Young Domestic Pigs (Sus scrofa) Can Perform Pavlovian Eyeblink Conditioning

Introduction: Pigs have been an increasingly popular preclinical model in nutritional neuroscience, as their anatomy, physiology, and nutrition requirements are highly comparable to those of humans. Eyeblink conditioning is one of the most well-validated behavioral paradigms in neuroscience to study underlying mechanisms of learning and memory formation in the cerebellum. Eyeblink conditioning has been performed in many species but has never been done on young pigs. Therefore, our aim here was to develop and validate an eyeblink conditioning paradigm in young pigs.Method: Eighteen intact male pigs were artificially reared from postnatal day 2–30. The eyeblink conditioning setup consisted of a sound-damping box with a hammock that pigs were placed in, which allowed the pig to remain comfortable yet maintain a typical range of head motion. In a delay conditioning paradigm, the conditional stimulus (CS) was a 550 ms blue light-emitting diode (LED), the unconditional stimulus (US) was a 50 ms eye air-puff, the CS-US interval was 500 ms. Starting at postnatal day 14, pigs were habituated for 5 days to the eyeblink conditioning setup, followed by 5 daily sessions of acquisition training (40 paired CS-US trials each day).Results: The group-averaged amplitude of conditioned eyelid responses gradually increased over the course of the 5 days of training, indicating that pigs learned to make the association between the LED light CS and the air-puff US. A similar increase was found for the conditioned response (CR) probability: the group-averaged CR probability on session 1 was about 12% and reached a CR probability of 55% on day 5. The latency to CR peak time lacked a temporal preference in the first session but clearly showed preference from the moment that animals started to show more CRs in session 2 and onwards whereby the eyelid was maximally closed exactly at the moment that the US would be delivered.Conclusion: We concluded that 3-week-old pigs have the capability of performing in a cerebellar classical conditioning task, demonstrating for the first time that eyeblink conditioning in young pigs has the potential to be a valuable behavioral tool to measure neurodevelopment.

Adaptively Timed Learning

This chapter explains how humans and other animals learn to adaptively time their behaviors to match external environmental constraints. It hereby explains how nerve cells learn to bridge big time intervals of hundreds of milliseconds or even several seconds, and thereby associate events that are separated in time. This is accomplished by a spectrum of cells that each respond in overlapping time intervals and whose population response can bridge intervals much larger than any individual cell can. Such spectral timing occurs in circuits that include the lateral entorhinal cortex and hippocampal cortex. Trace conditioning, in which CS and US are separated in time, requires the hippocampus, whereas delay conditioning, in which they overlap, does not. The Weber law observed in trace conditioning naturally emerges from spectral timing dynamics, as later confirmed by data about hippocampal time cells. Hippocampal adaptive timing enables a cognitive-emotional resonance to be sustained long enough to become conscious of its feeling and its causal event, and to support BDNF-modulated memory consolidation. Spectral timing supports balanced exploratory and consummatory behaviors whereby restless exploration for immediate gratification is replaced by adaptively timed consummation. During expected disconfirmations of reward, orienting responses are inhibited until an adaptively timed response is released. Hippocampally-mediated incentive motivation supports timed responding via the cerebellum. mGluR regulates adaptive timing in hippocampus, cerebellum, and basal ganglia. Breakdowns of mGluR and dopamine modulation cause symptoms of autism and Fragile X syndrome. Inter-personal circular reactions enable social cognitive capabilities, including joint attention and imitation learning, to develop.

Pigs as a new behavioral model for studying Pavlovian eyeblink conditioning

Intro: Pigs have been an increasingly popular preclinical model in nutritional neuroscience, as their anatomy, physiology, and nutrition requirements are highly comparable to those of humans. Eyeblink conditioning is one of the most well-validated behavioral paradigms in neuroscience to study underlying mechanisms of learning and memory formation in the cerebellum. Eyeblink conditioning has been performed in many species but has never been done on young pigs. Therefore, our aim here was to develop and validate an eyeblink conditioning paradigm in young pigs. Method: Eighteen intact male pigs were artificially reared from postnatal day 2 to 30. The eyeblink conditioning setup consisted of a sound-damping box with a hammock that pigs were placed in, which allowed the pig to remain comfortable yet maintain a typical range of head motion. In a delay conditioning paradigm, the conditional stimulus (CS) was a 550 ms blue light-emitting diode (LED), the unconditional stimulus (US) was a 50 ms eye air-puff, the CS-US interval was 500 ms. Starting at postnatal day 14, pigs were habituated for five days to the eyeblink conditioning setup, followed by 5 daily sessions of acquisition training (40 paired CS-US trials each day). Results: The group-averaged amplitude of eyelid responses gradually increased over the course of the five days of training, indicating that pigs learned to make the association between the LED light CS and the air-puff US. A similar increase was found for the conditioned response (CR) probability: the group-averaged CR probability on session 1 was about 12% and reached a CR probability of 55% on day 5. The latency to CR peak time lacked a temporal preference in the first session, but clearly showed preference from the moment that animals started to show more CRs in session 2 and onwards whereby the eyelid was maximally closed exactly at the moment that the US would be delivered. Conclusion: We concluded that 4-week-old pigs have the capability of performing in a cerebellar classical association learning task, demonstrating for the first time that eyeblink conditioning in young pigs has the potential to be a valuable behavioral tool to measure neurodevelopment.

