Reward circuitry is perturbed in the absence of the serotonin transporter

The serotonin transporter (SERT) modulates the entire serotonergic system in the brain and influences both the dopaminergic and norepinephrinergic systems. These three systems are intimately involved in normal physiological functioning of the brain and implicated in numerous pathological conditions. Here we use high-resolution magnetic resonance imaging (MRI) and spectroscopy to elucidate the effects of disruption of the serotonin transporter in an animal model system: the SERT knock-out mouse. Employing manganese-enhanced MRI, we injected Mn^(2+) into the prefrontal cortex and obtained 3D MR images at specific time points in cohorts of SERT and normal mice. Statistical analysis of co-registered datasets demonstrated that active circuitry originating in the prefrontal cortex in the SERT knock-out is dramatically altered, with a bias towards more posterior areas (substantia nigra, ventral tegmental area, and Raphé nuclei) directly involved in the reward circuit. Injection site and tracing were confirmed with traditional track tracers by optical microscopy. In contrast, metabolite levels were essentially normal in the SERT knock-out by in vivo magnetic resonance spectroscopy and little or no anatomical differences between SERT knock-out and normal mice were detected by MRI. These findings point to modulation of the limbic cortical–ventral striatopallidal by disruption of SERT function. Thus, molecular disruptions of SERT that produce behavioral changes also alter the functional anatomy of the reward circuitry in which all the monoamine systems are involved

Practice Makes Imperfect: Restorative Effects of Sleep on Motor Learning

Emerging evidence suggests that sleep plays a key role in procedural learning, particularly in the continued development of motor skill learning following initial acquisition. We argue that a detailed examination of the time course of performance across sleep on the finger-tapping task, established as the paradigm for studying the effect of sleep on motor learning, will help distinguish a restorative role of sleep in motor skill learning from a proactive one. Healthy subjects rehearsed for 12 trials and, following a night of sleep, were tested. Early training rapidly improved speed as well as accuracy on pre-sleep training. Additional rehearsal caused a marked slow-down in further improvement or partial reversal in performance to observed levels below theoretical upper limits derived on the basis of early pre-sleep rehearsal. This decrement in learning efficacy does not occur always, but if and only if it does, overnight sleep has an effect in fully or partly restoring the efficacy and actual performance to the optimal theoretically achieveable level. Our findings re-interpret the sleep-dependent memory enhancement in motor learning reported in the literature as a restoration of fatigued circuitry specialized for the skill. In providing restitution to the fatigued brain, sleep eliminates the rehearsal-induced synaptic fatigue of the circuitry specialized for the task and restores the benefit of early pre-sleep rehearsal. The present findings lend support to the notion that latent sleep-dependent enhancement of performance is a behavioral expression of the brain's restitution in sleep

Does Sleep Really Influence Face Recognition Memory?

Mounting evidence implicates sleep in the consolidation of various kinds of memories. We investigated the effect of sleep on memory for face identity, a declarative form of memory that is indispensable for nearly all social interaction. In the acquisition phase, observers viewed faces that they were required to remember over a variable retention period (0–36 hours). In the test phase, observers viewed intermixed old and new faces and judged seeing each before. Participants were classified according to acquisition and test times into seven groups. Memory strength (d′) and response bias (c) were evaluated. Substantial time spent awake (12 hours or more) during the retention period impaired face recognition memory evaluated at test, whereas sleep per se during the retention period did little to enhance the memory. Wakefulness during retention also led to a tightening of the decision criterion. Our findings suggest that sleep passively and transiently shelters face recognition memory from waking interference (exposure) but does not actively aid in its long-term consolidation

Recognition memory for highly significant (S) versus less significant (nS) faces.

<p>Group mean hit rates for highly significant (green bars) and less significant (blue bars) faces (ordinate) are plotted for each individual group (abscissa). Error bars are one s.e.m.</p

12 hr group: Mean speeds.

<p>12 hr group: Mean speeds.</p

Hit rates (HRs) and false alarm rates (FARs).

<p>Hit rates (HRs) and false alarm rates (FARs).</p

Stanford Sleepiness Scale scores.

<p>Stanford Sleepiness Scale scores.</p

Accuracy (error rate) as a function of transition.

<p>A) Post-sleep error rate order, as depicted in shades of gray, across the four transitions of the motor sequence arranged according to pre-sleep order (abscissa) for all forty-four subjects (ordinate). For instance, a white cell in the leftmost column of a row means the corresponding subject had the smallest error rate (highest accuracy) prior to sleep on the particular transition among four but the largest error rate following sleep. Ties, which correspond to multiple transitions sharing the same error rate, are shown in intermediate shades of gray. Inset shows pre-sleep error rates on individual transitions sorted by pre-sleep order. B) Error rates (number of errors / 30 sec trial) on the within-sequence transitions are shown. The transitions were ordered according to increasing error rate (decreasing accuracy) for each subject separately and later combined to yield a group mean and s.e.m., which is shown for pre-sleep (black) and post-sleep trials (red and green). For each subject, the post-sleep transitions were ordered by increasing pre-sleep error rate (green) or by increasing post-sleep error rate (red). In the case where the transitions were sorted by the respective degrees of accuracy, post-sleep error rates (red) were no more uniform statistically than pre-sleep error rates (black).</p

A framework for interpretation of accuracy data.

<p>(A, B) A schematic account of the accuracy data of the 12 hr group is illustrated. Two processes are initiated—a learning process that facilitates performance on the finger tapping task (yellow curve), and fatigue of the neural substrate local to the learning and task (red curve). Observed performance (green curve) is a function of the difference between the two processes (learning – local fatigue). The difference is minimal early on in training (left dashed line), increases sharply to a maximum (middle dashed line), and later settles to an intermediate plateau level (right dashed line). The combined dynamics of the twin processes is qualitatively similar to the true accuracy data shown on the right for comparison. Sleep counteracts the fatigue in the neural circuitry that drives the task, which is exhibited as an overnight latent enhancement on post-sleep test trials the next morning (not shown).</p