An energy costly architecture of neuromodulators for human brain evolution and cognition.

In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

The physiological effects of noninvasive brain stimulation fundamentally differ across the human cortex.

Transcranial magnetic stimulation (TMS) is a noninvasive method to modulate brain activity and behavior in humans. Still, stimulation effects substantially vary across studies and individuals, thereby restricting the large-scale application of TMS in research or clinical settings. We revealed that low-frequency stimulation had opposite impact on the functional connectivity of sensory and cognitive brain regions. Biophysical modeling then identified a neuronal mechanism underlying these region-specific effects. Stimulation of the frontal cortex decreased local inhibition and disrupted feedforward and feedback connections. Conversely, identical stimulation increased local inhibition and enhanced forward signaling in the occipital cortex. Last, we identified functional integration as a macroscale network parameter to predict the region-specific effect of stimulation in individual subjects. In summary, we revealed how TMS modulation critically depends on the connectivity profile of target regions and propose an imaging marker to improve sensitivity of noninvasive brain stimulation for research and clinical applications.

Intranetwork and Internetwork Effects of Navigated Transcranial Magnetic Stimulation Using Low- and High-Frequency Pulse Application to the Dorsolateral Prefrontal Cortex: A Combined rTMS-fMRI Approach.

PURPOSE: Although transcranial magnetic stimulation (TMS) is routinely applied in neuroscience and clinical settings, not much is known about its effects on brain networks. Therefore, this pilot study was set up using repetitive navigated transcranial magnetic stimulation (rTMS) combined with resting-state functional MRI (rs-fMRI) to explore frequency-dependent stimulation effects on an intranetwork and internetwork level. METHODS: Six healthy subjects (median age: 23.5 years) underwent two rTMS sessions (1 and 10 Hz), 7 days apart, and prestimulation and poststimulation rs-fMRI. Repetitive navigated transcranial magnetic stimulation was delivered to the left dorsolateral prefrontal cortex, with the exact stimulation target being determined by independent component analysis. Alterations of functional connectivity strength were evaluated using seed-based correlation analyses within and between the salience network, central executive network, and posterior and anterior default mode network. RESULTS: Low-frequency rTMS resulted in significant intranetwork alterations only for the anterior default mode network and primarily within the left hemisphere. In contrast, high-frequency rTMS led to changes within all four networks of interest. Moreover, the posterior and anterior default mode network largely showed opposite effects to rTMS, and the anterior default mode network was rather isolated from the other networks, which was especially true for low-frequency rTMS. Changes in functional connectivity strength because of low-frequency rTMS were even detectable 7 days after stimulation. CONCLUSIONS: This is one of the first studies using neuronavigated TMS with independent component analysis-based target selection to explore frequency-dependent stimulation effects in a combined rTMS-fMRI approach. Future studies including higher subject numbers may define the underlying mechanisms for the different responses to low- and high-frequency rTMS.

State and trait characteristics of anterior insula time-varying functional connectivity.

The human anterior insula (aINS) is a topographically organized brain region, in which ventral portions contribute to socio-emotional function through limbic and autonomic connections, whereas the dorsal aINS contributes to cognitive processes through frontal and parietal connections. Open questions remain, however, regarding how aINS connectivity varies over time. We implemented a novel approach combining seed-to-whole-brain sliding-window functional connectivity MRI and k-means clustering to assess time-varying functional connectivity of aINS subregions. We studied three independent large samples of healthy participants and longitudinal datasets to assess inter- and intra-subject stability, and related aINS time-varying functional connectivity profiles to dispositional empathy. We identified four robust aINS time-varying functional connectivity modes that displayed both "state" and "trait" characteristics: while modes featuring connectivity to sensory regions were modulated by eye closure, modes featuring connectivity to higher cognitive and emotional processing regions were stable over time and related to empathy measures.

Opposite Dynamics of GABA and Glutamate Levels in the Occipital Cortex during Visual Processing.

Magnetic resonance spectroscopy (MRS) measures the two most common inhibitory and excitatory neurotransmitters, GABA and glutamate, in the human brain. However, the role of MRS-derived GABA and glutamate signals in relation to system-level neural signaling and behavior is not fully understood. In this study, we investigated levels of GABA and glutamate in the visual cortex of healthy human participants (both genders) in three functional states with increasing visual input. Compared with a baseline state of eyes closed, GABA levels decreased after opening the eyes in darkness and Glx levels remained stable during eyes open but increased with visual stimulation. In relevant states, GABA and Glx correlated with amplitude of fMRI signal fluctuations. Furthermore, visual discriminatory performance correlated with the level of GABA, but not Glx. Our study suggests that differences in brain states can be detected through the contrasting dynamics of GABA and Glx, which has implications in interpreting MRS measurements.SIGNIFICANCE STATEMENT GABA and glutamate are the two most abundant neurotransmitters in human brain. Their interaction, known as inhibitory-excitatory balance, plays a crucial role in establishing spontaneous and stimulus-driven brain activity. Yet, the relationship between magnetic resonance spectroscopy (MRS)-derived levels of both metabolites and fMRI is still a matter of dispute. In this work, we study GABA and glutamate in three states of visual processing and in relation to fMRI and visual discriminatory performance in healthy people. We found that states of visual processing can be detected through the contrasting dynamics of GABA and glutamate and their correlation with fMRI signals. We also demonstrated that GABA, but not glutamate, in the visual system predicts visual performance. Our results provide insights into MRS-derived GABA and glutamate measurements.