Fluctuating Inhibitory Inputs Promote Reliable Spiking at Theta Frequencies in Hippocampal Interneurons

Theta-frequency (4–12 Hz) rhythms in the hippocampus play important roles in learning and memory. CA1 interneurons located at the stratum lacunosum-moleculare and radiatum junction (LM/RAD) are thought to contribute to hippocampal theta population activities by rhythmically pacing pyramidal cells with inhibitory postsynaptic potentials. This implies that LM/RAD cells need to fire reliably at theta frequencies in vivo. To determine whether this could occur, we use biophysically based LM/RAD model cells and apply different cholinergic and synaptic inputs to simulate in vivo-like network environments. We assess spike reliabilities and spiking frequencies, identifying biophysical properties and network conditions that best promote reliable theta spiking. We find that synaptic background activities that feature large inhibitory, but not excitatory, fluctuations are essential. This suggests that strong inhibitory input to these cells is vital for them to be able to contribute to population theta activities. Furthermore, we find that Type I-like oscillator models produced by augmented persistent sodium currents (INaP) or diminished A-type potassium currents (IA) enhance reliable spiking at lower theta frequencies. These Type I-like models are also the most responsive to large inhibitory fluctuations and can fire more reliably under such conditions. In previous work, we showed that INaP and IA are largely responsible for establishing LM/RAD cells’ subthreshold activities. Taken together with this study, we see that while both these currents are important for subthreshold theta fluctuations and reliable theta spiking, they contribute in different ways – INaP to reliable theta spiking and subthreshold activity generation, and IA to subthreshold activities at theta frequencies. This suggests that linking subthreshold and suprathreshold activities should be done with consideration of both in vivo contexts and biophysical specifics

Effect of Background Synaptic Activity on Excitatory-Postsynaptic Potential-Spike Coupling

Neurons receive large amount of synaptic inputs in vivo, which may impact the coupling between EPSPs and spikes. We mimicked the in vivo synaptic activity of the cell with the dynamic clamp system. We recorded from pyramidal cells in neocortical slices in vitro to investigate how timing and probability of spike generation in response to an EPSP is affected by background synaptic conductance under these conditions. We found that near threshold, background synaptic conductance improved the precision of spike timing by reducing the depolarization-related prolongation of the EPSP. In cells with ongoing spike activity and background synaptic conductances, an EPSP rapidly increased the probability of firing. The time window of the spike probability increase was comparable to the EPSP rise time and was followed by a long period of reduced firing. We found that the net synaptic gain was determined not only by the amplitude of the EPSP, but also by the firing frequency of the cell. In addition, a background fluctuating conductance reduced the time window of perturbation of spike patterns generated by EPSP related spikes. Taken together, these results indicate that in vivo, the level of the background synaptic activity may regulate spike-timing precision and affect synaptic gain

Dynamic Control of Network Level Information Processing through Cholinergic Modulation

Acetylcholine (ACh) release is a prominent neurochemical marker of arousal state within the brain. Changes in ACh are associated with changes in neural activity and information processing, though its exact role and the mechanisms through which it acts are unknown. Here I show that the dynamic changes in ACh levels that are associated with arousal state control informational processing functions of networks through its effects on the degree of Spike-Frequency Adaptation (SFA), an activity dependent decrease in excitability, synchronizability, and neuronal resonance displayed by single cells. Using numerical modeling I develop mechanistic explanations for how control of these properties shift network activity from a stable high frequency spiking pattern to a traveling wave of activity. This transition mimics the change in brain dynamics seen between high ACh states, such as waking and Rapid Eye Movement (REM) sleep, and low ACh states such as Non-REM (NREM) sleep. A corresponding, and related, transition in network level memory recall is also occurs as ACh modulates neuronal SFA. When ACh is at its highest levels (waking) all memories are stably recalled, as ACh is decreased (REM) in the model weakly encoded memories destabilize while strong memories remain stable. In levels of ACh that match Slow Wave Sleep (SWS), no encoded memories are stably recalled. This results from a competition between SFA and excitatory input strength and provides a mechanism for neural networks to control the representation of underlying synaptic information. Finally I show that during the low ACh conditions, oscillatory conditions allow for external inputs to be properly stored in and recalled from synaptic weights. Taken together this work demonstrates that dynamic neuromodulation is critical for the regulation of information processing tasks in neural networks. These results suggest that ACh is capable of switching networks between two distinct information processing modes. Rate coding of information is facilitated during high ACh conditions and phase coding of information is facilitated during low ACh conditions. Finally I propose that ACh levels control whether a network is in one of three functional states: (High ACh; Active waking) optimized for encoding of new information or the stable representation of relevant memories, (Mid ACh; resting state or REM) optimized for encoding connections between currently stored memories or searching the catalog of stored memories, and (Low ACh; NREM) optimized for renormalization of synaptic strength and memory consolidation. This work provides a mechanistic insight into the role of dynamic changes in ACh levels for the encoding, consolidation, and maintenance of memories within the brain.PHDNeuroscienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147503/1/roachjp_1.pd

