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.

Deviance distraction and stimulus-specific adaptation in the somatosensory cortex reduce with experience

Automatic detection of a surprising change in the sensory input is a central element of exogenous attentional control. Stimulus-specific adaptation (SSA) is a potential neuronal mechanism detecting such changes and has been robustly described across sensory modalities and different instances of the ascending sensory pathways. However, little is known about the relationship of SSA to perception. To assess how deviating stimuli influence target signal detection, we employed a behavioral cross-modal paradigm in mice and combined it with extracellular recordings from the primary somatosensory whisker cortex. In this paradigm, male mice performed a visual detection task while task-irrelevant whisker stimuli were either presented as repetitive 'standard' or as rare deviant stimuli. We found a deviance distraction effect on the animals' performance: Faster reaction times but worsened target detection was observed in the presence of a deviant stimulus. Multi-unit activity and local field potentials exhibited enhanced neuronal responses to deviant when compared to standard whisker stimuli across all cortical layers, as a result of SSA. The deviant-triggered behavioral distraction correlated with these enhanced neuronal deviant responses only in the deeper cortical layers. However, the layer-specific effect of SSA on perception reduced with increasing task-experience as a result of statistical distractor learning. These results demonstrate a layer-specific involvement of SSA on perception that is susceptible to modulation over time.SIGNIFICANCE STATEMENT:Detecting sudden changes in our immediate environment is behaviorally relevant and important for efficient perceptual processing. However, the connection between the underpinnings of cortical deviance detection and perception remains unknown. Here, we investigate how the cortical representation of deviant whisker stimuli impact visual target detection by recording local field potential and multi-unit activity in the primary somatosensory cortex of mice engaged in a cross-modal visual detection task. We find that deviant whisker stimuli distract animals in their task performance which correlates with enhanced neuronal responses for deviants in a layer-specific manner. Interestingly, this effect reduces with the increased experience of the animal as a result of distractor learning upon statistical regularities.

Bayesian surprise shapes neural responses in somatosensory cortical circuits

Numerous psychophysical studies show that Bayesian inference governs sensory decision-making; however, the specific neural circuitry underlying this probabilistic mechanism remains unclear. We record extracellular neural activity along the somatosensory pathway of mice while delivering sensory stimulation paradigms designed to isolate the response to the surprise generated by Bayesian inference. Our results demonstrate that laminar cortical circuits in early sensory areas encode Bayesian surprise. Systematic sensitivity to surprise is not identified in the somatosensory thalamus, rather emerging in the primary (S1) and secondary (S2) somatosensory cortices. Multiunit spiking activity and evoked potentials in layer 6 of these regions exhibit the highest sensitivity to surprise. Gamma power in S1 layer 2/3 exhibits an NMDAR-dependent scaling with surprise, as does alpha power in layers 2/3 and 6 of S2. These results show a precise spatiotemporal neural representation of Bayesian surprise and suggest that Bayesian inference is a fundamental component of cortical processing.

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.

Deep-learning based identification, tracking, pose estimation, and behavior 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.

A robust model of Stimulus-Specific Adaptation validated on neuromorphic hardware

Stimulus-Specific Adaptation (SSA) to repetitive stimulation is a phenomenon that has been observed across many different species and in several brain sensory areas. It has been proposed as a computational mechanism, responsible for separating behaviorally relevant information from the continuous stream of sensory information. Although SSA can be induced and measured reliably in a wide variety of conditions, the network details and intracellular mechanisms giving rise to SSA still remain unclear. Recent computational studies proposed that SSA could be associated with a fast and synchronous neuronal firing phenomenon called Population Spikes (PS). Here, we test this hypothesis using a mean-field rate model and corroborate it using a neuromorphic hardware. As the neuromorphic circuits used in this study operate in real-time with biologically realistic time constants, they can reproduce the same dynamics observed in biological systems, together with the exploration of different connectivity schemes, with complete control of the system parameter settings. Besides, the hardware permits the iteration of multiple experiments over many trials, for extended amounts of time and without losing the networks and individual neural processes being studied. Following this "neuromorphic engineering" approach, we therefore study the PS hypothesis in a biophysically inspired recurrent networks of spiking neurons and evaluate the role of different linear and non-linear dynamic computational primitives such as spike-frequency adaptation or short-term depression (STD). We compare both the theoretical mean-field model of SSA and PS to previously obtained experimental results in the area of novelty detection and observe its behavior on its neuromorphic physical equivalent model. We show how the approach proposed can be extended to other computational neuroscience modelling efforts for understanding high-level phenomena in mechanistic models.

Non-invasive molecularly-specific millimeter-resolution manipulation of brain circuits by ultrasound-mediated aggregation and uncaging of drug carriers

Non-invasive, molecularly-specific, focal modulation of brain circuits with low off-target effects can lead to breakthroughs in treatments of brain disorders. We systemically inject engineered ultrasound-controllable drug carriers and subsequently apply a novel two-component Aggregation and Uncaging Focused Ultrasound Sequence (AU-FUS) at the desired targets inside the brain. The first sequence aggregates drug carriers with millimeter-precision by orders of magnitude. The second sequence uncages the carrier's cargo locally to achieve high target specificity without compromising the blood-brain barrier (BBB). Upon release from the carriers, drugs locally cross the intact BBB. We show circuit-specific manipulation of sensory signaling in motor cortex in rats by locally concentrating and releasing a GABA_A receptor agonist from ultrasound-controlled carriers. Our approach uses orders of magnitude (1300x) less drug than is otherwise required by systemic injection and requires very low ultrasound pressures (20-fold below FDA safety limits for diagnostic imaging). We show that the BBB remains intact using passive cavitation detection (PCD), MRI-contrast agents and, importantly, also by sensitive fluorescent dye extravasation and immunohistochemistry.

