Neural Mechanisms for Predicting the Sensory Consequences of Behavior: Insights from Electrosensory Systems

Action does not enhance but attenuates predicted touch

Dominant motor control theories propose that the brain predicts and attenuates the somatosensory consequences of actions, referred to as somatosensory attenuation. Support comes from psychophysical and neuroimaging studies showing that touch applied on a passive hand elicits attenuated perceptual and neural responses if it is actively generated by one's other hand, compared to an identical touch from an external origin. However, recent experimental findings have challenged this view by providing psychophysical evidence that the perceived intensity of touch on the passive hand is enhanced if the active hand does not receive touch simultaneously with the passive hand (somatosensory enhancement) and by further attributing attenuation to the double tactile stimulation of the hands upon contact. Here, we directly contrasted the hypotheses of the attenuation and enhancement models regarding how action influences somatosensory perception by manipulating whether the active hand contacts the passive hand. We further assessed somatosensory perception in the absence of any predictive cues in a condition that turned out to be essential for interpreting the experimental findings. In three pre-registered experiments, we demonstrate that action does not enhance the predicted touch (Experiment 1), that the previously reported 'enhancement' effects are driven by the reference condition used (Experiment 2), and that self-generated touch is robustly attenuated regardless of whether the two hands make contact (Experiment 3). Our results provide conclusive evidence that action does not enhance but attenuates predicted touch and prompt a reappraisal of recent experimental findings upon which theoretical frameworks proposing a perceptual enhancement by action prediction are based.

Altered corollary discharge signaling in the auditory cortex of a mouse model of schizophrenia predisposition

The ability to distinguish sensations that are self-generated from those caused by external events is disrupted in schizophrenia patients. However, the neural circuit abnormalities underlying this sensory impairment and its relationship to the risk factors for the disease is not well understood. To address this, we examined the processing of self-generated sounds in male Df(16)A+/- mice, which model one of the largest genetic risk factors for schizophrenia, the 22q11.2 microdeletion. We find that auditory cortical neurons in Df(16)A+/- mice fail to attenuate their responses to self-generated sounds, recapitulating deficits seen in schizophrenia patients. Notably, the auditory cortex of Df(16)A+/- mice displayed weaker motor-related signals and received fewer inputs from the motor cortex, suggesting an anatomical basis underlying the sensory deficit. These results provide insights into the mechanisms by which a major genetic risk factor for schizophrenia disrupts the top-down processing of sensory information.

Hormonal coordination of motor output and internal prediction of sensory consequences in an electric fish

Steroid hormones remodel neural networks to induce seasonal or developmental changes in behavior. Hormonal changes in behavior likely require coordinated changes in sensorimotor integration. Here, we investigate hormonal effects on a predictive motor signal, termed corollary discharge, that modulates sensory processing in weakly electric mormyrid fish. In the electrosensory pathway mediating communication behavior, inhibition activated by a corollary discharge blocks sensory responses to self-generated electric pulses, allowing the downstream circuit to selectively analyze communication signals from nearby fish. These pulses are elongated by increasing testosterone levels in males during the breeding season. We induced electric-pulse elongation using testosterone treatment and found that the timing of electroreceptor responses to self-generated pulses was delayed as electric-pulse duration increased. Simultaneous recordings from an electrosensory nucleus and electromotor neurons revealed that the timing of corollary discharge inhibition was delayed and elongated by testosterone. Furthermore, this shift in the timing of corollary discharge inhibition was precisely matched to the shift in timing of receptor responses to self-generated pulses. We then asked whether the shift in inhibition timing was caused by direct action of testosterone on the corollary discharge circuit or by plasticity acting on the circuit in response to altered sensory feedback. We surgically silenced the electric organ of fish and found similar hormonal modulation of corollary discharge timing between intact and silent fish, suggesting that sensory feedback was not required for this shift. Our findings demonstrate that testosterone directly regulates motor output and internal prediction of the resulting sensory consequences in a coordinated manner.

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.

Active sensing: How to eliminate self-generated noise

Animals use active sensing to investigate their environment. The active sense inputs must be discriminated from those arising independently from environmental signals. An experimental and modelling study has revealed how precise control of dendritic spike backpropagation contributes to such discrimination.

Efficient Temporal Coding in the Early Visual System: Existing Evidence and Future Directions

While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information should be stored, or encoded. Information theory provides a mathematical formalism that can be used to measure the efficiency and utility of different coding schemes for data transfer and storage. This theory shows that codes become efficient when they remove predictable, redundant spatial and temporal information. Efficient coding has been used to understand retinal computations and may also be relevant to understanding more complicated temporal processing in visual cortex. However, the literature on efficient coding in cortex is varied and can be confusing since the same terms are used to mean different things in different experimental and theoretical contexts. In this work, we attempt to provide a clear summary of the theoretical relationship between efficient coding and temporal prediction, and review evidence that efficient coding principles explain computations in the retina. We then apply the same framework to computations occurring in early visuocortical areas, arguing that data from rodents is largely consistent with the predictions of this model. Finally, we review and respond to criticisms of efficient coding and suggest ways that this theory might be used to design future experiments, with particular focus on understanding the extent to which neural circuits make predictions from efficient representations of environmental statistics.

