Browsing by Subject "Nerve Net"
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Item Open Access A framework for integrating the songbird brain.(J Comp Physiol A Neuroethol Sens Neural Behav Physiol, 2002-12) Jarvis, ED; Smith, VA; Wada, K; Rivas, MV; McElroy, M; Smulders, TV; Carninci, P; Hayashizaki, Y; Dietrich, F; Wu, X; McConnell, P; Yu, J; Wang, PP; Hartemink, AJ; Lin, SBiological systems by default involve complex components with complex relationships. To decipher how biological systems work, we assume that one needs to integrate information over multiple levels of complexity. The songbird vocal communication system is ideal for such integration due to many years of ethological investigation and a discreet dedicated brain network. Here we announce the beginnings of a songbird brain integrative project that involves high-throughput, molecular, anatomical, electrophysiological and behavioral levels of analysis. We first formed a rationale for inclusion of specific biological levels of analysis, then developed high-throughput molecular technologies on songbird brains, developed technologies for combined analysis of electrophysiological activity and gene regulation in awake behaving animals, and developed bioinformatic tools that predict causal interactions within and between biological levels of organization. This integrative brain project is fitting for the interdisciplinary approaches taken in the current songbird issue of the Journal of Comparative Physiology A and is expected to be conducive to deciphering how brains generate and perceive complex behaviors.Item Open Access A Functionally Conserved Gene Regulatory Network Module Governing Olfactory Neuron Diversity.(PLoS Genet, 2016-01) Li, Qingyun; Barish, Scott; Okuwa, Sumie; Maciejewski, Abigail; Brandt, Alicia T; Reinhold, Dominik; Jones, Corbin D; Volkan, Pelin CayirliogluSensory neuron diversity is required for organisms to decipher complex environmental cues. In Drosophila, the olfactory environment is detected by 50 different olfactory receptor neuron (ORN) classes that are clustered in combinations within distinct sensilla subtypes. Each sensilla subtype houses stereotypically clustered 1-4 ORN identities that arise through asymmetric divisions from a single multipotent sensory organ precursor (SOP). How each class of SOPs acquires a unique differentiation potential that accounts for ORN diversity is unknown. Previously, we reported a critical component of SOP diversification program, Rotund (Rn), increases ORN diversity by generating novel developmental trajectories from existing precursors within each independent sensilla type lineages. Here, we show that Rn, along with BarH1/H2 (Bar), Bric-à-brac (Bab), Apterous (Ap) and Dachshund (Dac), constitutes a transcription factor (TF) network that patterns the developing olfactory tissue. This network was previously shown to pattern the segmentation of the leg, which suggests that this network is functionally conserved. In antennal imaginal discs, precursors with diverse ORN differentiation potentials are selected from concentric rings defined by unique combinations of these TFs along the proximodistal axis of the developing antennal disc. The combinatorial code that demarcates each precursor field is set up by cross-regulatory interactions among different factors within the network. Modifications of this network lead to predictable changes in the diversity of sensilla subtypes and ORN pools. In light of our data, we propose a molecular map that defines each unique SOP fate. Our results highlight the importance of the early prepatterning gene regulatory network as a modulator of SOP and terminally differentiated ORN diversity. Finally, our model illustrates how conserved developmental strategies are used to generate neuronal diversity.Item Open Access A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.(PLoS Comput Biol, 2015-08) Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, RiccardoUnderstanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns.Item Open Access Altered resting-state functional connectivity of basolateral and centromedial amygdala complexes in posttraumatic stress disorder.