Biology subjects

Neff, P.

Publications and source records attributed to Neff, P..

5 recordsLinked to original sources

bioRxiv2026

The hedonic evaluation of neurofeedback stimuli is fast, automatic and implicit: An ERP study on stimulus design.

Introduction - Neurofeedback (NFB) has demonstrated efficacy in treating various disorders, often achieving substantial symptom reductions. Despite its effectiveness, a significant percentage of users (non-responders), fail to benefit from NFB. Addressing this issue, the study at hand investigates the role of NFB design on neuro-physiological responses. Method - event related potentials (ERPs) are examined in response to the application of different aesthetic principles in the context of NFB stimulus design. Drawing from Self-Determination Theory and ERP studies in the field of web design, 16 feedback stimuli were developed according to specific design principles. Stimulus design effects were inspected by means of ERPs allowing for the assessment of implicit and fast electroencephalogram (EEG) reactions. Results of n = 38 participants indicated distinct ERP response patterns at time window of interest 1 (TWOI-1; 100-200 ms) and TWOI-2 (200-300 ms), predicted by beholder-based liking and complexity of stimuli. The findings align with the proposed hypotheses suggesting that aesthetic evaluation of NFB stimuli occurs rapidly and implicitly. In response to the aesthetic vs. non-aesthetic categories, the findings were mixed. The results underscore the importance of further exploration of aesthetic design guidelines in the context of NFB applications. It is discussed how NFB aesthetics relate to Processing Fluency and Affective Prediction Error Theory, while the theoretical methodological issue of the Fixed Effect Fallacy is taken into consideration. The study contributes to the broader understanding of how design elements can affect therapeutic efficacy and engagement in NFB and Human Computer Interaction in therapeutic contexts in general.

neuroscience↗

bioRxiv2025

Frequency-Specific Resting-State MEG Network Characteristics of Tinnitus Patients Revealed by Graph Learning

Tinnitus, the perception of sound without an external source, affects a significant portion of the population, yet its impact on brain communication diagram known as the functional connectome, remains limited. Traditional functional connectivity (FC) methods, such as Pearson correlation, phase lag index and coherence rely on pairwise comparisons and are therefore limited in providing a holistic encoding of FC. Here, we employ an alternative approach to estimate the entire connectivity structure by analyzing all time-courses simultaneously. This approach is robust even for short-duration recordings, facilitating faster functional connectome identification and real-time applications. Using resting-state MEG recordings from controls and individuals with tinnitus, we demonstrated that the learned connectomes outperform correlation-based connectomes in fingerprinting, that is, identifying an individual from test-retest acquisitions. Group-level analysis revealed distinct altered FC in tinnitus across multiple frequency bands, affecting the default mode, auditory, visual, and salience networks, suggesting a reorganization of these large-scale networks beyond auditory areas. Our study reveals that tinnitus presents highly individualized and heterogeneous whole-brain connectome profiles, highlighting the need to focus on individual variability rather than group-level differences to gain a more nuanced understanding of tinnitus. Personalized FC could enable patient-specific tinnitus models, optimizing treatment strategies for individualized care.

neuroscience↗

bioRxiv2024

Prediction of acoustic tinnitus suppression using resting state EEG: An explainable AI approach

Tinnitus, characterized by the perception of sound without an external source, affects a significant portion of the population and can lead to considerable individual suffering, yet understanding of its suppression remains limited. Understanding neural traits of tinnitus suppression may be crucial for developing accurate predictive models in tinnitus research and treatment. This study aims to classify individuals capable of brief acoustic tinnitus suppression (BATS; also known as residual inhibition) based on their independent resting state EEG (n=102), exploring the classifications robustness on various sample splits, and the relevance of resulting specific EEG features in the spirit of explainable AI. A comprehensive set of EEG features, including band power in standard frequency bands, spectral entropy, aperiodic slope and offset of the power spectrum, and connectivity, was included in both sensor and source space. Binary classification of the BATS status was performed using a comprehensive set of standard classifiers and Pearson correlation for feature selection, which addresses multicollinearity, avoiding complex dimensionality reduction techniques. Feature importance was assessed using Gini impurity metrics, allowing interpretation of the directionality of identified neural features. The Random Forest model showed the most consistent performance, with its majority voting mechanism effectively reducing overfitting and providing reliable predictions, and was therefore chosen for subsequent feature interpretation analysis. Our classification task demonstrated high accuracy across the various BATS split thresholds, suggesting that the choice of threshold does not significantly influence the underlying pattern in the data. We achieved classification accuracies of 98% for sensor and source models and 86% for the connectivity model in the main split. Looking at identified important features, our findings align with and extend existing neuroscience research in tinnitus by discovering highly specific and novel neural features in naive resting-state data predictive of BATS. Gamma power is identified as the most important feature in the sensor model, followed by alpha power, which fits current models of sensory processing, prediction, and updating (gamma) as well as inhibitory (alpha) frameworks. The overall spectral shape of the EEG power spectrum tends to be more normal in +BATS individuals, as reflected in the aperiodic offset and slope features. In the source model, important features are lateralized in that the gamma feature is more prominent in the left core auditory network, whereas the alpha feature is distributed more sparsely over the right hemisphere in line with auditory attention data. Furthermore, we identified several hotspots in the temporal, insular, parietal, parahippocampal, medial prefrontal, and (posterior) cingulate cortex implicated in sensory processing, gating, attention, and memory processes. Relevant network features were found in a hyperconnected bilateral auditory network (within the network), while the full auditory network was hyperconnected to limbic regions (between networks), which may reflect an intact sensory gating mechanism aiding tinnitus suppression. This studys implications extend to improving the understanding and prediction of tinnitus loudness perception and tinnitus distress as well as its (acoustic) suppression. Furthermore, our approach underscores the importance of careful feature selection, model choice, and validation strategies in analyzing complex neurophysiological data.

