Representation of acoustic deviations by neurons and local fieldpotentials in the auditory cortex of the awake rat

Veränderungen in der akustischen Umwelt sind häufig mit Ereignissen verbunden. Diese wiederum können für ein Tier eine besondere Verhaltensrelevanz haben, im Gegensatz zu einem gleichbleibenden akustischen Hintergrund, der mit keinem positiven oder negativen Ereignis verbunden ist. Es ist also naheliegend zu spekulieren, dass Veränderungen oder neue akustische Reize im zentralen Nervensystem anders repräsentiert werden als der kontinuierliche Hintergrund und dass diese Repräsentation sowohl von der Häufigkeit der Stimuli als auch vom Unterschied zum akustischen Hintergrund abhängt. In Elektroenzaphalografie-Messungen (EEG) am Menschen wurde eine besondere Aktivitätsänderung bei auditorischen Abweichungen erstmals 1978 nachgewiesen. Dabei wurde ein akustischer Reiz über einen längeren Zeitraum regelmäßig wiederholt (Standard) und in einigen, seltenen Fällen durch einen anderen Reiz (Deviant) ersetzt. Dieser Deviant löste eine zusätzliche negative Komponente im EEG aus (Mismatch negativity), die bei den Standard-Stimuli nicht vorhanden war. Eine Voraussetzung, um MMN auszulösen, ist die Präsentation von einigen Standard-Stimuli, sodass eine neuronale Repräsentation des Stimulus aufgebaut werden kann, gegen die jeder weitere Reiz abgeglichen wird. Die zelluläre Basis von MMN und des zugrunde liegenden Mechanismus zur Detektion von auditorischen Veränderungen ist nur wenig erforscht. Als möglicher zellulärer Detektionsmechanismus akustischer Veränderungen wurde die Stimulus-spezifische Adaptation (SSA) vorgeschlagen, die zugleich der Ursprung von MMN im primären auditorischen Kortex sein könnte. SSA beschreibt die Eigenschaft von Neuronen der Hörbahn, auf die Wiederholung von identischen Reizen mit abnehmender Aktivität zu antworten und zugleich die Fähigkeit beizubehalten, andere Stimuli weiterhin mit hoher Aktivität zu repräsentieren. Die veränderte neuronale Repräsentation von Tönen mit niedriger Auftrittswahrscheinlichkeit, im Vergleich zu Tönen mit hoher Auftrittswahrscheinlichkeit, wurde bereits sehr eindrücklich im auditorischen Kortex der anästhesierten Katzen demonstriert. Die vorliegende Arbeit hat es sich zum Ziel gesetzt, bei der Repräsentation von auditorischen Abweichungen die Lücke zwischen der Ebene aufsummierter Potenziale (EEG beim Menschen) und der Ebene einzelner kortikaler Neurone zu schließen. Gleichzeitig sollte dabei erstmalig SSA im auditorischen Kortex des wachen Tieres nachgewiesen und so eine pharmakologische Interaktion der normalerweise eingesetzten Anästhetika mit SSA ausgeschlossen werden. Der experimentelle Ansatz basierte auf elektrophysiologischen Messungen mit chronisch implantierten Mikroelektroden im wachen Tier. Die Elektroden waren im auditorischen Kortex positioniert und ermöglichten eine gleichzeitige Messung der lokalen aufsummierten Potenziale (lokale Feldpotenziale, LFP) und der Aktionspotenziale einzelner Neurone als extrazelluläre Potenzialveränderungen. Das Stimulationsparadigma bestand aus Folgen zweier Reintöne, die mit unterschiedlicher Auftrittwahrscheinlichkeit präsentiert wurden. Der Ton mit hoher Auftrittwahrscheinlichkeit bildete den akustischen Hintergrund, der Ton mit niedriger Auftrittswahrscheinlichkeit (Deviant) die akustische Abweichung. In dieser Arbeit konnte erstmalig nachgewiesen werden, dass Neurone im auditorischen Kortex der wachen Ratte akustische Abweichungen mit einer höheren Aktivität repräsentieren als den auditorischen Hintergrund (bis zu 19,5% Aktivitätsunterschied). Stimulusspezifische Adaptation ist somit auch im wachen Tier Teil der neuronalen Codierung der akustischen Umwelt. Mithilfe der Signalentdeckungstheorie konnte des Weiteren gezeigt werden, dass die unterschiedliche neuronale Repräsentation von häufigen und seltenen Stimuli auch zu einer erhöhten neuronalen Unterscheidbarkeit zwischen beiden Stimuli führte. Auf der Ebene der ereigniskorrelierten LFPs konnte SSA in zwei Komponenten nachgewiesen werden: der ersten, negativen Auslenkung und der folgenden, positiven Auslenkung. Besonders in der ersten, negativen Komponente war SSA systematisch nachzuweisen und sie war zusätzlich starkmit der Aktivität der einzelnen Neuronen korreliert, während die positive Komponente der LFPs keine Korrelation mit den Messungen der einzelnen Nervenzellen zeigte. Der Grad der SSA hing von der Auftrittwahrscheinlichkeit und dem Frequenzabstand der beiden Töne ab. Keine der Messungen hatte die besondere Charakteristik von MMN. Zusammenfassend lässt sich die Aussage treffen, dass SSA auch im wachen Tier nachgewiesen wurde, sowohl auf der Ebene einzelner Neurone als auch in der aufsummierten Aktivität, wenn auch in einer schwächeren Ausprägung als in den bisher veröffentlichten Ergebnissen in anästhesierten Tieren. Ein direkter Beitrag der kortikalen Neurone zu MMN konnte nicht gezeigt werden, es gab aber