Simple spike patterns and synaptic mechanisms encoding sensory and motor signals in Purkinje cells and the cerebellar nuclei

Whisker stimulation in awake mice evokes transient suppression of simple spike probability in crus I/II Purkinje cells. Here, we investigated how simple spike suppression arises synaptically, what it encodes, and how it affects cerebellar output. In vitro, monosynaptic parallel fiber (PF)-excitatory postsynaptic currents (EPSCs) facilitated strongly, whereas disynaptic inhibitory postsynaptic currents (IPSCs) remained stable, maximizing relative inhibitory strength at the onset of PF activity. Short-term plasticity thus favors the inhibition of Purkinje spikes before PFs facilitate. In vivo, whisker stimulation evoked a 2-6 ms synchronous spike suppression, just 6-8 ms (∼4 synaptic delays) after sensory onset, whereas active whisker movements elicited broadly timed spike rate increases that did not modulate sensory-evoked suppression. Firing in the cerebellar nuclei (CbN) inversely correlated with disinhibition from sensory-evoked simple spike suppressions but was decoupled from slow, non-synchronous movement-associated elevations of Purkinje firing rates. Synchrony thus allows the CbN to high-pass filter Purkinje inputs, facilitating sensory-evoked cerebellar outputs that can drive movements.

A review of the reproductive biology of mormyroid fishes: An emerging model for biomedical research

Mormyroidea is a superfamily of weakly electric African fishes with great potential as a model in a variety of biomedical research areas including systems neuroscience, muscle cell and craniofacial development, ion channel biophysics, and flagellar/ciliary biology. However, they are currently difficult to breed in the laboratory setting, which is essential for any tractable model organism. As such, there is a need to better understand the reproductive biology of mormyroids to breed them more reliably in the laboratory to effectively use them as a biomedical research model. This review seeks to (1) briefly highlight the biomedically relevant phenotypes of mormyroids and (2) compile information about mormyroid reproduction including sex differences, breeding season, sexual maturity, gonads, gametes, and courtship/spawning behaviors. We also highlight areas of mormyroid reproductive biology that are currently unexplored and/or have the potential for further investigation that may provide insights into more successful mormyroid laboratory breeding methods.

Cerebellum Lecture: the Cerebellar Nuclei-Core of the Cerebellum

The cerebellum is a key player in many brain functions and a major topic of neuroscience research. However, the cerebellar nuclei (CN), the main output structures of the cerebellum, are often overlooked. This neglect is because research on the cerebellum typically focuses on the cortex and tends to treat the CN as relatively simple output nuclei conveying an inverted signal from the cerebellar cortex to the rest of the brain. In this review, by adopting a nucleocentric perspective we aim to rectify this impression. First, we describe CN anatomy and modularity and comprehensively integrate CN architecture with its highly organized but complex afferent and efferent connectivity. This is followed by a novel classification of the specific neuronal classes the CN comprise and speculate on the implications of CN structure and physiology for our understanding of adult cerebellar function. Based on this thorough review of the adult literature we provide a comprehensive overview of CN embryonic development and, by comparing cerebellar structures in various chordate clades, propose an interpretation of CN evolution. Despite their critical importance in cerebellar function, from a clinical perspective intriguingly few, if any, neurological disorders appear to primarily affect the CN. To highlight this curious anomaly, and encourage future nucleocentric interpretations, we build on our review to provide a brief overview of the various syndromes in which the CN are currently implicated. Finally, we summarize the specific perspectives that a nucleocentric view of the cerebellum brings, move major outstanding issues in CN biology to the limelight, and provide a roadmap to the key questions that need to be answered in order to create a comprehensive integrated model of CN structure, function, development, and evolution.

Collective sensing in electric fish

A number of organisms, including dolphins, bats and electric fish, possess sophisticated active sensory systems that use self-generated signals (for example, acoustic or electrical emissions) to probe the environment1,2. Studies of active sensing in social groups have typically focused on strategies for minimizing interference from conspecific emissions2-4. However, it is well known from engineering that multiple spatially distributed emitters and receivers can greatly enhance environmental sensing (for example, multistatic radar and sonar)5-8. Here we provide evidence from modelling, neural recordings and behavioural experiments that the African weakly electric fish Gnathonemus petersii utilizes the electrical pulses of conspecifics to extend its electrolocation range, discriminate objects and increase information transmission. These results provide evidence for a new, collective mode of active sensing in which individual perception is enhanced by the energy emissions of nearby group members.

Sensorimotor content of multi-unit activity recorded in the paramedian lobule of the cerebellum using carbon fiber microelectrode arrays

The cerebellum takes in a great deal of sensory information from the periphery and descending signals from the cerebral cortices. It has been debated whether the paramedian lobule (PML) in the rat and its paravermal regions that project to the interpositus nucleus (IPN) are primarily involved in motor execution or motor planning. Studies that have relied on single spike recordings in behaving animals have led to conflicting conclusions regarding this issue. In this study, we tried a different approach and investigated the correlation of field potentials and multi-unit signals recorded with multi-electrode arrays from the PML cortex along with the forelimb electromyography (EMG) signals in rats during behavior. Linear regression was performed to predict the EMG signal envelopes using the PML activity for various time shifts (±25, ±50, ±100, and ± 400 ms) between the two signals to determine a causal relation. The highest correlations (~0.5 on average) between the neural and EMG envelopes were observed for zero and small (±25 ms) time shifts and decreased with larger time shifts in both directions, suggesting that paravermal PML is involved both in processing of sensory signals and motor execution in the context of forelimb reaching behavior. EMG envelopes were predicted with higher success rates when neural signals from multiple phases of the behavior were utilized for regression. The forelimb extension phase was the most difficult to predict while the releasing of the bar phase prediction was the most successful. The high frequency (>300 Hz) components of the neural signal, reflecting multi-unit activity, had a higher contribution to the EMG prediction than did the lower frequency components, corresponding to local field potentials. The results of this study suggest that the paravermal PML in the rat cerebellum is primarily involved in the execution of forelimb movements rather than the planning aspect and that the PML is more active at the initiation and termination of the behavior, rather than the progression.

Auditory Corticofugal Neurons Transmit Auditory and Non-auditory Information During Behavior

Layer 5 pyramidal neurons of sensory cortices project "corticofugal" axons to myriad sub-cortical targets, thereby broadcasting high-level signals important for perception and learning. Recent studies suggest dendritic Ca2+ spikes as key biophysical mechanisms supporting corticofugal neuron function: these long-lasting events drive burst firing, thereby initiating uniquely powerful signals to modulate sub-cortical representations and trigger learning-related plasticity. However, the behavioral relevance of corticofugal dendritic spikes is poorly understood. We shed light on this issue using 2-photon Ca2+ imaging of auditory corticofugal dendrites as mice of either sex engage in a GO/NO-GO sound-discrimination task. Unexpectedly, only a minority of dendritic spikes were triggered by behaviorally relevant sounds under our conditions. Task related dendritic activity instead mostly followed sound cue termination and co-occurred with mice's instrumental licking during the answer period of behavioral trials, irrespective of reward consumption. Temporally selective, optogenetic silencing of corticofugal neurons during the trial answer period impaired auditory discrimination learning. Thus, auditory corticofugal systems' contribution to learning and plasticity may be partially nonsensory in nature.

