Facilitative effect of repetitive presentation of one stimulus on cortical responses to other stimuli in macaque monkeys--a possible neural mechanism for mismatch negativity

Short-term neuronal and synaptic plasticity act in synergy for deviance detection in spiking networks

Sensory areas of cortex respond more strongly to infrequent stimuli when these violate previously established regularities, a phenomenon known as deviance detection (DD). Previous modeling work has mainly attempted to explain DD on the basis of synaptic plasticity. However, a large fraction of cortical neurons also exhibit firing rate adaptation, an underexplored potential mechanism. Here, we investigate DD in a spiking neuronal network model with two types of short-term plasticity, fast synaptic short-term depression (STD) and slower threshold adaptation (TA). We probe the model with an oddball stimulation paradigm and assess DD by evaluating the network responses. We find that TA is sufficient to elicit DD. It achieves this by habituating neurons near the stimulation site that respond earliest to the frequently presented standard stimulus (local fatigue), which diminishes the response and promotes the recovery (global fatigue) of the wider network. Further, we find a synergy effect between STD and TA, where they interact with each other to achieve greater DD than the sum of their individual effects. We show that this synergy is caused by the local fatigue added by STD, which inhibits the global response to the frequently presented stimulus, allowing greater recovery of TA-mediated global fatigue and making the network more responsive to the deviant stimulus. Finally, we show that the magnitude of DD strongly depends on the timescale of stimulation. We conclude that highly predictable information can be encoded in strong local fatigue, which allows greater global recovery and subsequent heightened sensitivity for DD.

Prediction-Related Frontal-Temporal Network for Omission Mismatch Activity in the Macaque Monkey

Sensory prediction is considered an important element of mismatch negativity (MMN) whose reduction is well known in patients with schizophrenia. Omission MMN is a variant of the MMN which is elicited by the absence of a tone previously sequentially presented. Omission MMN can eliminate the effects of sound differences in typical oddball paradigms and affords the opportunity to identify prediction-related signals in the brain. Auditory predictions are thought to reflect bottom-up and top-down processing within hierarchically organized auditory areas. However, the communications between the various subregions of the auditory cortex and the prefrontal cortex that generate and communicate sensory prediction-related signals remain poorly understood. To explore how the frontal and temporal cortices communicate for the generation and propagation of such signals, we investigated the response in the omission paradigm using electrocorticogram (ECoG) electrodes implanted in the temporal, lateral prefrontal, and orbitofrontal cortices of macaque monkeys. We recorded ECoG data from three monkeys during the omission paradigm and examined the functional connectivity between the temporal and frontal cortices by calculating phase-locking values (PLVs). This revealed that theta- (4-8 Hz), alpha- (8-12 Hz), and low-beta- (12-25 Hz) band synchronization increased at tone onset between the higher auditory cortex and the frontal pole where an early omission response was observed in the event-related potential (ERP). These synchronizations were absent when the tone was omitted. Conversely, low-beta-band (12-25 Hz) oscillation then became stronger for tone omission than for tone presentation approximately 200 ms after tone onset. The results suggest that auditory input is propagated to the frontal pole via the higher auditory cortex and that a reciprocal network may be involved in the generation of auditory prediction and prediction error. As impairments of prediction may underlie MMN reduction in patients with schizophrenia, an aberrant hierarchical temporal-frontal network might be related to this pathological condition.

Preattentive processing of visually guided self-motion in humans and monkeys

The visually-based control of self-motion is a challenging task, requiring - if needed - immediate adjustments to keep on track. Accordingly, it would appear advantageous if the processing of self-motion direction (heading) was predictive, thereby accelerating the encoding of unexpected changes, and un-impaired by attentional load. We tested this hypothesis by recording EEG in humans and macaque monkeys with similar experimental protocols. Subjects viewed a random dot pattern simulating self-motion across a ground plane in an oddball EEG paradigm. Standard and deviant trials differed only in their simulated heading direction (forward-left vs. forward-right). Event-related potentials (ERPs) were compared in order to test for the occurrence of a visual mismatch negativity (vMMN), a component that reflects preattentive and likely also predictive processing of sensory stimuli. Analysis of the ERPs revealed signatures of a prediction mismatch for deviant stimuli in both humans and monkeys. In humans, a MMN was observed starting 110 ms after self-motion onset. In monkeys, peak response amplitudes following deviant stimuli were enhanced compared to the standard already 100 ms after self-motion onset. We consider our results strong evidence for a preattentive processing of visual self-motion information in humans and monkeys, allowing for ultrafast adjustments of their heading direction.

