Inter-participant consistency of language-processing networks during abstract thoughts.

Human brain imaging typically employs structured and controlled tasks to avoid variable and inconsistent activation patterns. Here we expand this assumption by showing that an extremely open-ended, high-level cognitive task of thinking about an abstract content, loosely defined as "abstract thinking" - leads to highly consistent activation maps. Specifically, we show that activation maps generated during such cognitive process were precisely located relative to borders of well-known networks such as internal speech, visual and motor imagery. The activation patterns allowed decoding the thought condition at >95%. Surprisingly, the activated networks remained the same regardless of changes in thought content. Finally, we found remarkably consistent activation maps across individuals engaged in abstract thinking. This activation bordered, but strictly avoided visual and motor networks. On the other hand, it overlapped with left lateralized language networks. Activation of the default mode network (DMN) during abstract thought was similar to DMN activation during rest. These observations were supported by a quantitative neuronal distance metric analysis. Our results reveal that despite its high level, and varied content nature - abstract thinking activates surprisingly precise and consistent networks in participants' brains.

A unifying principle underlying the extracellular field potential spectral responses in the human cortex.

Electrophysiological mass potentials show complex spectral changes upon neuronal activation. However, it is unknown to what extent these complex band-limited changes are interrelated or, alternatively, reflect separate neuronal processes. To address this question, intracranial electrocorticograms (ECoG) responses were recorded in patients engaged in visuomotor tasks. We found that in the 10- to 100-Hz frequency range there was a significant reduction in the exponent χ of the 1/f(χ) component of the spectrum associated with neuronal activation. In a minority of electrodes showing particularly high activations the exponent reduction was associated with specific band-limited power modulations: emergence of a high gamma (80-100 Hz) and a decrease in the alpha (9-12 Hz) peaks. Importantly, the peaks' height was correlated with the 1/f(χ) exponent on activation. Control simulation ruled out the possibility that the change in 1/f(χ) exponent was a consequence of the analysis procedure. These results reveal a new global, cross-frequency (10-100 Hz) neuronal process reflected in a significant reduction of the power spectrum slope of the ECoG signal.

Intracranial recordings reveal transient response dynamics during information maintenance in human cerebral cortex.

Despite an extensive body of work, it is still not clear how short term maintenance of information is implemented in the human brain. Most prior research has focused on "working memory"-typically involving the storage of a number of items, requiring the use of a phonological loop and focused attention during the delay period between encoding and retrieval. These studies largely support a model of enhanced activity in the delay interval as the central mechanism underlying working memory. However, multi-item working memory constitutes only a subset of storage phenomena that may occur during daily life. A common task in naturalistic situations is short term memory of a single item-for example, blindly reaching to a previously placed cup of coffee. Little is known about such single-item, effortless, storage in the human brain. Here, we examined the dynamics of brain responses during a single-item maintenance task, using intracranial recordings implanted for clinical purpose in patients (ECoG). Our results reveal that active electrodes were dominated by transient short latency visual and motor responses, reflected in broadband high frequency power increases in occipito-temporal, frontal, and parietal cortex. Only a very small set of electrodes showed activity during the early part of the delay period. Interestingly, no cortical site displayed a significant activation lasting to the response time. These results suggest that single item encoding is characterized by transient high frequency ECoG responses, while the maintenance of information during the delay period may be mediated by mechanisms necessitating only low-levels of neuronal activations.

The Noisy Brain: Power of Resting-State Fluctuations Predicts Individual Recognition Performance.

The unique profile of strong and weak cognitive traits characterizing each individual is of a fundamental significance, yet their neurophysiological underpinnings remain elusive. Here, we present intracranial electroencephalogram (iEEG) measurements in humans pointing to resting-state cortical "noise" as a possible neurophysiological trait that limits visual recognition capacity. We show that amplitudes of slow (<1 Hz) spontaneous fluctuations in high-frequency power measured during rest were predictive of the patients' performance in a visual recognition 1-back task (26 patients, total of 1,389 bipolar contacts pairs). Importantly, the effect was selective only to task-related cortical sites. The prediction was significant even across long (mean distance 4.6 ± 2.8 days) lags. These findings highlight the level of the individuals' internal "noise" as a trait that limits performance in externally oriented demanding tasks.