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Rosenow, J. M.

Publications and source records attributed to Rosenow, J. M..

11 recordsLinked to original sources

Differential roles of frontoparietal regions in working memory and decision-making

Working memory (WM) and decision-making (DM) are closely linked cognitive processes that rely on frontoparietal regions, yet their distinct and shared neural dynamics remain unclear. Using intracranial EEG recordings from 24 human subjects performing a delayed match-to-sample task, we examined high-frequency broadband (HFB) activity to dissociate WM- and DM-related processes with high spatiotemporal resolution. Principal component analysis of frontoparietal HFB activity revealed multiple temporally distinct patterns spanning stimulus presentation and delay phases. The most dominant component reflected sustained WM-related activity across task phases, consistent with persistent maintenance of internal representations. Additional components captured transient WM encoding across trial phases, as well as both stimulus-linked and ramping DM-related activity suggesting dual early and late stages of evaluative processing. These processes were distributed across frontoparietal regions but showed systematic differences in anatomical focus, with WM-related activity concentrated in dorsolateral prefrontal cortex (PFC) and DM-related activity concentrated in ventrolateral PFC, while inferior parietal cortex preferentially tracked the behavioral significance of incoming stimuli and superior parietal cortex tracked the appearance of new information that may require updating ongoing processing. Together, these findings demonstrate that WM and DM processes are separable yet interleaved over time within distributed cortical networks, revealing coordinated but functionally distinct contributions to goal-directed behavior.

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Cycle-by-cycle respiration waveforms are coupled with the shape of neural oscillations

Beyond sustaining life, breathing is a vital physiological rhythm that shapes cognition, perception, emotional regulation, and mental health. Breathing has a direct effect on neuronal excitability and is coupled to neural oscillations across a variety of brain regions. Notably, both respiration and neural oscillations are asymmetric and not perfectly rhythmic: for example, every breath has a different shape and duration, and is interspersed with variable pauses. Here, we examined the coupling between breathing and the brain by quantifying the nonsinusoidal features of each breath and comparing it to the shape of each corresponding neural oscillation cycle. By leveraging invasive human brain recordings from 16 participants, we found respiration-neural waveform coupling on a breath-by-breath, cycle-by-cycle basis across limbic and cortical forebrain regions. For decades, the dominant perspective on cognition and mental health have focused on the brain, but recent work is highlighting the importance of brain-body interactions. Our results show that the coupling between breathing and neural activity is much richer than previously appreciated, and our approach opens new avenues for studying these peripheral-to-central nervous system interactions in a more robust, temporally precise manner.

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Distributed theta networks support the control of working memory: Evidence from scalp and intracranial EEG

We combined scalp EEG and intracranial EEG (iEEG) to identify spectral and network-level signatures of executive control during a delayed match-to-sample task working memory task. To isolate executive processes, we contrasted test and sample phases, matched in perceptual input but differing in cognitive demand. Scalp EEG revealed increased frontal midline theta event-related spectral perturbations (ERSPs), dynamic increases and decreases in posterior theta-alpha ERSPs, and decreased central alpha-beta ERSPs during the test phase. These local spectral changes were accompanied by enhanced frontoposterior theta phase synchrony and network hub strength, predicting higher behavioral accuracy. Using a novel cross-modal scalp EEG-iEEG ERSP similarity approach, we localized the sources of scalp-derived frontal midline, posterior, and central control effects to medial frontal, parietal, temporal, and occipital regions. Our results integrate power and connectivity measures across scalp and iEEG, linking local spectral fluctuations to broader network organization. Together, they support a model in which executive control emerges from flexible, temporally precise coordination between medial frontal control hubs and posterior representational systems.

