Dynamics of cognition

Abstract

The application of dynamical systems methods and concepts to cognitive phenomena has broadened the range of testable hypotheses and theoretical narratives available to cognitive scientists. Most research in cognitive dynamics tests the degree to which observed cognitive performance is consistent with one or another core phenomena associated with complex dynamical systems, such as tests for phase transitions, coupling among processes, or scaling laws. Early applications of dynamical systems theory to perceptual-motor performance and developmental psychology paved the way for more recent applications of dynamical systems analyses, models, and theoretical concepts in areas such as learning, memory, speech perception, decision making, problem solving, and reading, among others. Reviews of the empirical results of both foundational and contemporary cognitive dynamics are provided. © 2012 John Wiley & Sons, Ltd. How to cite this article:WIREs Cogn Sci 2012, 3:593-606. doi: 10.1002/wcs.1200 INTRODUCTION Adynamical system is simply one that changes over time (see Box 1). It is apparent that many of the processes cognitive scientists study-development, learning, the spread of activation in a semantic network, changing patterns of cortical activity, motor behavior, and so on-are intrinsically dynamical. Dynamical systems theory supplies new tools and concepts for understanding these and other cognitive phenomena. The theory offers a full complement of analytical methods (e.g., nonlinear time series analyses) and modeling strategies (e.g., differential equations). Most importantly, it motivates novel theoretical and empirical questions: One may explore the relative stability of a cognitive activity, test for meta-or multi-stability, or test for empirical patterns consistent with scaling behavior, emergence, and self-organization.These kinds of questions complement those posed by mainstream cognitive science-which traditionally has emphasized static properties of mind such as symbolic representations or structural mechanisms of information processing-by focusing explicitly on change 1-9 (see, e.g., Elman 10 for a dynamical interpretation of connectionist models). Much work in cognitive dynamics was inspired by parallel * Correspondence to: michael.riley@uc.edu Center for Cognition, Action, & Perception, Department of Psychology, University of Cincinnati, Cincinnati, OH, USA efforts to understand the dynamics of perceptionaction. [11][12][13][14][15] Early and significant progress emerged in the domain of motor coordination, where the behavioral phenomena were more obviously dynamical and high-resolution measurement technologies were more readily available. 16 The dynamical account of interlimb rhythmic coordination 12,14 is an example of an early success.Research in cognitive dynamics is often allied with some version of embodiment. [17][18][19][20][21] Dynamical systems were sometimes framed as replacements for computational-representational accounts, 8,19 as distinct but complementary, 22 or even as consistent with inform...

Studying micro RNA Function and Dysfunction in Alzheimer’s Disease

“…Indeed, accumulating data indicate that miRNAs are playing an expanding role from neuro-regeneration to neuro-degeneration in human brain development and neurological disorders (Rogaev, 2005; Lukiw and Pogue, 2007; Lukiw et al, 2008, 2011; Pogue et al, 2011; Li et al, 2012; Lukiw and Alexandrov, 2012). The characterization of RNA complexity in short PMI human brain tissues is highly informative, even though miRNA stability may be a real concern in data and bioinformatics analysis (Lukiw et al, 1992, 1998; Cui et al, 2005, 2010a; Lukiw, 2007b; Lukiw and Pogue, 2007; Sethi and Lukiw, 2009; Rüegger and Großhans, 2012; Zhang et al, 2012). Interestingly, whole nuclei isolated from human brain tissues with PMI’s of up to 3–4 h efficiently support run-on gene transcription, an effect that is inhibited using the octapeptide RNAPII nt incorporation and translocation inhibitor α-amanitin (Lukiw et al, 1998; Cui et al, 2005; Lukiw and Pogue, 2007).…”