(Neuropsychopharmacology, 2014-01) Brown, Vanessa M; LaBar, Kevin S; Haswell, Courtney C; Gold, Andrea L; Mid-Atlantic MIRECC Workgroup; McCarthy, Gregory; Morey, Rajendra AThe amygdala is a major structure that orchestrates defensive reactions to environmental threats and is implicated in hypervigilance and symptoms of heightened arousal in posttraumatic stress disorder (PTSD). The basolateral and centromedial amygdala (CMA) complexes are functionally heterogeneous, with distinct roles in learning and expressing fear behaviors. PTSD differences in amygdala-complex function and functional connectivity with cortical and subcortical structures remain unclear. Recent military veterans with PTSD (n=20) and matched trauma-exposed controls (n=22) underwent a resting-state fMRI scan to measure task-free synchronous blood-oxygen level dependent activity. Whole-brain voxel-wise functional connectivity of basolateral and CMA seeds was compared between groups. The PTSD group had stronger functional connectivity of the basolateral amygdala (BLA) complex with the pregenual anterior cingulate cortex (ACC), dorsomedial prefrontal cortex, and dorsal ACC than the trauma-exposed control group (p<0.05; corrected). The trauma-exposed control group had stronger functional connectivity of the BLA complex with the left inferior frontal gyrus than the PTSD group (p<0.05; corrected). The CMA complex lacked connectivity differences between groups. We found PTSD modulates BLA complex connectivity with prefrontal cortical targets implicated in cognitive control of emotional information, which are central to explanations of core PTSD symptoms. PTSD differences in resting-state connectivity of BLA complex could be biasing processes in target regions that support behaviors central to prevailing laboratory models of PTSD such as associative fear learning. Further research is needed to investigate how differences in functional connectivity of amygdala complexes affect target regions that govern behavior, cognition, and affect in PTSD.Item Open Access Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons.(Scientific reports, 2017-09-20) Tartaglia, Elisa M; Brunel, NicolasElectrophysiological recordings in cortex in vivo have revealed a rich variety of dynamical regimes ranging from irregular asynchronous states to a diversity of synchronized states, depending on species, anesthesia, and external stimulation. The average population firing rate in these states is typically low. We study analytically and numerically a network of sparsely connected excitatory and inhibitory integrate-and-fire neurons in the inhibition-dominated, low firing rate regime. For sufficiently high values of the external input, the network exhibits an asynchronous low firing frequency state (L). Depending on synaptic time constants, we show that two scenarios may occur when external inputs are decreased: (1) the L state can destabilize through a Hopf bifucation as the external input is decreased, leading to synchronized oscillations spanning d δ to β frequencies; (2) the network can reach a bistable region, between the low firing frequency network state (L) and a quiescent one (Q). Adding an adaptation current to excitatory neurons leads to spontaneous alternations between L and Q states, similar to experimental observations on UP and DOWN states alternations.Item Open Access Brain connectivity and visual attention.(Brain connectivity, 2013-01) Parks, Emily L; Madden, David JEmerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures.Item Open Access Changes in Brain Resting-state Functional Connectivity Associated with Peripheral Nerve Block: A Pilot Study.(Anesthesiology, 2016-08) Melton, M Stephen; Browndyke, Jeffrey N; Harshbarger, Todd B; Madden, David J; Nielsen, Karen C; Klein, Stephen MBACKGROUND: Limited information exists on the effects of temporary functional deafferentation (TFD) on brain activity after peripheral nerve block (PNB) in healthy humans. Increasingly, resting-state functional connectivity (RSFC) is being used to study brain activity and organization. The purpose of this study was to test the hypothesis that TFD through PNB will influence changes in RSFC plasticity in central sensorimotor functional brain networks in healthy human participants. METHODS: The authors achieved TFD using a supraclavicular PNB model with 10 healthy human participants undergoing functional connectivity magnetic resonance imaging before PNB, during active PNB, and during PNB recovery. RSFC differences among study conditions were determined by multiple-comparison-corrected (false discovery rate-corrected P value less than 0.05) random-effects, between-condition, and seed-to-voxel analyses using the left and right manual motor regions. RESULTS: The results of this pilot study demonstrated disruption of interhemispheric left-to-right manual motor region RSFC (e.g., mean Fisher-transformed z [effect size] at pre-PNB 1.05 vs. 0.55 during PNB) but preservation of intrahemispheric RSFC of these regions during PNB. Additionally, there was increased RSFC between the left motor region of interest (PNB-affected area) and bilateral higher order visual cortex regions after clinical PNB resolution (e.g., Fisher z between left motor region of interest and right and left lingual gyrus regions during PNB, -0.1 and -0.6 vs. 0.22 and 0.18 after PNB resolution, respectively). CONCLUSIONS: This pilot study provides evidence that PNB has features consistent with other models of deafferentation, making it a potentially useful approach to investigate brain plasticity. The findings provide insight into RSFC of sensorimotor functional brain networks during PNB and PNB recovery and support modulation of the sensory-motor integration feedback loop as a mechanism for explaining the behavioral correlates of peripherally induced TFD through PNB.Item Open Access Characteristics of sequential activity in networks with temporally asymmetric Hebbian learning.