Oscillatory mechanisms for controlling information flow in neural circuits

Mammalian brains generate complex, dynamic structures of oscillatory activity, in which distributed regions transiently engage in coherent oscillation, often at specific stages in behavioural or cognitive tasks. Much is now known about the dynamics underlying local circuit synchronisation and the phenomenology of where and when such activity occurs. While oscillations have been implicated in many high level processes, for most such phenomena we cannot say with confidence precisely what they are doing at an algorithmic or implementational level. This thesis presents work towards understanding the dynamics and possible function of large scale oscillatory network activity. We first address the question of how coherent oscillatory activity emerges between local networks by measuring phase response curves of an oscillating network in vitro. The network phase response curves provide mechanistic insight into inter-region synchronisation of local network oscillators. Highly simplified firing models are shown to reproduce the experimental data with remarkable accuracy. We then focus on one hypothesised computational function of network oscillations; flexibly controlling the gain of signal flow between anatomically connected networks. We investigate coding strategies and algorithmic operations that support flexible control of signal flow by oscillations, and their implementation by network dynamics. We identify two readout algorithms which selectively recover population rate coded signal with specific oscillatory modulations while ignoring other distracting inputs. By designing a spiking network model that implements one of these mechanisms, we demonstrate oscillatory control of signal flow in convergent pathways. We then investigate constraints on the structures of oscillatory activity that can be used to accurately and selectively control signal flow. Our results suggest that for inputs to be accurately distinguished from one another their oscillatory modulations must be close to orthogonal. This has implications for interpreting in vivo oscillatory activity, and may be an organising principle for the spatio-temporal structure of brain oscillations

Investigating the role of fast-spiking interneurons in neocortical dynamics

PhD ThesisFast-spiking interneurons are the largest interneuronal population in neocortex. It is well documented that this population is crucial in many functions of the neocortex by subserving all aspects of neural computation, like gain control, and by enabling dynamic phenomena, like the generation of high frequency oscillations. Fast-spiking interneurons, which represent mainly the parvalbumin-expressing, soma-targeting basket cells, are also implicated in pathological dynamics, like the propagation of seizures or the impaired coordination of activity in schizophrenia. In the present thesis, I investigate the role of fast-spiking interneurons in such dynamic phenomena by using computational and experimental techniques. First, I introduce a neural mass model of the neocortical microcircuit featuring divisive inhibition, a gain control mechanism, which is thought to be delivered mainly by the soma-targeting interneurons. Its dynamics were analysed at the onset of chaos and during the phenomena of entrainment and long-range synchronization. It is demonstrated that the mechanism of divisive inhibition reduces the sensitivity of the network to parameter changes and enhances the stability and exibility of oscillations. Next, in vitro electrophysiology was used to investigate the propagation of activity in the network of electrically coupled fast-spiking interneurons. Experimental evidence suggests that these interneurons and their gap junctions are involved in the propagation of seizures. Using multi-electrode array recordings and optogenetics, I investigated the possibility of such propagating activity under the conditions of raised extracellular K+ concentration which applies during seizures. Propagated activity was recorded and the involvement of gap junctions was con rmed by pharmacological manipulations. Finally, the interaction between two oscillations was investigated. Two oscillations with di erent frequencies were induced in cortical slices by directly activating the pyramidal cells using optogenetics. Their interaction suggested the possibility of a coincidence detection mechanism at the circuit level. Pharmacological manipulations were used to explore the role of the inhibitory interneurons during this phenomenon. The results, however, showed that the observed phenomenon was not a result of synaptic activity. Nevertheless, the experiments provided some insights about the excitability of the tissue through scattered light while using optogenetics. This investigation provides new insights into the role of fast-spiking interneurons in the neocortex. In particular, it is suggested that the gain control mechanism is important for the physiological oscillatory dynamics of the network and that the gap junctions between these interneurons can potentially contribute to the inhibitory restraint during a seizure.Wellcome Trust

