Change detection in the primate auditory cortex through feedback of prediction error signals.

Although cortical feedback signals are essential for modulating feedforward processing, no feedback error signal across hierarchical cortical areas has been reported. Here, we observed such a signal in the auditory cortex of awake common marmoset during an oddball paradigm to induce auditory duration mismatch negativity. Prediction errors to a deviant tone presentation were generated as offset calcium responses of layer 2/3 neurons in the rostral parabelt (RPB) of higher-order auditory cortex, while responses to non-deviant tones were strongly suppressed. Within several hundred milliseconds, the error signals propagated broadly into layer 1 of the primary auditory cortex (A1) and accumulated locally on top of incoming auditory signals. Blockade of RPB activity prevented deviance detection in A1. Optogenetic activation of RPB following tone presentation nonlinearly enhanced A1 tone response. Thus, the feedback error signal is critical for automatic detection of unpredicted stimuli in physiological auditory processing and may serve as backpropagation-like learning.

Tb3+-doped fluorescent glass for biology.

Optical investigation and manipulation constitute the core of biological experiments. Here, we introduce a new borosilicate glass material that contains the rare-earth ion terbium(III) (Tb3+), which emits green fluorescence upon blue light excitation, similar to green fluorescent protein (GFP), and thus is widely compatible with conventional biological research environments. Micropipettes made of Tb3+-doped glass allowed us to target GFP-labeled cells for single-cell electroporation, single-cell transcriptome analysis (Patch-seq), and patch-clamp recording under real-time fluorescence microscopic control. The glass also exhibited potent third harmonic generation upon infrared laser excitation and was usable for online optical targeting of fluorescently labeled neurons in the in vivo neocortex. Thus, Tb3+-doped glass simplifies many procedures in biological experiments.

Structural dynamics and stability of corticocortical and thalamocortical axon terminals during motor learning.

Synaptic plasticity is the cellular basis of learning and memory. When animals learn a novel motor skill, synaptic modifications are induced in the primary motor cortex (M1), and new postsynaptic dendritic spines relevant to motor memory are formed in the early stage of learning. However, it is poorly understood how presynaptic axonal boutons are formed, eliminated, and maintained during motor learning, and whether long-range corticocortical and thalamocortical axonal boutons show distinct structural changes during learning. In this study, we conducted two-photon imaging of presynaptic boutons of long-range axons in layer 1 (L1) of the mouse M1 during the 7-day learning of an accelerating rotarod task. The training-period-averaged rate of formation of boutons on axons projecting from the secondary motor cortical area increased, while the average rate of elimination of those from the motor thalamus (thalamic boutons) decreased. In particular, the elimination rate of thalamic boutons during days 4-7 was lower than that in untrained mice, and the fraction of pre-existing thalamic boutons that survived until day 7 was higher than that in untrained mice. Our results suggest that the late stabilization of thalamic boutons in M1 contributes to motor skill learning.

Common marmoset as a model primate for study of the motor control system.

The common marmoset (Callithrix jacchus), a New World monkey, is emerging as a promising animal model for biomedical and neuroscience research. This species shares its basic brain architecture, including the organization of the motor cortical areas and the connections between these and other areas, with humans and other primates. Its small and lissencephalic cerebral cortex is suitable for the application of modern biological techniques. Optogenetic stimulation of the motor cortex induces forelimb movements, and two-photon calcium imaging allows detection of forelimb movement-related activity in multiple motor cortical neurons. The common marmoset also has a large repertoire of forelimb-related behaviors and vocal communications. Thus, the common marmoset is a good model for research into voluntary forelimb movements, social behaviors, and their dysfunctions.

Arm movements induced by noninvasive optogenetic stimulation of the motor cortex in the common marmoset.

