Neurosystems: brain rhythms and cognitive processing

Neuronal rhythms are ubiquitous features of brain dynamics, and are highly correlated with cognitive processing. However, the relationship between the physiological mechanisms producing these rhythms and the functions associated with the rhythms remains mysterious. This article investigates the contributions of rhythms to basic cognitive computations (such as filtering signals by coherence and/or frequency) and to major cognitive functions (such as attention and multi-modal coordination). We offer support to the premise that the physiology underlying brain rhythms plays an essential role in how these rhythms facilitate some cognitive operations.098352 - Wellcome Trust; 5R01NS067199 - NINDS NIH HH

Neuronal Oscillations Enhance Stimulus Discrimination by Ensuring Action Potential Precision

Although oscillations in membrane potential are a prominent feature of sensory, motor, and cognitive function, their precise role in signal processing remains elusive. Here we show, using a combination of in vivo, in vitro, and theoretical approaches, that both synaptically and intrinsically generated membrane potential oscillations dramatically improve action potential (AP) precision by removing the membrane potential variance associated with jitter-accumulating trains of APs. This increased AP precision occurred irrespective of cell type and—at oscillation frequencies ranging from 3 to 65 Hz—permitted accurate discernment of up to 1,000 different stimuli. At low oscillation frequencies, stimulus discrimination showed a clear phase dependence whereby inputs arriving during the trough and the early rising phase of an oscillation cycle were most robustly discriminated. Thus, by ensuring AP precision, membrane potential oscillations dramatically enhance the discriminatory capabilities of individual neurons and networks of cells and provide one attractive explanation for their abundance in neurophysiological systems

Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks

We study the collective dynamics of a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at differentctime scales. Using an STDP-based learning process, we store in the connectivity several phase-coded spike patterns, and we find that, depending on the excitability of the network, different working regimes are possible, with transient or persistent replay activity induced by a brief signal. We introduce an order parameter to evaluate the similarity between stored and recalled phase-coded pattern, and measure the storage capacity. Modulation of spiking thresholds during replay changes the frequency of the collective oscillation or the number of spikes per cycle, keeping preserved the phases relationship. This allows a coding scheme in which phase, rate and frequency are dissociable. Robustness with respect to noise and heterogeneity of neurons parameters is studied, showing that, since dynamics is a retrieval process, neurons preserve stablecprecise phase relationship among units, keeping a unique frequency of oscillation, even in noisy conditions and with heterogeneity of internal parameters of the units

Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate-and-fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre- and post-synaptic activity. We store multiple patterns and study the network capacity. For the analog model, we find that the network capacity scales linearly with the network size, and that both capacity and the oscillation frequency of the retrieval state depend on the asymmetry of the learning time window. In addition to fully-connected networks, we study sparse networks, where each neuron is connected only to a small number z << N of other neurons. Connections can be short range, between neighboring neurons placed on a regular lattice, or long range, between randomly chosen pairs of neurons. We find that a small fraction of long range connections is able to amplify the capacity of the network. This imply that a small-world-network topology is optimal, as a compromise between the cost of long range connections and the capacity increase. Also in the spiking integrate and fire model the crucial result of storing and retrieval of multiple phase-coded patterns is observed. The capacity of the fully-connected spiking network is investigated, together with the relation between oscillation frequency of retrieval state and window asymmetry

Doctor of Philosophy

dissertationThe brain's medial entorhinal cortex (MEC) plays a key role in spatial navigation, serving as the node between the hippocampus and the rest of the mammalian cortex. In the last 10 years, spatially-modulated "grid" cells in the superficial MEC have been shown to preferentially fire as the animal moves into the apices of a hexagonal grid. Our incomplete understanding of the inhibitory dynamics within the MEC, however, limits our knowledge of how this brain structure executes such spatial navigation functions. Here, we explore various roles that inhibition plays in the superficial MEC and characterize the neuronal population that elicits this inhibition. We find that excitatory stellate cells in the layer 2 MEC exhibit membrane-dependent, nonlinear synaptic integration of inhibitory inputs, amplifying inputs that arrive near their firing threshold and dampening those that arrive closer to rest. Our next study is the first systematic anatomical/electrophysiological characterization of the superficial MEC's inhibitory interneuron population. We find that they are best classified into four clusters with distinct anatomical/electrophysiological profiles. In our last study, we investigated the viability of a novel, inhibition-mediated gamma rhythm model, finding that superficial MEC interneurons can exhibit resonant behaviors that could be key to generating neuronal network oscillations. The work presented here provides valuable groundwork for understanding MEC cortical computation

