Biology subjects

Kennedy, J. P.

Publications and source records attributed to Kennedy, J. P..

6 recordsLinked to original sources

bioRxiv2021

Genetically-based adaptive trait shifts at an expanding mangrove range margin

O_LIMany species are expanding beyond their distributional range margins in response to a warming planet. Due to marginal environmental conditions and novel selection pressures, range margins may foster unique genetic adaptations that can better enable species to thrive under the extreme climatic conditions at and beyond their current distributional limits. Neotropical black mangrove (Avicennia germinans) is expanding poleward into temperate salt marsh along Atlantic Florida, USA, with field evidence of adaptive trait shifts within range-margin A. germinans populations. However, whether these adaptive shifts have a genetic basis remains to be answered. C_LIO_LIWe monitored twenty A. germinans maternal cohorts from areas in both the Atlantic Florida range core and margin in a greenhouse common garden with annual temperatures analogous to range-margin conditions. We measured variation in a series of phenotypic traits starting at initial planting of field-collected propagules and continuing until two years development. C_LIO_LIMaternal cohorts from the Atlantic Florida range margin consistently outperformed those from the range core throughout the experiment. Range-margin cohorts survived in greater numbers, established faster, and were less stressed under winter chilling and sub-zero temperatures that are often reached at the Atlantic range margin, but not within the range core. Range-margin cohorts did not grow taller, but instead invested more into lateral growth and biomass accumulation that presumably reflects adaptation to their colder and open canopy environment. Range-margin cohorts also exhibited leaf traits consistent with greater resource acquisition that may compensate for a shorter growing season and reduced light quality at higher latitude. C_LIO_LISynthesis. We confirmed that there is a genetic basis to adaptive trait shifts towards an expanding mangrove range margin. Our results suggest that genetically-based phenotypic differences better enable these range-margin mangroves to thrive within their stressful environment and may facilitate further poleward expansion in the future. In addition, our documentation of adaptive trait variation among maternal cohorts of an ecologically-important mangrove foundation species, quantitative data that is lacking for mangroves, should help inform mangrove restoration initiatives. C_LI

ecology↗

bioRxiv2020

Spectrum Degradation of Hippocampal LFP during Euthanasia

AO_SCPLOWBSTRACTC_SCPLOWThe hippocampal local field potential (LFP) exhibits a strong correlation with behavior. During rest, the theta rhythm is not prominent, but during active behavior, there are strong rhythms in the theta, theta harmonics, and gamma ranges. With increasing running velocity, theta, theta harmonics and gamma increase in power and in cross-frequency coupling, suggesting that neural entrainment is a direct consequence of the total excitatory input. While it is common to study the parametric range between the LFP and its complementing power spectra between deep rest and epochs of high running velocity, it is also possible to explore how the spectra degrades as the energy is completely quenched from the system. Specifically, it is unknown whether the 1/f slope is preserved as synaptic activity becomes diminished, as low frequencies are generated by large pools of neurons while higher frequencies comprise the activity of more local neuronal populations. To test this hypothesis, we examined rat LFPs recorded from the hippocampus and entorhinal cortex during barbiturate overdose euthanasia. Within the hippocampus, the initial stage entailed a quasi-stationary stage when the LFP spectrum exhibited power-law feature while the frequency components over 20 Hz exhibited a power decay with a similar decay rate. This stage was followed by a rapid collapse of power spectrum towards the absolute electrothermal noise background. As the collapse of activity occurred later in hippocampus compared with medial entorhinal cortex or visual cortex, it suggests that the ability of a neural network to maintain the 1/f slope with decreasing energy is a function of general connectivity. Broadly, these data support the energy cascade theory where there is a cascade of energy from large cortical populations into smaller loops, such as those that supports the higher frequency gamma rhythm. As energy is pulled from the system, neural entrainment at gamma frequency (and higher) decline first. The larger loops, comprising a larger population, are fault-tolerant to a point capable of maintaining their activity before a final collapse.

