Layered hydrogels accelerate iPSC-derived neuronal maturation and reveal migration defects caused by MeCP2 dysfunction

Probing a wide range of cellular phenotypes in neurodevelopmental disorders using patient-derived neural progenitor cells (NPCs) can be facilitated by 3D assays, as 2D systems cannot entirely recapitulate the arrangement of cells in the brain. Here, we developed a previously unidentified 3D migration and differentiation assay in layered hydrogels to examine how these processes are affected in neurodevelopmental disorders, such as Rett syndrome. Our soft 3D system mimics the brain environment and accelerates maturation of neurons from human induced pluripotent stem cell (iPSC)-derived NPCs, yielding electrophysiologically active neurons within just 3 wk. Using this platform, we revealed a genotype-specific effect of methyl-CpG-binding protein-2 (MeCP2) dysfunction on iPSC-derived neuronal migration and maturation (reduced neurite outgrowth and fewer synapses) in 3D layered hydrogels. Thus, this 3D system expands the range of neural phenotypes that can be studied in vitro to include those influenced by physical and mechanical stimuli or requiring specific arrangements of multiple cell types.Neuronal migration and maturation is a key step in brain development. Defects in this process have been implicated in many disorders, including autism (1) and schizophrenia (2). Thoroughly understanding how neural progenitor cell (NPC) migration is affected in neurodevelopmental disorders requires a means of dissecting the process using cells with genetic alterations matching those in patients. Existing in vitro assays of migration generally involve measurement of cell movement across a scratch or gap or through a membrane toward a chemoattractant in 2D culture systems. Although widely used, such assays may not accurately reveal in vivo differences, as neuronal migration is tightly regulated by physical and chemical cues in the extracellular matrix (ECM) that NPCs encounter as they migrate.In vitro 3D culture systems offer a solution to these limitations (3–7). Compared with 2D culture, a 3D arrangement allows neuronal cells to interact with many more cells (4); this similarity to the in vivo setting has been shown to lengthen viability, enhance survival, and allow formation of longer neurites and more dense networks in primary neurons in uniform matrices or aggregate culture (8, 9). Indeed, 3D culture systems have been used to study nerve regeneration, neuronal and glial development (10–12), and amyloid-β and tau pathology (13). Thus, measuring neuronal migration through a soft 3D matrix would continue this trend toward using 3D systems to study neuronal development and pathology.We sought to develop a 3D assay to examine potential migration and neuronal maturation defects in Rett syndrome (RTT), a genetic neurodevelopmental disorder that affects 1 in 10,000 children in the United States and is caused by mutations in the X-linked methyl-CpG-binding protein-2 (MECP2) gene (14). Studies using induced pluripotent stem cells (iPSCs) from RTT patients in traditional 2D adherent culture have revealed reduced neurite outgrowth and synapse number, as well as altered calcium transients and spontaneous postsynaptic currents (1). However, 2D migration assays seemed unlikely to reveal inherent defects in this developmental process, which could be affected because MeCP2 regulates multiple developmental related genes (15). Migration of RTT iPSC-derived NPCs has not previously been studied.Using a previously unidentified 3D tissue culture system that allows creation of layered architectures, we studied differences in migration of MeCP2-mutant iPSC-derived versus control iPSC-derived NPCs. This approach revealed a defect in migration of MeCP2-mutant iPSC-derived NPCs induced by either astrocytes or neurons. Further, this 3D system accelerated maturation of neurons from human iPSC-derived NPCs, yielding electrophysiologically active neurons within just 3 wk. With mature neurons derived from RTT patients and controls, we further confirmed defective neurite outgrowth and synaptogenesis in MeCP2-mutant neurons. Thus, this 3D system enables study of morphological features accessible in 2D system as well as previously unexamined phenotypes.     

