Research on the Interaction of Genetic Algorithm in Assisted Composition

Computer-aided composition is an attempt to use a formalized process to minimize human (or composer) involvement in the creation of music using a computer. Exploring the problem of computer-aided composition can enable us to understand and simulate the thinking mode of composers in the special process of music creation, which is an important application of artificial intelligence in the field of art. Feature extraction on the MIDI files has been introduced in this paper. Based on the genetic algorithm in this paper, a platform of the sampling coding method to optimize the character representation has solved the traditional algorithmic music composition study. Music directly from the pitch and duration can be derived from the characteristics, respectively, in the form of a one-hot encoding independently said. Failure to the rhythm of the characterization of the pitch and duration are problems that lead to the inability of compositional networks to learn musical styles better. Rhythm is the combination of pitch and time values according to certain rules. The rhythm of music affects the overall style of music. By associating the pitch and time value coding, the rhythm style of music can be preserved better so that the composition network can learn the style characteristics of music more easily.

Sex differences in behavioral responding and dopamine release during early Pavlovian learning

Learning associations between cues and rewards requires the mesolimbic dopamine system. The dopamine response to cues signals differences in reward value in well-trained animals. These value-related dopamine responses are absent during early learning when cues signal differences in the reward rate, which suggests cue-evoked dopamine release conveys differences between outcomes only after extensive training. However, it is unclear if this lack of value coding by cue-evoked dopamine release during early learning is unique to when cues signal differences in reward rate, or if this is also evident when cues signal differences in other value-related parameters such as reward size. To address this, we utilized a Pavlovian conditioning task in which one audio cue was associated with a small reward (one pellet) and another audio cue was associated with a large reward (three pellets). We performed fast-scan cyclic voltammetry to record changes in dopamine release in the nucleus accumbens of male and female rats throughout early learning. Cue-evoked dopamine release did not encode differences in reward value, and there were no differences in this response between males and females. However, female rats exhibited higher levels of conditioned responding and a faster latency to respond. Reward-evoked dopamine release scaled with reward size in both sexes, though there were transient sex differences in the dynamics of this response. We additionally identified sex differences in the number of post-reward head entries. Collectively these data illustrate sustained sex differences in behavioral responding as well as transient sex differences in reward-evoked dopamine release.

Orthogonal but linked neural codes for value

Our ability to effectively choose between dissimilar options implies that information regarding the options values must be available, either explicitly or implicitly, in the brain. Explicit realizations of value involve single neurons whose responses depend on value and not on the specific features that determine it. Implicit realizations, by contrast, come from the coordinated action of neurons that encode specific features. One signature of implicit value coding is that population responses to offers with the same value but different features should occupy semi- or fully orthogonal neural subspaces that are nonetheless linked. Here, we examined responses of neurons in six core value-coding areas in a choice task with risky and safe options. Using stricter criteria than some past studies have used, we find, surprisingly, no evidence for abstract value neurons (i.e., neurons with the response to equally valued risky and safe options) in any of these regions. Moreover, population codes for value resided in orthogonal subspaces; these subspaces were linked through a linear transform of each of their constituent subspaces. These results suggest that in all six regions, populations of neurons embed value implicitly in a distributed population.

Subspace alignment as a mechanism for binding

To choose between options, we must solve two important binding problems. First, the features that determine each options values must be appropriately combined and kept separate from the corresponding features of other options. Second, options must be associated with the specific actions needed to select them. We hypothesized that the brain solves these problems through use of aligned (for bound dimensions) and orthogonal (for separated dimensions) population subspaces. We examined responses of single neurons in six putative value-coding regions in rhesus macaques performing a risky choice task. In all areas, single neurons encode the features that define the value of each option (stakes and probability) but only very weakly encode value per se. However, the coding dimensions associated with these features are aligned on a single subspace, from which a strong emergent value signal can be read out. Moreover, all six regions use nearly orthogonal subspaces for the left and right options, thereby linking options to their position in space, implementing functional partitioning, and reducing the possibility of misbinding. These results provide a new solution to the neuroeconomic binding problems and suggest that other forms of binding may work through similar principles.

