Neuronal Modeling of Cross-Sensory Visual Evoked Magnetoencephalography Responses in the Auditory Cortex.

Previous studies have demonstrated that auditory cortex activity can be influenced by cross-sensory visual inputs. Intracortical laminar recordings in nonhuman primates have suggested a feedforward (FF) type profile for auditory evoked but feedback (FB) type for visual evoked activity in the auditory cortex. To test whether cross-sensory visual evoked activity in the auditory cortex is associated with FB inputs also in humans, we analyzed magnetoencephalography (MEG) responses from eight human subjects (six females) evoked by simple auditory or visual stimuli. In the estimated MEG source waveforms for auditory cortex regions of interest, auditory evoked response showed peaks at 37 and 90 ms and visual evoked response at 125 ms. The inputs to the auditory cortex were modeled through FF- and FB-type connections targeting different cortical layers using the Human Neocortical Neurosolver (HNN), which links cellular- and circuit-level mechanisms to MEG signals. HNN modeling suggested that the experimentally observed auditory response could be explained by an FF input followed by an FB input, whereas the cross-sensory visual response could be adequately explained by just an FB input. Thus, the combined MEG and HNN results support the hypothesis that cross-sensory visual input in the auditory cortex is of FB type. The results also illustrate how the dynamic patterns of the estimated MEG source activity can provide information about the characteristics of the input into a cortical area in terms of the hierarchical organization among areas.

Cortical depth profiles of auditory and visual 7 T functional MRI responses in human superior temporal areas.

Invasive neurophysiological studies in nonhuman primates have shown different laminar activation profiles to auditory vs. visual stimuli in auditory cortices and adjacent polymodal areas. Means to examine the underlying feedforward vs. feedback type influences noninvasively have been limited in humans. Here, using 1-mm isotropic resolution 3D echo-planar imaging at 7 T, we studied the intracortical depth profiles of functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) signals to brief auditory (noise bursts) and visual (checkerboard) stimuli. BOLD percent-signal-changes were estimated at 11 equally spaced intracortical depths, within regions-of-interest encompassing auditory (Heschl's gyrus, Heschl's sulcus, planum temporale, and posterior superior temporal gyrus) and polymodal (middle and posterior superior temporal sulcus) areas. Effects of differing BOLD signal strengths for auditory and visual stimuli were controlled via normalization and statistical modeling. The BOLD depth profile shapes, modeled with quadratic regression, were significantly different for auditory vs. visual stimuli in auditory cortices, but not in polymodal areas. The different depth profiles could reflect sensory-specific feedforward versus cross-sensory feedback influences, previously shown in laminar recordings in nonhuman primates. The results suggest that intracortical BOLD profiles can help distinguish between feedforward and feedback type influences in the human brain. Further experimental studies are still needed to clarify how underlying signal strength influences BOLD depth profiles under different stimulus conditions.

Targeted Modulation of Human Brain Interregional Effective Connectivity With Spike-Timing Dependent Plasticity.

OBJECTIVE: The ability to selectively up- or downregulate interregional brain connectivity would be useful for research and clinical purposes. Toward this aim, cortico-cortical paired associative stimulation (ccPAS) protocols have been developed in which two areas are repeatedly stimulated with a millisecond-level asynchrony. However, ccPAS results in humans using bifocal transcranial magnetic stimulation (TMS) have been variable, and the mechanisms remain unproven. In this study, our goal was to test whether ccPAS mechanism is spike-timing-dependent plasticity (STDP). MATERIALS AND METHODS: Eleven healthy participants received ccPAS to the left primary motor cortex (M1) → right M1 with three different asynchronies (5 milliseconds shorter, equal to, or 5 milliseconds longer than the 9-millisecond transcallosal conduction delay) in separate sessions. To observe the neurophysiological effects, single-pulse TMS was delivered to the left M1 before and after ccPAS while cortico-cortical evoked responses were extracted from the contralateral M1 using source-resolved electroencephalography. RESULTS: Consistent with STDP mechanisms, the effects on synaptic strengths flipped depending on the asynchrony. Further implicating STDP, control experiments suggested that the effects were unidirectional and selective to the targeted connection. CONCLUSION: The results support the idea that ccPAS induces STDP and may selectively up- or downregulate effective connectivity between targeted regions in the human brain.

Rehabilitating the addicted brain with transcranial magnetic stimulation.

