Spike Timing Amplifies the Effect of Electric Fields on Neurons: Implications for Endogenous Field Effects

Radman, Thomas; Su, Yuzhuo; An, Je Hi; Parra, Lucas C.; Bikson, Marom

doi:10.1523/jneurosci.0095-07.2007

Cited by 258 publications

(251 citation statements)

References 55 publications

(63 reference statements)

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“…Extracellular recordings of local field potentials (LFPs) directly from the cortex reveal bursts of oscillatory activity. These might modulate stimulus-related activity, either directly (by providing additional synaptic inputs) or indirectly (by generating gradients in the extracellular potential 58 ), and thus might cause the apparent imprecision of cortical responses described above.…”

Section: The Contribution Of Cortical Oscillations To Precisionmentioning

confidence: 99%

Regulation of spike timing in visual cortical circuits

2008

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A train of action potentials (a spike train) can carry information in both the average firing rate and the pattern of spikes in the train. But can such a spike-pattern code be supported by cortical circuits? Neurons in vitro produce a spike pattern in response to the injection of a fluctuating current. However, cortical neurons in vivo are modulated by local oscillatory neuronal activity and by top-down inputs. In a cortical circuit, precise spike patterns thus reflect the interaction between internally generated activity and sensory information encoded by input spike trains. We review the evidence for precise and reliable spike timing in the cortex and discuss its computational role.Reliability and precision are two different quantities. When you make an appointment with your friend, she can either keep the appointment or not show up at all. If she does show up, she might or might not be on time. The former uncertainty is related to reliability, whereas the latter is related to precision. When the same stimulus waveform is repeatedly injected at the soma of a neuron in vitro (FIG. 1a), a similar spike train is obtained on each trial 1,2 (FIG. 1b). When approximately the same number of spikes occur on each trial the neuron is said to be reliable, whereas when the spikes occur almost at the same time across trials it is said to be precise (FIG. 1c). For a single neuron, the potential information content of precise and reliable spike times is many times larger than that which is contained in the firing rate, which is averaged across a typical interval of a hundred milliseconds [3][4][5][6] . The information contained in spike timing is available immediately, rather than after an averaging period. Furthermore, the timing of patterns of spikes can potentially transmit even more information than the timing of the individual constituent spikes 3,7 . The potential relevance of spike patterns becomes apparent when we consider neurons at the population level: when a group of similar neurons (a 'pool') produces precise and reliable spike trains, the neurons they project to receive volleys of synchronous spikes 8,9 . This opens up the possibility of communicating between different cortical areas through synchronous spike volleys.In contrast to the in vitro situation described above, in the intact cortex most excitatory synaptic inputs arrive at the dendrites rather than at the soma (FIG. 1d), and synaptic transmission is typically unreliable [10][11][12][13] . Furthermore, most of these dendritic inputs are not directly related to ongoing sensory stimulation; rather, they reflect spatiotemporally structured internal activity. Therefore, when the same stimulus is presented repeatedly, the resulting spike trains are usually neither precise nor reliable when they are aligned to the stimulus onset 6 . Instead, HHMI Author ManuscriptHHMI Author Manuscript HHMI Author Manuscript neural activity in vivo might be dominated by internally generated complex reverberations or rhythmic oscillations, and precise and reliable sp...

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Section: The Contribution Of Cortical Oscillations To Precisionmentioning

confidence: 99%

Regulation of spike timing in visual cortical circuits

2008

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“…Recently several studies have reported that endogenous electric fields provide an effective (and maybe indispensable) mechanism for a rapid orchestration of neocortical spatiotemporal synchronization patterns (e.g., Anastassiou et al, , 2011Fröhlich and MecCormick, 2010;Marshall et al, 2006;Ozen et al, 2010;Radman and Nicholson, 2007;Weiss and Paulsen, 2010). Although the magnitude of local fields is considerably lower than the typical threshold potential of a neuron Fröhlich and MecCormick, 2010) they still may modulate spike timing of single neurons via ephaptic coupling (Radman and Nicholson, 2007) as well as the collective neuronal dynamics of entire neuronal populations (Fröhlich and MecCormick, 2010;Weiss and Paulsen, 2010).…”