Prediction error signaling explains neuronal mismatch responses in the medial prefrontal cortex

The mismatch negativity (MMN) is a key biomarker of automatic deviance detection thought to emerge from 2 cortical sources. First, the auditory cortex (AC) encodes spectral regularities and reports frequency-specific deviances. Then, more abstract representations in the prefrontal cortex (PFC) allow to detect contextual changes of potential behavioral relevance. However, the precise location and time asynchronies between neuronal correlates underlying this frontotemporal network remain unclear and elusive. Our study presented auditory oddball paradigms along with "no-repetition" controls to record mismatch responses in neuronal spiking activity and local field potentials at the rat medial PFC. Whereas mismatch responses in the auditory system are mainly induced by stimulus-dependent effects, we found that auditory responsiveness in the PFC was driven by unpredictability, yielding context-dependent, comparatively delayed, more robust and longer-lasting mismatch responses mostly comprised of prediction error signaling activity. This characteristically different composition discarded that mismatch responses in the PFC could be simply inherited or amplified downstream from the auditory system. Conversely, it is more plausible for the PFC to exert top-down influences on the AC, since the PFC exhibited flexible and potent predictive processing, capable of suppressing redundant input more efficiently than the AC. Remarkably, the time course of the mismatch responses we observed in the spiking activity and local field potentials of the AC and the PFC combined coincided with the time course of the large-scale MMN-like signals reported in the rat brain, thereby linking the microscopic, mesoscopic, and macroscopic levels of automatic 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.

A Novel Modular Headmount Design for non-invasive Scalp EEG Recordings in Awake Animal Models

We have designed and developed a novel, noninvasive modular headmount to be used for awake animal scalp electroencephalography (EEG). The design is based on a developing rat that will accommodate rapid head growth. Desired characteristics include non-invasiveness, adjustable quantity and positioning, light weight, and tolerability by the animal. Axial Dependent Modular Electrode Mount (ADMEM), as designed here, addresses the aforementioned constraints by using light-weight and adjustable materials. The initial prototype of ADMEM has been tested in vivo with rat pups, using the open field test to assess for stress and anxiety at two post-installation time-points: one day after ADMEM installation (acute time-point) and four days after ADMEM installation (sub-acute time-point). There was no significant difference in normal developmental weight gain between Control and ADMEM rat groups. Although no significant difference was found in the level of anxiety between groups at the acute time-point, the ADMEM group spent significantly less time in the center of the open field test, suggesting higher anxiety. The test also showed no difference in the measured traveled distances between Control and ADMEM groups on either time-points.

Stimulus-Specific Adaptation Decreases the Coupling of Spikes to LFP Phase

Stimulus repetition suppresses the neural activity in different sensory areas of the brain. This mechanism of so-called stimulus-specific adaptation (SSA) has been observed in both spiking activity and local field potential (LFP) responses. However, much remains to be known about the effect of SSA on the spike–LFP relation. In this study, we approached this issue by investigating the spike-phase coupling (SPC) in control and adapting paradigms. For the control paradigm, pure tones were presented in a random unbiased sequence. In the adapting paradigm, the same stimuli were presented in a random pattern but it was biased to an adapter stimulus. In fact, the adapter occupied 80% of the adapting sequence. During the tasks, LFP and multi-unit activity were recorded simultaneously from the primary auditory cortex of 15 anesthetized rats. To clarify the effect of adaptation on the relation between spike and LFP responses, the SPC of the adapter stimulus in these two paradigms was evaluated. Here, we employed phase locking value method for calculating the SPC. Our data show a strong coupling of spikes to LFP phase most prominently in beta band. This coupling was observed to decrease in the adapting condition compared to the control one. Importantly, we found that adaptation reduces spikes dominantly from the preferred phase of LFP in which spikes are more likely to be present there. As a result, the preferred phase of LFP may play a key role in coordinating neuronal spiking activity in neural adaptation mechanism. This finding is important for interpretation of the underlying neural mechanism of adaptation and also can be used in the context of the network and related connectivity models.