Substance use disorders (SUDs) are one of the leading causes of morbidity and mortality worldwide. In spite of considerable advances in understanding the neural underpinnings of SUDs, therapeutic options remain limited. Recent studies have highlighted the potential of transcranial magnetic stimulation (TMS) as an innovative, safe and cost-effective treatment for some SUDs. Repetitive TMS (rTMS) influences neural activity in the short and long term by mechanisms involving neuroplasticity both locally, under the stimulating coil, and at the network level, throughout the brain. The long-term neurophysiological changes induced by rTMS have the potential to affect behaviours relating to drug craving, intake and relapse. Here, we review TMS mechanisms and evidence that rTMS is opening new avenues in addiction treatments.

A 3-axis coil design for multichannel TMS arrays.

PURPOSE: Multichannel Transcranial Magnetic Stimulation (mTMS) arrays enable multiple sites to be stimulated simultaneously or sequentially under electronic control without moving the system's stimulation coils. Here, we build and characterize the performance of a novel modular 3-axis TMS coil that can be utilized as a unit element in large-scale multichannel TMS arrays. METHODS: We determined the basic physical characteristics of the 3-axis TMS coil x-, y- and z-elements using a custom 2-channel programmable stimulator prototype. We mapped the temporal rate-of-change of the induced magnetic field (dB/dt) on a 2D plane parallel to the coil surface (including an extended line for full spatial coverage) and compared those values with predictions from magnetic field simulations. Temperature measurements were carried out to assess the incorporated air-cooling method. We measured the mutual and self-inductances of the x/y/z-elements to assess coupling between them. Additionally, we measured and calculated the coupling between z-elements in the array configuration. Finally, we performed electric field simulations to evaluate the stimulation intensity and focality of the coil and compared the results to conventional TMS coils as well as demonstrated suitability of the 3-axis coil for a multichannel array configuration. RESULTS: The experimentally obtained dB/dt values validated the computational model of the 3-axis coil and therefore confirmed that both the coil and stimulator system are operating as intended. The air-cooling system was effective for brief high-frequency pulse trains and extended single- and paired-pulse TMS protocols. The electromagnetic simulations suggested that an array of the 3-axis coils would have comparable stimulation intensity to conventional TMS coils, therefore enabling clearly suprathreshold stimulation of the human brain. The recorded coil coupling between the x/y/z-elements was < 1% and the maximal coupling between z-elements in the array configuration was 1.8% and 3.4% for the measured and calculated values, respectively. CONCLUSION: We presented a 3-axis coil intended for multichannel TMS arrays. The electromagnetic measurements and simulations verified that the coil fabrication met the desired specifications and that the inductive coupling between the elements was negligible. The air-cooled 3-axis TMS coil appears suitable to be used as an element in multichannel TMS arrays.

Rapid computation of TMS-induced E-fields using a dipole-based magnetic stimulation profile approach.

BACKGROUND: TMS neuronavigation with on-line display of the induced electric field (E-field) has the potential to improve quantitative targeting and dosing of stimulation, but present commercially available solutions are limited by simplified approximations. OBJECTIVE: Developing a near real-time method for accurate approximation of TMS induced E-fields with subject-specific high-resolution surface-based head models that can be utilized for TMS navigation. METHODS: Magnetic dipoles are placed on a closed surface enclosing an MRI-based head model of the subject to define a set of basis functions for the incident and total E-fields that define the subject's Magnetic Stimulation Profile (MSP). The near real-time speed is achieved by recognizing that the total E-field of the coil only depends on the incident E-field and the conductivity boundary geometry. The total E-field for any coil position can be obtained by matching the incident field of the stationary dipole basis set with the incident E-field of the moving coil and applying the same basis coefficients to the total E-field basis functions. RESULTS: Comparison of the MSP-based approximation with an established TMS solver shows great agreement in the E-field amplitude (relative maximum error around 5%) and the spatial distribution patterns (correlation >98%). Computation of the E-field took ~100 ms on a cortical surface mesh with 120k facets. CONCLUSION: The numerical accuracy and speed of the MSP approximation method make it well suited for a wide range of computational tasks including interactive planning, targeting, dosing, and visualization of the intracranial E-fields for near real-time guidance of coil positioning.

Customizing TMS Applications in Traumatic Brain Injury Using Neuroimaging.

