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Kopell, N. J.

Publications and source records attributed to Kopell, N. J..

7 recordsLinked to original sources

Interacting rhythms enhance sensitivity of target detection in a fronto-parietal computational model of visual attention

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and subsequent target detection) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar (mdPul) exhibit different activity and functional connectivity at , {beta}, and{gamma} frequencies--rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP. When driven by{theta} -rhythmic inputs simulating experimentally-observed mdPul activity, this model reproduced the rhythmic dynamics and behavioral consequences of observed attentional states, revealing that the frequencies and mechanisms of the observed rhythms allow for peak sensitivity in visual target detection while maintaining functional flexibility.

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Differential contributions of synaptic and intrinsic inhibitory currents to parsing via flexible phase-locking in neural oscillators

Current hypotheses suggest that speech segmentation - the initial division and grouping of the speech stream into candidate phrases, syllables, and phonemes for further linguistic processing - is executed by a hierarchy of oscillators in auditory cortex. Theta (~3-12 Hz) rhythms play a key role by phase-locking to recurring acoustic features marking syllable boundaries. Reliable synchronization to quasi-rhythmic inputs, whose variable frequency can dip below cortical theta frequencies (down to ~1 Hz), requires "flexible" theta oscillators whose underlying neuronal mechanisms remain unknown. Using biophysical computational models, we found that the flexibility of phase-locking in neural oscillators depended on the types of hyperpolarizing currents that paced them. Simulated cortical theta oscillators flexibly phase-locked to slow inputs when these inputs caused both (i) spiking and (ii) the subsequent buildup of outward current sufficient to delay further spiking until the next input. The greatest flexibility in phase-locking arose from a synergistic interaction between intrinsic currents that was not replicated by synaptic currents at similar timescales. Flexibility in phase-locking enabled improved entrainment to speech input, optimal at mid-vocalic channels, which in turn supported syllabic-timescale segmentation through identification of vocalic nuclei. Our results suggest that synaptic and intrinsic inhibition contribute to frequency-restricted and -flexible phase-locking in neural oscillators, respectively. Their differential deployment may enable neural oscillators to play diverse roles, from reliable internal clocking to adaptive segmentation of quasi-regular sensory inputs like speech. Author summaryOscillatory activity in auditory cortex is believed to play an important role in auditory and speech processing. One suggested function of these rhythms is to divide the speech stream into candidate phonemes, syllables, words, and phrases, to be matched with learned linguistic templates. This requires brain rhythms to flexibly synchronize with regular acoustic features of the speech stream. How neuronal circuits implement this task remains unknown. In this study, we explored the contribution of inhibitory currents to flexible phase-locking in neuronal theta oscillators, believed to perform initial syllabic segmentation. We found that a combination of specific intrinsic inhibitory currents at multiple timescales, present in a large class of cortical neurons, enabled exceptionally flexible phase-locking, which could be used to precisely segment speech by identifying vowels at mid-syllable. This suggests that the cells exhibiting these currents are a key component in the brains auditory and speech processing architecture.

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Flexible reset and entrainment of delta oscillations in primate primary auditory cortex: modeling and experiment

Salient auditory stimuli typically exhibit rhythmic temporal patterns. A growing body of evidence suggests that, in primary auditory cortex (A1), attention is associated with entrainment of delta rhythms (1 - 4 Hz) by these auditory stimuli. It is thought that this entrainment involves phase reset of ongoing spontaneous oscillations in A1 by thalamus matrix afferents, but precise mechanisms are unknown. Furthermore, naturalistic stimuli can vary widely in terms of their rhythmicity: some cycles can be longer than others and frequency can drift over time. It is not clear how the auditory system accommodates this natural variability. We show that in rhesus macaque monkey A1 in vivo, bottom-up gamma (40 Hz) click trains influence ongoing spontaneous delta rhythms by inducing an initial delta-timescale transient response, followed by entrainment to gamma and suppression of delta. We then construct a computational model to reproduce this effect, showing that transient thalamus matrix activation can reset A1 delta oscillations by directly activating deep (layer 5) IB cells, promoting bursting, and beginning a new delta cycle. In contrast, long duration gamma-rhythmic input stimuli induce a steady-state containing entrainment of superficial RS and FS cells at gamma, and suppression of delta oscillations. This suppression is achieved in the model by two complementary pathways. First, long-duration thalamus matrix input causes IB cells to switch from bursting to sparse firing, which disrupts the IB bursts associated with delta. Second, thalamus core input activates deep FS cells (by way of layer 4), which fire at gamma frequency and actively inhibit the delta oscillator. Together, these two fundamental operations of reset and suppression can respectively advance and delay the phase of the delta oscillator, allowing it to follow rhythms exhibiting the type of variability found in the natural environment. We discuss these findings in relation to functional implications for speech processing.\n\nAuthor summaryNeurons organize their firing into synchronous, rhythmic patterns. These neural oscillations have been shown to entrain to rhythmic stimuli in the external world, such as patterns of speech or patterns of movement. By entraining to a particular input stimulus, these oscillations are thought to help us attend to that stimulus and to exclude others. To understand how this synchronization emerges, we constructed a physiologically detailed mathematical model of the primary auditory cortex. By fitting this model to a variety of experimental data, we suggest fundamental mechanisms by which neurons of the auditory cortex can synchronize their activity to rhythmic external stimuli. This result will be useful for understanding the mechanism and limitations of oscillatory entrainment, which are thought to underlie the processing of naturalistic auditory inputs like speech or music. Furthermore, this model, though simplified, was shown to generalize and reproduce a wide range of experimental results, and can thus be used as a starting point for building more complex models of auditory cortex.

