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Ramanathan, D.

Publications and source records attributed to Ramanathan, D..

8 recordsLinked to original sources

Cortical oscillations reflect opponent ensemble dynamics through coordinated multifrequency activity

Neural oscillations are widely used as proxies for neuronal activity, where power in individual frequency bands is commonly interpreted as functionally indexing neural circuit engagement. However, power in individual frequency bands shows heterogeneous and sometimes opposing relationships with neuronal activity across regions and behavioral contexts, challenging the assumption of a stable frequency-to-circuit mapping. Here we show that glutamatergic population activity in rat medial prefrontal cortex is not stably linked with power in isolated frequency bands, but rather with dynamically recurring multi-frequency amplitude co-fluctuations. These multi-frequency patterns, termed spectral motifs, occurred in opponent pairs with nearly identical frequency composition but inverted relationships to population calcium activity. This opponent motif structure, observed across cortical regions and species, provides a key component for understanding how oscillations are linked to neuronal activity. We found that shifts in motif opponency balance explained changes in glutamatergic activity that occur during brain-computer interface learning better than models based on frequency band power alone. Furthermore, opponent motifs map selectively onto opponent cell ensembles and enable bidirectional mapping between local field potentials and ensemble activity. These findings identify multi-frequency opponent motifs as a conserved organizational principle linking oscillatory dynamics to population-level circuit states and challenge the notion that individual frequency bands can serve as interpretable functional units mapping onto neural circuit activity.

neuroscience↗

Differential glutamatergic and GABAergic responses drive divergent prefrontal cortex neural outcomes to low and high frequency stimulation

BackgroundRepetitive brain stimulation is hypothesized to bidirectionally modulate excitability, with low-frequency trains decreasing and high-frequency (>5 Hz) trains increasing activity. Most insights on the neuroplastic effects of repetitive stimulation protocols stem from non-invasive human studies (TMS/EEG) or data from rodent slice physiology. Here, we developed a rodent experimental preparation enabling simultaneous imaging of cellular activity during stimulation in vivo to understand the mechanisms by which brain stimulation modulates excitability of prefrontal cortex. MethodsRepetitive trains of intracortical stimulation were applied to the medial prefrontal cortex using current parameters mapped to human rTMS electric-field estimates. Calcium imaging of glutamatergic (CamKII) and GABAergic (mDLX) neurons was performed before, during, and after stimulation in awake rodents (n=9 females). Protocols included low-frequency (1 Hz, 1000 pulses) and high-frequency (10 Hz, 3000 pulses), with sham stimulation as a control. ResultsGlutamatergic neurons were differentially modulated by stimulation frequency, with 10 Hz increasing and 1 Hz decreasing activity. Post-stimulation, 1 Hz suppressed both glutamatergic and GABAergic activity, whereas 10 Hz selectively suppressed GABAergic neurons. ConclusionsThese findings provide direct evidence that clinical brain stimulation protocols induce long-term modulation of cortical excitability, with low-frequency stimulation broadly suppressing activity and high-frequency stimulation preferentially inhibiting GABAergic neurons after stimulation.

neuroscience↗

Intermittent Theta Burst Stimulation Drives Bi-Directional Changes in Excitability in Prefrontal Cortex

Intermittent Theta Burst Stimulation (iTBS) is a patterned stimulation protocol FDA-cleared to treat depression, yet its outcomes are variable and mechanistically unclear. Here, using a combination of calcium imaging, histology, optogenetics and behavior, we show that one parameter of iTBS, the inter-train interval (ITI) between stimulation trains, plays a critical role in modulating GABAergic (and especially parvalbumin) neuronal activity, modulating subsequent neuronal plasticity and antidepressant effects. Shorter ITI stimulation protocols (4-10Ssinter-train intervals) activate GABA neurons, limiting resulting changes in cortical excitability and plasticity compared to extended interval TBS protocols (eTBS, with a 20s ITI). eTBS also drives the largest changes in synaptic / spine plasticity and leads to rapid and durable antidepressant-like effects after only a single stimulation session. Optogenetic activation of GABAergic neurons during eTBS blocks synaptic plasticity and rapid antidepressant effects. Together, these findings reveal a temporal control principle for TBS-induced cortical plasticity and provides a physiology-based strategy to improve TBS efficacy. HighlightsO_LIInter-train interval (ITI) controls excitatory-inhibitory balance during theta burst stimulation C_LIO_LIShort ITIs strongly activate PV interneurons limiting longer-term changes in glutamatergic excitatory plasticity C_LIO_LIExtended ITI (20s in particular) reduces inhibitory activity while maintaining sufficient activation of glutamatergic neurons to promote post-stimulation plasticity C_LIO_LIeTBS produces rapid and durable antidepressant-like effects that are blocked by GABAergic co-activation C_LI Graphical AbstractInter-train interval (ITI) determines the balance between excitation and inhibition during theta burst stimulation (TBS), an FDA-cleared treatment for depression. (A) Short ITIs (4s) drive concurrent glutamatergic and GABAergic activation, with inhibitory dominance during stimulation and suppressed long-term modulation of excitability. Extending the ITI to 20s (eTBS) reduces GABAergic recruitment during stimulation, promoting sustained long-term glutamatergic modulation resulting cortical disinhibition, leading to rapid and durable antidepressant-like effects (B). Optogenetic activation of GABAergic interneurons during eTBS abolishes synaptic and antidepressant effects, demonstrating that reduced inhibitory recruitment during eTBS is required for the rapid and durable behavioral effects observed with that protocol. O_FIG O_LINKSMALLFIG WIDTH=182 HEIGHT=200 SRC="FIGDIR/small/608693v3_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@15a7decorg.highwire.dtl.DTLVardef@1220forg.highwire.dtl.DTLVardef@63258forg.highwire.dtl.DTLVardef@13707e7_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Ventral pallidum GABA and glutamate neurons drive approach and avoidance through distinct modulation of VTA cell types