Optimizing transcranial magnetic stimulation (TMS) treatments in traumatic brain injury (TBI) and co-occurring conditions may benefit from neuroimaging-based customization. PARTICIPANTS: Our total sample (N = 97) included 58 individuals with TBI (49 mild, 8 moderate, and 1 severe in a state of disordered consciousness), of which 24 had co-occurring conditions (depression in 14 and alcohol use disorder in 10). Of those without TBI, 6 individuals had alcohol use disorder and 33 were healthy controls. Of our total sample, 54 were veterans and 43 were civilians. DESIGN: Proof-of-concept study incorporating data from 5 analyses/studies that used multimodal approaches to integrate neuroimaging with TMS. MAIN MEASURES: Multimodal neuroimaging methods including structural magnetic resonance imaging (MRI), MRI-guided TMS navigation, functional MRI, diffusion MRI, and TMS-induced electric fields. Outcomes included symptom scales, neuropsychological tests, and physiological measures. RESULTS: It is feasible to use multimodal neuroimaging data to customize TMS targets and understand brain-based changes in targeted networks among people with TBI. CONCLUSIONS: TBI is an anatomically heterogeneous disorder. Preliminary evidence from the 5 studies suggests that using multimodal neuroimaging approaches to customize TMS treatment is feasible. To test whether this will lead to increased clinical efficacy, studies that integrate neuroimaging and TMS targeting data with outcomes are needed.

Frequency-specific noninvasive modulation of memory retrieval and its relationship with hippocampal network connectivity.

Episodic memory is thought to rely on interactions of the hippocampus with other regions of the distributed hippocampal-cortical network (HCN) via interregional activity synchrony in the theta frequency band. We sought to causally test this hypothesis using network-targeted transcranial magnetic stimulation. Healthy human participants completed four experimental sessions, each involving a different stimulation pattern delivered to the same individualized parietal cortex location of the HCN for all sessions. There were three active stimulation conditions, including continuous theta-burst stimulation, intermittent theta-burst stimulation, and beta-frequency (20-Hz) repetitive stimulation, and one sham condition. Resting-state fMRI and episodic memory testing were used to assess the impact of stimulation on hippocampal fMRI connectivity related to retrieval success. We hypothesized that theta-burst stimulation conditions would most strongly influence hippocampal-HCN fMRI connectivity and retrieval, given the hypothesized relevance of theta-band activity for HCN memory function. Continuous theta-burst stimulation improved item retrieval success relative to sham and relative to beta-frequency stimulation, whereas intermittent theta-burst stimulation led to numerical but nonsignificant item retrieval improvement. Mean hippocampal fMRI connectivity did not vary for any stimulation conditions, whereas individual differences in retrieval improvements due to continuous theta-burst stimulation were associated with corresponding increases in fMRI connectivity between the hippocampus and other HCN locations. No such memory-related connectivity effects were identified for the other stimulation conditions, indicating that only continuous theta-burst stimulation affected memory-related hippocampal-HCN connectivity. Furthermore, these effects were specific to the targeted HCN, with no significant memory-related fMRI connectivity effects for two distinct control brain networks. These findings support a causal role for fMRI connectivity of the hippocampus with the HCN in episodic memory retrieval and indicate that contributions of this network to retrieval are particularly sensitive to continuous theta-burst noninvasive stimulation.

Neuronal representations of distance in human auditory cortex.

Neuronal mechanisms of auditory distance perception are poorly understood, largely because contributions of intensity and distance processing are difficult to differentiate. Typically, the received intensity increases when sound sources approach us. However, we can also distinguish between soft-but-nearby and loud-but-distant sounds, indicating that distance processing can also be based on intensity-independent cues. Here, we combined behavioral experiments, fMRI measurements, and computational analyses to identify the neural representation of distance independent of intensity. In a virtual reverberant environment, we simulated sound sources at varying distances (15-100 cm) along the right-side interaural axis. Our acoustic analysis suggested that, of the individual intensity-independent depth cues available for these stimuli, direct-to-reverberant ratio (D/R) is more reliable and robust than interaural level difference (ILD). However, on the basis of our behavioral results, subjects' discrimination performance was more consistent with complex intensity-independent distance representations, combining both available cues, than with representations on the basis of either D/R or ILD individually. fMRI activations to sounds varying in distance (containing all cues, including intensity), compared with activations to sounds varying in intensity only, were significantly increased in the planum temporale and posterior superior temporal gyrus contralateral to the direction of stimulation. This fMRI result suggests that neurons in posterior nonprimary auditory cortices, in or near the areas processing other auditory spatial features, are sensitive to intensity-independent sound properties relevant for auditory distance perception.

