Climbing fibers provide essential instructive signals for associative learning.

Supervised learning depends on instructive signals that shape the output of neural circuits to support learned changes in behavior. Climbing fiber (CF) inputs to the cerebellar cortex represent one of the strongest candidates in the vertebrate brain for conveying neural instructive signals. However, recent studies have shown that Purkinje cell stimulation can also drive cerebellar learning and the relative importance of these two neuron types in providing instructive signals for cerebellum-dependent behaviors remains unresolved. In the present study we used cell-type-specific perturbations of various cerebellar circuit elements to systematically evaluate their contributions to delay eyeblink conditioning in mice. Our findings reveal that, although optogenetic stimulation of either CFs or Purkinje cells can drive learning under some conditions, even subtle reductions in CF signaling completely block learning to natural stimuli. We conclude that CFs and corresponding Purkinje cell complex spike events provide essential instructive signals for associative cerebellar learning.

A Novel Approach to Study Coherent γ-Band Oscillations in Hippocampal Brain Sections.

γ-Band oscillations (GBOs) are generated by fast-spiking interneurons (FSIs) and are critical for cognitive functions. Abnormalities in GBOs are frequently observed in schizophrenia and bipolar disorder and are strongly correlated with cognitive impairment. However, the underlying mechanisms are poorly understood. Studying GBOs in ex vivo preparations is challenging because of high energy demands and the need for continuous oxygen delivery to the tissue. As a result, GBOs are typically studied in brain tissue from very young animals or in experimental setups that maximize oxygen supply but compromise spatial resolution. Thus, there is a limited understanding of how GBOs interact within and between different brain structures and in brain tissue from mature animals. To address these limitations, we have developed a novel approach for studying GBOs in ex vivo hippocampal slices from mature animals, using 60-channel, perforated microelectrode arrays (pMEAs). pMEAs enhance oxygen delivery and increase spatial resolution in electrophysiological recordings, enabling comprehensive analyses of GBO synchronization within discrete brain structures. We found that transecting the Schaffer collaterals, a neural pathway within the hippocampus, impairs GBO coherence between CA1 and CA3 subfields. Furthermore, we validated our approach by studying GBO coherence in an Ank3 mutant mouse model exhibiting inhibitory synaptic dysfunction. We discovered that GBO coherence remains intact in the CA3 subfield of these mutant mice but is impaired within and between the CA1 subfield. Overall, our approach offers significant potential to characterize GBOs in ex vivo brain sections of animal models, enhancing our understanding of network dysfunction in psychiatric disorders.

Hemispheric and Sex Differences in Mustached Bat Primary Auditory Cortex Revealed by Neural Responses to Slow Frequency Modulations.

The mustached bat (Pteronotus parnellii) is a mammalian model of cortical hemispheric asymmetry. In this species, complex social vocalizations are processed preferentially in the left Doppler-shifted constant frequency (DSCF) subregion of primary auditory cortex. Like hemispheric specializations for speech and music, this bat brain asymmetry differs between sexes (i.e., males>females) and is linked to spectrotemporal processing based on selectivities to frequency modulations (FMs) with rapid rates (>0.5 kHz/ms). Analyzing responses to the long-duration (>10 ms), slow-rate (<0.5 kHz/ms) FMs to which most DSCF neurons respond may reveal additional neural substrates underlying this asymmetry. Here, we bilaterally recorded responses from 176 DSCF neurons in male and female bats that were elicited by upward and downward FMs fixed at 0.04 kHz/ms and presented at 0-90 dB SPL. In females, we found inter-hemispheric latency differences consistent with applying different temporal windows to precisely integrate spectrotemporal information. In males, we found a substrate for asymmetry less related to spectrotemporal processing than to acoustic energy (i.e., amplitude). These results suggest that in the DSCF area, (1) hemispheric differences in spectrotemporal processing manifest differently between sexes, and (2) cortical asymmetry for social communication is driven by spectrotemporal processing differences and neural selectivities for amplitude.

Locomotor activity modulates associative learning in mouse cerebellum.

