Shyam Sudhakar

Krea University · School of Interwoven Arts and Sciences

Traumatic brain injuries (TBIs) are characterized by myriad comorbidities that affect the functioning of the affected individuals. The comorbidities that TBI subjects experience span a wide range, ranging from psychiatric diseases to those that affect the various systems of the body. This is compounded by the fact that the problems that TBI subject...

The human gut microbiota is known to contribute to numerous physiological functions of the body through their interplay with multiple organs and also implicated in a myriad of pathological conditions. Prolific research work in the past few decades have yielded valuable information regarding the relative taxonomic distribution of the gut microbiota...

Traumatic brain injury (TBI) is associated with an increased risk of long-lasting health-related complications. Survivors of brain trauma often experience comorbidities which could further dampen functional recovery and severely interfere with their day-to-day functioning after injury. Of the three TBI severity types, mild TBI constitutes a signifi...

Traumatic brain injuries (TBI) caused by physical impact to the brain can adversely impact the welfare and well-being of the affected individuals. One of the leading causes of mortality and dysfunction in the world, TBI is a major public health problem facing the human community. Drugs that target GABAergic neurotransmission are commonly used for s...

The granular retrosplenial cortex (RSG) is critical for both spatial and non-spatial behaviors, but the underlying neural codes remain poorly understood. Here, we use optogenetic circuit mapping in mice to reveal a double dissociation that allows parallel circuits in superficial RSG to process disparate inputs. The anterior thalamus and dorsal subi...

Inhibitory neurons are critical for normal brain function but dysregulated in disorders such as epilepsy. At least two theories exist for how inhibition may acutely decrease during a seizure: hyperpolarization of fast-spiking (FS) inhibitory neurons by other inhibitory neurons, or depolarization block (DB) of FS neurons resulting in an inability to...

The granular retrosplenial cortex (RSG) is critical for both spatial navigation and fear conditioning, but the neural codes enabling these seemingly disparate functions remain unknown. Here, using optogenetic circuit mapping, we reveal a double dissociation that allows parallel circuits in superficial RSG to process navigation- versus fear-related...

The retrosplenial cortex (RSC) is essential for memory and navigation, but the neural codes underlying these functions remain largely unknown. Here, we show that the most prominent cell type in layers 2/3 (L2/3) of the mouse granular RSC is a hyperexcitable, small pyramidal cell. These cells have a low rheobase (LR), high input resistance, lack of...

[This corrects the article DOI: 10.1371/journal.pcbi.1005754.].

Variability in the Location of High-Frequency Oscillations During Prolonged Intracranial EEG Recordings Gliske SV, Irwin ZT, Chestek C, et al. Nat Commun. 2018;9(1):2155. doi:10.1038/s41467-018-04549-2. PMID: 29858570. The rate of interictal high-frequency oscillations (HFOs) is a promising biomarker of the seizure onset zone, though little is know...

The retrosplenial cortex (RSC) is essential for both memory and navigation, but the neural codes underlying these functions remain largely unknown. Here, we show that the most prominent cell type in layers 2/3 (L2/3) of the granular RSC is a uniquely excitable, small pyramidal cell. These cells have a low rheobase (LR), high input resistance, lack...

Stereotyped high-frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy. Liu S, Gurses C, Sha Z, Quach MM, Sencer A, Bebek N, et al. Brain. 2018;141(3):713-730. doi:10.1093/brain/awx374. PMID: 29394328 . High-frequency oscillations in local field potentials recorded with intracranial electroencephal...

Traumatic brain injuries (TBI) lead to dramatic changes in the surviving brain tissue. Altered ion concentrations, coupled with changes in the expression of membrane-spanning proteins, create a post-TBI brain state that can lead to further neuronal loss due to secondary excitotoxicity. Several GABA receptor agonists have been tested in the search f...

Objective: Neural recording is important for a wide variety of clinical applications. Until recently, recording from the surface of the brain, even when using micro-electrocorticography (µECoG) arrays, was not thought to enable recording from individual neurons. Recent results suggest that when the surface electrode contact size is sufficiently sm...

The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constr...

Firing rate and cross-correlation along the sagittal axis. A-D: GoC firing rate (A), cross-correlation (B), GrC firing rate (C), cross-correlation (D) along the sagittal axis when the network was activated with a single patch of mossy fibers with slow rate coded input. Black lines represent background network firing rate for the respective patches....

Models of dynamic synapses on GrCs. A: Black lines are the AMPA and NMDA current induced by presynaptic spikes (blue) in the original model [79]. Red lines are the same currents in our model where the glutamate diffusion is approximated by a cascade linear process (Eq 2). B: An experimental data of GrC eIPSC copied from [13] (black), and eIPSC of o...

Video of network activity in response to 60 Hz patchy mossy fiber input activated in a single patch at the center of the network. The blue and green dots represent mossy fiber and GoC activity respectively. The red points represent granule cell activity. The stimulus onset is at 0 ms. One can see the patchy mossy fiber activation, GrC spiking activ...