einen starken Zusammenhang zwischen den einzelnen Neuronen und den LFPs.The representation of behaviorally relevant stimuli in a noisy and complex environment that consists of multiple signals from different sources is one of the major challenges for the auditory system. The statistics of stimuli provide critical cues for structuring such an environment for optimizing the neuronal coding of it and for selecting vital information from it. In this respect, infrequent deviations in a repetitive auditory background are often events of behavioral importance. Such rarely occurring events are represented in the nervous system by a preattentive and automatic auditory process, which is only partially under attentional control. A correlate in human electroencephalographic recordings for neuronal mechanisms of change detection is the so-called mismatch negativity (MMN) that may serve as a trigger for reallocating attention toward the deviants. Its characteristic feature is a negative wave occurring 200 milliseconds after stimulus onset in response to an infrequent deviant stimulus, which is embedded in a sequence of repetitive standard tones. To evoke MMN, the deviant and standard stimuli can be selected from a variety of stimuli (i.e., pure tones, vowels) and differ in various aspects such as frequency, duration, and level or even being omitted. Although there is a large data basis on MMN available, only few publications approach its cellular basis in terms of cortical neuronal response properties. Recently, stimulus-specific adaptation has been proposed as a candidate neuronal mechanism underlying the generation of MMN. In experiments on anesthetized animals, stimulus-specific adaptation was identified at different stages of the auditory pathway, namely cat auditory cortex, mouse auditory thalamus, and rat inferior colliculus. In addition, there were attempts to demonstrate MMN with means of event-related potentials in rodents, but the resulting patterns are weak or ambiguous. To address the neuronal basis of MMN, the present study focuses on the awake rat primary auditory cortex. Neurons and evoked local field potentials were recorded in parallel and could provide a bridge between cellular properties and electroencephalographic recordings. The following questions are addressed. Whether and how is SSA present in neurons of the primary auditory cortex in the awake rat? Do the evoked local field potentials adapt in a similar manner as neurons and do they exhibit an MMN-like pattern? Finally, can we establish a contribution of single neuron adaptation to adaptation of evoked local field potentials? A total of 76 single units and small multiunit clusters were recorded (n = 27 and n = 49, respectively) from primary auditory cortex of the awake rat. For a subset of units, evoked local field potentials were recorded in parallel to the extracellular spike recordings from the same electrode. The frequency response area was characterized for each unit, and, depending on its characteristic frequency, two frequencies, symmetrically centered around the characteristic frequency, were chosen for the two tones in the adaptation paradigm. The two pure tones were presented in an oddball sequence of 800 tones, with one tone being the highly probable standard and the other one the rarely occurring deviant. In a second consecutive sequence, the frequencies of standard and deviant were swapped. To identify different factors controlling stimulus-specific adaptation, deviant probability and frequency separation were varied systematically, giving rise to four different stimulus conditions and one control condition. The main findings were as follows. (1) Isolated units in primary auditory cortex of the awake rat showed stimulus-specific adaptation primarily during the onset response but could not be observed during later inhibition or rebound of activity. Stimulus-specific adaptation of isolated units depended on at least two factors: frequency separation between standard tone and deviant and the deviant probability. However, stimulus-specific adaptation was independent of the specific frequency, indicating that stimulus-specific adaptation might be a more general property of cortical neurons. (2) Certain components of evoked local field potentials adapted in a stimulus-specific manner (i.e., the fast negative deflection and partially the slower positive deflection). There was, however, no MMN response present. (3) Spike adaptation correlated well with the adaptation of the negative deflection but not the positive deflection. Adaptation of the negative deflection resembled spike adaptation with respect to magnitude and dependency on frequency separation and deviant probability. (4) Stimulus specific adaptation improves on the level of single neurons the discriminability of deviant stimuli from the acoustic background. This was shown by a detailed analysis of neuronal responses with means of signal detection theory

