Dopamine (DA) receptor transmission through either D(1) or D(2)-like subtypes is involved critically in the processing of emotional information within the medial prefrontal cortex (mPFC). However the functional role of specific DA D(1)-like receptor transmission in the expression of emotionally salient associative memories (either aversive or rewarding) is not currently understood. Here we demonstrate that specific activation of DA D(1) receptors in the prelimbic (PLC) division of the mPFC causes a transient block in the behavioral expression of both aversive and rewarding associative memories. We report that intra-PLC microinfusions of a selective D(1) receptor agonist block the spontaneous expression of an associative olfactory fear memory, without altering the stability of the original memory trace. Furthermore, using an unbiased place conditioning procedure (CPP), intra-PLC D(1) receptor activation blocks the spontaneous expression of an associative morphine (5 mg/kg; i.p.) reward memory, while leaving morphine-primed memory expression intact. Interestingly, both intra-PLC D(1)-receptor mediated block of either fear-related or reward-related associative memories were dependent upon downstream cyclic-AMP (cAMP) signaling as both effects were rescued by co-administration of a cAMP signaling inhibitor. The blockade of both rewarding and aversive associative memories is mediated through a D(1)-specific signaling pathway, as neither forms of spontaneous memory expression were blocked by intra-PLC microinfusions of a D(2)-like receptor agonist. Our results demonstrate that the spontaneous expression of either rewarding or aversive emotionally salient memories shares a common, D(1)-receptor mediated substrate within the mPFC.
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http://dx.doi.org/10.1016/j.neuropharm.2012.10.029 | DOI Listing |
Hippocampus
January 2025
Center for Systems Neuroscience, Boston University, Boston, Massachusetts, USA.
In keeping with the historical focus of this special issue of Hippocampus, this paper reviews the history of my development of the SPEAR model. The SPEAR model proposes that separate phases of encoding and retrieval (SPEAR) allow effective storage of multiple overlapping associative memories in the hippocampal formation and other cortical structures. The separate phases for encoding and retrieval are proposed to occur within different phases of theta rhythm with a cycle time on the order of 125 ms.
View Article and Find Full Text PDFTop Cogn Sci
December 2024
Department of Linguistics, University of Massachusetts Amherst.
As they process complex linguistic input, language comprehenders must maintain a mapping between lexical items (e.g., morphemes) and their syntactic position in the sentence.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
December 2024
Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) UIB-CSIC, Campus Universitat Illes Balears, Palma de Mallorca 07122, Spain.
Quantum optical networks are instrumental in addressing the fundamental questions and enable applications ranging from communication to computation and, more recently, machine learning (ML). In particular, photonic artificial neural networks (ANNs) offer the opportunity to exploit the advantages of both classical and quantum optics. Photonic neuro-inspired computation and ML have been successfully demonstrated in classical settings, while quantum optical networks have triggered breakthrough applications such as teleportation, quantum key distribution and quantum computing.
View Article and Find Full Text PDFFront Hum Neurosci
December 2024
Department of Psychology and Institute of Neuroscience, University of Nevada, Reno, NV, United States.
The neural underpinnings of working memory (WM) have been of continuous scientific interest for decades. As the understanding of WM progresses and new theories, such as the distributed view of WM, develop, the need to advance the methods used to study WM also arises. This perspective discusses how building from the state-of-the-art in the field of transcranial magnetic stimulation (TMS), and utilising cortico-cortical TMS, may pave the way for testing some of the predictions proposed by the distributed WM view.
View Article and Find Full Text PDFPLoS Comput Biol
December 2024
Department of Psychology, University of California, Berkeley, Berkeley, California, United States of America.
Computational modeling has revealed that human research participants use both rapid working memory (WM) and incremental reinforcement learning (RL) (RL+WM) to solve a simple instrumental learning task, relying on WM when the number of stimuli is small and supplementing with RL when the number of stimuli exceeds WM capacity. Inspired by this work, we examined which learning systems and strategies are used by adolescent and adult mice when they first acquire a conditional associative learning task. In a version of the human RL+WM task translated for rodents, mice were required to associate odor stimuli (from a set of 2 or 4 odors) with a left or right port to receive reward.
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