The effect of ketamine on affective modulation of the startle reflex and its resting-state brain correlates.

Ketamine is a rapid-acting antidepressant that also influences neural reactivity to affective stimuli. However, the effect of ketamine on behavioral affective reactivity is yet to be elucidated. The affect-modulated startle reflex paradigm (AMSR) allows examining the valence-specific aspects of behavioral affective reactivity. We hypothesized that ketamine alters the modulation of the startle reflex during processing of unpleasant and pleasant stimuli and weakens the resting-state functional connectivity (rsFC) within the modulatory pathway, namely between the centromedial nucleus of the amygdala and nucleus reticularis pontis caudalis. In a randomized, double-blind, placebo-controlled, cross-over study, thirty-two healthy male participants underwent ultra-high field resting-state functional magnetic resonance imaging at 7 T before and 24 h after placebo and S-ketamine infusions. Participants completed the AMSR task at baseline and one day after each infusion. In contrast to our hypothesis, ketamine infusion did not impact startle potentiation during processing of unpleasant stimuli but resulted in diminished startle attenuation during processing of pleasant stimuli. This diminishment significantly correlated with end-of-infusion plasma levels of ketamine and norketamine. Furthermore, ketamine induced a decrease in rsFC within the modulatory startle reflex pathway. The results of this first study on the effect of ketamine on the AMSR suggest that ketamine might attenuate the motivational significance of pleasant stimuli in healthy participants one day after infusion.

Effect of cochlear implant side on early speech processing in adults with single-sided deafness.

OBJECTIVE: In binaurally deaf subjects, speech processing particularly benefits from a cochlear implant (CI) in the right ear, which is contralateral to the commonly left speech-dominant hemisphere. However, it is unclear whether such effects of implantation side also occur in speech processing in patients with single-sided deafness (SSD). METHODS: Lateralization of N1 responses was analyzed with a high-density electroencephalogram (EEG) in fourteen adults with postlingually acquired left or right SSD who received a CI in adulthood. During recording, patients performed a speech and a pure-tone discrimination task. Lateralization of N1 responses was assessed by side-specific global field power (GFP) and compared (a) between normal hearing and CI-implanted ears within subjects and (b) between implantation sides across subjects. RESULTS: N1 responses were stronger in the contralateral than in the ipsilateral hemisphere during stimulation of the normal hearing ear (except for left speech stimulation), and was bilateral symmetric with CI stimulation on either side. A significant correlation between speech discrimination performance and left lateralization was found across subjects for the left CI ear. CONCLUSIONS: CI stimulation altered auditory processing across hemispheres. Speech discrimination in left CI-implanted SSD patients improved with left lateralization of the N1 response. SIGNIFICANCE: Side-specific rehabilitation in SSD patients might improve speech processing across hemispheres.

Non-invasive recording of high-frequency signals from the human spinal cord.

Throughout the somatosensory system, neuronal ensembles generate high-frequency signals in the range of several hundred Hertz in response to sensory input. High-frequency signals have been related to neuronal spiking, and could thus help clarify the functional architecture of sensory processing. Recording high-frequency signals from subcortical regions, however, has been limited to clinical pathology whose treatment allows for invasive recordings. Here, we demonstrate the feasibility to record 200-1200 Hz signals from the human spinal cord non-invasively, and in healthy individuals. Using standard electroencephalography equipment in a cervical electrode montage, we observed high-frequency signals between 200 and 1200 Hz in a time window between 8 and 16 ms after electric median nerve stimulation (n = 15). These signals overlapped in latency, and, partly, in frequency, with signals obtained via invasive, epidural recordings from the spinal cord in a patient with neuropathic pain. Importantly, the observed high-frequency signals were dissociable from classic spinal evoked responses. A spatial filter that optimized the signal-to-noise ratio of high-frequency signals led to submaximal amplitudes of the evoked response, and vice versa, ruling out the possibility that high-frequency signals are merely a spectral representation of the evoked response. Furthermore, we observed spontaneous fluctuations in the amplitude of high-frequency signals over time, in the absence of any concurrent, systematic change to the evoked response. High-frequency, "spike-like" signals from the human spinal cord thus carry information that is complementary to the evoked response. The possibility to assess these signals non-invasively provides a novel window onto the neurophysiology of the human spinal cord, both in a context of top-down control over perception, as well as in pathology.

The extracellular matrix regulates cortical layer dynamics and cross-columnar frequency integration in the auditory cortex.

