Rhythm Generation through Period Concatenation in Rat Somatosensory Cortex

Rhythmic voltage oscillations resulting from the summed activity of neuronal populations occur in many nervous systems. Contemporary observations suggest that coexistent oscillations interact and, in time, may switch in dominance. We recently reported an example of these interactions recorded from in vitro preparations of rat somatosensory cortex. We found that following an initial interval of coexistent gamma (∼25 ms period) and beta2 (∼40 ms period) rhythms in the superficial and deep cortical layers, respectively, a transition to a synchronous beta1 (∼65 ms period) rhythm in all cortical layers occurred. We proposed that the switch to beta1 activity resulted from the novel mechanism of period concatenation of the faster rhythms: gamma period (25 ms)+beta2 period (40 ms) = beta1 period (65 ms). In this article, we investigate in greater detail the fundamental mechanisms of the beta1 rhythm. To do so we describe additional in vitro experiments that constrain a biologically realistic, yet simplified, computational model of the activity. We use the model to suggest that the dynamic building blocks (or motifs) of the gamma and beta2 rhythms combine to produce a beta1 oscillation that exhibits cross-frequency interactions. Through the combined approach of in vitro experiments and mathematical modeling we isolate the specific components that promote or destroy each rhythm. We propose that mechanisms vital to establishing the beta1 oscillation include strengthened connections between a population of deep layer intrinsically bursting cells and a transition from antidromic to orthodromic spike generation in these cells. We conclude that neural activity in the superficial and deep cortical layers may temporally combine to generate a slower oscillation

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

Period Concatenation Underlies Interactions between Gamma and Beta Rhythms in Neocortex

The neocortex generates rhythmic electrical activity over a frequency range covering many decades. Specific cognitive and motor states are associated with oscillations in discrete frequency bands within this range, but it is not known whether interactions and transitions between distinct frequencies are of functional importance. When coexpressed rhythms have frequencies that differ by a factor of two or more interactions can be seen in terms of phase synchronization. Larger frequency differences can result in interactions in the form of nesting of faster frequencies within slower ones by a process of amplitude modulation. It is not known how coexpressed rhythms, whose frequencies differ by less than a factor of two may interact. Here we show that two frequencies (gamma – 40 Hz and beta2 – 25 Hz), coexpressed in superficial and deep cortical laminae with low temporal interaction, can combine to generate a third frequency (beta1 – 15 Hz) showing strong temporal interaction. The process occurs via period concatenation, with basic rhythm-generating microcircuits underlying gamma and beta2 rhythms forming the building blocks of the beta1 rhythm by a process of addition. The mean ratio of adjacent frequency components was a constant – approximately the golden mean – which served to both minimize temporal interactions, and permit multiple transitions, between frequencies. The resulting temporal landscape may provide a framework for multiplexing – parallel information processing on multiple temporal scales

Are Different Rhythms Good for Different Functions?

This essay discusses the relationship between the physiology of rhythms and potential functional roles. We focus on how the biophysics underlying different rhythms can give rise to different abilities of a network to form and manipulate cell assemblies. We also discuss how changes in the modulatory setting of the rhythms can change the flow of information through cortical circuits, again tying physiology to computation. We suggest that diverse rhythms, or variations of a rhythm, can support different components of a cognitive act, with multiple rhythms potentially playing multiple roles

A unified approach to linking experimental, statistical and computational analysis of spike train data

A fundamental issue in neuroscience is how to identify the multiple biophysical mechanisms through which neurons generate observed patterns of spiking activity. In previous work, we proposed a method for linking observed patterns of spiking activity to specific biophysical mechanisms based on a state space modeling framework and a sequential Monte Carlo, or particle filter, estimation algorithm. We have shown, in simulation, that this approach is able to identify a space of simple biophysical models that were consistent with observed spiking data (and included the model that generated the data), but have yet to demonstrate the application of the method to identify realistic currents from real spike train data. Here, we apply the particle filter to spiking data recorded from rat layer V cortical neurons, and correctly identify the dynamics of an slow, intrinsic current. The underlying intrinsic current is successfully identified in four distinct neurons, even though the cells exhibit two distinct classes of spiking activity: regular spiking and bursting. This approach – linking statistical, computational, and experimental neuroscience – provides an effective technique to constrain detailed biophysical models to specific mechanisms consistent with observed spike train data.Published versio

Hetereogeneity in Neuronal Intrinsic Properties: A Possible Mechanism for Hub-Like Properties of the Rat Anterior Cingulate Cortex during Network Activity.