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A biophysical model of striatal microcircuits suggests theta-rhythmically interleaved gamma and beta oscillations mediate periodicity in motor control

Striatal oscillatory activity is associated with movement, reward, and decision-making, and observed in several interacting frequency bands. Local field potential recordings in rodent striatum show dopamine- and reward-dependent transitions between two states: a "spontaneous" state involving {beta} (~15-30 Hz) and low{gamma} (~40-60 Hz), and a state involving{theta} (~4-8 Hz) and high{gamma} (~60-100 Hz) in response to dopaminergic agonism and reward. The mechanisms underlying these rhythmic dynamics, their interactions, and their functional consequences are not well understood. In this paper, we propose a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of these rhythms, as well as their modulation by dopamine. Building on previous modeling and experimental work suggesting that striatal projection neurons (SPNs) are capable of generating {beta} oscillations, we show that networks of striatal fast-spiking interneurons (FSIs) are capable of generating{delta} /{theta} (ie, 2 to 6 Hz) and{gamma} rhythms. Under simulated low dopaminergic tone our model FSI network produces low{gamma} band oscillations, while under high dopaminergic tone the FSI network produces high{gamma} band activity nested within a{delta} /{theta} oscillation. SPN networks produce {beta} rhythms in both conditions, but under high dopaminergic tone, this {beta} oscillation is interrupted by{delta} /{theta}-periodic bursts of{gamma} -frequency FSI inhibition. Thus, in the high dopamine state, packets of FSI{gamma} and SPN {beta} alternate at a{delta} /{theta} timescale. In addition to a mechanistic explanation for previously observed rhythmic interactions and transitions, our model suggests a hypothesis as to how the relationship between dopamine and rhythmicity impacts motor function. We hypothesize that high dopamine-induced periodic FSI{gamma} -rhythmic inhibition enables switching between {beta}-rhythmic SPN cell assemblies representing the currently active motor program, and thus that dopamine facilitates movement in part by allowing for rapid, periodic shifts in motor program execution. Author summaryStriatal oscillatory activity is associated with movement, reward, and decision-making, and observed in several interacting frequency bands. The mechanisms underlying these rhythmic dynamics, their interactions, and their functional consequences are not well understood. In this paper, we propose a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of striatal rhythms, as well as their modulation by dopamine. Our model suggests a hypothesis as to how the relationship between dopamine and rhythmicity impacts the function of the motor system, enabling rapid, periodic shifts in motor program execution.

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Prefrontal oscillations modulate the propagation of neuronal activity required for working memory

Cognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream effectors that carry out the response. In this work, we used biophysically-detailed modeling to explore the hypothesis that network oscillations in prefrontal cortex (PFC), leveraging local inhibition, can independently gate responses to items in WM. The key role of local inhibition was to control the period between spike bursts in the outputs, and to produce an oscillatory response no matter whether the WM item was maintained in an asynchronous or oscillatory state. We found that the WM item that induced an oscillatory population response in the PFC output layer with the shortest period between spike bursts was most reliably propagated. The network resonant frequency (i.e., the input frequency that produces the largest response) of the output layer can be flexibly tuned by varying the excitability of deep layer principal cells. Our model suggests that experimentally-observed modulation of PFC beta-frequency (15-30 Hz) and gamma-frequency (30-80 Hz) oscillations could leverage network resonance and local inhibition to govern the flexible routing of signals in service to cognitive processes like gating outputs from working memory and the selection of rule-based actions. Importantly, we show for the first time that nonspecific changes in deep layer excitability can tune the output gates resonant frequency, enabling the specific selection of signals encoded by populations in asynchronous or fast oscillatory states. More generally, this represents a dynamic mechanism by which adjusting network excitability can govern the propagation of asynchronous and oscillatory signals throughout neocortex.

