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.

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.

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.

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Humans spend more energy on the brain than any other species. However, the high energy demand cannot be fully explained by brain size scaling alone. We hypothesized that energy-demanding signaling strategies may have contributed to human cognitive development. We measured the energy distribution along signaling pathways using multimodal brain imaging and found that evolutionarily novel connections have up to 67% higher energetic costs of signaling than sensory-motor pathways. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an upregulation of signaling at G-protein coupled receptors in energy-demanding regions. We found that neuromodulators are predominantly involved in complex cognition such as reading or memory processing. Our study suggests that the upregulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

Abbreviations 17Anterior insula = aINS; BOLD = blood oxygen level dependent; inferior frontal gyrus = IFG; task-free 18 functional MRI = tf-fMRI

Non-invasive brain stimulation reliably modulates brain activity and symptoms of neuropsychiatric disorders. However, stimulation effects substantially vary across individuals and brain regions. We combined transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) to investigate the neuronal basis of inter-individual and inter-areal differences after TMS. We found that stimulating sensory and cognitive areas yielded fundamentally heterogeneous effects. Stimulation of occipital cortex enhanced brain-wide functional connectivity and biophysical modeling identified increased local inhibition and enhanced forward-signaling after TMS. Conversely, frontal stimulation decreased functional connectivity, associated with local disinhibition and disruptions of both feedforward and feedback connections. Finally, we identified brain-wide functional integration as a predictive marker for these heterogeneous stimulation effects in individual subjects.Together, our study suggests that modeling of local and global signaling parameters of a target area will improve the specificity of non-invasive brain stimulation for research and clinical applications.

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