Frontiers in Neuroscience

BackgroundMotor threshold (MT) estimation is fundamental to transcranial magnetic stimulation (TMS), guiding individualized stimulation intensity in research and therapy. Conventional methods such as the 5-out-of-10 rule require many stimuli, while adaptive approaches like Parameter Estimation by Sequential Testing (PEST) improve efficiency but can exhibit poor convergence under certain conditions. ObjectiveThis study introduces the Bayesian Uncertainty Dynamic Algorithm for Parameter Estimatio...

ObjectiveWe developed and validated a detection-guided artifact removal framework for clinical electroencephalography (EEG). It corrects only the contaminated segments and preserves artifact-free data. ApproachThe framework employs convolutional neural network (CNN) detectors trained on the Temple University Hospital (TUH) Artifact Corpus of 150 recordings from 105 patients. For eye movement artifacts (20 second windows), it uses independent component analysis (ICA) and canonical correlation an...

The neural signature of rhythm and tempo remains difficult to study in both humans and non-human primates. Here we recorded from the motor cortex of human participants implanted with intracortical microelectrode arrays while they performed a series of rhythmic tapping tasks. We found that rhythmic tapping elicited low-dimensional rotational neural dynamics whose radii varied in a tempo-dependent manner and axes related to kinematic properties. Moreover, we observed a spectrum of kinematic and ne...

BackgroundAuditory steady-state responses (ASSRs) provide an objective method for estimating hearing thresholds in individuals unable to provide behavioural responses. Bone conduction (BC) testing is required to differentiate conductive from sensorineural hearing loss. Accurate BC ASSR threshold estimation relies on "correction" factors, which are not yet well established. This meta-analysis evaluated the reliability of BC ASSR thresholds to estimate hearing thresholds at 500, 1000, 2000 and 400...

Restoring communication for people with dysarthria secondary to pontine stroke remains a critical challenge. Intracortical brain-computer interfaces (iBCIs) have demonstrated great potential for speech restoration in people with amyotrophic lateral sclerosis (ALS), with 1-24% word error rates (WERs) on a 125,000-word vocabulary. In pontine stroke, electrocorticography (ECoG) BCIs achieved 25.5% WERs with a smaller 1,024-word vocabulary. Whether intracortical BCI performance improvements extend t...

BackgroundTinnitus affects a substantial proportion of the global population and can severely disrupt sleep, mood, and daily functioning, yet the quality of mobile health apps designed for tinnitus management remains highly variable. Traditional evaluation methods, including clinical trials, expert rating scales, and small-scale surveys, rarely capture large-scale, feature-level feedback from real-world users, leaving a gap in understanding which app characteristics drive sustained engagement an...

INTRODUCTIONConnected speech analyses can help characterize linguistic impairments in primary progressive aphasia (PPA) and classify variants, however, manual transcription of speech samples is time-consuming and expensive. Automated speech recognition (ASR) may be efficacious for transcribing PPA speech. METHODSTranscripts of picture descriptions (109 PPA, 32 healthy controls (HC)) were generated using a manual, automated (Whisper) or semi-automated approach including a quality control (QC) st...

Sensory organization at the spinal segment level is commonly inferred from dermatomal maps that assume a fixed correspondence between cutaneous regions and spinal segments. However, based on the complexities of spinal neuroanatomy and neurophysiology, the distribution of sensory signals within the cord may be broader and less segment-specific than dermatomal maps suggest, leaving the segment-level localization of sensory-evoked activity in humans uncertain. Spinal cord functional magnetic resona...

Effective connectivity of the human insula, mainly assessed at rest using cortico-cortical evoked potentials (CCEPs), is not yet fully characterized at high-resolution. Here, we significantly extend prior CCEP studies of the insula by leveraging an extensive multicenter CCEP database and fine-grained anatomical atlases of the insula. We analyzed CCEP datasets from 897 patients with refractory focal epilepsy (459 females, age: 26{+/-}14 years) explored by stereo electroencephalography and with a...

BackgroundArtificial Intelligence (AI) based approaches to speech analysis have the potential to assist with objective speech error analysis in aphasia but off-the shelf tools often fail to detect speech errors due to prioritizing "fluent transcription." Speech production errors (dysfluencies) are hallmark diagnostic features of the nonfluent (nfvPPA) and logopenic (lvPPA) variants of primary progressive aphasia, yet they can be challenging to detect and characterize even by expert clinicians. T...