In the adult vertebrate brain, enzymatic removal of the extracellular matrix (ECM) is increasingly recognized to promote learning, memory recall, and restorative plasticity. The impact of the ECM on translaminar dynamics during cortical circuit processing is still not understood. Here, we removed the ECM in the primary auditory cortex (ACx) of adult Mongolian gerbils using local injections of hyaluronidase (HYase). Using laminar current-source density (CSD) analysis, we found layer-specific changes of the spatiotemporal synaptic patterns with increased cross-columnar integration and simultaneous weakening of early local sensory input processing within infragranular layers Vb. These changes had an oscillatory fingerprint within beta-band (25-36 Hz) selectively within infragranular layers Vb. To understand the laminar interaction dynamics after ECM digestion, we used time-domain conditional Granger causality (GC) measures to identify the increased drive of supragranular layers towards deeper infragranular layers. These results showed that ECM degradation altered translaminar cortical network dynamics with a stronger supragranular lead of the columnar response profile.

Spatial Filtering of Electroencephalography Reduces Artifacts and Enhances Signals Related to Spinal Cord Stimulation (SCS).

OBJECTIVES: How spinal cord stimulation (SCS) in its different modes suppresses pain is poorly understood. Mechanisms of action may reside locally in the spinal cord, but also involve a larger network including subcortical and cortical brain structures. Tonic, burst, and high-frequency modes of SCS can, in principle, entrain distinct temporal activity patterns in this network, but finally have to yield specific effects on pain suppression. Here, we employ high-density electroencephalography (EEG) and recently developed spatial filtering techniques to reduce SCS artifacts and to enhance EEG signals specifically related to neuromodulation by SCS. MATERIALS AND METHODS: We recorded high-density resting-state EEGs in patients suffering from pain of various etiologies under different modes of SCS. We established a pipeline for the robust spectral analysis of oscillatory brain activity during SCS, which includes spatial filtering for attenuation of pulse artifacts and enhancement of brain activity potentially modulated by SCS. RESULTS: In sensor regions responsive to SCS, neuromodulation strongly reduced activity in the theta and low alpha range (6-10 Hz) in all SCS modes. Results were consistent in all patients, and in accordance with thalamocortical dysrhythmia hypothesis of pain. Only in the tonic mode showing paresthesia as side effect, SCS also consistently and strongly reduced high-gamma activity (>84 Hz). CONCLUSIONS: EEG spectral analysis combined with spatial filtering allows for a spatially and temporally specific assessment of SCS-related, neuromodulatory EEG activity, and may help to disentangle therapeutic and side effects of SCS.

Task rule and choice are reflected by layer-specific processing in rodent auditory cortical microcircuits.

The primary auditory cortex (A1) is an essential, integrative node that encodes the behavioral relevance of acoustic stimuli, predictions, and auditory-guided decision-making. However, the realization of this integration with respect to the cortical microcircuitry is not well understood. Here, we characterize layer-specific, spatiotemporal synaptic population activity with chronic, laminar current source density analysis in Mongolian gerbils (Meriones unguiculatus) trained in an auditory decision-making Go/NoGo shuttle-box task. We demonstrate that not only sensory but also task- and choice-related information is represented in the mesoscopic neuronal population code of A1. Based on generalized linear-mixed effect models we found a layer-specific and multiplexed representation of the task rule, action selection, and the animal's behavioral options as accumulating evidence in preparation of correct choices. The findings expand our understanding of how individual layers contribute to the integrative circuit in the sensory cortex in order to code task-relevant information and guide sensory-based decision-making.

Self-regulated critical brain dynamics originate from high frequency-band activity in the MEG.

Brain function requires the flexible coordination of billions of neurons across multiple scales. This could be achieved by scale-free, critical dynamics balanced at the edge of order and disorder. Criticality has been demonstrated in several, often reduced neurophysiological model systems. In the intact human brain criticality has yet been only verified for the resting state. A more direct link between the concept of criticality and oscillatory brain physiology, which is strongly related to cognition, is yet missing. In the present study we therefore carried out a frequency-specific analysis of criticality in the MEG, recorded while subjects were in a defined cognitive state through mindfulness meditation. In a two-step approach we assessed whether the macroscopic neural avalanche dynamics is scale-free by evaluating the goodness of a power-law fits of cascade size and duration distributions of MEG deflections in different frequency bands. In a second step we determined the closeness of the power-law exponents to a critical value of -1.5. Power-law fitting was evaluated by permutation testing, fitting of alternative distributions, and cascade shape analysis. Criticality was verified by defined relationships of exponents of cascade size and duration distributions. Behavioral relevance of criticality was tested by correlation of indices of criticality with individual scores of the Mindful Attention Awareness Scale. We found that relevant scale-free near-critical dynamics originated only from broad-band high-frequency (> 100 Hz) MEG activity, which has been associated with action potential firing, and therefore links criticality on the macroscopic level of MEG to critical spike avalanches on a microscopic level. Whereas a scale-free dynamics was found under mindfulness meditation and rest, avalanche dynamics shifted towards a critical point during meditation by reduction of neural noise. Together with our finding that during mindfulness meditation avalanches show differences in topography relative to rest, our results show that self-regulated attention as required during meditation can serve as a control parameter of criticality in scale-free brain dynamics.