Optogenetics is now a fundamental tool for investigating the relationship between neuronal activity and behavior. However, its application to the investigation of motor control systems in nonhuman primates is rather limited, because optogenetic stimulation of cortical neurons in nonhuman primates has failed to induce or modulate any hand/arm movements. Here, we used a tetracycline-inducible gene expression system carrying CaMKII promoter and the gene encoding a Channelrhodopsin-2 variant with fast kinetics in the common marmoset, a small New World monkey. In an awake state, forelimb movements could be induced when Channelrhodopsin-2-expressing neurons in the motor cortex were illuminated by blue laser light with a spot diameter of 1 mm or 2 mm through a cranial window without cortical invasion. Forelimb muscles responded 10 ms to 50 ms after photostimulation onset. Long-duration (500 ms) photostimulation induced discrete forelimb movements that could be markerlessly tracked with charge-coupled device cameras and a deep learning algorithm. Long-duration photostimulation mapping revealed that the primary motor cortex is divided into multiple domains that can induce hand and elbow movements in different directions. During performance of a forelimb movement task, movement trajectories were modulated by weak photostimulation, which did not induce visible forelimb movements at rest, around the onset of task-relevant movement. The modulation was biased toward the movement direction induced by the strong photostimulation. Combined with calcium imaging, all-optical interrogation of motor circuits should be possible in behaving marmosets.

Two-photon imaging of neuronal activity in motor cortex of marmosets during upper-limb movement tasks.

Two-photon imaging in behaving animals has revealed neuronal activities related to behavioral and cognitive function at single-cell resolution. However, marmosets have posed a challenge due to limited success in training on motor tasks. Here we report the development of protocols to train head-fixed common marmosets to perform upper-limb movement tasks and simultaneously perform two-photon imaging. After 2-5 months of training sessions, head-fixed marmosets can control a manipulandum to move a cursor to a target on a screen. We conduct two-photon calcium imaging of layer 2/3 neurons in the motor cortex during this motor task performance, and detect task-relevant activity from multiple neurons at cellular and subcellular resolutions. In a two-target reaching task, some neurons show direction-selective activity over the training days. In a short-term force-field adaptation task, some neurons change their activity when the force field is on. Two-photon calcium imaging in behaving marmosets may become a fundamental technique for determining the spatial organization of the cortical dynamics underlying action and cognition.

Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers.

Efficient and rapid prediction of domain regions from amino acid sequence information alone is often required for swift structural and functional characterization of large multi-domain proteins. Here we introduce Fast H-DROP, a thirty times accelerated version of our previously reported H-DROP (Helical Domain linker pRediction using OPtimal features), which is unique in specifically predicting helical domain linkers (boundaries). Fast H-DROP, analogously to H-DROP, uses optimum features selected from a set of 3000 ones by combining a random forest and a stepwise feature selection protocol. We reduced the computational time from 8.5 min per sequence in H-DROP to 14 s per sequence in Fast H-DROP on an 8 Xeon processor Linux server by using SWISS-PROT instead of Genbank non-redundant (nr) database for generating the PSSMs. The sensitivity and precision of Fast H-DROP assessed by cross-validation were 33.7 and 36.2%, which were merely ~2% lower than that of H-DROP. The reduced computational time of Fast H-DROP, without affecting prediction performances, makes it more interactive and user-friendly. Fast H-DROP and H-DROP are freely available from http://domserv.lab.tuat.ac.jp/ .

3D clustering of GABAergic neurons enhances inhibitory actions on excitatory neurons in the mouse visual cortex.

Neocortical neurons with similar functional properties assemble into spatially coherent circuits, but it remains unclear how inhibitory interneurons are organized. We applied in vivo two-photon functional Ca(2+) imaging and whole-cell recording of synaptic currents to record visual responses of cortical neurons and analyzed their spatial arrangements. GABAergic interneurons were clustered in the 3D space of the mouse visual cortex, and excitatory neurons located within the clusters (insiders) had a lower amplitude and sharper orientation tuning of visual responses than outsiders. Inhibitory synaptic currents recorded from the insiders were larger than those of the outsiders. Single, isolated interneurons did not show such a location-tuning/amplitude relationship. The two principal subtypes of interneurons, parvalbumin- and somatostatin-expressing neurons, also formed clusters with only slightly overlapping each other and exhibited a different location-tuning relationship. These findings suggest that GABAergic interneurons and their subgroups form clusters to make their inhibitory function more effective than isolated interneurons.

Curtailing effect of awakening on visual responses of cortical neurons by cholinergic activation of inhibitory circuits.

