sleep-induced modulations in sensory responses we presented participants with auditory stimuli possessing different levels of linguistic complexity. Ten participants were scanned using functional magnetic resonance imaging (fMRI) during the waking state and after falling asleep. Sleep staging was based on heart rate measures validated independently on 20 participants using concurrent EEG and heart rate measurements and the results were confirmed using permutation analysis. Participants were exposed to three types of auditory stimuli: scrambled sounds, meaningless word sentences and comprehensible sentences. During non-rapid eye movement (NREM) sleep, we found diminishing brain activation along the hierarchy of language processing, more pronounced in higher processing regions. Specifically, the auditory thalamus showed similar activation levels during sleep and waking states, primary auditory cortex remained activated but showed a significant reduction in auditory responses during sleep, and the high order language-related representation in inferior frontal gyrus (IFG) cortex showed a complete abolishment of responses during NREM sleep. In addition to an overall activation decrease in language processing regions in superior temporal gyrus and IFG, those areas manifested a loss of semantic selectivity during NREM sleep. Our results suggest that the decreased awareness to linguistic auditory stimuli during NREM sleep is linked to diminished activity in high order processing stations

Relaxation–Diffusion T2–ADC Correlations in Breast Cancer Patients: A Spatiotemporally Encoded 3T MRI Assessment

Quantitative correlations between T2 and ADC values were explored on cancerous breast lesions using spatiotemporally encoded (SPEN) MRI. To this end, T2 maps of patients were measured at more than one b-value, and ADC maps at several echo time values were recorded. SPEN delivered quality, artifact-free, TE-weighted DW images, from which T2-ADC correlations could be obtained despite the signal losses brought about by diffusion and relaxation. Data confirmed known aspects of breast cancer lesions, including their reduced ADC values vs. healthy tissue. Data also revealed an anticorrelation between the T2 and ADC values, when comparing regions with healthy and diseased tissues. This is contrary to expectations based on simple water restriction considerations. It is also contrary to what has been observed in a majority of porous materials and tissues. Differences between the healthy tissue of the lesion-affected breast and healthy tissue in the contralateral breast were also noticed. The potential significance of these trends is discussed, as is the potential of combining T2- and ADC-weightings to achieve an enhanced endogenous MRI contrast about the location of breast cancer lesions

Diffusion Is Directional: Innovative Diffusion Tensor Imaging to Improve Prostate Cancer Detection

In the prostate, water diffusion is faster when moving parallel to duct and gland walls than when moving perpendicular to them, but these data are not currently utilized in multiparametric magnetic resonance imaging (mpMRI) for prostate cancer (PCa) detection. Diffusion tensor imaging (DTI) can quantify the directional diffusion of water in tissue and is applied in brain and breast imaging. Our aim was to determine whether DTI may improve PCa detection. We scanned patients undergoing mpMRI for suspected PCa with a DTI sequence. We calculated diffusion metrics from DTI and diffusion weighted imaging (DWI) for suspected lesions and normal-appearing prostate tissue, using specialized software for DTI analysis, and compared predictive values for PCa in targeted biopsies, performed when clinically indicated. DTI scans were performed on 78 patients, 42 underwent biopsy and 16 were diagnosed with PCa. The median age was 62 (IQR 54.4–68.4), and PSA 4.8 (IQR 1.3–10.7) ng/mL. DTI metrics distinguished PCa lesions from normal tissue. The prime diffusion coefficient (λ1) was lower in both peripheral-zone (p < 0.0001) and central-gland (p < 0.0001) cancers, compared to normal tissue. DTI had higher negative and positive predictive values than mpMRI to predict PCa (positive predictive value (PPV) 77.8% (58.6–97.0%), negative predictive value (NPV) 91.7% (80.6–100%) vs. PPV 46.7% (28.8–64.5%), NPV 83.3% (62.3–100%)). We conclude from this pilot study that DTI combined with T2-weighted imaging may have the potential to improve PCa detection without requiring contrast injection

Cortical responses to auditory stimuli during wakefulness.

<p>Statistical parametric maps of GLM multi participant (n = 10) random effect analysis. Color coding denotes t values. <i>(a)</i> Response to scrambled sentences versus rest during wakefulness in the night session (blue shades), and in auditory localizer scans (orange shades). Note the high proportion of overlap (purple shades) <i>(b)</i> Regions showing preferred activation for comprehensible sentences over scrambled sentences in awake periods during the night session and in auditory localizer scans. HG = Heschl’s gyrus, IFG = inferior frontal gyrus, STG = superior temporal gyrus. Color bars denote the maps t values during the night (left scale) and daytime localizer (right scale) sessions.</p

Automatic Three-Dimensional Segmentation of MR Images Applied to the Rat Uterus

We introduce an automatic 3D multiscale automatic segmentation algorithm for delineating specific organs in Magnetic Resonance images (MRI). The algorithm can process several modalities simultaneously, and handle both isotropic and anisotropic data in only linear time complexity. It produces a hierarchical decomposition of MRI scans. During this segmentation process a rich set of features describing the segments in terms of intensity, shape and location are calculated, reflecting the formation of the hierarchical decomposition. We show that this method can delineate the entire uterus of the rat abdomen in 3D MR images utilizing a combination of scanning protocols that jointly achieve high contrast between the uterus and other abdominal organs and between inner structures of the rat uterus. Both single and multi-channel automatic segmentation demonstrate high correlation to a manual segmentation. While the focus here is on the rat uterus, the general approach can be applied to recognition in 2D, 3D and multi-channel medical images

Indices quantifying the effect of sleep on the different ROIs.

<p>Beta values were used to calculate the indices (n = 10). <i>(a)</i> Mean index assessing semantic selectivity during wakefulness (purple) and sleep (green), calculated by subtracting betas of scrambled from comprehensible sentences in each of the ROIs. <i>(b)</i> Median index measuring the effect of sleep on the response to comprehensible sentences, calculated by subtracting awake betas from sleep betas and dividing by awake betas for the comprehensible sentences category. Note the graded decrease in the index values moving along the hierarchy of semantic processing ROIs. sen = comprehensible sentences. Statistical specifications are the same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157143#pone.0157143.g004" target="_blank">Fig 4</a>.</p