Time for Zebrafish

Squire and colleagues have proposed that trace and delay eyeblink conditioning are fundamentally different kinds of learning: trace conditioning requires acquisition of a conscious declarative memory for the stimulus contingencies whereas delay conditioning does not. Declarative memory in trace conditioning is thought to generate conditioned responding through the activation of a conscious expectancy for when the unconditioned stimulus (US) is going to occur. Perruchet (1985) has previously shown that in a 50% partial reinforcement design it is possible to dissociate single cue delay eyeblink conditioning from conscious expectancy for the US by examining performance over runs of reinforced and nonreinforced trials. Clark, Manns, and Squire (2001) claim that this dissociation does not occur in trace eyeblink conditioning. In the present experiment we examined the Perruchet effect for short, moderate, and long trace intervals (600, 1000, and 1400 ms) and for the equivalent interstimulus intervals (ISIs) in a delay conditioning procedure. We found evidence for a dissociation of eyeblink CRs and US expectancy over runs regardless of whether there was a delay or a trace arrangement of cues. The reasons for the Perruchet effect are still unclear, but the present data suggest that it does not depend on a separate nondeclarative system of the type proposed by Squire and colleagues.

The Role of the Hippocampus in Trace Conditioning: Temporal Discontinuity or Task Difficulty?

Fishes rely on the neuromasts of their lateral line system to detect water flow during behaviors such as predator avoidance and prey localization. While the pattern of neuromast development has been a topic of detailed research, we still do not understand the functional consequences of its organization. Previous work has demonstrated somatotopy in the posterior lateral line, whereby afferent neurons that contact more caudal neuromasts project more dorsally in the hindbrain than those that contact more rostral neuromasts. Recently, patch clamp recordings of posterior lateral line afferent neurons in larval zebrafish (Danio rerio) show that larger cells are born earlier, have a lower input resistance, a lower spontaneous firing rate, and tend to contact multiple neuromasts located closer to the tail than smaller neurons, which are born later, have a higher input resistance, a higher spontaneous firing rate, and tend to contact single neuromasts. These data indicate that early-born neurons are poised to detect large stimuli during the initial stages of development. Later-born neurons are more easily driven to fire and thus likely to be more sensitive to local, weaker flows. Afferent projections onto identified glutamatergic regions in the hindbrain suggest a novel mechanism for lateral line somatotopy, where afferent fibers associated with tail neuromasts respond to stronger stimuli and contact dorsal hindbrain regions associated with Mauthner-mediated escape responses and fast, avoidance swimming. The ability to process flow stimuli by circumventing higher order brain centers would ease the task of processing where speed is of critical importance.

Sensory systems convey environmental information to the brain. A comprehensive description of neuronal anatomy and connectivity is essential to understand how sensory information is acquired, transmitted, and processed. Here we describe a high-resolution live imaging technique to quantify the architecture of sensory neurons in larval zebrafish. This approach is ideal to assess neuronal-circuit plasticity and regeneration.

Effects of hippocampal manipulations on the classically conditioned nictitating membrane response: Simulations by an attentional-associative model

The too few mutant selectively affects subgroups of monoaminergic neurons in the zebrafish forebrain

