Network-targeted transcranial direct current stimulation of the hypothalamus appetite-control network: a feasibility study.
Theresa EsterKatharina BertiRalf VeitCorinna DanneckerRicardo SalvadorGiulio RuffiniMartin HeniAndreas L BirkenfeldChristian PlewniaHubert PreißlStephanie KullmannPublished in: Scientific reports (2024)
The hypothalamus is the key regulator for energy homeostasis and is functionally connected to striatal and cortical regions vital for the inhibitory control of appetite. Hence, the ability to non-invasively modulate the hypothalamus network could open new ways for the treatment of metabolic diseases. Here, we tested a novel method for network-targeted transcranial direct current stimulation (net-tDCS) to influence the excitability of brain regions involved in the control of appetite. Based on the resting-state functional connectivity map of the hypothalamus, a 12-channel net-tDCS protocol was generated (Neuroelectrics Starstim system), which included anodal, cathodal and sham stimulation. Ten participants with overweight or obesity were enrolled in a sham-controlled, crossover study. During stimulation or sham control, participants completed a stop-signal task to measure inhibitory control. Overall, stimulation was well tolerated. Anodal net-tDCS resulted in faster stop signal reaction time (SSRT) compared to sham (p = 0.039) and cathodal net-tDCS (p = 0.042). Baseline functional connectivity of the target network correlated with SSRT after anodal compared to sham stimulation (p = 0.016). These preliminary data indicate that modulating hypothalamus functional network connectivity via net-tDCS may result in improved inhibitory control. Further studies need to evaluate the effects on eating behavior and metabolism.
Keyphrases
- transcranial direct current stimulation
- functional connectivity
- resting state
- working memory
- weight loss
- double blind
- metabolic syndrome
- type diabetes
- randomized controlled trial
- cancer therapy
- parkinson disease
- physical activity
- weight gain
- body mass index
- deep learning
- multiple sclerosis
- minimally invasive
- transcription factor
- electronic health record
- body weight
- machine learning
- blood brain barrier
- big data
- drug delivery
- adipose tissue
- combination therapy