Paul H. E. Tiesinga

Regulation of spike timing in visual cortical circuits.

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.

Cortical Enlightenment: Are Attentional Gamma Oscillations Driven by ING or PING?

The response of a neuron to sensory stimuli can only give correlational support for functional hypotheses. To experimentally test causal function, the neural activity needs to be manipulated in a cell-type-specific as well as spatially and temporally precise way. We review recent optogenetic experiments on parvalbumin-positive cortical interneurons that link modeling studies of synchronization to experimental studies on attentional modulation of gamma oscillations in primates.

Oscillations in the prefrontal cortex: a gateway to memory and attention

We consider the potential role of oscillations in the prefrontal cortex (PFC) in mediating attention, working memory and memory consolidation. Activity in the theta, beta, and gamma bands is related to communication between PFC and different brain areas. While gamma/beta oscillations mediate bottom-up and top-down interactions between PFC and visual cortices, related to attention, theta rhythms are engaged by hippocampal/PFC interplay. These interactions are dynamic, depending on the nature and relevance of the information currently being processed. The profound modifications of the PFC neuronal network associated with changes in oscillatory coherence are controlled by neuromodulators such as dopamine, which thereby allow or prevent the formation of cell assemblies for information encoding and storage.

Discovering Spike Patterns in Neuronal Responses

When a cortical neuron is repeatedly injected with the same fluctuating current stimulus (frozen noise) the timing of the spikes is highly precise from trial to trial and the spike pattern appears to be unique. We show here that the same repeated stimulus can produce more than one reliable temporal pattern of spikes. A new method is introduced to find these patterns in raw multitrial data and is tested on surrogate data sets. Using it, multiple coexisting spike patterns were discovered in pyramidal cells recorded from rat prefrontal cortex in vitro, in data obtained in vivo from the middle temporal area of the monkey (Buracas et al., 1998) and from the cat lateral geniculate nucleus (Reinagel and Reid, 2002). The spike patterns lasted from a few tens of milliseconds in vitro to several seconds in vivo. We conclude that the prestimulus history of a neuron may influence the precise timing of the spikes in response to a stimulus over a wide range of time scales.

Inhibitory synchrony as a mechanism for attentional gain modulation.

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing rate of the neuron can change and there can be an increase in the coherence between spikes and the local field potential (LFP) in the gamma-frequency range (30-50 Hz). The hypothesis explored here is that these observed effects of attention could be a consequence of changes in the synchrony of local interneuron networks. We performed computer simulations of a Hodgkin-Huxley type neuron driven by a constant depolarizing current, I, representing visual stimulation and a modulatory inhibitory input representing the effects of attention via local interneuron networks. We observed that the neurons firing rate and the coherence of its output spike train with the synaptic inputs was modulated by the degree of synchrony of the inhibitory inputs. When inhibitory synchrony increased, the coherence of spiking model neurons with the synaptic input increased, but the firing rate either increased or remained the same. The mean number of synchronous inhibitory inputs was a key determinant of the shape of the firing rate versus current (f-I) curves. For a large number of inhibitory inputs (approximately 50), the f-I curve saturated for large I and an increase in input synchrony resulted in a shift of sensitivity-the model neuron responded to weaker inputs I. For a small number (approximately 10), the f-I curves were non-saturating and an increase in input synchrony led to an increase in the gain of the response-the firing rate in response to the same input was multiplied by an approximately constant factor. The firing rate modulation with inhibitory synchrony was highest when the input network oscillated in the gamma frequency range. Thus, the observed changes in firing rate and coherence of neurons in the visual cortex could be controlled by top-down inputs that regulated the coherence in the activity of a local inhibitory network discharging at gamma frequencies.

Dynamic circuit motifs underlying rhythmic gain control, gating and integration

Brain circuitry processes information by rapidly and selectively engaging functional neuronal networks. The dynamic formation of networks is often evident in rhythmically synchronized neuronal activity and tightly correlates with perceptual, cognitive and motor performances. But how synchronized neuronal activity contributes to network formation and how it relates to the computation of behaviorally relevant information has remained difficult to discern. Here we structure recent empirical advances that link synchronized activity to the activation of so-called dynamic circuit motifs. These motifs explicitly relate (1) synaptic and cellular properties of circuits to (2) identified timescales of rhythmic activation and to (3) canonical circuit computations implemented by rhythmically synchronized circuits. We survey the ubiquitous evidence of specific cell and circuit properties underlying synchronized activity across theta, alpha, beta and gamma frequency bands and show that their activation likely implements gain control, context-dependent gating and state-specific integration of synaptic inputs. This evidence gives rise to the dynamic circuit motifs hypothesis of synchronized activation states, with its core assertion that activation states are linked to uniquely identifiable local circuit structures that are recruited during the formation of functional networks to perform specific computational operations.

