Distinct neural mechanisms and temporal constraints govern a cascade of audiotactile interactions

Synchrony is a crucial cue indicating whether sensory signals are caused by single or independent sources. In order to be integrated and produce multisensory behavioural benefits, signals must co-occur within a temporal integration window (TIW). Yet, the underlying neural determinants and mechanisms of integration across asynchronies remain unclear. This psychophysics and electroencephalography study investigated the temporal constraints of behavioural response facilitation and neural interactions for evoked response potentials (ERP), inter-trial coherence (ITC), and time-frequency (TF) power. Participants were presented with noise bursts, ‘taps to the face’, and their audiotactile (AT) combinations at seven asynchronies: 0, ±20, ±70, and ±500 ms. Behaviourally we observed an inverted U-shape function for AT response facilitation, which was maximal for synchronous AT stimulation and declined within a ≤70 ms TIW. For ERPs, we observed AT interactions at 110 ms for near-synchronous stimuli within a ≤20 ms TIW and at 400 ms within a ≤70 ms TIW consistent with behavioural response facilitation. By contrast, AT interactions for theta ITC and ERPs at 200 ms post-stimulus were selective for ±70 ms asynchrony, potentially mediated via phase resetting. Finally, interactions for induced theta power and alpha/beta power rebound emerged at 800-1100 ms across several asynchronies including even 500 ms auditory leading asynchrony. In sum, we observed neural interactions that were confined to or extending beyond the behavioural TIW or specific for ±70 ms asynchrony. This diversity of temporal profiles and constraints demonstrates that multisensory integration unfolds in a cascade of interactions that are governed by distinct neural mechanisms

The neural mechanisms of audiotactile binding depend on asynchrony

Asynchrony is a critical cue informing the brain whether sensory signals are caused by a common source and should be integrated or segregated. This psychophysics‐electroencephalography (EEG) study investigated the influence of asynchrony on how the brain binds audiotactile (AT) signals to enable faster responses in a redundant target paradigm. Human participants actively responded (psychophysics) or passively attended (EEG) to noise bursts, ‘taps‐to‐the‐face’, and their AT combinations at seven AT asynchronies: 0, ±20, ±70, and ±500ms. Behaviourally, observers were faster at detecting AT than unisensory stimuli within a temporal integration window: the redundant target effect was maximal for synchronous stimuli and declined within a ≤70ms AT asynchrony. EEG revealed a cascade of AT interactions that relied on different neural mechanisms depending on AT asynchrony. At small (≤20ms) asynchronies, AT interactions arose for evoked response potentials (ERPs) at 110ms and ~400ms post‐stimulus. Selectively at ±70ms asynchronies AT interactions were observed for the P200 ERP, theta‐band inter‐trial coherence (ITC) and power at ~200ms poststimulus. In conclusion, AT binding was mediated by distinct neural mechanisms depending on the asynchrony of the AT signals. Early AT interactions in ERPs and theta‐band ITC and power were critical for the behavioural response facilitation within a ≤±70ms temporal integration windo

Spatiotemporal integration of tactile information in human somatosensory cortex

BACKGROUND: Our goal was to examine the spatiotemporal integration of tactile information in the hand representation of human primary somatosensory cortex (anterior parietal somatosensory areas 3b and 1), secondary somatosensory cortex (S2), and the parietal ventral area (PV), using high-resolution whole-head magnetoencephalography (MEG). To examine representational overlap and adaptation in bilateral somatosensory cortices, we used an oddball paradigm to characterize the representation of the index finger (D2; deviant stimulus) as a function of the location of the standard stimulus in both right- and left-handed subjects. RESULTS: We found that responses to deviant stimuli presented in the context of standard stimuli with an interstimulus interval (ISI) of 0.33s were significantly and bilaterally attenuated compared to deviant stimulation alone in S2/PV, but not in anterior parietal cortex. This attenuation was dependent upon the distance between the deviant and standard stimuli: greater attenuation was found when the standard was immediately adjacent to the deviant (D3 and D2 respectively), with attenuation decreasing for non-adjacent fingers (D4 and opposite D2). We also found that cutaneous mechanical stimulation consistently elicited not only a strong early contralateral cortical response but also a weak ipsilateral response in anterior parietal cortex. This ipsilateral response appeared an average of 10.7 ± 6.1 ms later than the early contralateral response. In addition, no hemispheric differences either in response amplitude, response latencies or oddball responses were found, independent of handedness. CONCLUSION: Our findings are consistent with the large receptive fields and long neuronal recovery cycles that have been described in S2/PV, and suggest that this expression of spatiotemporal integration underlies the complex functions associated with this region. The early ipsilateral response suggests that anterior parietal fields also receive tactile input from the ipsilateral hand. The lack of a hemispheric difference in responses to digit stimulation supports a lack of any functional asymmetry in human somatosensory cortex

