Functional significance of complex fluctuations in brain activity: from resting state to cognitive neuroscience

D. PapoAvatar Inv

Frontiers in Systems Neuroscience, 8:112 (2014).

Behavioural studies have shown that human cognition is characterized by properties such as temporal scale invariance, heavy-tailed non-Gaussian distributions, and long-range correlations at long time scales, suggesting models of how (non observable) components of cognition interact. On the other hand, results from functional neuroimaging studies show that complex scaling and intermittency may be generic spatio-temporal properties of the brain at rest. Somehow surprisingly, though, hardly ever have the neural correlates of cognition been studied at time scales comparable to those at which cognition shows scaling properties. Here, we analyze the meanings of scaling properties and the significance of their task-related modulations for cognitive neuroscience. It is proposed that cognitive processes can be framed in terms of complex generic properties of brain activity at rest and, ultimately, of functional equations, limiting distributions, symmetries, and possibly universality classes characterizing them.

[Read more in Frontiers in Systems Neuroscience]

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Measuring brain temperature without a thermometer

Avatar InvD. Papo

Frontiers in Physiology, 5:24 (2014).

Temperature has profound effects on a wide range of parameters of neural activity at various scales [1]. At the cell level, ionic currents, membrane potential, input resistance, action potential amplitude, duration and propagation, and synaptic transmission have all been shown to be affected by temperature variations [1-5]. At mesoscopic scales of neural activity, temperature changes can steer network activity toward different functional regimes [6], affecting the duration, frequency and firing rate of activated states during slow frequency oscillations, and the ability to end these states [7]. Temperature also has a substantial effect on chemical reaction rates [8], and affects the blood oxygen saturation level by changing haemoglobin affinity for oxygen [9]. Furthermore, cooling reduces metabolic processes [10], and has been used to silence cortical areas to study their function [11].

[Read more in Frontiers in Fractal Physiology]

Time scales in cognitive neuroscience

D. PapoAvatar Inv

Frontiers in Physiology, 4:86 (2013).

Cognitive neuroscience boils down to describing the ways in which cognitive function results from brain activity. In turn, brain activity shows complex fluctuations, with structure at many spatio-temporal scales. Exactly how cognitive function inherits the physical dimensions of neural activity, though, is highly non-trivial, and so are generally the corresponding dimensions of cognitive phenomena. As for any physical phenomenon, when studying cognitive function, the first conceptual step should be that of establishing its dimensions. Here, we provide a systematic presentation of the temporal aspects of task-related brain activity, from the smallest scale of the brain imaging technique’s resolution, to the observation time of a given experiment, through the characteristic time scales of the process under study. We first review some standard assumptions on the temporal scales of cognitive function. In spite of their general use, these assumptions hold true to a high degree of approximation for many cognitive (viz. fast perceptual) processes, but have their limitations for other ones (e.g., thinking or reasoning). We define in a rigorous way the temporal quantifiers of cognition at all scales, and illustrate how they qualitatively vary as a function of the properties of the cognitive process under study. We propose that each phenomenon should be approached with its own set of theoretical, methodological and analytical tools. In particular, we show that when treating cognitive processes such as thinking or reasoning, complex properties of ongoing brain activity, which can be drastically simplified when considering fast (e.g., perceptual) processes, start playing a major role, and not only characterize the temporal properties of task-related brain activity, but also determine the conditions for proper observation of the phenomena. Finally, some implications on the design of experiments, data analyses, and the choice of recording parameters are discussed.

[Read more in Frontiers in Fractal Physiology]

Why should cognitive neuroscientists study the brain’s resting state?

D. PapoAvatar Inv

Frontiers in Human Neuroscience, 7:45 (2013).

