Time for the Fourth Dimension in Attention

Author(s):  
Anna C. (Kia) Nobre ◽  
Gustavo Rohenkohl

This chapter takes attention into the fourth dimension by considering research that explores how predictive information in the temporal structure of events can contribute to optimizing perception. The authors review behavioural and neural findings from three lines of investigation in which the temporal regularity and predictability of events are manipulated through rhythms, hazard functions, and cues. The findings highlight the fundamental role temporal expectations play in shaping several aspects of performance, from early perceptual analysis to motor preparation. They also reveal modulation of neural activity by temporal expectations all across the brain. General principles of how temporal expectations are generated and bias information processing are still emerging. The picture so far suggests that there may be multiple sources of temporal expectation, which can bias multiple stages of stimulus analysis depending on the stages of information processing that are critical for task performance. Neural oscillations are likely to provide an important medium through which the anticipated timing of events can regulate neuronal excitability.

1996 ◽  
Vol 07 (04) ◽  
pp. 497-505 ◽  
Author(s):  
HANS LILJENSTRÖM

We are interested in how the complex dynamics of the brain, which may include oscillations, chaos and noise, can affect the efficiency of neural information processing. Here, we consider the amplification and functional role of fluctuations, expressed as chaos or noise in the system. Using computer simulations of a neural network model of the olfactory cortex, we demonstrate how microscopic fluctuations can result in global effects at the network level. In particular, we show that the rate of information processing in associative memory tasks can be maximized for optimal noise levels. Noise can also induce transitions between different dynamical states, related to learning and memory. A chaotic-like behavior, induced by noise or by an increase in neuronal excitability, can enhance system performance if it is transient and converges to a limit cycle memory state. The level of accuracy required for correct pattern association further affects the rate of information processing. We discuss how neuromodulatory control of the cortical dynamics can shift the balance between rate and accuracy optimization, as well as between sensitivity and stability.


2007 ◽  
Author(s):  
Donatella Spinelli ◽  
Teresa Aprile Francesco Di Russo ◽  
Sabrina Pitzalis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fernando R. Fernandez ◽  
Mircea C. Iftinca ◽  
Gerald W. Zamponi ◽  
Ray W. Turner

AbstractT-type calcium channels are important regulators of neuronal excitability. The mammalian brain expresses three T-type channel isoforms (Cav3.1, Cav3.2 and Cav3.3) with distinct biophysical properties that are critically regulated by temperature. Here, we test the effects of how temperature affects spike output in a reduced firing neuron model expressing specific Cav3 channel isoforms. The modeling data revealed only a minimal effect on baseline spontaneous firing near rest, but a dramatic increase in rebound burst discharge frequency for Cav3.1 compared to Cav3.2 or Cav3.3 due to differences in window current or activation/recovery time constants. The reduced response by Cav3.2 could optimize its activity where it is expressed in peripheral tissues more subject to temperature variations than Cav3.1 or Cav3.3 channels expressed prominently in the brain. These tests thus reveal that aspects of neuronal firing behavior are critically dependent on both temperature and T-type calcium channel subtype.


2002 ◽  
Vol 13 (04) ◽  
pp. 188-204 ◽  
Author(s):  
Shigeyuki Kuwada ◽  
Julia S. Anderson ◽  
Ranjan Batra ◽  
Douglas C. Fitzpatrick ◽  
Natacha Teissier ◽  
...  

The scalp-recorded amplitude-modulation following response (AMFR)” is gaining recognition as an objective audiometric tool, but little is known about the neural sources that underlie this potential. We hypothesized, based on our human studies and single-unit recordings in animals, that the scalp-recorded AMFR reflects the interaction of multiple sources. We tested this hypothesis using an animal model, the unanesthetized rabbit. We compared AMFRs recorded from the surface of the brain at different locations and before and after the administration of agents likely to enhance or suppress neural generators. We also recorded AMFRs locally at several stations along the auditory neuraxis. We conclude that the surface-recorded AMFR is indeed a composite response from multiple brain generators. Although the response at any modulation frequency can reflect the activity of more than one generator, the AMFRs to low and high modulation frequencies appear to reflect a strong contribution from cortical and subcortical sources, respectively.


1983 ◽  
Vol 17 (4) ◽  
pp. 307-318 ◽  
Author(s):  
H. G. Stampfer

This article suggests that the potential usefulness of event-related potentials in psychiatry has not been fully explored because of the limitations of various approaches to research adopted to date, and because the field is still undergoing rapid development. Newer approaches to data acquisition and methods of analysis, combined with closer co-operation between medical and physical scientists, will help to establish the practical application of these signals in psychiatric disorders and assist our understanding of psychophysiological information processing in the brain. Finally, it is suggested that psychiatrists should seek to understand these techniques and the data they generate, since they provide more direct access to measures of complex cerebral processes than current clinical methods.


2005 ◽  
Vol 17 (10) ◽  
pp. 2139-2175 ◽  
Author(s):  
Naoki Masuda ◽  
Brent Doiron ◽  
André Longtin ◽  
Kazuyuki Aihara

Oscillatory and synchronized neural activities are commonly found in the brain, and evidence suggests that many of them are caused by global feedback. Their mechanisms and roles in information processing have been discussed often using purely feedforward networks or recurrent networks with constant inputs. On the other hand, real recurrent neural networks are abundant and continually receive information-rich inputs from the outside environment or other parts of the brain. We examine how feedforward networks of spiking neurons with delayed global feedback process information about temporally changing inputs. We show that the network behavior is more synchronous as well as more correlated with and phase-locked to the stimulus when the stimulus frequency is resonant with the inherent frequency of the neuron or that of the network oscillation generated by the feedback architecture. The two eigenmodes have distinct dynamical characteristics, which are supported by numerical simulations and by analytical arguments based on frequency response and bifurcation theory. This distinction is similar to the class I versus class II classification of single neurons according to the bifurcation from quiescence to periodic firing, and the two modes depend differently on system parameters. These two mechanisms may be associated with different types of information processing.


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