Previous functional magnetic resonance imaging (fMRI) studies with human subjects have explored the neural substrates involved in forming associations in Pavlovian fear conditioning. Most of these studies used delay procedures, in which the conditioned stimulus (CS) and unconditioned stimulus (UCS) coterminate. Less is known about brain regions that support trace conditioning, a procedure in which an interval of time (trace interval) elapses between CS termination and UCS onset. Previous work suggests significant overlap in the neural circuitry supporting delay and trace fear conditioning, although trace conditioning requires recruitment of additional brain regions. In the present event-related fMRI study, skin conductance and continuous measures of UCS expectancy were recorded concurrently with whole-brain blood oxygenation level-dependent (BOLD) imaging during direct comparison of delay and trace discrimination learning. Significant activation was observed within the visual cortex for all CSs. Anterior cingulate and medial thalamic activity reflected associative learning common to both delay and trace procedures. Activations within the supplementary motor area (SMA), frontal operculum, middle frontal gyri, and inferior parietal lobule were specifically associated with trace interval processing. The hippocampus displayed BOLD signal increases early in training during all conditions; however, differences were observed in hippocampal response magnitude related to the accuracy of predicting UCS presentations. These results demonstrate overlapping patterns of activation within the anterior cingulate, medial thalamus, and visual cortex during delay and trace procedures, with additional recruitment of the hippocampus, SMA, frontal operculum, middle frontal gyrus, and inferior parietal lobule during trace conditioning. These data suggest that the hippocampus codes temporal information during trace conditioning, whereas brain regions supporting working memory processes maintain the CS-UCS representation during the trace interval.

In trace fear conditioning a conditional stimulus (CS) predicts the occurrence of the unconditional stimulus (UCS), which is presented after a brief stimulus free period (trace interval)1. Because the CS and UCS do not co-occur temporally, the subject must maintain a representation of that CS during the trace interval. In humans, this type of learning requires awareness of the stimulus contingencies in order to bridge the trace interval2-4. However when a face is used as a CS, subjects can implicitly learn to fear the face even in the absence of explicit awareness*. This suggests that there may be additional neural mechanisms capable of maintaining certain types of "biologically-relevant" stimuli during a brief trace interval. Given that the amygdala is involved in trace conditioning, and is sensitive to faces, it is possible that this structure can maintain a representation of a face CS during a brief trace interval. It is challenging to understand how the brain can associate an unperceived face with an aversive outcome, even though the two stimuli are separated in time. Furthermore investigations of this phenomenon are made difficult by two specific challenges. First, it is difficult to manipulate the subject's awareness of the visual stimuli. One common way to manipulate visual awareness is to use backward masking. In backward masking, a target stimulus is briefly presented (< 30 msec) and immediately followed by a presentation of an overlapping masking stimulus5. The presentation of the mask renders the target invisible6-8. Second, masking requires very rapid and precise timing making it difficult to investigate neural responses evoked by masked stimuli using many common approaches. Blood-oxygenation level dependent (BOLD) responses resolve at a timescale too slow for this type of methodology, and real time recording techniques like electroencephalography (EEG) and magnetoencephalography (MEG) have difficulties recovering signal from deep sources. However, there have been recent advances in the methods used to localize the neural sources of the MEG signal9-11. By collecting high-resolution MRI images of the subject's brain, it is possible to create a source model based on individual neural anatomy. Using this model to "image" the sources of the MEG signal, it is possible to recover signal from deep subcortical structures, like the amygdala and the hippocampus*.

Classical (trace) conditioning is a specific variant of associative learning in which a neutral stimulus leads to the subsequent prediction of an emotionally charged or noxious stimulus after a temporal gap. When conditioning is concurrent with a distraction task, only participants who can report the relationship (the contingency) between stimuli explicitly show associative learning. This suggests that consciousness is a prerequisite for trace conditioning. We review and question three main controversies concerning this view. Firstly, virtually all animals, even invertebrate sea slugs, show this type of learning; secondly, unconsciously perceived stimuli may elicit trace conditioning; and thirdly, some vegetative state patients show trace learning. We discuss and analyze these seemingly contradictory arguments to find the theoretical boundaries of consciousness in classical conditioning. We conclude that trace conditioning remains one of the best measures to test conscious processing in the absence of explicit reports.