neuroscience↗

bioRxiv2020

Neurophysiological correlates of residual inhibition in tinnitus: Hints for trait-like EEG power spectra

Magneto- and electroencephalography (M/EEG) investigations in tinnitus patients demonstrated anomalous oscillatory brain activity patterns compared to healthy controls. A well-established phenomenon in tinnitus is the possibility to temporary suppress tinnitus following acoustic stimulation, which is termed residual inhibition (RI). The few former neurophysiological investigations of RI reported partly conflicting results hampering consensus on tinnitus-specific brain activity and basic neural models. Hence, our objective was to investigate RI-specific oscillatory brain activity changes and whether these changes can be associated with behavioral measures of tinnitus loudness. Further, contrasts between acoustic stimulation responders and non-responders provide further insights in RI-related spontaneous brain activity. Three different types of noise stimuli were administered for acoustic stimulation in 45 tinnitus patients. Subjects resting state brain activity was recorded before and during RI via EEG alongside with subjective measurements of tinnitus loudness. On the whole-group level, tinnitus-unspecific changes were observed which fit established knowledge about basic neural responses after acoustic stimulation. Responder non-responder contrasts revealed differences in alpha and gamma band activity in line with the proposed neural models for oscillatory brain activity in tinnitus. Further analysis of sample characteristics demonstrated divergences between responders and nonresponders notably for tinnitus duration. During RI, distinct differences between responders and non-responders were exclusively observed for alpha band activity in auditory cortical areas. Neither correlations of behavioral tinnitus measures nor differences between stimulus-induced changes in ongoing brain activity could be detected. Taken together, our observations might be indicative of trait-specific forms of oscillatory signatures in different subsets and chronification grades of the tinnitus population possibly related to acoustic tinnitus suppression. Results and insights are not only useful to understand basic neural mechanisms behind RI but are also valuable for general neural models of tinnitus. HighlightsO_LIResidual inhibition provides a key method to study the basic mechanisms of tinnitus. C_LIO_LIWe compared residual inhibition EEG activity between responders and non-responders. C_LIO_LIIn responders, the alpha activity in auditory areas was increased during tinnitus suppression. C_LIO_LIResults and insights are valuable for understanding the neural mechanisms behind acoustic tinnitus suppression. C_LI

neuroscience↗

bioRxiv2019

aMpLiTuDe MoDuLaTeD noise for tinnitus suppression in tonal and noise-like tinnitus

BackgroundAcoustic stimulation offers a potential treatment approach for tinnitus but also in-sights in its basic mechanisms by short-term tinnitus suppression called residual inhibition (RI). The effects of RI were found to be depending on intensity, length or sound types covering the individual tinnitus characteristics. In patients with tonal tinnitus RI was increased with amplitude modulated (AM) pure tones at the individual tinnitus frequency while the effects of modulated noise sounds have not been systematically researched.\n\nObjectivesThe aim of the present study was to investigate whether in patients with noise-like tinnitus RI can be increased by AM noise-like stimuli according to the individual tinnitus frequency range.\n\nMethodsFor this purpose the individual tinnitus characteristics (noise-like and tonal tinnitus) were assessed via customizable noise-band matching, in order to generate bandpass filtered stimuli according to the individual tinnitus sound (individualized bandpass filtered sounds; IBP). Subsequent, various stimuli differing in bandpass filtering and AM were tested with respect to their potential to induce RI. Patients were acoustically stimulated with seven different types of stimuli for three minutes each and had to rate the loudness of their tinnitus after each stimuli.\n\nResultsResults indicate a general efficacy of noise stimuli for the temporary suppression of tinnitus, but no significant differences between AM and unmodulated IBP. Significantly better effects were observed for the subgroup with noise-like tinnitus (n=14), especially directly after stimulation offset.\n\nConclusionsThe study at hand provides further insights in potential mechanisms behind RI for different types of tinnitus. Beyond that, derived principles may qualify for new or extend current tinnitus sound therapies.

neuroscience↗