Wolf-Julian Neumann
@julianneumann.bsky.social
Associate Professor für invasive neurotechnology, interested in dopamine, brain signal decoding and connectomics. Reach me electronically via @charite.de but add julian.neumann before that.
Charité - Universitätsmedizin Berlin
Opinions my own.
Charité - Universitätsmedizin Berlin
Opinions my own.
This has been a huge collaborative effort across Berlin, Boston and Beijing. I am truly grateful for the fantastic team spirit that has allowed us to develop this platform together.
a cartoon of tweety and jerry saying they are a team .
ALT: a cartoon of tweety and jerry saying they are a team .
media.tenor.com
September 24, 2025 at 12:01 PM
This has been a huge collaborative effort across Berlin, Boston and Beijing. I am truly grateful for the fantastic team spirit that has allowed us to develop this platform together.
The bigger picture: AI + connectomics are reshaping neurotechnology. Have a look at our recent perspective in Nature Reviews Neurology www.nature.com/articles/s41...
From adaptive deep brain stimulation to adaptive circuit targeting - Nature Reviews Neurology
Deep brain stimulation (DBS) is a highly effective treatment option for movement disorders and is also being explored for other brain disorders. This Perspective proposes a unified framework, termed adaptive circuit targeting, which combines adaptive and connectomic DBS to enable decoding of symptom severity from brain signals and activation of relevant symptom-response circuits.
www.nature.com
September 24, 2025 at 12:01 PM
The bigger picture: AI + connectomics are reshaping neurotechnology. Have a look at our recent perspective in Nature Reviews Neurology www.nature.com/articles/s41...
Inspired by @andreashorn.org, the core is connectomics-informed decoding: each electrode contact is mapped to a “fingerprint” of whole-brain connectivity, which predicts decoding performance. This enables out-of-cohort generalization without patient-specific training. is the innovator.
September 24, 2025 at 12:01 PM
Inspired by @andreashorn.org, the core is connectomics-informed decoding: each electrode contact is mapped to a “fingerprint” of whole-brain connectivity, which predicts decoding performance. This enables out-of-cohort generalization without patient-specific training. is the innovator.
For epilepsy, we optimized seizure detection using AI-guided parameter discovery. Connectomics revealed a distributed seizure network (hippocampus, cingulate, occipital cortex), enabling more accurate, personalized detection. Our parameters were constrained to device capabilities.
September 24, 2025 at 12:01 PM
For epilepsy, we optimized seizure detection using AI-guided parameter discovery. Connectomics revealed a distributed seizure network (hippocampus, cingulate, occipital cortex), enabling more accurate, personalized detection. Our parameters were constrained to device capabilities.
In depression, we decoded emotional states from the subgenual cingulate. Better decoding correlated with clinical outcomes after DBS, and network maps aligned with known TMS targets. A link between invasive decoding and non-invasive therapy for the next-generation of AI inspired neuromodulation.
September 24, 2025 at 12:01 PM
In depression, we decoded emotional states from the subgenual cingulate. Better decoding correlated with clinical outcomes after DBS, and network maps aligned with known TMS targets. A link between invasive decoding and non-invasive therapy for the next-generation of AI inspired neuromodulation.
For movement disorders, connectomics-informed decoders generalized across Parkinson’s and epilepsy patients. Plug-and-play decoding without per-patient calibration triggered adaptive DBS in a newly recruited patient. #cebra outperformed other decoder architectures.
September 24, 2025 at 12:01 PM
For movement disorders, connectomics-informed decoders generalized across Parkinson’s and epilepsy patients. Plug-and-play decoding without per-patient calibration triggered adaptive DBS in a newly recruited patient. #cebra outperformed other decoder architectures.
Traditional brain–computer interfaces (BCIs) often need individual retraining for every patient. Our approach shows that generalizable decoders can work across cohorts in Europe, the US, and China—sometimes even outperforming individual models. The platform translates offline data to real-time.
September 24, 2025 at 12:01 PM
Traditional brain–computer interfaces (BCIs) often need individual retraining for every patient. Our approach shows that generalizable decoders can work across cohorts in Europe, the US, and China—sometimes even outperforming individual models. The platform translates offline data to real-time.
Reposted by Wolf-Julian Neumann
Reduced function or injury to the frontal pole may increase creativity by disengaging the self-monitoring & cognitive control actions of the frontal pole to allow novelty seeking & creativity to be unleashed. @braincircuits.bsky.social @foxmdphd.bsky.social @julianneumann.bsky.social
February 13, 2025 at 4:13 PM
Reduced function or injury to the frontal pole may increase creativity by disengaging the self-monitoring & cognitive control actions of the frontal pole to allow novelty seeking & creativity to be unleashed. @braincircuits.bsky.social @foxmdphd.bsky.social @julianneumann.bsky.social