Auditory evoked fields measured noninvasively with small-animal MEG reveal rapid repetition suppression in the guinea pig

Mismatch Responses Evoked by Sound Pattern Violation in the Songbird Forebrain Suggest Common Auditory Processing With Human

Learning sound patterns in the natural auditory scene and detecting deviant patterns are adaptive behaviors that aid animals in predicting future events and behaving accordingly. Mismatch negativity (MMN) is a component of the event-related potential (ERP) that is reported in humans when they are exposed to unexpected or rare stimuli. MMN has been studied in several non-human animals using an oddball task by presenting deviant pure tones that were interspersed within a sequence of standard pure tones and comparing the neural responses. While accumulating evidence suggests the homology of non-human animal MMN-like responses (MMRs) and human MMN, it is still not clear whether the function and neural mechanisms of MMRs and MMN are comparable. The Java sparrow (Lonchura oryzivora) is a songbird that is a vocal learner, is highly social, and maintains communication with flock members using frequently repeated contact calls and song. We expect that the songbird is a potentially useful animal model that will broaden our understanding of the characterization of MMRs. Due to this, we chose this species to explore MMRs to the deviant sounds in the single sound oddball task using both pure tones and natural vocalizations. MMRs were measured in the caudomedial nidopallium (NCM), a higher-order auditory area. We recorded local field potentials under freely moving conditions. Significant differences were observed in the negative component between deviant and standard ERPs, both to pure tones and natural vocalizations in the oddball sequence. However, the subsequent experiments using the randomized standard sequence and regular pattern sequence suggest the possibility that MMR elicited in the oddball paradigm reflects the adaptation to a repeated standard sound but not the genuine deviance detection. Furthermore, we presented contact call triplet sequences and investigated MMR in the NCM in response to sound sequence order. We found a significant negative shift in response to a difference in sequence pattern. This demonstrates MMR elicited by violation of the pattern of the triplet sequence and the ability to extract sound sequence information in the songbird auditory forebrain. Our study sheds light on the electrophysiological properties of auditory sensory memory processing, expanding the scope of characterization of MMN-like responses beyond simple deviance detection, and provides a comparative perspective on syntax processing in human.

Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing

The human brain has the astonishing capacity of integrating streams of sensory information from the environment and forming predictions about future events in an automatic way. Despite being initially developed for visual processing, the bulk of predictive coding research has subsequently focused on auditory processing, with the famous mismatch negativity signal as possibly the most studied signature of a surprise or prediction error (PE) signal. Auditory PEs are present during various consciousness states. Intriguingly, their presence and characteristics have been linked with residual levels of consciousness and return of awareness. In this review we first give an overview of the neural substrates of predictive processes in the auditory modality and their relation to consciousness. Then, we focus on different states of consciousness - wakefulness, sleep, anesthesia, coma, meditation, and hypnosis - and on what mysteries predictive processing has been able to disclose about brain functioning in such states. We review studies investigating how the neural signatures of auditory predictions are modulated by states of reduced or lacking consciousness. As a future outlook, we propose the combination of electrophysiological and computational techniques that will allow investigation of which facets of sensory predictive processes are maintained when consciousness fades away.

Mismatch-negativity (MMN) in animal models: Homology of human MMN?

Mismatch negativity (MMN) has long been considered to be one of the deviance-detecting neural characteristics. Animal models exhibit similar neural activities, called MMN-like responses; however, there has been considerable debate on whether MMN-like responses are homologous to MMN in humans. Herein, we reviewed several studies that compared the electrophysiological, pharmacological, and functional properties of MMN-like responses and adaptation-exhibiting middle-latency responses (MLRs) in animals with those in humans. Accumulating evidence suggests that there are clear differences between MMN-like responses and MLRs, in particular that MMN-like responses can be distinguished from mere effects of adaptation, i.e., stimulus-specific adaptation. Finally, we discuss a new direction for research on MMN-like responses by introducing our recent work, which demonstrated that MMN-like responses represent empirical salience of deviant stimuli, suggesting a new functional role of MMN beyond simple deviance detection.

