Frequency-Dependent Stimulus-Specific Adaptation and Regularity Sensitivity in the Rat Auditory Thalamus

Accurate Machine Learning-based Monitoring of Anesthesia Depth with EEG Recording

General anesthesia, pivotal for surgical procedures, requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments. Traditional assessment methods, relying on physiological indicators or behavioral responses, fall short of accurately capturing the nuanced states of unconsciousness. This study introduces a machine learning-based approach to decode anesthesia depth, leveraging EEG data across different anesthesia states induced by propofol and esketamine in rats. Our findings demonstrate the model's robust predictive accuracy, underscored by a novel intra-subject dataset partitioning and a 5-fold cross-validation method. The research diverges from conventional monitoring by utilizing anesthetic infusion rates as objective indicators of anesthesia states, highlighting distinct EEG patterns and enhancing prediction accuracy. Moreover, the model's ability to generalize across individuals suggests its potential for broad clinical application, distinguishing between anesthetic agents and their depths. Despite relying on rat EEG data, which poses questions about real-world applicability, our approach marks a significant advance in anesthesia monitoring.

Neural correlates of novelty detection in the primary auditory cortex of behaving monkeys

The neural mechanisms underlying novelty detection are not well understood, especially in relation to behavior. Here, we present single-unit responses from the primary auditory cortex (A1) from two monkeys trained to detect deviant tones amid repetitive ones. Results show that monkeys can detect deviant sounds, and there is a strong correlation between late neuronal responses (250-350 ms after deviant onset) and the monkeys' perceptual decisions. The magnitude and timing of both neuronal and behavioral responses are increased by larger frequency differences between the deviant and standard tones and by increasing the number of standard tones preceding the deviant. This suggests that A1 neurons encode novelty detection in behaving monkeys, influenced by stimulus relevance and expectations. This study provides evidence supporting aspects of predictive coding in the sensory cortex.

Cross-Modal Interaction and Integration Through Stimulus-Specific Adaptation in the Thalamic Reticular Nucleus of Rats

Stimulus-specific adaptation (SSA), defined as a decrease in responses to a common stimulus that only partially generalizes to other rare stimuli, is a widespread phenomenon in the brain that is believed to be related to novelty detection. Although cross-modal sensory processing is also a widespread phenomenon, the interaction between the two phenomena is not well understood. In this study, the thalamic reticular nucleus (TRN), which is regarded as a hub of the attentional system that contains multi-modal neurons, was investigated. The results showed that SSA existed in an interactive oddball stimulation, which mimics stimulation changes from one modality to another. In the bimodal integration, SSA to bimodal stimulation was stronger than to visual stimulation alone but similar to auditory stimulation alone, which indicated a limited integrative effect. Collectively, the present results provide evidence for independent cross-modal processing in bimodal TRN neurons.

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.

Adaptation in the Dorsal Belt and Core Regions of the Auditory Cortex in the Awake Rat

The rat auditory cortex is divided anatomically into several areas, but little is known about the functional differences in information processing among these areas. Three tonotopically organized core fields, namely, the primary (A1), anterior (AAF), and ventral (VAF) auditory fields, as well as one non-tonotopically organized belt field, the dorsal belt (DB), were identified based on their response properties. Compared to neurons in A1, AAF and VAF, units in the DB exhibited little or no response to pure tones but strong responses to white noise. The few DB neurons responded to pure tones with thresholds greater than 60 dB SPL, which was significantly higher than the thresholds of neurons in the core regions. In response to white noise, units in DB showed significantly longer latency and lower peak response, as well as longer response duration, than those in the core regions. Responses to repeated white noise were also examined. In contrast to neurons in A1, AAF and VAF, DB neurons could not follow repeated stimulation at a 300 ms inter-stimulus interval (ISI) and showed a significant steeper ISI tuning curve slope when the ISI was increased from 300 ms to 4.8 s. These results indicate that the DB processes auditory information on broader spectral and longer temporal scales than the core regions, reflecting a distinct role in the hierarchical cortical pathway.

Thalamic gating contributes to forward suppression in the auditory cortex

The neural mechanisms underlying forward suppression in the auditory cortex remain a puzzle. Little attention is paid to thalamic contribution despite the important fact that the thalamus gates upstreaming information to the auditory cortex. This study compared the time courses of forward suppression in the auditory thalamus, thalamocortical inputs and cortex using the two-tone stimulus paradigm. The preceding and succeeding tones were 20-ms long. Their frequency and amplitude were set at the characteristic frequency and 20 dB above the minimum threshold of given neurons, respectively. In the ventral division of the medial geniculate body of the thalamus, we found that the duration of complete forward suppression was about 75 ms and the duration of partial suppression was from 75 ms to about 300 ms after the onset of the preceding tone. We also found that during the partial suppression period, the responses to the succeeding tone were further suppressed in the primary auditory cortex. The forward suppression of thalamocortical field excitatory postsynaptic potentials was between those of thalamic and cortical neurons but much closer to that of thalamic ones. Our results indicate that early suppression in the cortex could result from complete suppression in the thalamus whereas later suppression may involve thalamocortical and intracortical circuitry. This suggests that the complete suppression that occurs in the thalamus provides the cortex with a "silence" window that could potentially benefit cortical processing and/or perception of the information carried by the preceding sound.

