Biology subjects

Naim-Feil, J.

Publications and source records attributed to Naim-Feil, J..

4 recordsLinked to original sources

bioRxiv2026

Characterising cortical perturbation-recovery dynamics using TMS-EEG: The Brain Dynamic Toolbox

Objective: To adapt dynamical measures used in computational and experimental perturbation models to human transcranial magnetic stimulation and electroencephalography (TMS-EEG) and determine whether analysis of the extended post-stimulation trajectory reveals additional features of the cortical response to long-interval intracortical inhibition (LICI). Methods: Single pulse and paired pulse LICI TMS-EEG responses from the bilateral dorsolateral prefrontal cortex were re-analysed in 16 healthy adults. At the stimulation site, 75 single-pulse and 75 paired-pulse trials were delivered; paired pulses comprised conditioning and test stimuli separated by 100 ms. Responses from 20 frontocentral EEG channels were analysed from 50-950 ms following TMS using the open source Brain Dynamic Metric Toolbox. Perturbative Integration Latency Index (PILI) indexed cortical resilience via response energy and recovery, Autocorrelation Function Width (ACFW) captured temporal memory, and Lyapunov Exponent (LE) indicated the dynamical stability. Linear mixed-effects models examined temporal, spectral, and time-frequency effects from the measured metrics. Results: LICI altered the temporal evolution of the dynamical measures. PILI distinguished conditions in the earliest post-stimulation window before converging, whereas ACFW differences persisted across a broader early interval. LE showed weaker and less consistent discrimination. Spectral effects were most evident for ACFW, while time-frequency analyses revealed later, frequency-specific LICI effects for PILI and ACFW but not LE. Conclusions: The extended post-stimulation trajectory revealed LICI-related differences in cortical resilience and temporal memory with distinct temporal and spectral profiles, while effects on dynamical stability were less consistent. Significance: The Brain Dynamic Metric Toolbox provides a reproducible framework for quantifying perturbation-recovery dynamics in TMS-EEG and demonstrates that the extended perturbational response contains information about LICI not captured by discrete early response measures.

neuroscience↗

bioRxiv2026

Multiday rhythms modulate human heart rate: an observational study in healthy adults

BackgroundChronobiology research has historically focused on circadian rhythms; however, longer infradian rhythms are prevalent in human physiology and may have important implications for health and wellbeing. Previous studies have identified widespread infradian rhythms across human physiology, often in the context of hormonal regulation and disease. Despite growing evidence of their ubiquity, the mechanisms, significance, and clinical relevance of these rhythms remain poorly understood, largely due to lack of longitudinal datasets and robust detection methods. The emergence of new wearable technologies enables rich, continuous data capture within individuals, allowing physiological rhythms to be studied at scale. MethodsThis study analyzed a cohort of healthy, young adults (N=623), with up to four years of wearable and questionnaire data collected through the University of Notre Dames (USA) NetHealth project. Participants who recorded at least three months of continuous (>80% adherence) heart rate data were included and significant infradian rhythms were identified using wavelet analysis. Unsupervised non-negative matrix factorization was performed to cluster similar wavelet power spectrum distributions. Individuals heart rate rhythms were compared to known environmental cycles (day-of-week, lunar, seasonal) and considering demographics and social networks. A second, smaller cohort (N=70) with heart rate and menstrual timing were included to analyze the interplay of hormonal regulation on monthly cycles. Multinomial logistic regression, and statistical tests (i.e., one-way ANOVA) were applied to quantify the effects of environmental, behavioral and demographic factors on heart rate rhythms. FindingsSignificant infradian rhythms of heart rate were detected in 69.7% (365/523) of the cohort and 35.9% (188/523) had two or more rhythms. Annual, biannual and 10-week rhythms were the most common. Within the 4-45-day band, individuals clustered into four multiday chronotypes based on dominant periodicities in their wavelet power spectra: weekly ([~]7 days), shorter-monthly ([~]25 days), longer-monthly ([~]35 days), and multi-month (>35 days). Heart rate rhythms were influenced by environmental cycles (day-of-week and seasonality) but were not tightly correlated to external cues. Additionally, heart rate rhythms were synchronized to the menstrual cycle in most menstruating females, although monthly rhythms were also observed in males and menopausal women. InterpretationThe prevalence of infradian, or multiday heart rate rhythms in healthy young people motivates further scientific investigation to understand the mechanisms of these rhythms and their potential association with autonomic function, and risk of disease or disease-specific symptoms. Characterizing physiological rhythms can drive new insights into how multiscale fluctuations modulate disease symptoms across neurological, psychiatric, and broader health conditions.

physiology↗

bioRxiv2020

Variability of dynamic patterns of cortical excitability in schizophrenia: A test-retest TMS-EEG study

BackgroundAltered stimuli processing is a key feature of schizophrenia. Application of concurrent transcranial magnetic stimulation (TMS) with electroencephalography (TMS-EEG) is an effective stimulus which allows direct measurement of the cortical response within a millisecond time resolution. Test-retest TMS-EEG studies present evidence of high reproducibility in healthy controls (HC), however, this stability of response has not been examined in schizophrenia. ObjectiveThe current study maps TMS-evoked patterns of cortical excitability in schizophrenia and examine whether these cortical patterns are amenable to change as symptoms of schizophrenia improve. MethodsOne hundred single-pulse TMS and 100 sham pulses were applied to frontal regions of 19 schizophrenia in-patients and 26 HC while electroencephalography data were simultaneously acquired. Medication and schizophrenia symptoms were reported. This protocol was repeated across three sessions (1 week apart) for each participant. The TMS-evoked cortical response of each participant was averaged and compared between groups. ResultsSchizophrenia patients showed reduced cortical excitability at early time-windows and increased excitability at later time-windows. Increased excitability at later windows was associated with heightened symptom severity. Schizophrenia patients showed an increased variability in cortical response over sessions relative to HC. Increased change in cortical response from session 1 to session 3 correlated with symptom improvement. ConclusionsSchizophrenia patients presented with abnormal patterns of cortical excitability when processing TMS stimuli. These dynamic patterns of cortical response were amenable to change as symptoms of schizophrenia improved. Further research into electrophysiological biomarkers of symptom improvement is hoped to improve current diagnosis and treatment models of schizophrenia.

neuroscience↗

bioRxiv2019

Phase-amplitude markers of synchrony and noise: A resting-state and TMS-EEG study of schizophrenia

The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity we used three weekly sessions and analyzed both resting state and TMS-EEG data. For the TMS responses our analysis verifies known results. For the resting state we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha and beta resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally and temporally correlated activity is reduced in schizophrenia, a conclusion that is in accord with previous experiments on TMS-EEG and on resting-state EEG.

neuroscience↗