Biology subjects

Kandasamy, R.

Publications and source records attributed to Kandasamy, R..

3 recordsLinked to original sources

bioRxiv2026

Can the heartbeat-evoked potential (HEP) be separated from Cardiac Artefact (CA) using beamforming?

The heartbeat-evoked potential (HEP), a cortical response to heartbeats and neural marker of interoception, is clinically relevant but heavily contaminated by scalp cardiac-artefact (CA), making reliable distinction challenging. Because HEP and cardiac potentials are anatomically distinct, they may be separable via beamforming, a source localisation method isolating brain activity while suppressing external interference. Here, the first known validation of EEG beamforming for HEP source reconstruction was attempted, quantifying waveform recovery and spatial accuracy using simulated data. Linearly constrained minimal variance (LCMV) beamforming was used (A) to test signal recovery, 128-channel EEG was simulated for three models with known HEP waveforms: (1) a single right insula (R-Ins) HEP; (2) temporally distinct HEPs in R-Ins and right anterior cingulate cortex (R-ACC); (3) overlapping HEPs in both regions. Recovery was assessed by correlating reconstructed and known waveforms. (B) To test CA suppression, CA from brain-dead isoelectric EEGs was integrated to simulations, with varying source (-10-50dB) and sensor (0-30dB) signal-to-noise ratios (SNR). (C) To analyse empirical EEG from hypertensive and anxiety individuals (n=106). Null-space projection, using subject-specific QRS waveforms and its temporal derivative, removed residual CA in source waveforms. In model-1, beamforming achieved near-perfect recovery without CA (r>0.99, error=0mm) at -30dB source SNR, remaining robust in the presence of CA (r=0.72-0.94, error=0-5.7mm) but degrading below -20dB (r<0.3, error=27mm). Models 2 and 3 showed similar recovery but introduced R-ACC-to-R-Ins leakage. In empirical data, beamforming revealed significant HEP activity in R-Ins and R-ACC (p<0.001). A significant late R-ACC HEP difference (250-500ms post-R-peak) between hypertension and controls emerged after excluding low-SNR subjects and strengthened following QRS cleaning (p=0.035, d=0.96). LCMV beamforming reliably recovers simulated HEPs while suppressing CA given sufficient SNR. Applied empirically, beamforming detected clinically meaningful group differences in interoceptive regions (R-Ins/R-ACC), offering a source-level approach to separate HEP from CA that complements sensor-level methods.

neuroscience↗

bioRxiv2024

Methodological approaches to derive the heartbeat-evoked potential: pastpractices and future recommendations

The heartbeat-evoked potential (HEP) is an implicit, electrophysiological marker of cortical heartbeat processing and interoception, with increasing clinical relevance. However, on the scalp, HEP are low-amplitude signals mixed with cardiac field artefacts (CFA), requiring signal processing pipelines to separate HEP from CFA. This review evaluates current analytical approaches, addresses methodological gaps in HEP pipelines, and examines the impact of key parameter choices. HEP processing methods/parameters used in EEG (N=101) and MEG (N=10) studies were investigated, focusing on the effects of HEP window, electrodes, filters, independent component analysis (ICA) and artefact subspace reconstruction (ASR), on HEP extraction, using Temple Universitys normal scalp EEG data. EEG and MEG studies revealed clear inconsistencies in HEP parameter use and reporting. ASR-20 (ASR threshold for artifact identification) performed comparably to ICA for artefact removal, supporting its potential real-time EEG applicability. Epoch rejection, a HEP quality metric, appeared equivalent between ICA and ASR-20 after artefact removal. Linear Mixed Model analysis identified significant effects of RR interval, maximum epoch amplitude, HEP window and baseline correction start time on measured HEP amplitude. Publications should report critical values for reliable HEP extraction, emphasising the need for standardised methods to enhance study comparability and reproducibility.

neuroscience↗

bioRxiv2019

A novel mosaic tetracycline resistance gene tet(S/M) detected in a multidrug-resistant pneumococcal CC230 lineage that underwent capsular switching in South Africa

SynopsisO_ST_ABSObjectiveC_ST_ABSWe reported a novel tetracycline-resistant gene in Streptococcus pneumoniae and investigated its temporal spread in relation to nationwide clinical interventions.\n\nMethodsWe whole genome sequenced 12,254 pneumococcal isolates from twenty-nine countries on an Illumina HiSeq Sequencer. Serotypes, sequence types and antibiotic resistance were inferred from genomes. Phylogeny was built based on single-nucleotide variants. Temporal changes of spread were reconstructed using a birth-death model.\n\nResultsWe identified tet(S/M) in 131 pneumococcal isolates, 97 (74%) caused invasive pneumococcal diseases among young children (59% HIV-positive, where HIV status was available) in South Africa. A majority of tet(S/M)-positive isolates (129/131) belong to clonal complex (CC)230. A global phylogeny of CC230 (n=389) revealed that tet(S/M)-positive isolates formed a sub-lineage that exhibited multidrug-resistance. Using the genomic data and a birth-death model, we detected an unrecognised outbreak of this sub-lineage in South Africa between 2000 and 2004 with an expected secondary infections (R) of ~2.5. R declined to ~1.0 in 2005 and <1.0 in 2012. The declining epidemic coincided and could be related to the nationwide implementation of anti-retroviral treatment (ART) for HIV-infected individuals in 2004 and PCVs in late 2000s. Capsular switching from vaccine serotype 14 to non-vaccine serotype 23A was observed within the sub-lineage.\n\nConclusionsThe prevalence of tet(S/M) in pneumococci was low and its dissemination was due to an unrecognised outbreak of CC230 in South Africa prior to ART and PCVs. However, capsular switching in this multidrug-resistant sub-lineage highlighted its potential to continue to cause disease in the post-PCV13 era.

microbiology↗