Broadband chaos generated by an optoelectronic oscillator.

We study an optoelectronic time-delay oscillator that displays high-speed chaotic behavior with a flat, broad power spectrum. The chaotic state coexists with a linearly stable fixed point, which, when subjected to a finite-amplitude perturbation, loses stability initially via a periodic train of ultrafast pulses. We derive approximate mappings that do an excellent job of capturing the observed instability. The oscillator provides a simple device for fundamental studies of time-delay dynamical systems and can be used as a building block for ultrawide-band sensor networks.

The spatiotemporal dynamics of autobiographical memory: neural correlates of recall, emotional intensity, and reliving.

We sought to map the time course of autobiographical memory retrieval, including brain regions that mediate phenomenological experiences of reliving and emotional intensity. Participants recalled personal memories to auditory word cues during event-related functional magnetic resonance imaging (fMRI). Participants pressed a button when a memory was accessed, maintained and elaborated the memory, and then gave subjective ratings of emotion and reliving. A novel fMRI approach based on timing differences capitalized on the protracted reconstructive process of autobiographical memory to segregate brain areas contributing to initial access and later elaboration and maintenance of episodic memories. The initial period engaged hippocampal, retrosplenial, and medial and right prefrontal activity, whereas the later period recruited visual, precuneus, and left prefrontal activity. Emotional intensity ratings were correlated with activity in several regions, including the amygdala and the hippocampus during the initial period. Reliving ratings were correlated with activity in visual cortex and ventromedial and inferior prefrontal regions during the later period. Frontopolar cortex was the only brain region sensitive to emotional intensity across both periods. Results were confirmed by time-locked averages of the fMRI signal. The findings indicate dynamic recruitment of emotion-, memory-, and sensory-related brain regions during remembering and their dissociable contributions to phenomenological features of the memories.

Spatiotemporal Dynamics of CaMKI During Structural Plasticity of Single Dendritic Spines

Multifunctional calcium/calmodulin dependent protein kinases (CaMKs) are key regulators of spine structural plasticity and long-term potentiation (LTP) in neurons. CaMKs have promiscuous and overlapping substrate recognition motifs, and are distinguished in their regulatory role based on differences in the spatiotemporal dynamics of activity. While the function and activity of CaMKII in synaptic plasticity has been extensively studied, that of CaMKI, another major class of CaMK required for LTP, still remain elusive.

Here, we develop a Förster’s Resonance Energy Transfer (FRET) based sensor to measure the spatiotemporal activity dynamics of CaMK1. We monitored CaMKI activity using 2-photon fluorescence lifetime imaging, while inducing LTP in single dendritic spines of rat (Rattus Norvegicus, strain Sprague Dawley) hippocampal CA1 pyramidal neurons using 2-photon glutamate uncaging. Using RNA-interference and pharmacological means, we also characterize the role of CaMKI during spine structural plasticity.

We found that CaMKI was rapidly and transiently activated with a rise time of ~0.3 s and decay time of ~1 s in response to each uncaging pulse. Activity of CaMKI spread out of the spine. Phosphorylation of CaMKI by CaMKK was required for this spreading and for the initial phase of structural LTP. Combined with previous data showing that CaMKII is restricted to the stimulated spine and required for long-term maintenance of structural LTP, these results suggest that CaMK diversity allows the same incoming signal – calcium – to independently regulate distinct phases of LTP by activating different CaMKs with distinct spatiotemporal dynamics.

Detecting separate time scales in genetic expression data.

BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.

Object files can be purely episodic.

Our ability to track an object as the same persisting entity over time and motion may primarily rely on spatiotemporal representations which encode some, but not all, of an object's features. Previous researchers using the 'object reviewing' paradigm have demonstrated that such representations can store featural information of well-learned stimuli such as letters and words at a highly abstract level. However, it is unknown whether these representations can also store purely episodic information (i.e. information obtained from a single, novel encounter) that does not correspond to pre-existing type-representations in long-term memory. Here, in an object-reviewing experiment with novel face images as stimuli, observers still produced reliable object-specific preview benefits in dynamic displays: a preview of a novel face on a specific object speeded the recognition of that particular face at a later point when it appeared again on the same object compared to when it reappeared on a different object (beyond display-wide priming), even when all objects moved to new positions in the intervening delay. This case study demonstrates that the mid-level visual representations which keep track of persisting identity over time--e.g. 'object files', in one popular framework can store not only abstract types from long-term memory, but also specific tokens from online visual experience.