The ventral pallidum (VP) contains GABA and glutamate (Glut) neurons projecting to ventral tegmental area (VTA) whose stimulation drives approach and avoidance, respectively. Yet little is known about the cell-type-specific mechanisms by which VP projections to VTA drive behavior. Here, we found that both VP GABA and Glut neurons were activated during approach to reward or delivery of an aversive stimulus. Stimulation of VP GABA neurons inhibited VTA GABA, but activated dopamine (DA) and glutamate neurons. Remarkably, this cell-type-specific recruitment was behavior-contingent such that VTA recruitment was inhibited when evoked by the subjects own action. Conversely, VP Glut neurons activated VTA GABA, as well as DA and Glut neurons, despite driving aversion. However, VP Glut neurons evoked DA in reward-associated ventromedial nucleus accumbens (NAc), but reduced DA in aversion-associated dorsomedial NAc. These findings show how heterogeneous VP cell types can engage VTA cell types to shape approach and avoidance behaviors. HIGHLIGHTSO_LIVP GABA and Glut neurons are activated by approach to reward and aversive stimuli C_LIO_LIVP GABA and Glut neurons oppositely affect VTA GABA, both activate VTA DA and Glut C_LIO_LIVP Glut neurons activate DA release in ventral NAc but inhibit DA from dorsal NAc C_LIO_LIVTA DA responses to VP GABA activity are inhibited by the subjects own action C_LI

neuroscience↗

Disentangling reward processes underlying payoff maximization from individual differences in gain frequency bias and reinforcement learning

Choice selection strategies and decision making are typically investigated using multiple-choice gambling paradigms that require participants to maximize reward payoff. However, research shows that performance in such paradigms suffers from individual biases towards the frequency of gains to choose smaller local gains over larger longer term gain, also referred to as melioration. Here, we developed a simple two-choice reward task, implemented in 186 healthy human adult subjects across the adult lifespan to understand the behavioral, computational, and neural bases of payoff maximization versus melioration. The observed reward choice behavior on this task was best explained by a reinforcement learning model of differential future reward prediction. Simultaneously recorded and source-localized electroencephalography (EEG) showed that diminished theta-band activations in the right rostral anterior cingulate cortex (rACC) correspond to greater reward payoff maximization, specifically during the presentation of cumulative reward information at the end of each task trial. Notably, these activations (greater rACC theta) predicted depressed mood symptoms, thereby showcasing a reward processing marker of potential clinical utility. Significance StatementThis study presents cognitive, computational and neural (EEG-based) analyses of a rapid reward-based decision-making task. The research has the following three highlights. 1) It teases apart two core aspects of reward processing, i.e. long term expected value maximization versus immediate gain frequency melioration based choice behavior. 2) It models reinforcement learning based behavioral differences between individuals showing that observed performance is best explained by differential extents of reward prediction. 3) It investigates neural correlates in 186 healthy human subjects across the adult lifespan, revealing specific theta band cortical source activations in right rostral anterior cingulate as correlates for maximization that further predict depressed mood across subjects.