Epileptic baboons have lower numbers of neurons in specific areas of cortex

Epilepsy is characterized by recurrent seizure activity that can induce pathological reorganization and alter normal function in neocortical networks. In the present study, we determined the numbers of cells and neurons across the complete extent of the cortex for two epileptic baboons with naturally occurring seizures and two baboons without epilepsy. Overall, the two epileptic baboons had a 37% average reduction in the number of cortical neurons compared with the two nonepileptic baboons. The loss of neurons was variable across cortical areas, with the most pronounced loss in the primary motor cortex, especially in lateral primary motor cortex, representing the hand and face. Less-pronounced reductions of neurons were found in other parts of the frontal cortex and in somatosensory cortex, but no reduction was apparent in the primary visual cortex and little in other visual areas. The results provide clear evidence that epilepsy in the baboon is associated with considerable reduction in the numbers of cortical neurons, especially in frontal areas of the cortex related to motor functions. Whether or not the reduction of neurons is a cause or an effect of seizures needs further investigation.Epilepsy is associated with structural changes in the cerebral cortex (e.g., refs. 1–6), and partial epilepsies (i.e., seizures originating from a brain region) may lead to loss of neurons (7) and altered connectivity (8). The cerebral cortex is a heterogeneous structure comprised of multiple sensory and motor information-processing systems (e.g., refs. 9 and 10) that vary according to their processing demands, connectivity (e.g., refs. 11 and 12), and intrinsic numbers of cells and neurons (13–16). Chronic seizures have been associated with progressive changes in the region of the epileptic focus and in remote but functionally connected cortical or subcortical structures (3, 17). Because areas of the cortex are functionally and structurally different, they may also differ in susceptibility to pathological changes resulting from epilepsy.The relationship between seizure activity and neuron damage can be difficult to study in humans. Seizure-induced neuronal damage can be convincingly demonstrated in animals using electrically or chemically induced status epilepticus (one continuous seizure episode longer than 5 min) to reveal morphometric (e.g., refs. 18 and 19) or histological changes (e.g., refs. 20 and 21). Subcortical brain regions are often studied for vulnerability to seizure-induced injury (21–27); however, a recent study by Karbowski et al. (28) observed reduction of neurons in cortical layers 5 and 6 in the frontal lobes of rats with seizures. Seizure-induced neuronal damage in the cortex has also been previously demonstrated in baboons with convulsive status epilepticus (29).The goal of the present study was to determine if there is a specific pattern of cell or neuron reduction across the functionally divided areas of the neocortex in baboons with epilepsy. Selected strains of baboons have been studied as a natural primate model of generalized epilepsy (30–36) that is analogous to juvenile myoclonic epilepsy in humans. The baboons demonstrate generalized myoclonic and tonic-clonic seizures, and they have generalized interictal and ictal epileptic discharges on scalp EEG. Because of their phylogenetic proximity to humans, baboons and other Old World monkeys share many cortical areas and other features of cortical organization with humans (e.g., refs. 9 and 10). Cortical cell and neuron numbers were determined using the flow fractionator method (37, 38) in epileptic baboon tissue obtained from the Texas Biomedical Research Institute, where a number of individuals develop generalized epilepsy within a pedigreed baboon colony (31–36). Our results reveal a regionally specific neuron reduction in the cortex of baboons with naturally occurring, generalized seizures.     

Sleep promotes the formation of dendritic filopodia and spines near learning-inactive existing spines

Changes in synaptic connections are believed to underlie long-term memory storage. Previous studies have suggested that sleep is important for synapse formation after learning, but how sleep is involved in the process of synapse formation remains unclear. To address this question, we used transcranial two-photon microscopy to investigate the effect of postlearning sleep on the location of newly formed dendritic filopodia and spines of layer 5 pyramidal neurons in the primary motor cortex of adolescent mice. We found that newly formed filopodia and spines were partially clustered with existing spines along individual dendritic segments 24 h after motor training. Notably, posttraining sleep was critical for promoting the formation of dendritic filopodia and spines clustered with existing spines within 8 h. A fraction of these filopodia was converted into new spines and contributed to clustered spine formation 24 h after motor training. This sleep-dependent spine formation via filopodia was different from retraining-induced new spine formation, which emerged from dendritic shafts without prior presence of filopodia. Furthermore, sleep-dependent new filopodia and spines tended to be formed away from existing spines that were active at the time of motor training. Taken together, these findings reveal a role of postlearning sleep in regulating the number and location of new synapses via promoting filopodial formation.

