Biology subjects

Mazzoni, A.

Publications and source records attributed to Mazzoni, A..

17 recordsLinked to original sources

bioRxiv2026

Can we trust subthalamic local field potential? Geometrical and dynamical factors constraining the interpretability of extracellular recordings

Local field potentials (LFPs) are widely interpreted as readouts of population synaptic activity, an assumption derived almost entirely from cortical recordings. Whether these principles extend to subcortical structures remains unclear. We address this question in the subthalamic nucleus (STN), where LFPs are routinely recorded and used to guide adaptive deep brain stimulation for Parkinsons disease, using a biophysically detailed population model benchmarked against patient microelectrode recordings. As in the cortex, STN extracellular potentials were dominated by synaptic currents. Differently from the cortex, however, LFPs could not be reliably predicted from these currents or other average population quantities. This dissociation arises from the STN symmetric neuronal morphology and lack of recurrent connectivity, which promote destructive interference among single-neuron contributions, decoupling the LFP from population-level dynamics. This decoupling was not absolute: pathological beta synchrony restored a robust synapse-LFP relationship by consistent underlying dynamics, while the aperiodic slope of the power spectral density tracked STN neuronal morphology, firing rate, and excitatory-inhibitory balance. Together, these findings challenge the prevailing view of LFPs as universal readouts of population activity. Our results show that the interpretability of extracellular signals depends critically on neuronal morphology and synchronization state, and provide a mechanistic framework for the use of STN LFPs as biomarkers in adaptive deep brain stimulation for Parkinsons disease.

neuroscience↗

bioRxiv2026

Dopamine Depletion Drives Whole-Brain Oscillatory Disruptions via Cortico-Subcortical Resonance: A Multiscale Model of Parkinson's Disease in Mice

Parkinson's disease is defined by dopaminergic neuron loss in the substantia nigra, yet its hallmark, exaggerated beta-band synchrony, pervades motor cortex, thalamus, and cerebellum, implicating network dynamics far beyond any single circuit. How focal subcortical dopamine depletion translates into brain-wide oscillatory pathology remains unresolved. We use a connectome-constrained multiscale model of the mouse brain, embedding biophysically detailed spiking networks of basal ganglia and cerebellum within whole-brain corticothalamic dynamics grounded in the Allen Mouse Brain Connectivity Atlas. We show that confining dopamine depletion exclusively to subcortical circuits is sufficient to produce widespread beta hypersynchrony (10-30 Hz), accompanied by heterogeneous theta and gamma dysregulation. Virtual loop ablations reveal that cortical and cerebellar beta amplification strictly requires intact cortico-basal ganglia-thalamic feedback; severing this loop confines beta to subcortical generators. These results support resonance within closed large-scale loops, rather than local rhythmogenesis, as the mechanism underlying distributed Parkinsonian beta pathology.

neuroscience↗

bioRxiv2025

In silico model of basal ganglia Deep Brain Stimulation in Parkinsons Disease captures range of effective parameters for pathological beta power suppression

In Parkinsons disease (PD), the beta band ([12 30] Hz) component of basal ganglia activity is pathologically high. Deep brain stimulation (DBS) is an effective treatment to suppress symptoms of PD and is known to suppress pathological beta activity. However, the mechanism underlying this effect is not completely understood. Here, we tested the circuital effects of DBS in a computational model of the basal ganglia network in dopamine-depleted condition mimicking PD. Our model reproduces suppression of beta pathological oscillations in the basal ganglia network induced by subthalamic nucleus (STN) DBS. Crucially, this occurs for realistic levels of DBS intensity only if we incorporate short-term plasticity in STN projections to their downstream targets. STN stimulation hampers beta oscillations in the subthalamo-pallidal beta loop. This induces a progressive dephasing between this loop and the striato-pallidal beta loop, which leads in turn to a network-wide suppression of beta oscillations. This is also reflected in a restoration of the balance between D1 and D2 firing rates, which was altered by dopamine depletion. Moreover, the model also reproduces the DBS-induced gamma activity associated with symptom recovery. Finally, we explored the circuital effects of a broad range of DBS parameters in suppressing beta oscillations, focusing on the clinically relevant range of 60-150 Hz stimulation. The model suggests that 60-80 Hz stimulation frequencies might achieve beta desynchronization for an intensity even lower than the one needed at the standard 130 Hz frequency. Overall, our model lays the ground for in-silico tests of a broad spectrum of stimulation patterns. Author SummaryDeep brain stimulation (DBS) is an effective treatment for alleviating symptoms of Parkinsons disease (PD), but its underlying mechanism is unclear. Motor symptoms of PD are linked to exaggerated beta-band oscillations in a particular brain area called basal ganglia (BG). In this study, we developed a computational model to simulate how DBS affects brain circuits involved in PD. We found that stimulation can reduce pathological beta rhythms at realistic intensities only when we include realistic synaptic dynamics that temporarily adjust connection strength based on recent activity. Our model shows that stimulation decouples two available beta loops in the BG network and helps restore normal patterns of activity. Interestingly, we also found that stimulation at 60-80 Hz might be effective at lower intensities than the standard 130 Hz. Our work provides new insights into how DBS functions and supports safe and efficient exploration of a wide range of stimulation patterns.