Ketamine anaesthesia induces gain enhancement via recurrent excitation in granular input layers of the auditory cortex.

KEY POINTS: Ketamine is a common anaesthetic agent used in research and more recently as medication in treatment of depression. It has known effects on inhibition of interneurons and cortical stimulus-locked responses, but the underlying functional network mechanisms are still elusive. Analysing population activity across all layers within the auditory cortex, we found that doses of this anaesthetic induce a stronger activation and stimulus-locked response to pure-tone stimuli. This cortical response is driven by gain enhancement of thalamocortical input processing selectively within granular layers due to an increased recurrent excitation. Time-frequency analysis indicates a higher broadband magnitude response and prolonged phase coherence in granular layers, possibly pointing to disinhibition of this recurrent excitation. These results further the understanding of ketamine's functional mechanisms, which will improve the ability to interpret physiological studies moving from anaesthetized to awake paradigms and may lead to the development of better ketamine-based depression treatments with lower side effects. ABSTRACT: Ketamine is commonly used as an anaesthetic agent and has more recently gained attention as an antidepressant. It has been linked to increased stimulus-locked excitability, inhibition of interneurons and modulation of intrinsic neuronal oscillations. However, the functional network mechanisms are still elusive. A better understanding of these anaesthetic network effects may improve upon previous interpretations of seminal studies conducted under anaesthesia and have widespread relevance for neuroscience with awake and anaesthetized subjects as well as in medicine. Here, we investigated the effects of anaesthetic doses of ketamine (15 mg kg-1  h-1 i.p.) on the network activity after pure-tone stimulation within the auditory cortex of male Mongolian gerbils (Meriones unguiculatus). We used laminar current source density (CSD) analysis and subsequent layer-specific continuous wavelet analysis to investigate spatiotemporal response dynamics on cortical columnar processing in awake and ketamine-anaesthetized animals. We found thalamocortical input processing within granular layers III/IV to be significantly increased under ketamine. This layer-dependent gain enhancement under ketamine was not due to changes in cross-trial phase coherence but was rather attributed to a broadband increase in magnitude reflecting an increase in recurrent excitation. A time-frequency analysis was indicative of a prolonged period of stimulus-induced excitation possibly due to a reduced coupling of excitation and inhibition in granular input circuits - in line with the common hypothesis of cortical disinhibition via suppression of GABAergic interneurons.

Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks.

Electroencephalogram (EEG) microstates that represent quasi-stable, global neuronal activity are considered as the building blocks of brain dynamics. Therefore, the analysis of microstate sequences is a promising approach to understand fast brain dynamics that underlie various mental processes. Recent studies suggest that EEG microstate sequences are non-Markovian and nonstationary, highlighting the importance of the sequential flow of information between different brain states. These findings inspired us to model these sequences using Recurrent Neural Networks (RNNs) consisting of long-short-term-memory (LSTM) units to capture the complex temporal dependencies. Using an LSTM-based auto encoder framework and different encoding schemes, we modeled the microstate sequences at multiple time scales (200-2,000 ms) aiming to capture stably recurring microstate patterns within and across subjects. We show that RNNs can learn underlying microstate patterns with high accuracy and that the microstate trajectories are subject invariant at shorter time scales (≤400 ms) and reproducible across sessions. Significant drop in the reconstruction accuracy was observed for longer sequence lengths of 2,000 ms. These findings indirectly corroborate earlier studies which indicated that EEG microstate sequences exhibit long-range dependencies with finite memory content. Furthermore, we find that the latent representations learned by the RNNs are sensitive to external stimulation such as stress while the conventional univariate microstate measures (e.g., occurrence, mean duration, etc.) fail to capture such changes in brain dynamics. While RNNs cannot be configured to identify the specific discriminating patterns, they have the potential for learning the underlying temporal dynamics and are sensitive to sequence aberrations characterized by changes in metal processes. Empowered with the macroscopic understanding of the temporal dynamics that extends beyond short-term interactions, RNNs offer a reliable alternative for exploring system level brain dynamics using EEG microstate sequences.