Intrinsic and Extrinsic Value in Erin Brockovich Movie Script

This study focused on analyzing intrinsic and extrinsic value in “Erin Brockovich” by Susanah Grant. This study aimed to describe a character's utterance that contains intrinsic and extrinsic values in Erin Brockovich's movie script. There are two sources of data in this study, they are movie scripts from Erin Brockovich's movie as primary data and audiovisual movies as secondary data. Data is collected through Searching and downloading the movie script of Erin Brockovich, reading the script, looking for sentences containing the intrinsic and extrinsic value, taking note of Intrinsic value and extrinsic value, coding the data and rechecking the data. Techniques of Data analysis are done through the presentation of data, explaining and interpreting data, and concluding data. This study indicated that the Erin Brockovich movie script has two values as intrinsic and extrinsic value. First, the intrinsic value is presented in the form of Erin's care to the people at Hinkley. Second, the extrinsic value is presented in the form of PG&E's selfish attitude towards the people at Hinckley. The writer obtained 21 data. 18 intrinsic value data and 3 extrinsic data of intrinsic value found in this movie script meaning that intrinsic value is more dominant than extrinsic value. Intrinsic value is more dominant than the extrinsic value because in this movie script the focus is more on discussing positive actions carried out by the characters in the movie that are helping people by overcoming cases of water pollution.

Contextual gating of motivationally-relevant stimuli in the mouse nucleus accumbens

Neural activity in the nucleus accumbens (NAc) is thought to track fundamentally value- centric quantities such as current or future expected reward, reward prediction errors, the value of work, opportunity cost, and approach vigor. However, the NAc also contributes to flexible behavior in ways that are difficult to explain based on value signals alone, raising the question of if and how non-value signals are encoded in NAc. We recorded NAc neural ensembles while head-fixed mice performed a context-dependent odor discrimination task, and extracted single-unit and population-level correlates of task features. We found coding for context-setting cues that modulate the stimulus-outcome association of subsequently presented reward-predictive cues. This context signal occupied a subspace orthogonal to classic value representations, suggesting that it does not interfere with value-related NAc output. Finally, we show that the context signal is predictive of subsequent value coding, supporting a circuit-level gating model for how the NAc contributes to behavioral flexibility and providing a novel population-level perspective from which to view NAc computations.

Assembling and disassembling

“Towards the end of the first decade of the twenty-first century”, as Anthony Gardner and Charles Green propose, “biennials became self-conscious.” Increasingly they are reflecting on themselves as "hegemonic machines" (Oliver Marchart), and for this very reason also understand themselves as places of intervention. We have to come to terms with the fact that biennials today are both: "Brands and Sites of Resistance", "Spaces of Capital and Hope" (Panos Kompatsiaris).The article follows withdrawals and protests as well as interventions and strategies of appropriation of biennials in the second decade of the 21st century. Protests in St. Petersburg, Sydney and New York shape the biennials they boycott. In Kochi, Athens, Dhaka, and Kassel we encounter curatorial projects that challenge the apparatus of value coding. The relationship between bottom up and top down often becomes blurred. In Prague, Warsaw, Kiev, and Budapest it is even reversed. Here biennials are used as a means of counter-hegemony and institutional survival.

Value signals in orbitofrontal cortex predict economic decisions on a trial-to-trial basis

ABSTRACTNeuroeconomics seeks to explain how neural activity contributes to decision behavior. For value-based decisions, the primate orbitofrontal cortex (OFC) is thought to have a key role; however, the mechanism by which single OFC cells contribute to choices is still unclear. Here, we show for the first time a trial-to-trial relationship between choices and population-level value representations in OFC, defined by the weighted sum of activity from many individual value-coding neurons.