neuroscience↗

bioRxiv2018

TURBULENCE IN THE HIPPOCAMPUS: AN ANSATZ FOR THE ENERGY CASCADEHYPOTHESIS

Mesoscopic neural activity may play an important role in the cross-scale integration of brain activity and in the emergence of cognitive behavior. Mesoscale activity in the cortex can be defined as the organization of activity of large populations of neurons into collective actions, such as traveling waves in the hippocampus. A comprehensive description of collective activity is still lacking, in part because it cannot be built directly with methods and models developed for the microscale (individual neurons): the laws governing mesoscale dynamics are different from those governing a few neurons. To identify the characteristic features of mesoscopic dynamics, and to lay the foundations for a theoretical description of mesoscopic activity in the hippocampus, we conduct a comprehensive examination of observational data of hippocampal local field potential (LFP) recordings. We use the strong correlation between rat running-speed and the LFP power to parameterize the energy input into the hippocampus, and show that both the power, and the nonlinearity of mesoscopic scales of collective action (e.g., theta and gamma rhythms) increase as with energy input. Our results point to a few fundamental characteristics: collective-action dynamics are stochastic (the precise state of a single neuron is irrelevant), weakly nonlinear, and weakly dissipative. These are the principles of the theory of weak turbulence. Therefore, we propose weak turbulence as an ansatz for the development of a theoretical description of mesoscopic activity. The perspective of weak turbulence provides simple and meaningful explanations for the major features observed in the evolution of LFP spectra and bispectra with energy input, such as spectral slopes and their evolution, the increased nonlinear coupling observed between theta and gamma, as well as specific phase lags associated with their interaction. The weak turbulence ansatz is consistent with the theory of self organized criticality, which provides a simple explanation for the existence of the power-law background spectrum, and could provide a unifying approach to modeling the dynamics of mesoscopic activity.

neuroscience↗

bioRxiv2018

LINEAR ANALYSIS OF HIPPOCAMPAL LFP: SLOW GAMMA VS HIGH THETA

AO_SCPCAPBSTRACTC_SCPCAPLocal field potential (LFP) oscillations are the superposition of excitatory/inhibitory postsynaptic potentials. In the hippocampus, the 20-55 Hz range ( slow gamma) is proposed to support cognition independent of other frequencies. However, this band overlaps with theta harmonics. We aimed to dissociate the generators of slow gamma versus theta harmonics with current source density and different LFP decompositions. Hippocampal theta harmonic and slow gamma generators were not dissociable. Moreover, comparison of wavelet, ensemble empirical-mode (EEMD), and Fourier decompositions produced distinct outcomes with wavelet and EEMD failing to resolve high-order theta harmonics well defined by Fourier analysis. The varying sizes of the time-frequency atoms used by wavelet distributed the higher-order harmonics over a broader range giving the impression of a low frequency burst (\"slow gamma\"). The absence of detectable slow gamma refutes a multiplexed model of cognition in favor of the energy cascade hypothesis in which dependency across oscillatory frequencies exists.

neuroscience↗

bioRxiv2018

Theta-gamma coupling: a nonlinear dynamical model

Cross-frequency coupling in the hippocampus has been hypothesized to support higher-cognition functions. While gamma modulation by theta is widely accepted, evidence of phase-coupling between the two frequency components is so far unconvincing. Our observations show that theta and gamma energy increases with rat speed, while the overall nonlinearity of the LFP trace also increases, suggesting that energy flow is fundamental for hippocampal dynamics. This contradicts current representations based on the Kuramoto phase model. Therefore, we propose a new approach, based on the three-wave equation, a universally-valid nonlinear-physics paradigm that synthesizes the effects of leading order, quadratic nonlinearity. The paradigm identifies bispectral analysis as the natural tool for investigating LFP cross-frequency coupling. Our results confirm the effectiveness of the approach by showing unambiguous coupling between theta and gamma. Bispectra features agree with predictions of the three-wave model, supporting the conclusion that cross-frequency coupling is a manifestation of nonlinear energy transfers.

neuroscience↗

bioRxiv2017

Mesoscale turbulence in the hippocampus

Wave turbulence provides a powerful stochastic description for nonlinear collective neural activity in the hippocampus. Recent studies that show theta waves propagating across the hippocampus suggest that turbulence is a natural description for collective neural activity. We formulate the fundamental principles of a turbulence model and demonstrate turbulent behavior by analyzing rat hippocampal LFP traces. LFP spectra and bispectra exhibit fundamental turbulent properties: weak nonlinear coupling, energy cascade, and stationary spectra of the Kolmogorov-Zakharov type (power-law). Weak turbulence holds the promise of quantitative physical models of hippocampal dynamics, in the service of understanding the mechanisms of multi-scale integration of brain activity to cognition.

neuroscience↗