Visual responsiveness of cortical neurons changes depending on the brain state. Neural circuit mechanism underlying this change is unclear. By applying the method of in vivo two-photon functional calcium imaging to transgenic rats in which GABAergic neurons express fluorescent protein, we analyzed changes in visual response properties of cortical neurons when animals became awakened from anesthesia. In the awake state, the magnitude and reliability of visual responses of GABAergic neurons increased whereas the decay of responses of excitatory neurons became faster. To test whether the basal forebrain (BF) cholinergic projection is involved in these changes, we analyzed effects of electrical and optogenetic activation of BF on visual responses of mouse cortical neurons with in vivo imaging and whole-cell recordings. Electrical BF stimulation in anesthetized animals induced the same direction of changes in visual responses of both groups of neurons as awakening. Optogenetic activation increased the frequency of visually evoked action potentials in GABAergic neurons but induced the delayed hyperpolarization that ceased the late generation of action potentials in excitatory neurons. Pharmacological analysis in slice preparations revealed that photoactivation-induced depolarization of layer 1 GABAergic neurons was blocked by a nicotinic receptor antagonist, whereas non-fast-spiking layer 2/3 GABAergic neurons was blocked only by the application of both nicotinic and muscarinic receptor antagonists. These results suggest that the effect of awakening is mediated mainly through nicotinic activation of layer 1 GABAergic neurons and mixed nicotinic/muscarinic activation of layer 2/3 non-fast-spiking GABAergic neurons, which together curtails the visual responses of excitatory neurons.

H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection.

Domain linker prediction is attracting much interest as it can help identifying novel domains suitable for high throughput proteomics analysis. Here, we report H-DROP, an SVM-based Helical Domain linker pRediction using OPtimal features. H-DROP is, to the best of our knowledge, the first predictor for specifically and effectively identifying helical linkers. This was made possible first because a large training dataset became available from IS-Dom, and second because we selected a small number of optimal features from a huge number of potential ones. The training helical linker dataset, which included 261 helical linkers, was constructed by detecting helical residues at the boundary regions of two independent structural domains listed in our previously reported IS-Dom dataset. 45 optimal feature candidates were selected from 3,000 features by random forest, which were further reduced to 26 optimal features by stepwise selection. The prediction sensitivity and precision of H-DROP were 35.2 and 38.8%, respectively. These values were over 10.7% higher than those of control methods including our previously developed DROP, which is a coil linker predictor, and PPRODO, which is trained with un-differentiated domain boundary sequences. Overall, these results indicated that helical linkers can be predicted from sequence information alone by using a strictly curated training data set for helical linkers and carefully selected set of optimal features. H-DROP is available at http://domserv.lab.tuat.ac.jp.

IS-Dom: a dataset of independent structural domains automatically delineated from protein structures.

Protein domains that can fold in isolation are significant targets in diverse area of proteomics research as they are often readily analyzed by high-throughput methods. Here, we report IS-Dom, a dataset of Independent Structural Domains (ISDs) that are most likely to fold in isolation. IS-Dom was constructed by filtering domains from SCOP, CATH, and DomainParser using quantitative structural measures, which were calculated by estimating inter-domain hydrophobic clusters and hydrogen bonds from the full length protein's atomic coordinates. The ISD detection protocol is fully automated, and all of the computed interactions are stored in the server which enables rapid update of IS-Dom. We also prepared a standard IS-Dom using parameters optimized by maximizing the Youden's index. The standard IS-Dom, contained 54,860 ISDs, of which 25.5 % had high sequence identity and termini overlap with a Protein Data Bank (PDB) cataloged sequence and are thus experimentally shown to fold in isolation [coined autonomously folded domain (AFDs)]. Furthermore, our ISD detection protocol missed less than 10 % of the AFDs, which corroborated our protocol's ability to define structural domains that are able to fold independently. IS-Dom is available through the web server ( http://domserv.lab.tuat.ac.jp/IS-Dom.html ), and users can either, download the standard IS-Dom dataset, construct their own IS-Dom by interactively varying the parameters, or assess the structural independence of newly defined putative domains.

DROP: an SVM domain linker predictor trained with optimal features selected by random forest.

MOTIVATION: Biologically important proteins are often large, multidomain proteins, which are difficult to characterize by high-throughput experimental methods. Efficient domain/boundary predictions are thus increasingly required in diverse area of proteomics research for computationally dissecting proteins into readily analyzable domains. RESULTS: We constructed a support vector machine (SVM)-based domain linker predictor, DROP (Domain linker pRediction using OPtimal features), which was trained with 25 optimal features. The optimal combination of features was identified from a set of 3000 features using a random forest algorithm complemented with a stepwise feature selection. DROP demonstrated a prediction sensitivity and precision of 41.3 and 49.4%, respectively. These values were over 19.9% higher than those of control SVM predictors trained with non-optimized features, strongly suggesting the efficiency of our feature selection method. In addition, the mean NDO-Score of DROP for predicting novel domains in seven CASP8 FM multidomain proteins was 0.760, which was higher than any of the 12 published CASP8 DP servers. Overall, these results indicate that the SVM prediction of domain linkers can be improved by identifying optimal features that best distinguish linker from non-linker regions.