Section: Volume Conduction and Choice Of Referencementioning

confidence: 99%

“…Although the magnitude of local fields is considerably lower than the typical threshold potential of a neuron Fröhlich and MecCormick, 2010) they still may modulate spike timing of single neurons via ephaptic coupling (Radman and Nicholson, 2007) as well as the collective neuronal dynamics of entire neuronal populations (Fröhlich and MecCormick, 2010;Weiss and Paulsen, 2010). Endogenous local fields modulate neuronal membrane potentials on a subthreshold level (Fröh-lich and MecCormick, 2010;Ozen et al, 2010;Weiss and Paulsen, 2010) and thereby influence network activity.…”

Section: Volume Conduction and Choice Of Referencementioning

confidence: 99%

“…Coming back to the earlier-mentioned constructive role of endogenous fields the question arises whether they participate actively in such processes and what constitutes the fast and efficient mechanism that permits the recruitment or dismissal of neuronal assemblies. One possible explanation might be binding by resonance, where slow modulations of local fields may trigger the spiking of individual neurons (Radman and Nicholson, 2007) or entire populations (Ozen, 2010). On the other hand, individual neurons have preferred possibly narrow frequency ranges where they show optimal response to external stimuli (Hutcheon et al, 2000).…”

Section: Local Information Processing Versus Global Dynamicsmentioning

confidence: 99%

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Standing Waves as an Explanation for Generic Stationary Correlation Patterns in Noninvasive EEG of Focal Onset Seizures

et al. 2014

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Cerebral electrical activity is highly nonstationary because the brain reacts to ever changing external stimuli and continuously monitors internal control circuits. However, a large amount of energy is spent to maintain remarkably stationary activity patterns and functional inter-relations between different brain regions. Here we examine linear EEG correlations in the peri-ictal transition of focal onset seizures, which are typically understood to be manifestations of dramatically changing inter-relations. Contrary to expectations we find stable correlation patterns with a high similarity across different patients and different frequency bands. This skeleton of spatial correlations may be interpreted as a signature of standing waves of electrical brain activity constituting a dynamical ground state. Such a state could promote the formation of spatiotemporal neuronal assemblies and may be important for the integration of information stemming from different local circuits of the functional brain network.

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“…Radman, Su, An, Parra, and Bikson (2007) investigated the effect of Local Field Potentials (LFPs) on neural spikes and found that hyperpolarizing LFP delayed action potential while depolarizing LFP advanced it. In our model, an oscillatory signal representing LFP modulates the phase of the neural spikes.…”

Section: Introductionmentioning

confidence: 99%

Oscillatory synchronization model of attention to moving objects

Yılmaz¹

2012

Neural Networks

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a b s t r a c tThe world is a dynamic environment hence it is important for the visual system to be able to deploy attention on moving objects and attentively track them. Psychophysical experiments indicate that processes of both attentional enhancement and inhibition are spatially focused on the moving objects; however the mechanisms of these processes are unknown. The studies indicate that the attentional selection of target objects is sustained via a feedforward-feedback loop in the visual cortical hierarchy and only the target objects are represented in attention-related areas. We suggest that feedback from the attention-related areas to early visual areas modulates the activity of neurons; establishes synchronization with respect to a common oscillatory signal for target items via excitatory feedback, and also establishes de-synchronization for distractor items via inhibitory feedback. A two layer computational neural network model with integrate-and-fire neurons is proposed and simulated for simple attentive tracking tasks. Consistent with previous modeling studies, we show that via temporal tagging of neural activity, distractors can be attentively suppressed from propagating to higher levels. However, simulations also suggest attentional enhancement of activity for distractors in the first layer which represents neural substrate dedicated for low level feature processing. Inspired by this enhancement mechanism, we developed a feature based object tracking algorithm with surround processing. Surround processing improved tracking performance by 57% in PETS 2001 dataset, via eliminating target features that are likely to suffer from faulty correspondence assignments.

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Spike Timing Amplifies the Effect of Electric Fields on Neurons: Implications for Endogenous Field Effects

Cited by 258 publications

References 55 publications

Regulation of spike timing in visual cortical circuits

Regulation of spike timing in visual cortical circuits

Standing Waves as an Explanation for Generic Stationary Correlation Patterns in Noninvasive EEG of Focal Onset Seizures

Oscillatory synchronization model of attention to moving objects

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