“…Although amyloid over-expressing transgenic-AD (Tg-AD) murine models are informative, no adequate Tg-AD animal model currently exists that recapitulates all features of AD (Oakley et al, 2006; Ashe and Zahs, 2010; Philipson et al, 2010; Alexandrov et al, 2011; Li et al, 2011a,b). Analysis of miRNA array and Northern-blot-based tracking of specific miRNA abundances and decay kinetics in human neuronal-glial cells in primary co-culture and in short post-mortem interval (PMI, ∼1 h) human brain tissues reveals a limited stability and relatively short half-life for many brain-enriched miRNAs of 3 h or less (Lukiw et al, 1992; Lukiw, 2007b; Sethi and Lukiw, 2009; Cui et al, 2010a; Rüegger and Großhans, 2012; Zhang et al, 2012). The relatively high content of A + U ribonucleotides, AU and UA dinucleotide sequences, and small size in these sncRNAs further support the idea that miRNAs are relatively unstable signaling molecules (Sethi and Lukiw, 2009; Lukiw, 2012b; Rüegger and Großhans, 2012; Zhang et al, 2012).…”

“…Analysis of miRNA array and Northern-blot-based tracking of specific miRNA abundances and decay kinetics in human neuronal-glial cells in primary co-culture and in short post-mortem interval (PMI, ∼1 h) human brain tissues reveals a limited stability and relatively short half-life for many brain-enriched miRNAs of 3 h or less (Lukiw et al, 1992; Lukiw, 2007b; Sethi and Lukiw, 2009; Cui et al, 2010a; Rüegger and Großhans, 2012; Zhang et al, 2012). The relatively high content of A + U ribonucleotides, AU and UA dinucleotide sequences, and small size in these sncRNAs further support the idea that miRNAs are relatively unstable signaling molecules (Sethi and Lukiw, 2009; Lukiw, 2012b; Rüegger and Großhans, 2012; Zhang et al, 2012). AU-rich elements (AREs) are known predictors of mRNA half-life and, analogous to mRNA stabilities, there appears to be a significant correlation between the rate of miRNA decay and AU + UA dinucleotide content of brain miRNA ( r 2  ∼ 0.95, N  = 72; Chen and Shyu, 1995; Mattick and Makunin, 2005; Mehler and Mattick, 2007; Sethi and Lukiw, 2009).…”

“…However these observations should be interpreted with caution as ribonucleotide sequence-specific miRNA binding proteins might be expected to interact with and protect mature miRNAs from impending nucleolytic attack, thus extending their half-lives and adding yet another layer of complexity to miRNA-mediated gene regulation. To date all cumulative data suggests that unless specifically stabilized, certain brain-enriched miRNAs represent a relatively rapidly executed signaling system employing highly transient effectors of central nervous system (CNS) gene expression (Sethi and Lukiw, 2009; Rüegger and Großhans, 2012; Zhang et al, 2012). In past and ongoing studies we have therefore focused only on the analysis of up-regulated miRNAs as down-regulation of miRNA abundance may be, in part, a consequence of their relatively short half-life, and uncontrolled and rapid degradation, especially in human post-mortem tissues with difficult-to-control variability in agonal processes and related effects of dying human brain tissues on biomolecular integrity (Figure 2; Chen and Shyu, 1995; Lukiw et al, 1998, 2012b; Cui et al, 2005; Mattick and Makunin, 2005; Mehler and Mattick, 2007; Sethi and Lukiw, 2009; Lukiw, 2012b; Lukiw and Alexandrov, 2012; Rüegger and Großhans, 2012; Zhang et al, 2012).…”

“… miRNA stability – (A) RNA integrity number (RIN) versus post-mortem interval (PMI); the correlation of RNA integrity to a positive RIN number is statistically highly significant ( r 2  ∼ 0.95; N  = 72); (B) Half-life of several selected miRNAs; the content, position and 5′–3′orientation of A and U ribonucleotides, and AU-rich elements (AREs) appears to affect miRNA stability, with half-lives generally in the range of 1–7 h (see Sethi and Lukiw, 2009; Rüegger and Großhans, 2012; Zhang et al, 2012) .…”