Dopaminergic neuromodulation of high gamma stimulus phase-locking in gerbil primary auditory cortex mediated by D1/D5-receptors.

Cortical release of the neurotransmitter dopamine has been implied in adapting cortical processing with respect to various functions including coding of stimulus salience, expectancy, error prediction, behavioral relevance and learning. Dopamine agonists have been shown to modulate recurrent cortico-thalamic feedback, and should therefore also affect synchronization and amplitude of thalamo-cortical oscillations. In this study, we have used multitaper spectral and time-frequency analysis of stimulus-evoked and spontaneous current source density patterns in primary auditory cortex of Mongolian gerbils to characterize dopaminergic neuromodulation of the oscillatory structure of current sources and sinks. We systemically applied D1/D5-receptor agonist SKF-38393 followed by competitive D1/D5-receptor antagonist SCH-23390. Our results reveal an increase in stimulus phase-locking in the high gamma-band (88-97 Hz) by SKF-38393, specifically in layers III/IV at the best frequency, which occurred at 20 ms after tone onset, and was reversed by SCH-23390. However, changes in induced oscillatory power after SKF-38393 treatment occurred stimulus-independently in the background activity in different layers than phase-locking effects and were not reversed by SCH-23390. These effects might either reflect longer-lasting changes in neural background noise, non-specific changes due to ketamine anesthesia, or an interaction of both. Without concomitant stimulus-induced power increase, increased stimulus phase-locking in layers III/IV indicates enhanced phase-resetting of neural oscillations by the stimulus after D1/D5-receptor activation. The frequency characteristics, together with the demonstrated stimulus specificity and layer specificity, suggest that changes in phase-resetting originate from dopaminergic neuromodulation of thalamo-cortical interactions. Enhanced phase-resetting might be a key step in the recruitment of cortical activity modes interpreting sensory input.

Optogenetic stimulation of the VTA modulates a frequency-specific gain of thalamocortical inputs in infragranular layers of the auditory cortex.

Reward associations during auditory learning induce cortical plasticity in the primary auditory cortex. A prominent source of such influence is the ventral tegmental area (VTA), which conveys a dopaminergic teaching signal to the primary auditory cortex. Yet, it is unknown, how the VTA influences cortical frequency processing and spectral integration. Therefore, we investigated the temporal effects of direct optogenetic stimulation of the VTA onto spectral integration in the auditory cortex on a synaptic circuit level by current-source-density analysis in anesthetized Mongolian gerbils. While auditory lemniscal input predominantly terminates in the granular input layers III/IV, we found that VTA-mediated modulation of spectral processing is relayed by a different circuit, namely enhanced thalamic inputs to the infragranular layers Vb/VIa. Activation of this circuit yields a frequency-specific gain amplification of local sensory input and enhances corticocortical information transfer, especially in supragranular layers I/II. This effects persisted over more than 30 minutes after VTA stimulation. Altogether, we demonstrate that the VTA exhibits a long-lasting influence on sensory cortical processing via infragranular layers transcending the signaling of a mere reward-prediction error. We thereby demonstrate a cellular and circuit substrate for the influence of reinforcement-evaluating brain systems on sensory processing in the auditory cortex.

Electrocortical components of anticipation and consumption in a monetary incentive delay task.

In order to improve our understanding of the components that reflect functionally important processes during reward anticipation and consumption, we used principle components analyses (PCA) to separate and quantify averaged ERP data obtained from each stage of a modified monetary incentive delay (MID) task. Although a small number of recent ERP studies have reported that reward and loss cues potentiate ERPs during anticipation, action preparation, and consummatory stages of reward processing, these findings are inconsistent due to temporal and spatial overlap between the relevant electrophysiological components. Our results show three components following cue presentation are sensitive to incentive cues (N1, P3a, P3b). In contrast to previous research, reward-related enhancement occurred only in the P3b, with earlier components more sensitive to break-even and loss cues. During feedback anticipation, we observed a lateralized centroparietal negativity that was sensitive to response hand but not cue type. We also show that use of PCA on ERPs reflecting reward consumption successfully separates the reward positivity from the independently modulated feedback-P3. Last, we observe for the first time a new reward consumption component: a late negativity distributed over the left frontal pole. This component appears to be sensitive to response hand, especially in the context of monetary gain. These results illustrate that the time course and sensitivities of electrophysiological activity that follows incentive cues do not follow a simple heuristic in which reward incentive cues produce enhanced activity at all stages and substages.

