Higher GABA concentration in the medial prefrontal cortex of Type 2 diabetes patients is associated with episodic memory dysfunction.

Type 2 diabetes (T2D) is associated with an accelerated episodic memory decline, but the underlying pathophysiological mechanisms are not well understood. Hallmarks of T2D comprise impairment of insulin secretion and insulin sensitivity. Insulin signaling modulates cerebral neurotransmitter activity, including the excitatory glutamate and inhibitory gamma-aminobutyric acid (GABA) systems. Here we tested the hypothesis that the glutamate and GABA systems are altered in T2D patients and this relates to memory decline and insulin resistance. Using 1 H-magnetic resonance spectroscopy (MRS), we examined glutamate and GABA concentrations in episodic memory relevant brain regions (medial prefrontal cortex and precuneus) of T2D patients and matched controls. Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamps and memory performance was assessed using a face-profession associations test. T2D patients exhibited peripheral insulin resistance and had a decreased memory for face-profession associations as well as elevated GABA concentration in the medial prefrontal cortex but not precuneus. In addition, medial prefrontal cortex GABA concentration was negatively associated with memory performance suggesting that abnormal GABA levels in the medial prefrontal cortex are linked to the episodic memory decline that occurs in T2D patients.

The increase in medial prefrontal glutamate/glutamine concentration during memory encoding is associated with better memory performance and stronger functional connectivity in the human medial prefrontal-thalamus-hippocampus network.

The classical model of the declarative memory system describes the hippocampus and its interactions with representational brain areas in posterior neocortex as being essential for the formation of long-term episodic memories. However, new evidence suggests an extension of this classical model by assigning the medial prefrontal cortex (mPFC) a specific, yet not fully defined role in episodic memory. In this study, we utilized 1H magnetic resonance spectroscopy (MRS) and psychophysiological interaction (PPI) analysis to lend further support for the idea of a mnemonic role of the mPFC in humans. By using MRS, we measured mPFC γ-aminobutyric acid (GABA) and glutamate/glutamine (GLx) concentrations before and after volunteers memorized face-name association. We demonstrate that mPFC GLx but not GABA levels increased during the memory task, which appeared to be related to memory performance. Regarding functional connectivity, we used the subsequent memory paradigm and found that the GLx increase was associated with stronger mPFC connectivity to thalamus and hippocampus for associations subsequently recognized with high confidence as opposed to subsequently recognized with low confidence/forgotten. Taken together, we provide new evidence for an mPFC involvement in episodic memory by showing a memory-related increase in mPFC excitatory neurotransmitter levels that was associated with better memory and stronger memory-related functional connectivity in a medial prefrontal-thalamus-hippocampus network.

Transient relay function of midline thalamic nuclei during long-term memory consolidation in humans.

To test the hypothesis that thalamic midline nuclei play a transient role in memory consolidation, we reanalyzed a prospective functional MRI study, contrasting recent and progressively more remote memory retrieval. We revealed a transient thalamic connectivity increase with the hippocampus, the medial prefrontal cortex (mPFC), and a parahippocampal area, which decreased with time. In turn, mPFC-parahippocampal connectivity increased progressively. These findings support a model in which thalamic midline nuclei serve as a hub linking hippocampus, mPFC, and posterior representational areas during memory retrieval at an early (2 h) stage of consolidation, extending classical systems consolidation models by attributing a transient role to midline thalamic nuclei.

A comparison of sLASER and MEGA-sLASER using simultaneous interleaved acquisition for measuring GABA in the human brain at 7T.

γ-Aminobutyric acid (GABA), the major inhibitory neurotransmitter, is challenging to measure using proton spectroscopy due to its relatively low concentration, J-coupling and overlapping signals from other metabolites. Currently, the prevalent methods for detecting GABA at ultrahigh field strengths (≥ 7 T) are GABA-editing and model fitting of non-editing single voxel spectra. These two acquisition approaches have their own advantages: the GABA editing approach directly measures the GABA resonance at 3 ppm, whereas the fitting approach on the non-editing spectrum allows the detection of multiple metabolites, and has an SNR advantage over longer echo time (TE) acquisitions. This study aims to compare these approaches for estimating GABA at 7 T. We use an interleaved sequence of semi-LASER (sLASER: TE = 38 ms) and MEGA-sLASER (TE = 80 ms). This simultaneous interleaved acquisition minimizes the differential effect of extraneous factors, and enables an accurate comparison of the two acquisition methods. Spectra were acquired with an 8 ml isotropic voxel at six different brain regions: anterior-cingulate cortex, dorsolateral-prefrontal cortex, motor cortex, occipital cortex, posterior cingulate cortex, and precuneus. Spectral fitting with LCModel quantified the GABA to total Cr (tCr: Creatine + Phosphocreatine) concentration ratio. After correcting the T2 relaxation time variation, GABA/tCr ratios were similar between the two acquisition approaches. GABA editing showed smaller spectral fitting error according to Cramér-Rao lower bound than the sLASER approach for all regions examined. We conclude that both acquisition methods show similar accuracy but the precision of the MEGA-editing approach is higher for GABA measurement. In addition, the 2.28 ppm GABA resonance was found to be important for estimating GABA concentration without macromolecule contamination in the GABA-edited acquisition, when utilizing spectral fitting with LCModel.