Visual Mismatch and Predictive Coding: A Computational Single-Trial ERP Study

Predictive coding (PC) posits that the brain uses a generative model to infer the environmental causes of its sensory data and uses precision-weighted prediction errors (pwPEs) to continuously update this model. While supported by much circumstantial evidence, experimental tests grounded in formal trial-by-trial predictions are rare. One partial exception is event-related potential (ERP) studies of the auditory mismatch negativity (MMN), where computational models have found signatures of pwPEs and related model-updating processes. Here, we tested this hypothesis in the visual domain, examining possible links between visual mismatch responses and pwPEs. We used a novel visual "roving standard" paradigm to elicit mismatch responses in humans (of both sexes) by unexpected changes in either color or emotional expression of faces. Using a hierarchical Bayesian model, we simulated pwPE trajectories of a Bayes-optimal observer and used these to conduct a comprehensive trial-by-trial analysis across the time × sensor space. We found significant modulation of brain activity by both color and emotion pwPEs. The scalp distribution and timing of these single-trial pwPE responses were in agreement with visual mismatch responses obtained by traditional averaging and subtraction (deviant-minus-standard) approaches. Finally, we compared the Bayesian model to a more classical change model of MMN. Model comparison revealed that trial-wise pwPEs explained the observed mismatch responses better than categorical change detection. Our results suggest that visual mismatch responses reflect trial-wise pwPEs, as postulated by PC. These findings go beyond classical ERP analyses of visual mismatch and illustrate the utility of computational analyses for studying automatic perceptual processes.SIGNIFICANCE STATEMENT Human perception is thought to rely on a predictive model of the environment that is updated via precision-weighted prediction errors (pwPEs) when events violate expectations. This "predictive coding" view is supported by studies of the auditory mismatch negativity brain potential. However, it is less well known whether visual perception of mismatch relies on similar processes. Here we combined computational modeling and electroencephalography to test whether visual mismatch responses reflected trial-by-trial pwPEs. Applying a Bayesian model to series of face stimuli that violated expectations about color or emotional expression, we found significant modulation of brain activity by both color and emotion pwPEs. A categorical change detection model performed less convincingly. Our findings support the predictive coding interpretation of visual mismatch responses.

Late deviance detection in rats is reduced, while early deviance detection is augmented by the NMDA receptor antagonist MK-801

One of the most robust electrophysiological features of schizophrenia is reduced mismatch negativity, a component of the event related potential (ERP) induced by rare and unexpected stimuli in an otherwise regular pattern. Emerging evidence suggests that mismatch negativity (MMN) is not the only ERP index of deviance detection in the mammalian brain and that sensitivity to deviant sounds in a regular background can be observed at earlier latencies in both the human and rodent brain. Pharmacological studies in humans and rodents have previously found that MMN reductions similar to those seen in schizophrenia can be elicited by N-methyl-d-aspartate (NMDA) receptor antagonism, an observation in agreement with the hypothesised role of NMDA receptor hypofunction in schizophrenia pathogenesis. However, it is not known how NMDA receptor antagonism affects early deviance detection responses. Here, we show that NMDA antagonism impacts both early and late deviance detection responses. By recording EEG in awake, freely-moving rats in a drug-free condition and after varying doses of NMDA receptor antagonist MK-801, we found the hypothesised reduction of deviance detection for a late, negative potential (N55). However, the amplitude of an early component, P13, as well as deviance detection evident in the same component, were increased by NMDA receptor antagonism. These findings indicate that late deviance detection in rats is similar to human MMN, but the surprising effect of MK-801 in increasing ERP amplitudes as well as deviance detection at earlier latencies suggests that future studies in humans should examine ERPs over early latencies in schizophrenia and after NMDA antagonism.

Mismatch negativity in preclinical models of schizophrenia

Schizophrenia is a mental disorder associated with profoundly disruptive positive and negative symptomology that result in difficulties building close relationships with others, performing daily tasks and sustaining independent living, resulting in poor social, vocational and occupational attainment (functional outcome). Mismatch Negativity (MMN) is a change in the sensory event-related potential that occurs in response to deviation from an established pattern of stimulation. Patients with schizophrenia show a reduction in MMN that is positively associated with impaired cognition and poor functional outcome. This has led to interest in MMN as a potential clinical and pre-clinical biomarker of fundamental neural processes responsible for reduced functional outcome. To date, relatively few studies have sought to assess MMN in non-human primates or rodents. The validity of these studies will be reviewed using criteria used to identify true deviance detection based MMN responses in human subjects. Although MMN has been difficult to establish in pre-clinical models the weight of evidence suggests that non-human animals show true deviance based MMN.

Sensory Stream Adaptation in Chaotic Networks

Implicit expectations induced by predictable stimuli sequences affect neuronal response to upcoming stimuli at both single cell and neural population levels. Temporally regular sensory streams also phase entrain ongoing low frequency brain oscillations but how and why this happens is unknown. Here we investigate how random recurrent neural networks without plasticity respond to stimuli streams containing oddballs. We found the neuronal correlates of sensory stream adaptation emerge if networks generate chaotic oscillations which can be phase entrained by stimulus streams. The resultant activity patterns are close to critical and support history dependent response on long timescales. Because critical network entrainment is a slow process stimulus response adapts gradually over multiple repetitions. Repeated stimuli generate suppressed responses but oddball responses are large and distinct. Oscillatory mismatch responses persist in population activity for long periods after stimulus offset while individual cell mismatch responses are strongly phasic. These effects are weakened in temporally irregular sensory streams. Thus we show that network phase entrainment provides a biologically plausible mechanism for neural oddball detection. Our results do not depend on specific network characteristics, are consistent with experimental studies and may be relevant for multiple pathologies demonstrating altered mismatch processing such as schizophrenia and depression.