Machine learning reveals interhemispheric somatosensory coherence as indicator of anesthetic depth

The goal of this study was to identify features in mouse electrocorticogram recordings that indicate the depth of anesthesia as approximated by the administered anesthetic dosage. Anesthetic depth in laboratory animals must be precisely monitored and controlled. However, for the most common lab species (mice) few indicators useful for monitoring anesthetic depth have been established. We used electrocorticogram recordings in mice, coupled with peripheral stimulation, in order to identify features of brain activity modulated by isoflurane anesthesia and explored their usefulness in monitoring anesthetic depth through machine learning techniques. Using a gradient boosting regressor framework we identified interhemispheric somatosensory coherence as the most informative and reliable electrocorticogram feature for determining anesthetic depth, yielding good generalization and performance over many subjects. Knowing that interhemispheric somatosensory coherence indicates the effectively administered isoflurane concentration is an important step for establishing better anesthetic monitoring protocols and closed-loop systems for animal surgeries

Modelling novelty detection in the thalamocortical loop

In complex natural environments, sensory systems are constantly exposed to a large stream of inputs. Novel or rare stimuli, which are often associated with behaviorally important events, are typically processed differently than the steady sensory background, which has less relevance. Neural signatures of such differential processing, commonly referred to as novelty detection, have been identified on the level of EEG recordings as mismatch negativity (MMN) and on the level of single neurons as stimulus-specific adaptation (SSA). Here, we propose a multi-scale recurrent network with synaptic depression to explain how novelty detection can arise in the whisker-related part of the somatosensory thalamocortical loop. The “minimalistic” architecture and dynamics of the model presume that neurons in cortical layer 6 adapt, via synaptic depression, specifically to a frequently presented stimulus, resulting in reduced population activity in the corresponding cortical column when compared with the population activity evoked by a rare stimulus. This difference in population activity is then projected from the cortex to the thalamus and amplified through the interaction between neurons of the primary and reticular nuclei of the thalamus, resulting in rhythmic oscillations. These differentially activated thalamic oscillations are forwarded to cortical layer 4 as a late secondary response that is specific to rare stimuli that violate a particular stimulus pattern. Model results show a strong analogy between this late single neuron activity and EEG-based mismatch negativity in terms of their common sensitivity to presentation context and timescales of response latency, as observed experimentally. Our results indicate that adaptation in L6 can establish the thalamocortical dynamics that produce signatures of SSA and MMN and suggest a mechanistic model of novelty detection that could generalize to other sensory modalities

Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments

The quantification of behaviors of interest from video data is commonly used to study brain function, the effects of pharmacological interventions, and genetic alterations. Existing approaches lack the capability to analyze the behavior of groups of animals in complex environments. We present a novel deep learning architecture for classifying individual and social animal behavior, even in complex environments directly from raw video frames, while requiring no intervention after initial human supervision. Our behavioral classifier is embedded in a pipeline (SIPEC) that performs segmentation, identification, pose-estimation, and classification of complex behavior, outperforming the state of the art. SIPEC successfully recognizes multiple behaviors of freely moving individual mice as well as socially interacting non-human primates in 3D, using data only from simple mono-vision cameras in home-cage setups

Animal Models of Subjective Tinnitus

Tinnitus is one of themajor audiological diseases, affecting a significant portion of the ageing society. Despite its huge personal and presumed economic impact there are only limited therapeutic options available.Thereason for this deficiency lies in the very nature of the disease as it is deeply connected to elementary plasticity of auditory processing in the central nervous system. Understanding these mechanisms is essential for developing a therapy that reverses the plastic changes underlying the pathogenesis of tinnitus. This requires experiments that address individual neurons and small networks, something usually not feasible in human patients. However, in animals such invasive experiments on the level of single neurons with high spatial and temporal resolution are possible. Therefore, animal models are a very critical element in the combined efforts for engineering new therapies.This review provides an overview over the most important features of animal models of tinnitus: which laboratory species are suitable, how to induce tinnitus, and how to characterize the perceived tinnitus by behavioral means. In particular, these aspects of tinnitus animal models are discussed in the light of transferability to the human patients