Difference in binocularity and ocular dominance plasticity between GABAergic and excitatory cortical neurons.

Neuronal circuits in the cerebral cortex consist mainly of glutamatergic/excitatory and GABAergic/inhibitory neurons. In the visual cortex, the binocular responsiveness of neurons is modified by monocular visual deprivation during the critical period of postnatal development. Although GABAergic neurons are considered to play a key role in the expression of the critical period, it is not known whether their binocular responsiveness and ocular dominance plasticity are different from those of excitatory neurons. Recently, the end of the critical period was found to be not strict so that cortical neurons in the adult still have some ocular dominance plasticity. It is not known, however, which type of neurons or both maintain such plasticity in adulthood. To address these issues, we applied in vivo two-photon functional Ca(2+) imaging to transgenic mice whose GABAergic neurons express a yellow fluorescent protein called Venus. We found that GABAergic neurons are more binocular than excitatory neurons in the normal visual cortex, and both types of neurons show the same degree of modifiability to monocular visual deprivation during the critical period, but the modifiability of GABAergic neurons is stronger than that of excitatory neurons after the end of the critical period.

Loop-length-dependent SVM prediction of domain linkers for high-throughput structural proteomics.

The prediction of structural domains in novel protein sequences is becoming of practical importance. One important area of application is the development of computer-aided techniques for identifying, at a low cost, novel protein domain targets for large-scale functional and structural proteomics. Here, we report a loop-length-dependent support vector machine (SVM) prediction of domain linkers, which are loops separating two structural domains. (DLP-SVM is freely available at: http://www.tuat.ac.jp/ approximately domserv/cgi-bin/DLP-SVM.cgi.) We constructed three loop-length-dependent SVM predictors of domain linkers (SVM-All, SVM-Long and SVM-Short), and also built SVM-Joint, which combines the results of SVM-Short and SVM-Long into a single consolidated prediction. The performances of SVM-Joint were, in most aspects, the highest, with a sensitivity of 59.7% and a specificity of 43.6%, which indicated that the specificity and the sensitivity were improved by over 2 and 3% respectively, when loop-length-dependent characteristics were taken into account. Furthermore, the sensitivity and specificity of SVM-Joint were, respectively, 37.6 and 17.4% higher than those of a random guess, and also superior to those of previously reported domain linker predictors. These results indicate that SVMs can be used to predict domain linkers, and that loop-length-dependent characteristics are useful for improving SVM prediction performances.

Mutational analysis of protein solubility enhancement using short peptide tags.

Protein aggregation is a common phenomenon. The preparation of highly concentrated protein samples, typically required for biophysical measurements, often involves a time consuming and tedious testing of solvent conditions for improving protein solubility. Here, in a systematic analysis, we have determined the increase in solubility upon the addition of SEP-tags (solubility enhancement peptide tags) containing, one, three, and five lysines or arginines (or six arginines) to either the N or C terminus of our low solubility model protein, bovine pancreatic trypsin inhibitor variant, BPTI-22 (a BPTI variant containing 22 alanines). As anticipated, the BPTI-22 solubility increased in direct relation to the number of charged residues contained in the SEP-tag, and without altering either the activity or the structure of the protein. The largest solubility increases were of 4.2-, 4.8-, and 6.2-folds produced by the addition, at the C terminus, of five lysine (BPTI-22-C5K), five and six arginine residues (BPTI-22-C5R and BPTI-22-C6R), respectively. The increased solubility of the tagged BPTI-22 yielded higher quality NMR spectra (hetero single quantum correlation HSQC spectra; with respect of the signal-to-noise and line shapes) in a much shorter time than for the untagged BPTI-22. Furthermore, tagged samples remained soluble for over ten days, as observed by their HSQC spectra. We believe that lysine- and arginine-based SEP-tags may provide an effective and versatile method for enhancing protein solubility.