Changes in behavioral state can profoundly influence brain function. Here we show that behavioral state modulates performance in delay eyeblink conditioning, a cerebellum-dependent form of associative learning. Increased locomotor speed in head-fixed mice drove earlier onset of learning and trial-by-trial enhancement of learned responses that were dissociable from changes in arousal and independent of sensory modality. Eyelid responses evoked by optogenetic stimulation of mossy fiber inputs to the cerebellum, but not at sites downstream, were positively modulated by ongoing locomotion. Substituting prolonged, low-intensity optogenetic mossy fiber stimulation for locomotion was sufficient to enhance conditioned responses. Our results suggest that locomotor activity modulates delay eyeblink conditioning through increased activation of the mossy fiber pathway within the cerebellum. Taken together, these results provide evidence for a novel role for behavioral state modulation in associative learning and suggest a potential mechanism through which engaging in movement can improve an individual's ability to learn.

For things needing your attention: the role of neocortical gamma in sensory perception.

Two general classes of hypotheses for the role for gamma oscillations in sensation are those that predict gamma facilitates signal amplification through local synchronization of a distinct ensemble, and those that predict gamma modulates fine temporal relationships between neurons to represent information. Correlative evidence has been offered for and against these hypotheses. A recent study in which gamma was optogenetically entrained by driving fast-spiking interneurons showed enhanced sensory detection of harder-to-perceive stimuli, those that benefit most from attention, in agreement with the amplification hypotheses. These findings are supported by similar studies employing less specific optogenetic patterns or single neuron stimulation, but contrast with findings based on direct optogenetic stimulation of pyramidal neurons. Key next steps for this topic are described.

Attention drives synchronization of alpha and beta rhythms between right inferior frontal and primary sensory neocortex.

The right inferior frontal cortex (rIFC) is specifically associated with attentional control via the inhibition of behaviorally irrelevant stimuli and motor responses. Similarly, recent evidence has shown that alpha (7-14 Hz) and beta (15-29 Hz) oscillations in primary sensory neocortical areas are enhanced in the representation of non-attended stimuli, leading to the hypothesis that allocation of these rhythms plays an active role in optimal inattention. Here, we tested the hypothesis that selective synchronization between rIFC and primary sensory neocortex occurs in these frequency bands during inattention. We used magnetoencephalography to investigate phase synchrony between primary somatosensory (SI) and rIFC regions during a cued-attention tactile detection task that required suppression of response to uncertain distractor stimuli. Attentional modulation of synchrony between SI and rIFC was found in both the alpha and beta frequency bands. This synchrony manifested as an increase in the alpha-band early after cue between non-attended SI representations and rIFC, and as a subsequent increase in beta-band synchrony closer to stimulus processing. Differences in phase synchrony were not found in several proximal control regions. These results are the first to reveal distinct interactions between primary sensory cortex and rIFC in humans and suggest that synchrony between rIFC and primary sensory representations plays a role in the inhibition of irrelevant sensory stimuli and motor responses.

Gamma-range synchronization of fast-spiking interneurons can enhance detection of tactile stimuli.

We tested the sensory impact of repeated synchronization of fast-spiking interneurons (FS), an activity pattern thought to underlie neocortical gamma oscillations. We optogenetically drove 'FS-gamma' while mice detected naturalistic vibrissal stimuli and found enhanced detection of less salient stimuli and impaired detection of more salient ones. Prior studies have predicted that the benefit of FS-gamma is generated when sensory neocortical excitation arrives in a specific temporal window 20-25 ms after FS synchronization. To systematically test this prediction, we aligned periodic tactile and optogenetic stimulation. We found that the detection of less salient stimuli was improved only when peripheral drive led to the arrival of excitation 20-25 ms after synchronization and that other temporal alignments either had no effects or impaired detection. These results provide causal evidence that FS-gamma can enhance processing of less salient stimuli, those that benefit from the allocation of attention.

A matter of trial and error for motor learning.

Climbing fiber inputs to cerebellar Purkinje cells are thought to carry error signals that can trigger motor learning across multiple time scales. A new study by Kimpo et al. finds that the potency of climbing fibers as instructive signals for adaptation of the vestibulo-ocular reflex depends on task conditions.

The flexDrive: an ultra-light implant for optical control and highly parallel chronic recording of neuronal ensembles in freely moving mice.

