Biology subjects

Zaehle, T.

Publications and source records attributed to Zaehle, T..

4 recordsLinked to original sources

bioRxiv2026

Digital-twin optimized transcranial temporal interference electrical stimulation alters rat brain activity patterns and metabolism including deep structures

Non-invasive deep-brain stimulation (DBS) using transcranial alternating current stimulation (tACS) with temporal interference (TI) has emerged as a promising approach for therapeutic applications in motor and neuropsychiatric disorders. Here, we present a preclinical TI tACS protocol for adult rats that follows a systems approach: an anatomically realistic finite-element digital twin of the rat head is used to optimize electrode placement and injected currents for a deep target, and the model predictions are then tested in vivo. We combine, minimal invasive TI tACS with functional MRI (fMRI) to characterize stimulation-related brain-wide neural responses, alterations in functional connectivity, and changes in neurotransmitter levels. The optimized montage targeted in particular the ventral (motor-related) thalamus. Stimulation-evoked fMRI revealed robust bilateral activation across both subcortical and cortical regions, such as the thalamus, hippocampus, amygdala, retrosplenial and anterior cingulate cortex, which, in turn, reflects direct and indirect activations of brain circuitries by TI tACS. Changes in the connectivity patterns during resting-state fMRI were limited (e.g., fimbria of the hippocampus), but partially overlapped with regional stimulation-evoked fMRI. Therefore, we assume only a short-term influence of TI on neural networks following a single stimulation. MR spectroscopy indicated a trend towards an increased glutamate/GABA ratio in the thalamus. Overall, we demonstrate that TI is a feasible and effective approach for non-invasive DBS in rodents, and that digital twin-based optimization combined with in vivo validation provides a workflow towards individualized stimulation and a foundation for future mechanistic and translational studies in disease models.

neuroscience↗

bioRxiv2025

Novelty-dependent enhancement of sustained attention and electrophysiological signatures via transcutaneous auricular vagus nerve stimulation.

BackgroundSustained attention, the ability to remain focused during a task, relies on Locus coeruleus - Noradrenaline (LC-NA) activity. Noninvasive transcutaneous auricular vagus nerve stimulation (taVNS) is a promising tool to modulate LC-NA activity. We investigated the effects of taVNS on behavioral and electrophysiological markers of sustained attention during a Go-Nogo task. MethodsForty-four healthy participants (36 female) performed the gradual-onset Continuous Performance Task (gradCPT) on two days > 24 hours apart while EEG was recorded. 500 ms trains of taVNS or Sham stimulation was applied with each stimulus in a pseudorandomized fashion. Brain activity during the task was recorded with EEG. Behavioral and electrophysiological parameters of sustained attention were analyzed using (generalized) linear mixed models. ResultsWhen delivered during the first session, taVNS accelerated reaction times and enhanced fronto-central P1-N1 and parietal N1-P2 amplitudes. Larger P1-N1 amplitudes predicted faster responses, linking early cortical gain to behavioral performance. RT improvements persisted into the next-day sham session, whereas taVNS applied only during the familiar second session was ineffective. However, taVNS also increased RT variability, speaking against a general beneficial effect of taVNS on response automation. ConclusionWe show that taVNS modulates behavioral and electrophysiologial parameters of sustained attention and that this modulation depended on the applied stimulation order. These observations have important implications for future taVNS studies where the order of stimulation is counterbalanced across subjects.

neuroscience↗

bioRxiv2022

The AI Neuropsychologist: Automatic scoring of memory deficits with deep learning

BackgroundMemory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across the globe to assess the degree of non-verbal visual memory deterioration. To obtain a score, a trained clinician inspects a patients ROCF drawing and quantifies deviations from the original figure. This manual procedure is time-consuming, slow and scores vary depending on the clinicians experience, motivation and tiredness. MethodsHere, we leverage novel deep learning architectures to automatize the rating of memory deficits. For this, we collected more than 20k hand-drawn ROCF drawings from patients with various neurological and psychiatric disorders as well as healthy participants. Unbiased ground truth ROCF scores were obtained from crowdsourced human intelligence. This dataset was used to train and evaluate a multi-head convolutional neural network. ResultsThe model performs highly unbiased as it yielded predictions very close to the ground truth and the error was similarly distributed around zero. The neural network outperforms both online raters and clinicians. The scoring system can reliably identify and accurately score individual figure elements in previously unseen ROCF drawings, which facilitates explainability of the AI-scoring system. To ensure generalizability and clinical utility, the model performance was successfully replicated in a large independent prospective validation study that was pre-registered prior to data collection. ConclusionsOur AI-powered scoring system provides healthcare institutions worldwide with a digital tool to assess objectively, reliably and time-efficiently the performance in the ROCF test from hand-drawn images.

neuroscience↗

bioRxiv2022

Rhythmic interactions between the mediodorsal thalamus and prefrontal cortex precede human visual perception

The thalamus is much more than a simple sensory relay. High-order thalamic nuclei, such as the mediodorsal thalamus, exert a profound influence over animal cognition. However, given the difficulty of directly recording from the thalamus in humans, next-to-nothing is known about thalamic and thalamocortical contributions to human cognition. To address this, we analysed simultaneously-recorded thalamic iEEG and whole-head MEG in six patients (four female, two male; plus MEG recordings from twelve healthy controls) as they completed a visual detection task. We observed that the phase of both ongoing mediodorsal thalamic and prefrontal low-frequency activity was predictive of perceptual performance. Critically however, mediodorsal thalamic activity mediated prefrontal contributions to perceptual performance. These results suggest that it is thalamocortical interactions, rather than cortical activity alone, that is predictive of upcoming perceptual performance and, more generally, highlights the importance of accounting for the thalamus when theorising about cortical contributions to human cognition.

neuroscience↗