Short-Term Changes in Neural Activity and Behavior. A Conference Sponsored by King's College Research Center, Cambridge.Gabriel Horn , Robert A. Hinde

1971 ◽  
Vol 46 (3) ◽  
pp. 322-323
Author(s):  
Charles Walcott
2021 ◽  
Vol 24 (2) ◽  
pp. 201-209 ◽  
Author(s):  
Dominic Abrams ◽  
Fanny Lalot ◽  
Michael A. Hogg

COVID-19 is a challenge faced by individuals (personal vulnerability and behavior), requiring coordinated policy from national government. However, another critical layer—intergroup relations—frames many decisions about how resources and support should be allocated. Based on theories of self and social identity uncertainty, subjective group dynamics, leadership, and social cohesion, we argue that this intergroup layer has important implications for people’s perceptions of their own and others’ situation, political management of the pandemic, how people are influenced, and how they resolve identity uncertainty. In the face of the pandemic, initial national or global unity is prone to intergroup fractures and competition through which leaders can exploit uncertainties to gain short-term credibility, power, or influence for their own groups, feeding polarization and extremism. Thus, the social and psychological challenge is how to sustain the superordinate objective of surviving and recovering from the pandemic through mutual cross-group effort.


PEDIATRICS ◽  
1987 ◽  
Vol 80 (1) ◽  
pp. 124-125
Author(s):  
MILES WEINBERGER ◽  
SCOTT LINDGREN ◽  
JESSE JOAD

To the Editor.— Dr Rachelefsky and his colleagues reported, first in USA Today (Dec 2, 1986, p 1) and later in Pediatrics (1986;78:1133-1138) that theophylline adversely affected school performance. Specifically, they stated, "Teachers said kids couldn't sit still, they weren't remembering as well, they were acting up, and their handwriting had changed" (USA Today). They concluded that "the short-term administration of theophylline to asymptomatic asthmatic children not receiving oral bronchodilators can adversely affect school performance and behavior" (Pediatrics).


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Milad Jabbari ◽  
Abbas Erfanian

AbstractIn this paper, we propose a deep recurrent neural network (DRNN) for the estimation of bladder pressure and volume from neural activity recorded directly from spinal cord gray matter neurons. The model was based on the Long Short-Term Memory (LSTM) architecture, which has emerged as a general and effective model for capturing long-term temporal dependencies with good generalization performance. In this way, training the network with the data recorded from one rat could lead to estimating the bladder status of different rats. We combined modeling of spiking and local field potential (LFP) activity into a unified framework to estimate the pressure and volume of the bladder. Moreover, we investigated the effect of two-electrode recording on decoding performance. The results show that the two-electrode recordings significantly improve the decoding performance compared to single-electrode recordings. The proposed framework could estimate bladder pressure and volume with an average normalized root-mean-squared (NRMS) error of 14.9 ± 4.8% and 19.7 ± 4.7% and a correlation coefficient (CC) of 83.2 ± 3.2% and 74.2 ± 6.2%, respectively. This work represents a promising approach to the real-time estimation of bladder pressure/volume in the closed-loop control of bladder function using functional electrical stimulation.


2012 ◽  
Vol 24 (10) ◽  
pp. 2678-2699 ◽  
Author(s):  
Taro Toyoizumi

Many cognitive processes rely on the ability of the brain to hold sequences of events in short-term memory. Recent studies have revealed that such memory can be read out from the transient dynamics of a network of neurons. However, the memory performance of such a network in buffering past information has been rigorously estimated only in networks of linear neurons. When signal gain is kept low, so that neurons operate primarily in the linear part of their response nonlinearity, the memory lifetime is bounded by the square root of the network size. In this work, I demonstrate that it is possible to achieve a memory lifetime almost proportional to the network size, “an extensive memory lifetime,” when the nonlinearity of neurons is appropriately used. The analysis of neural activity revealed that nonlinear dynamics prevented the accumulation of noise by partially removing noise in each time step. With this error-correcting mechanism, I demonstrate that a memory lifetime of order [Formula: see text] can be achieved.


2021 ◽  
Vol 151 ◽  
pp. 105728
Author(s):  
B. Sikora-Wachowicz ◽  
A. Keresztes ◽  
M. Werkle-Bergner ◽  
K. Lewandowska ◽  
T. Marek ◽  
...  

2012 ◽  
Vol 24 (4) ◽  
pp. 775-777 ◽  
Author(s):  
Juha Silvanto ◽  
Alvaro Pascual-Leone

A central aim in cognitive neuroscience is to explain how neural activity gives rise to perception and behavior; the causal link of paramount interest is thus from brain to behavior. Functional neuroimaging studies, however, tend to provide information in the opposite direction by informing us how manipulation of behavior may affect neural activity. Although this may provide valuable insights into neuronal properties, one cannot use such evidence to make inferences about the behavioral significance of the observed activations; if A causes B, it does not necessarily follow that B causes A. In contrast, brain stimulation techniques enable us to directly modulate brain activity as the source of behavior and thus establish causal links.


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