Noise Suppression and Surplus Synchrony by Coincidence Detection

The functional significance of correlations between action potentials of neurons is still a matter of vivid debates. In particular it is presently unclear how much synchrony is caused by afferent synchronized events and how much is intrinsic due to the connectivity structure of cortex. The available analytical approaches based on the diffusion approximation do not allow to model spike synchrony, preventing a thorough analysis. Here we theoretically investigate to what extent common synaptic afferents and synchronized inputs each contribute to closely time-locked spiking activity of pairs of neurons. We employ direct simulation and extend earlier analytical methods based on the diffusion approximation to pulse-coupling, allowing us to introduce precisely timed correlations in the spiking activity of the synaptic afferents. We investigate the transmission of correlated synaptic input currents by pairs of integrate-and-fire model neurons, so that the same input covariance can be realized by common inputs or by spiking synchrony. We identify two distinct regimes: In the limit of low correlation linear perturbation theory accurately determines the correlation transmission coefficient, which is typically smaller than unity, but increases sensitively even for weakly synchronous inputs. In the limit of high afferent correlation, in the presence of synchrony a qualitatively new picture arises. As the non-linear neuronal response becomes dominant, the output correlation becomes higher than the total correlation in the input. This transmission coefficient larger unity is a direct consequence of non-linear neural processing in the presence of noise, elucidating how synchrony-coded signals benefit from these generic properties present in cortical networks

Real-time functional magnetic resonance imaging-brain-computer interfacing in the assessment and treatment of psychopathy : potential and challenges

This chapter focuses on the engagement of real-time functional magnetic resonance imaging-brain-computer interfacing (rtfMRI-BCI) in the treatment of psychopathy and some of the more pertinent ethico-legal and social issues fostered by such use of this neurotechnological approach. To this end, we first provide an overview of the nature of psychopathy. Second, we pose the premise that given the paucity – if not frank absence – of effective psychopharmacological treatment(s) or rehabilitation strategies presently available for psychopathy, it becomes important to examine the present state of neurotechnologies that might be used to effect potential benefit in the treatment of this disorder and focus this examination upon the possible utility of rtfMRI-brain-computer interface technology. Third, we present an overview of those tools that are currently used to determine and diagnose psychopathy and discuss their limitations. Finally, we address the major ethical questions and issues arising from the use of this technology to modify behavior in individuals with psychopathic trait

Modulation of synchrony without changes in firing rates

It was often reported and suggested that the synchronization of spikes can occur without changes in the firing rate. However, few theoretical studies have tested its mechanistic validity. In the present study, we investigate whether changes in synaptic weights can induce an independent modulation of synchrony while the firing rate remains constant. We study this question at the level of both single neurons and neuronal populations using network simulations of conductance based integrate-and-fire neurons. The network consists of a single layer that includes local excitatory and inhibitory recurrent connections, as well as long-range excitatory projections targeting both classes of neurons. Each neuron in the network receives external input consisting of uncorrelated Poisson spike trains. We find that increasing this external input leads to a linear increase of activity in the network, as well as an increase in the peak frequency of oscillation. In contrast, balanced changes of the synaptic weight of excitatory long-range projections for both classes of postsynaptic neurons modulate the degree of synchronization without altering the firing rate. These results demonstrate that, in a simple network, synchronization and firing rate can be modulated independently, and thus, may be used as independent coding dimensions

Dynamic predictions: oscillations and synchrony in top-down processing

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