Electrophysiological recordings from ensembles of neurons in behaving mice are a central tool in the study of neural circuits. Despite the widespread use of chronic electrophysiology, the precise positioning of recording electrodes required for high-quality recordings remains a challenge, especially in behaving mice. The complexity of available drive mechanisms, combined with restrictions on implant weight tolerated by mice, limits current methods to recordings from no more than 4-8 electrodes in a single target area. We developed a highly miniaturized yet simple drive design that can be used to independently position 16 electrodes with up to 64 channels in a package that weighs ~2 g. This advance over current designs is achieved by a novel spring-based drive mechanism that reduces implant weight and complexity. The device is easy to build and accommodates arbitrary spatial arrangements of electrodes. Multiple optical fibers can be integrated into the recording array and independently manipulated in depth. Thus, our novel design enables precise optogenetic control and highly parallel chronic recordings of identified single neurons throughout neural circuits in mice.

Effects of mindfulness meditation training on anticipatory alpha modulation in primary somatosensory cortex.

During selective attention, ∼7-14 Hz alpha rhythms are modulated in early sensory cortices, suggesting a mechanistic role for these dynamics in perception. Here, we investigated whether alpha modulation can be enhanced by "mindfulness" meditation (MM), a program training practitioners in sustained attention to body and breath-related sensations. We hypothesized that participants in the MM group would exhibit enhanced alpha power modulation in a localized representation in the primary somatosensory neocortex in response to a cue, as compared to participants in the control group. Healthy subjects were randomized to 8-weeks of MM training or a control group. Using magnetoencephalographic (MEG) recording of the SI finger representation, we found meditators demonstrated enhanced alpha power modulation in response to a cue. This finding is the first to show enhanced local alpha modulation following sustained attentional training, and implicates this form of enhanced dynamic neural regulation in the behavioral effects of meditative practice.

What do we gain from gamma? Local dynamic gain modulation drives enhanced efficacy and efficiency of signal transmission.

Gamma oscillations in neocortex are hypothesized to improve information transmission between groups of neurons. We recently showed that optogenetic drive of fast-spiking interneurons (FS) at 40 Hz in mouse neocortex in vivo modulates the spike count and precision of sensory evoked responses. At specific phases of alignment between stimuli and FS activation, total evoked spike count was unchanged compared to baseline, but precision was increased. In the present study, we used computational modeling to investigate the origin of these local transformations, and to make predictions about their impact on downstream signal transmission. We replicated the prior experimental findings, and found that the local gain observed can be explained by mutual inhibition of fast-spiking interneurons, leading to more robust sensory-driven spiking in a brief temporal window post-stimulus, increasing local synchrony. Enhanced spiking in a second neocortical area, without a net increase in overall driven spikes in the first area, resulted from faster depolarization of target neurons due to increased pre-synaptic synchrony. In addition, we found that the precise temporal structure of spiking in the first area impacted the gain between cortical areas. The optimal spike distribution matched the "window of opportunity" defined by the timing of inhibition in the target area: spiking beyond this window did not contribute to downstream spike generation, leading to decreased overall gain. This result predicts that efficient transmission between neocortical areas requires a mechanism to dynamically match the temporal structure of the output of one area to the timing of inhibition in the recipient zone.

Cued spatial attention drives functionally relevant modulation of the mu rhythm in primary somatosensory cortex.

Cued spatial attention modulates functionally relevant alpha rhythms in visual cortices in humans. Here, we present evidence for analogous phenomena in primary somatosensory neocortex (SI). Using magnetoencephalography, we measured changes in the SI mu rhythm containing mu-alpha (7-14 Hz) and mu-beta (15-29 Hz) components. We found that cued attention impacted mu-alpha in the somatopically localized hand representation in SI, showing decreased power after attention was cued to the hand and increased power after attention was cued to the foot, with significant differences observed 500-1100 ms after cue. Mu-beta showed differences in a time window 800-850 ms after cue. The visual cue also drove an early evoked response beginning ∼70 ms after cue with distinct peaks modulated with cued attention. Distinct components of the tactile stimulus-evoked response were also modulated with cued attention. Analysis of a second dataset showed that, on a trial-by-trial basis, tactile detection probabilities decreased linearly with prestimulus mu-alpha and mu-beta power. These results support the growing consensus that cue-induced alpha modulation is a functionally relevant sensory gating mechanism deployed by attention. Further, while cued attention had a weaker effect on the allocation of mu-beta, oscillations in this band also predicted tactile detection.

Transformations in oscillatory activity and evoked responses in primary somatosensory cortex in middle age: a combined computational neural modeling and MEG study.