On the role of parvalbumin interneurons in neuronal network activity in the prefrontal cortex

The prefrontal cortex (PFC) is an area important for executive functions, the initiation and temporal organization of goal-directed behavior, as well as social behaviors. Inhibitory interneurons expressing parvalbumin (PV) have a vital role in modulating PFC circuit plasticity and output, as inhibition by PV interneurons on excitatory pyramidal neurons regulates the excitability of the network. Thus, dysfunctions of prefrontal PV interneurons are implicated in the pathophysiology of a range of PFC-dependent neuropsychiatric disorders characterized by excitation and inhibition (E/I) imbalance and impaired gamma oscillations. In particular, the hypofunction of receptors important for neurotransmission and regulating cellular functions, such as the N-methyl-D-aspartate receptors (NMDARs) and the tyrosine receptor kinase B (trkB), has been implicated in PV dysfunction. Notably, this hypofunction is known to impair the normal development of PV interneurons. However, it can also affect adult brain activity. The effects of altered receptors on PV interneurons are multiple, from impaired morphological connectivity to disruption of intrinsic activity, but have not yet been fully characterized. Moreover, the effects of deficits of PV neuron-mediated inhibition on neuronal network activity are complex, involved with compensatory mechanisms, and not fully understood either. For instance, the E/I imbalance due to PV inhibition has been suggested to functionally disrupt the cortex, which can be observed through an abnormal increase in broadband gamma activity. But as the synchronous activity of cortical PV interneurons is necessary for the generation of cortical gamma oscillations, it is paradoxical that deficient PV inhibition is associated with increased broadband gamma power. This thesis aims to examine the role of PV interneurons in shaping neuronal network activity in the mouse PFC by investigating the microscopic to macroscopic functional effects of disrupting receptors necessary for the proper activity of PV interneurons. In paper I, we observed that the increase of broadband gamma power due to NMDAR hypofunction in PV neurons is associated with asynchronies of network activity, confirming that dysfunction of neuronal inhibition can cause desynchronization at multiple time scales (affecting entrainment of spikes by the LFP, as well as cross-frequency coupling and brain states fragmentation). In Paper II, we prompted and analyzed the rippling effect of PV dysfunction in the adult PFC by expressing a dominant-negative trkB receptor specifically in PV interneurons. Despite avoiding interfering with the development of the brain, we found pronounced morphological and functional alterations in the targeted PV interneurons. These changes were associated with unusual aggressive behavior coupled with gamma-band alterations and a decreased modulation of prefrontal excitatory neuronal populations by PV interneurons. Thus, the work presented in this thesis furthers our understanding of the role of PV function in PFC circuitry, particularly of two receptors that are central to the role of PV interneurons in coordinating local circuit activity. A better understanding of the potential mechanisms that could explain the neuronal changes seen in individuals with neuropsychiatric dysfunctions could lead to using gamma oscillations or BDNF-trkB levels as biomarkers in psychiatric disorders. It also presents possibilities for potential treatments designed around reestablishing E/I balance by modifying receptor levels in particular cell types