(Proceedings of the National Academy of Sciences of the United States of America, 2020-11-11) Gillett, Maxwell; Pereira, Ulises; Brunel, NicolasSequential activity has been observed in multiple neuronal circuits across species, neural structures, and behaviors. It has been hypothesized that sequences could arise from learning processes. However, it is still unclear whether biologically plausible synaptic plasticity rules can organize neuronal activity to form sequences whose statistics match experimental observations. Here, we investigate temporally asymmetric Hebbian rules in sparsely connected recurrent rate networks and develop a theory of the transient sequential activity observed after learning. These rules transform a sequence of random input patterns into synaptic weight updates. After learning, recalled sequential activity is reflected in the transient correlation of network activity with each of the stored input patterns. Using mean-field theory, we derive a low-dimensional description of the network dynamics and compute the storage capacity of these networks. Multiple temporal characteristics of the recalled sequential activity are consistent with experimental observations. We find that the degree of sparseness of the recalled sequences can be controlled by nonlinearities in the learning rule. Furthermore, sequences maintain robust decoding, but display highly labile dynamics, when synaptic connectivity is continuously modified due to noise or storage of other patterns, similar to recent observations in hippocampus and parietal cortex. Finally, we demonstrate that our results also hold in recurrent networks of spiking neurons with separate excitatory and inhibitory populations.Item Open Access Coherence potentials: loss-less, all-or-none network events in the cortex.(PLoS Biol, 2010-01-12) Thiagarajan, Tara C; Lebedev, Mikhail A; Nicolelis, Miguel A; Plenz, DietmarTransient associations among neurons are thought to underlie memory and behavior. However, little is known about how such associations occur or how they can be identified. Here we recorded ongoing local field potential (LFP) activity at multiple sites within the cortex of awake monkeys and organotypic cultures of cortex. We show that when the composite activity of a local neuronal group exceeds a threshold, its activity pattern, as reflected in the LFP, occurs without distortion at other cortex sites via fast synaptic transmission. These large-amplitude LFPs, which we call coherence potentials, extend up to hundreds of milliseconds and mark periods of loss-less spread of temporal and amplitude information much like action potentials at the single-cell level. However, coherence potentials have an additional degree of freedom in the diversity of their waveforms, which provides a high-dimensional parameter for encoding information and allows identification of particular associations. Such nonlinear behavior is analogous to the spread of ideas and behaviors in social networks.Item Open Access Complementary topology of maintenance and manipulation brain networks in working memory.(Scientific reports, 2018-12-13) Davis, SW; Crowell, CA; Beynel, L; Deng, L; Lakhlani, D; Hilbig, SA; Lim, W; Nguyen, D; Peterchev, AV; Luber, BM; Lisanby, SH; Appelbaum, LG; Cabeza, RWorking memory (WM) is assumed to consist of a process that sustains memory representations in an active state (maintenance) and a process that operates on these activated representations (manipulation). We examined evidence for two distinct, concurrent cognitive functions supporting maintenance and manipulation abilities by testing brain activity as participants performed a WM alphabetization task. Maintenance was investigated by varying the number of letters held in WM and manipulation by varying the number of moves required to sort the list alphabetically. We found that both maintenance and manipulation demand had significant effects on behavior that were associated with different cortical regions: maintenance was associated with bilateral prefrontal and left