Imaging Learned Song Representations in Populations of Sensorimotor Neurons Essential to Vocal Communication

Perceiving or producing complex vocalizations such as speech and birdsongs require the coordinated activity of neuronal populations, and these activity patterns can vary over space and time. How learned communication signals are represented by populations of sensorimotor neurons essential to vocal perception and production remains poorly understood. Using a combination of two-photon calcium imaging, intracellular electrophysiological recording and retrograde tracing methods in anesthetized adult male zebra finches (Taeniopygia guttata), I addressed how the bird's own song and its component syllables are represented by the spatiotemporal patterns of activity of two spatially intermingled populations of projection neurons (PNs) in HVC, a sensorimotor area required for song perception and production. These experiments revealed that neighboring PNs can respond at markedly different times to song playback and that different syllables activate spatially intermingled HVC PNs within a small region. Moreover, noise correlation analysis reveals enhanced functional connectivity between PNs that respond most strongly to the same syllable and also provides evidence of a spatial gradient of functional connectivity specific to PNs that project to song motor nucleus (i.e. HVC_RA cells). These findings support a model in which syllabic and temporal features of song are represented by spatially intermingled PNs functionally organized into cell- and syllable-type networks.

Anatomical identification of extracellularly recorded cells in large-scale multielectrode recordings.

This study combines for the first time two major approaches to understanding the function and structure of neural circuits: large-scale multielectrode recordings, and confocal imaging of labeled neurons. To achieve this end, we develop a novel approach to the central problem of anatomically identifying recorded cells, based on the electrical image: the spatiotemporal pattern of voltage deflections induced by spikes on a large-scale, high-density multielectrode array. Recordings were performed from identified ganglion cell types in the macaque retina. Anatomical images of cells in the same preparation were obtained using virally transfected fluorescent labeling or by immunolabeling after fixation. The electrical image was then used to locate recorded cell somas, axon initial segments, and axon trajectories, and these signatures were used to identify recorded cells. Comparison of anatomical and physiological measurements permitted visualization and physiological characterization of numerically dominant ganglion cell types with high efficiency in a single preparation.

Synchrony between sensory and cognitive networks is associated with subclinical variation in autistic traits

© 2015 Young, Smith, Coutlee and Huettel.Individuals with autistic spectrum disorders exhibit distinct personality traits linked to attentional, social, and affective functions, and those traits are expressed with varying levels of severity in the neurotypical and subclinical population. Variation in autistic traits has been linked to reduced functional and structural connectivity (i.e., underconnectivity, or reduced synchrony) with neural networks modulated by attentional, social, and affective functions. Yet, it remains unclear whether reduced synchrony between these neural networks contributes to autistic traits. To investigate this issue, we used functional magnetic resonance imaging to record brain activation while neurotypical participants who varied in their subclinical scores on the Autism-Spectrum Quotient (AQ) viewed alternating blocks of social and nonsocial stimuli (i.e., images of faces and of landscape scenes). We used independent component analysis (ICA) combined with a spatiotemporal regression to quantify synchrony between neural networks. Our results indicated that decreased synchrony between the executive control network (ECN) and a face-scene network (FSN) predicted higher scores on the AQ. This relationship was not explained by individual differences in head motion, preferences for faces, or personality variables related to social cognition. Our findings build on clinical reports by demonstrating that reduced synchrony between distinct neural networks contributes to a range of subclinical autistic traits.

A complex intronic enhancer regulates expression of the CFTR gene by direct interaction with the promoter.

Genes can maintain spatiotemporal expression patterns by long-range interactions between cis-acting elements. The cystic fibrosis transmembrane conductance regulator gene (CFTR) is expressed primarily in epithelial cells. An element located within a DNase I-hypersensitive site (DHS) 10 kb into the first intron was previously shown to augment CFTR promoter activity in a tissue-specific manner. Here, we reveal the mechanism by which this element influences CFTR transcription. We employed a high-resolution method of mapping DHS using tiled microarrays to accurately locate the intron 1 DHS. Transfection of promoter-reporter constructs demonstrated that the element displays classical tissue-specific enhancer properties and can independently recruit factors necessary for transcription initiation. In vitro DNase I footprinting analysis identified a protected region that corresponds to a conserved, predicted binding site for hepatocyte nuclear factor 1 (HNF1). We demonstrate by electromobility shift assays (EMSA) and chromatin immunoprecipitation (ChIP) that HNF1 binds to this element both in vitro and in vivo. Moreover, using chromosome conformation capture (3C) analysis, we show that this element interacts with the CFTR promoter in CFTR-expressing cells. These data provide the first insight into the three- dimensional (3D) structure of the CFTR locus and confirm the contribution of intronic cis-acting elements to the regulation of CFTR gene expression.