A Cerebellar Computational Mechanism for Delay Conditioning at Precise Time Intervals

The cerebellum is known to have an important role in sensing and execution of precise time intervals, but the mechanism by which arbitrary time intervals can be recognized and replicated with high precision is unknown. We propose a computational model in which precise time intervals can be identified from the pattern of individual spike activity in a population of parallel fibers in the cerebellar cortex. The model depends on the presence of repeatable sequences of spikes in response to conditioned stimulus input. We emulate granule cells using a population of Izhikevich neuron approximations driven by random but repeatable mossy fiber input. We emulate long-term depression (LTD) and long-term potentiation (LTP) synaptic plasticity at the parallel fiber to Purkinje cell synapse. We simulate a delay conditioning paradigm with a conditioned stimulus (CS) presented to the mossy fibers and an unconditioned stimulus (US) some time later issued to the Purkinje cells as a teaching signal. We show that Purkinje cells rapidly adapt to decrease firing probability following onset of the CS only at the interval for which the US had occurred. We suggest that detection of replicable spike patterns provides an accurate and easily learned timing structure that could be an important mechanism for behaviors that require identification and production of precise time intervals.

Evidence that instrumental conditioning requires conscious awareness in humans

Instrumental conditioning is a crucial substrate of adaptive behaviour, allowing individuals to selectively interact with the stimuli in their environment to maximise benefit and minimise harm. The extent to which complex forms of learning, such as instrumental conditioning, are possible without conscious awareness is a topic of considerable importance and ongoing debate. In light of recent theoretical and empirical contributions casting doubt on the early demonstrations of unconscious instrumental conditioning, we revisit the question of its feasibility in two modes of conditioning. In Experiment 1, we used trace conditioning, following a prominent paradigm (Pessiglione et al., 2008) and enhancing its sensitivity. Success in this task requires participants to learn to approach reward-predictive stimuli and avoid punishment-predictive stimuli through monetary reinforcement. All stimuli were rendered unconscious using forward-backward masking. In Experiment 2, we used delay conditioning to shorten the stimulus-outcome delay, retaining the structure of the original task but presenting the stimuli under continuous flash suppression to allow for an overlap of the stimulus, action, and outcome, as well as replacing monetary reinforcement with primary appetitive reinforcement. In both experiments, we found evidence for absence of unconscious instrumental conditioning, showing that participants were unable to learn to adjust their behaviour to approach positive stimuli and avoid negative ones. This result is consistent with evidence that unconscious stimuli fail to bring about long-term behavioural adaptations, and provides empirical evidence to support theoretical proposals that consciousness might be necessary for adaptive behaviour, where selective action is required.

A Model for Time Interval Learning in The Purkinje Cell

Recent experimental findings indicate that Purkinje cells in the cerebellum represent time intervals by mechanisms other than conventional synaptic weights. This finding adds to the theoretical and experimental observations suggesting the presence of intra-cellular mechanisms for adaptation and processing. To account for these experimental results we developed a biophysical model for time interval learning in a Purkinje cell. The numerical model focuses on a classical delay conditioning task (e.g. eyeblink conditioning) and relies on a few computational steps. In particular, the model posits the activation by the parallel fiber input of a local intra-cellular calcium store which can be modulated by intra-cellular pathways. The reciprocal interaction of the calcium signal with several proteins forming negative and positive feedback loops ensures that the timing of inhibition in the Purkinje cell anticipates the interval between parallel and climbing fiber inputs during training. We show that the model is able to learn along the 150-1000 ms interval range. Finally, we discuss how this model would allow the cerebellum to detect and generate specific spatio-temporal patterns, a classical theory for cerebellar function.Author SummaryThe prevailing view in neurosciences considers synaptic weights between neurons the determinant factor for learning and processing information in the nervous system. Theoretical considerations [1, 2] and experiments [3, 4] examined some potential limitations of this classical paradigm, pointing out that adaptation and computation might also have to rely on other mechanisms besides the learning of synaptic weights. Recent experimental findings [5–7] indicate that Purkinje cells in the cerebellum represent time intervals by mechanisms other than conventional synaptic weights. We propose here a biologically plausible model which complements the modification of synaptic weights for learning one time interval in one synapse of one Purkinje cell. In the model a calcium signal in a small domain keeps track of time. Several molecules read and modify this calcium signal to learn a time interval. We discuss how this model would allow the cerebellum to detect and generate specific patterns in space and time, a classical theory for cerebellar function proposed by Braitenberg [8, 9].