parietal cortex, and manipulation with right parietal activity, a link that is consistent with the role of parietal cortex in symbolic computations. Both structural and functional architecture of these systems suggested that these cognitive functions are supported by two dissociable brain networks. Critically, maintenance and manipulation functional networks became increasingly segregated with increasing demand, an effect that was positively associated with individual WM ability. These results provide evidence that network segregation may act as a protective mechanism to enable successful performance under increasing WM demand.Item Open Access Computational inference of neural information flow networks.(PLoS Comput Biol, 2006-11-24) Smith, V Anne; Yu, Jing; Smulders, Tom V; Hartemink, Alexander J; Jarvis, Erich DDetermining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks.Item Open Access Corollary discharge circuits in the primate brain.(Curr Opin Neurobiol, 2008-12) Crapse, Trinity B; Sommer, Marc AMovements are necessary to engage the world, but every movement results in sensorimotor ambiguity. Self-movements cause changes to sensory inflow as well as changes in the positions of objects relative to motor effectors (eyes and limbs). Hence the brain needs to monitor self-movements, and one way this is accomplished is by routing copies of movement commands to appropriate structures. These signals, known as corollary discharge (CD), enable compensation for sensory consequences of movement and preemptive updating of spatial representations. Such operations occur with a speed and accuracy that implies a reliance on prediction. Here we review recent CD studies and find that they arrive at a shared conclusion: CD contributes to prediction for the sake of sensorimotor harmony.Item Open Access Distinct and atypical intrinsic and extrinsic cell death pathways between photoreceptor cell types upon specific ablation of Ranbp2 in cone photoreceptors.(PLoS Genet, 2013-06) Cho, Kyoung-In; Haque, Mdemdadul; Wang, Jessica; Yu, Minzhong; Hao, Ying; Qiu, Sunny; Pillai, Indulekha CL; Peachey, Neal S; Ferreira, Paulo ANon-autonomous cell-death is a cardinal feature of the disintegration of neural networks in neurodegenerative diseases, but the molecular bases of this process are poorly understood. The neural retina comprises a mosaic of rod and cone photoreceptors. Cone and rod photoreceptors degenerate upon rod-specific expression of heterogeneous mutations in functionally distinct genes, whereas cone-specific mutations are thought to cause only cone demise. Here we show that conditional ablation in cone photoreceptors of Ran-binding protein-2 (Ranbp2), a cell context-dependent pleiotropic protein linked to neuroprotection, familial necrotic encephalopathies, acute transverse myelitis and tumor-suppression, promotes early electrophysiological deficits, subcellular erosive destruction and non-apoptotic death of cones, whereas rod photoreceptors undergo cone-dependent non-autonomous apoptosis. Cone-specific Ranbp2 ablation causes the temporal activation of a cone-intrinsic molecular cascade highlighted by the early activation of metalloproteinase 11/stromelysin-3 and up-regulation of Crx and CoREST, followed by the down-modulation of cone-specific phototransduction genes, transient up-regulation of regulatory/survival genes and activation of caspase-7 without apoptosis. Conversely, PARP1+ -apoptotic rods develop upon sequential activation of caspase-9 and caspase-3 and loss of membrane permeability. Rod photoreceptor demise ceases upon cone degeneration. These findings reveal novel roles of Ranbp2 in the modulation of intrinsic and extrinsic cell death mechanisms and pathways. They also unveil a novel spatiotemporal paradigm of progression of neurodegeneration upon cell-specific genetic damage whereby a cone to rod non-autonomous death pathway with intrinsically distinct cell-type death manifestations is triggered by cell-specific loss of Ranbp2. Finally, this study casts new light onto cell-death mechanisms that may be shared by human dystrophies with distinct retinal spatial signatures as well as with other etiologically distinct neurodegenerative disorders.Item Open Access Distress tolerance to auditory feedback and functional connectivity with the auditory cortex.