The relationship between magnetic and electrophysiological responses to complex tactile stimuli

<p>Abstract</p> <p>Background</p> <p>Magnetoencephalography (MEG) has become an increasingly popular technique for non-invasively characterizing neuromagnetic field changes in the brain at a high temporal resolution. To examine the reliability of the MEG signal, we compared magnetic and electrophysiological responses to complex natural stimuli from the same animals. We examined changes in neuromagnetic fields, local field potentials (LFP) and multi-unit activity (MUA) in macaque monkey primary somatosensory cortex that were induced by varying the rate of mechanical stimulation. Stimuli were applied to the fingertips with three inter-stimulus intervals (ISIs): 0.33s, 1s and 2s.</p> <p>Results</p> <p>Signal intensity was inversely related to the rate of stimulation, but to different degrees for each measurement method. The decrease in response at higher stimulation rates was significantly greater for MUA than LFP and MEG data, while no significant difference was observed between LFP and MEG recordings. Furthermore, response latency was the shortest for MUA and the longest for MEG data.</p> <p>Conclusion</p> <p>The MEG signal is an accurate representation of electrophysiological responses to complex natural stimuli. Further, the intensity and latency of the MEG signal were better correlated with the LFP than MUA data suggesting that the MEG signal reflects primarily synaptic currents rather than spiking activity. These differences in latency could be attributed to differences in the extent of spatial summation and/or differential laminar sensitivity.</p

MEG in the macaque monkey and human: distinguishing cortical fields in space and time.

Magnetoencephalography (MEG) is an increasingly popular non-invasive tool used to record, on a millisecond timescale, the magnetic field changes generated by cortical neural activity. MEG has the advantage, over fMRI for example, that it is a direct measure of neural activity. In the current investigation we used MEG to measure cortical responses to tactile and auditory stimuli in the macaque monkey. We had two aims. First, we sought to determine whether MEG, a technique that may have low spatial accuracy, could be used to distinguish the location and organization of sensory cortical fields in macaque monkeys, a species with a relatively small brain compared to that of the human. Second, we wanted to examine the temporal dynamics of cortical responses in the macaque monkey relative to the human. We recorded MEG data from anesthetized monkeys and, for comparison, from awake humans that were presented with simple tactile and auditory stimuli. Neural source reconstruction of MEG data showed that primary somatosensory and auditory cortex could be differentiated and, further, that separate representations of the digit and lip within somatosensory cortex could be identified in macaque monkeys as well as humans. We compared the latencies of activity from monkey and human data for the three stimulation types and proposed a correspondence between the neural responses of the two species. We thus demonstrate the feasibility of using MEG in the macaque monkey and provide a non-human primate model for examining the relationship between external evoked magnetic fields and their underlying neural sources

Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations

Cortical oscillations have been shown to represent fundamental functions of a working brain, e.g., communication, stimulus binding, error monitoring, and inhibition, and are directly linked to behavior. Recent studies intervening with these oscillations have demonstrated effective modulation of both the oscillations and behavior. In this review, we collect evidence in favor of how hypothesis-driven methods can be used to augment cognition by optimizing cortical oscillations. We elaborate their potential usefulness for three target groups: healthy elderly, patients with attention deficit/hyperactivity disorder, and healthy young adults. We discuss the relevance of neuronal oscillations in each group and show how each of them can benefit from the manipulation of functionally-related oscillations. Further, we describe methods for manipulation of neuronal oscillations including direct brain stimulation as well as indirect task alterations. We also discuss practical considerations about the proposed techniques. In conclusion, we propose that insights from neuroscience should guide techniques to augment human cognition, which in turn can provide a better understanding of how the human brain works

Abstract

We have developed a novel algorithm for integrating source localization and noise suppression based on a probabilistic graphical model of stimulus-evoked MEG/EEG data. Our algorithm localizes multiple dipoles while suppressing noise sources with the computational complexity equivalent to a single dipole scan, and is therefore more efficient than traditional multidipole fitting procedures. In simulation, the algorithm can accurately localize and estimate the time course of several simultaneously-active dipoles, with rotating or fixed orientation, at noise levels typical for averaged MEG data. Furthermore, the algorithm is superior to beamforming techniques, which we show to be an approximation to our graphical model, in estimation of temporally correlated sources. Success of this algorithm for localizing auditory cortex in a tumor patient and for localizing an epileptic spike source are also demonstrated.

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