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Declarative Memory Through the Lens of Single-Trial Peaks in High-Frequency Power

Declarative memory depends on the coordination of local processing, indexed by high-frequency broadband (HFB) activity, with global network organization, indexed by theta oscillations. However, theta and HFB exhibit asynchronous timing, raising the question of how results of local processing are communicated throughout the network. Using intracranial EEG in patients performing a recognition memory task, we examined this coordination across the medial temporal lobe (MTL) and prefrontal cortex (PFC). HFB peak activity was earlier in the MTL than PFC. Anchoring analyses of theta phase clustering and connectivity to HFB peaks revealed strong phase clustering locked to HFB peaks in the PFC, as well as connectivity between the PFC and MTL that predicted individual memory performance. Graph analysis revealed specific connections amidst sparse network connectivity during memory success. This study demonstrates that transient brain states linked to internal physiological events support memory and refines our understanding of local and network-level process interactions. HighlightsO_LIMemory-linked theta activity is time-locked to internal brain events C_LIO_LINetwork connectivity changes dynamically during memory processing C_LIO_LISparse network connectivity supports successful memory C_LIO_LISpecific sequences of transient states may be critical for declarative memory C_LI

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The development of aperiodic neural activity in the human brain

The neurophysiological mechanisms supporting brain maturation are fundamental to attention and memory capacity across the lifespan. Human brain regions develop at different rates, with many regions developing into the third and fourth decades of life. Here, in this preregistered study (https://osf.io/gsru7), we analyzed intracranial EEG (iEEG) recordings from widespread brain regions in a large developmental cohort. Using task-based (i.e., attention to-be-remembered visual stimuli) and task-free (resting-state) data from 101 children and adults (5.93 - 54.00 years, 63 males; n electrodes = 5691), we mapped aperiodic (1/[f]-like) activity, a proxy of neural noise, with steeper slopes indexing less noise and flatter slopes indexing more noise. We reveal that aperiodic slopes flatten with age into young adulthood in both association and sensorimotor cortices, challenging models of early sensorimotor development based on brain structure. In prefrontal cortex (PFC), attentional state modulated age effects, revealing steeper task-based than task-free slopes in adults and the opposite in children, consistent with the development of cognitive control. Age-related differences in task-based slopes also explained age-related gains in memory performance, linking the development of PFC cognitive control to the development of memory. Last, with additional structural imaging measures, we reveal that age-related differences in gray matter volume are similarly associated with aperiodic slopes in association and sensorimotor cortices. Our findings establish developmental trajectories of aperiodic activity in localized brain regions and illuminate the development of PFC control during adolescence in the development of attention and memory.

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High-gamma activity is coupled to low-gamma oscillations in precentral cortices and modulates with movement and speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger movements or speaking words aloud. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

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Sensory computations in the cuneate nucleus of macaques

AO_SCPLOWBSTRACTC_SCPLOWTactile nerve fibers fall into a few classes that can be readily distinguished based on their spatiotemporal response properties. Because nerve fibers reflect local skin deformations, they individually carry ambiguous signals about object features. In contrast, cortical neurons exhibit heterogeneous response properties that reflect computations applied to convergent input from multiple classes of afferents, which confer to them a selectivity for behaviorally relevant features of objects. The conventional view is that these complex response properties arise within the cortex itself, implying that sensory signals are not processed to any significant extent in the two intervening structures - the cuneate nucleus (CN) and the thalamus. To test this hypothesis, we recorded the responses evoked in CN to a battery of stimuli that have been extensively used to characterize tactile coding in both the periphery and cortex, including skin indentations, vibrations, random dot patterns, and scanned edges. We found that CN responses are more similar to their cortical counterparts than they are to their inputs: CN neurons receive input from multiple classes of nerve fibers, they have spatially complex receptive fields, and they exhibit selectivity for object features. Contrary to consensus, then, CN plays a key role in processing tactile information. SO_SCPLOWIGNIFICANCEC_SCPLOWPerception is the outcome of the sequential processing of sensory signals at multiple stages along the neuraxis. The conventional view is that tactile signals are processed predominantly in the cerebral cortex. We tested this view by investigating the response properties of neurons in the cuneate nucleus (CN), the first potential stage of processing along the primary touch neuraxis. We found that CN responses more nearly resemble those of cortical neurons than they do those of nerve fibers: CN neurons have spatially complex receptive fields reflecting convergent input from multiple classes of nerve fibers and exhibit a selectivity for object features, absent in the nerve. We conclude that CN plays a key, early role in the processing of tactile information.