The anterior cingulate cortex (ACC) is vital for a range of brain functions requiring cognitive control and has highly divergent inputs and outputs, thus manifesting as a hub in connectomic analyses. Studies show diverse functional interactions within the ACC are associated with network oscillations in the β (20-30 Hz) and γ (30-80 Hz) frequency range. Oscillations permit dynamic routing of information within cortex, a function that depends on bandpass filter-like behavior to selectively respond to specific inputs. However, a putative hub region such as ACC needs to be able to combine inputs from multiple sources rather than select a single input at the expense of others. To address this potential functional dichotomy, we modeled local ACC network dynamics in the rat in vitro. Modal peak oscillation frequencies in the β- and γ-frequency band corresponded to GABAAergic synaptic kinetics as seen in other regions; however, the intrinsic properties of ACC principal neurons were highly diverse. Computational modeling predicted that this neuronal response diversity broadened the bandwidth for filtering rhythmic inputs and supported combination-rather than selection-of different frequencies within the canonical γ and β electroencephalograph bands. These findings suggest that oscillating neuronal populations can support either response selection (routing) or combination, depending on the interplay between the kinetics of synaptic inhibition and the degree of heterogeneity of principal cell intrinsic conductances.Wellcome Trus

Visual cortical alpha rhythms : function and relation to other dynamic signatures in local networks

The alpha rhythm (8-12Hz) was the first EEG rhythm recorded by Hans Berger in 1929. Despite being the earliest rhythm discovered, alpha rhythms remain the most mysterious in terms of mechanism and function. In the visual system, post-stimulus alpha oscillations are observed upon closing of the eyes or removal of visual stimulus. Alpha rhythms have been implicated in functional inhibition and short term memory. This thesis presents a rat in vitro model of the cortical alpha rhythm. This was achieved by mimicking the neuromodulatory changes that occur upon the removal of visual stimulus. Beta oscillations were induced by excitation of the visual cortex slice using the glutamate agonist kainate [800nM] to mimic sensory stimulation. This excitatory drive was then reduced using the AMPA and KA receptor antagonist NBQX [5µM], followed by the blocking of neuronal Ih current with DK-AH269 [10µM] to produce alpha frequency oscillations.Alpha activity was seen throughout all cortical laminae, with alpha power predominating in layer IV of the V1. The rhythm was found to be criticallydependent upon NMDA receptor-mediated connections between neurons which required the need to be potentiated in the prior excitation phase leading to beta frequency oscillations. Alpha activity was also dependent upon gap junctional coupling and had neuromodulatory effects similar to the human profile of alpha.Alpha oscillations were generated by pyramidal neurons found in layer IV of the V1 which elicited burst discharges. The alpha rhythm was not dominated by synaptic inhibition despite the functional inhibition role it is thought to play. Instead, the alpha rhythm appeared to dynamically uncouple activity in the primary thalamorecipient neurons (layer IV regular spiking cells) from down-stream activity in both supragranular and infragranular layers. In this manner, the alpha rhythm appears to be ideally constructed to prevent ascending visual information from both passing on to higher order visual areas, and also being influenced by top-down signal from these areas

Golden rhythms as a theoretical framework for cross-frequency organization

While brain rhythms appear fundamental to brain function, why brain rhythms consistently organize into the small set of discrete frequency bands observed remains unknown. Here we propose that rhythms separated by factors of the golden ratio ($\phi=(1+ \sqrt{5})/2$) optimally support segregation and cross-frequency integration of information transmission in the brain. Organized by the golden ratio, pairs of transient rhythms support multiplexing by reducing interference between separate communication channels, and triplets of transient rhythms support integration of signals to establish a hierarchy of cross-frequency interactions. We illustrate this framework in simulation and apply this framework to propose four hypotheses.Comment: 8 figure

An investigation into the role of MeCP2 in sleep-related brain rhythms and memory consolidation

