Steady-state responses to concurrent melodies: source distribution, top-down, and bottom-up attention.

Humans can direct attentional resources to a single sound occurring simultaneously among others to extract the most behaviourally relevant information present. To investigate this cognitive phenomenon in a precise manner, we used frequency-tagging to separate neural auditory steady-state responses (ASSRs) that can be traced back to each auditory stimulus, from the neural mix elicited by multiple simultaneous sounds. Using a mixture of 2 frequency-tagged melody streams, we instructed participants to selectively attend to one stream or the other while following the development of the pitch contour. Bottom-up attention towards either stream was also manipulated with salient changes in pitch. Distributed source analyses of magnetoencephalography measurements showed that the effect of ASSR enhancement from top-down driven attention was strongest at the left frontal cortex, while that of bottom-up driven attention was dominant at the right temporal cortex. Furthermore, the degree of ASSR suppression from simultaneous stimuli varied across cortical lobes and hemisphere. The ASSR source distribution changes from temporal-dominance during single-stream perception, to proportionally more activity in the frontal and centro-parietal cortical regions when listening to simultaneous streams. These findings are a step forward to studying cognition in more complex and naturalistic soundscapes using frequency-tagging.

Auditory steady-state responses during and after a stimulus: Cortical sources, and the influence of attention and musicality.

The auditory steady-state response (ASSR) is an oscillatory brain response generated by periodic auditory stimuli and originates mainly from the temporal auditory cortices. Recent data show that while the auditory cortices are indeed strongly activated by the stimulus when it is present (ON ASSR), the anatomical distribution of ASSR sources involves also parietal and frontal cortices, indicating that the ASSR is a more complex phenomenon than previously believed. Furthermore, while the ASSR typically continues to oscillate even after the stimulus has stopped (OFF ASSR), very little is known about the characteristics of the OFF ASSR and how it compares to the ON ASSR. Here, we assessed whether the OFF and ON ASSR powers are modulated by the stimulus properties (i.e. volume and pitch), selective attention, as well as individual musical sophistication. We also investigated the cortical source distribution of the OFF ASSR using a melody tracking task, in which attention was directed between uniquely amplitude-modulated melody streams that differed in pitch. The ON and OFF ASSRs were recorded with magnetoencephalography (MEG) on a group of participants varying from low to high degree of musical sophistication. Our results show that the OFF ASSR is different from the ON ASSR in nearly every aspect. While the ON ASSR was modulated by the stimulus properties and selective attention, the OFF ASSR was not influenced by any of these factors. Furthermore, while the ON ASSR was generated primarily from temporal sources, the OFF ASSR originated mainly from the frontal cortex. These findings challenge the notion that the OFF ASSR is merely a continuation of the ON ASSR. Rather, they suggest that the OFF ASSR is an internally-driven signal that develops from an initial sensory processing state (ON ASSR), with both types of ASSRs clearly differing in cortical representation and character. Furthermore, our results show that the ON ASSR power was enhanced by selective attention at cortical sources within each of the bilateral frontal, temporal, parietal and insular lobes. Finally, the ON ASSR proved sensitive to musicality, demonstrating positive correlations between musical sophistication and ASSR power, as well as with the degree of attentional ASSR modulation at the left and right parietal cortices. Taken together, these results show new aspects of the ASSR response, and demonstrate its usefulness as an effective tool for analysing how selective attention interacts with individual abilities in music perception.

Attentional modulation of the auditory steady-state response across the cortex.

Selective auditory attention allows us to focus on relevant sounds within noisy or complex auditory environments, and is essential for the processing of speech and music. The auditory steady-state response (ASSR) has been proposed as a neural measure for tracking selective auditory attention, even within continuous and complex soundscapes. However, the current literature is inconsistent on how the ASSR is influenced by selective attention, with findings based primarily on attention being directed to either ear rather than to sound content. In this experiment, a mixture of melody streams was presented to both ears identically (diotically) as we examined if selective auditory attention to sound content influences the ASSR. Using magnetoencephalography (MEG), we assessed the stream-specific ASSRs from three frequency-tagged melody streams when attention was directed between each melody stream, based on their respective pitch and timing. Our main results showed that selective attention enhances the ASSR power of an attended melody stream by 14% at a general sensor level. This ability to readily capture attentional changes in a stimuli-precise manner makes the ASSR a useful tool for studying selective auditory attention, especially in complex auditory environments. As a secondary aim, we explored the distribution of cortical ASSR sources and their respective attentional modulation using a distributed source model of the ASSR activity. Notably, we uncovered the existence of ASSR attentional modulation outside the temporal cortices. Across-subject averages of the attentional enhancement over the cortical surface suggest that frontal regions show up to ~80% enhancement, while temporal and parietal cortices were enhanced by 20-25%. Importantly, this work advocates a novel 'beyond the temporal cortex' perspective on ASSR modulation and also serves as a template for future studies to precisely pin-point which cortical sites are more susceptible to ASSR attentional modulation.

The Swedish National Facility for Magnetoencephalography Parkinson's disease dataset.

Parkinson's disease (PD) is characterised by a loss of dopamine and dopaminergic cells. The consequences hereof are widespread network disturbances in brain function. It is an ongoing topic of investigation how the disease-related changes in brain function manifest in PD relate to clinical symptoms. We present The Swedish National Facility for Magnetoencephalography Parkinson's Disease Dataset (NatMEG-PD) as an Open Science contribution to identify the functional neural signatures of Parkinson's disease and contribute to diagnosis and treatment. The dataset contains whole-head magnetoencephalographic (MEG) recordings from 66 well-characterised PD patients on their regular dose of dopamine replacement therapy and 68 age- and sex-matched healthy controls. NatMEG-PD contains three-minute eyes-closed resting-state MEG, MEG during an active movement task, and MEG during passive movements. The data includes anonymised MRI for source analysis and clinical scores. MEG data is rich in nature and can be used to explore numerous functional features. By sharing these data, we hope other researchers will contribute to advancing our understanding of the relationship between brain activity and disease state or symptoms.

Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease.

Parkinson's disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients' disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.