Biology subjects

Garfinkel, S. N.

Publications and source records attributed to Garfinkel, S. N..

5 recordsLinked to original sources

bioRxiv2026

Delineating the heartbeat-evoked potential from cardiac artefact

Introduction The heartbeat-evoked potential (HEP) is widely interpreted as an EEG/MEG marker of cortical processing of cardiac afferent signals. It is superimposed on electrical and mechanical signals generated by the heartbeat. Because the neural response and cardiac artefact share the same trigger, conventional averaging and blind-source correction lack an observable cardiac-only reference. Methods We used clinically acquired EEGs with isoelectric-appearing cerebral activity and preserved cardiac activity as a negative control for non-neural heartbeat-locked scalp signal. Thirty-nine isoelectric participants were compared with 118 heart-rate-matched participants whose clinical EEGs were reported as normal. Participant-level heartbeat averages were analysed using covariate-adjusted spatiotemporal permutation tests. We characterised interindividual cardiac-artefact morphology and tested the primary group contrast across average-reference, surface-Laplacian and cardiac-artefact-directed ICA analyses, with pseudotrial correction for heartbeat-independent EEG activity. Results Cardiac-artefact morphology varied markedly across isoelectric participants and was predominantly posterior or posterolateral. In the prespecified primary analysis, controls showed a negative frontocentral cluster persisted at 90-365 ms, p=.016, and a posterior cluster at 145-310 ms, p=.03. The topography of the first cluster aligns with the spatiotemporal characteristics of the early window of the HEP as identified in the literature. This cluster was negative in polarity at the scalp. This suggests positive voltage changes in the early HEP are in fact reductions in HEP activity. Exploratory analyses explored the effects of montage, and artefact correction with independent component analysis to remove CA. There was no significant group difference in ECG. Conclusion These findings provide an important first empirical scalp-level dissociation of the early HEP from CA using an inversion-of-ground-truth approach. A robustly observed cluster of difference, consistent with the early HEP, suggests that this part of the HEP is a distinct, frontocentral, negative cortical response.

neuroscience↗

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

A hierarchical Bayesian model reveals increased precision weighting for afferent cardiac signals, and reduced anxiety, as a function of interoceptive training

Perceptual accuracy for interoceptive signals, such as heartbeats, varies in a trait-like manner across individuals and may influence the capacity for emotion regulation and vulnerability to affective symptoms, notably anxiety. Here, we demonstrate that an interoceptive training protocol improved perceptual accuracy in two tasks of heartbeat perception and reduced both state and trait anxiety in a subclinical sample, extending previous findings in autistic adults. Computational modelling indicated that accuracy improvement in the heartbeat discrimination task was associated with increases in the internal reliability estimate for interoceptive signals - their precision weighting - while a lower-level parameter representing noise in the interoceptive signal itself (which influences speed of learning) moderated this precision weighting improvement. Reductions in both state and trait anxiety in the training group were uniquely explained by computational parameter estimates, and not by conventional accuracy measures. These findings indicate that trait-like differences in interoceptive processing are modifiable and can be targeted to alleviate anxiety symptoms, and that interoceptive interventions may be best guided by a computational phenotyping approach.

neuroscience↗

bioRxiv2021

Relationship between systolic blood pressure and decision-making during emotional processing

ObjectiveEmotional states are expressed in body and mind through subjective experience of physiological changes. In previous work, subliminal priming of anger prior to lexical decisions increased systolic blood pressure (SBP). This increase predicted the slowing of response times (RT), suggesting that baroreflex-related autonomic changes and their interoceptive (feedback) representations, influence cognition. Alexithymia is a subclinical affective dysfunction characterized by difficulty in identifying emotions. Atypical autonomic and interoceptive profiles are observed in alexithymia. Therefore, we sought to identify mechanisms through which SBP fluctuations during emotional processing might influence decision-making, including whether alexithymia contributes to this relationship. MethodsThirty-two male participants performed an affect priming paradigm and completed the Toronto Alexithymia Scale. Emotional faces were briefly presented (20ms) prior a short-term memory task. RT, accuracy and SBP were recorded on a trial-by-trial basis. Generalized mixed-effects linear models were used to evaluate the impact of emotion, physiological changes, alexithymia score, and their interactions, on performances. ResultsA main effect of emotion was observed on accuracy. Participants were more accurate on trials with anger primes, compared to neutral priming. Greater accuracy was related to increased SBP. An interaction between SBP and emotion was observed on RT: Increased SBP was associated with RT prolongation in the anger priming condition, yet this relationship was absent under the sadness priming. Alexithymia did not significantly moderate the above relationships. ConclusionsOur data suggest that peripheral autonomic responses during affective challenges guide cognitive processes. We discuss our findings in the theoretical framework proposed by Lacey and Lacey (1970).

neuroscience↗

bioRxiv2020

The Filter Detection Task for measurement of breathing-related interoception and metacognition

The study of the brains processing of sensory inputs from within the body ( interoception) has been gaining rapid popularity in neuroscience, where interoceptive disturbances are thought to exist across a wide range of chronic physiological and psychological conditions. Here we present a task and analysis procedure to quantify specific dimensions of breathing-related interoception, including interoceptive sensitivity (accuracy), decision bias, metacognitive bias, and metacognitive performance. Two major developments address some of the challenges presented by low trial numbers in interoceptive experiments: (i) a novel adaptive algorithm to maintain task performance at 70-75% accuracy; (ii) an extended hierarchical metacognitive model to estimate regression parameters linking metacognitive performance to relevant (e.g. clinical) variables. We demonstrate the utility of the task and analysis developments, using both simulated data and three empirical datasets. This methodology represents an important step towards accurately quantifying interoceptive dimensions from a simple experimental procedure that is compatible with clinical settings.

neuroscience↗