Homology and Specificity of Natural Sound-Encoding in Human and Monkey Auditory Cortex

Understanding homologies and differences in auditory cortical processing in human and nonhuman primates is an essential step in elucidating the neurobiology of speech and language. Using fMRI responses to natural sounds, we investigated the representation of multiple acoustic features in auditory cortex of awake macaques and humans. Comparative analyses revealed homologous large-scale topographies not only for frequency but also for temporal and spectral modulations. In both species, posterior regions preferably encoded relatively fast temporal and coarse spectral information, whereas anterior regions encoded slow temporal and fine spectral modulations. Conversely, we observed a striking interspecies difference in cortical sensitivity to temporal modulations: While decoding from macaque auditory cortex was most accurate at fast rates (> 30 Hz), humans had highest sensitivity to ~3 Hz, a relevant rate for speech analysis. These findings suggest that characteristic tuning of human auditory cortex to slow temporal modulations is unique and may have emerged as a critical step in the evolution of speech and language

Dynamic Decomposition of Spatiotemporal Neural Signals

Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals

Bach speaks: A cortical "language-network" serves the processing of music

The aim of the present study was the investigation of neural correlates of music processing with fMRI. Chord sequences were presented to the participants, infrequently containing unexpected musical events. These events activated the areas of Broca and Wernicke, the superior temporal sulcus, Heschl's gyrus, both planum polare and planum temporale, as well as the anterior superior insular cortices. Some of these brain structures have previously been shown to be involved in music processing, but the cortical network comprising all these structures has up to now been thought to be domain-specific for language processing. To what extent this network might also be activated by the processing of non-linguistic information has remained unknown. The present fMRI-data reveal that the human brain employs this neuronal network also for the processing of musical information, suggesting that the cortical network known to support language processing is less domain-specific than previously believed

Top-down effects on early visual processing in humans: a predictive coding framework

An increasing number of human electroencephalography (EEG) studies examining the earliest component of the visual evoked potential, the so-called C1, have cast doubts on the previously prevalent notion that this component is impermeable to top-down effects. This article reviews the original studies that (i) described the C1, (ii) linked it to primary visual cortex (V1) activity, and (iii) suggested that its electrophysiological characteristics are exclusively determined by low-level stimulus attributes, particularly the spatial position of the stimulus within the visual field. We then describe conflicting evidence from animal studies and human neuroimaging experiments and provide an overview of recent EEG and magnetoencephalography (MEG) work showing that initial V1 activity in humans may be strongly modulated by higher-level cognitive factors. Finally, we formulate a theoretical framework for understanding top-down effects on early visual processing in terms of predictive coding

Perception-related modulations of local field potential power and coherence in primary visual cortex of awake monkey during binocular rivalry

Cortical synchronization at γ-frequencies (35–90 Hz) has been proposed to define the connectedness among the local parts of a perceived visual object. This hypothesis is still under debate. We tested it under conditions of binocular rivalry (BR), where a monkey perceived alternations among conflicting gratings presented singly to each eye at orthogonal orientations. We made multi-channel microelectrode recordings of multi-unit activity (MUA) and local field potentials (LFP) from striate cortex (V1) during BR while the monkey indicated his perception by pushing a lever. We analyzed spectral power and coherence of MUA and LFP over 4–90 Hz. As in previous work, coherence of γ-signals in most pairs of recording locations strongly depended on grating orientation when stimuli were presented congruently in both eyes. With incongruent (rivalrous) stimulation LFP power was often consistently modulated in consonance with the perceptual state. This was not visible in MUA. These perception-related modulations of LFP occurred at low and medium frequencies (<30 Hz), but not at γ-frequencies. Perception-related modulations of LFP coherence were also restricted to the low–medium range. In conclusion, our results do not support the expectation that γ-synchronization in V1 is related to the perceptual state during BR, but instead suggest a perception-related role of synchrony at low and medium frequencies

Enhanced amplitude modulations contribute to the Lombard intelligibility benefit: Evidence from the Nijmegen Corpus of Lombard Speech

Speakers adjust their voice when talking in noise, which is known as Lombard speech. These acoustic adjustments facilitate speech comprehension in noise relative to plain speech (i.e., speech produced in quiet). However, exactly which characteristics of Lombard speech drive this intelligibility benefit in noise remains unclear. This study assessed the contribution of enhanced amplitude modulations to the Lombard speech intelligibility benefit by demonstrating that (1) native speakers of Dutch in the Nijmegen Corpus of Lombard Speech (NiCLS) produce more pronounced amplitude modulations in noise vs. in quiet; (2) more enhanced amplitude modulations correlate positively with intelligibility in a speech-in-noise perception experiment; (3) transplanting the amplitude modulations from Lombard speech onto plain speech leads to an intelligibility improvement, suggesting that enhanced amplitude modulations in Lombard speech contribute towards intelligibility in noise. Results are discussed in light of recent neurobiological models of speech perception with reference to neural oscillators phase-locking to the amplitude modulations in speech, guiding the processing of speech

Brain rhythms of pain

Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain

Tuning of Human Modulation Filters Is Carrier-Frequency Dependent

Licensed under the Creative Commons Attribution License

Laminar fMRI: applications for cognitive neuroscience

The cortex is a massively recurrent network, characterized by feedforward and feedback connections between brain areas as well as lateral connections within an area. Feedforward, horizontal and feedback responses largely activate separate layers of a cortical unit, meaning they can be dissociated by lamina-resolved neurophysiological techniques. Such techniques are invasive and are therefore rarely used in humans. However, recent developments in high spatial resolution fMRI allow for non-invasive, in vivo measurements of brain responses specific to separate cortical layers. This provides an important opportunity to dissociate between feedforward and feedback brain responses, and investigate communication between brain areas at a more fine- grained level than previously possible in the human species. In this review, we highlight recent studies that successfully used laminar fMRI to isolate layer-specific feedback responses in human sensory cortex. In addition, we review several areas of cognitive neuroscience that stand to benefit from this new technological development, highlighting contemporary hypotheses that yield testable predictions for laminar fMRI. We hope to encourage researchers with the opportunity to embrace this development in fMRI research, as we expect that many future advancements in our current understanding of human brain function will be gained from measuring lamina-specific brain responses