The effects of stimulus distribution form during trace conditioning

Three experiments examined the effect of distribution form of the trace interval on trace conditioning. In Experiments 1 and 2, two groups of rats were conditioned to a fixed-duration conditioned stimulus (CS) in a trace interval procedure; rats in Group Fix received a fixed-duration trace interval, whereas for rats in Group Var the trace interval was of variable duration. Responding during the CS was higher in Group Var than in Group Fix, whereas during the trace interval this difference in responding reversed—Group Fix showed higher response rates than Group Var. Experiment 3 examined whether the greater response rate observed during the CS in Group Var was due to a performance effect or the acquisition of greater associative strength by the CS. Following trace conditioning, the rats from Experiment 1 underwent a second phase of delay conditioning with the same CS; a 5-s auditory stimulus was presented in compound with the last 5 s of the 15-s CS, and the unconditioned stimulus (US) was delivered at the offset of the CSs. On test with the auditory stimulus alone, subjects in Group Var showed lower response rates during the auditory stimulus than subjects in Group Fix. We interpreted these findings as evidence that the superior responding in Group Var during the CS was a result of it acquiring greater associative strength than in Group Fix.

Cortical processing of breathing perceptions in the athletic brain

Athletes regularly endure large increases in ventilation, and accompanying perceptions of breathlessness. While breathing perceptions often correlate poorly with objective measures of lung function in both health and clinical populations, we have previously demonstrated closer matching between subjective breathlessness and changes in ventilation in endurance athletes, suggesting that athletes may be more accurate during respiratory interoception. To better understand the link between exercise and breathlessness, we sought to identify the mechanisms by which the brain processing of respiratory perception might be optimised in athletes.Twenty endurance athletes and 20 sedentary controls underwent 7 Tesla functional magnetic resonance imaging. Inspiratory resistive loading induced conscious breathing perceptions (breathlessness), and a delay-conditioning paradigm was employed to evoke preceding periods of anticipation. Athletes demonstrated anticipatory brain activity that positively correlated with resulting breathing perceptions within key interoceptive areas, such as the thalamus, insula and primary sensorimotor cortices, which was negatively correlated in sedentary controls. Athletes also exhibited greater connectivity between interoceptive attention networks and primary sensorimotor cortex. These functional differences in athletic brains suggest that exercise may optimise processing of respiratory sensations. Future work may probe whether these brain mechanisms are harnessed when exercise is employed to treat breathlessness within chronic respiratory disease.

Active Inference and Learning in the Cerebellum

This letter offers a computational account of Pavlovian conditioning in the cerebellum based on active inference and predictive coding. Using eyeblink conditioning as a canonical paradigm, we formulate a minimal generative model that can account for spontaneous blinking, startle responses, and (delay or trace) conditioning. We then establish the face validity of the model using simulated responses to unconditioned and conditioned stimuli to reproduce the sorts of behavior that are observed empirically. The scheme’s anatomical validity is then addressed by associating variables in the predictive coding scheme with nuclei and neuronal populations to match the (extrinsic and intrinsic) connectivity of the cerebellar (eyeblink conditioning) system. Finally, we try to establish predictive validity by reproducing selective failures of delay conditioning, trace conditioning, and extinction using (simulated and reversible) focal lesions. Although rather metaphorical, the ensuing scheme can account for a remarkable range of anatomical and neurophysiological aspects of cerebellar circuitry—and the specificity of lesion-deficit mappings that have been established experimentally. From a computational perspective, this work shows how conditioning or learning can be formulated in terms of minimizing variational free energy (or maximizing Bayesian model evidence) using exactly the same principles that underlie predictive coding in perception.