Effect of linewidth on estimation of metabolic concentration when using water lineshape spectral model fitting for single voxel proton spectroscopy at 7 T.

Good B0 field homogeneity is considered an essential requirement to obtain high-quality MRS data. Many commonly used spectral fitting methods assume that all metabolite signals have Lorentzian or Gaussian shapes. However, B0 inhomogeneity can both broaden the linewidth and modify the lineshape. In this study, it is hypothesized that a realistic metabolite fitting model, which accounts for B0 homogeneity on the basis of the water lineshape, will improve the accuracy of estimation of metabolite concentrations. In-vivo water suppressed/unsuppressed single voxel spectroscopy signals were acquired under three different B0 field homogeneity regimes. Individual realistic basis sets were created for each acquisition. Frequency-domain spectral fitting with LCModel was used to quantify the metabolite concentrations with fitting uncertainties given in terms of the Cramer-Rao lower bound. The quantification results obtained using the water lineshape basis set yielded similar concentrations independent of linewidth and showed a larger fitting error as the linewidth increased. The conventional approach, however quantifies metabolite concentrations with greater variations despite showing a supposedly improved fitting quality. The water lineshape basis set achieved single voxel spectroscopy accuracy that is less sensitive to the linewidth compared to the conventional spectral fitting method for the range of linewidths used in this study, but the precision deteriorated with worsening B0 field inhomogeneity. The beneficial effect was ascribed to a reduction in the number of degrees of freedom when using the water lineshape to generate the basis set.

Implications of the magnetic susceptibility difference between grey and white matter for single-voxel proton spectroscopy at 7 T.

Magnetic susceptibility differences between grey matter (GM) and white matter (WM) can potentially affect lineshapes and chemical shifts in single-voxel spectroscopy. This study aimed to investigate the consequences and potential utility of these effects. Spectroscopy voxels were segmented into GM, WM, and cerebrospinal fluid based on T1-weighted images. GM and WM lineshapes were computed using multi-echo gradient-echo images to measure the frequency distribution. Twenty 7 Tesla single voxel spectra with corresponding T1-weighted images were acquired from the frontal and parietal lobes from five healthy human volunteers. Consistent frequency shifts (mean [±SD] 4.9 ±â€¯2.0 Hz) and linewidth differences (2.4 ±â€¯1.5 Hz) between the two tissue types were observed. Directly visible metabolites (creatine, choline, and myo-inositol) exhibited frequency shifts and linewidth differences that were consistent with a linear-weighted summation of their expected GM and WM distribution ratios. The magnetic susceptibility difference between GM and WM had a detectable effect on single-voxel proton spectra, which results in both frequency shifts and lineshape broadening. This effect can be used to estimate the relative metabolic distribution in the GM and WM for directly observable metabolites. Fractional distributions estimated with this method demonstrated good agreement with literature values for the selected metabolites.

Aerobic Activity in the Healthy Elderly Is Associated with Larger Plasticity in Memory Related Brain Structures and Lower Systemic Inflammation.

Cognitive abilities decline over the time course of our life, a process, which may be mediated by brain atrophy and enhanced inflammatory processes. Lifestyle factors, such as regular physical activities have been shown to counteract those noxious processes and are assumed to delay or possibly even prevent pathological states, such as dementing disorders. Whereas the impact of lifestyle and immunological factors and their interactions on cognitive aging have been frequently studied, their effects on neural parameters as brain activation and functional connectivity are less well studied. Therefore, we investigated 32 healthy elderly individuals (60.4 ± 5.0 SD; range 52-71 years) with low or high level of self-reported aerobic physical activity at the time of testing. A higher compared to a lower level in aerobic physical activity was associated with an increased encoding related functional connectivity in an episodic memory network comprising mPFC, thalamus, hippocampus precuneus, and insula. Moreover, encoding related functional connectivity of this network was associated with decreased systemic inflammation, as measured by systemic levels of interleukin 6.

Sleep supports selective retention of associative memories based on relevance for future utilization.

An outstanding question is whether memory consolidation occurs passively or involves active processes that selectively stabilize memories based on future utility. Here, we differentially modulated the expected future relevance of two sets of picture-location associations after learning. Participants first studied two sets of picture-location associations. After a baseline memory test, they were instructed that only one set of associations would be retested after a 14-hour delay. For half of the participants, this test-retest delay contained a night of sleep; for the other half the delay included a normal working day. At retest, participants were re-instructed and against their expectations tested on both sets of associations. Our results show that post-learning instruction about subsequent relevance selectively improves memory retention for specific associative memories. This effect was sleep-dependent; it was present only in the group of subjects for which the test-retest delay contained sleep. Moreover, time spent asleep for participants in this sleep group correlated with retention of relevant but not irrelevant associations; participants who slept longer forgot fewer associations from the relevant category. In contrast, participants that did not sleep forgot more relevant than irrelevant associations across the test-retest delay. In summary, our results indicate that it is possible to modulate the retention of selected memories after learning with simple verbal instructions on their future relevance. The finding that this effect depends on sleep demonstrates this state's active role in memory consolidation and may have utility for educational settings.