bioengineering↗

bioRxiv2025

Gamma oscillations in basal ganglia stem from the interplay between local inhibition and beta synchronization

Basal ganglia rhythms have mainly been studied in the beta band (12-30 Hz), a hallmark of Parkinsons disease (PD), while gamma oscillations (30-100 Hz) in the subthalamic nucleus (STN) have emerged as alternative markers for guiding adaptive deep brain stimulation. However, their underlying mechanisms remains unclear. Using a spiking network model of the basal ganglia, we identified two distinct gamma rhythms: a high-frequency gamma in pallidal (GPe-TI) neurons and a slower gamma in D2 medium spiny neurons (MSNs), both generated through self-inhibition. Under simulated parkinsonian condition, GPe-TI gamma intensity remained stable. In contrast, D2 MSN gamma emerged only in pathological conditions and was strongly modulated by beta activity in both intensity and frequency. Although STN did not generate gamma oscillations directly, gamma activity from GPe-TI population was reflected in simulated STN local field potentials. These results clarify the circuit origins of gamma rhythms and their modulation in PD.

neuroscience↗

bioRxiv2025

Altered cortical network in Parkinson's Disease: the central role of PV interneuron and synaptic remodelling

Parkinson's disease (PD) is traditionally defined by the progressive degeneration of nigrostriatal dopaminergic neurons; however, accumulating evidence highlights extensive cortical dysfunctions as key contributors to motor and non-motor symptoms. Despite this growing recognition, the precise mechanisms underlying cortical network disruptions and their contribution to PD pathophysiology remain poorly understood, particularly in relation to parvalbumin-positive interneurons (PV-INs) and maladaptive plasticity. Here, we investigate the dysregulation of cortical network homeostasis in PD using a 6-hydroxydopamine (6-OHDA) mouse model, focusing on the progressive disruption of parvalbumin-positive interneuron (PV-IN) connectivity, excitatory/inhibitory balance, and neuroinflammatory responses. Using a multimodal approach integrating longitudinal electrophysiology, wide-field calcium imaging, and histological analyses, we revealed striking alterations in cortical activity and connectivity. Specifically, we observed pathological high-gamma hyperactivity during movement, accompanied by severe disruptions in PV-IN connectivity across motor and somatosensory cortices. Histological analyses further revealed synaptic imbalances and microglial dysregulation, suggesting an extensive cortical response to dopaminergic loss. These findings indicate that PV-IN dysfunction drives cortical maladaptive plasticity, leading to network desynchronization and motor deficits. By reframing PD as a disorder of cortical network homeostasis, this study provides novel mechanistic insights and identifies cortical plasticity as a promising therapeutic target for disease modification.

neuroscience↗

bioRxiv2025

A spiking LIF model captures the role of Somatostatin and Parvalbumin neurons in generating oscillations in V1