Impact of fornix lesions on tone-off delay vs tone-on trace eyeblink conditioning in rats

Temporal contiguity between conditioned (CS) and unconditioned stimuli (US) is a crucial factor in Pavlovian learning, yet little is known about its role in appetitive conditioning and extinction. In a within-subject design, 60 participants underwent both a delay (DC) and trace conditioning (TC) session with partial reinforcement (75%) by monetary rewards (US) and varying interval between CS offset and US onset (DC: 0s; TC: 4s). In addition to self-report indices (reward expectancy, arousal, valence), psychophysiological markers (pupil dilation, heart-period and startle reflex modulation) were recorded during acquisition and extinction training. For most measures, significant differential conditioned responses emerged, irrespective of temporal contiguity, with no major differences observed between TC and DC during acquisition (except for potentially diminished startle attenuation in TC). Despite overall similar patterns in conditioned responding (with small to moderate effects on physiological measures), there was no intraindividual concordance between sessions, yet evidence for differential TC effects on extinction learning. Specifically, smaller reductions in differential reward expectancy, heart-period deceleration and startle modulation after extinction in TC suggested relatively diminished extinction learning. Conditioned pupil dilation (0–2 s after CS onset) remained comparatively stable. Taken together, our findings extend evidence of differences in underlying learning mechanisms between TC and DC to the context of reward learning.

Pharmacological dissociation of trace and long-delay fear conditioning in young rats

A food-associated CS activates c-Fos in VTA DA neurons and elicits conditioned approach

In four experiments, it was shown that the onset and offset of a tone conditioned stimulus (CS) in trace conditioning interact in much the same way as a sequence of two stimuli from different sensory sources, such as a tone and a light. The duration of the tone was manipulated across values ranging from 400 to 30,000 msec, whereas the trace interval between the tone offset and the US was fixed at 400 msec. The rate and level of total CR acquisition were high and constant across all tone durations. Likewise, responding during the trace interval on paired trials was relatively constant. However, when the tone onset and tone offset were tested in relative isolation from each other on test trials using a 30,000-msec tone, there was a reciprocal relationship in responding to tone onset and tone offset. When training had been conducted with shorter tone durations, responding to tone onset was only moderate but, nonetheless, higher than responding to tone offset, which was negligible. At the longer tone durations, responding to tone onset declined to lower levels, whereas responding to tone offset rose to a high level equal to the total level of responding. These effects were consistent across manipulations of tone intensity and prior delay conditioning, in which only tone onset could function as a CS. Consequently, the trace CS appears to act as a compound stimulus that engages complex associative processes as well as simple associative processes. The implications of the present results for understanding the susceptibility of trace conditioning to hippocampal damage in the rabbit nictitating membrane preparation are discussed.

Dopamine (DA) neurons of the VTA track cues and rewards to generate a reward prediction error signal during Pavlovian conditioning. Here we explored how these neurons respond to a self-paced, operant task in freely moving mice. The animal could trigger a reward-predicting cue by remaining in a specific location of an operant box for a brief time before moving to a spout for reward collection. VTA DA neurons were identified using DAT-Cre male mice that carried an optrode with minimal impact on the behavioral task. In vivo single-unit recordings revealed transient fast spiking responses to the cue and reward in correct trials, while for incorrect ones the activity paused, reflecting positive and negative error signals of a reward prediction. In parallel, a majority of VTA DA neurons simultaneously encoded multiple actions (e.g., movement velocity, acceleration, distance to goal, and licking) in sustained slow firing modulation. Applying a GLM, we show that such multiplexed encoding of rewarding and motor variables by individual DA neurons was only apparent while the mouse was engaged in the task. Downstream targets may exploit such goal-directed multiplexing of VTA DA neurons to adjust actions to optimize the task's outcome.SIGNIFICANCE STATEMENT VTA DA neurons code for multiple functions, including the reward prediction error but also motivation and locomotion. Here we show that about half of the recorded VTA DA neurons perform multiplexing: they exploit the phasic and tonic activity modes to encode, respectively, the cue/reward responses and motor parameters, most prominently when the mouse engages in a self-paced operand task. VTA non-DA neurons, by contrast, encode motor parameters regardless of task engagement.