Predictive neural computations in the cerebellum contribute to motor planning and faster behavioral responses in larval zebrafish

The ability to predict the future based on past experience lies at the core of the brain's ability to adapt behavior. However, the neural mechanisms that participate in generating and updating predictions are not clearly understood. Further, the evolutionary antecedents and the prevalence of predictive processing among vertebrates are even less explored. Here, we show evidence of predictive processing via the involvement of cerebellar circuits in larval zebrafish. We presented stereotyped optic flow stimuli to larval zebrafish to evoke swims and discovered that lesioning the cerebellum abolished prediction-dependent modulation of swim latency. When expectations of optic flow direction did not match with reality, error signals arrive at Purkinje cells via the olivary climbing fibers, whereas granule cells and Purkinje cells encode signals of expectation. Strong neural representations of expectation correlate with faster swim responses and vice versa. In sum, our results show evidence for predictive processing in nonmammalian vertebrates with the involvement of cerebellum, an evolutionarily conserved brain structure.

A synaptic corollary discharge signal suppresses midbrain visual processing during saccade-like locomotion

In motor control, the brain not only sends motor commands to the periphery, but also generates concurrent internal signals known as corollary discharge (CD) that influence sensory information processing around the time of movement. CD signals are important for identifying sensory input arising from self-motion and to compensate for it, but the underlying mechanisms remain unclear. Using whole-cell patch clamp recordings from neurons in the zebrafish optic tectum, we discovered an inhibitory synaptic signal, temporally locked to spontaneous and visually driven locomotion. This motor-related inhibition was appropriately timed to counteract visually driven excitatory input arising from the fish's own motion, and transiently suppressed tectal spiking activity. High-resolution calcium imaging revealed localized motor-related signals in the tectal neuropil and the upstream torus longitudinalis, suggesting that CD enters the tectum via this pathway. Together, our results show how visual processing is suppressed during self-motion by motor-related phasic inhibition. This may help explain perceptual saccadic suppression observed in many species.

Internal feedback in the cortical perception-action loop enables fast and accurate behavior

Animals move smoothly and reliably in unpredictable environments. Models of sensorimotor control, drawing on control theory, have assumed that sensory information from the environment leads to actions, which then act back on the environment, creating a single, unidirectional perception-action loop. However, the sensorimotor loop contains internal delays in sensory and motor pathways, which can lead to unstable control. We show here that these delays can be compensated by internal feedback signals that flow backward, from motor toward sensory areas. This internal feedback is ubiquitous in neural sensorimotor systems, and we show how internal feedback compensates internal delays. This is accomplished by filtering out self-generated and other predictable changes so that unpredicted, actionable information can be rapidly transmitted toward action by the fastest components, effectively compressing the sensory input to more efficiently use feedforward pathways: Tracts of fast, giant neurons necessarily convey less accurate signals than tracts with many smaller neurons, but they are crucial for fast and accurate behavior. We use a mathematically tractable control model to show that internal feedback has an indispensable role in achieving state estimation, localization of function (how different parts of the cortex control different parts of the body), and attention, all of which are crucial for effective sensorimotor control. This control model can explain anatomical, physiological, and behavioral observations, including motor signals in the visual cortex, heterogeneous kinetics of sensory receptors, and the presence of giant cells in the cortex of humans as well as internal feedback patterns and unexplained heterogeneity in neural systems.

Collective Sensing in Electric Fish

A number of organisms, including dolphins, bats, and electric fish, possess sophisticated active sensory systems that use self-generated signals (e.g. acoustic or electrical emissions) to probe the environment1,2. Studies of active sensing in social groups have typically focused on strategies for minimizing interference from conspecific emissions2-4. However, it is well-known from engineering that multiple spatially distributed emitters and receivers can greatly enhance environmental sensing (e.g. multistatic radar and sonar)5-8. Here we provide evidence from modeling, neural recordings, and behavioral experiments that the African weakly electric fish Gnathonemus petersii utilizes the electrical pulses of conspecifics to extend electrolocation range, discriminate objects, and increase information transmission. These results suggest a novel, collective mode of active sensing in which individual perception is enhanced by the energy emissions of nearby group members.

Task-dependent optimal representations for cerebellar learning

The cerebellar granule cell layer has inspired numerous theoretical models of neural representations that support learned behaviors, beginning with the work of Marr and Albus. In these models, granule cells form a sparse, combinatorial encoding of diverse sensorimotor inputs. Such sparse representations are optimal for learning to discriminate random stimuli. However, recent observations of dense, low-dimensional activity across granule cells have called into question the role of sparse coding in these neurons. Here, we generalize theories of cerebellar learning to determine the optimal granule cell representation for tasks beyond random stimulus discrimination, including continuous input-output transformations as required for smooth motor control. We show that for such tasks, the optimal granule cell representation is substantially denser than predicted by classical theories. Our results provide a general theory of learning in cerebellum-like systems and suggest that optimal cerebellar representations are task-dependent.

Optimal routing to cerebellum-like structures

The vast expansion from mossy fibers to cerebellar granule cells (GrC) produces a neural representation that supports functions including associative and internal model learning. This motif is shared by other cerebellum-like structures and has inspired numerous theoretical models. Less attention has been paid to structures immediately presynaptic to GrC layers, whose architecture can be described as a 'bottleneck' and whose function is not understood. We therefore develop a theory of cerebellum-like structures in conjunction with their afferent pathways that predicts the role of the pontine relay to cerebellum and the glomerular organization of the insect antennal lobe. We highlight a new computational distinction between clustered and distributed neuronal representations that is reflected in the anatomy of these two brain structures. Our theory also reconciles recent observations of correlated GrC activity with theories of nonlinear mixing. More generally, it shows that structured compression followed by random expansion is an efficient architecture for flexible computation.

An internal model for canceling self-generated sensory input in freely behaving electric fish

Internal models that predict the sensory consequences of motor actions are vital for sensory, motor, and cognitive functions. However, the relationship between motor action and sensory input is complex, often varying from one moment to another depending on the state of the animal and the environment. The neural mechanisms for generating predictions under such challenging, real-world conditions remain largely unknown. Using novel methods for underwater neural recording, a quantitative analysis of unconstrained behavior, and computational modeling, we provide evidence for an unexpectedly sophisticated internal model at the first stage of active electrosensory processing in mormyrid fish. Closed-loop manipulations reveal that electrosensory lobe neurons are capable of simultaneously learning and storing multiple predictions of the sensory consequences of motor commands specific to different sensory states. These results provide mechanistic insights into how internal motor signals and information about the sensory environment are combined within a cerebellum-like circuitry to predict the sensory consequences of natural behavior.