Learning and memory consolidation are associated with the rewiring of neuronal network connectivity (1–3). Previous studies have shown that motor training leads to the formation and elimination of postsynaptic dendritic spines of pyramidal neurons in the primary motor cortex (M1) (4–8). Learning-induced new spines stabilize and persist over long periods of time (4). The extent of spine remodeling correlates with behavioral improvement after learning (4, 9), and the disruption of spine remodeling impairs learned motor behavior (10–12). These studies suggest that learning-induced new synapses contribute to changes in neuronal circuits that are likely important for the retention of learned behaviors (13, 14).Cumulative evidence suggests that sleep affects synaptic structural plasticity in many brain regions (15–17). For example, sleep has been shown to promote spine formation and elimination in developing somatosensory and visual cortices (18, 19). In the motor cortex, sleep promotes branch-specific formation of new dendritic spines following motor learning and selectively stabilizes learning-induced new synaptic connections (11, 12). Sleep has also been shown to regulate dendritic spine numbers in hippocampal CA1 area (20–22). In addition, many lines of evidence have revealed the function of sleep in increasing, decreasing, or stabilizing synaptic strength and neuronal firing in various brain regions (23–31). Together, these studies strongly suggest that sleep has an important role in promoting synaptic structural plasticity in neuronal circuits during development and after learning.While sleep promotes the formation of new spines after learning (12), it remains unknown how postlearning sleep regulates new synapse formation along dendritic branches. Synapse formation is a prolonged process often involving the generation of dendritic filopodia, thin and long protrusions without bulbous heads (32–35). These highly dynamic filopodia have been shown to initiate the contact with presynaptic axonal terminals and transform into new spines (36, 37). It is not known whether sleep promotes new spine formation via filopodia formation and subsequent transformation. Furthermore, it is also unclear whether sleep-dependent formation of new dendritic protrusions (filopodia and spines) is distributed on dendritic branches in a random or nonrandom manner. On the one hand, new synapses may be formed in clusters with synapses of similar functions to allow nonlinear summation of inputs important for increasing memory storage capacity (9, 38–43). On the other hand, new connections may be formed preferentially near less active/strong synapses to avoid competition for limited synaptic resources (44–47).In this study, we found that dendritic filopodia and spines formed after motor training were partially clustered with existing spines on apical tuft dendrites of layer 5 (L5) pyramidal neurons in the mouse primary motor cortex. Posttraining sleep was critical for the clustered formation of new filopodia, some of which were transformed into new spines. In addition, the clustered new filopodia and spines tended to be formed near existing spines that were inactive at the time of motor training. These findings reveal a role for sleep in neuronal circuit plasticity by promoting clustered spine formation via dendritic filopodia near learning-inactive existing spines.     

Rehabilitation drives enhancement of neuronal structure in functionally relevant neuronal subsets