Probing neural mechanisms underlying auditory stream segregation in humans by transcranial direct current stimulation (tDCS).

One hypothesis concerning the neural underpinnings of auditory streaming states that frequency tuning of tonotopically organized neurons in primary auditory fields in combination with physiological forward suppression is necessary for the separation of representations of high-frequency A and low-frequency B tones. The extent of spatial overlap between the tonotopic activations of A and B tones is thought to underlie the perceptual organization of streaming sequences into one coherent or two separate streams. The present study attempts to interfere with these mechanisms by transcranial direct current stimulation (tDCS) and to probe behavioral outcomes reflecting the perception of ABAB streaming sequences. We hypothesized that tDCS by modulating cortical excitability causes a change in the separateness of the representations of A and B tones, which leads to a change in the proportions of one-stream and two-stream percepts. To test this, 22 subjects were presented with ambiguous ABAB sequences of three different frequency separations (∆F) and had to decide on their current percept after receiving sham, anodal, or cathodal tDCS over the left auditory cortex. We could confirm our hypothesis at the most ambiguous ∆F condition of 6 semitones. For anodal compared with sham and cathodal stimulation, we found a significant decrease in the proportion of two-stream perception and an increase in the proportion of one-stream perception. The results demonstrate the feasibility of using tDCS to probe mechanisms underlying auditory streaming through the use of various behavioral measures. Moreover, this approach allows one to probe the functions of auditory regions and their interactions with other processing stages.

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis.

Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning.

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning.

Shuttle-box avoidance learning is a well-established method in behavioral neuroscience and experimental setups were traditionally custom-made; the necessary equipment is now available by several commercial companies. This protocol provides a detailed description of a two-way shuttle-box avoidance learning paradigm in rodents (here Mongolian gerbils; Meriones unguiculatus) in combination with site-specific electrical intracortical microstimulation (ICMS) and simultaneous chronical electrophysiological in vivo recordings. The detailed protocol is applicable to study multiple aspects of learning behavior and perception in different rodent species. Site-specific ICMS of auditory cortical circuits as conditioned stimuli here is used as a tool to test the perceptual relevance of specific afferent, efferent and intracortical connections. Distinct activation patterns can be evoked by using different stimulation electrode arrays for local, layer-dependent ICMS or distant ICMS sites. Utilizing behavioral signal detection analysis it can be determined which stimulation strategy is most effective for eliciting a behaviorally detectable and salient signal. Further, parallel multichannel-recordings using different electrode designs (surface electrodes, depth electrodes, etc.) allow for investigating neuronal observables over the time course of such learning processes. It will be discussed how changes of the behavioral design can increase the cognitive complexity (e.g. detection, discrimination, reversal learning).

Enhanced cognitive flexibility in reversal learning induced by removal of the extracellular matrix in auditory cortex.

During brain maturation, the occurrence of the extracellular matrix (ECM) terminates juvenile plasticity by mediating structural stability. Interestingly, enzymatic removal of the ECM restores juvenile forms of plasticity, as for instance demonstrated by topographical reconnectivity in sensory pathways. However, to which degree the mature ECM is a compromise between stability and flexibility in the adult brain impacting synaptic plasticity as a fundamental basis for learning, lifelong memory formation, and higher cognitive functions is largely unknown. In this study, we removed the ECM in the auditory cortex of adult Mongolian gerbils during specific phases of cortex-dependent auditory relearning, which was induced by the contingency reversal of a frequency-modulated tone discrimination, a task requiring high behavioral flexibility. We found that ECM removal promoted a significant increase in relearning performance, without erasing already established-that is, learned-capacities when continuing discrimination training. The cognitive flexibility required for reversal learning of previously acquired behavioral habits, commonly understood to mainly rely on frontostriatal circuits, was enhanced by promoting synaptic plasticity via ECM removal within the sensory cortex. Our findings further suggest experimental modulation of the cortical ECM as a tool to open short-term windows of enhanced activity-dependent reorganization allowing for guided neuroplasticity.