A mechanism for differential control of axonal and dendritic spiking underlying learning in a cerebellum-like circuit

In addition to the action potentials used for axonal signaling, many neurons generate dendritic "spikes" associated with synaptic plasticity. However, in order to control both plasticity and signaling, synaptic inputs must be able to differentially modulate the firing of these two spike types. Here, we investigate this issue in the electrosensory lobe (ELL) of weakly electric mormyrid fish, where separate control over axonal and dendritic spikes is essential for the transmission of learned predictive signals from inhibitory interneurons to the output stage of the circuit. Through a combination of experimental and modeling studies, we uncover a novel mechanism by which sensory input selectively modulates the rate of dendritic spiking by adjusting the amplitude of backpropagating axonal action potentials. Interestingly, this mechanism does not require spatially segregated synaptic inputs or dendritic compartmentalization but relies instead on an electrotonically distant spike initiation site in the axon-a common biophysical feature of neurons.

The effect of auditory cues on gait variability in people with Parkinson's disease and older adults: a systematic review

Aim: The goal of this study was to analyze the effects of external rhythmic auditory stimulation (RAS) on gait variability in older adults and people with Parkinson's disease (PD). Methods: Academic databases searched included PubMed, Web of Science, PEDro and Cochrane, from inception to September 2021. Eligible articles scored a minimum of 4 on the PEDro scale. Results: Twenty-three papers were included. People with PD show varied responses in gait variability to RAS during cued walking trials. Healthy older adults tended to increase variability during cued trials. Cue rates below preferred walking cadence tend to increase gait variability. Conclusion: Gait variability is closely associated with fall risk and an important consideration in development of gait rehabilitation techniques.

Focusing on the Emerging Role of Kainate Receptors in the Dorsal Cochlear Nucleus (DCN) and Cerebellum

Mammals have a dorsal cochlear nucleus (DCN), which is thought to be a cerebellum-like structure with similar features in terms of structure and microcircuitry to the cerebellum. Both the DCN and cerebellum perform their functions depending on synaptic and neuronal networks mediated by various glutamate receptors. Kainate receptors (KARs) are one class of the glutamate receptor family and are strongly expressed in the hippocampus, the cerebellum, and cerebellum-like structures. The cellular distribution and the potential role of KARs in the hippocampus have been extensively investigated. However, the cellular distribution and the potential role of KARs in cerebellum-like structures, including the DCN and cerebellum, are poorly understood. In this review, we summarize the similarity between the DCN and cerebellum at the levels of structure, circuitry, and cell type as well as the investigations referring to the expression patterns of KARs in the DCN and cerebellum according to previous studies. Recent studies on the role of KARs have shown that KARs mediate a bidirectional modulatory effect at parallel fiber (PF)-Purkinje cell (PC) synapses in the cerebellum, implying insights into their roles in cerebellum-like structures, including the DCN, that remain to be explored in the coming years.

Structured cerebellar connectivity supports resilient pattern separation

The cerebellum is thought to help detect and correct errors between intended and executed commands^1,2 and is critical for social behaviours, cognition and emotion^3-6. Computations for motor control must be performed quickly to correct errors in real time and should be sensitive to small differences between patterns for fine error correction while being resilient to noise⁷. Influential theories of cerebellar information processing have largely assumed random network connectivity, which increases the encoding capacity of the network's first layer^8-13. However, maximizing encoding capacity reduces the resilience to noise⁷. To understand how neuronal circuits address this fundamental trade-off, we mapped the feedforward connectivity in the mouse cerebellar cortex using automated large-scale transmission electron microscopy and convolutional neural network-based image segmentation. We found that both the input and output layers of the circuit exhibit redundant and selective connectivity motifs, which contrast with prevailing models. Numerical simulations suggest that these redundant, non-random connectivity motifs increase the resilience to noise at a negligible cost to the overall encoding capacity. This work reveals how neuronal network structure can support a trade-off between encoding capacity and redundancy, unveiling principles of biological network architecture with implications for the design of artificial neural networks.

Getting the news in milliseconds: The role of early novelty detection in active electrosensory exploration

The pulse emitting weakly electric fish Gymnotus omarorum shows stereotyped "novelty responses" consisting of a transient acceleration of the rhythm of a self-emitted electric organ discharge that carries electrosensory signals. Here we show that rapid increases in electric image amplitude cause a "novelty detection potential" in the first electrosensory relay. This sign precedes and its amplitude predicts, the amplitude of the subsequent behavioral novelty response. Current source density analyses indicates its origin ar the layers of the electrosensory lobe where the main output neurons occur. Two types of units, referred to as "ON" and "OFF". Were recorded there in decerebrated fish. Firing probability of "OFF" units drastically decreased after a stepwise increase in electric image. By contrast, the very first novel stimuli after the increase evoked a sharp peak in firing rate of "ON" units followed by a very fast adaptation phase that contrasted with the slow adaptation observed in previous recordings of primary afferents. The amplitudes of this peak, the novelty detection potential, and the behavioral novelty responses, show the same dependence on the departure of the newest stimulus intensity from the weighted average of preceding ones suggesting that the signals encoded by "ON" neurons underlay the novelty detection potential, propagates through the hierarchical organization of the electromotor control, and finally contribute to accelerate the electric organ discharge rate. This suggests that detecting novelty at the very early processing stage of electrosensory signals is essential to adapt the electrosensory sampling rate to exploration requirements as they change dynamically.

Mobile zinc as a modulator of sensory perception

Mobile zinc is an abundant transition metal ion in the central nervous system, with pools of divalent zinc accumulating in regions of the brain engaged in sensory perception and memory formation. Here, we present essential tools that we developed to interrogate the role(s) of mobile zinc in these processes. Most important are (a) fluorescent sensors that report the presence of mobile zinc and (b) fast, Zn-selective chelating agents for measuring zinc flux in animal tissue and live animals. The results of our studies, conducted in collaboration with neuroscientist experts, are presented for sensory organs involved in hearing, smell, vision, and learning and memory. A general principle emerging from these studies is that the function of mobile zinc in all cases appears to be downregulation of the amplitude of the response following overstimulation of the respective sensory organs. Possible consequences affecting human behavior are presented for future investigations in collaboration with interested behavioral scientists.