We determined whether rehabilitation after cortical injury also drives dynamic dendritic and spine changes in functionally distinct subsets of neurons, resulting in functional recovery. Moreover, given known requirements for cholinergic systems in mediating complex forms of cortical plasticity, including skilled motor learning, we hypothesized that cholinergic systems are essential mediators of neuronal structural and functional plasticity associated with motor rehabilitation. Adult rats learned a skilled forelimb grasping task and then, underwent destructive lesions of the caudal forelimb region of the motor cortex, resulting in nearly complete loss of grasping ability. Subsequent intensive rehabilitation significantly enhanced both dendritic architecture and spine number in the adjoining rostral forelimb area compared with that in the lesioned animals that were not rehabilitated. Cholinergic ablation markedly attenuated rehabilitation-induced recovery in both neuronal structure and motor function. Thus, rehabilitation focused on an affected limb robustly drives structural compensation in perilesion cortex, enabling functional recovery.Studies over the past decade have indicated that the adult brain is structurally dynamic (1–3). Indeed, dendritic spines dynamically turn over in the adult brain (3, 4), and learning of novel tasks is associated with further increases in spine turnover (4). Moreover, total and stable increases in spine number together with enhanced dendritic complexity can be detected when analyses are focused specifically on neuronal subpopulations that are functionally related to a newly learned motor skill (5). For example, we recently reported that cortical layer V pyramidal neurons, which project to spinal segment C8 and are specifically engaged when learning a skilled forelimb grasping task, elaborate a 22% increase in apical dendritic spines and exhibit significant increases in dendritic branching and total dendritic length (5); an adjoining control population of cortical layer V pyramidal neurons that project to C4, which are not specifically shaped by the skilled motor task, exhibits no change in spines or dendritic complexity when the same task is learned (5). The detection of stable structural increases in neurons engaged by skilled motor learning in contrast to a lack of change in adjacent neurons that are not engaged by learning advances our understanding of mechanisms underlying experience-dependent cortical plasticity.Damage to the adult CNS also generates adaptive brain plasticity. For example, focal cortical lesions evoke cortical map plasticity (6, 7), extension of new axonal connections (7, 8), and neurogenesis (9). A very important and unresolved question in the neural plasticity and injury fields is whether rehabilitation—that is, specific retraining of injured neural circuits—can drive, alter, or enhance neural plasticity subsequent to brain lesions. Whereas extensive literature has shown that rehabilitation can increase the numbers of dendritic spines and dendritic complexity in the cortical hemisphere opposite a brain lesion (10–13) and is associated with improved skill in the limb unaffected by the lesion, effects of rehabilitation on neuronal structure in perilesioned cortex have not been described. Indeed, some studies suggest either stability or early loss of dendritic structure in perilesion cortex (14–16). However, knowing whether rehabilitation can drive adaptive brain plasticity could be essential in improving outcomes of numerous CNS disorders acquired in adulthood, including stroke, traumatic brain injury, and spinal cord injury.Prior studies that have sought to interrogate neuronal structure after injury have been limited by their use of nonspecific cellular sampling methods, such as Golgi–Cox staining or EM; these approaches lack the ability to specifically sample structural changes in neurons associated with specific tasks that are practiced in rehabilitation. Sampling from subpopulations of neurons mediating specific behaviors, such as skilled grasping in the motor cortex, may yield far more sensitive measures of changes in dendritic structure and spine number as a function of rehabilitation, fundamentally advancing our understanding of the role of experience and rehabilitation on structural neuronal plasticity.Another consideration in understanding cortical mechanisms underlying plasticity after CNS injury is the contribution of subcortical systems that modulate cortical activity, including cholinergic inputs. Studies have identified an essential role for cholinergic activation in modulating cortical plasticity associated with learning (17–19) and motor map plasticity that is evoked after lesions of the caudal forelimb region of the motor cortex (6, 20). These observations raise the possibility that cholinergic inputs to the motor cortex are also essential for generating neuronal structural adaptations in response to rehabilitation training after injury.In this study, we hypothesized that rehabilitation after injury to the adult brain drives adaptive plasticity, rebuilding spines and enhancing dendritic architecture in neurons surrounding the lesion site. We further hypothesize that these changes are cholinergic-dependent. We examined specific subpopulations of layer V cortical neurons directly related to the learning, loss, and subsequent relearning of skilled forelimb grasping, allowing detailed and specific sampling of structural parameters among subpopulations of neurons specifically engaged in the skilled grasping task.     

