scholarly journals Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations

2016 ◽  
Author(s):  
Jovana J. Belić ◽  
Arvind Kumar ◽  
Jeanette Hellgren Kotaleski
Keyword(s):  
Large Scale ◽  
Medium Spiny Neuron ◽  
Network Activity ◽  
Exact Nature ◽  
Striatal Neurons ◽  
Cortical Oscillations ◽  
Large Scale Network ◽  
Scale Network ◽  
Fast Spiking ◽  
External Stimuli

AbstractThe network oscillations are ubiquitous across many brain regions. In the basal ganglia, oscillations are also present at many levels and a wide range of characteristic frequencies have been reported to occur during both health and disease.The striatum is the input nucleus of the basal ganglia that receives massive glutamatergic inputs from the cortex and is highly susceptible to cortical oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, periodic external stimuli propagate through the striatal circuitry. Using a large-scale network model of the striatum and corticostriatal projections, here we try to elucidate the importance of specific GABAergic neurons and their interactions in shaping striatal oscillatory activity. Our results show that fast-spiking interneurons, despite their uncorrelated firing, might have a crucial role in the emergence of high-frequency oscillations in the medium spiny neuron population, even if their activity is kept low. Rather, what matters is the firing time relative to just a few other neurons within an oscillation cycle. Finally, we show how the state of ongoing activity, the strengths of different types of inhibitions, the density of outgoing projections, and the overall activity of striatal cells influence network activity. These results suggest that the propagation of oscillatory inputs into the medium spiny neuron population is efficient, if indirect, through fast-spiking interneurons. Therefore, pharmaceuticals that target fast-spiking interneurons may provide a novel treatment for regaining the spectral characteristics of striatal activity that correspond to the healthy state.Author SummaryThe striatum is the largest and primary gateway component of the BG, receiving glutamatergic inputs from all cortical areas and is highly susceptible to cortical oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, external stimuli propagate through the striatal circuitry. The vast majority of striatal neurons, at least 95% of them, are medium spiny neurons (MSNs) that are also the only source of output from the nucleus. Two of the most examined sources of GABAergic inhibition into MSNs are the feedback inhibition (FB) from the axon collaterals of the MSNs themselves, and the feedforward inhibition (FF) via the small population of fast-spiking interneurons (FSIs) comprising roughly 1-2% of striatal neurons. Using a large-scale network model of the striatum we systematically investigate the propagation of asynchronous periodic cortical inputs, throughout the physiologically relevant range, onto the striatal neurons and their influence on striatal network dynamics. Our results show that FSIs, despite their firing being uncorrelated, may play a crucial role in the efficient propagation of external oscillations onto MSNs. Finally, we show how the state of ongoing activity, the strengths of different types of inhibitions, the density of outgoing projections, and the overall activity of striatal cells influence network activity.

Synchrony of Fast-Spiking Interneurons Interconnected by GABAergic and Electrical Synapses

2003 ◽  
Vol 15 (9) ◽  
pp. 2179-2198 ◽  
Author(s):  
Masaki Nomura ◽  
Tomoki Fukai ◽  
Toshio Aoyagi
Keyword(s):  
Potassium Channel ◽  
Large Scale ◽  
Gaba A ◽  
Neuron Pair ◽  
Large Scale Network ◽  
Synchronous Firing ◽  
Scale Network ◽  
Fast Spiking ◽  
Conductance Ratio ◽  
Chemical Synapses

Fast-spiking (FS) interneurons have specific types (Kv3.1/3.2 type) of the delayed potassium channel, which differ from the conventional Hodgkin-Huxley (HH) type potassium channel (Kv1.3 type) in several aspects. In this study, we show dramatic effects of the Kv3.1/3.2 potassium channel on the synchronization of the FS interneurons. We show analytically that two identical electrically coupled FS interneurons modeled with Kv3.1/3.2 channel fire synchronously at arbitrary firing frequencies, unlike similarly coupled FS neurons modeled with Kv1.3 channel that show frequency-dependent synchronous and antisynchronous firing states. Introducing GABA A receptor-mediated synaptic connections into an FS neuron pair tends to induce an antisynchronous firing state, even if the chemical synapses are bidirectional. Accordingly, an FS neuron pair connected simultaneously by electrical and chemical synapses achieves both synchronous firing state and antisynchronous firing state in a physiologically plausible range of the conductance ratio between electrical and chemical synapses. Moreover, we find that a large-scale network of FS interneurons connected by gap junctions and bidirectional GABAergic synapses shows similar bistability in the range of gamma frequencies (30–70 Hz).

Voltage-Sensitive Dye Imaging

2015 ◽  
Author(s):  
William Frost ◽  
Jian-young Wu
Keyword(s):  
Large Scale ◽  
Brain Slices ◽  
Network Activity ◽  
Neural Signals ◽  
Voltage Sensitive Dye ◽  
Large Scale Network ◽  
Scale Network ◽  
Invertebrate Ganglia ◽  
Voltage Sensitive Dye Imaging

Voltage sensitive dye imaging (VSD) can be used to record neural activity in hundreds of locations in preparations ranging from mammalian cortex to invertebrate ganglia. Because fast VSDs respond to membrane potential changes with microsecond temporal resolution, these are better suited than calcium indicators for recording rapid neural signals. Here we describe methods for using a 464- element photodiode array and fast VSDs to record signals ranging from large scale network activity in brain slices and in vivo mammalian preparations, to action potentials in over 100 individual neurons in invertebrate ganglia.

scholarly journals Stimulus-dependent spiking relationships with the EEG

2015 ◽  
Vol 114 (3) ◽  
pp. 1468-1482 ◽  
Author(s):  
Adam C. Snyder ◽  
Matthew A. Smith
Keyword(s):  
Large Scale ◽  
Visual Stimulation ◽  
Rhesus Macaques ◽  
Local Population ◽  
Network Activity ◽  
Eeg Signals ◽  
Area V4 ◽  
Large Scale Network ◽  
Scale Network ◽  
Local Circuitry

The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network

Attention Biases Visual Activity in Visual Short-term Memory

2014 ◽  
Vol 26 (7) ◽  
pp. 1377-1389 ◽  
Author(s):  
Bo-Cheng Kuo ◽  
Mark G. Stokes ◽  
Alexandra M. Murray ◽  
Anna Christina Nobre
Keyword(s):  
Large Scale ◽  
Short Term Memory ◽  
Control Mechanisms ◽  
Top Down ◽  
Short Term ◽  
Visual Activity ◽  
Visual Short Term Memory ◽  
Large Scale Network ◽  
Visual Areas ◽  
Scale Network

In the current study, we tested whether representations in visual STM (VSTM) can be biased via top–down attentional modulation of visual activity in retinotopically specific locations. We manipulated attention using retrospective cues presented during the retention interval of a VSTM task. Retrospective cues triggered activity in a large-scale network implicated in attentional control and led to retinotopically specific modulation of activity in early visual areas V1–V4. Importantly, shifts of attention during VSTM maintenance were associated with changes in functional connectivity between pFC and retinotopic regions within V4. Our findings provide new insights into top–down control mechanisms that modulate VSTM representations for flexible and goal-directed maintenance of the most relevant memoranda.

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