Biology subjects

Wiest, C.

Publications and source records attributed to Wiest, C..

9 recordsLinked to original sources

bioRxiv2025

Beyond beta: Aperiodic broadband power reflects Parkinson's disease severity - a multicenter study

Parkinsons disease is linked to increased beta oscillations in the subthalamic nucleus, which correlate with motor symptoms. However, findings across studies have varied. Our standardized analysis of multicenter datasets shows that small sample sizes contributed to these discrepancies--a challenge we address by pooling datasets into one large cohort (n=119). Moving beyond beta power, we disentangled spectral components reflecting distinct neural processes. Combining aperiodic offset, low beta, and low gamma oscillations explained significantly more variance in symptom severity than beta alone. Moreover, interhemispheric within-patient analyses showed that, unlike beta oscillations, aperiodic broadband power-likely reflecting spiking activity-was increased in the more affected hemisphere. These findings identify aperiodic broadband power as a potential biomarker for adaptive deep brain stimulation and provide novel insights into the relationship between subthalamic hyperactivity and motor symptoms in human Parkinsons disease.

neuroscience↗

bioRxiv2025

Topographically organized dorsal raphe activity modulates forebrain sensory-motor computations and adaptive behaviors.

The dorsal raphe nucleus (DRN) plays an important role in shaping a wide range of behaviors, including mood, motivation, appetite, sleep, and social interactions. Reflecting these diverse roles, the DRN is composed of molecularly distinct and topographically organized groups of neurons that target specific regions of the forebrain. Despite these insights, fundamental questions remain regarding how DRN neurons process sensory information, what do DRN communicate to forebrain, and the role of DRN inputs in forebrain computations and animal behavior. To address these questions, we investigated the spatiotemporal activity patterns of DRN neurons, along with DRN axons and their targets in the juvenile zebrafish forebrain. Our findings revealed a remarkable topographic organization of ongoing activity and sensory-motor responses within the DRN. We discovered that a large fraction of DRN neurons are primarily driven by animals locomotor activity. We also observed that an anterior group of DRN neurons, marked by Gad1, exhibited distinct activity patterns during rest, locomotor activity and sensory stimulation. DRN axons broadly innervating the forebrain exhibit topographically organized excitation and inhibition in response to sensory stimulation and motor activity. Notably, we observed significant and rapid covariation between the activity of DRN axons and nearby forebrain neurons. Chemogenetic ablation of the DRN led to a marked reduction in the synchrony and sensory-motor responses across forebrain neurons, accompanied by significant deficits in adaptive behaviors. Collectively, our findings revealed the functional diversity of DRN neurons and their role in transmitting sensory and locomotor signals via topographically organized projections, which can regulate forebrain activity and play a crucial role in modulating animal behavior.

neuroscience↗

bioRxiv2025

The role of STN beta oscillations on lower extremity muscle activity in Parkinsonian stepping

Freezing of gait (FOG) is a devastating symptom of Parkinsons disease (PD) often resulting in disabling falls and loss of independence. It affects half of patients, yet current therapeutic strategies are insufficient, and the underlying neural mechanisms remain poorly understood. This study investigated beta oscillation dynamics in the STN during different locomotor states, while examining the effects of levodopa. In particular, it aimed to identify pathological activity by analysing the relationship between the STN and lower limb muscles during stepping. Local field potentials (LFP) in the STN and muscle activity (EMG) of the gastrocnemius and peroneus longus were recorded in 14 PD patients during standing and stepping, ON and OFF levodopa. Levodopa reduced stepping variability, implying improved stepping abilities. Distinct STN beta patterns were observed between stepping and standing, with lower high-beta and higher low-beta during stepping compared to standing, suggesting a distinct role of these frequency bands in motor control during postural and movement states. Levodopa reduced low-beta but increased high-beta activity, highlighting a potential physiological function of high-beta in the STN during standing and stepping. In addition, step-phase specific effects of levodopa included reduced broad-beta band activity in the STN and lower limb muscles during the late-stance and pushing-off phase of the contralateral leg when ON medication. Further analyses suggest that pathological STN activity amplifies muscle activation around movement initiation, potentially reducing the ability of the patient to move freely. These findings offer insight for developing phase-specific stimulation strategies targeting STN beta oscillations during gait.