Behavioral response inhibition and maturation of goal representation in prefrontal cortex after puberty

Executive functions including behavioral response inhibition mature after puberty, in tandem with structural changes in the prefrontal cortex. Little is known about how activity of prefrontal neurons relates to this profound cognitive development. To examine this, we tracked neuronal responses of the prefrontal cortex in monkeys as they transitioned from puberty into adulthood and compared activity at different developmental stages. Performance of the antisaccade task greatly improved in this period. Among neural mechanisms that could facilitate it, reduction of stimulus-driven activity, increased saccadic activity, or enhanced representation of the opposing goal location, only the latter was evident in adulthood. Greatly accentuated in adults, this neural correlate of vector inversion may be a prerequisite to the formation of a motor plan to look away from the stimulus. Our results suggest that the prefrontal mechanisms that underlie mature performance on the antisaccade task are more strongly associated with forming an alternative plan of action than with suppressing the neural impact of the prepotent stimulus.Behavioral response inhibition, and cognitive task performance more generally, improves substantially between the time of puberty and adulthood (1–4). Risky decision-making peaks in adolescence, the time period between puberty and adulthood that is most closely linked to delinquent behavior in humans (5–7). Performance in tasks that assay response inhibition, such as the antisaccade task, improves into adulthood, reflecting the progressive development of behavioral control (3). This period of cognitive enhancement parallels the maturation of the prefrontal cortex (8–11). Anatomical changes in the prefrontal cortex continue during adolescence, involving gray and white matter volumes and myelination of axon fibers within the prefrontal cortex and between the prefrontal cortex and other areas (8–15). Changes in prefrontal activation, including increases (12, 16–20) and decreases (21, 22), have been documented in imaging studies for tasks that require inhibition of prepotent behavioral responses and filtering of distractors.Much less is known about how the physiological properties of prefrontal neurons develop after puberty. Similar to the human pattern of development, the monkey prefrontal cortex undergoes anatomical maturation in adolescence and early adulthood (23, 24). Male monkeys enter puberty at ∼3.5 y of age and reach full sexual maturity at 5 y, approximately equivalent to the human ages of 11 y and 16 y, respectively (25, 26). By some accounts, biochemical and anatomical changes characteristic of adolescence in humans occur at an earlier, prepubertal age in the monkey prefrontal cortex (27, 28), so it is not known if cognitive maturation or neurophysiological changes occur in monkeys after puberty. The contribution of prefrontal cortex to antisaccade performance has also been a matter of debate, with contrasting views favoring mechanisms of inhibiting movement toward the visual stimulus or enhancing movement away from it (29–31). Potential maturation of behavioral response inhibition may therefore be associated with a more efficient suppression of the stimulus representation in neural activity (weaker visual responses to stimuli inside the receptive field), stronger motor responses (higher activity to saccades), or enhancement of the appropriate goal representation (stronger activity for planning a saccade away from the stimulus). To examine the mechanisms that facilitate the mature ability to resist generating a response toward a salient stimulus, we used developmental markers to track transition from puberty to adulthood in monkeys and sought to identify neural correlates of changes in antisaccade performance within the visual and saccade-related activations of prefrontal neurons.     

Eye contact marks the rise and fall of shared attention in conversation

Conversation is the platform where minds meet: the venue where information is shared, ideas cocreated, cultural norms shaped, and social bonds forged. Its frequency and ease belie its complexity. Every conversation weaves a unique shared narrative from the contributions of independent minds, requiring partners to flexibly move into and out of alignment as needed for conversation to both cohere and evolve. How two minds achieve this coordination is poorly understood. Here we test whether eye contact, a common feature of conversation, predicts this coordination by measuring dyadic pupillary synchrony (a corollary of shared attention) during natural conversation. We find that eye contact is positively correlated with synchrony as well as ratings of engagement by conversation partners. However, rather than elicit synchrony, eye contact commences as synchrony peaks and predicts its immediate and subsequent decline until eye contact breaks. This relationship suggests that eye contact signals when shared attention is high. Furthermore, we speculate that eye contact may play a corrective role in disrupting shared attention (reducing synchrony) as needed to facilitate independent contributions to conversation.

