Brain areas within the lateral parietal cortex (LPC) and ventral temporal cortex (VTC) have been shown to code for abstract quantity representations and for symbolic numerical representations, respectively. To explore the fast dynamics of activity within each region and the interaction between them, we used electrocorticography recordings from 16 neurosurgical subjects implanted with grids of electrodes over these two regions and tracked the activity within and between the regions as subjects performed three different numerical tasks. Although our results reconfirm the presence of math-selective hubs within the VTC and LPC, we report here a remarkable heterogeneity of neural responses within each region at both millimeter and millisecond scales. Moreover, we show that the heterogeneity of response profiles within each hub mirrors the distinct patterns of functional coupling between them. Our results support the existence of multiple bidirectional functional loops operating between discrete populations of neurons within the VTC and LPC during the visual processing of numerals and the performance of arithmetic functions. These findings reveal information about the dynamics of numerical processing in the brain and also provide insight into the fine-grained functional architecture and connectivity within the human brain.A lthough the ability to approximate or compare rough quantities is present even in human infants (1) and in other species such as nonhuman primates (2-4) and birds (5), the association of exact quantities with symbols (e.g., the numeral "10") or verbal representations (e.g., the word "ten") is unique to humans exposed to such culturally learned entities (6-8). Moreover, dissociable number-and quantity-related behavioral deficits (i.e., deficits relating to symbolic or verbal numerical representations versus abstract quantity representations) are associated with different lesion locations within the brain (9-14). These observations in part motivated the Triple Code model positing that the human brain contains three different numerical representations: symbolic, verbal, and abstract quantity, each coded in a different brain region (15,16). The model also predicts that, depending on task demands (e.g., simple visual recognition of a numeral versus determining the larger of two numerals versus verbal naming of a numeral), all or a subset of these brain regions interact with each other (15, 16).Neuroimaging, electrophysiology, and lesion studies in both humans and nonhuman primates have long implicated the parietal lobe, particularly the anterior segment of the intraparietal sulcus (aIPS), in abstract quantity representations irrespective of the modality of presentation (e.g., "4" vs. "four" vs. "::"), with specific neurons or neuronal populations exhibiting tuning around a preferred numerosity (4, 17-25). Moreover, brain activity within this region and its functional and anatomical connectivity with other brain regions are correlated with mathematical performance in individual subjects (26)(27)(28)(29),...

Selective attention allows us to filter out irrelevant information in the environment and focus neural resources on information relevant to our current goals. Functional brain-imaging studies have identified networks of broadly distributed brain regions that are recruited during different attention processes; however, the dynamics by which these networks enable selection are not well understood. Here, we first used functional MRI to localize dorsal and ventral attention networks in human epileptic subjects undergoing seizure monitoring. We subsequently recorded cortical physiology using subdural electrocorticography during a spatialattention task to study network dynamics. Attention networks become selectively phase-modulated at low frequencies (δ, θ) during the same task epochs in which they are recruited in functional MRI. This mechanism may alter the excitability of task-relevant regions or their effective connectivity. Furthermore, different attention processes (holding vs. shifting attention) are associated with synchrony at different frequencies, which may minimize unnecessary cross-talk between separate neuronal processes.O ne of the hallmarks of effective behavior is the ability to flexibly attend to particular stimuli in the environment. Selective attention can be driven endogenously by one's current goals or by salient external stimuli. Human neuroimaging studies have identified two sets of fronto-parietal regions that are recruited during these two types of attention. A set of dorsal fronto-parietal regions (dorsal attention network or DAN) shows sustained activity during endogenous or goal-driven attention (1), and reorienting to unexpected targets transiently activates both the DAN and a second set of regions, the ventral attention network (VAN) (2). Although functional MRI (fMRI) has identified the brain regions that are involved in these attentional operations (3, 4), the slow nature of the hemodynamic response has severely limited the study of network dynamics at behaviorally relevant time scales (5). Here, we report results obtained by cortical surface (electrocorticography or ECoG) recordings in epilepsy patients undergoing clinical monitoring to identify seizure foci. Electrode locations for each subject were colocalized with functional brain networks, including the DAN and VAN identified in the same subjects using fMRI. This experimental paradigm allowed us to objectively link fast electrophysiological dynamics, during performance of an attention task, to well-studied functional brain networks.ECoG measures nonspiking, local field potential oscillations across a range of frequencies, which are thought to reflect fluctuations in local neuronal excitability (6, 7). Phase modulations of activity within a region and between regions may therefore affect, respectively, their ability to respond to inputs and to transfer information between one another (8, 9). In support of this theory, previous studies in both animals and humans have shown that either local or long-distance synchrony change in a tas...

The human default network (DN) plays a critical role in internally directed cognition, behavior, and neuropsychiatric disease. Despite much progress with functional neuroimaging, persistent questions still linger concerning the electrophysiological underpinnings, fast temporal dynamics, and causal importance of the DN. Here, we review how direct intracranial recording and stimulation of the DN provides a unique combination of high spatiotemporal resolution and causal information that speaks directly to many of these outstanding questions. Our synthesis highlights the electrophysiological basis of activation, suppression, and connectivity of the DN, each key areas of debate in the literature. Integrating these unique electrophysiological data with extant neuroimaging findings will help lay the foundation for a mechanistic account of DN function in human behavior and cognition.

Neuroimaging evidence suggests that the default mode network (DMN) exhibits antagonistic activity with dorsal attention (DAN) and salience (SN) networks. Here we use human intracranial electroencephalography to investigate the behavioral relevance of fine-grained dynamics within and between these networks. The three networks show dissociable profiles of task-evoked electrophysiological activity, best captured in the high-frequency broadband (HFB; 70-170 Hz) range. On the order of hundreds of milliseconds, HFB responses peak fastest in the DAN, at intermediate speed in the SN, and slowest in the DMN. Lapses of attention (behavioral errors) are marked by distinguishable patterns of both pre-and poststimulus HFB activity within each network. Moreover, the magnitude of temporally lagged, negative HFB coupling between the DAN and DMN (but not SN and DMN) is associated with greater sustained attention performance and is reduced during wakeful rest. These findings underscore the behavioral relevance of temporally delayed coordination between antagonistic brain networks.

This study shows that electrocorticographic (ECoG) signals recorded from the surface of the brain provide detailed information about shifting of visual attention and its directional orientation in humans. ECoG allows for the identification of the cortical areas and time periods that hold the most information about covert attentional shifts. Our results suggest a transient distributed fronto-parietal mechanism for orienting of attention that is represented by different physiological processes. This neural mechanism encodes not only whether or not a subject shifts their attention to a location, but also the locus of attention. This work contributes to our understanding of the electrophysiological representation of attention in humans. It may also eventually lead to brain-computer interfaces (BCIs) that optimize user interaction with their surroundings or that allow people to communicate choices simply by shifting attention to them.