PurposeOscillations in the primary visual cortex of the mammalian brain have been demonstrated to arise from the balance between excitatory and inhibitory activity. Experimental studies suggest that different inhibitory neuron populations might make specific contributions to such oscillations, but the underlying mechanism has not yet been assessed. MethodsWe modified a standard excitatory-inhibitory spiking neuron model of layer 4 of the primary visual cortex and we investigated the effects on oscillations of the differentiation of inhibitory neurons in somatostatin and parvalbumin neurons. ResultsOur model reproduced the hypothesis that somatostatin and parvalbumin neurons are responsible for beta (15-25)Hz and gamma (40-70)Hz band oscillations, respectively. ConclusionTo date, this is the simplest model accounting for this phenomenon and could therefore be suited to study pathologies in which the two populations have specific roles, such as migraine.

neuroscience↗

bioRxiv2024

Kernel-based LFP estimation in detailed large-scale spiking network model of mouse visual cortex

Simulations of large-scale neural activity are powerful tools for investigating neural networks. Calculating measurable brain signals like local field potentials (LFPs) bridges the gap between model predictions and experimental observations. However, accurately simulating LFPs from large-scale models has traditionally required highly detailed multicompartmental neuron models, posing significant computational challenges. Here, we demonstrate that a kernel-based method can efficiently and accurately estimate LFPs in a state-of-the-art multicompartmental model of the mouse primary visual cortex (V1). Beyond its computational efficiency, the kernel method aids analysis by disentangling contributions of individual neuronal populations to the LFP. Using this approach, we found that LFPs in the V1 model were dominated by external synaptic inputs, with local synaptic activity playing a minimal role. Our findings establish the kernel method as a powerful tool for LFP estimation in large-scale network models and for uncovering the synaptic mechanisms underlying brain signals.

neuroscience↗

bioRxiv2024

Event-Related Potential Markers of Subject Cognitive Decline and Mild Cognitive Impairment during a sustained visuo-attentive task

Subjective cognitive decline (SCD), mild cognitive impairment (MCI), or severe Alzheimers disease stages are still lacking clear electrophysiological correlates. In 178 individuals (119 SCD, 40 MCI, and 19 healthy subjects (HS)), we analysed event-related potentials recorded during a sustained visual attention task, aiming to distinguish biomarkers associated with clinical conditions and task performance. We observed condition-specific anomalies in event-related potentials (ERPs) during visual encoding (P1/N1/P2) and decision-making (P300/P600/P900): SCD individuals showed attenuated dynamics compared to HS, while MCI individuals showed amplified dynamics, except for P300, which matched clinical severity. ERP features confirmed a non-monotonic trend, with MCI showing higher neural resource recruitment. Moreover, task performance correlated with condition-specific ERP gain and latencies across early and late ERP components. These findings enhanced the understanding of the neural mechanisms underlying cognitive decline in SCD and MCI and suggested potential biomarkers for early diagnosis and intervention. HighlightsO_LIIn encoding (P1/N1/P2) and decision (P600/P900) ERPs, SCD individuals showed attenuated dynamics compared to HS, while MCI individuals exhibited amplified dynamics compared to SCD. C_LIO_LIP300 dynamics matched clinical severity. C_LIO_LIMCI individuals demonstrated higher recruitment of neural resources, indicating a non-monotonic trend in ERP features between clinical conditions. C_LIO_LITask performance correlated with condition-specific gain and latencies across multiple ERP components. C_LI

neuroscience↗

bioRxiv2023

Dopamine-dependent cerebellar dysfunction enhances beta oscillations and disrupts motor learning in a multiarea model