Good conversations proceed effortlessly, as if conversation partners share a single mind. This effortlessness obscures the complexities involved. Conversation partners must weave shared understanding from alternating independent contributions (1–4) in an act of spontaneous, dynamic cocreation. Given too few independent insights, conversation stagnates. When there is insufficient common ground, people talk past each other. Even deciding when conversation should end is a feat of social coordination (5). Engaging conversation must continuously negotiate the delicate balance between creating shared understanding while allowing the conversation to move forward and evolve. How do two minds negotiate this balance?There are several reasons to believe that eye contact may play an instrumental role. Eye contact—when two people look at each other’s eyes—occurs ubiquitously in conversation, often at the ends of turns when partners pass the conversational baton (6–9). It is possible that the known effects of eye contact on arousal (10–12) and attention (13–15) may nudge partners at critical moments in the conversation that facilitate this exchange. The ubiquity yet brevity of eye contact in natural conversation, averaging 1.9 s (9), also suggests that these attentional nudges are not scattered randomly but occur at precise times to optimize the attention of both parties. Here we tested whether eye contact has a particular relationship with shared attention during natural conversation.To quantify the dynamic wax and wane of shared attention during natural conversation, we employed dyadic high temporal resolution pupillometry. Under light constancy, pupil diameter fluctuates coincident with neuronal activity in the locus coeruleus (16, 17), which is associated with attention (18–20). Furthermore, an attention-inducing stimulus evokes an associated pupillary response (i.e., a dilation and return to baseline) (21). Monitoring these pupil responses over time provides a continuous index of attention (22–26). When people attend to the same dynamic stimulus, their pupillary time series can be compared as a measure of shared attention, with similar pupillary time series indexing similar time series of attention. Unlike joint attention, shared attention does not require eye contact or gestures followed by attention to a third object. Rather, shared attention can refer to any situation in which individuals are attending to the same stimulus and can occur with or without eye contact (27). While pupil mimicry has been a documented outcome of looking at another’s eyes (28, 29), shared attention can also exist in the absence of any visual stimulus (e.g., two people listening to the same music) (30).We use the term “pupillary synchrony” to refer to how closely two conversation partners’ pupillary time series covary over time (31). Previous studies have also used this definition of synchrony to measure covariation of other physiological and behavioral responses [e.g., brain blood oxygenation levels (32); neuroelectrical activity (33–35); heart-rate variability (36)]. Here we used pupillary synchrony between conversation partners to capture temporal variation in shared attention over the course of a natural conversation.We are not the first to examine intersubject synchrony and eye contact. Leong et al. (33) showed that infant–adult dyads exhibit more brain-to-brain synchrony in EEG while making direct gaze than when interacting with their gaze averted. Similarly, students in real classrooms showed more neural synchrony in EEG while learning with classmates with whom they had previously made eye contact (34). Kinreich et al. (35) used EEG to measure synchrony while dyads planned a fun day to spend together and found that moments of eye contact were correlated with neural synchrony. Additionally, research with both functional near infrared spectroscopy and hyperscanning fMRI paradigms have also found neural synchrony during eye contact in a wide variety of scenarios and across multiple brain regions (37–41), leading to the prevailing inference that eye contact enhances synchrony (37). Yet exactly how eye contact and synchrony are linked is not understood. Does eye contact precede synchrony, as enhancement would suggest, or follow it? Here we probe how eye contact is linked to pupillary synchrony by investigating the temporal relationship between the two.It is also unclear when synchrony in conversation is desirable. The majority of the synchrony literature relies on tasks in which shared attention equates to better performance. For example, when individuals hear the same story or watch the same movie, the degree to which they have similar responses positively predicts their comprehension of (42, 43) and shared memory for (44) the shared stimulus. But conversation involves more than perceiving a shared stimulus: it requires fluidly shifting between shared and independent modes of thought, from comprehension of what is being said to formulating one’s next contribution (45). These independent contributions allow a conversation to move and evolve. We therefore not only test the relationship between eye contact and pupillary synchrony, but also how both relate to success in conversation as measured by ratings of engagement (46, 47) made by the partners themselves.In the present study, dyads engaged in unstructured conversation while their eyes were tracked. Afterward, they separately rewatched their conversations while continuously rating how engaged they remembered feeling. We show that eye contact is correlated with dyadic pupillary synchrony during these unstructured conversations, consistent with the research summarized above. Furthermore, we find that eye contact has a distinct temporal relationship with pupillary synchrony consistent with (though not proof of) a coordinative role. Conversation partners make eye-contact as pupillary synchrony peaks, which may provide a communicative signal that shared attention is high. Pupillary synchrony then immediately and sharply decreases until eye contact stops. This temporal relationship suggests that eye contact (or its correlates) may actually reduce shared attention, perhaps to allow for individual contributions that enable a conversation to evolve. Consistent with this inference, we find that the amount of eye contact—not synchrony—predicts self-reported engagement by conversation partners. Rather than maximizing shared attention, a good conversation may require shifts into and out of a shared attentional state, with these shifts accompanied by eye contact.     