Cognitive neuroscience studies how cognitive function is produced by the brain. Seen from a reverse angle, cognitive neuroscience studies how brain activity is modulated by the execution of cognitive tasks. In the former case, cognitive function is characterized in terms of neural properties associated with the execution of given cognitive tasks, while in the latter it can be thought of as a probe exposing information on brain dynamics. Brain activity displays dynamics independently of whether a particular task is carried out or not. The question is then: should cognitive neuroscience get interested in the properties of resting brain activity? And, if so, how and to what extent can studying resting brain activity help characterizing the neural correlates of cognitive processes?

[Read more in Frontiers in Human Neuroscience]

Feedback modulates the temporal scale-free dynamics of brain electrical activity in a hypothesis testing task

Marco Buiatti, David Papo, Pierre-Marie Baudonnière, and Carl Van VreeswijkAvatar Inv

Neuroscience, 146:1400-1412 (2007).

We used the electroencephalogram (EEG) to investigate whether positive and negative performance feedbacks exert different long-lasting modulations of electrical activity in a reasoning task. Nine college students serially tested hypotheses concerning a hidden rule by judging its presence or absence in triplets of digits, and revised them on the basis of an exogenous performance feedback. The scaling properties of the transition period between feedback and triplet presentation were investigated with detrended fluctuation analysis (DFA). DFA showed temporal scale-free dynamics of EEG activity in both feedback conditions for time scales larger than 150 ms. Furthermore, DFA revealed that negative feedback elicits significantly higher scaling exponents than positive feedback. This effect covers a wide network comprising parietooccipital and left frontal regions. We thus showed that specific task demands can modify the temporal scale-free dynamics of the ongoing brain activity. Putative neural correlates of these long-lasting feedback-specific modulations are proposed.

[Read more in Pubmed]     [Read more in Neuroscience]

Time-frequency intracranial source localization of feedback-related EEG activity in hypothesis testing

Papo, D., Douiri, A., Bouchet, F., Bourzeix, J.-C., Caverni, J.-P., & Baudonnière, P.-M.feedback

Cerebral Cortex, 17:1314-1322 (2007).

The neural correlates of the response to performance feedback have been the object of numerous neuroimaging studies. However, the precise timing and functional meaning of the resulting activations are poorly understood. We studied the electroencephalographic response time locked to positive and negative performance feedback in a hypothesis testing paradigm. The signal was convoluted with a family of complex wavelets. Intracranial sources of activity at various narrow-band frequencies were estimated in the 100- to 400-ms time window following feedback onset. Positive and negative feedback were associated to 1) early parahippocampo-cingular sources of alpha oscillations, more posteriorly located and long lasting for negative feedback and to 2) late partially overlapping neural circuits comprising regions in prefrontal, cingular, and temporal cortices but operating at feedback-specific latencies and frequencies. The results were interpreted in the light of neurophysiological models of feedback and were used to discuss methodological issues in the study of high-level cognitive functions, including reasoning and decision making.

[Read more in Cerebral Cortex]

Feedback in Hypothesis Testing: An ERP Study

Papo D, Baudonnière PM, Hugueville L, Caverni JPfeedback

Journal of Cognitive Neuroscience, 15:508-522 (2003).

We used event-related potentials (ERPs) to probe the effects of feedback in a hypothesis testing (HT) paradigm. Thirteen college students serially tested hypotheses concerning a hidden rule by judging its presence or absence in triplets of digits and revised them on the basis of an exogenous performance feedback. ERPs time-locked to performance feedback were then examined. The results showed differences between responses to positive and negative feedback at all cortical sites. Negative feedback, indicating incorrect performance, was associated to a negative deflection preceding a P300-like wave. Spatiotemporal principal component analysis (PCA) showed the interplay between early frontal components and later central and posterior ones. Lateralization of activity was selectively detectable at frontal sites, with a left frontal dominance for both positive and negative feedback. These results are discussed in terms of a proposed computational model of trial-to-trial feedback in HT in which the cognitive and emotive aspects of feedback are explicitly linked to putative mediating brain mechanisms. The properties of different feedback types and feedback-related deficits in depression are also discussed.

[Read more in Journal of Cognitive Neuroscience]