Parkinsons disease (PD) is a chronic degenerative disorder of the central nervous system that affects the motor system. The discovery that PD motor symptoms result from the death of dopaminergic cells in the substantia nigra led to focus most of PD research on the basal ganglia. However, recent findings point to an active involvement of the cerebellum in PD. Here, we have developed a multiscale computational model of the rodent brains basal ganglia-cerebellar network. Simulations showed that a direct effect of dopamine depletion on the cerebellum must be taken into account to reproduce the alterations of PD neural activity, particularly the increased beta oscillations widely reported in PD patients. Moreover, dopamine depletion indirectly impacted spike-time-dependent plasticity at the parallel fiber-Purkinje cell synapses, degrading associative motor learning as observed in PD. Overall, these results suggest a relevant involvement of cerebellum in PD motor symptoms. Significance StatementThis study highlights the role of cerebellum in Parkinsons disease (PD). While most studies on PD concentrate on dopaminergic mechanisms in the basal ganglia, here we show that dopamine depletion impacts also on the cerebellum, generating a complex dysfunctional interaction between the two subcortical circuits. To investigate this interaction, we developed de novo a multiarea multiscale network model that mechanistically addresses the effects of dopamine depletionon the cerebellum. Our study demonstrates that this aspect is crucial to reproduce experimental data, particularly the increased beta wave activity. Moreover, alterations in spike-time-dependent plasticity at the parallel fibre - Purkinje cell synapse of cerebellum can explain the link between dopamine depletion to motor learning impairment. These simulations indicate that the cerebellum warrants more attention in future PD research.

neuroscience↗

bioRxiv2022

Dopamine depletion leads to pathological synchronization of distinct basal ganglia loops in the beta band

Motor symptoms of Parkinsons Disease (PD) are associated with dopamine deficits and pathological oscillation of basal ganglia (BG) neurons in the {beta} range ([12-30] Hz). However, how the dopamine depletion affects the oscillation dynamics of BG nuclei is still unclear. With a spiking neurons model, we here captured the features of BG nuclei interactions leading to oscillations in dopamine-depleted condition. We found that both the loop between subthalamic nucleus and Globus Pallidus pars externa (GPe) and the loop between striatal fast spiking and medium spiny neurons and GPe displayed resonances in the {beta} range, and synchronized to a common {beta} frequency through interaction. Crucially, the synchronization depends on dopamine depletion: the two loops were largely independent for high levels of dopamine, but progressively synchronized as dopamine was depleted due to the increased strength of the striatal loop. Our results highlight the role of the interplay between the GPe-STN and the GPe-striatum loop in generating sustained {beta} oscillations in PD subjects, and explain how this interplay depends on the level of dopamine. This paves the way to the design of therapies specifically addressing the onset of pathological {beta} oscillations. Author summaryParkinsons Disease is associated to the death of neurons generating a particular neurotransmitter: the dopamine. Motor symptoms of PD, on the other hand, are known to be due to dysfunctions in a particular subcortical area of the brain, the BG network. In particular, the BG network develops pathological oscillations in a specific frequency range ({beta}: [12-30] Hz). What is unclear is how dopamine depletion leads to these oscillations. In this work we developed a BG network model and we found the actual reason for these abnormal oscillations is the synchronization of two loops within the network that are individually oscillating in the {beta} range. For healthy level of dopamine the two loops are decoupled and the oscillation power is low. When dopamine is depleted (as in PD) the two loops synchronize and originate the pathological oscillations associated with motor symptoms.

neuroscience↗

bioRxiv2021

Euler method can outperform more complex ODE solvers in the numerical implementation of the Izhikevich artificial Spiking Neuron Model given the allocated FLOPS

The Izhikevich artificial spiking neuron model is among the most employed models in neuromorphic engineering and computational neuroscience, due to the affordable computational effort to discretize it and its biological plausibility. It has been adopted also for applications with limited computational resources in embedded systems. It is important therefore to realize a compromise between error and computational expense to solve numerically the models equations. Here we investigate the effects of discretization and we study the solver that realizes the best compromise between accuracy and computational cost, given an available amount of Floating Point Operations per Second (FLOPS). We considered three fixed-step solvers for Ordinary Differential Equations (ODE), commonly used in computational neuroscience: Euler method, the Runge-Kutta 2 method and the Runge-Kutta 4 method. To quantify the error produced by the solvers, we used the Victor Purpura spike train Distance from an ideal solution of the ODE. Counterintuitively, we found that simple methods such as Euler and Runge Kutta 2 can outperform more complex ones (i.e. Runge Kutta 4) in the numerical solution of the Izhikevich model if the same FLOPS are allocated in the comparison. Moreover, we quantified the neuron rest time (with input under threshold resulting in no output spikes) necessary for the numerical solution to converge to the ideal solution and therefore to cancel the error accumulated during the spike train; in this analysis we found that the required rest time is independent from the firing rate and the spike train duration. Our results can generalize in a straightforward manner to other spiking neuron models and provide a systematic analysis of fixed step neural ODE solvers towards an accuracy-computational cost tradeoff.