Transcranial stimulation of alpha oscillations up-regulates the default mode network

The default mode network (DMN) is the most-prominent intrinsic connectivity network, serving as a key architecture of the brain’s functional organization. Conversely, dysregulated DMN is characteristic of major neuropsychiatric disorders. However, the field still lacks mechanistic insights into the regulation of the DMN and effective interventions for DMN dysregulation. The current study approached this problem by manipulating neural synchrony, particularly alpha (8 to 12 Hz) oscillations, a dominant intrinsic oscillatory activity that has been increasingly associated with the DMN in both function and physiology. Using high-definition alpha-frequency transcranial alternating current stimulation (α-tACS) to stimulate the cortical source of alpha oscillations, in combination with simultaneous electroencephalography and functional MRI (EEG-fMRI), we demonstrated that α-tACS (versus Sham control) not only augmented EEG alpha oscillations but also strengthened fMRI and (source-level) alpha connectivity within the core of the DMN. Importantly, increase in alpha oscillations mediated the DMN connectivity enhancement. These findings thus identify a mechanistic link between alpha oscillations and DMN functioning. That transcranial alpha modulation can up-regulate the DMN further highlights an effective noninvasive intervention to normalize DMN functioning in various disorders.

It is widely recognized that the brain self-organizes into large-scale intrinsic networks. Such intrinsic organization is so fundamental to normal neural functioning that it commands 60 to 80% of the brain’s energy (1). Two main mechanisms—intrinsic interregional connectivity and interneuronal synchrony—are thought to underpin the brain’s organization (2–6). The default mode network (DMN), emerging from intrinsic interregional connectivity crisscrossing a large extent of the brain, occupies the apex of intrinsic connectivity networks (7) and dominates the brain’s intrinsic activity (1, 8). Accordingly, the DMN supports advanced human mental faculties (e.g., consciousness, self-reference, social inference, remembering the past, and expecting the future) (8), while its dysregulation is characteristic of major neuropsychiatric disorders (e.g., DMN hyperconnectivity in major depression and hypoconnectivity in Alzheimer’s disease, schizophrenia, and posttraumatic stress disorder) (9–12). However, mechanisms regulating the DMN remain elusive, while effective interventions for DMN dysregulation are lacking.Interneuronal synchrony is thought to be inherently related to interregional connectivity and potentially bind and sculpt such connectivity through neural development (2–6). Importantly, the alpha (8 to 12 Hz) oscillation, the primary rhythm of intrinsic neural synchrony (13, 14), has been linked to the DMN functioning (4, 15). In fact, rapid advances in neuroimaging and neurocomputing have brought forward mounting evidence of multifaceted physiological and functional associations between the alpha oscillation and the DMN. Physiologically, resting-state (RS) simultaneous EEG-fMRI (electroencephalography and functional MRI) recordings have revealed intrinsic positive coupling between alpha oscillations and DMN activity (16–20). Of particular relevance, akin to its role in long-range neural communication, alpha oscillations are found to be the primary neural synchrony linking the posterior and anterior hubs of the DMN (the posterior cingulate cortex [PCC] and medial prefrontal cortex [mPFC], respectively) (15, 19, 21, 22). Functionally, alpha oscillations and the DMN are both involved in disengaging the brain from the sensory environment and maintaining the RS (1, 13, 23), while alpha desynchrony and DMN dysconnectivity, including specific disruption of alpha-oscillatory PCC-mPFC connectivity, co-occur in several major neuropsychiatric disorders (e.g., Alzheimer’s disease, schizophrenia, and posttraumatic stress disorder) (24–26).Nonetheless, these associations between alpha oscillations and the DMN remain correlational in nature, calling for experimental investigation to ascertain their mechanistic linkage. Owing to the proximity of its primary source (the occipitoparietal cortex) to the scalp, the alpha oscillation is highly responsive to transcranial stimulation (27–30) and can be a viable target for experimental manipulation. Among the many transcranial stimulation technologies, transcranial alternating current stimulation (tACS) applies frequency-specific sinusoidal electric currents through the scalp, which is uniquely advantageous in mimicking and entraining endogenous oscillations by tuning not only the frequency and amplitude but also the oscillatory phase. The latter, by enhancing phase synchronization, could be particularly effective at facilitating interregional connectivity (31). Therefore, we experimentally manipulated alpha oscillations with MR-compatible high-definition (HD) alpha-frequency tACS (α-tACS) targeting the occipitoparietal alpha source. Using RS simultaneous EEG-fMRI recordings, we measured concurrent changes in alpha synchrony (EEG alpha power and connectivity) and DMN connectivity (fMRI blood oxygen level–dependent [BOLD] connectivity) before and after tACS (versus Sham control) and tested the hypothesis that enhanced alpha synchrony via tACS can facilitate the synchronization of BOLD fluctuations, resulting in increased DMN connectivity.     

Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers

Visual search is a workhorse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed a search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified “feature columns” which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4’s superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.

Throughout cortex, sensory information is organized into maps. This phenomenon is readily observable in visual cortex where maps organize information in both the radial (e.g., within cortical columns) and tangential (e.g., across a cortical area) dimensions (1–4). Importantly, sensory information attributed to these maps is malleable. For example, selective attention is linked to profound changes in neural activity organizing sensory information in both space and time (5–34).In visual cortex, cortical columnar microcircuits comprise many neurons that respond to the same location of visual space and similar stimulus features. For example, primary visual cortex (V1) features “orientation columns” consisting of neurons sharing response preference for the same stimulus orientation (35, 36) and “ocular dominance columns” consisting of neurons that preferentially respond to the same eye (37). Similar columnar organization for feature selectivity has been described across many other visual cortical areas, including area V2 (36, 38, 39), area V3 (40), middle temporal area (area MT) (41–43), and inferotemporal cortex (44–46). Midlevel visual cortical area V4, a well-studied area contributing to attentional modulation, follows suit with columnar organization of visual responses and feature preferences (44, 47–53). Yet, we do not know the extent to which attention impacts feature preferences along columns. While canonical microcircuit models of cortex predict laminar differences for attentional modulation [e.g., feedback-recipient extragranular layers modulating before granular layers (54–56)], how this modulation interacts with columnar feature selectivity is largely unknown.We sought to determine the spatiotemporal profile of feature preferences within the V4 laminar microcircuit during attentional selection. To address this question, we performed neurophysiological recordings along V4 layers in monkeys performing an attention-demanding pop-out search task. We identified feature columns demonstrating homogeneous feature preference along cortical depth. When the search array item presented in the column’s receptive field (RF) was unattended, the upper cortical layers were most selective. However, when attended, feature selectivity in the deep layers enhanced the most, resulting in overall strongest feature selectivity in both extragranular compartments. We further found that the enhancement of feature selectivity associated with attention was rhythmically gated in the beta range. While beta activity was measurable across both unattended and attended conditions, rhythmic gating of feature selectivity was only present with attention. Moreover, beta power modulating the neural response was predictive of response time (RT), suggesting a link between attentional gating and behavior. Synaptic currents revealed the beta rhythm originates in superficial cortical layers, which is compatible with top-down influence.