Functional Brain Networks Develop from a "Local to Distributed" Organization
Damien A. Fair, Alexander L. Cohen, Jonathan D. Power, Nico U. F. Dosenbach, Jessica A. Church,Francis M. Miezin, Bradley L. Schlaggar, Steven E. Petersen
PLoS Computational Biology | 1 May 2009 | Volume 5 | Issue 5 | e1000381
The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways.
Whats and Whens of sleep-dependent memory consolidation
The whats and whens of sleep-dependent memory consolidation
Susanne Diekelmann, Ines Wilhelm, Jan Born
Sleep Medicine Reviews (2009), doi:10.1016
Sleep benefits memory consolidation. The reviewed studies indicate that this consolidating effect is not revealed under all circumstances but is linked to specific psychological conditions. Specifically, we discuss to what extent memory consolidation during sleep depends on the type of learning materials, type of learning and retrieval test, different features of sleep and the subject population. Post-learning sleep enhances consolidation of declarative, procedural and emotional memories. The enhancement is greater for weakly than strongly encoded associations and more consistent for explicitly than implicitly encoded memories. Memories associated with expected reward gain preferentially access to sleep-dependent consolidation. For declarative memories, sleep benefits are more consistently revealed with recall than recognition procedures at retrieval testing. Slow wave sleep (SWS) particularly enhances declarative memories whereas rapid eye movement (REM) sleep preferentially supports procedural and emotional memory aspects. Declarative memory profits already from rather short sleep periods (1–2 h). Procedural memory profits seem more dose-dependent on the amount of sleep following the day after learning. Children’s sleep with high amounts of SWS distinctly enhances declarative memories whereas elderly and psychiatric patients with disturbed sleep show impaired sleep-associated consolidation often of declarative memories. Based on the constellation of psychological conditions identified we hypothesize that access to sleep-dependent consolidation requires memories to be encoded under control of prefrontal-hippocampal circuitry, with the same circuitry controlling subsequent consolidation during sleep.
Susanne Diekelmann, Ines Wilhelm, Jan Born
Sleep Medicine Reviews (2009), doi:10.1016
Sleep benefits memory consolidation. The reviewed studies indicate that this consolidating effect is not revealed under all circumstances but is linked to specific psychological conditions. Specifically, we discuss to what extent memory consolidation during sleep depends on the type of learning materials, type of learning and retrieval test, different features of sleep and the subject population. Post-learning sleep enhances consolidation of declarative, procedural and emotional memories. The enhancement is greater for weakly than strongly encoded associations and more consistent for explicitly than implicitly encoded memories. Memories associated with expected reward gain preferentially access to sleep-dependent consolidation. For declarative memories, sleep benefits are more consistently revealed with recall than recognition procedures at retrieval testing. Slow wave sleep (SWS) particularly enhances declarative memories whereas rapid eye movement (REM) sleep preferentially supports procedural and emotional memory aspects. Declarative memory profits already from rather short sleep periods (1–2 h). Procedural memory profits seem more dose-dependent on the amount of sleep following the day after learning. Children’s sleep with high amounts of SWS distinctly enhances declarative memories whereas elderly and psychiatric patients with disturbed sleep show impaired sleep-associated consolidation often of declarative memories. Based on the constellation of psychological conditions identified we hypothesize that access to sleep-dependent consolidation requires memories to be encoded under control of prefrontal-hippocampal circuitry, with the same circuitry controlling subsequent consolidation during sleep.
Genetic and molecular regulation of sleep
The genetic and molecular regulation of sleep: from fruit flies to humans
Nature Reviews | Neuroscience Volume 10 | August 2009 | 549
Chiara Cirelli
It has been known for a long time that genetic factors affect sleep quantity and quality. Genetic screens have identified several mutations that affect sleep across species, pointing to an evolutionary conserved regulation of sleep. Moreover, it has also been recognized that sleep affects gene expression. These findings have given valuable insights into the molecular underpinnings of sleep regulation and function that might lead the way to more efficient treatments for sleep disorders.
Nature Reviews | Neuroscience Volume 10 | August 2009 | 549
Chiara Cirelli
It has been known for a long time that genetic factors affect sleep quantity and quality. Genetic screens have identified several mutations that affect sleep across species, pointing to an evolutionary conserved regulation of sleep. Moreover, it has also been recognized that sleep affects gene expression. These findings have given valuable insights into the molecular underpinnings of sleep regulation and function that might lead the way to more efficient treatments for sleep disorders.
Neurons that Fire Together Also Conspire Together
Neurons that Fire Together Also Conspire Together: Is Normal Sleep Circuitry Hijacked to Generate Epilepsy?
Neuron 62, June 11, 2009 (DOI 10.1016/j.neuron.2009.05.015)
Mark P. Beenhakker and John R. Huguenard
Brain circuits oscillate during sleep. The same circuits appear to generate pathological oscillations. In this review, we discuss recent advances in our understanding of how epilepsy co-opts normal, sleep-related circuits to generate seizures.
Neuron 62, June 11, 2009 (DOI 10.1016/j.neuron.2009.05.015)
Mark P. Beenhakker and John R. Huguenard
Brain circuits oscillate during sleep. The same circuits appear to generate pathological oscillations. In this review, we discuss recent advances in our understanding of how epilepsy co-opts normal, sleep-related circuits to generate seizures.
How to Tell If a Particular Memory Is True or False
How to Tell If a Particular Memory Is True or False
Perspectives on Psychological Science, Volume 4, Issue 4, Pages 370-374
Daniel M. Bernstein and Elizabeth F. Loftus
How can you tell if a particular memory belonging to you or someone else is true or false? Cognitive scientists use a variety of techniques to measure groups of memories, whereas police, lawyers, and other researchers use procedures to determine whether an individual can be believed or not. We discuss evidence from behavioral and neuroimaging studies and research on lying that have attempted to distinguish true from false memories.
Perspectives on Psychological Science, Volume 4, Issue 4, Pages 370-374
Daniel M. Bernstein and Elizabeth F. Loftus
How can you tell if a particular memory belonging to you or someone else is true or false? Cognitive scientists use a variety of techniques to measure groups of memories, whereas police, lawyers, and other researchers use procedures to determine whether an individual can be believed or not. We discuss evidence from behavioral and neuroimaging studies and research on lying that have attempted to distinguish true from false memories.
How Technology May Soon "Read" Your Mind
Neuroscience has learned so much about how we think and the brain activity linked to certain thoughts that it is now possible - on a very basic scale - to read a person's mind.
Watch this CBS 60 Minutes video to learn more about how this incredible research lets scientists get a glimpse at your thoughts.
Watch this CBS 60 Minutes video to learn more about how this incredible research lets scientists get a glimpse at your thoughts.
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