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Biology subjects

Adams, W. R.

Publications and source records attributed to Adams, W. R..

4 recordsLinked to original sources

Recurrent activity within microcircuits of macaque dorsolateral prefrontal cortex tracks cognitive flexibility

Human and non-human primate data clearly implicate the dorsolateral prefrontal cortex (dlPFC) as critical for advanced cognitive functions1,2. It is thought that intracortical synaptic architectures within dlPFC are the integral neurobiological substrate that gives rise to these processes, including working memory, inferential reasoning, and decision-making3-7. In the prevailing model, each cortical column makes up one fundamental processing unit composed of dense intrinsic connectivity, conceptualized as the canonical cortical microcircuit3,8. Each cortical microcircuit receives sensory and cognitive information from a variety of sources which are represented by sustained activity within the microcircuit, referred to as persistent or recurrent activity4,9. Via recurrent connections within the microcircuit, activity can propagate for a variable length of time, thereby allowing temporary storage and computations to occur locally before ultimately passing a transformed representation to a downstream output4,5,10. Competing theories regarding how microcircuit activity is coordinated have proven difficult to reconcile in vivo where intercortical and intracortical computations cannot be fully dissociated5,9,11,12. Here, we interrogated the intrinsic features of isolated microcircuit networks using high-density calcium imaging of macaque dlPFC ex vivo. We found that spontaneous activity is intrinsically maintained by microcircuit architecture, persisting at a high rate in the absence of extrinsic connections. Further, using perisulcal stimulation to evoke persistent activity in deep layers, we found that activity propagates through stochastically assembled intracortical networks, creating predictable population-level events from largely non-overlapping ensembles. Microcircuit excitability covaried with individual cognitive performance, thus anchoring heuristic models of abstract cortical functions within quantifiable constraints imposed by the underlying synaptic architecture.

neuroscience↗

Visualizing the Role of Lipid Dynamics during Infrared Neural Stimulation with Hyperspectral Stimulated Raman Scattering Microscopy

Infrared neural stimulation, or INS, is a method of using pulsed infrared light to yield label-free neural stimulation with broad experimental and translational utility. Despite its robust demonstration, the mechanistic and biophysical underpinnings of INS have been the subject of debate for more than a decade. The role of lipid membrane thermodynamics appears to play an important role in how fast IR-mediated heating nonspecifically drives action potential generation. Direct observation of lipid membrane dynamics during INS remains to be shown in a live neural model system. To directly test the involvement of lipid dynamics in INS, we used hyperspectral stimulated Raman scattering (hsSRS) microscopy to study biochemical signatures of high-speed vibrational dynamics underlying INS in a live neural cell culture model. Findings suggest that lipid bilayer structural changes are occurring during INS in vitro in NG108-15 neuroglioma cells. Lipid-specific signatures of cell SRS spectra were found to vary with stimulation energy and radiant exposure. Spectroscopic observations were verified against high-speed ratiometric fluorescence imaging of a conventional lipophilic membrane structure reporter, di-4-ANNEPS. Overall, the presented data supports the hypothesis that INS causes changes in the lipid membrane of neural cells by changing lipid membrane packing order - which coincides with likelihood of cell stimulation. Furthermore, this work highlights the potential of hsSRS as a method to study biophysical and biochemical dynamics safely in live cells.

biophysics↗

Multimodal Nonlinear Optical and Thermal Imaging Platform for Label-Free Characterization of Biological Tissue

The ability to characterize the combined structural, functional, and thermal properties of biophysically dynamic samples is needed to address critical questions related to tissue structure, physiological dynamics, and disease progression. Towards this, we have developed an imaging platform that enables multiple nonlinear imaging modalities to be combined with thermal imaging on a common sample. Here we demonstrate label-free multimodal imaging of live cells, excised tissues, and live rodent brain models. While potential applications of this technology are wide-ranging, we expect it to be especially useful in addressing biomedical research questions aimed at the biomolecular and biophysical properties of tissue and their physiology.

biophysics↗

The detection of hand tremor through the characteristics of finger movement while typing

Parkinsons Disease (PD) is a neurodegenerative movement disease affecting over 6 million people worldwide. Current diagnosis is based on clinical and observational criteria only, resulting in a high misdiagnosis rate. Approximately 75% of people with PD have hand tremor, which can precede clinical diagnosis by up to 6 years. Previous studies have shown that early PD can be accurately detected from keystroke features while typing, and this study investigated whether tremor can be detected as well. Typing data from 76 subjects, with and without PD, including 27 with PD and 15 with tremor, was analysed and showed that hand tremor in PD can be detected from keystroke features. This novel technique has not been used before and was able to achieve an overall sensitivity of 67% and a specificity of 80% and was also able to differentiate PD tremor from essential tremor. This means that the diagnosis of early PD through typing can achieve the clinical requirement of at least two cardinal features being present (bradykinesia and tremor). Less than half a page of typing is needed, the technique does not require any specialised equipment, and can take place in the patients home as they type normally on a computer.

neuroscience↗