Predictive attenuation of touch and tactile gating are distinct perceptual phenomena

In recent decades, research on somatosensory perception has led to two important observations. First, self-generated touches that are predicted by voluntary movements become attenuated compared with externally generated touches of the same intensity (attenuation). Second, externally generated touches feel weaker and are more difficult to detect during movement than at rest (gating). At present, researchers often consider gating and attenuation the same suppression process; however, this assumption is unwarranted because, despite more than 40 years of research, no study has combined them in a single paradigm. We quantified how people perceive self-generated and externally generated touches during movement and rest. We show that whereas voluntary movement gates the precision of both self-generated and externally generated touch, the amplitude of self-generated touch is robustly attenuated compared with externally generated touch. Furthermore, attenuation and gating do not interact and are not correlated, and we conclude that they represent distinct perceptual phenomena.

Increased upper-limb sensory attenuation with age

The pressure of our own finger on the arm feels differently than the same pressure exerted by an external agent: the latter involves just touch, whereas the former involves a combination of touch and predictive output from the internal model of the body. This internal model predicts the movement of our own finger and hence the intensity of the sensation of the finger press is decreased. A decrease in intensity of the self-produced stimulus is called sensory attenuation. It has been reported that, due to decreased proprioception with age and an increased reliance on the prediction of the internal model, sensory attenuation is increased in older adults. In this study, we used a force-matching paradigm to test if sensory attenuation is also present over the arm and if aging increases sensory attenuation. We demonstrated that, while both young and older adults overestimate a self-produced force, older adults overestimate it even more showing an increased sensory attenuation. In addition, we also found that both younger and older adults self-produce higher forces when activating the homologous muscles of the upper limb. While this is traditionally viewed as evidence for an increased reliance on internal model function in older adults because of decreased proprioception, proprioception appeared unimpaired in our older participants. This begs the question of whether an age-related decrease in proprioception is really responsible for the increased sensory attenuation observed in older people.

Right parietotemporal activity predicts sense of agency under uncertain delays of sensory outcomes

Sense of agency is the experience of control over one's own action and its consequent outcomes. The perceived time between a motor action and its consequent sensory outcomes (e.g., a flash of light) is shorter for a voluntary than involuntary action, a phenomenon known as intentional binding, which has been used extensively as an implicit measure of sense of agency. We developed a novel task in which participants had to respond whether a flash appeared immediately or with a delay relative to their voluntary action. We found that under high, but not low, uncertainty about the perceived time between voluntary finger movement and a subsequent flash of light, a prediction signal was generated in the right inferior parietal lobule prior to motor action. This prediction signal was linked to the emergence of a sudden insight solution (colloquially referred to as "Aha!" moment) in the right superior temporal gyrus prior to response. Single-trial event-related potential analysis revealed a reliable correlation between amplitudes of premotor and preresponse activities. The results suggest the existence of a predictive mechanism under high uncertainty about the timing of the sensory consequences of a voluntary motor action. The results are in line with the optimal cue integration theory of sense of agency, which states that both predictive and postdictive agency cues are crucial for the formation of sense of agency and the weight of each type of cue (predictive or postdictive) depends on their availability and reliability.NEW & NOTEWORTHY According to the optimal cue integration theory, the formation of sense of agency relies on both predictive and postdictive agency cues and how they are weighted based on their availability and reliability. Using a novel paradigm, we show for the first time a possible existence of a prediction signal prior to voluntary movement, which appears when postdictive agency cues (i.e., the judgment of the time between voluntary movement and a subsequent flash) are not reliable.

50 Years Since the Marr, Ito, and Albus Models of the Cerebellum

Fifty years have passed since David Marr, Masao Ito, and James Albus proposed seminal models of cerebellar functions. These models share the essential concept that parallel-fiber-Purkinje-cell synapses undergo plastic changes, guided by climbing-fiber activities during sensorimotor learning. However, they differ in several important respects, including holistic versus complementary roles of the cerebellum, pattern recognition versus control as computational objectives, potentiation versus depression of synaptic plasticity, teaching signals versus error signals transmitted by climbing-fibers, sparse expansion coding by granule cells, and cerebellar internal models. In this review, we evaluate different features of the three models based on recent computational and experimental studies. While acknowledging that the three models have greatly advanced our understanding of cerebellar control mechanisms in eye movements and classical conditioning, we propose a new direction for computational frameworks of the cerebellum, that is, hierarchical reinforcement learning with multiple internal models.