Stimulus competition by inhibitory interference

When two stimuli are present in the receptive field of a V4 neuron, the firing rate response is between the weakest and strongest response elicited by each of the stimuli alone (Reynolds et al, 1999, Journal of Neuroscience 19:1736-1753). When attention is directed towards the stimulus eliciting the strongest response (the preferred stimulus), the response to the pair is increased, whereas the response decreases when attention is directed to the other stimulus (the poor stimulus). These experimental results were reproduced in a model of a V4 neuron under the assumption that attention modulates the activity of local interneuron networks. The V4 model neuron received stimulus-specific asynchronous excitation from V2 and synchronous inhibitory inputs from two local interneuron networks in V4. Each interneuron network was driven by stimulus-specific excitatory inputs from V2 and was modulated by a projection from the frontal eye fields. Stimulus competition was present because of a delay in arrival time of synchronous volleys from each interneuron network. For small delays, the firing rate was close to the rate elicited by the preferred stimulus alone, whereas for larger delays it approached the firing rate of the poor stimulus. When either stimulus was presented alone the neuron's response was not altered by the change in delay. The model suggests that top-down attention biases the competition between V2 columns for control of V4 neurons by changing the relative timing of inhibition rather than by changes in the degree of synchrony of interneuron networks. The mechanism proposed here for attentional modulation of firing rate - gain modulation by inhibitory interference - is likely to have more general applicability to cortical information processing.Comment: 20 pages, 7 figures, 1 tabl

Direct and indirect cholinergic septo-hippocampal pathways cooperate to structure spiking activity in the hippocampus

The medial septum/vertical diagonal band of Broca complex (MSvDB) is a key structure that modulates hippocampal rhythmogenesis. Cholinergic neurons of the MSvDB play a central role in generating and pacing theta-band oscillations in the hippocampal formation during exploration, novelty detection, and memory encoding. However, how precisely cholinergic neurons affect hippocampal oscillatory activity and spiking rates of hippocampal neurons in vivo, has remained elusive. I therefore used silicon probe recordings of local field potentials and unit activity in the dorsal hippocampus in combination with cell type specific optogenetic activation of cholinergic MSvDB neurons to study the effects of synaptically released acetylcholine on hippocampal network activity in urethane-anesthetized mice.In vivo optogenetic activation of cholinergic MSvDB neurons induced hippocampal rhythmogenesis at the theta (3-6 Hz) and slow gamma (26-48 Hz) frequency range with a suppression of peri-theta frequencies. Interestingly, this effect was independent from the stimulation frequency. In addition, stimulation of cholinergic MSvDB neurons resulted in a net increase of interneuron firing with a concomitant net decrease of principal cell firing in the hippocampal CA3 subfield. I used focal injections of cholinergic blockers either into the MSvDB or the hippocampus to demonstrate that cholinergic MSvDB neurons modulate hippocampal network activity via two distinct pathways. Focal injection of a cholinergic blocker cocktail into the hippocampus strongly diminished the cholinergic stimulation-induced spiking rate modulation of hippocampal interneurons and principal cells. This demonstrates that modulation of neuronal activity in hippocampal subfield CA3 by cholinergic MSvDB neurons is mediated via direct septo-hippocampal projections. In contrast, focal injection of atropine, a blocker of the muscarinic type of acetylcholine receptors, into the MSvDB had no effect on spiking rate modulation in CA3, but abolished hippocampal theta synchronization. This strongly suggests that activity of an indirect septo-hippocampal pathway induces hippocampal theta oscillations via an intraseptal relay. Furthermore, cholinergic neurons depolarized parvalbumin-positive (PV+) GABAergic neurons within the MSvDB in vitro, and optogenetic activation of these fast spiking neurons in vivo induced hippocampal rhythmic activity precisely at the stimulation frequency. Taken together, these data suggest an intraseptal relay with a strong contribution of PV+ GABAergic MSvDB neurons in pacing hippocampal theta oscillations. Activation of both the direct and indirect pathways causes a reduction in CA3 pyramidal neuron firing and a more precise coupling to theta oscillatory phase with CA3 interneurons preferentially firing at the descending phase and CA3 principal neurons preferentially firing near the trough of the ongoing theta oscillation recorded at the pyramidal cell layer. The two identified anatomically and functionally distinct pathways are likely relevant for cholinergic control of encoding vs. retrieval modes in the hippocampus

Support for a synaptic chain model of neuronal sequence generation

In songbirds, the remarkable temporal precision of song is generated by a sparse sequence of bursts in the premotor nucleus HVC. To distinguish between two possible classes of models of neural sequence generation, we carried out intracellular recordings of HVC neurons in singing zebra finches (Taeniopygia guttata). We found that the subthreshold membrane potential is characterized by a large, rapid depolarization 5–10 ms before burst onset, consistent with a synaptically connected chain of neurons in HVC. We found no evidence for the slow membrane potential modulation predicted by models in which burst timing is controlled by subthreshold dynamics. Furthermore, bursts ride on an underlying depolarization of ~10-ms duration, probably the result of a regenerative calcium spike within HVC neurons that could facilitate the propagation of activity through a chain network with high temporal precision. Our results provide insight into the fundamental mechanisms by which neural circuits can generate complex sequential behaviours.National Institutes of Health (U.S.) (Grant MH067105)National Institutes of Health (U.S.) (Grant DC009280)National Science Foundation (U.S.) (IOS-0827731)Alfred P. Sloan Foundation (Research Fellowship