Parameterizing neural power spectra into periodic and aperiodic components.

Electrophysiological signals exhibit both periodic and aperiodic properties. Periodic oscillations have been linked to numerous physiological, cognitive, behavioral and disease states. Emerging evidence demonstrates that the aperiodic component has putative physiological interpretations and that it dynamically changes with age, task demands and cognitive states. Electrophysiological neural activity is typically analyzed using canonically defined frequency bands, without consideration of the aperiodic (1/f-like) component. We show that standard analytic approaches can conflate periodic parameters (center frequency, power, bandwidth) with aperiodic ones (offset, exponent), compromising physiological interpretations. To overcome these limitations, we introduce an algorithm to parameterize neural power spectra as a combination of an aperiodic component and putative periodic oscillatory peaks. This algorithm requires no a priori specification of frequency bands. We validate this algorithm on simulated data, and demonstrate how it can be used in applications ranging from analyzing age-related changes in working memory to large-scale data exploration and analysis.

Individual EEG measures of attention, memory, and motivation predict population level TV viewership and Twitter engagement.

Television (TV) programming attracts ever-growing audiences and dominates the cultural zeitgeist. Viewership and social media engagement have become standard indices of programming success. However, accurately predicting individual episode success or future show performance using traditional metrics remains a challenge. Here we examine whether TV viewership and Twitter activity can be predicted using electroencephalography (EEG) measures, which are less affected by reporting biases and which are commonly associated with different cognitive processes. 331 participants watched an hour-long episode from one of nine prime-time shows (~36 participants per episode). Three frequency-based measures were extracted: fronto-central alpha/beta asymmetry (indexing approach motivation), fronto-central alpha/theta power (indexing attention), and fronto-central theta/gamma power (indexing memory processing). All three EEG measures and the composite EEG score significantly correlated across episode segments with the two behavioral measures of TV viewership and Twitter volume. EEG measures explained more variance than either of the behavioral metrics and mediated the relationship between the two. Attentional focus was integral for both audience retention and Twitter activity, while emotional motivation was specifically linked with social engagement and program segments with high TV viewership. These findings highlight the viability of using EEG measures to predict success of TV programming and identify cognitive processes that contribute to audience engagement with television shows.

Temporal Dynamics and Response Modulation across the Human Visual System in a Spatial Attention Task: An ECoG Study.

The selection of behaviorally relevant information from cluttered visual scenes (often referred to as "attention") is mediated by a cortical large-scale network consisting of areas in occipital, temporal, parietal, and frontal cortex that is organized into a functional hierarchy of feedforward and feedback pathways. In the human brain, little is known about the temporal dynamics of attentional processing from studies at the mesoscopic level of electrocorticography (ECoG), that combines millisecond temporal resolution with precise anatomical localization of recording sites. We analyzed high-frequency broadband responses (HFB) responses from 626 electrodes implanted in 8 epilepsy patients who performed a spatial attention task. Electrode locations were reconstructed using a probabilistic atlas of the human visual system. HFB responses showed high spatial selectivity and tuning, constituting ECoG response fields (RFs), within and outside the topographic visual system. In accordance with monkey physiology studies, both RF widths and onset latencies increased systematically across the visual processing hierarchy. We used the spatial specificity of HFB responses to quantitatively study spatial attention effects and their temporal dynamics to probe a hierarchical top-down model suggesting that feedback signals back propagate the visual processing hierarchy. Consistent with such a model, the strengths of attentional modulation were found to be greater and modulation latencies to be shorter in posterior parietal cortex, middle temporal cortex and ventral extrastriate cortex compared with early visual cortex. However, inconsistent with such a model, attention effects were weaker and more delayed in anterior parietal and frontal cortex.SIGNIFICANCE STATEMENT In the human brain, visual attention has been predominantly studied using methods with high spatial, but poor temporal resolution such as fMRI, or high temporal, but poor spatial resolution such as EEG/MEG. Here, we investigate temporal dynamics and attention effects across the human visual system at a mesoscopic level that combines precise spatial and temporal measurements by using electrocorticography in epilepsy patients performing a classical spatial attention task. Electrode locations were reconstructed using a probabilistic atlas of the human visual system, thereby relating them to topography and processing hierarchy. We demonstrate regional differences in temporal dynamics across the attention network. Our findings do not fully support a top-down model that promotes influences on visual cortex by reversing the processing hierarchy.