Diversity of cellular physiology and morphology of Purkinje cells in the adult zebrafish cerebellum

This study was designed to explore the functional circuitry of the adult zebrafish cerebellum, focusing on its Purkinje cells and using whole-cell patch recordings and single cell labeling in slice preparations. Following physiological characterizations, the recorded single cells were labeled for morphological identification. It was found that the zebrafish Purkinje cells are surprisingly diverse. Based on their physiology and morphology, they can be classified into at least three subtypes: Type I, a narrow spike cell, which fires only narrow Na⁺ spikes (<3 ms in duration), and has a single primary dendrite with an arbor restricted to the distal molecular layer; Type II, a broad spike cell, which fires broad Ca²⁺ spikes (5-7 ms in duration) and has a primary dendrite with limited branching in the inner molecular layer and then further radiates throughout the molecular layer; and Type III, a very broad spike cell, which fires very broad Ca²⁺ spikes (≥10 ms in duration) and has a dense proximal dendritic arbor that is either restricted to the inner molecular layer (Type IIIa), or radiates throughout the entire molecular layer (Type IIIb). The graded paired-pulse facilitation of these Purkinje cells' responses to parallel fiber activations and the all-or-none, paired-pulse depression of climbing fiber activation are largely similar to those reported for mammals. The labeled axon terminals of these Purkinje cells end locally, as reported for larval zebrafish. The present study provides evidence that the corresponding functional circuitry and information processing differ from what has been well-established in the mammalian cerebellum.

Distribution of neurogranin-like immunoreactivity in the brain and sensory organs of the adult zebrafish

We studied the expression of neurogranin in the brain and some sensory organs (barbel taste buds, olfactory organs, and retina) of adult zebrafish. Database analysis shows zebrafish has two paralog neurogranin genes (nrgna and nrgnb) that translate into three peptides with a conserved IQ domain, as in mammals. Western blots of zebrafish brain extracts using an anti-neurogranin antiserum revealed three separate bands, confirming the presence of three neurogranin peptides. Immunohistochemistry shows neurogranin-like expression in the brain and sensory organs (taste buds, neuromasts and olfactory epithelium), not being able to discern its three different peptides. In the retina, the most conspicuous positive cells were bipolar neurons. In the brain, immunopositive neurons were observed in all major regions (pallium, subpallium, preoptic area, hypothalamus, diencephalon, mesencephalon and rhombencephalon, including the cerebellum), a more extended distribution than in mammals. Interestingly, dendrites, cell bodies and axon terminals of some neurons were immunopositive, thus zebrafish neurogranins may play presynaptic and postsynaptic roles. Most positive neurons were found in primary sensory centers (viscerosensory column and medial octavolateral nucleus) and integrative centers (pallium, subpallium, optic tectum and cerebellum), which have complex synaptic circuitry. However, we also observed expression in areas not related to sensory or integrative functions, such as in cerebrospinal fluid-contacting cells associated with the hypothalamic recesses, which exhibited high neurogranin-like immunoreactivity. Together, these results reveal important differences with the patterns reported in mammals, suggesting divergent evolution from the common ancestor.

Evolution of behavioural control from chordates to primates

This article outlines a hypothetical sequence of evolutionary innovations, along the lineage that produced humans, which extended behavioural control from simple feedback loops to sophisticated control of diverse species-typical actions. I begin with basic feedback mechanisms of ancient mobile animals and follow the major niche transitions from aquatic to terrestrial life, the retreat into nocturnality in early mammals, the transition to arboreal life and the return to diurnality. Along the way, I propose a sequence of elaboration and diversification of the behavioural repertoire and associated neuroanatomical substrates. This includes midbrain control of approach versus escape actions, telencephalic control of local versus long-range foraging, detection of affordances by the dorsal pallium, diversified control of nocturnal foraging in the mammalian neocortex and expansion of primate frontal, temporal and parietal cortex to support a wide variety of primate-specific behavioural strategies. The result is a proposed functional architecture consisting of parallel control systems, each dedicated to specifying the affordances for guiding particular species-typical actions, which compete against each other through a hierarchy of selection mechanisms.

This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.

Restoring Shank3 in the rostral brainstem of shank3ab-/- zebrafish autism models rescues sensory deficits

People with Phelan-McDermid Syndrome, caused by mutations in the SHANK3 gene, commonly exhibit reduced responses to sensory stimuli; yet the changes in brain-wide activity that link these symptoms to mutations in the shank3 gene remain unknown. Here we quantify movement in response to sudden darkness in larvae of two shank3 zebrafish mutant models and show that both models exhibit dampened responses to this stimulus. Using brain-wide activity mapping, we find that shank3^−/− light-sensing brain regions show normal levels of activity while sensorimotor integration and motor regions are less active. Specifically restoring Shank3 function in a sensorimotor nucleus of the rostral brainstem enables the shank3^−/− model to respond like wild-type. In sum, we find that reduced sensory responsiveness in shank3^−/− models is associated with reduced activity in sensory processing brain regions and can be rescued by restoring Shank3 function in the rostral brainstem. These studies highlight the importance of Shank3 function in the rostral brainstem for integrating sensory inputs to generate behavioral adaptations to changing sensory stimuli.

Robert Kozol et al. developed two zebrafish Shank3 models to characterize the basis of sensorimotor deficits, which are a consistent feature in SHANK3-deficient human patients (Phelan-McDermid Syndrome). Their results suggest that hindbrain regions require Shank3 for normal responses to light, and provide further insight toward the biology of sensory deficits in Shank3 mutants.

An Integrated Perspective of Evolution and Development: From Genes to Function to Ear, Lateral Line and Electroreception

Four sensory systems (vestibular, lateral line, electroreception, auditory) are unique and project exclusively to the brainstem of vertebrates. All sensory neurons depend on a common set of genes (Eya1, Sox2, Neurog1, Neurod1) that project to a dorsal nucleus and an intermediate nucleus, which differentiate into the vestibular ear, lateral line and electroreception in vertebrates. In tetrapods, a loss of two sensory systems (lateral line, electroreception) leads to the development of a unique ear and auditory system in amniotes. Lmx1a/b, Gdf7, Wnt1/3a, BMP4/7 and Atoh1 define the lateral line, electroreception and auditory nuclei. In contrast, vestibular nuclei depend on Neurog1/2, Ascl1, Ptf1a and Olig3, among others, to develop an independent origin of the vestibular nuclei. A common origin of hair cells depends on Eya1, Sox2 and Atoh1, which generate the mechanosensory cells. Several proteins define the polarity of hair cells in the ear and lateral line. A unique connection of stereocilia requires CDH23 and PCDH15 for connections and TMC1/2 proteins to perceive mechanosensory input. Electroreception has no polarity, and a different system is used to drive electroreceptors. All hair cells function by excitation via ribbons to activate neurons that innervate the distinct target areas. An integrated perspective is presented to understand the gain and loss of different sensory systems.