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.

Tactile frequency discrimination is enhanced by circumventing neocortical adaptation

Neocortical responses typically adapt to repeated sensory stimulation, improving sensitivity to stimulus changes, but possibly also imposing limitations on perception. For example, it is unclear whether information about stimulus frequency is perturbed by adaptation or encoded by precise response timing. We addressed this question in rat barrel cortex by comparing performance in behavioral tasks with either whisker stimulation, which causes frequency-dependent adaptation, or optical activation of cortically expressed channelrhodopsin-2, which elicits non-adapting neural responses. Circumventing adaption by optical activation substantially improved cross-hemispheric discrimination of stimulus frequency. This improvement persisted when temporal precision of optically evoked spikes was reduced. We were able to replicate whisker-driven behavior only by applying adaptation rules mimicking sensory-evoked responses to optical stimuli. Conversely, in a change-detection task, animals performed better with whisker than optical stimulation. Our results directly demonstrate that sensory adaptation critically governs the perception of stimulus patterns, decreasing fidelity under steady-state conditions in favor of change detection.

Novel two-alternative forced choice paradigm for bilateral vibrotactile whisker frequency discrimination in head-fixed mice and rats

Rats and mice receive a constant bilateral stream of tactile information with their large mystacial vibrissae when navigating in their environment. In a two-alternative forced choice paradigm (2-AFC), head-fixed rats and mice learned to discriminate vibrotactile frequencies applied simultaneously to individual whiskers on the left and right sides of the snout. Mice and rats discriminated 90-Hz pulsatile stimuli from pulsatile stimuli with lower repetition frequencies (10-80 Hz) but with identical kinematic properties in each pulse. Psychometric curves displayed an average perceptual threshold of 50.6-Hz and 53.0-Hz frequency difference corresponding to Weber fractions of 0.56 and 0.58 in mice and rats, respectively. Both species performed >400 trials a day (>200 trials per session, 2 sessions/day), with a peak performance of >90% correct responses. In general, rats and mice trained in the identical task showed comparable psychometric curves. Behavioral readouts, such as reaction times, learning rates, trial omissions, and impulsivity, were also very similar in the two species. Furthermore, whisking of the animals before stimulus presentation reduced task performance. This behavioral paradigm, combined with whisker position tracking, allows precise stimulus control in the 2-AFC task for head-fixed rodents. It is compatible with state-of-the-art neurophysiological recording techniques, such as electrophysiology and two-photon imaging, and therefore represents a valuable framework for neurophysiological investigations of perceptual decision-making.

Discrimination of direction in fast frequency-modulated tones by rats

Fast frequency modulations (FM) are an essential part of species-specific auditory signals in animals as well as in human speech. Major parameters characterizing non-periodic frequency modulations are the direction of frequency change in the FM sweep (upward/downward) and the sweep speed, i.e., the speed of frequency change. While it is well established that both parameters are represented in the mammalian central auditory pathway, their importance at the perceptual level in animals is unclear. We determined the ability of rats to discriminate between upward and downward modulated FM-tones as a function of sweep speed in a two-alternative-forced-choice-paradigm. Directional discrimination in logarithmic FM-sweeps was reduced with increasing sweep speed between 20 and 1,000 octaves/s following a psychometric function. Average threshold sweep speed for FM directional discrimination was 96 octaves/s. This upper limit of perceptual FM discrimination fits well the upper limit of preferred sweep speeds in auditory neurons and the upper limit of neuronal direction selectivity in the rat auditory cortex and midbrain, as it is found in the literature. Influences of additional stimulus parameters on FM discrimination were determined using an adaptive testing-procedure for efficient threshold estimation based on a maximum likelihood approach. Directional discrimination improved with extended FM sweep range between two and five octaves. Discrimination performance declined with increasing lower frequency boundary of FM sweeps, showing an especially strong deterioration when the boundary was raised from 2 to 4 kHz. This deterioration corresponds to a frequency-dependent decline in direction selectivity of FM-encoding neurons in the rat auditory cortex, as described in the literature. Taken together, by investigating directional discrimination of FM sweeps in the rat we found characteristics at the perceptual level that can be related to several aspects of FM encoding in the central auditory pathway.

Transient calretinin expression defines early postmitotic step of neuronal differentiation in adult hippocampal neurogenesis of mice

We here show that the early postmitotic stage of granule cell development during adult hippocampal neurogenesis is characterized by the transient expression of calretinin (CR). CR expression was detected as early as 1 day after labeling dividing cells with bromodeoxyuridine (BrdU), but not before. Staining for Ki-67 confirmed that no CR-expressing cells were in cell cycle. Early after BrdU, CR colocalized with immature neuronal marker doublecortin; and later with persisting neuronal marker NeuN. BrdU/CR-labeled cells were negative for GABA and GABAA1 receptor, but early on expressed granule cell marker Prox-1. After 6 weeks, no new neurons expressed CR, but all contained calbindin. Stimuli inducing adult neurogenesis have limited (enriched environment), strong (voluntary wheel running), and very strong effects on cell proliferation (kainate-induced seizures). In these models the induction of cell proliferation was paralleled by an increase of CR-positive cells, indicating the stimulus-dependent progression from cell division to a postmitotic stage.