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise.

How can we concentrate on relevant sounds in noisy environments? A "gain model" suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A "tuning model" suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMRI) while subjects attended to tones delivered to one ear and ignored opposite-ear inputs. The attended ear was switched every 30 s to quantify how quickly the effects evolve. To produce overlapping inputs, the tones were presented alone vs. during white-noise masking notch-filtered ±1/6 octaves around the tone center frequencies. Amplitude modulation (39 vs. 41 Hz in opposite ears) was applied for "frequency tagging" of attention effects on maskers. Noise masking reduced early (50-150 ms; N1) auditory responses to unattended tones. In support of the tuning model, selective attention canceled out this attenuating effect but did not modulate the gain of 50-150 ms activity to nonmasked tones or steady-state responses to the maskers themselves. These tuning effects originated at nonprimary auditory cortices, purportedly occupied by neurons that, without attention, have wider frequency tuning than ±1/6 octaves. The attentional tuning evolved rapidly, during the first few seconds after attention switching, and correlated with behavioral discrimination performance. In conclusion, a simple gain model alone cannot explain auditory selective attention. In nonprimary auditory cortices, attention-driven short-term plasticity retunes neurons to segregate relevant sounds from noise.

Association between fatigue, peripheral serotonin, and L-carnitine in hypothyroidism and in chronic fatigue syndrome.

Background: Fatigue of unknown origin is a hallmark symptom in chronic fatigue syndrome (CFS) and is also found in 20% of hypothyroidism patients despite appropriate levothyroxine treatment. Here, we suggest that in these disorders, peripheral serotonin levels are low, and elevating them to normal range with L-carnitine is accompanied with reduced fatigue. Methods: We conducted a retrospective analysis of follow-up clinical data (CFS N=12; hypothyroidism with fatigue N=40) where serum serotonin and fatigue levels were compared before vs. after 7 weeks of oral L-carnitine supplementation. Results: After L-carnitine, serotonin increased (8-fold in CFS, Sig. = 0.002, 6-fold in hypothyroidism, Sig. < 0.001) whereas fatigue decreased (2-fold in both CFS and hypothyroidism, Sig. = 0.002 for CFS, Sig. < 0.001 for hypothyroidism). There was a negative correlation between serotonin level and fatigue (for CFS, rho = -0.49 before and -0.67 after L-carnitine; for hypothyroidism, rho = -0.24 before and -0.83 after L-carnitine). Conclusions: These findings suggest a new link between low peripheral serotonin, L-carnitine, and fatigue.

Neuronal modeling of magnetoencephalography responses in auditory cortex to auditory and visual stimuli.

Previous studies have demonstrated that auditory cortex activity can be influenced by crosssensory visual inputs. Intracortical recordings in non-human primates (NHP) have suggested a bottom-up feedforward (FF) type laminar profile for auditory evoked but top-down feedback (FB) type for cross-sensory visual evoked activity in the auditory cortex. To test whether this principle applies also to humans, we analyzed magnetoencephalography (MEG) responses from eight human subjects (six females) evoked by simple auditory or visual stimuli. In the estimated MEG source waveforms for auditory cortex region of interest, auditory evoked responses showed peaks at 37 and 90 ms and cross-sensory visual responses at 125 ms. The inputs to the auditory cortex were then modeled through FF and FB type connections targeting different cortical layers using the Human Neocortical Neurosolver (HNN), which consists of a neocortical circuit model linking the cellular- and circuit-level mechanisms to MEG. The HNN models suggested that the measured auditory response could be explained by an FF input followed by an FB input, and the crosssensory visual response by an FB input. Thus, the combined MEG and HNN results support the hypothesis that cross-sensory visual input in the auditory cortex is of FB type. The results also illustrate how the dynamic patterns of the estimated MEG/EEG source activity can provide information about the characteristics of the input into a cortical area in terms of the hierarchical organization among areas.

Fast and Accurate EEG/MEG BEM-Based Forward Problem Solution for High-Resolution Head Models.

