Excitation creates a distributed pattern of cortical suppression due to varied recurrent input.

Dense local, recurrent connections are a major feature of cortical circuits, yet how they affect neurons' responses has been unclear, with some studies reporting weak recurrent effects, some reporting amplification, and others indicating local suppression. Here, we show that optogenetic input to mouse V1 excitatory neurons generates salt-and-pepper patterns of both excitation and suppression. Responses in individual neurons are not strongly predicted by that neuron's direct input. A balanced-state network model reconciles a set of diverse observations: the observed dynamics, suppressed responses, decoupling of input and output, and long tail of excited responses. The model shows recurrent excitatory-excitatory connections are strong and also variable across neurons. Together, these results demonstrate that excitatory recurrent connections can have major effects on cortical computations by shaping and changing neurons' responses to input.

Amplified cortical neural responses as animals learn to use novel activity patterns.

Cerebral cortex supports representations of the world in patterns of neural activity, used by the brain to make decisions and guide behavior. Past work has found diverse, or limited, changes in the primary sensory cortex in response to learning, suggesting that the key computations might occur in downstream regions. Alternatively, sensory cortical changes may be central to learning. We studied cortical learning by using controlled inputs we insert: we trained mice to recognize entirely novel, non-sensory patterns of cortical activity in the primary visual cortex (V1) created by optogenetic stimulation. As animals learned to use these novel patterns, we found that their detection abilities improved by an order of magnitude or more. The behavioral change was accompanied by large increases in V1 neural responses to fixed optogenetic input. Neural response amplification to novel optogenetic inputs had little effect on existing visual sensory responses. A recurrent cortical model shows that this amplification can be achieved by a small mean shift in recurrent network synaptic strength. Amplification would seem to be desirable to improve decision-making in a detection task; therefore, these results suggest that adult recurrent cortical plasticity plays a significant role in improving behavioral performance during learning.

Topographic organization of the human caudate functional connectivity and age-related changes with resting-state fMRI.

The striatum is postulated to play a central role in gating cortical processing during goal-oriented behavior. While many human neuroimaging studies have treated the striatum as an undivided whole or several homogeneous compartments, some recent studies showed that its circuitry is topographically organized and has more complex relations with the cortical networks than previously assumed. Here, we took a gradient functional connectivity mapping approach that utilizes the entire anatomical space of the caudate nucleus to examine the organization of its functional relationship with the rest of the brain and how its topographic mapping changes with age. We defined the topography of the caudate functional connectivity using three publicly available resting-state fMRI datasets. We replicated and extended previous findings. First, we found two stable gradients of caudate connectivity patterns along its medial-lateral (M-L) and anterior-posterior (A-P) axes, supporting findings from previous tract-tracing studies of non-human primates that there are at least two main organizational principles within the caudate nucleus. Second, unlike previous emphasis of the A-P topology, we showed that the differential connectivity patterns along the M-L gradient of caudate are more clearly organized with the large-scale neural networks; such that brain networks associated with internal vs. external orienting behavior are respectively more closely linked to the medial vs. lateral extent of the caudate. Third, the caudate's M-L organization showed greater age-related reduction in integrity, which was further associated with age-related changes in behavioral measures of executive functions. In sum, our analysis confirmed a sometimes overlooked M-L functional connectivity gradient within the caudate nucleus, with its lateral longitudinal zone more closely linked to the frontoparietal cortical circuits and age-related changes in cognitive control. These findings provide a more precise mapping of the human caudate functional connectivity, both in terms of the gradient organization with cortical networks and age-related changes in such organization.

Functional neural network configuration in late childhood varies by age and cognitive state.

Late childhood and early adolescence is characterized by substantial brain maturation which contributes to both adult-like and age-dependent resting-state network connectivity patterns. However, it remains unclear whether these functional network characteristics in children are subject to differential modulation by distinct cognitive demands as previously found in adults. We conducted network analyses on fMRI data from 60 children (aged 9-12) during resting and during three distinct tasks involving decision making, visual perception, and spatial working memory. Graph measures of network architecture, functional integration, and flexibility were calculated for each of the four states. During resting state, the children's network architecture was similar to that in young adults (N = 60, aged 20-23) but the degree of similarity was age- and network-dependent. During the task states, the children's whole-brain network exhibited enhanced integration in response to increased cognitive demand. Additionally, the frontoparietal network showed flexibility in connectivity patterns across states while networks implicated in motor and visual processing remained relatively stable. Exploratory analyses suggest different relationships between behavioral performance and connectivity profiles for the working memory and perceptual tasks. Together, our findings demonstrate state- and age-dependent features in functional network connectivity during late childhood, potentially providing markers for brain and cognitive development.

Topographic Mapping as a Basic Principle of Functional Organization for Visual and Prefrontal Functional Connectivity.