neuroscience↗

Mapping Cognitive Brain Functions at Scale

A fundamental set of cognitive abilities enable humans to efficiently process goal-relevant information, suppress irrelevant distractions, maintain information in working memory, and act flexibly in different behavioral contexts. Yet, studies of human cognition and their underlying neural mechanisms usually evaluate these cognitive constructs in silos, instead of comprehensively in-tandem within the same individual. Here, we developed a scalable, mobile platform, "BrainE" (short for Brain Engagement), to rapidly assay several essential aspects of cognition simultaneous with wireless electroencephalography (EEG) recordings. Using BrainE, we rapidly assessed five aspects of cognition including (1) selective attention, (2) response inhibition, (3) working memory, (4) flanker interference and (5) emotion interference processing, in 102 healthy young adults. We evaluated stimulus encoding in all tasks using the EEG neural recordings, and isolated the cortical sources of the spectrotemporal EEG dynamics. Additionally, we used BrainE in a two-visit study in 24 young adults to investigate the reliability of the neuro-cognitive data as well as its plasticity to transcranial magnetic stimulation (TMS). We found that stimulus encoding on multiple cognitive tasks could be rapidly assessed, identifying common as well as distinct task processes in both sensory and cognitive control brain regions. Event related synchronization (ERS) in the theta (3-7 Hz) and alpha (8-12 Hz) frequencies as well as event related desynchronization (ERD) in the beta frequencies (13-30 Hz) were distinctly observed in each task. The observed ERS/ERD effects were overall anticorrelated. The two-visit study confirmed high test-retest reliability for both cognitive and neural data, and neural responses showed specific TMS protocol driven modulation. We also show that the global cognitive neural responses are sensitive to mental health symptom self-reports. This first study with the BrainE platform showcases its utility in studying neuro-cognitive dynamics in a rapid and scalable fashion. HighlightsO_LIRapid and scalable EEG recordings reveal common and distinct cortical activations across five core cognitive tasks. C_LIO_LIData acquired across visits one-week-apart show high test-retest reliability for both cognitive and neural measurements. C_LIO_LIEvoked neural responses during emotion interference processing demonstrate specific short-term plasticity driven by type of neurostimulation. C_LIO_LICognitively evoked neural responses are sensitive to variations in mental health symptoms. C_LI

neuroscience↗

Autism-linked Cullin3 germline haploinsufficiency impacts cytoskeletal dynamics and cortical neurogenesis through RhoA signaling

E3-ubiquitin ligase Cullin3 (Cul3) is a high confidence risk gene for Autism Spectrum Disorder (ASD) and Developmental Delay (DD). To investigate how Cul3 mutations impact brain development, we generated haploinsufficient Cul3 mouse model using CRISPR/Cas9 genome engineering. Cul3 mutant mice exhibited social and cognitive deficits and hyperactive behavior. Brain MRI found decreased volume of cortical regions and changes in many other brain regions of Cul3 mutant mice starting from early postnatal development. Spatiotemporal transcriptomic and proteomic profiling of the brain implicated neurogenesis and cytoskeletal defects as key drivers of Cul3 functional impact. Specifically, dendritic growth, filamentous actin puncta, and spontaneous network activity were reduced in Cul3 mutant mice. Inhibition of small GTPase RhoA, a molecular substrate of Cul3 ligase, rescued dendrite length and network activity phenotypes. Our study identified neuronal cytoskeleton and Rho signaling as primary targets of Cul3 mutation during early brain development.

neuroscience↗

SimBSI: An open-source Simulink library for developingclosed-loop brain signal interfaces in animals and humans

ObjectiveA promising application of BCI technology is in the development of personalized therapies that can target neural circuits linked to mental or physical disabilities. Typical BCIs, however, offer limited value due to simplistic designs and poor understanding of the conditions being treated. Building BCIs on more solid grounds may require the characterization of the brain dynamics supporting cognition and behavior at multiple scales, from single-cell and local field potential (LFP) recordings in animals to non-invasive electroencephalography (EEG) in humans. Despite recent efforts, a unifying software framework to support closed-loop studies in both animals and humans, is still lacking. The objective of this paper is to develop such a neurotechnology software framework.\n\nApproachHere we develop the Simulink for Brain Signal Interfaces library (SimBSI). Simulink is a mature graphical programming environment within MATLAB that has gained traction for processing electrophysiological data. SimBSI adds to this ecosystem: 1) advanced human EEG source imaging, 2) cross-species multimodal data acquisition based on the Lab Streaming Layer library, and 3) a graphical experimental design platform.\n\nMain resultsWe used several examples to demonstrate the capabilities of the library, ranging from simple signal processing, to online EEG source imaging, cognitive task design, and closed-loop neuromodulation. We further demonstrate the simplicity of developing a sophisticated experimental environment for rodents within this environment.\n\nSignificanceWith the SimBSI library we hope to aid BCI practitioners of dissimilar backgrounds in the development of, much needed, single and cross-species closed-loop neuroscientific experiments. These experiments may provide the necessary mechanistic data for BCIs to become effective therapeutic tools.

bioengineering↗