In Alzheimer's disease (AD), the loss of cerebral connectivity has been evidenced by numerous studies. There is growing evidence of attention related failures already in prodromal stages of AD; however, connectivity changes within attention networks have been rarely reported. Here we focused on effective connectivity of top-down attention control in patients with prodromal Alzheimer's disease (pAD). We scanned 15 pAD patients and 16 healthy elderly using the Attentional Network Task and determined effective connectivity within a cingulo-fronto-parietal network using Dynamic Causal Modeling. We related connectivity parameters to structural and behavioral parameters (gray matter volume as well as reaction time) to examine the relation between affected domains. Our analyses revealed that effective connectivity from the right middle frontal gyrus to the left superior parietal cortex as well as from the right to the left superior parietal gyrus was reduced in pAD patients. Furthermore, we found that, effective connectivity varied as a function of GM volume in the patient group: right middle frontal gray matter volume significantly correlated with connectivity from the right parietal cortex to the right middle frontal gyrus as well as from the middle frontal gyrus to the anterior cingulate cortex. In addition, inter-parietal connectivity was correlated to right and left parietal gray matter volume. We conclude that, at very early stages of AD, the reduction of effective connectivity in fronto-parietal circuits is related to regional gray matter volume and contributes to impairments in top-down attentional control.

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In rodents, the five-choice serial reaction time task (5-CSRTT) has been established as a reliable measure of waiting impulsivity being defined as the ability to regulate a response in anticipation of reinforcement. Key brain structures are the nucleus accumbens (NAcc) and prefrontal regions (for example, pre- and infralimbic cortex), which are, together with other transmitters, modulated by serotonin. In this functional magnetic resonance imaging study, we examined 103 healthy males while performing the 5-CSRTT measuring brain activation in humans by means of a paradigm that has been widely applied in rodents. Subjects were genotyped for the tryptophan hydroxylase-2 (TPH2; G-703T; rs4570625) variant, an enzyme specific for brain serotonin synthesis. We addressed neural activation patterns of waiting impulsivity and the interaction between the NAcc and the ventromedial prefrontal cortex (vmPFC) using dynamic causal modeling. Genetic influence was examined via interaction analyses between the TPH2 genotype (GG homozygotes vs T allele carriers) and the degree of impulsivity as measured by the 5-CSRTT. We found that the driving input of the vmPFC was reduced in highly impulsive T allele carriers (reflecting a reduced top-down control) in combination with an enhanced response in the NAcc after correct target processing (reflecting an augmented response to monetary reward). Taken together, we found a high overlap of our findings with reports from animal studies in regard to the underlying cognitive processes, the brain regions associated with waiting impulsivity and the neural interplay between the NAcc and vmPFC. Therefore, we conclude that the 5-CSRTT is a promising tool for translational studies.

Fractal phenomena can be found in numerous scientific areas including neuroscience. Fractals are structures, in which the whole has the same shape as its parts. A specific structure known as pink noise (also called fractal or 1/f noise) is one key fractal manifestation, exhibits both stability and adaptability, and can be addressed via the Hurst exponent (H). FMRI studies using H on regional fMRI time courses used fractality as an important characteristic to unravel neural networks from artificial noise. In this fMRI-study, we examined 103 healthy male students at rest and while performing the 5-choice serial reaction time task. We addressed fractality in a network associated with waiting impulsivity using the adaptive fractal analysis (AFA) approach to determine H. We revealed the fractal nature of the impulsivity network. Furthermore, fractality was influenced by individual impulsivity in terms of decreasing fractality with higher impulsivity in regions of top-down control (left middle frontal gyrus) as well as reward processing (nucleus accumbens and anterior cingulate cortex). We conclude that fractality as determined via H is a promising marker to quantify deviations in network functions at an early stage and, thus, to be able to inform preventive interventions before the manifestation of a disorder.

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