neuroscience↗

bioRxiv2024

Evoked resonant neural activity outperforms spectral markers in decoding sleep from the subthalamic nucleus

BackgroundDeep brain stimulation is a treatment for advanced Parkinsons disease and currently tuned to target motor symptoms during daytime. Parkinsons disease is associated with multiple nocturnal symptoms such as akinesia, insomnia and sleep fragmentation which may require adjustments of stimulation during sleep for best treatment outcome. ObjectivesThere is a need for a robust biomarker to guide stimulation titration across sleep stages. This study aimed to investigate whether evoked resonant neural activity (ERNA) is modulated during sleep. MethodsWe recorded local field potentials from the subthalamic nucleus of four Parkinsons patients with externalised electrodes while applying single stimulation pulses to investigate the effect of sleep on ERNA. ResultsWe found that ERNA features change with wakefulness and sleep stages, and are correlated with canonical frequency bands and heart rate. We further evaluated the performance of machine learning models in classifying non-REM sleep versus wakefulness and found that ERNA amplitude outperforms all spectral markers. ConclusionsGiven the heterogeneity of spectral features during sleep, their susceptibility to movement artefacts and superior classification accuracy of models using ERNA features, this study paves the way for ERNA as a marker for automatic stimulation titration during sleep and improved patient care.

neuroscience↗

bioRxiv2024

Evoked Resonant Neural Activity Long-Term Dynamics can be Reproduced by a Computational Model with Vesicle Depletion

Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinsons disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we therefore aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. We further validate the model against experimental data from Parkinsons disease patients by simulating variable stimulation and medication states, as well as the response of individual neurons. Our results demonstrate that it is possible to reproduce the slow dynamics of ERNA with a single neuronal population, and, crucially, with vesicle depletion as the key mechanism behind the ERNA frequency decay. We provide a series of predictions from the model that could be the subject of future studies for further validation. Author SummaryERNA is a high amplitude response to stimulation of deep brain structures, with a frequency over twice that of the frequency of stimulation. While the underlying mechanisms of ERNA are still unclear, recent findings have demonstrated its importance as the best indicator of which stimulation contact to select for DBS therapy in patients with Parkinsons disease. Previous modelling studies of ERNA focus on the immediate responses to stimulation (<200ms) and rely on interconnected neural structures and delays. Our work shows that the long-term (on the scale of one or more seconds) ERNA response to continuous stimulation can be modelled using a single neural structure. The proposed model also captures the long-term frequency and amplitude characteristics of ERNA with variable stimulation and medication paradigms. The key features of the model, in particular the depletion of vesicles carrying neurotransmitters between neurons by high-frequency stimulation, may provide insights into the underlying mechanisms of ERNA and inform future investigations into this neural response.

neuroscience↗

bioRxiv2023

Tuning the brakes: Modulatory role of transcranial random noise stimulation on inhibition

BackgroundEveryday decision-making requires the ability to flexibly modify and sometimes terminate our actions, such as avoiding a tempting slice of cake to hitting the brakes in an emergency. Neural oscillations, such as beta-band rhythms observed over the medial prefrontal cortex(mPFC), help regulate these context-dependent behaviours. However, how random noise stimulation would modulate neural rhythms and corresponding inhibitory behaviors remain understudied. ObjectivesTo target the mPFC using random noise stimulation and modulate neural activity underlying inhibitory behaviours. MethodsUsing a single-blinded within-subject design, fifteen participants received random noise or sham stimulation in a pseudo-randomized order while performing a Go/Conflict/No-Go task. We measured neural activity and behavior before and after stimulation. ResultsWe show that random noise stimulation significantly improved inhibitory behaviors (4.6{+/-}4.42percent) by reducing the number of errors in No-Go trials. This improvement was a function of participants impulsivity-levels and baseline performance, i.e., impulsive individuals who made more baseline errors improved more after receiving stimulation. At the neural level, we show that random noise stimulation increases low-beta power at stimulation site, mediated by an increase in the duration of intermittent beta-bursts. ConclusionWe show for the first time that random noise stimulation improves the ability to withhold response to unexpected inhibitory cues as a function of an individuals impulsivity level. This improvement could be attributed to increased low-beta band power and intermittent-burst duration. These results suggest that random noise stimulation of the mPFC could potentially be used as a neuromodulatory intervention to target maladaptive behaviors in impulse control disorders.

