Pragmatism,Bohr, and the Copenhagen Interpretation of Quantum Mechanics

In this article, we argue that although Bohr's version of the Copenhagen interpretation is in line with several key elements of logical positivism, pragmatism is the closest approximation to a classification of the Copenhagen interpretation, whether or not pragmatists directly influenced the key figures of the interpretation. Pragmatism already encompasses important elements of operationalism and logical positivism, especially the liberalized Carnapian reading of logical positivism. We suggest that some elements of the Copenhagen interpretation, which are in line with logical positivism, are also supported by pragmatism. Some of these elements are empirical realism, fallibilism, holism, and instrumentalism. However, pragmatism goes beyond logical positivism in espousing some other key elements of the Copenhagen interpretation, though imperfectly, such as the correspondence principle, complementarity, and indeterminism.     

A model of amygdala–hippocampal–prefrontal interaction in fear conditioning and extinction in animals

Empirical research has shown that the amygdala, hippocampus, and ventromedial prefrontal cortex (vmPFC) are involved in fear conditioning. However, the functional contribution of each brain area and the nature of their interactions are not clearly understood. Here, we extend existing neural network models of the functional roles of the hippocampus in classical conditioning to include interactions with the amygdala and prefrontal cortex. We apply the model to fear conditioning, in which animals learn physiological (e.g. heart rate) and behavioral (e.g. freezing) responses to stimuli that have been paired with a highly aversive event (e.g. electrical shock). The key feature of our model is that learning of these conditioned responses in the central nucleus of the amygdala is modulated by two separate processes, one from basolateral amygdala and signaling a positive prediction error, and one from the vmPFC, via the intercalated cells of the amygdala, and signaling a negative prediction error. In addition, we propose that hippocampal input to both vmPFC and basolateral amygdala is essential for contextual modulation of fear acquisition and extinction. The model is sufficient to account for a body of data from various animal fear conditioning paradigms, including acquisition, extinction, reacquisition, and context specificity effects. Consistent with studies on lesioned animals, our model shows that damage to the vmPFC impairs extinction, while damage to the hippocampus impairs extinction in a different context (e.g., a different conditioning chamber from that used in initial training in animal experiments). We also discuss model limitations and predictions, including the effects of number of training trials on fear conditioning.     

Word associations contribute to machine learning in automatic scoring of degree of emotional tones in dream reports

Scientific study of dreams requires the most objective methods to reliably analyze dream content. In this context, artificial intelligence should prove useful for an automatic and non subjective scoring technique. Past research has utilized word search and emotional affiliation methods, to model and automatically match human judges’ scoring of dream report’s negative emotional tone. The current study added word associations to improve the model’s accuracy. Word associations were established using words’ frequency of co-occurrence with their defining words as found in a dictionary and an encyclopedia. It was hypothesized that this addition would facilitate the machine learning model and improve its predictability beyond those of previous models. With a sample of 458 dreams, this model demonstrated an improvement in accuracy from 59% to 63% (kappa = .485) on the negative emotional tone scale, and for the first time reached an accuracy of 77% (kappa = .520) on the positive scale.     

Activation of cannabinoid CB1 receptors in the central amygdala impairs inhibitory avoidance memory consolidation via NMDA receptors

