Synapse-specific expression of mu opioid receptor long-term depression in the dorsomedial striatum

The dorsal striatum is a brain region involved in action control, with dorsomedial striatum (DMS) mediating goal-directed actions and dorsolateral striatum (DLS) mediating habitual actions. Presynaptic long-term synaptic depression (LTD) plasticity at glutamatergic inputs to dorsal striatum mediates many dorsal striatum-dependent behaviors and disruption of LTD influences action control. Our previous work identified mu opioid receptors (MORs) as mediators of synapse-specific forms of synaptic depression at a number of different DLS synapses. We demonstrated that anterior insular cortex inputs are the sole inputs that express alcohol-sensitive MOR-mediated LTD (mOP-LTD) in DLS. Here, we explore mOP-LTD in DMS using mouse brain slice electrophysiology. We found that contrary to DLS, DMS mOP-LTD is induced by activation of MORs at inputs from both anterior cingulate and medial prefrontal cortices as well as at basolateral amygdala inputs and striatal cholinergic interneuron synapses on to DMS medium spiny neurons, suggesting that MOR synaptic plasticity in DMS is less synapse-specific than in DLS. Furthermore, only mOP-LTD at cortical inputs was sensitive to alcohol’s deleterious effects. These results suggest that alcohol-induced neuroadaptations are differentially expressed in a synapse-specific manner and could be playing a role in alterations of goal-directed and habitual behaviors

An overview of memory: some issues on structures and organization in the legal domain

Lawyers often need to look for previous similar legal cases when analysing new ones. The more previous cases, the more time is spent. Classical search engines execute termbased retrieval, which may miss relevant documents as well as fetch several irrelevant ones, causing lack of useful information and waste of time. Ideally, retrieval should be meaning-based. Humans beings are able to do e cient searches due to their knowledge. Therefore, semantic search requires knowledge. This paper presents a semantic search engine. Along the paper, several issues concerning specially knowledge representation and memory are discussed. A formalism based on models of comprehension is introduced, as well as its motivation. Examples of representation of sentences in natural language from the Legal Domain are provided. The search engine and its architecture, based on domain knowledge, are brie y commented. The main goal is to give legal o ces the opportunity to save time by providing a more suitable document retrieval.Eje: Agentes y Sistemas Inteligentes (ASI)Red de Universidades con Carreras en Informática (RedUNCI

An overview of memory: some issues on structures and organization in the legal domain

Lawyers often need to look for previous similar legal cases when analysing new ones. The more previous cases, the more time is spent. Classical search engines execute termbased retrieval, which may miss relevant documents as well as fetch several irrelevant ones, causing lack of useful information and waste of time. Ideally, retrieval should be meaning-based. Humans beings are able to do e cient searches due to their knowledge. Therefore, semantic search requires knowledge. This paper presents a semantic search engine. Along the paper, several issues concerning specially knowledge representation and memory are discussed. A formalism based on models of comprehension is introduced, as well as its motivation. Examples of representation of sentences in natural language from the Legal Domain are provided. The search engine and its architecture, based on domain knowledge, are brie y commented. The main goal is to give legal o ces the opportunity to save time by providing a more suitable document retrieval.Eje: Agentes y Sistemas Inteligentes (ASI)Red de Universidades con Carreras en Informática (RedUNCI

Query expansion and noise treatment for information retrieval

Most of the search engines available over the Web are based on mathematical approaches | classical techniques in the Information Retrieval area. Thereby, they are suitable for the retrieval of documents containing some or all the terms of a query, though not to retrieve the documents containing the meaning those terms were intended to express. This paper presents some advantages obtained from query expansion with WordNet and noise treatment with knowledge on top of Paraconsistent Logic. Both methods are semantically driven, allowing the retrieval of documents which do not contain any term of the original query. Noise treatment results from the combination of a smooth term comparison with knowledge about term authentication based on behaviors of features in the collection. Although query expansion recurs for every query, noise treatment is part of the indexing mechanism, causing no overhead in queries. The domain is retrieval of ontologies represented in Resource Description Framework.Eje: Agentes y Sistemas Inteligentes (ASI)Red de Universidades con Carreras en Informática (RedUNCI