Dopamine-modulated recurrent corticoefferent feedback in primary sensory cortex promotes detection of behaviorally relevant stimuli.

Dopaminergic neurotransmission in primary auditory cortex (AI) has been shown to be involved in learning and memory functions. Moreover, dopaminergic projections and D1/D5 receptor distributions display a layer-dependent organization, suggesting specific functions in the cortical circuitry. However, the circuit effects of dopaminergic neurotransmission in sensory cortex and their possible roles in perception, learning, and memory are largely unknown. Here, we investigated layer-specific circuit effects of dopaminergic neuromodulation using current source density (CSD) analysis in AI of Mongolian gerbils. Pharmacological stimulation of D1/D5 receptors increased auditory-evoked synaptic currents in infragranular layers, prolonging local thalamocortical input via positive feedback between infragranular output and granular input. Subsequently, dopamine promoted sustained cortical activation by prolonged recruitment of long-range corticocortical networks. A detailed circuit analysis combining layer-specific intracortical microstimulation (ICMS), CSD analysis, and pharmacological cortical silencing revealed that cross-laminar feedback enhanced by dopamine relied on a positive, fast-acting recurrent corticoefferent loop, most likely relayed via local thalamic circuits. Behavioral signal detection analysis further showed that activation of corticoefferent output by infragranular ICMS, which mimicked auditory activation under dopaminergic influence, was most effective in eliciting a behaviorally detectable signal. Our results show that D1/D5-mediated dopaminergic modulation in sensory cortex regulates positive recurrent corticoefferent feedback, which enhances states of high, persistent activity in sensory cortex evoked by behaviorally relevant stimuli. In boosting horizontal network interactions, this potentially promotes the readout of task-related information from cortical synapses and improves behavioral stimulus detection.

Auditory cortical activity after intracortical microstimulation and its role for sensory processing and learning.

Several studies have shown that animals can learn to make specific use of intracortical microstimulation (ICMS) of sensory cortex within behavioral tasks. Here, we investigate how the focal, artificial activation by ICMS leads to a meaningful, behaviorally interpretable signal. In natural learning, this involves large-scale activity patterns in widespread brain-networks. We therefore trained gerbils to discriminate closely neighboring ICMS sites within primary auditory cortex producing evoked responses largely overlapping in space. In parallel, during training, we recorded electrocorticograms (ECoGs) at high spatial resolution. Applying a multivariate classification procedure, we identified late spatial patterns that emerged with discrimination learning from the ongoing poststimulus ECoG. These patterns contained information about the preceding conditioned stimulus, and were associated with a subsequent correct behavioral response by the animal. Thereby, relevant pattern information was mainly carried by neuron populations outside the range of the lateral spatial spread of ICMS-evoked cortical activation (approximately 1.2 mm). This demonstrates that the stimulated cortical area not only encoded information about the stimulation sites by its focal, stimulus-driven activation, but also provided meaningful signals in its ongoing activity related to the interpretation of ICMS learned by the animal. This involved the stimulated area as a whole, and apparently required large-scale integration in the brain. However, ICMS locally interfered with the ongoing cortical dynamics by suppressing pattern formation near the stimulation sites. The interaction between ICMS and ongoing cortical activity has several implications for the design of ICMS protocols and cortical neuroprostheses, since the meaningful interpretation of ICMS depends on this interaction.

Segregation of task-relevant conditioned stimuli from background stimuli by associative learning.

In the real world, task-relevant, conditioned stimuli are often embedded in a varying background, from which they have to be segregated. Besides sensory mechanisms, associative learning assumingly plays an important role for the segregation of the conditioned from the background stimuli, especially if conditioned and background stimuli are spectro-temporally structured, and psychophysically similar. We therefore investigated the influence of spectro-temporally structured background tones on associative learning of conditioned tones depending on the complexity of the behavioral task and the psychophysical similarity between conditioned and background tones. Frequency-modulated tone sweeps were used as conditioned stimuli, and persisting frequency-modulated tones as background. In a shuttle-box, Mongolian gerbils were subjected to a simple detection task, or to a more complex discrimination task. In contrast to detection learning, introduction or change of background tones affected discrimination performance both during learning and at the stage of retrieval, especially when conditioned and background tones were spectro-temporally similar. The change from a familiar to a new background tone at the stage of retrieval caused a prefrontal dopamine increase and lead to relearning of task-relevant associations. We conclude that conditioned stimuli and background stimuli are processed concomitantly, which might provide contextual information, but requires additional cognitive processing.