In the present study, we investigated the influence of bilateral intra-central amygdala (intra-CeA) microinjections of N-methyl-d-aspartate (NMDA) receptor agents on amnesia induced by a cannabinoid CB1 receptor agonist, arachydonilcyclopropylamide (ACPA). This study used a step-through inhibitory (passive) avoidance task to assess memory in adult male Wistar rats. The results showed that intra-CeA administration of ACPA (2 ng/rat) immediately after training decreased inhibitory avoidance (IA) memory consolidation as evidenced by a decrease in step-through latency on the test day, which was suggestive of drug-induced amnesia. Post-training intra-CeA microinjections of NMDA (0.0001, 0.001 and 0.01 μg/rat) did not affect IA memory consolidation. However co-administration of NMDA with ACPA (2 ng/rat) prevented the impairment of IA memory consolidation that was induced by ACPA. Although post-training intra-CeA administration of the NMDA receptor antagonist, d-(−)-2-amino-5-phosphonopentanoic acid (d-AP5; 0.01, 0.05 and 0.1 μg/rat) alone had no effect, its co-administration with an ineffective dose of ACPA (1 ng/rat) impaired IA memory consolidation. Post-training intra-CeA microinjection of an ineffective dose of d-AP5 (0.01 μg/rat) prevented an NMDA response to the impaired effect of ACPA. These results suggest that amnesia induced by intra-CeA administration of ACPA is at least partly mediated through an NMDA receptor mechanism in the Ce-A.     

A neural model of hippocampal–striatal interactions in associative learning and transfer generalization in various neurological and psychiatric patients

Building on our previous neurocomputational models of basal ganglia and hippocampal region function (and their modulation by dopamine and acetylcholine, respectively), we show here how an integration of these models can inform our understanding of the interaction between the basal ganglia and hippocampal region in associative learning and transfer generalization across various patient populations. As a common test bed for exploring interactions between these brain regions and neuromodulators, we focus on the acquired equivalence task, an associative learning paradigm in which stimuli that have been associated with the same outcome acquire a functional similarity such that subsequent generalization between these stimuli increases. This task has been used to test cognitive dysfunction in various patient populations with damages to the hippocampal region and basal ganglia, including studies of patients with Parkinson’s disease (PD), schizophrenia, basal forebrain amnesia, and hippocampal atrophy. Simulation results show that damage to the hippocampal region—as in patients with hippocampal atrophy (HA), hypoxia, mild Alzheimer’s (AD), or schizophrenia—leads to intact associative learning but impaired transfer generalization performance. Moreover, the model demonstrates how PD and anterior communicating artery (ACoA) aneurysm—two very different brain disorders that affect different neural mechanisms—can have similar effects on acquired equivalence performance. In particular, the model shows that simulating a loss of dopamine function in the basal ganglia module (as in PD) leads to slow acquisition learning but intact transfer generalization. Similarly, the model shows that simulating the loss of acetylcholine in the hippocampal region (as in ACoA aneurysm) also results in slower acquisition learning. We argue from this that changes in associative learning of stimulus–action pathways (in the basal ganglia) or changes in the learning of stimulus representations (in the hippocampal region) can have similar functional effects.     

What Are the Main Differences Between Behavioral and Systems Therapy with Couples? A Critical Account

This paper describes the main differences between behavioral and systems therapy with couples. To improve clinical decision making for a given case, the theoretical assumptions of the chosen treatment approach need to be clearly understood. Contrasting the two approaches will assist couple therapists in providing clinical services that better reflect the chosen theoretical framework. This paper reviews the common elements that can be found across models. A case example is presented to demonstrate the use of the therapy's theories and techniques.     

Generalization as a behavioral window to the neural mechanisms of learning internal models

In generating motor commands, the brain seems to rely on internal models that predict physical dynamics of the limb and the external world. How does the brain compute an internal model? Which neural structures are involved? We consider a task where a force field is applied to the hand, altering the physical dynamics of reaching. Behavioral measures suggest that as the brain adapts to the field, it maps desired sensory states of the arm into estimates of force. If this neural computation is performed via a population code, i.e., via a set of bases, then activity fields of the bases dictate a generalization function that uses errors experienced in a given state to influence performance in any other state. The patterns of generalization suggest that the bases have activity fields that are directionally tuned, but directional tuning may be bimodal. Limb positions as well as contextual cues multiplicatively modulate the gain of tuning. These properties are consistent with the activity fields of cells in the motor cortex and the cerebellum. We suggest that activity fields of cells in these motor regions dictate the way we represent internal models of limb dynamics.