bioengineering↗

bioRxiv2021

Fast-spiking interneurons of the premotor cortex contribute to action planning

Planning and execution of voluntary movement depend on the contribution of distinct classes of neurons in primary motor and premotor areas. However, the specific functional role of GABAergic cells remains only partly understood. Here, electrophysiological and computational analyses are employed to compare directly the response properties of putative pyramidal (PNs) and fast-spiking, GABAergic neurons (FSNs) during licking and forelimb retraction in mice. Recordings from anterolateral motor cortex and rostral forelimb area, reveal that FSNs fire earlier and for a longer duration than PNs, with the exception of a subset of early-modulated PNs in deep layers. Computational analysis reveals that FSNs carry vastly more information than PNs about the onset of movement. While PNs differently modulate their discharge during distinct motor acts, most FSNs respond with a stereotyped increase in firing rate. Accordingly, the informational redundancy was greater among FSNs than PNs. These data suggest that a global rise of inhibition contributes to early action planning.

physiology↗

bioRxiv2020

Thalamocortical spectral transmission relies on balanced input strengths

The thalamus is a key element of sensory transmission in the brain, as all sensory information is processed by the thalamus before reaching the cortex. The thalamus is known to gate and select sensory streams through a modulation of its internal activity in which spindle oscillations play a preponderant role, but the mechanism underlying this process is not completely understood. In particular, how do thalamocortical connections convey stimulus-driven information selectively over the background of thalamic internally generated activity (such as spindle oscillations)? Here we investigate this issue with a spiking network model of connectivity between thalamus and primary sensory cortex reproducing the local field potential of both areas. We found two features of the thalamocortical dynamics that filter out spindle oscillations: i) spindle oscillations are weaker in neurons projecting to the cortex, ii) the resonance dynamics of cortical networks selectively blocks frequency in the range encompassing spindle oscillations. This latter mechanism depends on the balance of the strength of thalamocortical connections toward excitatory and inhibitory neurons in the cortex. Our results pave the way toward an integrated understanding of the sensory streams traveling between the periphery and the cortex.

neuroscience↗

bioRxiv2020

Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals

Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nervous system and visceral organs, the vagus nerve (VN) is one of the most promising targets. Closed-loop neuromodulation would be crucial to increase effectiveness and reduce side effects, but it depends on the possibility of extracting useful physiological information from VN electrical activity, which is currently very limited. Here, we present a new decoding algorithm properly detecting different functional changes from VN signals. They were recorded using intraneural electrodes in anaesthetized pigs during cardiovascular and respiratory challenges mimicking increases in arterial blood pressure, tidal volume and respiratory rate. A novel decoding algorithm was developed combining discrete wavelet transformation, principal component analysis, and ensemble learning made of classification trees. It robustly achieved high accuracy levels in identifying different functional changes and discriminating among them. We also introduced a new index for the characterization of recording and decoding performance of neural interfaces. Finally, by combining an anatomically validated hybrid neural model and discrimination analysis, we provided new evidence suggesting a functional topographical organization of VN fascicles. This study represents an important step towards the comprehension of VN signaling, paving the way to the development of effective closed-loop bioelectronic systems.

neuroscience↗

bioRxiv2019

Antigen-driven PD1+Tox+Eomes+ and PD1+Tox+BHLHE40+ synovial T lymphocytes regulate chronic inflammation in situ

Introduction/AbstractT lymphocytes accumulate in inflamed tissues of patients with chronic inflammatory diseases (CIDs) and express pro-inflammatory cytokines upon re-stimulation in vitro1-29. Further, a significant genetic linkage to MHC genes suggests that T lymphocytes play an important role in the pathogenesis of CIDs including juvenile idiopathic arthritis (JIA)30-33. However, the functions of T lymphocytes in established disease remain elusive. Here we dissect the heterogeneity of synovial T lymphocytes in JIA patients by single cell RNA-sequencing. We identify subpopulations of T lymphocytes expressing genes reflecting recent activation by antigen in situ. A PD-1+TOX+EOMES+ population of CD4+ T lymphocytes expressed immune regulatory genes and chemoattractant genes for myeloid cells. A PD-1+TOX+BHLHE40+ population of CD4+, and a mirror population of CD8+ T lymphocytes expressed genes driving inflammation, and genes supporting B lymphocyte activation. This analysis points out that multiple types of T lymphocytes have to be targeted for therapeutic regeneration of tolerance in arthritis.

