Multisensory integration is particularly important in the human olfactory system, which is highly dependent on non-olfactory cues, yet its underlying neural mechanisms are not well understood. In this study, we use intracranial electroencephalography techniques to record neural activity in auditory and olfactory cortices during an auditory-olfactory matching task. Spoken cues evoke phase locking between low frequency oscillations in auditory and olfactory cortices prior to odor arrival. This phase synchrony occurs only when the participant’s later response is correct. Furthermore, the phase of low frequency oscillations in both auditory and olfactory cortical areas couples to the amplitude of high-frequency oscillations in olfactory cortex during correct trials. These findings suggest that phase synchrony is a fundamental mechanism for integrating cross-modal odor processing and highlight an important role for primary olfactory cortical areas in multisensory integration with the olfactory system.

Anticipating an odor improves detection and perception, yet the underlying neural mechanisms of olfactory anticipation are not well understood. In this study, we used human intracranial electroencephalography (iEEG) to show that anticipation resets the phase of delta oscillations in piriform cortex prior to odor arrival. Anticipatory phase reset correlates with ensuing odor-evoked theta power and improvements in perceptual accuracy. These effects were consistently present in each individual subject and were not driven by potential confounds of pre-inhale motor preparation or power changes. Together, these findings suggest that states of anticipation enhance olfactory perception through phase resetting of delta oscillations in piriform cortex.

Transcranial magnetic stimulation (TMS) is a powerful technique to noninvasively activate neurons in the brain. However, the relationship between TMS-generated electric fields (E-fields) and specific cortical responses is not well understood. The goal of this study was to investigate the relationship between induced E-fields and neocortical activation measured by metabolic responses. Human subject-specific detailed finite element models (FEM) of the head were constructed to calculate the distribution of induced cortical E-field vectors. Positron emission tomography (PET) recordings were made during concurrent TMS application as a measure of cortical activation. A functional model of local circuit connections was developed to study the relationship between applied magnetic fields and neocortical activation and was fitted to experimental data. Sensitivity of interneurons to induced tangential E-fields was over twice as strong as pyramidal neuron sensitivity to induced normal E-fields which may help explain why cortical electrophysiological responses to TMS have specific sensitivities to coil orientation. Furthermore, this study produced an algorithm for predicting electrophysiological responses in human neocortex with high accuracy (>95%) that could provide an invaluable tool for planning of specific regional cortical activation critical in both research and clinical applications.

Background: Breast cancer may result in remodeling of adjacent normal appearing breast tissues. Magnetic resonance imaging (MRI) is increasingly used in the diagnosis and follow-up of breast cancer by means of diffusion weighted imaging, which is based on thermal motion of water molecules in the extracellular fluid. Objectives: We investigated the correlation of visual assessment of peri-tumoral edema with peri-tumoral and tumoral apparent diffusion coefficient (ADC) values. Patients and Methods: In this cross-sectional study, from 2016 to 2018, 78 patients with 89 malignant breast lesions (mean age, 47 years) were examined by 1.5-T breast MRI. The lesions were categorized based on the visual assessment of peri-tumoral edema on T2 weighted imaging (T2WI) into two groups: (A) with edema (36 lesions) and (B) without edema (53 lesions). Measuring ADC values in the contralateral normal breast tissue, peri-tumoral tissue and peri-tumoral-normal tissue ADC ratio were compared between the two groups for all lesions. Results: The number of in situ lesions was higher in group B (7.5% vs 2.7%) with the p value of 0.01. The mean of ADC values in the normal breast tissue was 1.76 × 10-3mm2/s. Tumor ADCs were significantly lower in group A compared to group B (0.95 × 10-3mm2/s vs. 1.11 × 10-3mm2/s) with the P value of 0.003. However, peri-tumoral ADCs were significantly higher in group A (1.82 × 10-3mm2/s vs. 1.53 × 10-3mm2/s) with the p value of 0.005. The peri-tumoral-normal tissue ADC ratio was 0.87 in group B and about 1 in group A. However, the difference between normal tissue ADCs and peri-tumoral ADCs was only significant (P value of 0.005) in group B. The cut-off point value for differentiating normal tissue ADCs and peri-tumoral ADCs was 1.61 × 10-3mm2/s with the sensitivity of 65% and specificity of 70%. Conclusion: Breast cancer with peri-tumoral edema has lower tumoral ADC values, higher peri-tumoral ADC values and lower prevalence of in situ lesions. Visual assessment of peri-tumoral edema on T2WI could predict the tumoral characteristic on diffusion-weighted imaging.