Cortical mapping of mismatch responses to independent acoustic features

Predictive coding is an influential theory of neural processing underlying perceptual inference. However, it is unknown to what extent prediction violations of different sensory features are mediated in different regions in auditory cortex, with different dynamics, and by different mechanisms. This study investigates the neural responses to synthesized acoustic syllables, which could be expected or unexpected, along several features. By using electrocorticography (ECoG) in rat auditory cortex (subjects: adult female Wistar rats with normal hearing), we aimed at mapping regional differences in mismatch responses to different stimulus features. Continuous streams of morphed syllables formed roving oddball sequences in which each stimulus was repeated several times (thereby forming a standard) and subsequently replaced with a deviant stimulus which differed from the standard along one of several acoustic features: duration, pitch, interaural level differences (ILD), or consonant identity. Each of these features could assume one of several different levels, and the resulting change from standard to deviant could be larger or smaller. The deviant stimuli were then repeated to form new standards. We analyzed responses to the first repetition of a new stimulus (deviant) and its last repetition in a stimulus train (standard). For the ECoG recording, we implanted urethane-anaesthetized rats with 8 × 8 surface electrode arrays covering a 3 × 3 mm cortical patch encompassing primary and higher-order auditory cortex. We identified the response topographies and latencies of population activity evoked by acoustic stimuli in the rat auditory regions, and mapped their sensitivity to expectation violations along different acoustic features. For all features, the responses to deviant stimuli increased in amplitude relative to responses to standard stimuli. Deviance magnitude did not further modulate these mismatch responses. Mismatch responses to different feature violations showed a heterogeneous distribution across cortical areas, with no evidence for systematic topographic gradients for any of the tested features. However, within rats, the spatial distribution of mismatch responses varied more between features than the spatial distribution of tone-evoked responses. This result supports the notion that prediction error signaling along different stimulus features is subserved by different cortical populations, albeit with substantial heterogeneity across individuals.

Enhanced deviant responses in patterned relative to random sound sequences

The brain draws on knowledge of statistical structure in the environment to facilitate detection of new events. Understanding the nature of this representation is a key challenge in sensory neuroscience. Specifically, it is unknown whether real-time perception of rapidly-unfolding sensory signals is driven by a coarse or detailed representation of the proximal stimulus history. We recorded electroencephalography brain responses to frequency outliers in regularly-patterned (REG) versus random (RAND) tone-pip sequences which were generated anew on each trial. REG and RAND sequences were matched in frequency content and span, only differing in the specific order of the tone-pips. Stimuli were very rapid, limiting conscious reasoning in favour of automatic processing of regularity. Listeners were naïve and performed an incidental visual task. Outliers within REG evoked a larger response than matched outliers in RAND. These effects arose rapidly (within 80 msec) and were underpinned by distinct sources from those classically associated with frequency-based deviance detection. These findings are consistent with the notion that the brain continually maintains a detailed representation of ongoing sensory input and that this representation shapes the processing of incoming information. Predominantly auditory-cortical sources code for frequency deviance whilst frontal sources are associated with tracking more complex sequence structure.

High-sensitivity multi-channel probe beam detector towards MEG measurements of small animals with an optically pumped K-Rb hybrid magnetometer

Multi-channel measurements with fine spatial resolution will make magnetoencephalograms (MEGs) possible with small animals using optically pumped magnetometers (OPMs). Therefore, we fabricated a 20-channel probe-beam detector that uses a K-Rb hybrid OPM to increase the spatial resolution. First, we investigated the sensitivity of the detector using the multi-channel measurements and demonstrated that the detector had a fine sensitivity (10-20 fT/Hz^1/2 at 10 Hz). Subsequently, we measured magnetic field distribution generated from a loop coil and compared those measurements with analytically calculated distributions. The measurements were in good agreement with the theoretical predictions. The experimental results indicate that our newly developed multi-channel OPM detector has sufficient performance specifications for MEG measurements.

Development of a bio-magnetic measurement system and sensor configuration analysis for rats

Magnetoencephalography (MEG) based on superconducting quantum interference devices enables the measurement of very weak magnetic fields (10-1000 fT) generated from the human or animal brain. In this article, we introduce a small MEG system that we developed specifically for use with rats. Our system has the following characteristics: (1) variable distance between the pick-up coil and outer Dewar bottom (∼5 mm), (2) small pick-up coil (4 mm) for high spatial resolution, (3) good field sensitivity (45∼ 80fT/cm/Hz), (4) the sensor interval satisfies the Nyquist spatial sampling theorem, and (5) small source localization error for the region to be investigated. To reduce source localization error, it is necessary to establish an optimal sensor layout. To this end, we simulated confidence volumes at each point on a grid on the surface of a virtual rat head. In this simulation, we used locally fitted spheres as model rat heads. This enabled us to consider more realistic volume currents. We constrained the model such that the dipoles could have only four possible orientations: the x- and y-axes from the original coordinates, and two tangentially layered dipoles (local x- and y-axes) in the locally fitted spheres. We considered the confidence volumes according to the sensor layout and dipole orientation and positions. We then conducted a preliminary test with a 4-channel MEG system prior to manufacturing the multi-channel system. Using the 4-channel MEG system, we measured rat magnetocardiograms. We obtained well defined P-, QRS-, and T-waves in rats with a maximum value of 15 pT/cm. Finally, we measured auditory evoked fields and steady state auditory evoked fields with maximum values 400 fT/cm and 250 fT/cm, respectively.