Biology subjects

Kaboodvand, N.

Publications and source records attributed to Kaboodvand, N..

3 recordsLinked to original sources

bioRxiv2022

Multisite Thalamic Recordings to Characterize Seizure Propagation in the Human Brain

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in patients with refractory focal epilepsy, but it is not uniformly effective. One important uncertainty is to what extent thalamic subregions other than the ANT are recruited earlier and more prominently in the propagation of seizures in patients with presumed temporal lobe epilepsy (TLE). To address this unknown, we studied 11 patients with clinical manifestations of TLE planned to undergo invasive stereo-encephalography (sEEG) monitoring. We extended cortical electrodes to reach thalamic nuclear subdivisions in the anterior (ANT), middle (mediodorsal) and or posterior (pulvinar) sites. This multisite thalamic sampling was without any adverse events. Intracranial EEG (iEEG) recordings confirmed seizure-onset in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites - highlighting the importance of iEEG for more accurate localization of seizure foci. Visual review of EEGs documented early and prominent involvement of specific thalamic sites. Seizures originating from the same brain origin produced a stereotyped thalamic EEG signature. Visual review of EEGs, validated with singlepulse corticothalamic evoked potentials, documented early and prominent involvement of thalamic sites that would have not been predicted given the anatomy of seizure onset zones. Pulvinar was involved earlier and more prominently than other sampled nuclear subgroups in 60% of patients, even though all patients had a presumed diagnosis of TLE prior to invasive monitoring. Our findings document the feasibility and safety of multisite sampling from the human thalamus and suggest that the anatomy of thalamic involvement may not be entirely predictable on the basis of clinical information or lobar localization of seizures. Future clinical trials can establish whether offering more personalized targets for thalamic neuromodulation will lead to greater meaningful improvements in outcome.

neuroscience↗

bioRxiv2020

Differentiating ADHD subtypes and simulation of in silico therapeutic neuronal excitation in a whole-brain nonlinear dynamic modelling frame-work

Recent advances in non-linear computational and dynamical modelling have opened up the possibility to param etrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully understand disorders of the brain as it may provide a quantitative platform that is capable of binding multiple neurophysiological processes to phenotype profiles. In this study, we apply a newly developed adaptive frequency-based model of whole-brain oscillations to resting-state fMRI data acquired from healthy controls and a cohort of attention deficit hyperactivity disorder (ADHD) subjects. As expected, we found that healthy control subjects differed from ADHD in terms of attractor dynamics. However, we also found a marked dichotomy in neural dynamics within the ADHD cohort. Next, we classified the ADHD group according to the level of distance of each individuals empirical network from the two model-based simulated networks. Critically, the model was mirrored in the empirical behavior data with the two ADHD subgroups displaying distinct behavioral phenotypes related to emotional instability (i.e., depression and hypomanic personality traits). Finally, we investigated the applicability and feasibility of our whole-brain model in a therapeutic setting by conducting in silico excitatory stimulations to parsimoniously mimic clinical neuro-stimulation paradigms in ADHD. We tested the effect of stimulating any individual brain region on the key network measures derived from the simulated brain network and its contribution in rectifying the brain dynamics to that of the healthy brain, separately for each ADHD subgroup. This showed that this was indeed possible for both subgroups. However, the current effect sizes were small suggesting that the stimulation protocol needs to be tailored at the individual level. These findings demonstrate the potential of this new modelling framework to unveil hidden neurophysiological profiles and establish tailored clinical interventions.

neuroscience↗

bioRxiv2019

Dynamic synergetic configurations of resting-state networks in ADHD.

Attention deficit hyperactivity disorder (ADHD) is characterized by high distractibility and impaired executive functions. Notably, there is mounting evidence suggesting that ADHD could be regarded as a default mode network (DMN) disorder. In particular, failure in regulating the dynamics of activity and interactions of the DMN and cognitive control networks have been hypothesized as the main source of task interference causing attentional problems. On the other hand, previous studies indicated pronounced fluctuations in the strength of functional connections over time, particularly for the inter-network connections between the DMN and fronto-parietal control networks. Hence, characterization of connectivity disturbances in ADHD disorder requires a thorough assessment of time-varying FCs. In this study, we propose a dynamical systems perspective to assess how the DMN over time recruits different configurations of network segregation and integration. Specifically, we were interested in configurations for which both intra- and inter-network connections are retained, as opposed to commonly used methods which assess network segregation as a single measure. From resting-state fMRI data, we extracted three different stable configurations of FC patterns for the DMN, namely synergies. We provide evidence supporting our hypothesis that the ADHD brain differs in both recruitment rate and the topology of specific synergies between resting-state networks.

neuroscience↗