A BEM (boundary element method) based approach is developed to accurately solve an EEG/MEG forward problem for a modern high-resolution head model in approximately 60 seconds using a common workstation. The method utilizes a charge-based BEM with fast multipole acceleration (BEM-FMM) and a "smart" mesh pre-refinement (called b-refinement) close to the singular source(s). No costly matrix-filling or direct solution steps typical for the standard BEM are required; the method generates on-skin voltages as well as MEG magnetic fields for high-resolution head models in approximately 60 seconds after initial model assembly. The method is verified both theoretically and experimentally.

Accuracy of dipole source reconstruction in the 3-layer BEM model against the 5-layer BEM-FMM model.

Objective: To compare cortical dipole fitting spatial accuracy between the widely used yet highly simplified 3-layer and modern more realistic 5-layer BEM-FMM models with and without adaptive mesh refinement (AMR) methods. Methods: We generate simulated noiseless 256-channel EEG data from 5-layer (7-compartment) meshes of 15 subjects from the Connectome Young Adult dataset. For each subject, we test four dipole positions, three sets of conductivity values, and two types of head segmentation. We use the boundary element method (BEM) with fast multipole method (FMM) acceleration, with or without (AMR), for forward modeling. Dipole fitting is carried out with the FieldTrip MATLAB toolbox. Results: The average position error (across all tested dipoles, subjects, and models) is ~4 mm, with a standard deviation of ~2 mm. The orientation error is ~20° on average, with a standard deviation of ~15°. Without AMR, the numerical inaccuracies produce a larger disagreement between the 3- and 5-layer models, with an average position error of ~8 mm (6 mm standard deviation), and an orientation error of 28° (28° standard deviation). Conclusions: The low-resolution 3-layer models provide excellent accuracy in dipole localization. On the other hand, dipole orientation is retrieved less accurately. Therefore, certain applications may require more realistic models for practical source reconstruction. AMR is a critical component for improving the accuracy of forward EEG computations using a high-resolution 5-layer volume conduction model. Significance: Improving EEG source reconstruction accuracy is important for several clinical applications, including epilepsy and other seizure-inducing conditions.

fMRI hemodynamics accurately reflects neuronal timing in the human brain measured by MEG.

Neuronal activation sequence information is essential for understanding brain functions. Extracting such timing information from blood oxygenation level dependent (BOLD) fMRI is confounded by interregional neurovascular differences and poorly understood relations between BOLD and electrophysiological response delays. Here, we recorded whole-head BOLD fMRI at 100 ms resolution and magnetoencephalography (MEG) during a visuomotor reaction-time task. Both methods detected the same activation sequence across five regions, from visual towards motor cortices, with linearly correlated interregional BOLD and MEG response delays. The smallest significant interregional BOLD delay was 100 ms; all delays ≥400 ms were significant. Switching the order of external events reversed the sequence of BOLD activations, indicating that interregional neurovascular differences did not confound the results. This may open new avenues for using fMRI to follow rapid activation sequences in the brain.

Spectrotemporal content of human auditory working memory represented in functional connectivity patterns.

Recent research suggests that working memory (WM), the mental sketchpad underlying thinking and communication, is maintained by multiple regions throughout the brain. Whether parts of a stable WM representation could be distributed across these brain regions is, however, an open question. We addressed this question by examining the content-specificity of connectivity-pattern matrices between subparts of cortical regions-of-interest (ROI). These connectivity patterns were calculated from functional MRI obtained during a ripple-sound auditory WM task. Statistical significance was assessed by comparing the decoding results to a null distribution derived from a permutation test considering all comparable two- to four-ROI connectivity patterns. Maintained WM items could be decoded from connectivity patterns across ROIs in frontal, parietal, and superior temporal cortices. All functional connectivity patterns that were specific to maintained sound content extended from early auditory to frontoparietal cortices. Our results demonstrate that WM maintenance is supported by content-specific patterns of functional connectivity across different levels of cortical hierarchy.

Depression core network-based individualized targeting for transcranial magnetic stimulation.

