Biology subjects

Bonaiuto, J.

Publications and source records attributed to Bonaiuto, J..

4 recordsLinked to original sources

bioRxiv2025

Distorting anatomy to test MEG models and metrics

Current flow that gives rise to non-invasive Magnetoencephalographic (MEG) data derives predominantly from pyramidal neurons oriented orthogonal to the cortical surface. The estimate of current flow based on extra-cranial magnetic fields is a well-known ill-posed problem; however, this current distribution must depend on anatomy. In other words, a veridical estimate of current flow should discriminate between true and distorted versions of the brain. Here, we make use of advances in diffeomorphic brain shape modelling to construct a set of parametrically deformable cortical surfaces. We use a latent space of 100 components to construct cortical surfaces that are representative of the population. We show how these geometric distortions can be used to quantify the performance of MEG source reconstruction algorithms and metrics of fit.

neuroscience↗

bioRxiv2019

Mapping effective connectivity between the frontal and contralateral primary motor cortex using dual-coil transcranial magnetic stimulation

Cytoarchitectonic, anatomical and electrophysiological studies have divided the frontal cortex into distinct functional subdivisions. Many of these subdivisions are anatomically connected with the contralateral primary motor cortex (M1); however, effective neurophysiological connectivity between these regions is not well defined in humans. Therefore, we aimed to use dual-coil transcranial magnetic stimulation (TMS) to map, with high spatial resolution, the effective connectivity between different frontal regions of the right hemisphere and contralateral M1 (cM1). TMS was applied over the left M1 alone (test pulse) or after a conditioning pulse was applied to different grid points covering the right frontal cortex, while subjects were at rest, prepared an index finger abduction (Prep-ABD) or precision grip (Prep-PG). MEP motor maps were generated by creating synthetic fMRI volumes, including the normalised MEP values at vertices corresponding to the TMS grid locations. These maps were registered to a common atlas, and statistical parametric mapping was used to identify cortical clusters in which stimulation differentially modulated conditioned MEPs across conditions. We found five significant clusters in the frontal cortex. Three clusters in ventral premotor regions (areas 6v and 44) showed significant differential modulations of contralateral MEPs when rest was compared to Prep-ABD and Prep-PG. Two clusters in rostral dorsolateral prefrontal cortex (areas 8Av and 46) showed differential modulation in MEPs when Prep-ABD was compared to Prep-PG. Our findings demonstrate distinct regions that show task-related connectivity whereby interactions between ventral premotor regions and cM1 differentiate between rest and movement preparation and the dorsolateral prefrontal cortex differentiates primarily between preparation of different types of hand movements. These results thus demonstrate the utility of dual-coil TMS and MEP motor maps to define fine-grained sub-regions in the human frontal cortex, which are functional and causally involved in hand movements. HighlightsO_LIDual-coil TMS mapping allows defining of fine-grained frontal cortex subdivisions C_LIO_LIFrontal cortex houses multiple areas with different neurophysiological properties C_LIO_LIInteractions between premotor areas and M1 control rest vs movement C_LIO_LIInteractions between prefrontal areas and M1 reflect movement selection C_LI

neuroscience↗

bioRxiv2018

Motor cortical beta transients delay movement initiation and track errors

Motor cortical activity in the beta range (13-30 Hz) is a hallmark signature of healthy and pathological movement, but its behavioural relevance remains unclear. Recent work in primates and human sensory cortex suggests that sustained oscillatory beta activity observed on average, may arise from the summation of underlying short-lasting, high-amplitude bursts of activity. Classical human movement-related event-related beta desynchronisation (ERD) and synchronization (ERS) may thus provide insufficient, non-dynamic, summaries of underlying focal spatio-temporal burst activity, limiting insight into their functional role during healthy and pathological movement.\n\nHere we directly investigate this transient beta burst activity and its putative behavioural relevance for movement control, using high-precision magnetoencephalography (MEG). We quantified the subject-specific (n=8), trial-wise (n>12,000) dynamics of beta bursts, before and after movement. We show that beta activity on individual trials is dominated by high amplitude, short lasting bursts. While average beta changes generally manifest as bilaterally distributed activity (FWHM = 25mm), individual bursts are spatially more focal (FWHM = 6 mm), sporadic (1.3 -1.5/s), and transient (mean: 96 ms).\n\nPrior to movement (the period of the classical ERD), the timing of the last pre-movement burst predicts movement onset, suggesting a role in the specification of the goal of movement. After movement (the period of the classical ERS), the first beta burst is delayed by ~100ms after a response error occurs, intimating a role in error monitoring and evaluation.\n\nMovement-related beta activity is therefore dominated by a spatially dispersed summation of short lasting, sporadic and focal bursts. Movement-related beta bursts coordinate the retrieval and updating of movement goals in the pre- and post-movement periods, respectively.

neuroscience↗

bioRxiv2018

Quantifying the performance of MEG source reconstruction using resting state data

Resting state networks measured with magnetoencephalography (MEG) form transiently stable spatio-temporal patterns in the subsecond range, and therefore fluctuate more rapidly than previously appreciated. These states populate and interact across the whole brain, are simple to record, and possess the same dynamic structure of task related changes. They therefore provide a generic, heterogeneous, and plentiful functional substrate against which to test different MEG recording and reconstruction approaches. Here we validate a non-invasive method for quantifying the resolution of different inversion assumptions under different recording regimes (with and without head-casts) based on resting state MEG. Spatio-temporally partitioning of data into self-similar periods confirmed a rich and rapidly dynamic temporal structure with a small number of regularly reoccurring states. To test the anatomical precision that could be resolved through these transient states we then inverted these data onto libraries of systematically distorted, subject specific, cortical meshes and compared the quality of the fit using Cross Validation and a Free Energy metric. This revealed which inversion scheme was able to best support the least distorted (most accurate) anatomical models. Both datasets showed an increase in model fit as anatomical models moved towards the true cortical surface. In the head-cast MEG data, the Empirical Bayesian Beamformer (EBB) algorithm showed the best mean anatomical discrimination (3.7 mm) compared with Minimum Norm / LORETA (6.0 mm) and Multiple Sparse priors (9.4 mm). This pattern was replicated in the second (conventional dataset) although with a marginally poorer prediction of the missing (cross-validated) data. Our findings suggest that the abundant resting state data now commonly available could be used to refine and validate MEG source reconstruction methods or recording paradigms.

neuroscience↗