The organization of region-to-region functional connectivity has major implications for understanding information transfer and transformation between brain regions. We extended connective field mapping methodology to 3-D anatomic space to derive estimates of corticocortical functional organization. Using multiple publicly available human (both male and female) resting-state fMRI data samples for model testing and replication analysis, we have three main findings. First, we found that the functional connectivity between early visual regions maintained a topographic relationship along the anterior-posterior dimension, which corroborates previous research. Higher order visual regions showed a pattern of connectivity that supports convergence and biased sampling, which has implications for their receptive field properties. Second, we demonstrated that topographic organization is a fundamental aspect of functional connectivity across the entire cortex, with higher topographic connectivity between regions within a functional network than across networks. The principle gradient of topographic connectivity across the cortex resembled whole-brain gradients found in previous work. Last but not least, we showed that the organization of higher order regions such as the lateral prefrontal cortex demonstrate functional gradients of topographic connectivity and convergence. These organizational features of the lateral prefrontal cortex predict task-based activation patterns, particularly visual specialization and higher order rules. In sum, these findings suggest that topographic input is a fundamental motif of functional connectivity between cortical regions for information processing and transfer, with maintenance of topography potentially important for preserving the integrity of information from one region to another.

Posterior parietal influences on visual network specialization during development: An fMRI study of functional connectivity in children ages 9 to 12.

Visual processing in the primate brain is highly organized along the ventral visual pathway, although it is still unclear how categorical selectivity emerges in this system. While many theories have attempted to explain the pattern of visual specialization within the ventral occipital and temporal areas, the biased connectivity hypothesis provides a framework which postulates extrinsic connectivity as a potential mechanism in shaping the development of category selectivity. As the posterior parietal cortex plays a central role in visual attention, we examined whether the pattern of parietal connectivity with the face and scene processing regions is closely linked with the functional properties of these two visually selective networks in a cohort of 60 children ages 9 to 12. Functionally localized face and scene selective regions were used in deriving each visual network's resting-state functional connectivity. The children's face and scene processing networks appeared to show a weak network segregation during resting state, which was confirmed when compared to that of a group of gender and handedness matched adults. Parietal regions of these children showed differential connectivity with the face and scene networks, and the extent of this differential parietal-visual connectivity predicted individual differences in the degree of segregation between the two visual networks, which in turn predicted individual differences in visual perception performance. Finally, the pattern of parietal connectivity with the face processing network also predicted the foci of face-related activation in the right fusiform gyrus across children. These findings provide evidence that extrinsic connectivity with regions such as the posterior parietal cortex may have important implications in the development of specialized visual processing networks.

Model testing for distinctive functional connectivity gradients with resting-state fMRI data.

In accordance with the concept of topographic organization of neuroanatomical structures, there is an increased interest in estimating and delineating continuous changes in the functional connectivity patterns across neighboring voxels within a region of interest using resting-state fMRI data. Fundamental to this functional connectivity gradient analysis is the assumption that the functional organization is stable and uniform across the region of interest. To evaluate this assumption, we developed a statistical model testing procedure to arbitrate between overlapping, shifted, or different topographic connectivity gradients across subdivisions of a structure. We tested the procedure using the striatum, a subcortical structure consisting of the caudate nucleus and putamen, in which an extensive literature, primarily from rodents and non-human primates, suggest to have a shared topographic organization of a single diagonal gradient. We found, across multiple resting state fMRI data samples of different spatial resolutions in humans, and one macaque resting state fMRI data sample, that the models with different functional connectivity gradients across the caudate and putamen was the preferred model. The model selection procedure was validated in control conditions of checkerboard subdivisions, demonstrating the expected overlapping gradient. More specifically, while we replicated the diagonal organization of the functional connectivity gradients in both the caudate and putamen, our analysis also revealed a medial-lateral organization within the caudate. Not surprisingly, performing the same analysis assuming a unitary gradient obfuscates the medial-lateral organization of the caudate, producing only a diagonal gradient. These findings demonstrate the importance of testing basic assumptions and evaluating interpretations across species. The significance of differential topographic gradients across the putamen and caudate and the medial-lateral gradient of the caudate in humans should be tested in future studies.

Preschool negative emotionality predicts activity and connectivity of the fusiform face area and amygdala in later childhood.

Negative emotionality (NE) refers to individual differences in the propensity to experience and react with negative emotions and is associated with increased risk of psychological disorder. However, research on the neural bases of NE has focused almost exclusively on amygdala activity during emotional face processing. This study broadened this framework by examining the relationship between observed NE in early childhood and subsequent neural responses to emotional faces in both the amygdala and the fusiform face area (FFA) in a late childhood/early adolescent sample. Measures of NE were obtained from children at age 3 using laboratory observations, and functional magnetic resonance imaging (fMRI) data were collected when these children were between the ages of 9 and 12 while performing a visual stimulus identity matching task with houses and emotional faces as stimuli. Multiple regression analyses revealed that higher NE at age 3 is associated with significantly greater activation in the left amygdala and left FFA but lower functional connectivity between these two regions during the face conditions. These findings suggest that those with higher early NE have subsequent alterations in both activity and connectivity within an extended network during face processing.