The Thalamocortical Circuit of Auditory Mismatch Negativity

BACKGROUND

Mismatch negativity (MMN) is an extensively validated biomarker of cognitive function across both normative and clinical populations and has previously been localized to supratemporal auditory cortex. MMN is thought to represent a comparison of the features of the present stimulus versus a mnemonic template formed by the prior stimuli.

METHODS

We used concurrent thalamic and primary auditory cortical (A1) laminar recordings in 7 macaques to evaluate the relative contributions of core (lemniscal) and matrix (nonlemniscal) thalamic afferents to MMN generation.

RESULTS

We demonstrated that deviance-related activity is observed mainly in matrix regions of auditory thalamus, MMN generators are most prominent in layer 1 of cortex as opposed to sensory responses that activate layer 4 first and sequentially all cortical layers, and MMN is elicited independent of the frequency tuning of A1 neuronal ensembles. Consistent with prior reports, MMN-related thalamocortical activity was strongly inhibited by ketamine.

CONCLUSIONS

Taken together, our results demonstrate distinct matrix versus core thalamocortical circuitry underlying the generation of a higher-order brain response (MMN) versus sensory responses.

Spectral tuning of adaptation supports coding of sensory context in auditory cortex

Perception of vocalizations and other behaviorally relevant sounds requires integrating acoustic information over hundreds of milliseconds. Sound-evoked activity in auditory cortex typically has much shorter latency, but the acoustic context, i.e., sound history, can modulate sound evoked activity over longer periods. Contextual effects are attributed to modulatory phenomena, such as stimulus-specific adaption and contrast gain control. However, an encoding model that links context to natural sound processing has yet to be established. We tested whether a model in which spectrally tuned inputs undergo adaptation mimicking short-term synaptic plasticity (STP) can account for contextual effects during natural sound processing. Single-unit activity was recorded from primary auditory cortex of awake ferrets during presentation of noise with natural temporal dynamics and fully natural sounds. Encoding properties were characterized by a standard linear-nonlinear spectro-temporal receptive field (LN) model and variants that incorporated STP-like adaptation. In the adapting models, STP was applied either globally across all input spectral channels or locally to subsets of channels. For most neurons, models incorporating local STP predicted neural activity as well or better than LN and global STP models. The strength of nonlinear adaptation varied across neurons. Within neurons, adaptation was generally stronger for spectral channels with excitatory than inhibitory gain. Neurons showing improved STP model performance also tended to undergo stimulus-specific adaptation, suggesting a common mechanism for these phenomena. When STP models were compared between passive and active behavior conditions, response gain often changed, but average STP parameters were stable. Thus, spectrally and temporally heterogeneous adaptation, subserved by a mechanism with STP-like dynamics, may support representation of the complex spectro-temporal patterns that comprise natural sounds across wide-ranging sensory contexts.

Top-down or bottom up: decreased stimulus salience increases responses to predictable stimuli of auditory thalamic neurons

KEY POINTS

Temporal imprecision leads to deficits in the comprehension of signals in cluttered acoustic environments, and the elderly are shown to use cognitive resources to disambiguate these signals. To mimic ageing in young rats, we delivered sound signals that are temporally degraded, which led to temporally imprecise neural codes. Instead of adaptation to repeated stimuli, with degraded signals, there was a relative increase in firing rates, similar to that seen in aged rats. We interpret this increase with repetition as a repair mechanism for strengthening the internal representations of degraded signals by the higher-order structures.

ABSTRACT

To better understand speech in challenging environments, older adults increasingly use top-down cognitive and contextual resources. The medial geniculate body (MGB) integrates ascending inputs with descending predictions to dynamically gate auditory representations based on salience and context. A previous MGB single-unit study found an increased preference for predictable sinusoidal amplitude modulated (SAM) stimuli in aged rats relative to young rats. The results suggested that the age-degraded/jittered up-stream acoustic code may engender an increased preference for predictable/repeating acoustic signals, possibly reflecting increased use of top-down resources. In the present study, we recorded from units in young-adult MGB, comparing responses to standard SAM with those evoked by less salient SAM (degraded) stimuli. We hypothesized that degrading the SAM stimulus would simulate the degraded ascending acoustic code seen in the elderly, increasing the preference for predictable stimuli. Single units were recorded from clusters of advanceable tetrodes implanted above the MGB of young-adult awake rats. Less salient SAM significantly increased the preference for predictable stimuli, especially at higher modulation frequencies. Rather than adaptation, higher modulation frequencies elicited increased numbers of spikes with each successive trial/repeat of the less salient SAM. These findings are consistent with previous findings obtained in aged rats suggesting that less salient acoustic signals engage the additional use of top-down resources, as reflected by an increased preference for repeating stimuli that enhance the representation of complex environmental/communication sounds.