The organized mind: how to better structure our time in the age of social media and constant distraction.

The information age is drowning us in a deluge of data, and it is becoming increasingly difficult to separate facts from pseudo-facts, objective from biased sources, and at the same time, we’re all being asked to do more at home and at work. Daniel Levitin reviews the cognitive neuroscience of attention and memory, presents the differences between mind-wandering mode and task-focused mode and offers advice for how to boost creativity and limit exhausting brain-shifting distractions

Metric Spaces of Arbitrary Finitely-Generated Scaling Group

For a metric space $X$ with a compatible measure $\mu$, Genevois and Tessera defined the Scaling Group of $(X,\mu)$ as the subgroup $\Gamma$ of $\mathbb{R}_{>0}$ of positive real numbers $\gamma$ for which there are quasi-isometries of $X$ coarsely scaling $\mu$ by a factor of $\gamma$. We show that for any finitely generated subgroup $\Gamma$ of $\mathbb{R}_{>0}$ there exists a space $N_\Gamma$, bi-Lipschitz equivalent to a graph of finite degree, with scaling group $\Gamma$.Comment: 29 pages, 4 figure

Plans, Takes, and Mis-takes

This paper analyzes what may have been a mistake bypianist Thelonious Monk playing a jazz solo in 1958.Even in a Monk composition designed for patternedmayhem, a note can sound out of pattern. We reframethe question of whether the note was a mistake and askinstead about how Monk handles the problem. Amazingly,he replays the note into a new pattern that resituatesits jarring effect in retrospect. The mistake, orbetter, the mis-take, was “saved” by subsequent notes.Our analysis, supported by reflections from jazz musiciansand the philosopher John Dewey, encourages areformulation of plans, takes, and mis-takes as categoriesfor the interpretation of contingency, surprise, andrepair in all human activities. A final section suggeststhat mistakes are essential to the practical plying andplaying of knowledge into performances, particularlythose that highlight learning

A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks.

