Interactions between circuit architecture and plasticity in a closed-loop cerebellar system.

Determining the sites and directions of plasticity underlying changes in neural activity and behavior is critical for understanding mechanisms of learning. Identifying such plasticity from neural recording data can be challenging due to feedback pathways that impede reasoning about cause and effect. We studied interactions between feedback, neural activity, and plasticity in the context of a closed-loop motor learning task for which there is disagreement about the loci and directions of plasticity: vestibulo-ocular reflex learning. We constructed a set of circuit models that differed in the strength of their recurrent feedback, from no feedback to very strong feedback. Despite these differences, each model successfully fit a large set of neural and behavioral data. However, the patterns of plasticity predicted by the models fundamentally differed, with the direction of plasticity at a key site changing from depression to potentiation as feedback strength increased. Guided by our analysis, we suggest how such models can be experimentally disambiguated. Our results address a long-standing debate regarding cerebellum-dependent motor learning, suggesting a reconciliation in which learning-related changes in the strength of synaptic inputs to Purkinje cells are compatible with seemingly oppositely directed changes in Purkinje cell spiking activity. More broadly, these results demonstrate how changes in neural activity over learning can appear to contradict the sign of the underlying plasticity when either internal feedback or feedback through the environment is present.

Cerebellar Purkinje cells control eye movements with a rapid rate code that is invariant to spike irregularity.

The rate and temporal pattern of neural spiking each have the potential to influence computation. In the cerebellum, it has been hypothesized that the irregularity of interspike intervals in Purkinje cells affects their ability to transmit information to downstream neurons. Accordingly, during oculomotor behavior in mice and rhesus monkeys, mean irregularity of Purkinje cell spiking varied with mean eye velocity. However, moment-to-moment variations revealed a tight correlation between eye velocity and spike rate, with no additional information conveyed by spike irregularity. Moreover, when spike rate and irregularity were independently controlled using optogenetic stimulation, the eye movements elicited were well-described by a linear population rate code with 3-5 ms temporal precision. Biophysical and random-walk models identified biologically realistic parameter ranges that determine whether spike irregularity influences responses downstream. The results demonstrate cerebellar control of movements through a remarkably rapid rate code, with no evidence for an additional contribution of spike irregularity.

Magnetic eye tracking in mice.

Eye movements provide insights about a wide range of brain functions, from sensorimotor integration to cognition; hence, the measurement of eye movements is an important tool in neuroscience research. We describe a method, based on magnetic sensing, for measuring eye movements in head-fixed and freely moving mice. A small magnet was surgically implanted on the eye, and changes in the magnet angle as the eye rotated were detected by a magnetic field sensor. Systematic testing demonstrated high resolution measurements of eye position of <0.1°. Magnetic eye tracking offers several advantages over the well-established eye coil and video-oculography methods. Most notably, it provides the first method for reliable, high-resolution measurement of eye movements in freely moving mice, revealing increased eye movements and altered binocular coordination compared to head-fixed mice. Overall, magnetic eye tracking provides a lightweight, inexpensive, easily implemented, and high-resolution method suitable for a wide range of applications.

Timing Rules for Synaptic Plasticity Matched to Behavioral Function.

It is widely assumed that the complexity of neural circuits enables them to implement diverse learning tasks using just a few generic forms of synaptic plasticity. In contrast, we report that synaptic plasticity can itself be precisely tuned to the requirements of a learning task. We found that the rules for induction of long-term and single-trial plasticity at parallel fiber-to-Purkinje cell synapses vary across cerebellar regions. In the flocculus, associative plasticity in vitro and in vivo is narrowly tuned for an interval of ∼120 ms, which compensates for the specific processing delay for error signals to reach the flocculus during oculomotor learning. In the vermis, which supports a range of behavioral functions, plasticity is induced by a range of intervals, with individual cells tuned for different intervals. Thus, plasticity at a single, anatomically defined type of synapse can have properties that vary in a way that is precisely matched to function.

Growth and splitting of neural sequences in songbird vocal development.

Neural sequences are a fundamental feature of brain dynamics underlying diverse behaviours, but the mechanisms by which they develop during learning remain unknown. Songbirds learn vocalizations composed of syllables; in adult birds, each syllable is produced by a different sequence of action potential bursts in the premotor cortical area HVC. Here we carried out recordings of large populations of HVC neurons in singing juvenile birds throughout learning to examine the emergence of neural sequences. Early in vocal development, HVC neurons begin producing rhythmic bursts, temporally locked to a 'prototype' syllable. Different neurons are active at different latencies relative to syllable onset to form a continuous sequence. Through development, as new syllables emerge from the prototype syllable, initially highly overlapping burst sequences become increasingly distinct. We propose a mechanistic model in which multiple neural sequences can emerge from the growth and splitting of a common precursor sequence.

Gating of neural error signals during motor learning.

Cerebellar climbing fiber activity encodes performance errors during many motor learning tasks, but the role of these error signals in learning has been controversial. We compared two motor learning paradigms that elicited equally robust putative error signals in the same climbing fibers: learned increases and decreases in the gain of the vestibulo-ocular reflex (VOR). During VOR-increase training, climbing fiber activity on one trial predicted changes in cerebellar output on the next trial, and optogenetic activation of climbing fibers to mimic their encoding of performance errors was sufficient to implant a motor memory. In contrast, during VOR-decrease training, there was no trial-by-trial correlation between climbing fiber activity and changes in cerebellar output, and climbing fiber activation did not induce VOR-decrease learning. Our data suggest that the ability of climbing fibers to induce plasticity can be dynamically gated in vivo, even under conditions where climbing fibers are robustly activated by performance errors. DOI: http://dx.doi.org/10.7554/eLife.02076.001.

MRI-coupled fluorescence tomography quantifies EGFR activity in brain tumors.

RATIONALE AND OBJECTIVES: This report demonstrates the diagnostic potential of magnetic resonance imaging (MRI)-coupled fluorescence molecular tomography (FMT) to determine epidermal growth factor receptor (EGFR) status in brain cancer. MATERIALS AND METHODS: Two orthotopic glioma xenograft models were used in this study: one represented high EGFR expression and the other low expression. Nude mice were inoculated with cells from either one of the tumor lines or were used in a sham surgery control group. Animals were imaged using a unique MRI-FMT scanner 48 hours after intravenous injection of a near-infrared fluorophore bound to epidermal growth factor (EGF) ligand. Coronal images of fluorescence activity of the injected dye in the mouse brain were recovered using the MRI images as anatomical templates. RESULTS: In vivo images of fluorescence activity showed significant differences between animal populations, an observation confirmed by receiver operating characteristic analysis that revealed 100% sensitivity and specificity between animal groups implanted with EGFR((+)) and EGFR((-)) tumor lines. Similar performance was observed between EGFR((+)) and sham surgery control animals. CONCLUSIONS: This preclinical study suggests that MRI-FMT with fluorescent EGF provides excellent discrimination between tumors based on EGFR status. Reliable quantification of receptor status using minimally invasive techniques would be an important innovation for investigating new and existing cancer treatments that target these cellular mechanisms in research animals, and may be applied to identify receptor amplification in human brain cancer patients. This study represents the first systematic multianimal validation of receptor-specific imaging using MRI-guided fluorescence tomography.