A novel inhibitor rescues cerebellar defects in a zebrafish model of Down syndrome-associated kinase Dyrk1A overexpression

The highly conserved dual-specificity tyrosine phosphorylation-regulated kinase 1A (Dyrk1A) plays crucial roles during central nervous system development and homeostasis. Furthermore, its hyperactivity is considered responsible for some neurological defects in individuals with Down syndrome. We set out to establish a zebrafish model expressing human Dyrk1A that could be further used to characterize the interaction between Dyrk1A and neurological phenotypes. First, we revealed the prominent expression of dyrk1a homologs in cerebellar neurons in the zebrafish larval and adult brains. Overexpression of human dyrk1a in postmitotic cerebellar Purkinje neurons resulted in a structural misorganization of the Purkinje cells in cerebellar hemispheres and a compaction of this cell population. This impaired Purkinje cell organization was progressive, leading to an age-dependent dispersal of Purkinje neurons throughout the cerebellar molecular layer with larval swim deficits resulting in miscoordination of swimming and reduced exploratory behavior in aged adults. We also found that the structural misorganization of the larval Purkinje cell layer could be rescued by pharmacological treatment with Dyrk1A inhibitors. We further reveal the in vivo efficiency of a novel selective Dyrk1A inhibitor, KuFal194. These findings demonstrate that the zebrafish is a well-suited vertebrate organism to genetically model severe neurological diseases with single cell type specificity. Such models can be used to relate molecular malfunction to cellular deficits, impaired tissue formation, and organismal behavior and can also be used for pharmacological compound testing and validation.

Synergistic population coding of natural communication stimuli by hindbrain electrosensory neurons

Understanding how neural populations encode natural stimuli with complex spatiotemporal structure to give rise to perception remains a central problem in neuroscience. Here we investigated population coding of natural communication stimuli by hindbrain neurons within the electrosensory system of weakly electric fish Apteronotus leptorhynchus. Overall, we found that simultaneously recorded neural activities were correlated: signal but not noise correlations were variable depending on the stimulus waveform as well as the distance between neurons. Combining the neural activities using an equal-weight sum gave rise to discrimination performance between different stimulus waveforms that was limited by redundancy introduced by noise correlations. However, using an evolutionary algorithm to assign different weights to individual neurons before combining their activities (i.e., a weighted sum) gave rise to increased discrimination performance by revealing synergistic interactions between neural activities. Our results thus demonstrate that correlations between the neural activities of hindbrain electrosensory neurons can enhance information about the structure of natural communication stimuli that allow for reliable discrimination between different waveforms by downstream brain areas.

Multiple behavior-specific cancellation signals contribute to suppressing predictable sensory reafference in a cerebellum-like structure

Movement induces sensory stimulation of an animal's own sensory receptors, termed reafference. With a few exceptions, notably vestibular and proprioception, this reafference is unwanted sensory noise and must be selectively filtered in order to detect relevant external sensory signals. In the cerebellum-like electrosensory nucleus of elasmobranch fish, an adaptive filter preserves novel signals by generating cancellation signals that suppress predictable reafference. A parallel fiber network supplies the principal Purkinje-like neurons (called ascending efferent neurons, AENs) with behavior-associated internal reference signals, including motor corollary discharge and sensory feedback, from which predictive cancellation signals are formed. How distinct behavior-specific cancellation signals interact within AENs when multiple behaviors co-occur and produce complex, changing patterns of reafference is unknown. Here, we show that when multiple streams of internal reference signals are available, cancellation signals form that are specific to parallel fiber inputs temporally correlated with, and therefore predictive of, sensory reafference. A single AEN has the capacity to form more than one cancellation signal, and AENs form multiple cancellation signals simultaneously and modify them independently during co-occurring behaviors. Cancellation signals update incrementally during continuous behaviors, as well as episodic bouts of behavior that last minutes to hours. Finally, individual AENs, independently of their neighbors, form unique AEN-specific cancellation signals that depend on the particular sensory reafferent input it receives. Together, these results demonstrate the capacity of the adaptive filter to utilize multiple cancellation signals to suppress dynamic patterns of reafference arising from complex co-occurring and intermittently performed behaviors.

Polarity- and Intensity-Independent Modulation of Timing During Delay Eyeblink Conditioning Using Cerebellar Transcranial Direct Current Stimulation

Delay eyeblink conditioning (dEBC) is widely used to assess cerebellar-dependent associative motor learning, including precise timing processes. Transcranial direct current stimulation (tDCS), noninvasive brain stimulation used to indirectly excite and inhibit select brain regions, may be a promising tool for understanding how functional integrity of the cerebellum influences dEBC behavior. The aim of this study was to assess whether tDCS-induced inhibition (cathodal) and excitation (anodal) of the cerebellum differentially impact timing of dEBC. A standard 10-block dEBC paradigm was administered to 102 healthy participants. Participants were randomized to stimulation conditions in a double-blind, between-subjects sham-controlled design. Participants received 20-min active (anodal or cathodal) stimulation at 1.5 mA (n = 20 anodal, n = 22 cathodal) or 2 mA (n = 19 anodal, n = 21 cathodal) or sham stimulation (n = 20) concurrently with dEBC training. Stimulation intensity and polarity effects on percent conditioned responses (CRs) and CR peak and onset latency were examined using repeated-measures analyses of variance. Acquisition of CRs increased over time at a similar rate across sham and all active stimulation groups. CR peak and onset latencies were later, i.e., closer to air puff onset, in all active stimulation groups compared to the sham group. Thus, tDCS facilitated cerebellar-dependent timing of dEBC, irrespective of stimulation intensity and polarity. These findings highlight the feasibility of using tDCS to modify cerebellar-dependent functions and provide further support for cerebellar contributions to human eyeblink conditioning and for exploring therapeutic tDCS interventions for cerebellar dysfunction.

Neurotransmitters, Cell Types, and Circuit Mechanisms of Motor Skill Learning and Clinical Applications

Animals acquire motor skills to better survive and adapt to a changing environment. The ability to learn novel motor actions without disturbing learned ones is essential to maintaining a broad motor repertoire. During motor learning, the brain makes a series of adjustments to build novel sensory–motor relationships that are stored within specific circuits for long-term retention. The neural mechanism of learning novel motor actions and transforming them into long-term memory still remains unclear. Here we review the latest findings with regard to the contributions of various brain subregions, cell types, and neurotransmitters to motor learning. Aiming to seek therapeutic strategies to restore the motor memory in relative neurodegenerative disorders, we also briefly describe the common experimental tests and manipulations for motor memory in rodents.

Does the Cerebellum Implement or Select Geometries? A Speculative Note

During evolution, living systems, actively interacting with their environment, developed the ability, through sensorimotor contingencies, to construct functional spaces shaping their perception and their movements. These geometries were modularly embedded in specific functional neuro-architectures. In particular, human movements were shown to obey several empirical laws, such as the 2/3 power law, isochrony, or jerk minimization principles, which constrain and adapt motor planning and execution. Outstandingly, such laws can be deduced from a combination of Euclidean, affine, and equi-affine geometries, whose neural correlates have been partly detected in several brain areas including the cerebellum and the basal ganglia. Reviving Pellionisz and Llinas general hypothesis regarding the cerebrum and the cerebellum as geometric machines, we speculate that the cerebellum should be involved in implementing and/or selecting task-specific geometries for motor and cognitive skills. More precisely, the cerebellum is assumed to compute forward internal models to help specific cortical and subcortical regions to select appropriate geometries among, at least, Euclidean and affine geometries. We emphasize that the geometrical role of the cerebellum deserves a renewal of interest, which may provide a better understanding of its specific contributions to motor and associative (cognitive) functions.