Methyl-CpG binding protein 2 (MeCP2) is a chromatin-associated protein which functions in epigenetic gene regulation. Mutations in MeCP2 lead to a variety of neurological disorders, including Rett Syndrome (RTT). Learning and memory deficits are prevalent in RTT, as are sleep disturbances: throughout the night, RTT patients spend less time in Stage 3 non-rapid eye movement (NREM) sleep. Delta oscillations (0.5 – 4 Hz) are the main constituent of Stage 3 NREM sleep, and are thought to be vital for sleep-related memory consolidation. In this thesis, the mechanisms and networks involved in delta oscillation generation were studied in a mouse model of RTT. In isolated sections of somatosensory cortex, loss of MeCP2 function resulted in the disruption of pharmacologically-induced cortical delta oscillations. In contrast, delta oscillations that arise via the thalamic generator remained intact. Pre-symptomatic Mecp2-null animals showed partial preservation of cortical delta oscillations, suggesting that neurological deficits precede phenotype onset. Intracellular current clamp recordings revealed that loss of MeCP2 function impairs the firing pattern of layer V intrinsically bursting pyramidal neurons, the cells responsible for generating the cortical delta rhythm. The bursting mechanism of these cells was restored by reducing the intracellular calcium ion concentration in these cells, which was also sufficient to reinstate the cortical delta rhythm. Finally, delta oscillations, sleep spindles and hippocampal sharp-wave ripples were studied in vivo during NREM sleep, since the coupling of these rhythms is thought to facilitate sleep-related memory consolidation. Rhythm coupling was unaffected by the loss of MeCP2 function, however the incidence of all three rhythms was significantly reduced, resulting in impaired performance on a hippocampus-dependent spatial memory task. The implication of these results on our understanding of the precise role of MeCP2 in coordinating NREM-associated brain rhythms and on the development of learning and memory deficits in RTT are discussed

Clozapine-induced paroxysmal discharges

PhD ThesisThe atypical antipsychotic clozapine is a widely prescribed and effective treatment for the positive and negative symptoms of schizophrenia, but reports of side effects are common. In one study EEG abnormalities were observed in 53% of patients treated with clozapine, and the absence or presence of EEG abnormalities correlated with the plasma clozapine concentration. Here, epileptiform activity was present in conventional EEG recordings from a 32 year old male patient with psychiatric illness taking clozapine for 3 weeks. Brief (ca.100ms), transient epileptiform spikes occurred at a frequency of approximately 2 per h and originated primarily in parietal cortex. One month after withdrawal of clozapine, epileptiform spikes were no longer present. An in vitro model was developed using the equivalent region of association cortex, namely 2⁰ somatosensory cortex, in normal rat brain slices to probe such activity with increased spatial and temporal resolution, and to investigate mechanisms underlying its generation. Wide band in vitro recordings revealed that clozapine (10-20µM) induced regular, frequent very fast oscillations (VFO, > 70Hz) in this region. These VFO comprised short transient high frequency discharges and were maximal in patches along layer V. The atypical antipsychotic olanzapine, but not the classical antipsychotic haloperidol, also induced prominent VFO in this region. Sharp electrode intracellular recordings revealed that there was almost no correlation between the somatic activity of layer V regular spiking (RS) pyramidal cells and field VFO, but layer V intrinsically bursting (IB) cells did correlate to some extent with the local field. Interestingly, IB cell spikelets were also weakly correlated with field VFO suggesting a role for axonal hyperexcitability in this cell type in the mechanism. Clozapine-induced VFO persisted following blockade of AMPA, NMDA, and GABAA chemical synaptic receptors, and the gap junction blockers carbenoxolone and quinine also failed to significantly attenuate the power of this activity. Although octanol abolished clozapine-induced VFO, it was not clear that this effect resulted from blockade of gap junctions as this drug also blocks spikes. In addition to VFO events, clozapine (10-20µM) also induced occasional, spontaneous transient paroxysmal discharges, similar to the EEG phenomena, in 33% (11/33 slices) of slices in vitro. Sharp electrode intracellular recordings revealed that clozapine- induced full paroxysmal discharges were associated with spikes, EPSPs and IPSPs in layer V RS and IB cells, suggesting that these events were mediated via chemical synaptic transmission in both of these cell types. Multi-electrode array recordings of local field potentials and units suggested that clozapine-induced paroxysmal events started superficially in association cortex, moved deeper and then propagated horizontally along these deep layers. The onset of clozapine-induced VFO was accompanied by a significant elevation in parvalbumin immunoreactivity, particularly in layer II-IV, where there was a greater than twofold increase in the signal, and this may be relevant to the therapeutic action of the drug