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Flexible resonance in prefrontal networks with strong feedback inhibition

Oscillations are ubiquitous features of brain dynamics that undergo task-related changes in synchrony, power, and frequency. The impact of those changes on target networks is poorly understood. In this work, we used a biophysically detailed model of prefrontal cortex (PFC) to explore the effects of varying the spike rate, synchrony, and waveform of strong oscillatory inputs on the behavior of cortical networks driven by them. Interacting populations of excitatory and inhibitory neurons with strong feedback inhibition are inhibition-based network oscillators that exhibit resonance (i.e., larger responses to preferred input frequencies). We quantified network responses in terms of mean firing rates and the population frequency of network oscillation; and characterized their behavior in terms of the natural response to asynchronous input and the resonant response to oscillatory inputs. We show that strong feedback inhibition causes the PFC to generate internal (natural) oscillations in the beta/gamma frequency range (>15 Hz) and to maximize principal cell spiking in response to external oscillations at slightly higher frequencies. Importantly, we found that the fastest oscillation frequency that can be relayed by the network maximizes local inhibition and is equal to a frequency even higher than that which maximizes the firing rate of excitatory cells; we call this phenomenon population frequency resonance. This form of resonance is shown to determine the optimal driving frequency for suppressing responses to asynchronous activity. Lastly, we demonstrate that the natural and resonant frequencies can be tuned by changes in neuronal excitability, the duration of feedback inhibition, and dynamic properties of the input. Our results predict that PFC networks are tuned for generating and selectively responding to beta- and gamma-rhythmic signals due to the natural and resonant properties of inhibition-based oscillators. They also suggest strategies for optimizing transcranial stimulation and using oscillatory networks in neuromorphic engineering.\n\nAuthor SummaryThe prefrontal cortex (PFC) flexibly encodes task-relevant representations and outputs biases to mediate higher cognitive functions. The relevant neural ensembles undergo task-related changes in oscillatory dynamics at beta- and gamma frequencies. Using a computational model of the PFC network, we show that strong feedback inhibition causes the PFC to generate internal oscillations and to prefer external oscillations at similar frequencies. The precise frequencies that are generated and preferred can be flexibly tuned by varying the synchrony and strength of input network activity, the level of background excitation, and neuromodulation of intrinsic ion currents. We also show that the peak output frequency in response to external oscillations, which depends on the synchrony and strength of the input as well as the strong inhibitory feedback, is faster than the internally generated frequency, and that this difference enables exclusive response to oscillatory inputs. These properties enable changes in oscillatory dynamics to govern the selective processing and gating of task-relevant signals in service of cognitive control.

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Striatal cholinergic receptor activation causes a rapid, selective, & state-dependent rise in corticostriatal β activity.

Cortico-basal ganglia-thalamic (CBT) {beta} oscillations (15-30 Hz) are elevated in Parkinsons disease and correlated with movement disability. To date, no experimental paradigm outside of loss of dopamine has been able to specifically elevate {beta} oscillations in the CBT loop. Here, we show that activation of striatal cholinergic receptors selectively increased {beta} oscillations in mouse striatum and motor cortex. In individuals showing simultaneous {beta} increases in both striatum and M1, {beta} partial directed coherence (PDC) increased from striatum to M1 (but not in the reverse direction). In individuals that did not show simultaneous {beta} increases, {beta} PDC increased from M1 to striatum (but not in the reverse direction), and M1 was characterized by persistent {beta}-HFO phase-amplitude coupling. Finally, the direction of {beta} PDC distinguished between {beta} subbands. This suggests: (1) striatal cholinergic tone exerts state-dependent and frequency-selective control over CBT {beta} power and coordination; (2) ongoing rhythmic dynamics can determine whether elevated {beta} oscillations are expressed in striatum and M1; (3) altered striatal cholinergic tone differentially modulates distinct {beta} subbands.

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