Prediction signals in the cerebellum: beyond supervised motor learning

While classical views of cerebellar learning have suggested that this structure predominantly operates according to an error-based supervised learning rule to refine movements, emerging evidence suggests that the cerebellum may also harness a wider range of learning rules to contribute to a variety of behaviors, including cognitive processes. Together, such evidence points to a broad role for cerebellar circuits in generating and testing predictions about movement, reward, and other non-motor operations. However, this expanded view of cerebellar processing also raises many new questions about how such apparent diversity of function arises from a structure with striking homogeneity. Hence, this review will highlight both current evidence for predictive cerebellar circuit function that extends beyond the classical view of error-driven supervised learning, as well as open questions that must be addressed to unify our understanding cerebellar circuit function.

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.

Learning to Expect: Predicting Sounds During Movement Is Related to Sensorimotor Association During Listening

Sensory experiences, such as sound, often result from our motor actions. Over time, repeated sound-producing performance can generate sensorimotor associations. However, it is not clear how sensory and motor information are associated. Here, we explore if sensory prediction is associated with the formation of sensorimotor associations during a learning task. We recorded event-related potentials (ERPs) while participants produced index and little finger-swipes on a bespoke device, generating novel sounds. ERPs were also obtained as participants heard those sounds played back. Peak suppression was compared to assess sensory prediction. Additionally, transcranial magnetic stimulation (TMS) was used during listening to generate finger-motor evoked potentials (MEPs). MEPs were recorded before and after training upon hearing these sounds, and then compared to reveal sensorimotor associations. Finally, we explored the relationship between these components. Results demonstrated that an increased positive-going peak (e.g., P2) and a suppressed negative-going peak (e.g., N2) were recorded during action, revealing some sensory prediction outcomes (P2: p = 0.050, ηp2 = 0.208; N2: p = 0.001, ηp2 = 0.474). Increased MEPs were also observed upon hearing congruent sounds compared with incongruent sounds (i.e., associated to a finger), demonstrating precise sensorimotor associations that were not present before learning (Index finger: p < 0.001, ηp2 = 0.614; Little finger: p < 0.001, ηp2 = 0.529). Consistent with our broad hypotheses, a negative association between the MEPs in one finger during listening and ERPs during performance of the other was observed (Index finger MEPs and Fz N1 action ERPs; r = −0.655, p = 0.003). Overall, data suggest that predictive mechanisms are associated with the fine-tuning of sensorimotor associations.

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.

Corollary Discharge Signals in the Cerebellum

The cerebellum is known to make movements fast, smooth, and accurate. Many hypotheses emphasize the role of the cerebellum in computing learned predictions important for sensorimotor calibration and feedforward control of movements. Hypotheses of the computations performed by the cerebellum in service of motor control borrow heavily from control systems theory, with models that frequently invoke copies of motor commands, called corollary discharge. This review describes evidence for corollary discharge inputs to the cerebellum and highlights the hypothesized roles for this information in cerebellar motor-related computations. Insights into the role of corollary discharge in motor control, described here, are intended to inform the exciting but still untested roles of corollary discharge in cognition, perception, and thought control relevant in psychiatric disorders.

Internal Models in Biological Control

Rationality principles such as optimal feedback control and Bayesian inference underpin a probabilistic framework that has accounted for a range of empirical phenomena in biological sensorimotor control. To facilitate the optimization of flexible and robust behaviors consistent with these theories, the ability to construct internal models of the motor system and environmental dynamics can be crucial. In the context of this theoretic formalism, we review the computational roles played by such internal models and the neural and behavioral evidence for their implementation in the brain.

Differential developmental changes in cortical representations of auditory-vocal stimuli in songbirds