Persistent neuronal activity in human prefrontal cortex links perception and action.

How do humans flexibly respond to changing environmental demands on a sub-second temporal scale? Extensive research has highlighted the key role of the prefrontal cortex in flexible decision-making and adaptive behavior, yet the core mechanisms that translate sensory information into behavior remain undefined. Utilizing direct human cortical recordings, we investigated the temporal and spatial evolution of neuronal activity, indexed by the broadband gamma signal, while sixteen participants performed a broad range of self-paced cognitive tasks. Here we describe a robust domain- and modality-independent pattern of persistent stimulus-to-response neural activation that encodes stimulus features and predicts motor output on a trial-by-trial basis with near-perfect accuracy. Observed across a distributed network of brain areas, this persistent neural activation is centered in the prefrontal cortex and is required for successful response implementation, providing a functional substrate for domain-general transformation of perception into action, critical for flexible behavior.

Amygdala-hippocampal dynamics during salient information processing.

Recognizing motivationally salient information is critical to guiding behaviour. The amygdala and hippocampus are thought to support this operation, but the circuit-level mechanism of this interaction is unclear. We used direct recordings in the amygdala and hippocampus from human epilepsy patients to examine oscillatory activity during processing of fearful faces compared with neutral landscapes. We report high gamma (70-180 Hz) activation for fearful faces with earlier stimulus evoked onset in the amygdala compared with the hippocampus. Attending to fearful faces compared with neutral landscape stimuli enhances low-frequency coupling between the amygdala and the hippocampus. The interaction between the amygdala and hippocampus is largely unidirectional, with theta/alpha oscillations in the amygdala modulating hippocampal gamma activity. Granger prediction, phase slope index and phase lag analysis corroborate this directional coupling. These results demonstrate that processing emotionally salient events in humans engages an amygdala-hippocampal network, with the amygdala influencing hippocampal dynamics during fear processing.

Redefining the role of Broca's area in speech.

For over a century neuroscientists have debated the dynamics by which human cortical language networks allow words to be spoken. Although it is widely accepted that Broca's area in the left inferior frontal gyrus plays an important role in this process, it was not possible, until recently, to detail the timing of its recruitment relative to other language areas, nor how it interacts with these areas during word production. Using direct cortical surface recordings in neurosurgical patients, we studied the evolution of activity in cortical neuronal populations, as well as the Granger causal interactions between them. We found that, during the cued production of words, a temporal cascade of neural activity proceeds from sensory representations of words in temporal cortex to their corresponding articulatory gestures in motor cortex. Broca's area mediates this cascade through reciprocal interactions with temporal and frontal motor regions. Contrary to classic notions of the role of Broca's area in speech, while motor cortex is activated during spoken responses, Broca's area is surprisingly silent. Moreover, when novel strings of articulatory gestures must be produced in response to nonword stimuli, neural activity is enhanced in Broca's area, but not in motor cortex. These unique data provide evidence that Broca's area coordinates the transformation of information across large-scale cortical networks involved in spoken word production. In this role, Broca's area formulates an appropriate articulatory code to be implemented by motor cortex.

Shifts in gamma phase-amplitude coupling frequency from theta to alpha over posterior cortex during visual tasks.

