Decoding of human identity by computer vision and neuronal vision

Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes. This is the same challenge faced by the nervous system and partially addressed by the concept cells—neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL) ⁠. Yet, access to neurons representing a particular concept is limited due to these neurons’ sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series “24”. First, we devised a minimally supervised CV algorithm (with comparable performance against manually-labeled data) to detect the most prevalent characters (above 1% overall appearance) in each frame. Next, we implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the four main characters throughout the episode. This methodology allowed us to compare “computer vision” with “neuronal vision”—footprints associated with each character present in the activity of a subset of neurons—and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants’ subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL

Augmenting hippocampal-prefrontal neuronal synchrony during sleep enhances memory consolidation in humans.

Memory consolidation during sleep is thought to depend on the coordinated interplay between cortical slow waves, thalamocortical sleep spindles and hippocampal ripples, but direct evidence is lacking. Here, we implemented real-time closed-loop deep brain stimulation in human prefrontal cortex during sleep and tested its effects on sleep electrophysiology and on overnight consolidation of declarative memory. Synchronizing the stimulation to the active phases of endogenous slow waves in the medial temporal lobe (MTL) enhanced sleep spindles, boosted locking of brain-wide neural spiking activity to MTL slow waves, and improved coupling between MTL ripples and thalamocortical oscillations. Furthermore, synchronized stimulation enhanced the accuracy of recognition memory. By contrast, identical stimulation without this precise time-locking was not associated with, and sometimes even degraded, these electrophysiological and behavioral effects. Notably, individual changes in memory accuracy were highly correlated with electrophysiological effects. Our results indicate that hippocampo-thalamocortical synchronization during sleep causally supports human memory consolidation

Neuroimaging of Supraventricular Frontal White Matter in Children with Familial Attention-Deficit Hyperactivity Disorder and Attention-Deficit Hyperactivity Disorder Due to Prenatal Alcohol Exposure

Attention-deficit hyperactivity disorder (ADHD) is common in patients with (ADHD+PAE) and without (ADHD-PAE) prenatal alcohol exposure (PAE). Many patients diagnosed with idiopathic ADHD actually have covert PAE, a treatment-relevant distinction. To improve differential diagnosis, we sought to identify brain differences between ADHD+PAE and ADHD-PAE using neurobehavioral, magnetic resonance spectroscopy, and diffusion tensor imaging metrics that had shown promise in past research. Children 8-13 were recruited in three groups: 23 ADHD+PAE, 19 familial ADHD-PAE, and 28 typically developing controls (TD). Neurobehavioral instruments included the Conners 3 Parent Behavior Rating Scale and the Delis-Kaplan Executive Function System (D-KEFS). Two dimensional magnetic resonance spectroscopic imaging was acquired from supraventricular white matter to measure N-acetylaspartate compounds, glutamate, creatine + phosphocreatine (creatine), and choline-compounds (choline). Whole brain diffusion tensor imaging was acquired and used to to calculate fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity from the same superventricular white matter regions that produced magnetic resonance spectroscopy data. The Conners 3 Parent Hyperactivity/Impulsivity Score, glutamate, mean diffusivity, axial diffusivity, and radial diffusivity were all higher in ADHD+PAE than ADHD-PAE. Glutamate was lower in ADHD-PAE than TD. Within ADHD+PAE, inferior performance on the D-KEFS Tower Test correlated with higher neurometabolite levels. These findings suggest white matter differences between the PAE and familial etiologies of ADHD. Abnormalities detected by magnetic resonance spectroscopy and diffusion tensor imaging co-localize in supraventricular white matter and are relevant to executive function symptoms of ADHD

Decoding of human identity by computer vision and neuronal vision

Abstract Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes. This is the same challenge faced by the nervous system and partially addressed by the concept cells—neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL) ⁠. Yet, access to neurons representing a particular concept is limited due to these neurons’ sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series “24”. First, we devised a minimally supervised CV algorithm (with comparable performance against manually-labeled data) to detect the most prevalent characters (above 1% overall appearance) in each frame. Next, we implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the four main characters throughout the episode. This methodology allowed us to compare “computer vision” with “neuronal vision”—footprints associated with each character present in the activity of a subset of neurons—and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants’ subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL

Dorsolateral prefrontal γ-aminobutyric acid in patients with treatment-resistant depression after transcranial magnetic stimulation measured with magnetic resonance spectroscopy.

BACKGROUND: The therapeutic mechanism of repetitive transcranial magnetic stimulation (rTMS) for treatment-resistant depression (TRD) may involve modulation of γ-aminobutyric acid (GABA) levels. We used proton magnetic resonance spectroscopy (MRS) to assess changes in GABA levels at the site of rTMS in the left dorsolateral prefrontal cortex (DLPFC). METHODS: In 26 adults with TRD, we used Mescher–Garwood point-resolved spectroscopy (MEGA-PRESS) spectral-editing MRS to measure GABA in the left DLPFC before and after standard clinical treatment with rTMS. All participants but 1 were medicated, including 12 patients on GABA agonist agents. RESULTS: Mean GABA in the DLPFC increased 10.0% (p = 0.017) post-rTMS in the overall sample. As well, GABA increased significantly in rTMS responders (n = 12; 23.6%, p = 0.015) but not in nonresponders (n = 14; 4.1%, p = not significant). Changes in GABA were not significantly affected by GABAergic agonists, but clinical response was less frequent (p = 0.005) and weaker (p = 0.035) in the 12 participants who were receiving GABA agonists concomitant with rTMS treatment. LIMITATIONS: This study had an open-label design in a population receiving naturalistic treatment. CONCLUSION: Treatment using rTMS was associated with increases in GABA levels at the stimulation site in the left DLPFC, and the degree of GABA change was related to clinical improvement. Participants receiving concomitant treatment with a GABA agonist were less likely to respond to rTMS. These findings were consistent with earlier studies showing the effects of rTMS on GABA levels and support a GABAergic model of depression

Combining neuroimaging and behavior to discriminate children with attention deficit-hyperactivity disorder with and without prenatal alcohol exposure

In many patients, ostensible idiopathic attention deficit-hyperactivity disorder (ADHD) may actually stem from covert prenatal alcohol exposure (PAE), a treatment-relevant distinction. This study attempted a receiver-operator characteristic (ROC) classification of children with ADHD into those with PAE (ADHD+PAE) and those without (ADHD-PAE) using neurobehavioral instruments alongside magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) of supraventricular brain white matter. Neurobehavioral, MRS, and DTI endpoints had been suggested by prior findings. Participants included children aged 8-13 years, 23 with ADHD+PAE, 19 with familial ADHD-PAE, and 28 typically developing (TD) controls. With area-under-the-curve (AUC) >0.90, the Conners 3 Parent Rating Scale Inattention (CIn) and Hyperactivity/Impulsivity (CHp) scores and the Behavioral Regulation Index (BRI) of the Behavior Rating Inventory of Executive Function (BRIEF2) excellently distinguished the clinical groups from TD, but not from each other (AUC < 0.70). Combinations of MRS glutamate (Glu) and N-acetyl-compounds (NAA) and DTI mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and fractional anisotropy (FA) yielded "good" (AUC > 0.80) discrimination. Neuroimaging combined with CIn and BRI achieved AUC 0.72 and AUC 0.84, respectively. But neuroimaging combined with CHp yielded 14 excellent combinations with AUC ≥ 0.90 (all p < 0.0005), the best being Glu·AD·RD·CHp/(NAA·FA) (AUC 0.92, sensitivity 1.00, specificity 0.82, p < 0.0005). Using Cho in lieu of Glu yielded AUC 0.83. White-matter microstructure and metabolism may assist efforts to discriminate ADHD etiologies and to detect PAE, beyond the ability of commonly used neurobehavioral measures alone

Cortical gyrification in children with attention deficit-hyperactivity disorder and prenatal alcohol exposure.

BackgroundAn improved understanding of the neurodevelopmental differences between attention deficit hyperactivity disorder with and without prenatal alcohol exposure (ADHD + PAE and ADHD-PAE, respectively) is needed. Herein, we evaluated gyrification (cortical folding) in children with ADHD + PAE compared to that in children with familial ADHD-PAE and typically developing (TD) children.MethodsADHD + PAE (n = 37), ADHD-PAE (n = 25), and TD children (n = 27), aged 8-13 years, were compared on facial morphological, neurobehavioral, and neuroimaging assessments. Local gyrification index (LGI) maps were compared between groups using general linear modelling. Relationships between LGI and clincobehavioral parameters in children with ADHD ± PAE were evaluated using multivariate partial least squares.ResultsADHD + PAE and ADHD-PAE groups showed significantly lower LGI (relative to TD) in numerous regions, overlapping in medial prefrontal, parietal, and temporo-occipital cortices (p < 0.001). However, LGI in left mid-dorsolateral prefrontal cortex was uniquely lower in the ADHD + PAE group (p < 0.001). Partial least squares analysis identified one significant latent variable (accounting for 59.3 % of the crossblock correlation, p < 0.001), reflecting a significant relationship between a profile of lower LGI in prefrontal (including left mid-dorsolateral), insular, cingulate, temporal, and parietal cortices and a clinicobehavioral profile of PAE, including a flat philtrum and upper vermillion border, lower IQ, poorer behavioral regulation scores, and greater hyperactivity/impulsivity.ConclusionsChildren with ADHD + PAE uniquely demonstrate lower mid-dorsolateral LGI, with widespread lower LGI related to more severe facial dysmorphia and neurobehavioral impairments. These findings add insight into the brain bases of PAE symptoms, potentially informing more targeted ADHD treatments based on an objective differential diagnosis of ADHD + PAE vs. ADHD-PAE

Dorsolateral prefrontal γ-aminobutyric acid in patients with treatment-resistant depression after transcranial magnetic stimulation measured with magnetic resonance spectroscopy

BackgroundThe therapeutic mechanism of repetitive transcranial magnetic stimulation (rTMS) for treatment-resistant depression (TRD) may involve modulation of γ-aminobutyric acid (GABA) levels. We used proton magnetic resonance spectroscopy (MRS) to assess changes in GABA levels at the site of rTMS in the left dorsolateral prefrontal cortex (DLPFC).MethodsIn 26 adults with TRD, we used Mescher–Garwood point-resolved spectroscopy (MEGA-PRESS) spectral-editing MRS to measure GABA in the left DLPFC before and after standard clinical treatment with rTMS. All participants but 1 were medicated, including 12 patients on GABA agonist agents.ResultsMean GABA in the DLPFC increased 10.0% (p = 0.017) post-rTMS in the overall sample. As well, GABA increased significantly in rTMS responders (n = 12; 23.6%, p = 0.015) but not in nonresponders (n = 14; 4.1%, p = not significant). Changes in GABA were not significantly affected by GABAergic agonists, but clinical response was less frequent (p = 0.005) and weaker (p = 0.035) in the 12 participants who were receiving GABA agonists concomitant with rTMS treatment.LimitationsThis study had an open-label design in a population receiving naturalistic treatment.ConclusionTreatment using rTMS was associated with increases in GABA levels at the stimulation site in the left DLPFC, and the degree of GABA change was related to clinical improvement. Participants receiving concomitant treatment with a GABA agonist were less likely to respond to rTMS. These findings were consistent with earlier studies showing the effects of rTMS on GABA levels and support a GABAergic model of depression

Dorsolateral prefrontal γ-aminobutyric acid in patients with treatment-resistant depression after transcranial magnetic stimulation measured with magnetic resonance spectroscopy

BackgroundThe therapeutic mechanism of repetitive transcranial magnetic stimulation (rTMS) for treatment-resistant depression (TRD) may involve modulation of γ-aminobutyric acid (GABA) levels. We used proton magnetic resonance spectroscopy (MRS) to assess changes in GABA levels at the site of rTMS in the left dorsolateral prefrontal cortex (DLPFC).MethodsIn 26 adults with TRD, we used Mescher–Garwood point-resolved spectroscopy (MEGA-PRESS) spectral-editing MRS to measure GABA in the left DLPFC before and after standard clinical treatment with rTMS. All participants but 1 were medicated, including 12 patients on GABA agonist agents.ResultsMean GABA in the DLPFC increased 10.0% (p = 0.017) post-rTMS in the overall sample. As well, GABA increased significantly in rTMS responders (n = 12; 23.6%, p = 0.015) but not in nonresponders (n = 14; 4.1%, p = not significant). Changes in GABA were not significantly affected by GABAergic agonists, but clinical response was less frequent (p = 0.005) and weaker (p = 0.035) in the 12 participants who were receiving GABA agonists concomitant with rTMS treatment.LimitationsThis study had an open-label design in a population receiving naturalistic treatment.ConclusionTreatment using rTMS was associated with increases in GABA levels at the stimulation site in the left DLPFC, and the degree of GABA change was related to clinical improvement. Participants receiving concomitant treatment with a GABA agonist were less likely to respond to rTMS. These findings were consistent with earlier studies showing the effects of rTMS on GABA levels and support a GABAergic model of depression