(Psychiatry research. Neuroimaging, 2018-12) Addicott, Merideth A; Daughters, Stacey B; Strauman, Timothy J; Appelbaum, L GregoryDistress tolerance is the capacity to withstand negative affective states in pursuit of a goal. Low distress tolerance may bias an individual to avoid or escape experiences that induce affective distress, but the neural mechanisms underlying the bottom-up generation of distress and its relationship to behavioral avoidance are poorly understood. During a neuroimaging scan, healthy participants completed a mental arithmetic task with easy and distress phases, which differed in cognitive demands and positive versus negative auditory feedback. Then, participants were given the opportunity to continue playing the distress phase for a financial bonus and were allowed to quit at any time. The persistence duration was the measure of distress tolerance. The easy and distress phases activated auditory cortices and fronto-parietal regions. A task-based functional connectivity analysis using the left secondary auditory cortex (i.e., planum temporale) as the seed region revealed stronger connectivity to fronto-parietal regions and anterior insula during the distress phase. The distress-related connectivity between the seed region and the left anterior insula was negatively correlated with distress tolerance. The results provide initial evidence of the role of the anterior insula as a mediating link between the bottom-up generation of affective distress and top-down behavioral avoidance of distress.Item Open Access Emotion-attention network interactions during a visual oddball task.(Brain Res Cogn Brain Res, 2004-06) Fichtenholtz, Harlan M; Dean, Heather L; Dillon, Daniel G; Yamasaki, Hiroshi; McCarthy, Gregory; LaBar, Kevin SEmotional and attentional functions are known to be distributed along ventral and dorsal networks in the brain, respectively. However, the interactions between these systems remain to be specified. The present study used event-related functional magnetic resonance imaging (fMRI) to investigate how attentional focus can modulate the neural activity elicited by scenes that vary in emotional content. In a visual oddball task, aversive and neutral scenes were presented intermittently among circles and squares. The squares were frequent standard events, whereas the other novel stimulus categories occurred rarely. One experimental group [N=10] was instructed to count the circles, whereas another group [N=12] counted the emotional scenes. A main effect of emotion was found in the amygdala (AMG) and ventral frontotemporal cortices. In these regions, activation was significantly greater for emotional than neutral stimuli but was invariant to attentional focus. A main effect of attentional focus was found in dorsal frontoparietal cortices, whose activity signaled task-relevant target events irrespective of emotional content. The only brain region that was sensitive to both emotion and attentional focus was the anterior cingulate gyrus (ACG). When circles were task-relevant, the ACG responded equally to circle targets and distracting emotional scenes. The ACG response to emotional scenes increased when they were task-relevant, and the response to circles concomitantly decreased. These findings support and extend prominent network theories of emotion-attention interactions that highlight the integrative role played by the anterior cingulate.Item Open Access Functional parcellation of attentional control regions of the brain.(J Cogn Neurosci, 2004-01) Woldorff, Marty G; Hazlett, Chad J; Fichtenholtz, Harlan M; Weissman, Daniel H; Dale, Anders M; Song, Allen WRecently, a number of investigators have examined the neural loci of psychological processes enabling the control of visual spatial attention using cued-attention paradigms in combination with event-related functional magnetic resonance imaging. Findings from these studies have provided strong evidence for the involvement of a fronto-parietal network in attentional control. In the present study, we build upon this previous work to further investigate these attentional control systems. In particular, we employed additional controls for nonattentional sensory and interpretative aspects of cue processing to determine whether distinct regions in the fronto-parietal network are involved in different aspects of cue processing, such as cue-symbol interpretation and attentional orienting. In addition, we used shorter cue-target intervals that were closer to those used in the behavioral and event-related potential cueing literatures. Twenty participants performed a cued spatial attention task while brain activity was recorded with functional magnetic resonance imaging. We found functional specialization for different aspects of cue processing in the lateral and medial subregions of the frontal and parietal cortex. In particular, the medial subregions were more specific to the orienting of visual spatial attention, while the lateral subregions were associated with more general aspects of cue processing, such as cue-symbol interpretation. Additional cue-related effects included differential activations in midline frontal regions and pretarget enhancements in the thalamus and early visual cortical areas.Item Open Access General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks.(NeuroImage, 2019-04) Elliott, Maxwell L; Knodt, Annchen R; Cooke, Megan; Kim, M Justin; Melzer, Tracy R; Keenan, Ross; Ireland, David; Ramrakha, Sandhya; Poulton, Richie; Caspi, Avshalom; Moffitt, Terrie E; Hariri, Ahmad RIntrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.Item Open Access Inhibition stabilization is a widespread property of cortical networks.(eLife, 2020-06-29) Sanzeni, Alessandro; Akitake, Bradley; Goldbach, Hannah C; Leedy, Caitlin E; Brunel, Nicolas; Histed, Mark HMany cortical network models use recurrent coupling strong enough to require inhibition for stabilization. Yet it has been experimentally unclear whether inhibition-stabilized network (ISN) models describe cortical function well across areas and states. Here, we test several ISN predictions, including the counterintuitive (paradoxical) suppression of inhibitory firing in response to optogenetic inhibitory stimulation. We find clear evidence for ISN operation in mouse visual, somatosensory, and motor cortex. Simple two-population ISN models describe the data well and let us quantify coupling strength. Although some models predict a non-ISN to ISN transition with increasingly strong sensory stimuli, we find ISN effects without sensory stimulation and even during light anesthesia. Additionally, average paradoxical effects result only with transgenic, not viral, opsin expression in parvalbumin (PV)-positive neurons; theory and expression data show this is consistent with ISN operation. Taken together, these results show strong coupling and inhibition stabilization are common features of the cortex.Item Open Access Low- and High-Frequency Repetitive Transcranial Magnetic Stimulation Effects on Resting-State Functional Connectivity Between the Postcentral Gyrus and the Insula.(Brain connectivity, 2019-05) Addicott, Merideth A; Luber, Bruce; Nguyen, Duy; Palmer, Hannah; Lisanby, Sarah H; Appelbaum, Lawrence GregoryThe insular cortex supports the conscious awareness of physical and emotional sensations, and the ability to modulate the insula could have important clinical applications in psychiatry. Repetitive transcranial magnetic stimulation (rTMS) uses transient magnetic fields to induce electrical currents in the superficial cortex. Given its deep location in the brain, the insula may not be directly stimulated by rTMS; however, rTMS may modulate the insula via its functional connections with superficial cortical regions. Furthermore, low- versus high-frequency rTMS is thought to have opposing effects on cortical excitability, and the present study investigated these effects on brain activity and functional connectivity with the insula. Separate groups of healthy participants (n = 14 per group) received low (1 Hz)- or high (10 Hz)-frequency rTMS in five daily sessions to the right postcentral gyrus, a superficial region known to be functionally connected to the insula. Resting-state functional connectivity (RSFC) was measured pre- and post-rTMS. Both 1 and 10 Hz rTMS increased RSFC between the right postcentral gyrus and the left insula. These results suggest that low- and high-frequency rTMS has similar long-term effects on brain activity and RSFC. However, given the lack of difference, we cannot exclude the possibility that these effects are simply due to a nonspecific effect. Given this limitation, these unexpected results underscore the need for acoustic- and stimulation-matched sham control conditions in rTMS research.Item Open Access Measuring robustness of brain networks in autism spectrum disorder with Ricci curvature.(Scientific reports, 2020-07-02) Simhal, Anish K; Carpenter, Kimberly LH; Nadeem, Saad; Kurtzberg, Joanne; Song, Allen; Tannenbaum, Allen; Sapiro, Guillermo; Dawson, GeraldineOllivier-Ricci curvature is a method for measuring the robustness of connections in a network. In this work, we use curvature to measure changes in robustness of brain networks in children with autism spectrum disorder (ASD). In an open label clinical trials, participants with ASD were administered a single infusion of autologous umbilical cord blood and, as part of their clinical outcome measures, were imaged with diffusion MRI before and after the infusion. By using Ricci curvature to measure changes in robustness, we quantified both local and global changes in the brain networks and their potential relationship with the infusion. Our results find changes in the curvature of the connections between regions associated with ASD that were not detected via traditional brain network analysis.