immunology↗

bioRxiv2019

Spatio-temporal structure of single neuron subthalamic activity in Tourette Syndrome explored during DBS procedures

Basal ganglia dysfunctions have been suggested to play a causal role in the pathophysiology of most motor and non-motor symptoms of movement disorders as Tourette Syndrome (TS) or Parkinsons Disease (PD). Intra/post-operative recordings from the subthalamic nucleus (STN) during Deep Brain Stimulation (DBS) procedures in PD patients have highlighted specific pathological patterns of neural activity. Spatial and temporal patterns of STN neural activity in TS are still unknown due to the lack of direct microrecordings in humans. Here, we describe for the first time specific neural activities of sensorimotor STN in TS patients, as recorded during intraoperative microrecordings. We analyzed 125 single units at 0.5 mm-spaced depths from the STN of anesthetized TS patients and we observed a large fraction of units (39/125, 31.2%) intensely bursting in the delta band (<4 Hz). In anesthetized PD patients we found similar average firing rate and spectral density of STN units, but differently to TS patients, only 4/54 (7.4%) of the units displayed bursting. Remarkably, bursting units in TS STN were not homogeneously distributed over the dorso-ventral trajectory of the recording: the highest density of bursting units was reliably found at the depth for which the clinical effect was maximal. Our results provide an unprecedented characterization of STN functional architecture and single units dynamics in TS patients, paving the way to an understanding of the role of STN subterritories in TS. Key PointsO_LISingle neuron activity in Subthalamic Nucleus (STN) of patients with Tourette Syndrome (TS) was analyzed for the first time in literature. C_LIO_LIFiring rate and spectral content of single STN neurons in TS patients were found to be similar to those of anesthetized PD patients, while the analysis of arrhythmic bursting activity revealed that in TS patients the STN is characterized by a larger fraction of bursting neurons and more intense bursts C_LIO_LIBursting activity in TS was widespread across the whole STN, but with a higher density at the optimal lead location depth for DBS C_LI

neuroscience↗

bioRxiv2018

A closed-loop hand prosthesis with simultaneous intraneural tactile and position feedback

Current myoelectric prostheses allow upper-limb amputees to regain voluntary motor control of their artificial limb by exploiting residual muscle function in the forearm1. However, the over-reliance on visual cues resulting from a lack of sensory feedback is a common complaint2,3. Recently, several groups have provided tactile feedback in upper-limb amputees by using implanted electrodes4,5,6,7,8, surface nerve stimulation9,10 or sensory substitution11,12. These approaches have led to improved function and prosthesis embodiment4,5,6,7,13,14. Nevertheless, the provided information remains limited to a subset of the rich sensory cues available to healthy individuals. More specifically, proprioception, the sense of limb position and movement, is predominantly absent from current systems. Here we show that sensory substitution based on intraneural stimulation can deliver position feedback in real-time and in conjunction with somatotopic tactile feedback. This approach allowed two trans-radial amputees to regain high and close-to-natural remapped proprioceptive acuity, with a median joint angle reproduction accuracy of 9.1{degrees} and a median threshold to detection of passive movements of 9.5{degrees}, which was compatible with results obtained in healthy subjects15,16,17. The simultaneous delivery of position information and somatotopic tactile feedback allowed both amputees to discriminate object size and compliance with high levels of accuracy (75.5%). These results demonstrate that touch information delivered via somatotopic neural stimulation and position information delivered via sensory substitution can be exploited simultaneously and efficiently by trans-radial amputees. This study paves the way towards more sophisticated bidirectional bionic limbs conveying rich, multimodal sensations.

neuroscience↗