The phase of ongoing theta (4-8 Hz) and alpha (8-12 Hz) electrophysiological oscillations is coupled to high gamma (80-150 Hz) amplitude, which suggests that low-frequency oscillations modulate local cortical activity. While this phase-amplitude coupling (PAC) has been demonstrated in a variety of tasks and cortical regions, it has not been shown whether task demands differentially affect the regional distribution of the preferred low-frequency coupling to high gamma. To address this issue we investigated multiple-rhythm theta/alpha to high gamma PAC in two subjects with implanted subdural electrocorticographic grids. We show that high gamma amplitude couples to the theta and alpha troughs and demonstrate that, during visual tasks, alpha/high gamma coupling preferentially increases in visual cortical regions. These results suggest that low-frequency phase to high-frequency amplitude coupling is modulated by behavioral task and may reflect a mechanism for selection between communicating neuronal networks.

Automatic and strategic representation of the self in major depression: trait and state abnormalities.

OBJECTIVE: Dysfunctional negative thoughts about the self have long been hypothesized to reflect mood-independent cognitive vulnerability for major depressive disorder. These thoughts are believed to be predominantly automatic, in that they are involuntary and hard to inhibit. However, existing empirical evidence provides limited support for this theory, instead emphasizing the role of intentional ruminative (i.e., effortful) thoughts. To help clarify this theoretical controversy and investigate biased processing of emotional self-referent information in major depression, the authors utilized event-related brain potentials, which are used to index neural engagement during specific stages of cognitive processing. METHOD: The P2 and late positive event-related brain components were examined during a free recall task in patients with current (N=17) or remitted (N=18) major depression and healthy comparison subjects (N=17). Participants made judgments on whether a word described them (self-referential condition) or former U.S. President Bill Clinton (other-referential condition). RESULTS: Healthy comparison subjects and subjects with remitted, but not current, major depression demonstrated enhanced recall of positive self-referent items. Greater component amplitudes in response to negative relative to positive self-referent items were evident in individuals with current and remitted major depression during the automatic processing stage (indexed by the P2 component) and in individuals with current depression during effortful encoding (indexed by the late positive component). CONCLUSIONS: Observed mood-independent abnormalities in automatic processing and mood-dependent abnormalities in effortful processing of emotional self-referent information provide direct support for an integrative theory of cognitive dysfunction in major depression, which amalgamates two main, but largely competing, theories of the disorder.

Anticipation of affect in dysthymia: behavioral and neurophysiological indicators.

Anticipation for future affective events and prediction uncertainty were examined in healthy controls and individuals with dysthymia (DYS) using behavioral responses and the contingent negative variation (CNV) and post-imperative negative variation (PINV) event-related potential (ERP) components. Warning stimuli forecasted the valence of subsequently presented adjectives ("+", positive; "=", neutral; "-", negative), and participants indicated whether each adjective would describe them over the next two weeks. Controls expected fewer negative, and individuals with DYS expected fewer positive, adjectives to apply to them. CNV amplitudes were enhanced in controls prior to positive versus other adjectives. Response times and PINV amplitudes were greater following neutral compared to other adjectives, and PINV was larger overall in dysthymics compared to controls. In sum, healthy controls and individuals with DYS exhibit different behavioral and neurophysiological biases in anticipation for future affective events. These results are discussed in the context of cognitive theories of depression.

Reduced sustained brain activity during processing of positive emotional stimuli in major depression.

BACKGROUND: This study examines the directionality and temporal specificity of brain activity during sustained processing of emotional stimuli in individuals with current major depressive disorder (MDD) and nondepressed control participants. METHODS: Slow wave (SW) components of the event-related brain potential (ERP) were recorded from 16 control participants and 15 participants with MDD during a working memory task. During the task, individuals were shown a positive, neutral, or negative word and were asked to maintain it in memory for 5 sec. Participants then saw a letter and had to decide whether it was a part of the previously presented word. The ERP components were measured from nine scalp sites (F3, Fz, F4, C3, Cz, C4, P3, Pz, P4) during the encoding of emotional words. RESULTS: Compared with control individuals, MDD participants exhibited decreased brain responses to positive relative to negative or neutral stimuli. This decrease in brain activity during processing of positive information was evident across all sites and SW components. CONCLUSIONS: Our findings suggest that cognitive deficits in MDD may stem from diminished brain responses during processing of positive information and may not be associated with an augmented response to negative stimuli.