Interneuron precursor transplants in adult hippocampus reverse psychosis-relevant features in a mouse model of hippocampal disinhibition.

GABAergic interneuron hypofunction is hypothesized to underlie hippocampal dysfunction in schizophrenia. Here, we use the cyclin D2 knockout (Ccnd2(-/-)) mouse model to test potential links between hippocampal interneuron deficits and psychosis-relevant neurobehavioral phenotypes. Ccnd2(-/-) mice show cortical PV(+) interneuron reductions, prominently in hippocampus, associated with deficits in synaptic inhibition, increased in vivo spike activity of projection neurons, and increased in vivo basal metabolic activity (assessed with fMRI) in hippocampus. Ccnd2(-/-) mice show several neurophysiological and behavioral phenotypes that would be predicted to be produced by hippocampal disinhibition, including increased ventral tegmental area dopamine neuron population activity, behavioral hyperresponsiveness to amphetamine, and impairments in hippocampus-dependent cognition. Remarkably, transplantation of cells from the embryonic medial ganglionic eminence (the major origin of cerebral cortical interneurons) into the adult Ccnd2(-/-) caudoventral hippocampus reverses these psychosis-relevant phenotypes. Surviving neurons from these transplants are 97% GABAergic and widely distributed within the hippocampus. Up to 6 mo after the transplants, in vivo hippocampal metabolic activity is lowered, context-dependent learning and memory is improved, and dopamine neuron activity and the behavioral response to amphetamine are normalized. These findings establish functional links between hippocampal GABA interneuron deficits and psychosis-relevant dopaminergic and cognitive phenotypes, and support a rationale for targeting limbic cortical interneuron function in the prevention and treatment of schizophrenia.

Therapeutic hypothermia and hypoxia-ischemia in the term-equivalent neonatal rat: characterization of a translational preclinical model.

BACKGROUND: Hypoxic-ischemic encephalopathy (HIE) is a major cause of morbidity in survivors. Therapeutic hypothermia (TH) is the only available intervention, but the protection is incomplete. Preclinical studies of HIE/TH in the rodent have relied on the postnatal day (P) 7 rat whose brain approximates a 32-36 wk gestation infant, less relevant for these studies. We propose that HIE and TH in the term-equivalent P10 rat will be more translational. METHODS: P10-11 rat pups were subjected to unilateral hypoxia-ischemia (HI) and 4 h recovery in normothermic (N) or hypothermic (TH) conditions. Brain damage was assessed longitudinally at 24 h, 2 wk, and 12 wk. Motor function was assessed with the beam walk; recognition memory was measured by novel object recognition. RESULTS: Neuroprotection with TH was apparent at 2 and 12 wk in both moderately and severely damaged animals. TH improved motor function in moderate, but not severe, damage. Impaired object recognition occurred with severe damage with no evidence of protection of TH. CONCLUSION: This adaptation of the immature rat model of HI provides a reproducible platform to further study HIE/TH in which individual animals are followed up longitudinally to provide a useful translational preclinical model.

A Statistical Foundation for Derived Attention.

According to the theory of derived attention, organisms attend to cues with strong associations. Prior work has shown that - combined with a Rescorla-Wagner style learning mechanism - derived attention explains phenomena such as learned predictiveness, inattention to blocked cues, and value-based salience. We introduce a Bayesian derived attention model that explains a wider array of results than previous models and gives further insight into the principle of derived attention. Our approach combines Bayesian linear regression with the assumption that the associations of any cue with various outcomes share the same prior variance, which can be thought of as the inherent importance of that cue. The new model simultaneously estimates cue-outcome associations and prior variance through approximate Bayesian learning. A significant cue will develop large associations, leading the model to estimate a high prior variance and hence develop larger associations from that cue to novel outcomes. This provides a normative, statistical explanation for derived attention. Through simulation, we show that this Bayesian derived attention model not only explains the same phenomena as previous versions, but also retrospective revaluation. It also makes a novel prediction: inattention after backward blocking. We hope that further development of the Bayesian derived attention model will shed light on the complex relationship between uncertainty and predictiveness effects on attention.

Explaining the Return of Fear with Revised Rescorla-Wagner Models.

Exposure therapy - exposure to a feared stimulus without harmful consequences - can reduce fear responses in many mental disorders. However, such relief is often partial and temporary: fear can return after the therapy has ended. Conditioning research has identified three mechanisms for the return of fear, viz. change in physical context (renewal), the passage of time (spontaneous recovery), and an encounter with the fear-producing unconditioned stimulus (reinstatement). To understand why fear returns and thereby develop more effective therapies, we develop mathematical learning models based on that of Rescorla and Wagner. According to this model, context cues present during extinction become conditioned inhibitors (i.e. safety signals) which prevent total erasure of the threat association. Adding various mechanisms to the model allows it to explain different facets of the return of fear. Among these mechanisms is decay of inhibitory associations, which provides a novel explanation for spontaneous recovery. To make the benefits of exposure robust and permanent, one must minimize the degree to which the extinction context becomes inhibitory in order to maximize unlearning. We simulate several experimental paradigms that reduce the return of fear and explain them according to this principle.

Dissecting EXIT.

Kruschke's EXIT model (Kruschke, 2001b) has been very successful in explaining a variety of learning phenomena by means of selective attention. In particular, EXIT produces learned predictiveness effects (Le Pelley & McLaren, 2003), the inverse base rate effect (Kruschke, 1996; Medin & Edelson, 1988), inattention after blocking (Beesley & Le Pelley, 2011; Kruschke & Blair, 2000), differential cue use across the stimulus space (Aha & Goldstone, 1992) and conditional learned predictiveness effects (Uengoer, Lachnit, Lotz, Koenig, & Pearce, 2013). We dissect EXIT into its component mechanisms (error-driven learning, selective attention, attentional competition, rapid attention shifts and exemplar mediation of attention) and test whether simplified versions of EXIT can explain the same experimental results as the full model. Most phenomena can be explained by either rapid attention shifts or attentional competition, without the need for combining them as in EXIT. There is little evidence for exemplar mediation of attention when people learn linearly separable category structures (e.g. Kruschke & Blair, 2000; Le Pelley & McLaren, 2003); whether or not it is needed for non-linear categories depends on stimulus representation (Aha & Goldstone, 1992; Uengoer et al., 2013). On the whole, we believe that attentional competition-embodied in a model which we dub CompAct-offers the simplest explanation for the experimental results we examine.