Gsx2 is required for specification of neurons in the inferior olivary nuclei from Ptf1a-expressing neural progenitors in zebrafish

Neurons in the inferior olivary nuclei (IO neurons) send climbing fibers to Purkinje cells to elicit functions of the cerebellum. IO neurons and Purkinje cells are derived from neural progenitors expressing the proneural gene ptf1a In this study, we found that the homeobox gene gsx2 was co-expressed with ptf1a in IO progenitors in zebrafish. Both gsx2 and ptf1a zebrafish mutants showed a strong reduction or loss of IO neurons. The expression of ptf1a was not affected in gsx2 mutants, and vice versa. In IO progenitors, the ptf1a mutation increased apoptosis whereas the gsx2 mutation did not, suggesting that ptf1a and gsx2 are regulated independently of each other and have distinct roles. The fibroblast growth factors (Fgf) 3 and 8a, and retinoic acid signals negatively and positively, respectively, regulated gsx2 expression and thereby the development of IO neurons. mafba and Hox genes are at least partly involved in the Fgf- and retinoic acid-dependent regulation of IO neuronal development. Our results indicate that gsx2 mediates the rostro-caudal positional signals to specify the identity of IO neurons from ptf1a-expressing neural progenitors.

A History of Corollary Discharge: Contributions of Mormyrid Weakly Electric Fish

Corollary discharge is an important brain function that allows animals to distinguish external from self-generated signals, which is critical to sensorimotor coordination. Since discovery of the concept of corollary discharge in 1950, neuroscientists have sought to elucidate underlying neural circuits and mechanisms. Here, we review a history of neurophysiological studies on corollary discharge and highlight significant contributions from studies using African mormyrid weakly electric fish. Mormyrid fish generate brief electric pulses to communicate with other fish and to sense their surroundings. In addition, mormyrids can passively locate weak, external electric signals. These three behaviors are mediated by different corollary discharge functions including inhibition, enhancement, and predictive “negative image” generation. Owing to several experimental advantages of mormyrids, investigations of these mechanisms have led to important general principles that have proven applicable to a wide diversity of animal species.

Calsequestrins New Calcium Store Markers of Adult Zebrafish Cerebellum and Optic Tectum

Calcium stores in neurons are heterogeneous in compartmentalization and molecular composition. Danio rerio (zebrafish) is an animal model with a simply folded cerebellum similar in cellular organization to that of mammals. The aim of the study was to identify new endoplasmic reticulum (ER) calcium store markers in zebrafish adult brain with emphasis on cerebellum and optic tectum. By quantitative polymerase chain reaction, we found three RNA transcripts coding for the intra-ER calcium binding protein calsequestrin: casq1a, casq1b, and casq2. In brain homogenates, two isoforms were detected by mass spectrometry and western blotting. Fractionation experiments of whole brain revealed that Casq1a and Casq2 were enriched in a heavy fraction containing ER microsomes and synaptic membranes. By in situ hybridization, we found the heterogeneous expression of casq1a and casq2 mRNA to be compatible with the cellular localization of calsequestrins investigated by immunofluorescence. Casq1 was expressed in neurogenic differentiation 1 expressing the granule cells of the cerebellum and the periventricular zone of the optic tectum. Casq2 was concentrated in parvalbumin expressing Purkinje cells. At a subcellular level, Casq1 was restricted to granular cell bodies, and Casq2 was localized in cell bodies, dendrites, and axons. Data are discussed in relation to the differential cellular and subcellular distribution of other cerebellum calcium store markers and are evaluated with respect to the putative relevance of calsequestrins in the neuron-specific functional activity.

Angelman syndrome: a journey through the brain

Angelman syndrome (AS) is an incurable neurodevelopmental disease caused by loss of function of the maternally inherited UBE3A gene. AS is characterized by a defined set of symptoms, namely severe developmental delay, speech impairment, uncontrolled laughter, and ataxia. Current understanding of the pathophysiology of AS relies mostly on studies using the murine model of the disease, although alternative models based on patient-derived stem cells are now emerging. Here, we summarize the literature of the last decade concerning the three major brain areas that have been the subject of study in the context of AS: hippocampus, cortex, and the cerebellum. Our comprehensive analysis highlights the major phenotypes ascribed to the different brain areas. Moreover, we also discuss the major drawbacks of current models and point out future directions for research in the context of AS, which will hopefully lead us to an effective treatment of this condition in humans.

Anatomy and Connectivity of the Torus Longitudinalis of the Adult Zebrafish

This study describes the cytoarchitecture of the torus longitudinalis (TL) in adult zebrafish by using light and electron microscopy, as well as its main connections as revealed by DiI tract tracing. In addition, by using high resolution confocal imaging followed by digital tracing, we describe the morphology of tectal pyramidal cells (type I cells) that are GFP positive in the transgenic line Tg(1.4dlx5a-dlx6a:GFP)^ot1. The TL consists of numerous small and medium-sized neurons located in a longitudinal eminence attached to the medial optic tectum. A small proportion of these neurons are GABAergic. The neuropil shows three types of synaptic terminals and numerous dendrites. Tracing experiments revealed that the main efference of the TL is formed of parallel-like fibers that course within the marginal layer of the optic tectum. A toral projection to the thalamic nucleus rostrolateralis is also observed. Afferents to the TL come from visual and cerebellum-related nuclei in the pretectum, namely the central, intercalated and the paracommissural pretectal nuclei, as well as from the subvalvular nucleus in the isthmus. Additional afferents to the TL may come from the cerebellum but their origins could not be confirmed. The tectal afferent projection to the TL originates from cells similar to the type X cells described in other cyprinids. Tectal pyramidal neurons show round or piriform cell bodies, with spiny apical dendritic trees in the marginal layer. This anatomical study provides a basis for future functional and developmental studies focused on this cerebellum-like circuit in zebrafish.

Neural Networks: How a Multi-Layer Network Learns to Disentangle Exogenous from Self-Generated Signals

Artificial multi-layer networks can learn difficult tasks, such as recognizing faces, but their architecture and learning rules appear to be very different from those of biological neural networks. Experimental and computational studies of a two-layered biological neural network have revealed how the learning rules used in artificial neural networks can be efficiently implemented by neurons with complex dynamics and precisely organized connectivity.

