scholarly journals Multivariate Neural Connectivity Patterns in Early Infancy Predict Later Autism Symptoms

2020 ◽  
Author(s):  
Abigail Dickinson ◽  
Manjari Daniel ◽  
Andrew Marin ◽  
Bilwaj Gaonkar ◽  
Mirella Dapretto ◽  
...  
Keyword(s):  
Early Infancy ◽  
Neural Connectivity ◽  
Autism Symptoms ◽  
Connectivity Patterns

Genetic dyslexia risk variant is related to neural connectivity patterns underlying phonological awareness in children

NeuroImage ◽  
2015 ◽  
Vol 118 ◽  
pp. 414-421 ◽  
Author(s):  
Michael A. Skeide ◽  
Holger Kirsten ◽  
Indra Kraft ◽  
Gesa Schaadt ◽  
Bent Müller ◽  
...  
Keyword(s):  
Phonological Awareness ◽  
Neural Connectivity ◽  
Risk Variant ◽  
Connectivity Patterns

scholarly journals The key role of prefrontal cortex structure and function

2006 ◽  
Vol 29 (1) ◽  
pp. 22-22
Author(s):  
Antonino Raffone ◽  
Gary L. Brase
Keyword(s):  
Prefrontal Cortex ◽  
Species Differences ◽  
Structure And Function ◽  
Primary Role ◽  
Neural Connectivity ◽  
Neuronal Connectivity ◽  
Connectivity Patterns ◽  
Brain Expansion ◽  
And Function

The tension between focusing on species similarities versus species differences (phylogenetic versus adaptationist approaches) recurs in discussions about the nature of neural connectivity and organization following brain expansion. Whereas Striedter suggests a primary role for response inhibition, other possibilities include dense recurrent connectivity loops. Computer simulations and brain imaging technologies are crucial in better understanding actual neuronal connectivity patterns.

scholarly journals A simple generative model of the mouse mesoscale connectome

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Sid Henriksen ◽  
Rich Pang ◽  
Mark Wronkiewicz
Keyword(s):  
Mouse Brain ◽  
Network Model ◽  
Generative Model ◽  
Data Sets ◽  
Neural Connectivity ◽  
Developmental Processes ◽  
Technological Advances ◽  
Connectivity Patterns ◽  
Organizational Principles

Recent technological advances now allow for the collection of vast data sets detailing the intricate neural connectivity patterns of various organisms. Oh et al. (2014) recently published the most complete description of the mouse mesoscale connectome acquired to date. Here we give an in-depth characterization of this connectome and propose a generative network model which utilizes two elemental organizational principles: proximal attachment ‒ outgoing connections are more likely to attach to nearby nodes than to distant ones, and source growth ‒ nodes with many outgoing connections are likely to form new outgoing connections. We show that this model captures essential principles governing network organization at the mesoscale level in the mouse brain and is consistent with biologically plausible developmental processes.

scholarly journals Highly task-specific and distributed neural connectivity in working memory revealed by single-trial decoding in mice and humans

2021 ◽  
Author(s):  
Daniel Strahnen ◽  
Sampath K.T. Kapanaiah ◽  
Alexei M. Bygrave ◽  
Birgit Liss ◽  
David M. Bannerman ◽  
...  
Keyword(s):  
Working Memory ◽  
Activity Patterns ◽  
Brain Regions ◽  
Cognitive Domain ◽  
Neural Connectivity ◽  
Task Specificity ◽  
Electrophysiological Recordings ◽  
Connectivity Patterns ◽  
Unbiased Manner ◽  
Beta Frequency

AbstractWorking memory (WM), the capacity to briefly and intentionally maintain mental items, is key to successful goal-directed behaviour and impaired in a range of psychiatric disorders. To date, several brain regions, connections, and types of neural activity have been correlatively associated with WM performance. However, no unifying framework to integrate these findings exits, as the degree of their species- and task-specificity remains unclear. Here, we investigate WM correlates in three task paradigms each in mice and humans, with simultaneous multi-site electrophysiological recordings. We developed a machine learning-based approach to decode WM-mediated choices in individual trials across subjects from hundreds of electrophysiological measures of neural connectivity with up to 90% prediction accuracy. Relying on predictive power as indicator of correlates of psychological functions, we unveiled a large number of task phase-specific WM-related connectivity from analysis of predictor weights in an unbiased manner. Only a few common connectivity patterns emerged across tasks. In rodents, these were thalamus-prefrontal cortex delta- and beta-frequency connectivity during memory encoding and maintenance, respectively, and hippocampal-prefrontal delta- and theta-range coupling during retrieval, in rodents. In humans, task-independent WM correlates were exclusively in the gamma-band. Mostly, however, the predictive activity patterns were unexpectedly specific to each task and always widely distributed across brain regions. Our results suggest that individual tasks cannot be used to uncover generic physiological correlates of the psychological construct termed WM and call for a new conceptualization of this cognitive domain in translational psychiatry.

scholarly journals Infants’ Brain Responses to Looming Danger: Degeneracy of Neural Connectivity Patterns

2019 ◽  
Vol 31 (3) ◽  
pp. 182-197 ◽  
Author(s):  
F. R. (Ruud) van der Weel ◽  
Seth B. Agyei ◽  
Audrey L. H. van der Meer
Keyword(s):  
Neural Connectivity ◽  
Brain Responses ◽  
Connectivity Patterns

scholarly journals Cognitive ornithology: the evolution of avian intelligence

2005 ◽  
Vol 361 (1465) ◽  
pp. 23-43 ◽  
Author(s):  
Nathan J Emery
Keyword(s):  
Natural Habitat ◽  
Social Groups ◽  
Developmental Period ◽  
Human Cognition ◽  
Neural Connectivity ◽  
Connectivity Patterns ◽  
Shared Ancestry ◽  
Adaptive Specialization ◽  
Complex Cognition ◽  
Productive Method

Comparative psychologists interested in the evolution of intelligence have focused their attention on social primates, whereas birds tend to be used as models of associative learning. However, corvids and parrots, which have forebrains relatively the same size as apes, live in complex social groups and have a long developmental period before becoming independent, have demonstrated ape-like intelligence. Although, ornithologists have documented thousands of hours observing birds in their natural habitat, they have focused their attention on avian behaviour and ecology, rather than intelligence. This review discusses recent studies of avian cognition contrasting two different approaches; the anthropocentric approach and the adaptive specialization approach. It is argued that the most productive method is to combine the two approaches. This is discussed with respects to recent investigations of two supposedly unique aspects of human cognition; episodic memory and theory of mind. In reviewing the evidence for avian intelligence, corvids and parrots appear to be cognitively superior to other birds and in many cases even apes. This suggests that complex cognition has evolved in species with very different brains through a process of convergent evolution rather than shared ancestry, although the notion that birds and mammals may share common neural connectivity patterns is discussed.

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