Publications by authors named "Mitchell R Riley"

Background: There are pushes toward non-invasive stimulation of neural tissues to prevent issues that arise from invasive brain recordings and stimulation. Transcranial Focused Ultrasound (TFUS) has been examined as a way to stimulate non-invasively, but previous studies have limitations in the application of TFUS. As a result, refinement is needed to improve stimulation results.

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Rationale: Deep brain stimulation (DBS) of the hippocampus is proposed for enhancement of memory impaired by injury or disease. Many pre-clinical DBS paradigms can be addressed in epilepsy patients undergoing intracranial monitoring for seizure localization, since they already have electrodes implanted in brain areas of interest. Even though epilepsy is usually not a memory disorder targeted by DBS, the studies can nevertheless model other memory-impacting disorders, such as Traumatic Brain Injury (TBI).

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Training in working memory tasks is associated with lasting changes in prefrontal cortical activity. To assess the neural activity changes induced by training, we recorded single units, multi-unit activity (MUA) and local field potentials (LFP) with chronic electrode arrays implanted in the prefrontal cortex of two monkeys, throughout the period they were trained to perform cognitive tasks. Mastering different task phases was associated with distinct changes in neural activity, which included recruitment of larger numbers of neurons, increases or decreases of their firing rate, changes in the correlation structure between neurons, and redistribution of power across LFP frequency bands.

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The amount of information that can be stored in working memory is limited but may be improved with practice. The basis of improved efficiency at the level of neural activity is unknown. To investigate this question, we trained monkeys to perform a working memory task that required memory for multiple stimuli.

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The functional organization of the primate prefrontal cortex has been a matter of debate with some models speculating dorso-ventral and rostro-caudal specialization while others suggesting that information is represented dynamically by virtue of plasticity across the entire prefrontal cortex. To address functional properties and capacity for plasticity, we recorded from different prefrontal sub-regions and analyzed changes in responses following training in a spatial working memory task. This training induces more pronounced changes in anterior prefrontal regions, including increased firing rate during the delay period, selectivity, reliability, information for stimuli, representation of whether a test stimulus matched the remembered cue or not, and variability and correlation between neurons.

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Working memory capacity, the amount of information that may be maintained in mind over a period of seconds, is extremely limited, to a handful of items. Some evidence exists that the number of visual items that may be maintained in working memory is independent for the two hemifields. To test this idea, we trained monkeys to perform visual working memory tasks that required maintenance in memory of the locations and/or shapes of 3-5 visual stimuli.

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Functional specialization of areas along the anterior-posterior axis of the lateral prefrontal cortex has been speculated but little evidence exists about distinct neurophysiological properties between prefrontal sub-regions. To address this issue we divided the lateral prefrontal cortex into a posterior-dorsal, a mid-dorsal, an anterior-dorsal, a posterior-ventral, and an anterior ventral region. Selectivity for spatial locations, shapes, and colors was evaluated in six monkeys never trained in working memory tasks, while they viewed the stimuli passively.

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The prefrontal cortex is activated during working memory, as evidenced by fMRI results in human studies and neurophysiological recordings in animal models. Persistent activity during the delay period of working memory tasks, after the offset of stimuli that subjects are required to remember, has traditionally been thought of as the neural correlate of working memory. In the last few years several findings have cast doubt on the role of this activity.

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A major factor involved in providing closed loop feedback for control of neural function is to understand how neural ensembles encode online information critical to the final behavioral endpoint. This issue was directly assessed in rats performing a short-term delay memory task in which successful encoding of task information is dependent upon specific spatio-temporal firing patterns recorded from ensembles of CA3 and CA1 hippocampal neurons. Such patterns, extracted by a specially designed nonlinear multi-input multi-output (MIMO) nonlinear mathematical model, were used to predict successful performance online via a closed loop paradigm which regulated trial difficulty (time of retention) as a function of the "strength" of stimulus encoding.

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Collaborative investigations have characterized how multineuron hippocampal ensembles encode memory necessary for subsequent successful performance by rodents in a delayed nonmatch to sample (DNMS) task and utilized that information to provide the basis for a memory prosthesis to enhance performance. By employing a unique nonlinear dynamic multi-input/multi-output (MIMO) model, developed and adapted to hippocampal neural ensemble firing patterns derived from simultaneous recorded CA1 and CA3 activity, it was possible to extract information encoded in the sample phase necessary for successful performance in the nonmatch phase of the task. The extension of this MIMO model to online delivery of electrical stimulation delivered to the same recording loci that mimicked successful CA1 firing patterns, provided the means to increase levels of performance on a trial-by-trial basis.

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