A cerebellum-like circuit in the lateral line system of fish cancels mechanosensory input associated with its own movements

An animal's own movement exerts a profound impact on sensory input to its nervous system. Peripheral sensory receptors do not distinguish externally generated stimuli from stimuli generated by an animal's own behavior (reafference) - although the animal often must. One way that nervous systems can solve this problem is to provide movement-related signals (copies of motor commands and sensory feedback) to sensory systems, which can then be used to generate predictions that oppose or cancel out sensory responses to reafference. Here, we studied the use of movement-related signals to generate sensory predictions in the lateral line medial octavolateralis nucleus (MON) of the little skate. In the MON, mechanoreceptive afferents synapse on output neurons that also receive movement-related signals from central sources, via a granule cell parallel fiber system. This parallel fiber system organization is characteristic of a set of so-called cerebellum-like structures. Cerebellum-like structures have been shown to support predictive cancellation of reafference in the electrosensory systems of fish and the auditory system of mice. Here, we provide evidence that the parallel fiber system in the MON can generate predictions that are negative images of (and therefore cancel) sensory input associated with respiratory and fin movements. The MON, found in most aquatic vertebrates, is probably one of the most primitive cerebellum-like structures and a starting point for cerebellar evolution. The results of this study contribute to a growing body of work that uses an evolutionary perspective on the vertebrate cerebellum to understand its functional diversity in animal behavior.

Synaptic Plasticity Forms and Functions

Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.

Presynaptic developmental plasticity allows robust sparse wiring of the Drosophila mushroom body

In order to represent complex stimuli, principle neurons of associative learning regions receive combinatorial sensory inputs. Density of combinatorial innervation is theorized to determine the number of distinct stimuli that can be represented and distinguished from one another, with sparse innervation thought to optimize the complexity of representations in networks of limited size. How the convergence of combinatorial inputs to principle neurons of associative brain regions is established during development is unknown. Here, we explore the developmental patterning of sparse olfactory inputs to Kenyon cells of the Drosophila melanogaster mushroom body. By manipulating the ratio between pre- and post-synaptic cells, we find that postsynaptic Kenyon cells set convergence ratio: Kenyon cells produce fixed distributions of dendritic claws while presynaptic processes are plastic. Moreover, we show that sparse odor responses are preserved in mushroom bodies with reduced cellular repertoires, suggesting that developmental specification of convergence ratio allows functional robustness.

Motor Behavior Selectively Inhibits Hair Cells Activated by Forward Motion in the Lateral Line of Zebrafish

How do sensory systems disambiguate events in the external world from signals generated by the animal's own motor actions? One strategy is to use an "efference copy" of the motor command to inhibit the sensory input caused by active behavior [1]. But does inhibition of self-generated inputs also block transmission of external stimuli? We investigated this question in the lateral line, a sensory system that allows fish and amphibians to detect water currents and that contributes to behaviors such as rheotaxis [2] and predator avoidance [3, 4]. This mechanical sense begins in hair cells grouped into neuromasts dotted along the animal's body [5]. Each neuromast contains two populations of hair cells, activated by deflection in either the anterior or posterior direction [6], as well as efferent fibers that are active during motor behavior to suppress afferents projecting to the brain [7-12]. To test how far the efference copy signal modulates responses to external stimuli, we imaged neural and synaptic activity in larval zebrafish during fictive swimming. We find that efferents transmit a precise copy of the motor signal and a single spike in the motor nerve can be associated with ∼50% inhibition of glutamate release. The efference copy signal acted with high selectivity on hair cells polarized to be activated by posterior deflections, as would occur during forward motion. During swimming, therefore, "push-pull" encoding of stimulus direction by afferents of opposite polarity is disrupted while still allowing a subset of hair cells to detect stimuli originating in the external world.

Task-Related Sensorimotor Adjustments Increase the Sensory Range in Electrolocation

Perception and motor control traditionally are studied separately. However, motor activity can serve as a scaffold to shape the sensory flow. This tight link between motor actions and sensing is particularly evident in active sensory systems. Here, we investigate how the weakly electric mormyrid fish Gnathonemus petersii of undetermined sex structure their sensing and motor behavior while learning a perceptual task. We find systematic adjustments of the motor behavior that correlate with an increased performance. Using a model to compute the electrosensory input, we show that these behavioral adjustments improve the sensory input. As we find low neuronal detection thresholds at the level of medullary electrosensory neurons, it seems that the behavior-driven improvements of the sensory input are highly suitable to overcome the sensory limitations, thereby increasing the sensory range. Our results show that motor control is an active component of sensory learning, demonstrating that a detailed understanding of contribution of motor actions to sensing is needed to understand even seemingly simple behaviors.SIGNIFICANCE STATEMENT Motor-guided sensation and perception are intertwined, with motor behavior serving as a scaffold to shape the sensory input. We characterized how the weakly electric mormyrid fish Gnathonemus petersii, as it learns a perceptual task, restructures its sensorimotor behavior. We find that systematic adjustments of the motor behavior correlate with increased performance and a shift of the sensory attention of the animal. Analyzing the afferent electrosensory input shows that a significant gain in information results from these sensorimotor adjustments. Our results show that motor control can be an active component of sensory learning. Researching the sensory corollaries of motor control thus can be crucial to understand sensory sensation and perception under naturalistic conditions.

Continual Learning in a Multi-Layer Network of an Electric Fish

Distributing learning across multiple layers has proven extremely powerful in artificial neural networks. However, little is known about how multi-layer learning is implemented in the brain. Here, we provide an account of learning across multiple processing layers in the electrosensory lobe (ELL) of mormyrid fish and report how it solves problems well known from machine learning. Because the ELL operates and learns continuously, it must reconcile learning and signaling functions without switching its mode of operation. We show that this is accomplished through a functional compartmentalization within intermediate layer neurons in which inputs driving learning differentially affect dendritic and axonal spikes. We also find that connectivity based on learning rather than sensory response selectivity assures that plasticity at synapses onto intermediate-layer neurons is matched to the requirements of output neurons. The mechanisms we uncover have relevance to learning in the cerebellum, hippocampus, and cerebral cortex, as well as in artificial systems.

Multiscale Community Detection in Functional Brain Networks Constructed Using Dynamic Time Warping

Previous studies have focused on the detection of community structures of brain networks constructed with resting-state functional magnetic resonance imaging (fMRI) data. Pearson correlation is often used to describe the connections between nodes in the construction of functional brain networks, which typically ignores the inherent timing and validity of fMRI time series. To solve this problem, this study applied the Dynamic Time Warp (DTW) algorithm to determine the correlation between two brain regions by comparing the synchronization and asynchrony of the time series. In addition, to determine the best community structure for each subject, we further divided the brain network into different scales, and then detected the different communities in these brain networks by using Modularity, Variation of Information (VI) and Normalized Mutual Information (NMI) as structural monitoring variables. Finally, we affirmed each subject's best community structure based on them. The experiments showed that through the method proposed in this paper, we not only accurately discovered important components of seven basic functional subnetworks, but also found that the putamen and Heschl's gyrus have a relationship with the inferior parietal network. Most importantly, this method can also determine each subject's functional brain network density, thus confirming the findings of studies testing real brain networks.