Procedural skill learning requires iterative comparisons between feedback of self-generated motor output and a goal sensorimotor pattern. In juvenile songbirds, neural representations of both self-generated behaviors (each bird's own immature song) and the goal motor pattern (each bird's adult tutor song) are essential for vocal learning, yet little is known about how these behaviorally relevant stimuli are encoded. We made extracellular recordings during song playback in anesthetized juvenile and adult zebra finches ( Taeniopygia guttata) in adjacent cortical regions RA (robust nucleus of the arcopallium), AId (dorsal intermediate arcopallium), and RA cup, each of which is well situated to integrate auditory-vocal information: RA is a motor cortical region that drives vocal output, AId is an adjoining cortical region whose projections converge with basal ganglia loops for song learning in the dorsal thalamus, and RA cup surrounds RA and receives inputs from primary and secondary auditory cortex. We found strong developmental differences in neural selectivity within RA, but not in AId or RA cup. Juvenile RA neurons were broadly responsive to multiple songs but preferred juvenile over adult vocal sounds; in addition, spiking responses lacked consistent temporal patterning. By adulthood, RA neurons responded most strongly to each bird's own song with precisely timed spiking activity. In contrast, we observed a complete lack of song responsivity in both juvenile and adult AId, even though this region receives song-responsive inputs. A surprisingly large proportion of sites in RA cup of both juveniles and adults did not respond to song playback, and responsive sites showed little evidence of song selectivity. NEW & NOTEWORTHY Motor skill learning entails changes in selectivity for behaviorally relevant stimuli across cortical regions, yet the neural representation of these stimuli remains understudied. We investigated how information important for vocal learning in zebra finches is represented in regions analogous to infragranular layers of motor and auditory cortices during vs. after the developmentally regulated learning period. The results provide insight into how neurons in higher level stages of cortical processing represent stimuli important for motor skill learning.

Feedback optimizes neural coding and perception of natural stimuli

Growing evidence suggests that sensory neurons achieve optimal encoding by matching their tuning properties to the natural stimulus statistics. However, the underlying mechanisms remain unclear. Here we demonstrate that feedback pathways from higher brain areas mediate optimized encoding of naturalistic stimuli via temporal whitening in the weakly electric fish Apteronotus leptorhynchus. While one source of direct feedback uniformly enhances neural responses, a separate source of indirect feedback selectively attenuates responses to low frequencies, thus creating a high-pass neural tuning curve that opposes the decaying spectral power of natural stimuli. Additionally, we recorded from two populations of higher brain neurons responsible for the direct and indirect descending inputs. While one population displayed broadband tuning, the other displayed high-pass tuning and thus performed temporal whitening. Hence, our results demonstrate a novel function for descending input in optimizing neural responses to sensory input through temporal whitening that is likely to be conserved across systems and species.

Selective and Context-Dependent Social and Behavioral Effects of Δ9-Tetrahydrocannabinol in Weakly Electric Fish

Cannabinoid (CB) receptors are widespread in the nervous system and influence a variety of behaviors. Weakly electric fish have been a useful model system in the study of the neural basis of behavior, but we know nothing of the role played by the CB system. Here, we determine the overall behavioral effect of a nonselective CB receptor agonist, namely Δ9-tetrahydrocannabinol (THC), in the weakly electric fish Apte-ronotus leptorhynchus. Using various behavioral paradigms involving social stimuli, we show that THC decreases locomotor behavior, as in many species, and influences communication and social behavior. Across the different experiments, we found that the propensity to emit communication signals (chirps) and seek social interactions was affected in a context-dependent manner. We explicitly tested this hypothesis by comparing the behavioral effects of THC injection in fish placed in a novel versus a familiar social and physical environment. THC-injected fish were less likely to chirp than control fish in familiar situations but not in novel ones. The tendency to be in close proximity to other fish was affected only in novel environments, with control fish clustering more than THC-injected ones. By identifying behaviors affected by CB agonists, our study can guide further comparative and neurophysiological studies of the role of the CB system using a weakly electric fish as a model.

Movement Rate Is Encoded and Influenced by Widespread, Coherent Activity of Cerebellar Molecular Layer Interneurons

Inhibition from molecular layer interneurons (MLIs) is thought to play an important role in cerebellar function by sharpening the precision of Purkinje cell spike output. Yet the coding features of MLIs during behavior are poorly understood. To study MLI activity, we used in vivo Ca²⁺ imaging in head-fixed mice during the performance of a rhythmic motor behavior, licking during water consumption. MLIs were robustly active during lick-related movement across a lobule-specific region of the cerebellum showing high temporal correspondence within their population. Average MLI Ca²⁺ activity strongly correlated with movement rate but not to the intentional, or unexpected, adjustment of lick position or to sensory feedback that varied with task condition. Chemogenetic suppression of MLI output reduced lick rate and altered tongue movements, indicating that activity of these interneurons not only encodes temporal aspects of movement kinematics but also influences motor outcome pointing to an integral role in online control of rhythmic behavior.SIGNIFICANCE STATEMENT The cerebellum helps fine-tune coordinated motor actions via signaling from projection neurons called Purkinje cells. Molecular layer interneurons (MLIs) provide powerful inhibition onto Purkinje cells, but little is understood about how this inhibitory circuit is engaged during behavior or what type of information is transmitted through these neurons. Our work establishes that MLIs in the lateral cerebellum are broadly activated during movement with calcium activity corresponding to movement rate. We also show that suppression of MLI output slows and disorganizes the precise movement pattern. Therefore, MLIs are an important circuit element in the cerebellum allowing for accurate motor control.