BACKGROUND: Transcranial magnetic stimulation (TMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for major depressive disorder (MDD). Recent attempts to improve TMS efficacy by individually targeting DLPFC subregions that are functionally connected to the subgenual anterior cingulate cortex (sgACC) appear promising. However, sgACC covers only a small subset of core MDD-related areas. Further, fMRI connectivity of sgACC is poorly repeatable within subjects. METHODS: Based on an fMRI database analysis, we first constructed a novel core network model (CNM), capturing voxelwise emotion regulation- and MDD-related DLPFC connectivity. Then, in a sample of 15 healthy subjects and 29 MDD patients, we assessed (i) within-subject repeatability of the DLPFC connectivity patterns computed from time segments of varying lengths of individual-level fMRI data and (ii) association of MDD severity with the individual DLPFC connectivity strengths. We extracted group-level connectivity strengths in CNM from individual DLPFC coordinates stimulated with neuronavigated TMS in a separate sample of 25 MDD patients. These connectivity strengths were then correlated with individual TMS efficacy. RESULTS: Compared with sgACC connectivity, CNM increased intraindividual repeatability 5-fold. DLPFC connectivity strength from CNM was associated with MDD severity and TMS efficacy. While the locations of CNM-based individual TMS targets remained constant within individuals, they varied considerably between individuals. CONCLUSIONS: CNM increased repeatability of functional targeting to a clinically feasible level. The observed association of MDD severity and TMS efficacy with DLPFC connectivity supports the validity of the CNM. The interindividual differences in target locations motivate future individualized clinical trials leveraging the CNM.

Ultrafast inverse imaging techniques for fMRI.

Inverse imaging (InI) supercharges the sampling rate of traditional functional MRI 10-100 fold at a cost of a moderate reduction in spatial resolution. The technique is inspired by similarities between multi-sensor magnetoencephalography (MEG) and highly parallel radio-frequency (RF) MRI detector arrays. Using presently available 32-channel head coils at 3T, InI can be sampled at 10 Hz and provides about 5-mm cortical spatial resolution with whole-brain coverage. Here we discuss the present applications of InI, as well as potential future challenges and opportunities in further improving its spatiotemporal resolution and sensitivity. InI may become a helpful tool for clinicians and neuroscientists for revealing the complex dynamics of brain functions during task-related and resting states.

Synchronization patterns reveal neuronal coding of working memory content.

Neuronal oscillations are suggested to play an important role in auditory working memory (WM), but their contribution to content-specific representations has remained unclear. Here, we measure magnetoencephalography during a retro-cueing task with parametric ripple-sound stimuli, which are spectrotemporally similar to speech but resist non-auditory memory strategies. Using machine learning analyses, with rigorous between-subject cross-validation and non-parametric permutation testing, we show that memorized sound content is strongly represented in phase-synchronization patterns between subregions of auditory and frontoparietal cortices. These phase-synchronization patterns predict the memorized sound content steadily across the studied maintenance period. In addition to connectivity-based representations, there are indices of more local, "activity silent" representations in auditory cortices, where the decoding accuracy of WM content significantly increases after task-irrelevant "impulse stimuli." Our results demonstrate that synchronization patterns across auditory sensory and association areas orchestrate neuronal coding of auditory WM content. This connectivity-based coding scheme could also extend beyond the auditory domain.

Onset timing of cross-sensory activations and multisensory interactions in auditory and visual sensory cortices.

Here we report early cross-sensory activations and audiovisual interactions at the visual and auditory cortices using magnetoencephalography (MEG) to obtain accurate timing information. Data from an identical fMRI experiment were employed to support MEG source localization results. Simple auditory and visual stimuli (300-ms noise bursts and checkerboards) were presented to seven healthy humans. MEG source analysis suggested generators in the auditory and visual sensory cortices for both within-modality and cross-sensory activations. fMRI cross-sensory activations were strong in the visual but almost absent in the auditory cortex; this discrepancy with MEG possibly reflects the influence of acoustical scanner noise in fMRI. In the primary auditory cortices (Heschl's gyrus) the onset of activity to auditory stimuli was observed at 23 ms in both hemispheres, and to visual stimuli at 82 ms in the left and at 75 ms in the right hemisphere. In the primary visual cortex (Calcarine fissure) the activations to visual stimuli started at 43 ms and to auditory stimuli at 53 ms. Cross-sensory activations thus started later than sensory-specific activations, by 55 ms in the auditory cortex and by 10 ms in the visual cortex, suggesting that the origins of the cross-sensory activations may be in the primary sensory cortices of the opposite modality, with conduction delays (from one sensory cortex to another) of 30-35 ms. Audiovisual interactions started at 85 ms in the left auditory, 80 ms in the right auditory and 74 ms in the visual cortex, i.e., 3-21 ms after inputs from the two modalities converged.