Resynthesizing behavior through phylogenetic refinement

This article proposes that biologically plausible theories of behavior can be constructed by following a method of "phylogenetic refinement," whereby they are progressively elaborated from simple to complex according to phylogenetic data on the sequence of changes that occurred over the course of evolution. It is argued that sufficient data exist to make this approach possible, and that the result can more effectively delineate the true biological categories of neurophysiological mechanisms than do approaches based on definitions of putative functions inherited from psychological traditions. As an example, the approach is used to sketch a theoretical framework of how basic feedback control of interaction with the world was elaborated during vertebrate evolution, to give rise to the functional architecture of the mammalian brain. The results provide a conceptual taxonomy of mechanisms that naturally map to neurophysiological and neuroanatomical data and that offer a context for defining putative functions that, it is argued, are better grounded in biology than are some of the traditional concepts of cognitive science.

Sequence and hierarchy in vocal rhythms and phonology

I explore the neural and evolutionary origins of phonological hierarchy, building on Peter MacNeilage's frame/content model, which suggests that human speech evolved from primate nonvocal jaw oscillations, for example, lip smack displays, combined with phonation. Considerable recent data, reviewed here, support this proposition. I argue that the evolution of speech motor control required two independent components. The first, identified by MacNeilage, is the diversification of phonetic "content" within a simple sequential "frame," and would be within reach of nonhuman primates, by simply intermittently activating phonation during lip smack displays. Such voicing control requires laryngeal control, hypothesized to necessitate direct corticomotor connections to the nucleus ambiguus. The second component, proposed here, involves imposing additional hierarchical rhythmic structure upon the "flat" control sequences typifying mammalian vocal tract oscillations and is required for the flexible combinatorial capacity observed in modern phonology. I hypothesize that phonological hierarchy resulted from a marriage of a preexisting capacity for sequential structure seen in other primates, with novel hierarchical motor control circuitry (potentially evolved in tool use and/or musical contexts). In turn, this phonological hierarchy paved the way for phrasal syntactic hierarchy. I support these arguments using comparative and neural data from nonhuman primates and birdsong.

Internally Generated Predictions Enhance Neural and Behavioral Detection of Sensory Stimuli in an Electric Fish

Studies of cerebellum-like circuits in fish have demonstrated that synaptic plasticity shapes the motor corollary discharge responses of granule cells into highly-specific predictions of self-generated sensory input. However, the functional significance of such predictions, known as negative images, has not been directly tested. Here we provide evidence for improvements in neural coding and behavioral detection of prey-like stimuli due to negative images. In addition, we find that manipulating synaptic plasticity leads to specific changes in circuit output that disrupt neural coding and detection of prey-like stimuli. These results link synaptic plasticity, neural coding, and behavior and also provide a circuit-level account of how combining external sensory input with internally generated predictions enhances sensory processing.

Role of Reelin in cell positioning in the cerebellum and the cerebellum-like structure in zebrafish

The cerebellum and the cerebellum-like structure in the mesencephalic tectum in zebrafish contain multiple cell types, including principal cells (i.e., Purkinje cells and type I neurons) and granule cells, that form neural circuits in which the principal cells receive and integrate inputs from granule cells and other neurons. It is largely unknown how these cells are positioned and how neural circuits form. While Reelin signaling is known to play an important role in cell positioning in the mammalian brain, its role in the formation of other vertebrate brains remains elusive. Here we found that zebrafish with mutations in Reelin or in the Reelin-signaling molecules Vldlr or Dab1a exhibited ectopic Purkinje cells, eurydendroid cells (projection neurons), and Bergmann glial cells in the cerebellum, and ectopic type I neurons in the tectum. The ectopic Purkinje cells and type I neurons received aberrant afferent fibers in these mutants. In wild-type zebrafish, reelin transcripts were detected in the internal granule cell layer, while Reelin protein was localized to the superficial layer of the cerebellum and the tectum. Laser ablation of the granule cell axons perturbed the localization of Reelin, and the mutation of both kif5aa and kif5ba, which encode major kinesin I components in the granule cells, disrupted the elongation of granule cell axons and the Reelin distribution. Our findings suggest that in zebrafish, (1) Reelin is transported from the granule cell soma to the superficial layer by axonal transport; (2) Reelin controls the migration of neurons and glial cells from the ventricular zone; and (3) Purkinje cells and type I neurons attract afferent axons during the formation of the cerebellum and the cerebellum-like structure.

Electroreception, electrogenesis and electric signal evolution

Electroreception, the capacity to detect external underwater electric fields with specialised receptors, is a phylogenetically widespread sensory modality in fishes and amphibians. In passive electroreception, a capacity possessed by c. 16% of fish species, an animal uses low-frequency-tuned ampullary electroreceptors to detect microvolt-range bioelectric fields from prey, without the need to generate its own electric field. In active electroreception (electrolocation), which occurs only in the teleost lineages Mormyroidea and Gymnotiformes, an animal senses its surroundings by generating a weak (< 1 V) electric-organ discharge (EOD) and detecting distortions in the EOD-associated field using high-frequency-tuned tuberous electroreceptors. Tuberous electroreceptors also detect the EODs of neighbouring fishes, facilitating electrocommunication. Several other groups of elasmobranchs and teleosts generate weak (< 10 V) or strong (> 50 V) EODs that facilitate communication or predation, but not electrolocation. Approximately 1.5% of fish species possess electric organs. This review has two aims. First, to synthesise our knowledge of the functional biology and phylogenetic distribution of electroreception and electrogenesis in fishes, with a focus on freshwater taxa and with emphasis on the proximate (morphological, physiological and genetic) bases of EOD and electroreceptor diversity. Second, to describe the diversity, biogeography, ecology and electric signal diversity of the mormyroids and gymnotiforms and to explore the ultimate (evolutionary) bases of signal and receptor diversity in their convergent electrogenic-electrosensory systems. Four sets of potential drivers or moderators of signal diversity are discussed. First, selective forces of an abiotic (environmental) nature for optimal electrolocation and communication performance of the EOD. Second, selective forces of a biotic nature targeting the communication function of the EOD, including sexual selection, reproductive interference from syntopic heterospecifics and selection from eavesdropping predators. Third, non-adaptive drift and, finally, phylogenetic inertia, which may arise from stabilising selection for optimal signal-receptor matching.

Vestibular processing during natural self-motion: implications for perception and action

How the brain computes accurate estimates of our self-motion relative to the world and our orientation relative to gravity in order to ensure accurate perception and motor control is a fundamental neuroscientific question. Recent experiments have revealed that the vestibular system encodes this information during everyday activities using pathway-specific neural representations. Furthermore, new findings have established that vestibular signals are selectively combined with extravestibular information at the earliest stages of central vestibular processing in a manner that depends on the current behavioural goal. These findings have important implications for our understanding of the brain mechanisms that ensure accurate perception and behaviour during everyday activities and for our understanding of disorders of vestibular processing.