IntroductionSleep spindles are electroencephalographic elements characteristic of non-rapid eye movement sleep generated by thalamo-cortical interactions. Spindles have been linked to some of the cognitive benefits afforded by sleep and high spindle activity is associated with increased arousal threshold (deeper sleep). Here, we demonstrate that targeting the thalamus with Transcranial Electrical Stimulation with Temporal Interference (TES-TI) can enhance spindle activity. Methods24 participant...

PurposeNeonatal imaging is particularly challenging because newborns have a high likelihood of head motion, which can degrade image quality and complicate interpretation. Improving MRI brain image quality may help reduce diagnostic uncertainty and facilitate the nuanced assessment of early myelinating structures in the neonatal brain. Although deep learning reconstruction algorithms designed to improve MRI image quality have been evaluated in pediatric imaging, they have not been specifically st...

Chemical shift-encoded magnetic resonance imaging using high-resolved 3D Dixon techniques enables the non-invasive and radiation-free assessment of whole-body adipose tissue and ectopic fat distribution. Automatic deep learning-based segmentation of metabolically relevant adipose tissue compartments and ectopic fat deposits in parenchymal tissue is the most important image processing step for the quantification of adipose tissue volumes and ectopic fat percentages from whole-body imaging. This ...

ObjectiveDespite substantial variability in the severity of post-anoxic encephalopathy, all comatose patients after cardiac arrest are usually treated according to the same standardized intensive care protocol, including sedation, mechanical ventilation, and targeted temperature management (TTM). We hypothesize that patients with a favourable EEG pattern (continuous EEG within 12 hours after cardiac arrest) may not benefit from prolonged sedation and TTM. We studied the feasibility and safety of...

A critical challenge in endocrine neurosurgery is intraoperative discrimination between normal pituitary tissue and pituitary neuroendocrine tumors (PitNETs). Suggesting the universal persistence of near-infrared autofluorescence (NIRAF) in endocrine organs and inspired by routine clinical use of NIRAF for parathyroid gland identification, we discovered that pituitary NIRAF can be employed for label-free transsphenoidal surgery guidance. Ex vivo confocal spectral imaging of 33 specimens identifi...

About half of patients who undergo epilepsy surgery for drug-resistant epilepsy have seizure recurrence, supporting the need for approaches that more accurately identify the epileptogenic zone, defined as the brain areas whose removal causes cessation of seizures. Altered network connectivity has emerged as a candidate biomarker of the epileptogenic zone, but how connectivity is altered in the epileptogenic zone remains uncertain, with prior studies reporting inconsistent results. We hypothesize...

In this randomized, double-blind, controlled trial of 8 weeks of repetitive transcranial magnetic stimulation (rTMS) for chronic pain, we compared the classic primary motor cortex (M1) rTMS with a novel target-selection strategy based on pre-therapy cortical connectivity. Guided by principles of homeostatic plasticity, we tested whether stimulating the cortical site with the lowest pre-therapy global connectivity would be more effective than two active comparators: stimulating the site with the ...

ObjectiveQuantitative assessment of extent of tissue resection following epilepsy surgery requires accurate delineation of the resection cavity on postoperative MRI. Current methods for resection cavity masking are time-consuming and labour-intensive, while existing automated approaches exhibit variable segmentation accuracy, particularly on extra-temporal resections. We developed MELD-PostOp, a deep learning tool trained and evaluated on a large, international, heterogeneous cohort to automatic...

BackgroundDeep brain stimulation has emerged as an effective investigational treatment for select cases of severe Gilles de la Tourette Syndrome. Defining the optimal stimulation sites within different targets and the specific tic improvement network across targets will be important to guide neuromodulation therapies. MethodsThis retrospective multi-center cohort study analyzed stimulation locations in patients who received bilateral deep brain stimulation for Gilles de la Tourette Syndrome acr...

Visual Snow Syndrome (VSS) is a neurological condition characterized by continuous visual disturbances resembling television static across the visual field. Despite its significant impact on quality of life, objective assessment methods remain limited, with diagnosis relying primarily on subjective patient reports. Current understanding of VSS pathophysiology suggests cortical hyperexcitability, but precise mechanisms remain unclear. Here we developed an integrated protocol combining transcrania...