Oscillatory brain rhythms and evoked responses are widely believed to impact cognition, but relatively little is known about how these measures are affected by healthy aging. The present study used MEG to examine age-related changes in spontaneous oscillations and tactile evoked responses in primary somatosensory cortex (SI) in healthy young (YA) and middle-aged (MA) adults. To make specific predictions about neurophysiological changes that mediate age-related MEG changes, we applied a biophysically realistic model of SI that accurately reproduces SI MEG mu rhythms, containing alpha (7-14 Hz) and beta (15-30 Hz) components, and evoked responses. Analyses of MEG data revealed a significant increase in prestimulus mu power in SI, driven predominately by greater mu-beta dominance, and a larger and delayed M70 peak in the SI evoked response in MA. Previous analysis with our computational model showed that the SI mu rhythm could be reproduced with a stochastic sequence of rhythmic approximately 10 Hz feedforward (FF) input to the granular layers of SI (representative of lemniscal thalamic input) followed nearly simultaneously by approximately 10 Hz feedback (FB) input to the supragranular layers (representative of input from high order cortical or non-specific thalamic sources) (Jones et al., 2009). In the present study, the model further predicted that the rhythmic FF and FB inputs become stronger with age. Further, the FB input is predicted to arrive more synchronously to SI on each cycle of the 10 Hz input in MA. The simulated neurophysiological changes are sufficient to account for the age-related differences in both prestimulus mu rhythms and evoked responses. Thus, the model predicts that a single set of neurophysiological changes intimately links these age-related changes in neural dynamics.

Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses.

Variations in cortical oscillations in the alpha (7-14 Hz) and beta (15-29 Hz) range have been correlated with attention, working memory, and stimulus detection. The mu rhythm recorded with magnetoencephalography (MEG) is a prominent oscillation generated by Rolandic cortex containing alpha and beta bands. Despite its prominence, the neural mechanisms regulating mu are unknown. We characterized the ongoing MEG mu rhythm from a localized source in the finger representation of primary somatosensory (SI) cortex. Subjects showed variation in the relative expression of mu-alpha or mu-beta, which were nonoverlapping for roughly 50% of their respective durations on single trials. To delineate the origins of this rhythm, a biophysically principled computational neural model of SI was developed, with distinct laminae, inhibitory and excitatory neurons, and feedforward (FF, representative of lemniscal thalamic drive) and feedback (FB, representative of higher-order cortical drive or input from nonlemniscal thalamic nuclei) inputs defined by the laminar location of their postsynaptic effects. The mu-alpha component was accurately modeled by rhythmic FF input at approximately 10-Hz. The mu-beta component was accurately modeled by the addition of approximately 10-Hz FB input that was nearly synchronous with the FF input. The relative dominance of these two frequencies depended on the delay between FF and FB drives, their relative input strengths, and stochastic changes in these variables. The model also reproduced key features of the impact of high prestimulus mu power on peaks in SI-evoked activity. For stimuli presented during high mu power, the model predicted enhancement in an initial evoked peak and decreased subsequent deflections. In agreement, the MEG-evoked responses showed an enhanced initial peak and a trend to smaller subsequent peaks. These data provide new information on the dynamics of the mu rhythm in humans and the model provides a novel mechanistic interpretation of this rhythm and its functional significance.

Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study.

Previous reports conflict as to the role of primary somatosensory neocortex (SI) in tactile detection. We addressed this question in normal human subjects using whole-head magnetoencephalography (MEG) recording. We found that the evoked signal (0-175 ms) showed a prominent equivalent current dipole that localized to the anterior bank of the postcentral gyrus, area 3b of SI. The magnitude and timing of peaks in the SI waveform were stimulus amplitude dependent and predicted perception beginning at approximately 70 ms after stimulus. To make a direct and principled connection between the SI waveform and underlying neural dynamics, we developed a biophysically realistic computational SI model that contained excitatory and inhibitory neurons in supragranular and infragranular layers. The SI evoked response was successfully reproduced from the intracellular currents in pyramidal neurons driven by a sequence of lamina-specific excitatory input, consisting of output from the granular layer (approximately 25 ms), exogenous input to the supragranular layers (approximately 70 ms), and a second wave of granular output (approximately 135 ms). The model also predicted that SI correlates of perception reflect stronger and shorter-latency supragranular and late granular drive during perceived trials. These findings strongly support the view that signatures of tactile detection are present in human SI and are mediated by local neural dynamics induced by lamina-specific synaptic drive. Furthermore, our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception.