Biology subjects

Shofty, B.

Publications and source records attributed to Shofty, B..

16 recordsLinked to original sources

bioRxiv2026

Low-dimensional factorized neural computations underlie risk-adaptive choices

Real-world decision-making rarely occurs with perfect information. Instead, individuals must constantly weigh potential rewards against the probability of adverse outcomes.1 Failures of this process can lead to maladaptive decisions associated with reduced lifetime success, and numerous psychiatric disorders such as gambling addictions, bulimia nervosa, and substance use disorder.2,3 The neural computations that facilitate inference about the landscape of potential outcomes remain unclear, but are thought to occur in distributed frontotemporal circuits.4 Here we used deep reinforcement learning agents to predict distinct behavioral strategies and their underlying neural population dynamics during a risky decision-making task. Across a range of training conditions, deep reinforcement learning agents separated into strategies marked by either overly cautious exploration of the reward contingency space or a high-performing, risk-adaptive Bimodal strategy. The internal dynamics of high-performing Bimodal agents formed low-dimensional representations that segregated safe and risky states. In contrast, the cautious exploration agents were associated with more skewed and entangled neural representations. We found remarkably similar dynamical representations and their associated behavioral strategies in neuronal ensemble recordings from human epilepsy patients performing a similar risky decision-making task. These results reveal the structure of dynamical computations that underlie inferences about uncertain outcomes and their associated behavioral strategies.

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bioRxiv2026

Temporal Processing during Decision Making under Uncertainty.

Time perception and decision-making are interrelated processes that are critical to much of human and animal behavior. Although the behavioral importance of this link between the processes has been established, the neural underpinnings of temporal decision-making are unclear. The current study leverages human intracranial electro-physiology to investigate the neural contribution of temporal processing to decision-making under risk. To probe temporal decision-making, we use a version of the Balloon Analogue Risk Task, in which participants inflate virtual balloons with the goal of reaching maximal balloon size but stopping inflation before the balloon pops. Points are awarded based on inflation duration of successful trials, such that points awarded are linearly related to balloon size. By decoding temporal features of the task on a trial-by-trial basis, we find neural representations of time during balloon inflation. Specifically, we find that both medial and lateral temporal regions of the brain encode the majority of this time-related signal. Importantly, we can decode the progression of time leading up to the outcome of a successful decision (pressing a button to stop inflation before the balloon pops). This encoding of time depends on an active decision to end the trial: we cannot decode time during passive observation of balloon inflation to a known maximal size. To validate these results further, we use a temporal convolution network to predict participants response (i.e., time of button press) based on the brain activity leading up to the response. We find that we can predict the moment of response with high accuracy and temporal resolution. The model predicts the timing of successful decisions but not the timing of balloon pops. Together, these findings reveal neural representations that encode the progression of time, specifically in relation to an active decision.

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bioRxiv2026

Polysemanticity in human hippocampal neurons

To comprehend language, the brain must navigate a high-dimensional semantic landscape while seamlessly contextualizing meaning. Inspired by recent advances in the mechanistic interpretability of large language models (LLMs), we hypothesized that the brain utilizes polysemanticity, a coding strategy wherein individual neurons represent multiple semantically unrelated features through high-dimensional superposition (Elhage et al., 2022; Olah et al., 2020). We recorded single-unit activity from the human hippocampus during podcast listening. We found that hippocampal neurons exhibit dense semantic codes characterized by multiple tuning peaks with an overdispersed, isotropic geometry. This geometry satisfies the theoretical requirements for interference minimization in superimposed codes. Furthermore, semantic responses are strongly modulated by lexical and speaker-identity context; nonetheless, the underlying population geometry remains stable. This coding strategy permits rapid contextualization without requiring specialized, context-specific neurons. Indeed, we show clear pattern separation of similar terms, along with pattern completion for held-out words. Together, these results demonstrate that the human brain leverages superposition to solve a universal computational problem: maximizing semantic capacity within a constrained representational space.

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bioRxiv2026

Asymmetric Reinforcement Learning Explains Human Choice Patterns in Decision-making Under Risk

Human decisions under uncertainty are shaped by experience, but the computations that translate expectation and experience into choice remain debated in neural and cognitive science. Prior studies highlight reinforcement learning (RL) as a unifying framework, yet it is unclear whether human behavior under risk is better captured by symmetric updating from outcomes or by asymmetric learning that weights reward and loss differently. This work examines which learning strategies better explain trial-by-trial choices given contextual uncertainty and manipulations of outcome distributions. Our results show that a Risk Sensitive (RS) model with asymmetric learning rates best explains human behavior in our novel decision-making task. Fitting candidate models to individual trial histories yielded value signals that predicted both choice and response time. These results highlight that RS model, as an asymmetric learning provides a concise and identifiable account of behavior in decision-making under risk tasks.

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bioRxiv2025

Increased Aperiodic Exponents Track Depression Symptom Severity

Roughly one-third of patients with major depressive disorder (MDD) fail to respond to standard treatments and develop treatment-resistant MDD. For these patients, alternative therapies ofer additional options but yield inconsistent outcomes. Progress has been limited by the absence of objective, brain-based biomarkers to guide target selection or track therapeutic response in real time. Instead, clinicians rely on behavioral assessments that evolve slowly over weeks to months, obscuring the underlying neural dynamics of symptom changes. Here, we test whether the aperiodic exponent of intracranial EEG (iEEG) local field potentials can serve as a neurophysiological marker of depression symptom severity. We leveraged a large iEEG cohort (N = 20) undergoing invasive monitoring for refractory epilepsy, yielding over 1,800 contacts spanning cortical and subcortical zones. For each contact, we estimated the aperiodic exponent (thought to reflect aspects of cortical excitability) of the power spectrum across 10-100 Hz within local brain regions and across distributed cortical association networks. Depressive symptoms were assessed with the Beck Depression Inventory-II (BDI-II) immediately before intracranial resting state recordings. With respect to the BDI-II scale, participants were identified as experiencing minimal (BDI-II [≤] 13) or elevated depression symptoms (BDI-II [≥] 14). Associations between symptom severity (BDI-II total score and Somatic-Afective, Cognitive, and Anhedonia subscales) and region- or network-level exponents were modeled with ordinary least squares (OLS) regression. The whole-brain, mean aperiodic exponent for each participant discriminated symptom status (AUC = 0.82). At the regional level, the orbitofrontal cortex, anterior cingulate cortex, insula, and amygdala showed higher exponents in the elevated depression symptom group (d = 1.18-1.71; p = 0.032-0.004). A post-hoc classification analysis across these four regions misclassified one participant per group (AUC = 0.86; 95% CI 0.64-1.00). In continuous analyses, BDI-II scores correlated positively with exponents in these same four regions (pFDR = 0.019-0.027; partial r=0.61-0.70) and at the network level in the Salience network (pFDR = 0.024; partial r = 0.63) and Default (pFDR = 0.046; partial r = 0.55) network. The Salience network significantly tracked Anhedonia symptoms (p = 0.004; partial r = 0.62). Here we report that intracranial aperiodic exponents within fronto-limbic and insular circuits, overlapping with networks implicated in contemporary accounts of depression pathophysiology, diferentiate depressive symptom status and scale with severity. These findings support the aperiodic exponent as a candidate neurophysiological marker of current depression symptom burden, with potential relevance for individualized neuromodulation in MDD.

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bioRxiv2025

The neural basis of emotional generalization in empathy

The essence of empathy is generalization of emotion across persons. Here, we leverage recent theoretical advances in the neuroscience of generalization to help us understand empathy. We measured brain activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one identifying emotional responses in others. We quantified the representational geometry of local field potential (LFP) high-gamma activity in four regions: the medial temporal lobe, anterior cingulate cortex, orbitofrontal cortex, and insula. We found encoding of both self- and other-emotions in all four regions, but codes for emotion and person are disentangled (that is, factorized) in the insula, but not the other regions. This factorized representation allows for cross-person generalization of emotion in a way that tangled (non-factorized) representations do not. Together, these results support the hypothesis that the insula uniquely contributes to social mirroring processes by which we understand emotions across individuals.

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bioRxiv2025

Human brain network control of creativity

The ability to think creatively is fundamental to human cognition, shaping how we interact with the world and navigate complex problems. Creativity depends on the interaction of multiple large-scale brain networks, but how these networks represent creative thought and distinguish it from other cognitive states remains unclear. Here, we use invasive intracranial recordings in the human brain to explore the network-level representations underlying creative thinking. Our results demonstrate that cortical networks in the human brain differentially encode distinct cognitive states: we found unique brain states underlying creative thinking vs. arithmetic calculations, particularly in the default mode network. Further, in the dorsal attention network, we uncovered nonlinear, high-dimensional representations of moment-by-moment fluctuations in creative performance. These representations define a neural creativity axis shared between network-level and single-neuron computations. Our findings reveal widespread neural representations of cognitive state and suggest distinct roles of specific cortical networks in controlling creativity, with the default mode network gating access to creative states and the dorsal attention network regulating the quality of creative output.

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bioRxiv2024

Cell-type specific responses to single-pulse electrical stimulation of the human brain

Neuromodulation techniques, such as deep brain stimulation, intraoperative brain mapping, and responsive neurostimulation, use electricity to alter brain activity. Despite daily clinical use in thousands of patients, it remains fundamentally unknown how human neurons respond to intracranial stimulation. We address this question at a basic level by characterizing neuronal cell-type specific firing rate responses to single pulses of electrical stimulation of the human brain. We carried out broadly distributed stimulation in 30 patients undergoing neuromonitoring for epilepsy while recording from isolated neurons on microwires implanted into the medial temporal and frontal lobes. Out of a total of 228 recorded units, 16.2% (N = 191) were classified as interneurons and 83.8% (N = 37) were classified as principal cells, using a threshold clustering method, based on intrinsic waveshape characteristics. To see how stimulation affected neuronal activation for each cell type, we calculated firing rate change between a pre-stimulation and post-stimulation window and observed that 174 units were significantly modulated with the vast majority (91%) showing firing rate suppression. We then characterized stimulation-evoked changes in firing rate to gain insight into cell type-specific responses. Additionally, in a subset of the units, we observed that firing rate responses were modulated by stimulation distance, where local stimulation (within approximately 40 mm) could evoke instantaneous firing, whereas distant stimulation reliably suppressed firing in the same units. Finally, we analyzed a subset of units within the seizure onset zone, which exhibited unique waveform features and responses to stimulation. This study bridges a gap in the neuromodulation field by examining the single-unit firing rate response to direct electrical stimulation of the human brain and analyzing cell-type specific firing rate responses. We show that low frequency, single-pulse stimulation broadly elicits firing rate suppression, but parameters, such as distance from the unit, can have diverse effects on firing rate responses. This work informs the neuronal basis of CCEP generation and therefore has implications for clinical mapping and informs novel active probing strategies for precision diagnosis and neuromodulation of seizure pathophysiology in surgical cases. Moreover, this research has general implications for understanding neuromodulation via direct brain stimulation. Highlights- Putative principal cell waveform shapes are characterized by longer trough-to-peak and full-width half max durations (s) compared to interneurons. - Monopolar stimulation @ 3 mA generally has a widespread suppressive effect on neuronal firing, lasting approximately 1.5 s. - Principal cells show greater suppression amplitude and longer suppression durations than interneurons. - Stimulation within [~] 40 mm is capable of evoking instantaneous firing, despite general suppression from stimulation at greater distances.

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bioRxiv2024

Human single-neuron activity is modulated by intracranial theta burst stimulation of the basolateral amygdala

Direct electrical stimulation of the human brain has been used for numerous clinical and scientific applications. At present, however, little is known about how intracranial stimulation affects activity at the microscale. In this study, we recorded intracranial EEG data from a cohort of patients with medically refractory epilepsy as they completed a visual recognition memory task. During the memory task, brief trains of intracranial theta burst stimulation (TBS) were delivered to the basolateral amygdala (BLA). Using simultaneous microelectrode recordings, we isolated neurons in the hippocampus, amygdala, orbitofrontal cortex, and anterior cingulate cortex and tested whether stimulation enhanced or suppressed firing rates. Additionally, we characterized the properties of modulated neurons, clustered presumed excitatory and inhibitory neurons by waveform morphology, and examined the extent to which modulation affected memory task performance. We observed a subset of neurons ([~]30%) whose firing rate was modulated by TBS, exhibiting highly heterogeneous responses with respect to onset latency, duration, and direction of effect. Notably, location and baseline activity predicted which neurons were most susceptible to modulation, although the impact of this neuronal modulation on memory remains unclear. These findings advance our limited understanding of how focal electrical fields influence neuronal firing at the single-cell level. HighlightsIndividual neurons in the human brain were responsive to theta burst stimulation Basolateral amygdala stimulation preferentially modulated neurons in the hippocampus, orbitofrontal cortex, and amygdala Excitatory and inhibitory neurons were modulated equally Neurons modulated by stimulation tended to have greater baseline firing rates Duration, onset, and valence of neuronal modulation were heterogeneous

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bioRxiv2024

Insula uses overlapping codes for emotion in self and others

In daily life, we must recognize others emotions so we can respond appropriately. This ability may rely, at least in part, on neural responses similar to those associated with our own emotions. We hypothesized that the insula, a cortical region near the junction of the temporal, parietal, and frontal lobes, may play a key role in this process. We recorded local field potential (LFP) activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one on identifying facial emotional responses in others. We found matching patterns of gamma- and high-gamma band activity for the two tasks in the insula. Three other regions (MTL, ACC, and OFC) clearly encoded both self- and other-emotions, but used orthogonal activity patterns to do so. These results support the hypothesis that the insula plays a particularly important role in mediating between experienced vs. observed emotions.

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bioRxiv2023

Default mode network spatio-temporal electrophysiological signature and causal role in creativity

The default mode network (DMN) is a widely distributed, intrinsic brain network thought to play a crucial role in internally-directed cognition. It subserves self-referential thinking, recollection of the past, mind wandering, and creativity. Knowledge about the electrophysiology underlying DMN activity is scarce, due to the difficulty to simultaneously record from multiple distant cortical areas with commonly-used techniques. The present study employs stereo-electroencephalography depth electrodes in 13 human patients undergoing monitoring for epilepsy, obtaining high spatiotemporal resolution neural recordings across multiple canonical DMN regions. Our results offer a rare insight into the temporal evolution and spatial origin of theta (4-8Hz) and gamma signals (30-70Hz) during two DMN-associated higher cognitive functions: mind-wandering and alternate uses. During the performance of these tasks, DMN activity is defined by a specific pattern of decreased theta coupled with increased gamma power. Critically, creativity and mind wandering engage the DMN with different dynamics: creativity recruits the DMN strongly during the covert search of ideas, while mind wandering displays the strongest modulation of DMN during the later recall of the train of thoughts. Theta band power modulations, predominantly occurring during mind wandering, do not show a predominant spatial origin within the DMN. In contrast, gamma power effects were similar for mind wandering and creativity and more strongly associated to lateral temporal nodes. Interfering with DMN activity through direct cortical stimulation within several DMN nodes caused a decrease in creativity, specifically reducing the originality of the alternate uses, without affecting creative fluency or mind wandering. These results suggest that DMN activity is flexibly modulated as a function of specific cognitive processes and supports its causal role in creative thinking. Our findings shed light on the neural constructs supporting creative cognition and provide causal evidence for the role of DMN in the generation of original connections among concepts.

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bioRxiv2022

Frontotemporal network engagement by human intracranial stimulation in limbic hubs

BackgroundPrefrontal circuits in the human brain play an important role in cognitive and affective processing. Neuromodulation therapies delivered to certain key hubs within these circuits are being used with increasing frequency to treat a host of neuropsychiatric disorders. However, the detailed neurophysiological effects of stimulation to these hubs are largely unknown. MethodsHere, we performed intracranial recordings across prefrontal networks while delivering electrical stimulation to two well-established white matter hubs involved in cognitive regulation and depression: the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). ResultsWe demonstrate a shared frontotemporal circuit consisting of the ventromedial PFC, amygdala, and lateral orbitofrontal cortex where gamma oscillations are differentially modulated by stimulation target. Additionally, we found subject-specific responses to stimulation in the dorsal anterior cingulate cortex and demonstrate the capacity for further tuning of neural activity using current-steered stimulation. ConclusionsOur findings indicate a potential neurophysiological mechanism for the dissociable therapeutic effects seen across the SCC and VC/VS DBS targets for psychiatric neuromodulation and our results lay the groundwork for personalized, network-guided neurostimulation therapy.

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bioRxiv2022

Intracranial EEG spectral feature analysis and focal brain stimulation reveal affective specialization within dorsal anterior cingulate cortex

Emotion is represented in several limbic and prefrontal cortical brain areas herein referred to as the Affective Salience Network (ASN). Within this network, less is known about how valence and intensity are processed in the dorsal anterior cingulate (dACC), and how affective processes in dACC compare to activity in other nodes within the ASN. Using a novel spectral feature approach to analyze intracranial electrophysiological data, we discover hemispheric specialization in the dACC such that the right hemisphere is sensitive to intensity while the left hemisphere is sensitive to valence and negative affective bias. We further applied 130 Hz continuous stimulation to the anterior cingulum bundle while patients viewed emotional faces. Faces were rated happier in all patients, an effect modulated by baseline affective bias, suggesting a causal role for the dACC during the processing of external affective stimuli.

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bioRxiv2021

Spontaneous Neuronal Oscillations in the Human Insula are Hierarchically Organized Traveling Waves

The insula plays a fundamental role in a wide range of adaptive human behaviors, but its electrophysiological dynamics are poorly understood. Here we used human intracranial electroencephalographic recordings to investigate the electrophysiological properties and hierarchical organization of spontaneous neuronal oscillations within the insula. We analyzed the neuronal oscillations of the insula directly and found that rhythms in the theta and beta frequency oscillations are widespread and spontaneously present. These oscillations are largely organized along the anterior-posterior axis of the insula. Both the left and right insula showed anterior-to-posterior decreasing gradients for the power of oscillations in the beta frequency band. The left insula also showed a posterior-to-anterior decreasing frequency gradient and an anterior-to-posterior decreasing power gradient in the theta frequency band. In addition to measuring the power of these oscillations, we also examined the phase of these signals across simultaneous recording channels and found that the insula oscillations in the theta and beta bands are traveling waves. The strength of the traveling waves in each frequency was positively correlated with the amplitude of each oscillation. However, the theta and beta traveling waves were uncoupled to each other in terms of phase and amplitude, which suggested that insula traveling waves in the theta and beta bands operate independently. Our findings provide new insights into the spatiotemporal dynamics and hierarchical organization of neuronal oscillations within the insula, which, given its rich connectivity with widespread cortical regions, indicates that oscillations and traveling waves have an important role in intra- and inter-insula communication.

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bioRxiv2020

Brain-wide structural and functional disruption in mice with oligodendrocyte specific Nf1 deletion is rescued by inhibition of NOS

Neurofibromin gene (NF1) mutation causes Neurofibromatosis type 1 (NF1), a disorder in which brain white matter deficits identified by neuroimaging are common, yet of unknown cellular etiology. In mice, Nf1 loss in adult oligodendrocyte causes myelin decompaction, and increases oligodendrocyte nitric oxide (NO) levels. Nitric oxide synthase (NOS) inhibitors rescue this pathology. Whether oligodendrocyte pathology is sufficient to affect brainwide structure and account for NF1 imaging findings is unknown. Here, we show that Nf1 gene inactivation in adult oligodendrocytes (Plp-Nf1fl/+ mice) results in a motor coordination deficit. Magnetic resonance imaging in awake mice shows that fractional anisotropy is reduced in Plp-Nf1fl/+ corpus callosum and that interhemispheric functional connectivity in motor cortex is also reduced, consistent with disrupted myelin integrity. Further, NOS-specific inhibition rescued both measures. These results demonstrate that oligodendrocyte defects account for aspects of brain dysfunction in NF1, which can be identified by neuroimaging and ameliorated by NOS inhibition. Significance statementThis study assesses the effects of myelin decompaction on motor behavior and brain-wide structural and functional connectivity, and the effect of nitric oxide synthase (NOS) inhibition by N-nitro-L-arginine methyl ester (L-NAME) on these imaging measures. We report that inducible oligodendrocyte-specific inactivation of the Nf1 gene, which causes myelin decompaction, results in reduced motor coordination. Using diffusion-based MRI we show reduced myelin integrity and using functional MRI we show reduced functional connectivity in awake passive mice. L-NAME administration results in rescue of the pathology at the mesoscopic level using imaging procedures that can be directly applied to humans to study treatment efficacy in clinical trials.

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bioRxiv2019

Loss of function in the autism and learning disabilities associated gene Nf1 disrupts corticocortical and corticostriatal functional connectivity in human and mouse

Children with the autosomal dominant single gene disorder, neurofibromatosis type 1 (NF1), display multiple structural and functional changes in the central nervous system, resulting in neuropsychological cognitive abnormalities. Here we assessed the pathological functional organization that may underlie the behavioral impairments in NF1 using resting-state functional connectivity MRI. Coherent spontaneous fluctuations in the fMRI signal across the entire brain were used to interrogate the pattern of functional organization of corticocortical and corticostriatal networks in both NF1 pediatric patients and mice with a heterozygous mutation in the Nf1 gene (Nf1+/-). Children with NF1 demonstrated abnormal organization of cortical association networks and altered posterior-anterior functional connectivity in the default network. Examining the contribution of the striatum revealed that corticostriatal functional connectivity was altered. NF1 children demonstrated reduced functional connectivity between striatum and the frontoparietal network and increased striatal functional connectivity with the limbic network. Awake passive mouse functional connectivity MRI in Nf1+/- mice similarly revealed reduced posterior-anterior connectivity along the cingulate cortex as well as disrupted corticostriatal connectivity. The striatum of Nf1+/- mice showed increased functional connectivity to somatomotor and frontal cortices and decreased functional connectivity to the auditory cortex. Collectively, these results demonstrate similar alterations across species, suggesting that NF1 pathogenesis is linked to striatal dysfunction and disrupted corticocortical connectivity in the default network.

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