In humans, food is considered a powerful primary reinforcer, whereas money is a secondary reinforcer, as it gains a value through learning experience. Here, we aimed to identify the neural regions supporting the processing of food-related reinforcers, relate it to the neural underpinnings of monetary reinforcers, and explore their modulation by metabolic state (hunger vs satiety). Twenty healthy male participants were tested in two experimental sessions, once hungry and once satiated, using functional magnetic resonance imaging. Participants performed an associative learning task, receiving food or monetary rewards (in the form of images) on separate blocks. Irrespective of incentive type, both food and monetary rewards engaged ventral striatum, medial orbitofrontal cortex and amygdala, regions that have been previously associated with reward processing. Food incentives additionally engaged the opercular part of the inferior frontal gyrus and the insula, collectively known as a primary gustatory cortex. Moreover, in response to negative feedback (here, reward omission), robust activation was observed in anterior insula, supplementary motor area and lateral parts of the prefrontal cortex, including middle and inferior frontal gyrus. Furthermore, the interaction between metabolic state and incentive type resulted in supramarginal gyrus (SMG) activity, among other motor and sensory-related regions. Finally, functional connectivity analysis showed correlation in the hungry state between the SMG and mesolimbic regions, including the hippocampus, midbrain and cingulate areas. Also, the interaction between metabolic state and incentive type revealed coupling between SMG and ventral striatum. Whereas general purpose reward-related regions process incentives of different kinds, the current results suggest that the SMG might play a key role in integrating the information related to current metabolic state and available incentive type.
Novelty can promote subsequent long‐term memory via the mesolimbic system, including the medial temporal lobe and midbrain structures. Importantly, these and other brain regions typically degenerate during healthy aging, which suggests a reduced impact of novelty on learning. However, evidence in favor of such a hypothesis is scarce. Thus, we used functional MRI in combination with an established paradigm in healthy young (19–32 years, n = 30) and older (51–81 years, n = 32) humans. During encoding, colored cues predicted the subsequent presentation of either a novel or previously familiarized image (75% cue validity), and approximately 24 h later, recognition memory for novel images was tested. Behaviorally, expected novel images, as compared to unexpected novel images, were better recognized in young and, to a lesser degree, older subjects. At the neural level, familiar cues activated memory related areas, especially the medial temporal lobe, whereas novelty cues activated the angular gyrus and inferior parietal lobe, which may reflect enhanced attentional processing. During outcome processing, expected novel images activated the medial temporal lobe, angular gyrus and inferior parietal lobe. Importantly, a similar activation pattern was observed for subsequently recognized novel items, which helps to explain the behavioral effect of novelty on long‐term memory. Finally, age‐effects were pronounced for successfully recognized novel images with relatively stronger activations in attention‐related brain regions in older adults; younger adults, on the other hand, showed stronger hippocampal activation. Together, expectancy promotes memory formation for novel items via neural activity in medial temporal lobe structures and this effect appears to be reduced with age.
The dendritic pattern defines the input capacity of a neuron. Existing methods such as Golgi impregnation or intracellular staining only label a small number of neurons. By using high-resolution imaging and 3D reconstruction of green fluorescent protein-expressing neurons, the present study provides an approach to investigate the anatomical organization of dendritic structures in defined brain regions. We characterized the structural organization of dendrites in the CA1 region of the mouse hippocampus by analyzing Sholl intersections, dendritic branches, branching and orientation angles of dendrites, and the different types of spine on the dendritic branches. Utilizing this quantitative imaging approach, we show that there are differences in the number of Sholl intersections and in the orientation of apical and basal dendrites of CA1 pyramidal neurons. Performing 3D reconstructions of the CA1 region of the reeler hippocampus, we show that neurons of this mutant display an arbitrary orientation of apical dendrites at angles ranging from -180 to +180 degrees in contrast to wild-type mice that show a preferred orientation angle. This methodology provides a way of analyzing network organization in wild type and mutant brains using quantitative imaging techniques. Here, we have provided evidence that in reeler a sparse, weakly connected network results from the altered lamination of CA1 pyramidal neurons and the variable orientation of their dendrites. Highlights-High-resolution imaging and 3D reconstruction of CA1 pyramidal neurons -Analysis of Sholl intersections -Analysis of the orientation of apical and basal dendrites of CA1 pyramidal neurons -Altered dendrite orientation angle of apical dendrites in reeler mutant mice -More stubby spines compared to thin and mushroom spines in wild-type CA1
BACKGROUND AND OBJECTIVES: Recent models of Alzheimer's Disease (AD) suggest the nucleus basalis of Meynert (NbM) as the origin of structural degeneration followed by the entorhinal cortex (EC). However, the functional properties of NbM and EC regarding amyloid-beta and hyperphosphorylated tau remain unclear. METHODS: We analyzed resting-state (rs)fMRI data with CSF assays from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n=71) at baseline and two years later. RESULTS: At baseline, local activity, as quantified by fractional amplitude of low-frequency fluctuations (fALFF), differentiated between normal and abnormal CSF groups in the NbM but not EC. Further, NbM activity linearly decreased as a function of CSF ratio, resembling the disease status. Finally, NbM activity predicted the annual percentage signal change in EC, but not the reverse, independent from CSF ratio. DISCUSSION: Our findings give novel insights into the pathogenesis of AD by showing that local activity in NbM is affected by proteinopathology and predicts functional degeneration within the EC.
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