Volumetric maps of network activity in response to slow rate coded input activated in two patches along the transverse axis. A: GrC population PSTH showing the timing of volumetric maps at various points during the network activity. B-G: Volumetric maps that portray the network activity at various time points. The stimulus onset is at 0 ms. One can...

Membrane potential traces of Golgi and granule neurons for various stimulation paradigms. A-D: Membrane potential traces of ON patch Golgi (blue) and granule neurons (red) when stimulated with 60 Hz Poisson input. E-H: Same as A-D for slow rate modulated input. I-L: Same as A-D for burst input. (TIFF)

Volumetric maps of network activity in response to single burst input activated in a single patch at the center of the network. A: GrC population PSTH showing the timing of volumetric maps at various points during the network activity. B-G: Volumetric maps that portray the network activity at various time points. The stimulus onset is at 0 ms. One...

Convergence, divergence, total number of synapses and synaptic parameters for various synapses in the network. (DOCX)

Firing rate and cross-correlation along the sagittal axis with bursting mossy fiber input. A-D: GoC firing rate (A), cross-correlation (B), GrC firing rate (C), cross-correlation (D) along the sagittal axis when the network was activated with a single patch of mossy fibers with bursting inputs. Black lines represent background network firing rate f...

Video of network activity in response to slow rate coded input activated in two patches along the transverse axis. The colors represent the same scheme as explained in S1 Movie. (MP4)

Video of network activity in response to burst input activated in a single patch at the center of the network. The colors represent the same scheme as explained in S1 Movie. (MP4)

Neurons of the cerebellar nuclei convey the final output of the cerebellum to their targets in various parts of the brain. Within the cerebellum their direct upstream connections originate from inhibitory Purkinje neurons. Purkinje neurons have a complex firing pattern of regular spikes interrupted by intermittent pauses of variable length. How can...

Generation of synthetic PN spikes. Synthetic PN spikes were generated using a three-step process: First we segregated the experimental ISIs into regular firing patterns (group of regular ISIs, blue) and pause ISIs (red) (step 1). For each regular firing pattern a corresponding synthetic regular firing pattern was generated based on gamma distributi...

CN neuron's firing rate increase mediated by pause ending synchronization and pause overlapping synchronization are not significantly different from each other. Analysis for 20 ms (A-D) and 40 ms (E-H) synchronous pauses. (A&E) Population spike timing histogram of all PNs projecting onto the CN neuron. (B&F) Increase in firing rate of CN neuron qua...

Comparison of distribution of experimental and synthetic PN ISIs. A-I: Distribution of experimental and synthetic PN ISIs for nine randomly selected PNs. The similarity between experimental and synthetic ISIs was determined by Kolmogorov-Smirnov test. None of the generated synthetic ISIs was significantly different from experimental ones (99% confi...

Effect of increasing PN pause synchronization on the rate increases of CN neuron for pause beginning type (A-D) and pause overlapping type (E-H) synchronization. (A&E) Population spike timing histogram of all Purkinje cells projecting onto CN neuron. Pause beginning type synchronization is illustrated in A and pause overlapping type is explained in...

Time-locking of CN neuron spikes quantified for pause ending and pause overlapping synchronization condition. (A&E) Population spike timing histogram of all PNs projecting onto the CN neuron. Note the presence of synchronous pause of length 20 ms (A) and 40 ms (E) for both types of synchronization. (B&F) Variability of latency calculated from 100 t...

Effect of pause length on the coding strategy of CN neuron. (A&E) Population spike timing histogram of all Purkinje cells projecting onto the nuclear neuron. Note the presence of synchronous pause beginning spikes and pause length of 20 ms (or 40 ms). Plots B,C and D represents quantification of variability in latency of CN neuron’s spiking for low...

Synaptic parameters used in the model and steady state release probability and time constants for synaptic depression. (DOCX)

There exist several declarative computer languages for describing computational neuroscience models. NeuroML[1] encompasses ion channels, cell morphology, and networks, NineML[2] is focused on hybrid spiking neurons, and SBML[3] has been successfully used to describe ion channel kinetics. However, despite the existence of these standards, only a ha...

Cerebellar granule cells (CGNs) are one of many neurons that express phasic and tonic GABAergic conductances. Although it is well established that Golgi cells (GoCs) mediate phasic GABAergic currents in CGNs, their role in mediating tonic currents in CGNs (CGN-I(tonic)) is controversial. Earlier studies suggested that GoCs mediate a component of CG...

We present a prototype framework for exploring hypotheses about the neuroanatomical structures and connectivity in the cerebellar cortex at various levels of granularity, based on experimental data and hypotheses from the scientific literature [1]. As illustrated in Figure Figure1,1, the framework consists of declarative and algorithmic components....