A mechanism for the cortical computation of hierarchical linguistic structure

Biological systems often detect species-specific signals in the environment. In humans, speech and language are species-specific signals of fundamental biological importance. To detect the linguistic signal, human brains must form hierarchical representations from a sequence of perceptual inputs distributed in time. What mechanism underlies this ability? One hypothesis is that the brain repurposed an available neurobiological mechanism when hierarchical linguistic representation became an efficient solution to a computational problem posed to the organism. Under such an account, a single mechanism must have the capacity to perform multiple, functionally related computations, e.g., detect the linguistic signal and perform other cognitive functions, while, ideally, oscillating like the human brain. We show that a computational model of analogy, built for an entirely different purpose—learning relational reasoning—processes sentences, represents their meaning, and, crucially, exhibits oscillatory activation patterns resembling cortical signals elicited by the same stimuli. Such redundancy in the cortical and machine signals is indicative of formal and mechanistic alignment between representational structure building and “cortical” oscillations. By inductive inference, this synergy suggests that the cortical signal reflects structure generation, just as the machine signal does. A single mechanism—using time to encode information across a layered network—generates the kind of (de)compositional representational hierarchy that is crucial for human language and offers a mechanistic linking hypothesis between linguistic representation and cortical computatio

A theory of relation learning and cross-domain generalization

People readily generalize knowledge to novel domains and stimuli. We present a theory, instantiated in a computational model, based on the idea that cross-domain generalization in humans is a case of analogical inference over structured (i.e., symbolic) relational representations. The model is an extension of the LISA and DORA models of relational inference and learning. The resulting model learns both the content and format (i.e., structure) of relational representations from non-relational inputs without supervision, when augmented with the capacity for reinforcement learning, leverages these representations to learn individual domains, and then generalizes to new domains on the first exposure (i.e., zero-shot learning) via analogical inference. We demonstrate the capacity of the model to learn structured relational representations from a variety of simple visual stimuli, and to perform cross-domain generalization between video games (Breakout and Pong) and between several psychological tasks. We demonstrate that the model's trajectory closely mirrors the trajectory of children as they learn about relations, accounting for phenomena from the literature on the development of children's reasoning and analogy making. The model's ability to generalize between domains demonstrates the flexibility afforded by representing domains in terms of their underlying relational structure, rather than simply in terms of the statistical relations between their inputs and outputs.Comment: Includes supplemental materia

Poiesis in/between the Transferential Matrix: Insight, Imagination and the Relational Interpretation

The most important question for the Psychoanalytic Process Research is presumably what Mitchell calls the problem of “bootstrapping” the transferential matrix: how do the members of the dyad manage to disengage from being ‘heard’ according to old or unsuitable affective categories? On the grounds of a bi-phasic Conceptual and in-depth Analysis of the Psychoanalytic Complexity literature, I construct a minimal model of the psychoanalytic process as a theoretical context for conducting Process Research. According to the ‘story’ that I have read in the literature four main themes describe the process: a) the gradual emergence of a ‘phenomenological’ language that facilitates the flow of experience, b) the coupling, synchronicity and coordination of analyst and analysand, in ‘phase’ and ‘anti-phase’ at several levels, c) the shifting of the mental states and the thin and delicate slicing and sampling of experience that actualizes the emergence of mental objects and finally, d) Scaling that involves all those ‘mental’ processes that correct for the excesses or the deficiencies that are made evident during the shifting of mental states. Experience is generated as we ‘couple and shift’, and generative tensions appear as we ‘scale’ through this coupling and shifting process. Enactments, role-responsive transferences and countertransferences, testing of the transference and alliance or communication ruptures appear as coupled oscillating patterns that have both a repetitive and a developmental dynamic. Regarding the question of how we should study ‘Coupling, Shifting and Scaling’ I propose the adoption of an Enactivist epistemological framework which perceives the mind not as the workings of a representational machine but as a living process and the expression of an embodied living organism which in a “precarious” state of “needful freedom” (Jonas, in Thompson, 2007) strives to make sense of its environment. On the grounds of this framework I defend the view that we should study Scaling as an expression of the ‘radical dialogicality’ of the human mind that underlies the ‘structuring of experience’. I examine this ‘radical dialogicality’ at the level of inter-hemispheric differences, psychopathology and the enactive structuring of experience and the horizon of affective affordances in the clinical process. Finally, on the grounds of this conceptual analysis and its application to a case-study, I try to defend the view that, adopting relevant “dialogical” and micro-analytic methodological tools, we can achieve an appropriate level of ‘resolution’ so as to study “bootstrapping” at the moment-to-moment shifts in the experiential states or the shifts in attitudes that appear at bifurcation points in the system’s evolution. Through Scaling, the clinical dyad strives for a “maximum grip” of those experiential dimensions that carry the potential to expand the shared reality as a generative field and engage those surfaces of experience that bridge lost connections and separations, by fractalizing the dimensionality of the generative space. A detailed examination of the Scaling processes may bring us closer to a better understanding of the problem of “bootstrapping”

A computational memory and processing model for prosody

Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts & Sciences, 1999.Includes bibliographical references (p. 209-226).This thesis links processing in working memory to prosody in speech, and links different working memory capacities to different prosodic styles. It provides a causal account of prosodic differences and an architecture for reproducing them in synthesized speech. The implemented system mediates text-based information through a model of attention and working memory. The main simulation parameter of the memory model quantifies recall. Changing its value changes what counts as given and new information in a text, and therefore determines the intonation with which the text is uttered. Other aspects of search and storage in the memory model are mapped to the remainder of the continuous and categorical features of pitch and timing, producing prosody in three different styles: for small recall values, the exaggerated and sing-song melodies of children's speech; for mid-range values, an adult expressive style; for the largest values, the prosody of a speaker who is familiar with the text, and at times sounds bored or irritated. In addition, because the storage procedure is stochastic, the prosody from simulation to simulation varies, even for identical control parameters. As with with human speech, no two renditions are alike. Informal feedback indicates that the stylistic differences are recognizable and that the prosody is improved over current offerings. A comparison with natural data shows clear and predictable trends although not at significance. However, a comparison within the natural data also did not produce results at significance. One practical contribution of this work is a text mark-up schema consisting of relational annotations to grammatical structures. Another is the product - varied and plausible prosody in synthesized speech. The main theoretical contribution is to show that resource-bound cognitive activity has prosodic correlates, thus providing a rationale for the individual and stylistic differences in melody and rhythm that are ubiquitous in human speech.by Janet Elizabeth Cahn.Ph.D

Attention Restraint, Working Memory Capacity, and Mind Wandering: Do Emotional Valence or Intentionality Matter?

Attention restraint appears to mediate the relationship between working memory capacity (WMC) and mind wandering (Kane et al., 2016). Prior work has identifed two dimensions of mind wandering—emotional valence and intentionality. However, less is known about how WMC and attention restraint correlate with these dimensions. Te current study examined the relationship between WMC, attention restraint, and mind wandering by emotional valence and intentionality. A confrmatory factor analysis demonstrated that WMC and attention restraint were strongly correlated, but only attention restraint was related to overall mind wandering, consistent with prior fndings. However, when examining the emotional valence of mind wandering, attention restraint and WMC were related to negatively and positively valenced, but not neutral, mind wandering. Attention restraint was also related to intentional but not unintentional mind wandering. Tese results suggest that WMC and attention restraint predict some, but not all, types of mind wandering

College of Arts and Sciences

Cornell University Courses of Study Vol. 91 1999/200