Deviant processing in the primary somatosensory cortex

Stimulus-specific adaptation (SSA) to repetitive stimulation has been proposed to separate behaviorally relevant features from a stream of continuous sensory information. However, the exact mechanisms giving rise to SSA and cortical deviance detection are not well understood. We therefore used an oddball paradigm and multicontact electrodes to characterize single-neuron and local field potential responses to various deviant stimuli across the rat somatosensory cortex. Changing different single-whisker stimulus features evoked robust SSA in individual cortical neurons over a wide range of stimulus repetition rates (0.25–80 Hz). Notably, SSA was weakest in the granular input layer and significantly stronger in the supra- and infragranular layers, suggesting that a major part of SSA is generated within cortex. Moreover, we found a small subset of neurons in the granular layer with a deviant-specific late response, occurring roughly 200 ms after stimulus offset. This late deviant response exhibited true-deviance detection properties that were not explained by depression of sensory inputs. Our results show that deviant responses are actively amplified within cortex and contain an additional late component that is sensitive for context-specific sensory deviations. This strongly implicates deviance detection as a feature of intracortical stimulus processing beyond simple sensory input depression

Deviant Processing in the Primary Somatosensory Cortex

Stimulus-specific adaptation (SSA) to repetitive stimulation has been proposed to separate behaviorally relevant features from a stream of continuous sensory information. However, the exact mechanisms giving rise to SSA and cortical deviance detection are not well understood. We therefore used an oddball paradigm and multicontact electrodes to characterize single-neuron and local field potential responses to various deviant stimuli across the rat somatosensory cortex. Changing different single-whisker stimulus features evoked robust SSA in individual cortical neurons over a wide range of stimulus repetition rates (0.25-80 Hz). Notably, SSA was weakest in the granular input layer and significantly stronger in the supra- and infragranular layers, suggesting that a major part of SSA is generated within cortex. Moreover, we found a small subset of neurons in the granular layer with a deviant-specific late response, occurring roughly 200 ms after stimulus offset. This late deviant response exhibited true-deviance detection properties that were not explained by depression of sensory inputs. Our results show that deviant responses are actively amplified within cortex and contain an additional late component that is sensitive for context-specific sensory deviations. This strongly implicates deviance detection as a feature of intracortical stimulus processing beyond simple sensory input depression

Electrocorticography based monitoring of anaesthetic depth in mice

To improve animal welfare and data quality and reproducibility during research conducted under anaesthesia, anaesthetic depth in laboratory animals must be precisely monitored and controlled. While a variety of methods have been developed to estimate the depth of anaesthesia in humans, such tools for monitoring anaesthetic depth in laboratory animals remain limited. Here we propose an epidural electrocorticogram-based monitoring system that accurately tracks the depth of anesthesia in mice receiving inhalable isoflurane anaesthesia. Several features of the electrocorticogram signals exhibit robust modulation by the concentration of the administered anesthetic, notably, corticocortical coherence serves as an excellent indicator of anaesthetic depth. We developed a gradient boosting regressor framework that utilizes the extracted features to accurately estimate the depth of anaesthesia. Our method for feature extraction and estimation is conducted with a latency of only ten seconds, establishing a system for the real-time tracking of anaesthetic depth in mice

Stimulus-specific adaptation in field potentials and neuronal responses to frequency-modulated tones in the primary auditory cortex

In order to structure the sensory environment our brain needs to detect changes in the surrounding that might indicate events of presumed behavioral relevance. A characteristic brain response presumably related to the detection of such novel stimuli is termed mismatch negativity (MMN) observable in human scalp recordings. A candidate mechanism underlying MMN at the neuronal level is stimulus-specific adaptation (SSA) which has several characteristics in common. SSA is the specific decrease in the response to a frequent stimulus, which does not generalize to an interleaved rare stimulus in a sequence of events. SSA was so far mainly described for changes in the response to simple pure tone stimuli differing in tone frequency. In this study we provide data from the awake rat auditory cortex on adaptation in the responses to frequency- modulated tones (FM) with the deviating feature being the direction of FM modulation. Adaptation of cortical neurons to the direction of FM modulation was stronger for slow modulation than for faster modulation. In contrast to pure tone SSA which showed no stimulus preference, FM adaptation in neuronal data differed sometimes between upward and downward FM. This, however, was not the case in the local field potential data recorded simultaneously. Our findings support the role of the auditory cortex as the source for change related activity induced by FM stimuli by showing that dynamic stimulus features such as FM modulation can evoke SSA in the rat in a way very similar to FM-induced MMN in the human auditory cortex