neuroscience↗

bioRxiv2022

The aperiodic exponent of subthalamic field potentials reflects excitation/inhibition balance in Parkinsonism: a cross-species study in vivo

AO_SCPLOWBSTRACTC_SCPLOWPeriodic features of neural time series data, such as local field potentials (LFP), are often quantified using power spectra. While the aperiodic exponent of spectra is typically disregarded, it is nevertheless modulated in a physiologically-relevant manner and was recently hypothesised to reflect excitation/inhibition (E/I) balance in neuronal populations. Here, we used a cross-species in vivo electrophysiological approach to test the E/I hypothesis in the context of experimental and idiopathic Parkinsonism. We demonstrate in dopamine-depleted rats that aperiodic exponents and power at 30-100 Hz in subthalamic nucleus (STN) LFPs reflect defined changes in basal ganglia network activity; higher aperiodic exponents tally with lower levels of STN neuron firing and a balance tipped towards inhibition. Using STN-LFPs recorded from awake Parkinsons patients, we show that higher exponents accompany dopaminergic medication and deep brain stimulation (DBS) of STN, consistent with untreated Parkinsons manifesting as reduced inhibition and hyperactivity of STN. These results suggest that the aperiodic exponent of STN-LFPs in Parkinsonism reflects E/I balance, and might be a candidate biomarker for adaptive DBS.

neuroscience↗

bioRxiv2021

Gait-phase modulates alpha and beta oscillations in the pedunculopontine nucleus

BackgroudThe pedunculopontine nucleus (PPN) is a reticular collection of neurons at the junction of the midbrain and pons, playing an important role in modulating posture and locomotion. Deep brain stimulation of the PPN has been proposed as an emerging treatment for patients with Parkinsons disease (PD) or multiple system atrophy (MSA) suffering gait-related atypical parkinsonian syndromes. ObjectiveIn this study, we investigated PPN activities during gait to better understand its functional role in locomotion. Specifically, we investigated whether PPN activity is rhythmically modulated during locomotion. MethodsPPN local field potential (LFP) activities were recorded from PD or MSA patients suffering from gait difficulties during stepping in place or free walking. Simultaneous measurements from force plates or accelerometers were used to determine the phase within each gait cycle at each time point. ResultsOur results showed that activities in the alpha and beta frequency bands in the PPN LFPs were rhythmically modulated by the gait phase within gait cycles, with a higher modulation index when the stepping rhythm was more regular. Meanwhile, the PPN-cortical coherence was most prominent in the alpha band. Both gait-phase related modulation in the alpha/beta power and the PPN-cortical coherence in the alpha frequency band were spatially specific to the PPN and did not extend to surrounding regions. ConclusionsThese results raise the possibility that alternating PPN stimulation in tandem with the gait rhythm may be more beneficial for gait control than continuous stimulation, although this remains to be established in future studies.

neuroscience↗

bioRxiv2019

Investigating olfactory behaviors in adult zebrafish

Odor-driven behaviors such as feeding, mating and predator avoidance are crucial for animal survival. While the zebrafish olfactory circuitry is well understood, a comprehensive description of odor-driven behaviors is needed to better relate olfactory computations to animal responses. Here, we used a medium-throughput setup to measure the swimming trajectories of 10 zebrafish in response to 17 ecologically relevant odors. By selecting appropriate locomotor metrics, we constructed ethograms systematically describing odor-induced changes in the swimming trajectory. We found that fish reacted to most odorants, using different behavioral programs and that combination of few relevant behavioral metrics enabled to capture most of the variance in these innate odor responses. We observed that monomolecular odors in similar chemical categories were weakly clustered based on the behavioral responses, likely because natural odors elicited stronger reactions than the monomolecular odors. Finally, we uncovered a previously undescribed intra and inter-individual variability of olfactory behaviors and suggest a small set of odors that elicit robust responses. In conclusion, our setup and results will be useful resources for future studies interested in characterizing olfactory responses in aquatic animals.

animal behavior and cognition↗