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ENCODING OF LIMB STATE BY SINGLE NEURONS IN THE CUNEATE NUCLEUS OF AWAKE MONKEYS

The cuneate nucleus (CN) is among the first sites along the neuraxis where proprioceptive signals can be integrated, transformed, and modulated. The objective of the study was to characterize the proprioceptive representations in CN. To this end, we recorded from single CN neurons in three monkeys during active reaching and passive limb perturbation. We found that many neurons exhibited responses that were tuned approximately sinusoidally to limb movement direction, as has been found for other sensorimotor neurons. The distribution of their preferred directions (PDs) was highly non-uniform and resembled that of muscle spindles within individual muscles, suggesting that CN neurons typically receive inputs from only a single muscle. We also found that the responses of proprioceptive CN neurons tended to be modestly amplified during active reaching movements compared to passive limb perturbations, in contrast to cutaneous CN neurons whose responses were not systematically different in the active and passive conditions. Somatosensory signals thus seem to be subject to a "spotlighting" of relevant sensory information rather than uniform suppression as has been suggested previously.

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Rapid coordination of effective learning by the human hippocampus

Although the human hippocampus is necessary for long-term memory, controversial findings suggest that hippocampal computations support short-term memory in the service of guiding effective behaviors during learning. We tested the counterintuitive theory that the hippocampus contributes to long-term memory through remarkably short-term processing, as reflected in the sequence of eye movements during encoding of naturalistic scenes. While viewing scenes for the first time, participants generated patterns of eye movements that reflected a shift from stimulus-driven to memory-driven viewing and signaled effective spatiotemporal memory formation. Hippocampal theta oscillations recorded from depth electrodes predicted this viewing pattern. Moreover, effective viewing patterns were preceded by shifts towards top-down influence of hippocampal theta on activity within cortical networks that support visual perception and visuospatial attention. The hippocampus thus supports short-term memory processing that coordinates perception, attention, and behavior in the service of effective spatiotemporal learning. These findings motivate re-interpretation of long-term memory disorders as reflecting loss of the organizing influence of hippocampal short-term memory on learning.

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Distinct representations of finger movement and force in human motor and premotor cortices

The ability to grasp and manipulate objects requires controlling both finger movement kinematics and isometric force. Previous work suggests that these behavioral modes are controlled separately, but it is unknown whether the cerebral cortex represents them differently. Here, we investigated this question by recording high-density electrocorticography from the motor and premotor cortices of seven human subjects performing a sequential movement-force motor task. We decoded finger movement (0.7{+/-}0.3 fractional variance account for; FVAF) and force (0.7{+/-}0.2 FVAF) with high accuracy, yet found different spatial representations. We also found clear distinctions in electrocorticographic activity by using deep learning methods to uncover state-space representations, and by developing a new metric, the neural vector angle. Thus, state-space techniques can help to investigate broad cortical networks. Finally, we were able to classify the behavioral mode from neural signals with high accuracy (90{+/-}6%). Thus, finger movement and force have distinct representations in motor/premotor cortices. This will inform our understanding of the neural control of movement as well as the design of grasp brain-machine interfaces.

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Hippocampal theta coordinates memory processing during visual exploration

The hippocampus supports memory encoding and retrieval, with distinct phases of theta oscillations modulating the amplitude of gamma-band activity during each process. Encoding and retrieval operations dynamically interact over rapid timescales, especially when sensory information conflicts with memory. The ability to link hippocampal dynamics to specific memory-guided behaviors has been limited by experiments that lack the temporal resolution to segregate when encoding and retrieval occur. To resolve this issue, we simultaneously tracked eye movements and hippocampal field potentials while neurosurgical patients performed a spatial memory task. Novelty-driven fixations increased phase-locking to the theta rhythm, which predicted successful memory performance. Theta to gamma phase amplitude coupling increased during these viewing behaviors and predicted forgetting of conflicting memories. In contrast, theta phase-locking preceded fixations initiated by memory retrieval, indicating that the hippocampus coordinates memory-guided eye movements. These findings suggest that theta oscillations in the hippocampus support learning through two interleaved processes: strengthening the encoding of novel information and guiding exploration based on prior experience.

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