Cognitively demanding tasks that evoke activation in the brain's central-executive network (CEN) have been consistently shown to evoke decreased activation (deactivation) in the default-mode network (DMN). The neural mechanisms underlying this switch between activation and deactivation of large-scale brain networks remain completely unknown. Here, we use functional magnetic resonance imaging (fMRI) to investigate the mechanisms underlying switching of brain networks in three different experiments. We first examined this switching process in an auditory event segmentation task. We observed significant activation of the CEN and deactivation of the DMN, along with activation of a third network comprising the right fronto-insular cortex (rFIC) and anterior cingulate cortex (ACC), when participants perceived salient auditory event boundaries. Using chronometric techniques and Granger causality analysis, we show that the rFIC-ACC network, and the rFIC, in particular, plays a critical and causal role in switching between the CEN and the DMN. We replicated this causal connectivity pattern in two additional experiments: (i) a visual attention ''oddball'' task and (ii) a task-free resting state. These results indicate that the rFIC is likely to play a major role in switching between distinct brain networks across task paradigms and stimulus modalities. Our findings have important implications for a unified view of network mechanisms underlying both exogenous and endogenous cognitive control. brain networks ͉ cognitive control ͉ insula ͉ attention ͉ prefrontal cortex O ne distinguishing feature of the human brain, compared with brains lower on the phylogenetic ladder, is the amount of cognitive control available for selecting, switching, and attending to salient events in the environment. Recent research suggests that the human brain is intrinsically organized into distinct functional networks that support these processes (1-4). Analysis of resting-state functional connectivity, using both model-based and model-free approaches, has suggested the existence of at least three canonical networks: (i) a centralexecutive network (CEN), whose key nodes include the dorsolateral prefrontal cortex (DLPFC), and posterior parietal cortex (PPC); (ii) the default-mode network (DMN), which includes the ventromedial prefrontal cortex (VMPFC) and posterior cingulate cortex (PCC); and (iii) a salience network (SN), which includes the ventrolateral prefrontal cortex (VLPFC) and anterior insula (jointly referred to as the fronto-insular cortex; FIC) and the anterior cingulate cortex (ACC) In a recent meta-analysis, Dosenbach and colleagues hypothesized that several brain regions that overlap with the CEN and SN are important for multiple cognitive control functions, including initiation, maintenance, and adjustment of attention (7). However, no studies to date have directly assessed the temporal dynamics and causal interactions of specific nodes within the CEN, SN, and DMN. Converging evidence from a number of brain imaging studies across several task domains suggests that the FIC and ACC nodes of the SN, in particular, respond to the degree of subjective salience, whether cognitive, homeostatic, or emotional We used three functional magnetic resonance imaging (fMRI) experiments to examine the interaction between the SN, CEN, and DMN, with particular interest in the role of the FIC/ACC in regulating these networks. In the first experiment, we scanned 18 participants as they listened with focused attention to classical music symphonies inside the scanner. We analyzed brain responses during the occurrence of ''movement transitions:'' salient, orienting events arising from transitions between adjacent ''movements'' in the music (19). To specifically elucidate the role of the FIC in driving network changes, we used chronometry and Granger Causality Analysis (GCA), to provide information about the dynamics and directionality of signaling in cortical circuits In the second experiment, we investigated the generality of network switching mechanisms involving the FIC by examining brain responses elicited during a visual "oddball" attention task (23). A third experiment examined whether the network switching mechanism could be observed during task-free resting state where there was no overt task and no behavioral response (4). Our motivation for examining the resting-state fMRI data was the recent finding, based on computer simulation of large-scale brain networks, that even in the absence of external stimuli, certain nodes can regulate other nodes and function as hubs (24). NEUROSCIENCE Our aim was to test the hypothesis that common network switching mechanisms apply across tasks with varying cognitive demands and differing stimulus modalities. If confirmed, our findings would provide insights into fundamental control mechanisms in the human brain. Results We describe findings from Experiment 1 in the first three sections. Convergent findings from Experiments 2 and 3 are described subsequently. Activation of CEN and SN, and Deactivation of DMN During Auditory Event Segmentation. As reported previously (19), we found robust right-lateralized activation in the DLPFC, PPC, and FIC during ''movement transitions'' in the auditory event segmentation task. Here, we extend these findings to characterize network-specific responses in the CEN, DMN, and SN. Activations in the CEN and SN were found to be accompanied by robust deactivation in the DMN at the movement transition [ Latency Analysis Reveals Early Activation of the rFIC Relative to the CEN and DMN. First, we identified differences in the latency of the event-related fMRI responses across the entire brain using the method developed by Henson and colleagues (26). Briefly, this method provides a way to estimate the peak latency of the BOLD response at each voxel using the ratio of the derivative to canonical parameter estimates (see SI Materials and Methods for details). This analysis revealed that the event-related fMRI signal in the right FIC (rFIC) and ACC peaks earlier compared to the signal in the nodes of the CEN and DMN, indicating that the neural responses in the rFIC and ACC precede the CEN and DMN (see GCA Reveals that the rFIC Is a Causal Outflow Hub at the Junction of the CEN and DMN. Finally, to elucidate the dynamic interactions between the three networks we applied GCA. Briefly, GCA detects causal interactions between brain regions by assessing the Activations height and extent thresholded at the P Ͻ 0.001 level (uncorrected). The ICA prunes out extraneous activation and deactivation clusters visible in the GLM analysis to reveal brain regions that constitute independent and tightly coupled networks. Fig. 3. Granger causality analysis (GCA) of the six key nodes of the Salience (blue nodes), Central-Executive (green nodes) and Default-Mode (yellow nodes) networks during (A) auditory event segmentation, (B) visual oddball attention task, and (C) task-free resting state. GCA revealed significant causal outflow from the rFIC across tasks and stimulus modalities. In each subfigure, the thickness of the connecting arrows between two regions corresponds to the strength of directed connection (F-value) normalized by the maximum F-value between any pair of regions for that task (''raw'' F-values reported in NEUROSCIENCE shorter path length than all of the other regions except the VMPFC (t test, P Ͻ 0.05); however, these differences did not remain significant after multiple comparison correction (data not shown). These results suggest that the rFIC is an outflow hub at the junction of the CEN and DMN. Converging Evidence from Two Additional fMRI Experiments. To provide converging evidence for the rFIC as a causal outflow hub, we analyzed fMRI data from two other experiments using the same GCA and network analyses methods described above: (i) a visual ''oddball'' attention experiment, and (ii) a task-free resting state experiment (see also SI Materials and Methods). We found a pattern of significant causal outflow from the rFIC that was strikingly similar to the auditory event segmentation experiment ( Discussion ICA revealed the existence of statistically independent CEN, DMN, and SN during task performance, extending our recent discovery of similar networks in task-free, resting-state, conditions (4). Our analysis indicates that the rFIC, a key node of the SN, plays a critical and causal role in switching between the CEN and the DMN (we use the term ''causal'' here, and in the following sections in the sense implied by, and consistent with, latency analysis, GCA and network analysis). The striking similarity of significant causal outflow from the rFIC across tasks, involving different stimulus modalities, indicates a general role for the rFIC in switching between two key brain networks. Furthermore, our replication of this effect in the task-free resting state suggests that the rFIC is a network hub that can also initiate spontaneous switching between the CEN and DMN (24). Our findings help to provide a more unified perspective on exogenous and endogenous mechanisms underlying cognitive control. In the SI Discussion, we suggest that these interactions are the result of neural, rather than vascular processes. Here, we focus on the neurobiological implications of our findings in the context of the three networks that we set out to examine; analyses of several other control regions (including the sensory and association cortices) that further clarify the crucial role of the FIC in the switching process are discussed in the SI Text. FIC-ACC Network Is Neuroanatomically Uniquely Positioned to Gen- erate Control Signals. In primates, anatomical studies have revealed that the insular cortex is reciprocally connected to multiple sensory, motor, limbic, and association areas of the brain (30, 31). The FIC and ACC themselves share significant topographic reciprocal connectivity and form an anatomically tightly coupled network ideally placed to integrate information from several brain regions (9, 10, 32). Indeed, analysis of the auditory and visual experiments in our study found coactivation of these regions during task performance, as in many other studies involving cognitively demanding tasks (7). Previous neurophysiological and brain imaging studies have shown that the FIC-ACC complex moderates arousal during cognitively demanding tasks and that the rFIC, in particular, plays a critical role in the interoceptive awareness of both stimulus-induced and stimulus-independent changes in homeostatic states (9, 10). Furthermore, the FIC and ACC share a unique feature at the neuronal level: The human FIC-ACC network has a specialized class of neurons with distinctive anatomical and functional features that might facilitate the network switching process that we report here. The von Economo neurons (VENs) are specialized neurons exclusively localized to the FIC and ACC (33). Based on the dendritic architecture of the VENs, Allman and colleagues have proposed that ''the function of the VENs may be to provide a rapid relay to other parts of the brain of a simple signal derived from information processed within FI and ACC.'' (34). We propose that the VENs may, therefore, constitute the neuronal basis of control signals generated by the FIC and ACC in our study. Taken together, these findings suggest that the FIC and ACC, anchored within the SN, are uniquely positioned to initiate control signals that activate the CEN and deactivate the DMN. Differential Roles of the rFIC, ACC, and Lateral Prefrontal Cortex in Initiating Control Signals. Many previous studies of attentional and cognitive control have reported coactivation of the FIC and Comparison of the net causal outflow (out-in degree) for the six key nodes of the Salience, Central-Executive, and Default-Mode networks as assessed by Granger causality analysis revealed that the rFIC has a significantly higher net causal outflow than the CEN and DMN regions across tasks (conventions as in 12572 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.0800005105 Sridharan et al. ACC (7, Our findings help to synthesize these and other extant findings in the literature into a common network dynamical framework and they suggest a causal, and potentially critical, role for the rFIC in cognitive control. We propose that one fundamental mechanism underlying such control is a transient signal from the rFIC, which engages the brain's attentional, working memory and higher-order control processes while disengaging other systems that are not task-relevant. We predict that disruptions to these processes may constitute a key aspect of psychopathology in several neurological and psychiatric disorders, including frontotemporal dementia, autism, and anxiety disorders (34, 50, 51). More generally, our study illustrates the power of a unified network approach-wherein we first specify intrinsic brain networks and then analyze interactions among anatomically discrete regions within these networks during cognitive information processing-for understanding fundamental aspects of human brain function and dysfunction