Rapid Temporal Modulation of Synchrony by Competition in Cortical Interneuron Networks

The synchrony of neurons in extrastriate visual cortex is modulated by selective attention even when there are only small changes in firing rate (Fries, Reynolds, Rorie, & Desimone, 2001). We used Hodgkin-Huxley type models of cortical neurons to investigate the mechanism by which the degree of synchrony can be modulated independently of changes in firing rates. The synchrony of local networks of model cortical interneurons interacting through GABAA synapses was modulated on a fast timescale by selectively activating a fraction of the interneurons. The activated interneurons became rapidly synchronized and suppressed the activity of the other neurons in the network but only if the network was in a restricted range of balanced synaptic background activity. During stronger background activity, the network did not synchronize, and for weaker background activity, the network synchronized but did not return to an asynchronous state after synchronizing. The inhibitory output of the network blocked the activity of pyramidal neurons during asynchronous network activity, and during synchronous network activity, it enhanced the impact of the stimulus-related activity of pyramidal cells on receiving cortical areas (Salinas & Sejnowski, 2001). Synchrony by competition provides a mechanism for controlling synchrony with minor alterations in rate, which could be useful for information processing. Because traditional methods such as cross-correlation and the spike field coherence require several hundred milliseconds of recordings and cannot measure rapid changes in the degree of synchrony, we introduced a new method to detect rapid changes in the degree of coincidence and precision of spike timing.

Robust gamma oscillations in networks of inhibitory hippocampal interneurons

Recent experiments suggest that inhibitory networks of interneurons can synchronize the neuronal discharge in in vitro hippocampal slices. Subsequent theoretical work has shown that strong synchronization by mutual inhibition is only moderately robust against neuronal heterogeneities in the current drive, provided by activation of metabotropic glutamate receptors. In vivo neurons display greater variability in the interspike intervals due to the presence of synaptic noise. Noise and heterogeneity affect synchronization properties differently. In this paper we study, using model simulations, how robust synchronization can be in the presence of synaptic noise and neuronal heterogeneity. We find that stochastic weak synchronization (SWS) (i.e. when neurons spike within a short interval from each other, but not necessarily at each period) is produced with at least a minimum amount of noise and that it is much more robust than strong synchronization (i.e. when neurons spike at each period). The statistics produced by the SWS population discharge are consistent with previous experimental data. We also find robust SWS in the gamma-frequency range (20-80 Hz) for a stronger synaptic coupling compared with previous models and for networks with 10-1000 neurons.

Mechanisms for Phase Shifting in Cortical Networks and their Role in Communication through Coherence

In the primate visual cortex, the phase of spikes relative to oscillations in the local field potential (LFP) in the gamma frequency range (30–80 Hz) can be shifted by stimulus features such as orientation and thus the phase may carry information about stimulus identity. According to the principle of communication through coherence (CTC), the relative LFP phase between the LFPs in the sending and receiving circuits affects the effectiveness of the transmission. CTC predicts that phase shifting can be used for stimulus selection. We review and investigate phase shifting in models of periodically driven single neurons and compare it with phase shifting in models of cortical networks. In a single neuron, as the driving current is increased, the spike phase varies systematically while the firing rate remains constant. In a network model of reciprocally connected excitatory (E) and inhibitory (I) cells phase shifting occurs in response to both injection of constant depolarizing currents and to brief pulses to I cells. These simple models provide an account for phase-shifting observed experimentally and suggest a mechanism for implementing CTC. We discuss how this hypothesis can be tested experimentally using optogenetic techniques.

Role of Interneuron Diversity in the Cortical Microcircuit for Attention

Receptive fields of neurons in cortical area V4 are large enough to fit multiple stimuli, making V4 the ideal place to study the effects of selective attention at the single-neuron level. Experiments have revealed evidence for stimulus competition and have characterized the effect thereon of spatial and feature-based attention. We developed a biophysical model with spiking neurons and conductance-based synapses. To account for the comprehensive set of experimental results, it was necessary to include in the model, in addition to regular spiking excitatory (E) cells, two types of interneurons: feedforward interneurons (FFI) and top-down interneurons (TDI). Feature-based attention was mediated by a projection of the TDI to the FFI, stimulus competition was mediated by a cross-columnar excitatory connection to the FFI, whereas spatial attention was mediated by an increase in activity of the feedforward inputs from cortical area V2. The model predicts that spatial attention increases the FFI firing rate, whereas feature-based attention decreases the FFI firing rate and increases the TDI firing rate. During strong stimulus competition, the E cells were synchronous in the beta frequency range (15-35 Hz), but with feature-based attention, they became synchronous in the gamma frequency range (35-50 Hz). We propose that the FFI correspond to fast-spiking, parvalbumin-positive basket cells and that the TDI correspond to cells with a double-bouquet morphology that are immunoreactive to calbindin or calretinin. Taken together, the model results provide an experimentally testable hypothesis for the behavior of two interneuron types under attentional modulation.