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Review
. 2014 Jun 26:8:119.
doi: 10.3389/fnsys.2014.00119. eCollection 2014.

Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations

Jörn M Horschig  1 , Johanna M Zumer  2 , Ali Bahramisharif  1
Affiliations
Review

Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations

Jörn M Horschig et al. Front Syst Neurosci. .

Abstract

Cortical oscillations have been shown to represent fundamental functions of a working brain, e.g., communication, stimulus binding, error monitoring, and inhibition, and are directly linked to behavior. Recent studies intervening with these oscillations have demonstrated effective modulation of both the oscillations and behavior. In this review, we collect evidence in favor of how hypothesis-driven methods can be used to augment cognition by optimizing cortical oscillations. We elaborate their potential usefulness for three target groups: healthy elderly, patients with attention deficit/hyperactivity disorder, and healthy young adults. We discuss the relevance of neuronal oscillations in each group and show how each of them can benefit from the manipulation of functionally-related oscillations. Further, we describe methods for manipulation of neuronal oscillations including direct brain stimulation as well as indirect task alterations. We also discuss practical considerations about the proposed techniques. In conclusion, we propose that insights from neuroscience should guide techniques to augment human cognition, which in turn can provide a better understanding of how the human brain works.

Keywords: ADHD; attention; brain state dependent tasks; brain stimulation; brain-computer interfacing; elderly; neuronal oscillations; working memory.

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Figures

Figure 1
Figure 1
Example of the functional involvement of neuronal oscillations. (A) The time-frequency representation of an anticipation task. The gray dotted line shows the time that the stimulus could have been presented, but was not. The black dotted line indicates the onset of the target. Alpha power decreases in anticipation of a stimulus even without subsequent stimulation. Reproduced with permission from Rohenkohl and Nobre (2011). (B) The dynamics of frontal theta power. Depending on the encoding task, both increases and decreases of frontal theta power were found for successful versus unsuccessful remembering. SME = subsequent memory effect. Reproduced with permission from Hanslmayr and Staudigl (2014). (C) During visual stimulus encoding, posterior gamma power (60–90 Hz) is predictive of subsequent memory performance in young, healthy adults. The vertical dashed bars indicate the window for significance testing and beamformer application. The left panel shows gamma power from one significant posterior sensor and the right panel is the beamformer projection (Osipova et al., 2006).
Figure 2
Figure 2
Oscillatory power differences in different task settings in the three discussed population groups. (A) Frontal theta power during stimulus encoding is significantly higher for elderly versus young adults, and scales with relevance of the stimuli in young, healthy adults, but not in the elderly (* p < 0.001). Reproduced with permission from Gazzaley et al. (2008). (B) During visual spatial covert attention, the degree of alpha lateralization indexes the relative disengagement of the task-irrelevant ipsilateral hemisphere versus the task-relevant contralateral hemisphere. While young, healthy adults are able to modulate their alpha lateralization symmetrically around zero, inattentive ADHD patients show a lack of maintaining a high degree of alpha lateralization to the left side. In addition, there is an absence of correlation between alpha lateralization index and behavioral cueing effect in ADHD patients, whereas there is a strong relationship in healthy, young adults. Reproduced with permission from ter Huurne et al. (2013).
Figure 3
Figure 3
Examples of manipulating neuronal oscillations and their impact on cognition. (A) rTMS stimulation at 10 Hz to right parietal cortex results in alpha oscillations outlasting the stimulation period (t = 0 s), compared to the control condition of rotating the TMS coil by 90° (TMS90). The condition contrast with other control conditions confirmed the exclusive effect of rTMS at 10 Hz. w1 = time window of the first two pulses and w2 = time window of the last three pulses. Reproduced with permission from Thut et al. (2011b). (B) 10 Hz rTMS stimulation, but not 5 or 20 Hz, of parietal cortex ipsilateral to stimulation results in behavioral improvement, whereas contralateral stimulation results in decreased performance (* p < 0.05, ** p < 0.01, *** p < 0.001). Reproduced with permission from Romei et al. (2010). (C) Frontal theta neurofeedback training results in increased frontal theta in both young and old adults. OSFT = old subjects, sham feedback; ONFT = old subjects, neurofeedback group; YSFT = young subjects, sham feedback; YNFT = young subjects, neurofeedback (* p < 0.01). Taken with permission from Wang and Hsieh (2013). (D) Only old adults receiving neurofeedback on frontal theta increased working memory accuracy in a Sternberg task (depicted on the y-axis). Young adults were already performing at ceiling level. (for acronym, see panel C; * p < 0.01). Taken with permission from Wang and Hsieh (2013).
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