Experimental Demonstration of Post-Selection based Continuous Variable Quantum Key Distribution in the Presence of Gaussian Noise

In realistic continuous variable quantum key distribution protocols, an eavesdropper may exploit the additional Gaussian noise generated during transmission to mask her presence. We present a theoretical framework for a post-selection based protocol which explicitly takes into account excess Gaussian noise. We derive a quantitative expression of the secret key rates based on the Levitin and Holevo bounds. We experimentally demonstrate that the post-selection based scheme is still secure against both individual and collective Gaussian attacks in the presence of this excess noise.Comment: 4 pages, 4 figure

Bhatara, A., Quintin, E., Fombonne, E., Heaton, P. & Levitin, D. (2009).The Effects of Music on Social Attribution in Adolescents with Autism Spectrum Disorders. Child Neuropsychology, 13; 1 – 22.

High-functioning adolescents with ASD and matched controls were presented with animations that depicted varying levels of social interaction and were either accompanied by music or silent. Participants described the events of the animation, and we scored responses for intentionality, appropriateness, and length of description. Adolescents with ASD were less likely to make social attributions, especially for those animations with the most complex social interactions. When stimuli were accompanied by music, both groups were equally impaired in appropriateness and intentionality. We conclude that adolescents with ASD perceive and integrate musical soundtracks with visual displays equivalent to typically developing individuals

Non-linear operations in quantum information theory

Quantum information theory is used to analize various non-linear operations on quantum states. The universal disentanglement machine is shown to be impossible, and partial (negative) results are obtained in the state-dependent case. The efficiency of the transformation of non-orthogonal states into orthogonal ones is discussed.Comment: 11 pages, LaTeX, 3 figures on separate page

Music Perception Spring

The neuroanatomical correlates of temporal structure and expectancies in music were investigated using a unique stimulus manipulation involving scrambled music. The experiment compared brain responses (using functional magnetic resonance imaging) while participants listened to classical music and scrambled versions of that same music. The scrambled versions disrupted musical structure while holding low-level musical attributes constant, including such psychoacoustic parameters as pitch, loudness, and timbre. Comparing music to its scrambled counterpart, we found focal activation in the pars orbitalis region (Brodmann Area 47) of the left inferior frontal cortex, a region that has been previously closely associated with the processing of linguistic structure in spoken and signed language, and additional activation in the right hemisphere homologue of that area. We speculate that this particular region of inferior frontal cortex may be more generally responsible for processing fine-structured stimuli that evolve over time, not merely those that are linguistic